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After more than twenty years of research, the molecular events of apoptotic cell death can be succinctly stated; different pathways, activated by diverse signals, increase the activity of proteases called caspases that rapidly and irreversibly dismantle condemned cell by cleaving specific substrates. In this time the ideas that apoptosis protects us from tumourigenesis and that cancer chemotherapy works by inducing apoptosis also emerged. Currently, apoptosis research is shifting away from the intracellular events within the dying cell to focus on the effect of apoptotic cells on surrounding tissues. This is producing counterintuitive data showing that our understanding of the role of apoptosis in tumourigenesis and cancer therapy is too simple, with some interesting and provocative implications. Here, we will consider evidence supporting the idea that dying cells signal their presence to the surrounding tissue and, in doing so, elicit repair and regeneration that compensates for any loss of function caused by cell death. We will discuss evidence suggesting that cancer cell proliferation may be driven by inappropriate or corrupted tissue-repair programmes that are initiated by signals from apoptotic cells and show how this may dramatically modify how we view the role of apoptosis in both tumourigenesis and cancer therapy.
Software developers build complex systems using plenty of third-party libraries. Documentation is key to understand and use the functionality provided via the libraries’ APIs. Therefore, functionality is the main focus of contemporary API documentation, while cross-cutting concerns such as security are almost never considered at all, especially when the API itself does not provide security features. Documentations of JavaScript libraries for use in web applications, e.g., do not specify how to add or adapt a Content Security Policy (CSP) to mitigate content injection attacks like Cross-Site Scripting (XSS). This is unfortunate, as security-relevant API documentation might have an influence on secure coding practices and prevailing major vulnerabilities such as XSS. For the first time, we study the effects of integrating security-relevant information in non-security API documentation. For this purpose, we took CSP as an exemplary study object and extended the official Google Maps JavaScript API documentation with security-relevant CSP information in three distinct manners. Then, we evaluated the usage of these variations in a between-group eye-tracking lab study involving N=49 participants. Our observations suggest: (1) Developers are focused on elements with code examples. They mostly skim the documentation while searching for a quick solution to their programming task. This finding gives further evidence to results of related studies. (2) The location where CSP-related code examples are placed in non-security API documentation significantly impacts the time it takes to find this security-relevant information. In particular, the study results showed that the proximity to functional-related code examples in documentation is a decisive factor. (3) Examples significantly help to produce secure CSP solutions. (4) Developers have additional information needs that our approach cannot meet.
Overall, our study contributes to a first understanding of the impact of security-relevant information in non-security API documentation on CSP implementation. Although further research is required, our findings emphasize that API producers should take responsibility for adequately documenting security aspects and thus supporting the sensibility and training of developers to implement secure systems. This responsibility also holds in seemingly non-security relevant contexts.
Das sogenannte „Deutschlandstipendium“ ist 2010 ins Leben gerufen worden. Gemäß den gesetzlichen Vorgaben sollen die Stipendien nach Begabung und Leistung vergeben werden. Darüber hinaus sollen auch gesellschaftliches Engagement oder besondere soziale, familiäre oder persönliche Umstände berücksichtigt werden. Bei der Finanzierung sind die Hochschulen zunächst auf das Einwerben privater Fördermittel angewiesen, die von Bund und Land um denselben Betrag aufgestockt werden. Die privaten Mittelgeber können für die von ihnen anteilig finanzierten Stipendien festlegen, aus welchen Studiengängen ihre Stipendiaten ausgewählt werden sollen. Die Hochschulen haben jedoch darauf zu achten, dass ein Drittel aller zu vergebenden Stipendien ohne eine entsprechende Zweckbindung vergeben werden. Einen direkten Einfluss auf die Auswahl einzelner Kandidaten dürfen die Förderer nicht haben. Vor diesem Hintergrund sind die Hochschulen angehalten, Anreize für private Förderer zu schaffen und parallel Bewerbungs- und Auswahlverfahren zu konzipieren, die die genannten gesetzlichen Vorgaben einhalten. Dadurch entsteht bei den Hochschulen ein erheblicher Verwaltungsaufwand. Zu dessen Reduzierung wird in diesem Artikel ein transparenter, nachvollziehbarer, zeit- und kostensparender Prozess durch einen programmierten Workflow beschrieben.
2-methylacetoacetyl-coenzyme A thiolase (beta-ketothiolase) deficiency: one disease - two pathways
(2020)
Background: 2-methylacetoacetyl-coenzyme A thiolase deficiency (MATD; deficiency of mitochondrial acetoacetyl-coenzyme A thiolase T2/ “beta-ketothiolase”) is an autosomal recessive disorder of ketone body utilization and isoleucine degradation due to mutations in ACAT1.
Methods: We performed a systematic literature search for all available clinical descriptions of patients with MATD. Two hundred forty-four patients were identified and included in this analysis. Clinical course and biochemical data are presented and discussed.
Results: For 89.6% of patients at least one acute metabolic decompensation was reported. Age at first symptoms ranged from 2 days to 8 years (median 12 months). More than 82% of patients presented in the first 2 years of life, while manifestation in the neonatal period was the exception (3.4%). 77.0% (157 of 204 patients) of patients showed normal psychomotor development without neurologic abnormalities. Conclusion: This comprehensive data analysis provides a systematic overview on all cases with MATD identified in the literature. It demonstrates that MATD is a rather benign disorder with often favourable outcome, when compared with many other organic acidurias.
Nitrile-type inhibitors are known to interact with cysteine proteases in a covalent-reversible manner. The chemotype of 3-cyano-3-aza-β-amino acid derivatives was designed in which the N-cyano group is centrally arranged in the molecule to allow for interactions with the nonprimed and primed binding regions of the target enzymes. These compounds were evaluated as inhibitors of the human cysteine cathepsins K, S, B, and L. They exhibited slow-binding behavior and were found to be exceptionally potent, in particular toward cathepsin K, with second-order rate constants up to 52 900 × 103 M–1 s–1.
Background: 3-hydroxy-3-methylglutaryl-coenzyme A lyase deficiency (HMGCLD) is an autosomal recessive disorder of ketogenesis and leucine degradation due to mutations in HMGCL.
Method: We performed a systematic literature search to identify all published cases. Two hundred eleven patients of whom relevant clinical data were available were included in this analysis. Clinical course, biochemical findings and mutation data are highlighted and discussed. An overview on all published HMGCL variants is provided.
Results: More than 95% of patients presented with acute metabolic decompensation. Most patients manifested within the first year of life, 42.4% already neonatally. Very few individuals remained asymptomatic. The neurologic long-term outcome was favorable with 62.6% of patients showing normal development.
Conclusion: This comprehensive data analysis provides a systematic overview on all published cases with HMGCLD including a list of all known HMGCL mutations.
3-Hydroxyisobutyrate Dehydrogenase (HIBADH) deficiency - a novel disorder of valine metabolism
(2021)
3-Hydroxyisobutyric acid (3HiB) is an intermediate in the degradation of the branched-chain amino acid valine. Disorders in valine degradation can lead to 3HiB accumulation and its excretion in the urine. This article describes the first two patients with a new metabolic disorder, 3-hydroxyisobutyrate dehydrogenase (HIBADH) deficiency, its phenotype and its treatment with a low-valine diet. The detected mutation in the HIBADH gene leads to nonsense-mediated mRNA decay of the mutant allele and to a complete loss-of-function of the enzyme. Under strict adherence to a low-valine diet a rapid decrease of 3HiB excretion in the urine was observed. Due to limited patient numbers and intrafamilial differences in phenotype with one affected and one unaffected individual, the clinical phenotype of HIBADH deficiency needs further evaluation.
Animal models are often needed in cancer research but some research questions may be answered with other models, e.g., 3D replicas of patient-specific data, as these mirror the anatomy in more detail. We, therefore, developed a simple eight-step process to fabricate a 3D replica from computer tomography (CT) data using solely open access software and described the method in detail. For evaluation, we performed experiments regarding endoscopic tumor treatment with magnetic nanoparticles by magnetic hyperthermia and local drug release. For this, the magnetic nanoparticles need to be accumulated at the tumor site via a magnetic field trap. Using the developed eight-step process, we printed a replica of a locally advanced pancreatic cancer and used it to find the best position for the magnetic field trap. In addition, we described a method to hold these magnetic field traps stably in place. The results are highly important for the development of endoscopic tumor treatment with magnetic nanoparticles as the handling and the stable positioning of the magnetic field trap at the stomach wall in close proximity to the pancreatic tumor could be defined and practiced. Finally, the detailed description of the workflow and use of open access software allows for a wide range of possible uses.
Background: Cancer heterogeneity poses a serious challenge concerning the toxicity and adverse effects of therapeutic inhibitors, especially when it comes to combinatorial therapies that involve multiple targeted inhibitors. In particular, in non-small cell lung cancer (NSCLC), a number of studies have reported synergistic effects of drug combinations in the preclinical models, while they were only partially successful in the clinical setup, suggesting those alternative clinical strategies (with genetic background and immune response) should be considered. Herein, we investigated the antitumor effect
of cytokine-induced killer (CIK) cells in combination with ALK and PD-1 inhibitors in vitro on genetically variable NSCLC cell lines.
Methods: We co-cultured the three genetically different NSCLC cell lines NCI-H2228 (EML4-ALK), A549 (KRAS mutation), and HCC-78 (ROS1 rearrangement) with and without nivolumab (PD-1 inhibitor) and crizotinib (ALK inhibitor). Additionally, we profiled the variability of surface expression multiple immune checkpoints, the concentration of absolute dead cells, intracellular granzyme B on CIK cells using flow cytometry as well as RT-qPCR. ELISA and Western blot were performed to verify the activation of CIK cells.
Results: Our analysis showed that (a) nivolumab significantly weakened PD-1 surface expression on CIK cells without impacting other immune checkpoints or PD-1 mRNA expression, (b) this combination strategy showed an effective response on cell viability, IFN-g production, and intracellular release of granzyme B in CD3+ CD56+ CIK cells, but solely in NCI-H2228, (c) the intrinsic expression of Fas ligand (FasL) as a T-cell activation marker in CIK cells was upregulated by this additive effect, and (d) nivolumab induced Foxp3 expression in CD4+CD25+ subpopulation of CIK cells significantly increased. Taken together, we could show that CIK cells in combination with crizotinib and nivolumab can enhance the anti-tumor immune response through FasL activation, leading to increased IFN-g and granzyme B, but only in NCI-H2228 cells with EML4-ALK rearrangement. Therefore, we hypothesize that CIK therapy may be a potential alternative in NSCLC patients harboring EML4-ALK rearrangement, in addition, we support the idea that combination therapies offer significant potential when they are optimized on a patient-by-patient basis.
The simultaneous operation of multiple different semiconducting metal oxide (MOX) gas sensors is demanding for the readout circuitry. The challenge results from the strongly varying signal intensities of the various sensor types to the target gas. While some sensors change their resistance only slightly, other types can react with a resistive change over a range of several decades. Therefore, a suitable readout circuit has to be able to capture all these resistive variations, requiring it to have a very large dynamic range. This work presents a compact embedded system that provides a full, high range input interface (readout and heater management) for MOX sensor operation. The system is modular and consists of a central mainboard that holds up to eight sensor-modules, each capable of supporting up to two MOX sensors, therefore supporting a total maximum of 16 different sensors. Its wide input range is archived using the resistance-to-time measurement method. The system is solely built with commercial off-the-shelf components and tested over a range spanning from 100Ω to 5 GΩ (9.7 decades) with an average measurement error of 0.27% and a maximum error of 2.11%. The heater management uses a well-tested power-circuit and supports multiple modes of operation, hence enabling the system to be used in highly automated measurement applications. The experimental part of this work presents the results of an exemplary screening of 16 sensors, which was performed to evaluate the system’s performance.
The choice of suitable semiconducting metal oxide (MOX) gas sensors for the detection of a specific gas or gas mixture is time-consuming since the sensor’s sensitivity needs to be characterized at multiple temperatures to find its optimal operating conditions. To obtain reliable measurement results, it is very important that the power for the sensor’s integrated heater is stable, regulated and error-free (or error-tolerant). Especially the error-free requirement can be only be achieved if the power supply implements failure-avoiding and failure-detection methods. The biggest challenge is deriving multiple different voltages from a common supply in an efficient way while keeping the system as small and lightweight as possible. This work presents a reliable, compact, embedded system that addresses the power supply requirements for fully automated simultaneous sensor characterization for up to 16 sensors at multiple temperatures. The system implements efficient (avg. 83.3% efficiency) voltage conversion with low ripple output (<32 mV) and supports static or temperature-cycled heating modes. Voltage and current of each channel are constantly monitored and regulated to guarantee reliable operation. To evaluate the proposed design, 16 sensors were screened. The results are shown in the experimental part of this work.
Electrical signal transmission in power electronic devices takes place through high-purity aluminum bonding wires. Cyclic mechanical and thermal stresses during operation lead to fatigue loads, resulting in premature failure of the wires, which cannot be reliably predicted. The following work presents two fatigue lifetime models calibrated and validated based on experimental fatigue results of an aluminum bonding wire and subsequently transferred and applied to other wire types. The lifetime modeling of Wöhler curves for different load ratios shows good but limited applicability for the linear model. The model can only be applied above 10,000 cycles and within the investigated load range of R = 0.1 to R = 0.7. The nonlinear model shows very good agreement between model prediction and experimental results over the entire investigated cycle range. Furthermore, the predicted Smith diagram is not only consistent in the investigated load range but also in the extrapolated load range from R = −1.0 to R = 0.8. A transfer of both model approaches to other wire types by using their tensile strengths can be implemented as well, although the nonlinear model is more suitable since it covers the entire load and cycle range.
Climate change is increasingly affecting vulnerable groups and resulting in dire social and economic consequences, especially for those in the Global South. Managing current and emerging climate-related risks will require increasing individual’s and communities’ resilience, including enhancing absorptive, adaptive, and transformative capacities. Policymakers are now considering the role that social protection policies and programmes can play in building climate resilience by contributing to these capacities. However, there is a limited understanding of the extent to which social protection instruments can influence these three resilience-related capacities. Lack of assessment tools or frameworks might contribute to limited evidence of social protection’s ability to increase climate resilience. In particular, there appear to be no frameworks or tools that help assess the role of social cash transfers (SCT) in building adaptive capacity. Based on a multi-staged literature review, we develop an adaptive capacity outcomes framework (ACOF) that can help assess SCT’s contribution to building adaptive capacity, and, consequently, resilience. The framework is then tested using impact evaluation and assessment reports from SCT programmes in Indonesia, Zambia, Ethiopia, Bangladesh, and Tanzania. The exercise finds that SCTs alone have a limited contribution to adaptive capacity outcomes, but interventions that combine cash transfers with other components such as nutrition or livelihood training show positive impacts. We find that the ACOF can support assessments of SCT’s contribution towards adaptive capacity. It can help build evidence, evaluate impacts, and through further research, can facilitate learning on SCTs' role in increasing climate resilience.
Failure prognostic builds up on constant data acquisition and processing and fault diagnosis and is an essential part of predictive maintenance of smart manufacturing systems enabling condition based maintenance, optimised use of plant equipment, improved uptime and yield and to prevent safety problems. Given known control inputs into a plant and real sensor outputs or simulated measurements, the model-based part of the proposed hybrid method provides numerical values of unknown parameter degradation functions at sampling time points by the evaluation of equations that have been derived offline from a bicausal diagnostic bond graph. These numerical values are computed concurrently to the constant monitoring of a system and are stored in a buffer of fixed length. The data-driven part of the method provides a sequence of remaining useful life estimates by repeated projection of the parameter degradation into the future based on the use of values in a sliding time window. Existing software can be used to determine the best fitting function and can account for its random parameters. The continuous parameter estimation and their projection into the future can be performed in parallel for multiple isolated simultaneous parametric faults on a multicore, multiprocessor computer.
The proposed hybrid bond graph model-based, data-driven method is verified by an offline simulation case study of a typical power electronic circuit. It can be used to implement embedded systems that enable cooperating machines in smart manufacturing to perform prognostic themselves.
A Method for the Sustainable Documentation of Operations Processes in Parcel Distribution Centers
(2018)
There is often no common understanding on operational processes in logistics companies as they are not properly documented. Hence, people execute the same process differently and training is conducted by experienced operators on an ad-hoc basis. Furthermore, continuous process improvement is hampered as neither the ideal process nor current issues in as-is processes are visible. A major reason for the missing documentation is the complexity of existing business process modelling languages. Modelling experts are required for initially describing the processes and also for updating the models after process changes. Furthermore, operations people are usually not used to read complex process models in EPCs or BPMN diagrams. In order to overcome these limitations, a domain-specific modelling language which facilitates maintaining up-to-date process models has been designed with a large logistics company in Germany. The paper at hand briefly describes this language and illustrates the method on how to apply it in operations environments.
Integrating physical simulation data into data ecosystems challenges the compatibility and interoperability of data management tools. Semantic web technologies and relational databases mostly use other data types, such as measurement or manufacturing design data. Standardizing simulation data storage and harmonizing the data structures with other domains is still a challenge, as current standards such as the ISO standard STEP (ISO 10303 ”Standard for the Exchange of Product model data”) fail to bridge the gap between design and simulation data. This challenge requires new methods, such as ontologies, to rethink simulation results integration. This research describes a new software architecture and application methodology based on the industrial standard ”Virtual Material Modelling in Manufacturing” (VMAP). The architecture integrates large quantities of structured simulation data and their analyses into a semantic data structure. It is capable of providing data permeability from the global digital twin level to the detailed numerical values of data entries and even new key indicators in a three-step approach: It represents a file as an instance in a knowledge graph, queries the file’s metadata, and finds a semantically represented process that enables new metadata to be created and instantiated.
Recessive mutations in the MPV17 gene cause mitochondrial DNA depletion syndrome, a fatal infantile genetic liver disease in humans. Loss of function in mice leads to glomerulosclerosis and sensineural deafness accompanied with mitochondrial DNA depletion. Mutations in the yeast homolog Sym1, and in the zebra fish homolog tra cause interesting, but not obviously related phenotypes, although the human gene can complement the yeast Sym1 mutation. The MPV17 protein is a hydrophobic membrane protein of 176 amino acids and unknown function. Initially localised in murine peroxisomes, it was later reported to be a mitochondrial inner membrane protein in humans and in yeast. To resolve this contradiction we tested two new mouse monoclonal antibodies directed against the human MPV17 protein in Western blots and immunohistochemistry on human U2OS cells. One of these monoclonal antibodies showed specific reactivity to a protein of 20 kD absent in MPV17 negative mouse cells. Immunofluorescence studies revealed colocalisation with peroxisomal, endosomal and lysosomal markers, but not with mitochondria. This data reveal a novel connection between a possible peroxisomal/endosomal/lysosomal function and mitochondrial DNA depletion.
With the increasing demand for ultrapure water in the pharmaceutical and semiconductor industry, the need for precise measuring instruments for those applications is also growing. One critical parameter of water quality is the amount of total organic carbon (TOC). This work presents a system that uses the advantage of the increased oxidation power achieved with UV/O3 advanced oxidation process (AOP) for TOC measurement in combination with a significant miniaturization compared to the state of the art. The miniaturization is achieved by using polymer-electrolyte membrane (PEM) electrolysis cells for ozone generation in combination with UV-LEDs for irradiation of the measuring solution, as both components are significantly smaller than standard equipment. Conductivity measurement after oxidation is the measuring principle and measurements were carried out in the TOC range between 10 and 1000 ppb TOC. The suitability of the system for TOC measurement is demonstrated using the oxidation by ozonation combined with UV irradiation of defined concentrations of isopropyl alcohol (IPA).
This paper presents a novel approach to address noise, vibration, and harshness (NVH) issues in electrically assisted bicycles (e-bikes) caused by the drive unit. By investigating and optimising the structural dynamics during early product development, NVH can decisively be improved and valuable resources can be saved, emphasising its significance for enhancing riding performance. The paper offers a comprehensive analysis of the e-bike drive unit’s mechanical interactions among relevant components, culminating—to the best of our knowledge—in the development of the first high-fidelity model of an entire e-bike drive unit. The proposed model uses the principles of elastic multi body dynamics (eMBD) to elucidate the structural dynamics in dynamic-transient calculations. Comparing power spectra between measured and simulated motion variables validates the chosen model assumptions. The measurements of physical samples utilise accelerometers, contactless laser Doppler vibrometry (LDV) and various test arrangements, which are replicated in simulations and provide accessibility to measure vibrations onto rotating shafts and stationary structures. In summary, this integrated system-level approach can serve as a viable starting point for comprehending and managing the NVH behaviour of e-bikes.
In this paper, a gas-to-power (GtoP) system for power outages is digitally modeled and experimentally developed. The design includes a solid-state hydrogen storage system composed of TiFeMn as a hydride forming alloy (6.7 kg of alloy in five tanks) and an air-cooled fuel cell (maximum power: 1.6 kW). The hydrogen storage system is charged under room temperature and 40 bar of hydrogen pressure, reaching about 110 g of hydrogen capacity. In an emergency use case of the system, hydrogen is supplied to the fuel cell, and the waste heat coming from the exhaust air of the fuel cell is used for the endothermic dehydrogenation reaction of the metal hydride. This GtoP system demonstrates fast, stable, and reliable responses, providing from 149 W to 596 W under different constant as well as dynamic conditions. A comprehensive and novel simulation approach based on a network model is also applied. The developed model is validated under static and dynamic power load scenarios, demonstrating excellent agreement with the experimental results.
A qualitative study of Machine Learning practices and engineering challenges in Earth Observation
(2021)
Machine Learning (ML) is ubiquitously on the advance. Like many domains, Earth Observation (EO) also increasingly relies on ML applications, where ML methods are applied to process vast amounts of heterogeneous and continuous data streams to answer socially and environmentally relevant questions. However, developing such ML- based EO systems remains challenging: Development processes and employed workflows are often barely structured and poorly reported. The application of ML methods and techniques is considered to be opaque and the lack of transparency is contradictory to the responsible development of ML-based EO applications. To improve this situation a better understanding of the current practices and engineering-related challenges in developing ML-based EO applications is required. In this paper, we report observations from an exploratory study where five experts shared their view on ML engineering in semi-structured interviews. We analysed these interviews with coding techniques as often applied in the domain of empirical software engineering. The interviews provide informative insights into the practical development of ML applications and reveal several engineering challenges. In addition, interviewees participated in a novel workflow sketching task, which provided a tangible reflection of implicit processes. Overall, the results confirm a gap between theoretical conceptions and real practices in ML development even though workflows were sketched abstractly as textbook-like. The results pave the way for a large-scale investigation on requirements for ML engineering in EO.
This work presents the analysis of data recorded by an eye tracking device in the course of evaluating a foveated rendering approach for head-mounted displays (HMDs). Foveated rendering methods adapt the image synthesis process to the user’s gaze and exploiting the human visual system’s limitations to increase rendering performance. Especially, foveated rendering has great potential when certain requirements have to be fulfilled, like low-latency rendering to cope with high display refresh rates. This is crucial for virtual reality (VR), as a high level of immersion, which can only be achieved with high rendering performance and also helps to reduce nausea, is an important factor in this field. We put things in context by first providing basic information about our rendering system, followed by a description of the user study and the collected data. This data stems from fixation tasks that subjects had to perform while being shown fly-through sequences of virtual scenes on an HMD. These fixation tasks consisted of a combination of various scenes and fixation modes. Besides static fixation targets, moving tar- gets on randomized paths as well as a free focus mode were tested. Using this data, we estimate the precision of the utilized eye tracker and analyze the participants’ accuracy in focusing the displayed fixation targets. Here, we also take a look at eccentricity-dependent quality ratings. Comparing this information with the users’ quality ratings given for the displayed sequences then reveals an interesting connection between fixation modes, fixation accuracy and quality ratings.
Jet engines of airplanes are designed such that in some components damage occurs and accumulates in service without being critical up to a certain level of damage. Since maintenance, repair, and component exchange are very cost-intensive, it is necessary to predict efficiently the component lifetime with high accuracy. A former developed lifetime model, based on interpolated results of aerodynamic and structural mechanics simulations, uses material parameters estimated from literature values of standard creep experiments. For improved accuracy, an experimental procedure is developed for the characterization of the short-time creep behavior, which is relevant for the operation of turbine blades of jet engines. To consider microstructural influences resulting from the manufacturing of thin-walled single crystal turbine blades, small-scale specimens from used turbine blades are extracted and tested in short- and medium-time creep experiments. Based on experimental results and literature values, a creep model, which describes the fracture behavior for a wide range of creep loads, is calibrated and is now used for the lifetime prediction of turbine blades under real loading conditions.
Pozzolanic properties of Pennisetum purpureum grass ash were tested on Portland cement. Results show that the ash can be blended with cements without compromising binding strength of the cement. It was found that Portland cement could be blended with Pennisetum purpureum up to a ratio of 3:2 compromising compressive strength of mortar.Mortar with lower cement replacement took longer to set as evidenced by lower compressive strength within the 28-day aging time. Mortar with higher cement replacement had lower water absorption capacity, an indication that the test pozzolan was of smaller particulate size. XRF analysis and the FTIR spectrum showed that the ash has a higher content of silica. The XRD pattern of the ash showed that the ash was predominantly amorphous. SEM images showed that the ash produced at 600 o C had residual carbon material.
Host-derived succinate accumulates in the airways during bacterial infection. Here, we show that luminal succinate activates murine tracheal brush (tuft) cells through a signaling cascade involving the succinate receptor 1 (SUCNR1), phospholipase Cβ2, and the cation channel transient receptor potential channel subfamily M member 5 (TRPM5). Stimulated brush cells then trigger a long-range Ca2+ wave spreading radially over the tracheal epithelium through a sequential signaling process. First, brush cells release acetylcholine, which excites nearby cells via muscarinic acetylcholine receptors. From there, the Ca2+ wave propagates through gap junction signaling, reaching also distant ciliated and secretory cells. These effector cells translate activation into enhanced ciliary activity and Cl- secretion, which are synergistic in boosting mucociliary clearance, the major innate defense mechanism of the airways. Our data establish tracheal brush cells as a central hub in triggering a global epithelial defense program in response to a danger-associated metabolite.
The development of advanced robotic systems is challenging as expertise from multiple domains needs to be integrated conceptually and technically. Model-driven engineering promises an efficient and flexible approach for developing robotics applications that copes with this challenge. Domain-specific modeling allows to describe robotics concerns with concepts and notations closer to the respective problem domain. This raises the level of abstraction and results in models that are easier to understand and validate. Furthermore, model-driven engineering allows to increase the level of automation, e.g. through code generation, and to bridge the gap between modeling and implementation. The anticipated results are improved efficiency and quality of the robotics systems engineering process. Within this contribution, we survey the available literature on domain-specific modeling and languages that target core robotics concerns. In total 137 publications were identified that comply with a set of defined criteria, which we consider essential for contributions in this field. With the presented survey, we provide an overview on the state-of-the-art of domain-specific modeling approaches in robotics. The surveyed publications are investigated from the perspective of users and developers of model-based approaches in robotics along a set of quantitative and qualitative research questions. The presented quantitative analysis clearly indicates the rising popularity of applying domain-specific modeling approaches to robotics in the academic community. Beyond this statistical analysis, we map the selected publications to a defined set of robotics subdomains and typical development phases in robotic systems engineering as reference for potential users. Furthermore, we analyze these contributions from a language engineering viewpoint and discuss aspects such as the methods and tools used for their implementation as well as their documentation status, platform integration, typical use cases and the evaluation strategies used for validation of the proposed approaches. Finally, we conclude with recommendations for discussion in the model-driven engineering and robotics community based on the insights gained in this survey.
Background
Consumers rely heavily on online user reviews when shopping online and cybercriminals produce fake reviews to manipulate consumer opinion. Much prior research focuses on the automated detection of these fake reviews, which are far from perfect. Therefore, consumers must be able to detect fake reviews on their own. In this study we survey the research examining how consumers detect fake reviews online.
Methods
We conducted a systematic literature review over the research on fake review detection from the consumer-perspective. We included academic literature giving new empirical data. We provide a narrative synthesis comparing the theories, methods and outcomes used across studies to identify how consumers detect fake reviews online.
Results
We found only 15 articles that met our inclusion criteria. We classify the most often used cues identified into five categories which were (1) review characteristics (2) textual characteristics (3) reviewer characteristics (4) seller characteristics and (5) characteristics of the platform where the review is displayed.
Discussion
We find that theory is applied inconsistently across studies and that cues to deception are often identified in isolation without any unifying theoretical framework. Consequently, we discuss how such a theoretical framework could be developed.
Abstract Classical ballet requires dancers to exercise significant muscle control and strength both while stationary and when moving. Following the Royal Academy of Dance (RAD) syllabus, 8 male and 27 female dancers (aged 20.2 + 1.9 yr) in a full-time university undergraduate dance training program were asked to stand in first position for 10 seconds and then perform 10 repeats of a demi-plié exercise to a counted rhythm. Accelerometer records from the wrist, sacrum, knee and ankle were compared with the numerical scores from a professional dance instructor. The sacrum mounted sensor detected lateral tilts of the torso in dances with lower scores (Spearman’s rank correlation coefficient r = -0.64, p < 0.005). The 5RMS6 acceleration amplitude of wrist mounted sensor was linearly correlated to the movement scores (Spearman’s rank correlation coefficient r = 0.63, p < 0.005). The application of sacrum and wrist mounted sensors for biofeedback during dance training is a realistic, low cost option.
This article concerns with the accessibility of Business process modelling tools (BPMo tools) and business process modelling languages (BPMo languages). Therefore the reader will be introduced to business process management and the authors' motivation behind this inquiry. Afterwards, the paper will reflect problems when applying inaccessible BPMo tools. To illustrate these problems the authors distinguish between two different categories of issues and provide practical examples. Finally the article will present three approaches to improve the accessibility of BPMo tools and BPMo languages.
Low power dissipation is a current topic in digital design, and therefore, it should be covered in a state-of-the-art electrical engineering curriculum. This paper describes how low-power design can be addressed within a digital design course. Doing so would be beneficial for both topics because low-power design is not detached from the systems perspective, and the digital design course would be enriched by references to current challenges and applications. Thus, the presented course should serve as an example of how a course can be developed to also teach students about sustainable engineering.
Introduction: The paper analyses – basing itself on reports and other documents created by different parts of the International Labour Organisation (ILO) – the process which led to the adoption of Social Protection Floor Recommendation No. 202 and the shift in focus of social policy advice towards basic protection and to the Global South countries. We look at the actions of different actors which shape the standard setting and policy stand of the organisation. Objective: To provide a comprehensive analysis of the historical trajectory of ILO social security standards, examining the evolution of principles, conventions, and the global dynamics that have shaped the organization's approach to social protection over time. Materials and methods: The methods include examining ILO documents, relevant subject literature, and the author's participant observations from over twenty-years of service in the ILO's Social Security Department, aiming to provide insights into the decision-making processes within the organization. Conclusion: We conclude that change was brought by: 1) shift in the membership of the ILO and of its decision-making bodies towards the increased presence and powers of representatives from countries of the Global South, 2) the shift in the global development community policy priorities towards poverty reduction, 3) emergence of experimental social assistance schemes in Global South countries, with designs often ignoring principles embedded in the ILO standards. The Social Protection Floor Recommendation complements previous standards in response to the challenges of widespread poverty and informality and spreading atypical forms of employment. It provides two directions of policy responses: 1) formalizing informal employment relationships and 2) expanding universal or targeted rights-based social assistance schemes. Assistance provided by ILO to member states focuses now more on building the non-contributory schemes and on identifying the fiscal space necessary to close the coverage gaps. Nowadays, the ILO must collaborate more than before with other development partners and the main challenge is to build among them awareness and acceptance of the principles of the ILO social security standards.
The steadily decreasing prices of display technologies and computer graphics hardware contribute to the increasing popularity of multiple-display environments, like large, high-resolution displays. It is therefore necessary that educational organizations give the new generation of computer scientists an opportunity to become familiar with this kind of technology. However, there is a lack of tools that allow for getting started easily. Existing frameworks and libraries that provide support for multi-display rendering are often complex in understanding, configuration and extension. This is critical especially in educational context where the time that students have for their projects is limited and quite short. These tools are also rather known and used in research communities only, thus providing less benefit for future non-scientists. In this work we present an extension for the Unity game engine. The extension allows – with a small overhead – for implementation of applications that are apt to run on both single-display and multi-display systems. It takes care of the most common issues in the context of distributed and multi-display rendering like frame, camera and animation synchronization, thus reducing and simplifying the first steps into the topic. In conjunction with Unity, which significantly simplifies the creation of different kinds of virtual environments, the extension affords students to build mock-up virtual reality applications for large, high-resolution displays, and to implement and evaluate new interaction techniques and metaphors and visualization concepts. Unity itself, in our experience, is very popular among computer graphics students and therefore familiar to most of them. It is also often employed in projects of both research institutions and commercial organizations; so learning it will provide students with qualification in high demand.
The clear-sky radiative effect of aerosol–radiation interactions is of relevance for our understanding of the climate system. The influence of aerosol on the surface energy budget is of high interest for the renewable energy sector. In this study, the radiative effect is investigated in particular with respect to seasonal and regional variations for the region of Germany and the year 2015 at the surface and top of atmosphere using two complementary approaches.
First, an ensemble of clear-sky models which explicitly consider aerosols is utilized to retrieve the aerosol optical depth and the surface direct radiative effect of aerosols by means of a clear-sky fitting technique. For this, short-wave broadband irradiance measurements in the absence of clouds are used as a basis. A clear-sky detection algorithm is used to identify cloud-free observations. Considered are measurements of the short-wave broadband global and diffuse horizontal irradiance with shaded and unshaded pyranometers at 25 stations across Germany within the observational network of the German Weather Service (DWD). The clear-sky models used are the Modified MAC model (MMAC), the Meteorological Radiation Model (MRM) v6.1, the Meteorological–Statistical solar radiation model (METSTAT), the European Solar Radiation Atlas (ESRA), Heliosat-1, the Center for Environment and Man solar radiation model (CEM), and the simplified Solis model. The definition of aerosol and atmospheric characteristics of the models are examined in detail for their suitability for this approach.
Second, the radiative effect is estimated using explicit radiative transfer simulations with inputs on the meteorological state of the atmosphere, trace gases and aerosol from the Copernicus Atmosphere Monitoring Service (CAMS) reanalysis. The aerosol optical properties (aerosol optical depth, Ångström exponent, single scattering albedo and asymmetry parameter) are first evaluated with AERONET direct sun and inversion products. The largest inconsistency is found for the aerosol absorption, which is overestimated by about 0.03 or about 30 % by the CAMS reanalysis. Compared to the DWD observational network, the simulated global, direct and diffuse irradiances show reasonable agreement within the measurement uncertainty. The radiative kernel method is used to estimate the resulting uncertainty and bias of the simulated direct radiative effect. The uncertainty is estimated to −1.5 ± 7.7 and 0.6 ± 3.5 W m−2 at the surface and top of atmosphere, respectively, while the annual-mean biases at the surface, top of atmosphere and total atmosphere are −10.6, −6.5 and 4.1 W m−2, respectively.
The retrieval of the aerosol radiative effect with the clear-sky models shows a high level of agreement with the radiative transfer simulations, with an RMSE of 5.8 W m−2 and a correlation of 0.75. The annual mean of the REari at the surface for the 25 DWD stations shows a value of −12.8 ± 5 W m−2 as the average over the clear-sky models, compared to −11 W m−2 from the radiative transfer simulations. Since all models assume a fixed aerosol characterization, the annual cycle of the aerosol radiation effect cannot be reproduced. Out of this set of clear-sky models, the largest level of agreement is shown by the ESRA and MRM v6.1 models.
Agiles IT-Controlling
(2022)
Während im IT-Projektmanagement agile Methoden seit vielen Jahren in der Praxis Zuspruch finden, werden im IT-Controlling überwiegend noch klassische Methoden eingesetzt. Der Beitrag untersucht die Fragestellung, ob und wie die im IT-Controlling eingesetzten Methoden auch agilen Paradigmen folgen und Methoden des agilen IT-Projektmanagements adaptiert werden können.
The following work presents algorithms for semi-automatic validation, feature extraction and ranking of time series measurements acquired from MOX gas sensors. Semi-automatic measurement validation is accomplished by extending established curve similarity algorithms with a slope-based signature calculation. Furthermore, a feature-based ranking metric is introduced. It allows for individual prioritization of each feature and can be used to find the best performing sensors regarding multiple research questions. Finally, the functionality of the algorithms, as well as the developed software suite, are demonstrated with an exemplary scenario, illustrating how to find the most power-efficient MOX gas sensor in a data set collected during an extensive screening consisting of 16,320 measurements, all taken with different sensors at various temperatures and analytes.
Many workers experience their jobs as effortful or even stressful, which can result in strain. Although recovery from work would be an adaptive strategy to prevent the adverse effects of work-related strain, many workers face problems finding enough time to rest and to mentally disconnect from work during nonwork time. What goes on in workers’ minds after a stressful workday? What is it about their jobs that makes them think about their work? This special issue aims to bridge the gap between research on recovery processes mainly examined in Occupational Health Psychology, and research on work stress and working hours, often investigated in the field of Human Resource Management. We first summarize conceptual and theoretical streams from both fields of research. In the following, we discuss the contributions of the five special issue papers and conclude with key messages and directions for further research.
Amino acids perform multiple essential physiological roles in humans, and accordingly, their importance to health has been the subject of extensive attention. In this special issue of the Journal of Nutrition and Metabolism, we focus on the various inborn errors of amino acid metabolism, their diagnostic challenges, new treatment approaches, and recent advances in patient monitoring as well as clinical outcomes.
This paper proposes an approach to an ANN-based temperature controller design for a plastic injection moulding system. This design approach is applied to the development of a controller based on a combination of a classical ANN and integrator. The controller provides a fast temperature response and zero steady-state error for three typical heaters (bar, nozzle, and cartridge) for a plastic moulding system. The simulation results in Matlab Simulink software and in comparison to an industrial PID regulator have shown the advantages of the controller, such as significantly less overshoot and faster transient (compared to PID with autotuning) for all examined heaters. In order to verify the proposed approach, the designed ANN controller was implemented and tested using an experimental setup based on an STM32 board.
The design of a fully superconducting wind power generator is influenced by several factors. Among them, a low number of pole pairs is desirable to achieve low AC losses in the superconducting stator winding, which greatly influences the cooling system design and, consecutively, the efficiency of the entire wind power plant. However, it has been identified that a low number of pole pairs in a superconducting generator tends to greatly increase its output voltage, which in turn creates challenging conditions for the necessary power electronic converter. This study highlights the interdependencies between the design of a fully superconducting 10 MW wind power generator and the corresponding design of its power electronic converter.
The analysis of used engine oils from industrial engines enables the study of engine wear and oil degradation in order to evaluate the necessity of oil changes. As the matrix composition of an engine oil strongly depends on its intended application, meaningful diagnostic oil analyses bear considerable challenges. Owing to the broad spectrum of available oil matrices, we have evaluated the applicability of using an internal standard and/or preceding sample digestion for elemental analysis of used engine oils via inductively coupled plasma optical emission spectroscopy (ICP OES). Elements originating from both wear particles and additives as well as particle size influence could be clearly recognized by their distinct digestion behaviour. While a precise determination of most wear elements can be achieved in oily matrix, the measurement of additives is performed preferably after sample digestion. Considering a dataset of physicochemical parameters and elemental composition for several hundred used engine oils, we have further investigated the feasibility of predicting the identity and overall condition of an unknown combustion engine using the machine learning system XGBoost. A maximum accuracy of 89.6% in predicting the engine type was achieved, a mean error of less than 10% of the observed timeframe in predicting the oil running time and even less than 4% for the total engine running time, based purely on common oil check data. Furthermore, obstacles and possibilities to improve the performance of the machine learning models were analysed and the factors that enabled the prediction were explored with SHapley Additive exPlanation (SHAP). Our results demonstrate that both the identification of an unknown engine as well as a lifetime assessment can be performed for a first estimation of the actual sample without requiring meticulous documentation.
Nitrosamines have been identified as a probable human carcinogen and thus are of high concern in many manufacturing industries and various matrices (for example pharmaceutical, cosmetic and food products, workplace air or potable- and wastewater). This study aims to analyse nine nitrosamines relevant in the field of occupational safety using a gas chromatography-drift tube ion mobility spectrometry (GC-DT-IMS) system. To do this, single nitrosamine standards as well as a standard mix, each at 0.1 g/L, were introduced via liquid injection. A GC-DT-IMS method capable of separating the nitrosamine signals according to retention time (first dimension) and drift time (second dimension) in 10 min was developed. The system shows excellent selectivity as each nitrosamine gives two signals pertaining to monomer and dimer in the second dimension. For the first time, reduced ion mobility values for nitrosamines were determined, ranging from 1.18 to 2.03 cm2s−1V−1. The high selectivity of the GC-DT-IMS method could provide a definite advantage for monitoring nitrosamines in different manufacturing industries and consumer products.
PURPOSE
Cervical cancer (CC) is caused by a persistent high-risk human papillomavirus (hrHPV) infection. The cervico-vaginal microbiome may influence the development of (pre)cancer lesions. Aim of the study was (i) to evaluate the new CC screening program in Germany for the detection of high-grade CC precursor lesions, and (ii) to elucidate the role of the cervico-vaginal microbiome and its potential impact on cervical dysplasia.
METHODS
The microbiome of 310 patients referred to colposcopy was determined by amplicon sequencing and correlated with clinicopathological parameters.
RESULTS
Most patients were referred for colposcopy due to a positive hrHPV result in two consecutive years combined with a normal PAP smear. In 2.1% of these cases, a CIN III lesion was detected. There was a significant positive association between the PAP stage and Lactobacillus vaginalis colonization and between the severity of CC precursor lesions and Ureaplasma parvum.
CONCLUSION
In our cohort, the new cervical cancer screening program resulted in a low rate of additional CIN III detected. It is questionable whether these cases were only identified earlier with additional HPV testing before the appearance of cytological abnormalities, or the new screening program will truly increase the detection rate of CIN III in the long run. Colonization with U. parvum was associated with histological dysplastic lesions. Whether targeted therapy of this pathogen or optimization of the microbiome prevents dysplasia remains speculative.
Lower back pain is one of the most prevalent diseases in Western societies. A large percentage of European and American populations suffer from back pain at some point in their lives. One successful approach to address lower back pain is postural training, which can be supported by wearable devices, providing real-time feedback about the user’s posture. In this work, we analyze the changes in posture induced by postural training. To this end, we compare snapshots before and after training, as measured by the Gokhale SpineTracker™. Considering pairs of before and after snapshots in different positions (standing, sitting, and bending), we introduce a feature space, that allows for unsupervised clustering. We show that resulting clusters represent certain groups of postural changes, which are meaningful to professional posture trainers.
Cytokine-induced killer cells (CIK) in combination with dendritic cells (DCs) have shown favorable outcomes in renal cell carcinoma (RCC), yet some patients exhibit recurrence or no response to this therapy. In a broader perspective, enhancing the antitumor response of DC-CIK cells may help to address this issue. Considering this, herein, we investigated the effect of anti-CD40 and anti-CTLA-4 antibodies on the antitumor response of DC-CIK cells against RCC cell lines. Our analysis showed that, a) anti-CD40 antibody (G28.5) increased the CD3+CD56+ effector cells of CIK cells by promoting the maturation and activation of DCs, b) G28.5 also increased CTLA-4 expression in CIK cells via DCs, but the increase could be hindered by the CTLA-4 inhibitor (ipilimumab), c) adding ipilimumab was also able to significantly increase the proportion of CD3+CD56+ cells in DC-CIK cells, d) anti-CD40 antibodies predominated over anti-CTLA-4 antibodies for cytotoxicity, apoptotic effect and IFN-g secretion of DC-CIK cells against RCC cells, e) after ipilimumab treatment, the population of Tregs in CIK cells remained unaffected, but ipilimumab combined with G28.5 significantly reduced the expression of CD28 in CIK cells. Taken together, we suggest that the agonistic anti-CD40 antibody rather than CTLA-4 inhibitor may improve the antitumor response of DC-CIK cells, particularly in RCC. In addition, we pointed towards the yet to be known contribution of CD28 in the crosstalk between anti-CTLA-4 and CIK cells.
The antiradical and antimicrobial activity of lignin and lignin-based films are both of great interest for applications such as food packaging additives. The polyphenolic structure of lignin in addition to the presence of O-containing functional groups is potentially responsible for these activities. This study used DPPH assays to discuss the antiradical activity of HPMC/lignin and HPMC/lignin/chitosan films. The scavenging activity (SA) of both binary (HPMC/lignin) and ternary (HPMC/lignin/chitosan) systems was affected by the percentage of the added lignin: the 5% addition showed the highest activity and the 30% addition had the lowest. Both scavenging activity and antimicrobial activity are dependent on the biomass source showing the following trend: organosolv of softwood > kraft of softwood > organosolv of grass. Testing the antimicrobial activities of lignins and lignin-containing films showed high antimicrobial activities against Gram-positive and Gram-negative bacteria at 35 °C and at low temperatures (0-7 °C). Purification of kraft lignin has a negative effect on the antimicrobial activity while storage has positive effect. The lignin release in the produced films affected the activity positively and the chitosan addition enhances the activity even more for both Gram-positive and Gram-negative bacteria. Testing the films against spoilage bacteria that grow at low temperatures revealed the activity of the 30% addition on HPMC/L1 film against both B. thermosphacta and P. fluorescens while L5 was active only against B. thermosphacta. In HPMC/lignin/chitosan films, the 5% addition exhibited activity against both B. thermosphacta and P. fluorescens.
Due to global ecological and economic challenges that have been correlated to the transition from fossil-based to renewable resources, fundamental studies are being performed worldwide to replace fossil fuel raw materials in plastic production. One aspect of current research is the development of lignin-derived polyols to substitute expensive fossil-based polyol components for polyurethane and polyester production. This article describes the synthesis of bioactive lignin-based polyurethane coatings using unmodified and demethylated Kraft lignins. Demethylation was performed to enhance the reaction selectivity toward polyurethane formation. The antimicrobial activity was tested according to a slightly modified standard test (JIS Z 2801:2010). Besides effects caused by the lignins themselves, triphenylmethane derivatives (brilliant green and crystal violet) were used as additional antimicrobial substances. Results showed increased antimicrobial capacity against Staphylococcus aureus. Furthermore, the coating color could be varied from dark brown to green and blue, respectively.
This study investigated the application potential of Black Soldier Fly Larva Hermetia illucens Stratiomyidae: Diptera (L.1758) for wastewater treatment and the removal potential of chemical oxygen demand, ammonia, and phosphorus of and liquid manure residue and municipal waste water containing 1% solids content. Black Soldier Fly Larva were found to reduce the concentration of chemical oxygen demand, but unfortunately, increase the concentration of ammonia and phosphorus. The ability of Black Soldier Fly Larva to feed on organic waste of Liquid manure residue showed that Black Soldier Fly Larva increase their weight by 365% in a solution with 12% solids content and by 595% in a solution having 6% solids content. The study also showed that Black Soldier Fly Larva have the ability to survive in a solution of 1% solids content and have the ability to reduce chemical oxygen demand by up to 86.4% for liquid manure residue and 46.9% for municipal wastewater after 24 hours. Generally, ammonia increased by 43.9% for Liquid manure residue and 98.6% for municipal wastewater. Total phosphorus showed an increase of 11.0% and 88.6% increase for liquid manure residue and municipal wastewater respectively over the 8-day study. Transparent environments tend to reduce the COD content more than the dark environment, both for the liquid manure residue (55.8% and 65.4%) and municipal wastewater (71.5% and 66.4%).
Analytical pyrolysis technique hyphenated to gas chromatography/mass spectrometry (Py-GC/MS) has extended the range of possible tools for characterization of synthetic polymers/copolymers. Pyrolysis involves thermal fragmentation of the analytical sample at elevated temperature between 500 and 1400 °C. In the presence of an inert gas, reproducible decomposition products characteristic for the original polymer/copolymer sample are formed. The pyrolysis products are chromatographically separated by using a fused silica capillary column and subsequently identified by interpretation of the obtained mass spectra or by using mass spectra libraries. The analytical technique eliminate the need for pre-treatment by performing analyses directly on the solid or liquid polymer sample.
In this paper, application examples of the analytical pyrolysis hyphenated to gas chromatography/mass spectrometry for the identification of different polymeric materials in the plastic and automotive industry, dentistry and occupational safety are demonstrated. For the first time results of identification of commercially light-curing dental filling material and a car wrapping foil by pyrolysis-GC/MS are presented.
The white ground crater by the Phiale Painter (450–440 BC) exhibited in the “Pietro Griffo” Archaeological Museum in Agrigento (Italy) depicts two scenes from Perseus myth. The vase is of utmost importance to archaeologists because the figures are drawn on a white background with remarkable daintiness and attention to detail. Notwithstanding the white ground ceramics being well documented from an archaeological and historical point of view, doubts concerning the compositions of pigments and binders and the production technique are still unsolved. This kind of vase is a valuable rarity, the use of which is documented in elitist funeral rituals. The study aims to investigate the constituent materials and the execution technique of this magnificent crater. The investigation was carried out using non-destructive and non-invasive techniques in situ. Portable X-ray fluorescence and Fourier-transform total reflection infrared spectroscopy complemented the use of visible and ultraviolet light photography to get an overview and specific information on the vase. The XRF data were used to produce false colour maps showing the location of the various elements detected, using the program SmART_scan. The use of gypsum as the material for the white ground is an important result that deserves to be further investigated in similar vases.
Are There Extended Cognitive Improvements from Different Kinds of Acute Bouts of Physical Activity?
(2020)
Acute bouts of physical activity of at least moderate intensity have shown to enhance cognition in young as well as older adults. This effect has been observed for different kinds of activities such as aerobic or strength and coordination training. However, only few studies have directly compared these activities regarding their effectiveness. Further, most previous studies have mainly focused on inhibition and have not examined other important core executive functions (i.e., updating, switching) which are essential for our behavior in daily life (e.g., staying focused, resisting temptations, thinking before acting), as well. Therefore, this study aimed to directly compare two kinds of activities, aerobic and coordinative, and examine how they might affect executive functions (i.e., inhibition, updating, and switching) in a test-retest protocol. It is interesting for practical implications, as coordinative exercises, for example, require little space and would be preferable in settings such as an office or a classroom. Furthermore, we designed our experiment in such a way that learning effects were controlled. Then, we tested the influence of acute bouts of physical activity on the executive functioning in both young and older adults (young 16–22 years, old 65–80 years). Overall, we found no differences between aerobic and coordinative activities and, in fact, benefits from physical activities occurred only in the updating tasks in young adults. Additionally, we also showed some learning effects that might influence the results. Thus, it is important to control cognitive tests for learning effects in test-retest studies as well as to analyze effects from physical activity on a construct level of executive functions.
Research has identified nudging as a promising and effective tool to improve healthy eating behavior in a cafeteria setting. However, it remains unclear who is and who is not “nudgeable” (susceptible to nudges). An important influencing factor at the individual level is nudge acceptance. While some progress has been made in determining influences on the acceptance of healthy eating nudges, research on how personal characteristics (such as the perception of social norms) affect nudge acceptance remains scarce. We conducted a survey on 1032 university students to assess the acceptance of nine different types of healthy eating nudges in a cafeteria setting with four influential factors (social norms, health-promoting collaboration, responsibility to promote healthy eating, and procrastination). These factors are likely to play a role within a university and a cafeteria setting. The present study showed that key influential factors of nudge acceptance were the perceived responsibility to promote healthy eating and health-promoting collaboration. We also identified three different student clusters with respect to nudge acceptance, demonstrating that not all nudges were accepted equally. In particular, default, salience, and priming nudges were at least moderately accepted regardless of the degree of nudgeability. Our findings provide useful policy implications for nudge development by university, cafeteria, and public health officials. Recommendations are formulated for strengthening the theoretical background of nudge acceptance and the susceptibility to nudges.
This paper explores the role of artificial intelligence (AI) in elite sports. We approach the topic from two perspectives. Firstly, we provide a literature based overview of AI success stories in areas other than sports. We identified multiple approaches in the area of Machine Perception, Machine Learning and Modeling, Planning and Optimization as well as Interaction and Intervention, holding a potential for improving training and competition. Secondly, we discover the present status of AI use in elite sports. Therefore, in addition to another literature review, we interviewed leading sports scientist, which are closely connected to the main national service institute for elite sports in their countries. The analysis of this literature review and the interviews show that the most activity is carried out in the methodical categories of signal and image processing. However, projects in the field of modeling & planning have become increasingly popular within the last years. Based on these two perspectives, we extract deficits, issues and opportunities and summarize them in six key challenges faced by the sports analytics community. These challenges include data collection, controllability of an AI by the practitioners and explainability of AI results.
The implementation of the Sustainable Development Goals (SDGs) and the conservation and protection of nature are among the greatest challenges facing urban regions. There are few approaches so far that link the SDGs to natural diversity and related ecosystem services at the local level and track them in terms of increasing sustainable development at the local level. We want to close this gap by developing a set of indicators that capture ecosystem services in the sense of the SDGs and which are based on data that are freely available throughout Germany and Europe. Based on 10 SDGs and 35 SDG indicators, we are developing an ecosystem service and biodiversity-related indicator set for the evaluation of sustainable development in urban areas. We further show that it is possible to close many of the data gaps between SDGs and locally collected data mentioned in the literature and to translate the universal SDGs to the local level. Our example develops this set of indicators for the Bonn/Rhein-Sieg metropolitan area in North Rhine-Westphalia, Germany, which comprises both rural and densely populated settlements. This set of indicators can also help improve communication and plan sustainable development by increasing transparency in local sustainability, implementing a visible sustainability monitoring system, and strengthening the collaboration between local stakeholders.
Background: Type 2 diabetes mellitus is associated with increased cardiovascular risk. One laboratory marker for cardiovascular risk assessment is high-sensitivity C-reactive protein (hsCRP).
Methods: This cross-sectional study attempted to analyze the association of hsCRP levels with insulin resistance, β-cell dysfunction and macrovascular disease in 4270 non-insulin-treated patients with type 2 diabetes [2146 male, 2124 female; mean age ±SD, 63.9±11.1years; body mass index (BMI) 30.1±5.5kg/m2; disease duration 5.4±5.6years; hemoglobin A1c (HbA1c) 6.8±1.3%]. It consisted of a single morning visit with collection of a fasting blood sample. Observational parameters included several clinical scores and laboratory biomarkers.
Results: Stratification into cardiovascular risk groups according to hsCRP levels revealed that 934 patients had low risk (hsCRP <1mg/L), 1369 patients had intermediate risk (hsCRP 1–3mg/L), 1352 patients had high risk (hsCRP >3–10mg/L), and 610 patients had unspecific hsCRP elevation (>10mg/L). Increased hsCRP levels were associated with other indicators of diabetes-related cardiovascular risk (homeostatic model assessment, intact proinsulin, insulin, BMI, β-cell dysfunction, all p<0.001), but showed no correlation with disease duration or glucose control. The majority of the patients were treated with diet (34.1%; hsCRP levels 2.85±2.39mg/L) or metformin monotherapy (21.1%; 2.95±2.50mg/L hsCRP). The highest hsCRP levels were observed in patients treated with sulfonylurea (17.0%; 3.00±2.43mg/L).
Conclusions: Our results indicate that hsCRP may be used as a cardiovascular risk marker in patients with type 2 diabetes mellitus and should be evaluated in further prospective studies.
Due to the COVID-19 pandemic, health education programs and workplace health promotion (WHP) could only be offered under difficult conditions, if at all. In Germany for example, mandatory lockdowns, working from home, and physical distancing have led to a sharp decline in expenditure on prevention and health promotion from 2019 to 2020. At the same time, the pandemic has negatively affected many people’s mental health. Therefore, our goal was to examine audiovisual stimulation as a possible measure in the context of WHP, because its usage is contact-free, time flexible, and offers, additionally, voice-guided health education programs. In an online survey following a cross-sectional single case study design with 393 study participants, we examined the associations between audiovisual stimulation and mental health, work engagement, and burnout. Using multiple regression analyses, we could identify positive associations between audiovisual stimulation and mental health, burnout, and work engagement. However, longitudinal data are needed to further investigate causal mechanisms between mental health and the use of audiovisual stimulation. Nevertheless, especially with regard to the pandemic, audiovisual stimulation may represent a promising measure for improving mental health at the workplace.
In a research project funded by the German Research Foundation, meteorologists, data publication experts, and computer scientists optimised the publication process of meteorological data and developed software that supports metadata review. The project group placed particular emphasis on scientific and technical quality assurance of primary data and metadata. At the end, the software automatically registers a Digital Object Identifier at DataCite. The software has been successfully integrated into the infrastructure of the World Data Center for Climate, but a key was to make the results applicable to data publication processes in other sciences as well.
Ausrangierte Nachrichten
(2022)
Wichtige Nachrichten finden nicht ihre Bestimmung, nämlich das politisch interessierte und gesellschaftlich aufgeschlossene Publikum. Man kann diesen Vorgang als Agenda Cutting bezeichnen. Der Beitrag stellt die wichtigsten theoretischen Positionen zu diesem bislang noch wenig erforschten Phänomen dar, präsentiert wichtige Studienergebnisse und auch eigene empirische Ergebnisse zu innerredaktionellen Entscheidungsfindungsprozessen, bei denen Themen von der Agenda gestrichen werden. Zuletzt wird auch die Rolle des Publikums als Akteur beim Vorgang des Agenda Cuttings kritisch beleuchtet, die man als »news ignorance« beschreiben könnte.[1]
Die schleichende Abschaffung der Lernmittelfreiheit in den deutschen Bundesländern steht im Jahr 2022 auf Platz 1 der Top Ten der ›Vergessenen Nachrichten‹, die die Initiative Nachrichtenaufklärung (INA) e.V. jedes Jahr in die Öffentlichkeit lanciert. Der Chef des Fernsehnachrichtenmagazins Tagesthemen und stellvertretender Chefredakteur von ARD-Aktuell, Helge Fuhst, konzedierte in der Mediensendung eines öffentlich-rechtlichen Radiosenders, dass er dieses Thema für hochrelevant halte und es tatsächlich in seiner TV-Nachrichtensendung nicht behandelt worden sei. »Was das Schwierigste ist, ist tatsächlich Themen wegzulassen«, so Fuhst. »Es schmerzt uns jeden Tag, wenn wir Themen weglassen müssen. Es gibt wenige Tage im Laufe des Jahres, wo wir absolut keine Idee haben, was wir in die Sendung nehmen sollen« (WDR 2022).
Der Vorgang der Nachrichtenselektion ist redaktionelle Routine, und zu dieser Routine zählt auch, Themen wegzulassen, auszusortieren, fortzuschmeißen. Wenn dieser negative Prozess intentional erfolgt, kann man auch von Agenda Cutting sprechen. Dieser kommunikationswissenschaftliche Begriff beschreibt eine eigene Form redaktioneller Routine, die bislang nur wenig untersucht worden ist und deren Mechanismen mit ihrem erheblichen Einfluss auf die öffentliche Meinungsbildung dringend unter das Seziermesser der Medienforschung gehören.
Automated parameterization of intermolecular pair potentials using global optimization techniques
(2014)
In this work, different global optimization techniques are assessed for the automated development of molecular force fields, as used in molecular dynamics and Monte Carlo simulations. The quest of finding suitable force field parameters is treated as a mathematical minimization problem. Intricate problem characteristics such as extremely costly and even abortive simulations, noisy simulation results, and especially multiple local minima naturally lead to the use of sophisticated global optimization algorithms. Five diverse algorithms (pure random search, recursive random search, CMA-ES, differential evolution, and taboo search) are compared to our own tailor-made solution named CoSMoS. CoSMoS is an automated workflow. It models the parameters’ influence on the simulation observables to detect a globally optimal set of parameters. It is shown how and why this approach is superior to other algorithms. Applied to suitable test functions and simulations for phosgene, CoSMoS effectively reduces the number of required simulations and real time for the optimization task.
A company's financial documents use tables along with text to organize the data containing key performance indicators (KPIs) (such as profit and loss) and a financial quantity linked to them. The KPI’s linked quantity in a table might not be equal to the similarly described KPI's quantity in a text. Auditors take substantial time to manually audit these financial mistakes and this process is called consistency checking. As compared to existing work, this paper attempts to automate this task with the help of transformer-based models. Furthermore, for consistency checking it is essential for the table's KPIs embeddings to encode the semantic knowledge of the KPIs and the structural knowledge of the table. Therefore, this paper proposes a pipeline that uses a tabular model to get the table's KPIs embeddings. The pipeline takes input table and text KPIs, generates their embeddings, and then checks whether these KPIs are identical. The pipeline is evaluated on the financial documents in the German language and a comparative analysis of the cell embeddings' quality from the three tabular models is also presented. From the evaluation results, the experiment that used the English-translated text and table KPIs and Tabbie model to generate table KPIs’ embeddings achieved an accuracy of 72.81% on the consistency checking task, outperforming the benchmark, and other tabular models.
Yams of the most widely differing nature are produced in textile mills. The production stages necessary for this are carried out with the aid of textile machines. Between these individual textile machines - from cards to spinning machines - sliver cans serve as a rule as transport containers, in which the sensitive sliver material is temporarily stored, and presented to the next production stage.
Der vorliegende Beitrag befaßt sich mit Automatisierungsmöglichkeiten in Textilbetrieben für konventionelle als auch für nichtkonventionelle Spinnverfahren. Aus der Vielzahl derzeit existenter Produktionsschritte werden die standardisierbaren Automatisierungskombinationen zwischen den eingesetzten Textilmaschinen von Karden bis zu Spinnautomaten herausgearbeitet. Hierfür werden die heute in der Praxis befindlichen Transportmittel aufgezeigt und, vom Materialfluß ausgehend, die Zuordnungsmöglichkeiten der Maschinen in den Produktionsschritten und deren Automatisierungsbausteine definiert. Durch eine ganzheitliche Betrachtungsweise werden je nach Automatisierungsziel die verschiedenen Lösungsansätze diskutiert und als Bausteine gegenübergestellt. Hierdurch werden neue mechatronische Automatisierungslösungen vorgestellt, die eine Integration von Produktionsschritten oder die Automatisierung zwischen den einzelnen Produktionsschritten ermöglicht.
In March 2020, the world was hit by the coronavirus disease (COVID‐19) pandemic which led to all‐embracing measures to contain its spread. Most employees were forced to work from home and take care of their children because schools and daycares were closed. We present data from a research project in a large multinational organisation in the Netherlands with monthly quantitative measurements from January to May 2020 (N = 253–516), enriched with qualitative data from participants' comments before and after telework had started. Growth curve modelling showed major changes in employees' work‐related well‐being reflected in decreasing work engagement and increasing job satisfaction. For work‐non‐work balance, workload and autonomy, cubic trends over time were found, reflecting initial declines during crisis onset (March/April) and recovery in May. Participants' additional remarks exemplify that employees struggled with fulfilling different roles simultaneously, developing new routines and managing boundaries between life domains. Moderation analyses demonstrated that demographic variables shaped time trends. The diverging trends in well‐being indicators raise intriguing questions and show that close monitoring and fine‐grained analyses are needed to arrive at a better understanding of the impact of the crisis across time and among different groups of employees.
In der heutigen Zeit nimmt die Bedeutung schlanker und effektiver Prozesse in Unternehmen vor dem Hintergrund des Wettbewerbs sowie Kostendrucks stetig zu. Um dieser Herausforderung entgegenzuwirken, fokussieren sich Unternehmen auf die Identifikation neuer innovativer Potenziale. Aufgrund der Tatsache, dass monotone und regelbasierte Prozesse durch Softwareroboter automatisiert werden können, ist das Interesse an Robotic Process Automation (RPA) in den letzten Jahren stetig gestiegen. Bevor sich Unternehmen allerdings für oder gegen den Einsatz von RPA entscheiden, ist es zunächst notwendig, dass die Entscheidungsträger ein Verständnis von RPA erlangen sowie die entsprechenden Einsatzpotenziale und Risiken einschätzen können. Dieser Artikel trägt diesem Bedürfnis Rechnung, indem es diese auf Basis einer Literaturrecherche ermittelt und bewertet. Im Ausblick wird das zukünftige Potenzial von RPA eingeschätzt.
Here, we present a miR mechanism which is active in the nucleus and is essential for the production of intron included, C-terminal truncated and biologically active proteins, like e.g. Vim3. We exemplified this mechanism by miRs, miR-15a and miR-498, which are overexpressed in clear cell renal carcinoma or oncocytoma. Both miRs directly interact with DNA in an intronic region, leading to transcriptional stop, and therefore repress the full length version of the pre-mRNA, resulting in intron included truncated proteins (Mxi-2 and Vim3). A computational survey shows that this miR:DNA interactions mechanism may be generally involved in regulating the human transcriptome, with putative interaction sites in intronic regions for over 1000 genes. In this work, an entirely new mechanism is revealed how miRs can repress full length protein translation, resulting in C-terminal truncated proteins.
When optimizing the process parameters of the acidic ethanolic organosolv process, the aim is usually to maximize the delignification and/or lignin purity. However, process parameters such as temperature, time, ethanol and catalyst concentration, respectively, can also be used to vary the structural properties of the obtained organosolv lignin, including the molecular weight and the ratio of aliphatic versus phenolic hydroxyl groups, among others. This review particularly focuses on these influencing factors and establishes a trend analysis between the variation of the process parameters and the effect on lignin structure. Especially when larger data sets are available, as for process temperature and time, correlations between the distribution of depolymerization and condensation reactions are found, which allow direct conclusions on the proportion of lignin's structural features, independent of the diversity of the biomass used. The newfound insights gained from this review can be used to tailor organosolv lignins isolated for a specific application.
The backdated research dedicated to digital entrepreneurship education is immense, which makes it difficult to create an overview. Conversely, forward-thinking bibliometric visualization mapping and clustering can assist in visualizing and structuring difficult research literature. Hence, the goal of this mapping visualization study is to thoroughly discover and create clusters of EE to convey a taxonomic structure that can oblige as a basis for upcoming research. The analyzed data, which is drawn from Google Scholar through Publish or Perish tool, contain 1000 documents published between 2007 and 2022. This taxonomy should generate stronger bonds with digital entrepreneurial education research; on the other, it should stand in international research association to boost both interdisciplinary digital entrepreneurial education and its influence on a universal basis. This work strengthens student’s understanding of current digital entrepreneurial education research by classifying and decontaminating the most powerful knowledgeable relationship among its contributions and contributors. The bibliographic analysis includes ‘citation network’, ‘author’s research area’ and ‘paper content’ regarding the desired topic. In this paper, the above three mentioned terms are integrated which produces a bibliographic model of authors, titles of their papers, keywords and abstract by using Harzing’s Publish or Perish tool for extracting data from Google Scholar and further using VOSViewer to visualize networking map of co-authorship and term co-occurrence to administer the data for an instinctive and appropriate understanding of university students concerning ‘digital entrepreneurial intention’ research. This paper uses bibliometric analysis to analyze the keyword co-occurrence and co-authorship and VOSViewer is used for visualization.
A firm link between endoplasmic reticulum (ER) stress and tumors has been wildly reported. Endoplasmic reticulum oxidoreductase 1 alpha (ERO1α), an ER-resident thiol oxidoreductase, is confirmed to be highly upregulated in various cancer types and associated with a significantly worse prognosis. Of importance, under ER stress, the functional interplay of ERO1α/PDI axis plays a pivotal role to orchestrate proper protein folding and other key processes. Multiple lines of evidence propose ERO1α as an attractive potential target for cancer treatment. However, the unavailability of specific inhibitor for ERO1α, its molecular inter-relatedness with closely related paralog ERO1β and the tightly regulated processes with other members of flavoenzyme family of enzymes, raises several concerns about its clinical translation. Herein, we have provided a detailed description of ERO1α in human cancers and its vulnerability towards the aforementioned concerns. Besides, we have discussed a few key considerations that may improve our understanding about ERO1α in tumors.
There is an unmet need for the development and validation of biomarkers and surrogate endpoints for clinical trials in propionic acidemia (PA) and methylmalonic acidemia (MMA). This review examines the pathophysiology and clinical consequences of PA and MMA that could form the basis for potential biomarkers and surrogate endpoints. Changes in primary metabolites such as methylcitric acid (MCA), MCA:citric acid ratio, oxidation of 13C-propionate (exhaled 13CO2), and propionylcarnitine (C3) have demonstrated clinical relevance in patients with PA or MMA. Methylmalonic acid, another primary metabolite, is a potential biomarker, but only in patients with MMA. Other potential biomarkers in patients with either PA and MMA include secondary metabolites, such as ammonium, or the mitochondrial disease marker, fibroblast growth factor 21. Additional research is needed to validate these biomarkers as surrogate endpoints, and to determine whether other metabolites or markers of organ damage could also be useful biomarkers for clinical trials of investigational drug treatments in patients with PA or MMA. This review examines the evidence supporting a variety of possible biomarkers for drug development in propionic and methylmalonic acidemias.
Blickpunkt
(2024)
Introduction: Chronic pain is a frequent severe disease and often associated with anxiety, depression, insomnia, disability, and reduced quality of life. This maladaptive condition is further characterized by sensory loss, hyperalgesia, and allodynia. Blue light has been hypothesized to modulate sensory neurons and thereby influence nociception.
Objectives: Here, we compared the effects of blue light vs red light and thermal control on pain sensation in a human experimental pain model.
Methods: Pain, hyperalgesia, and allodynia were induced in 30 healthy volunteers through high-density transcutaneous electrical stimulation. Subsequently, blue light, red light, or thermal control treatment was applied in a cross-over design. The nonvisual effects of the respective light treatments were examined using a well-established quantitative sensory testing protocol. Somatosensory parameters as well as pain intensity and quality were scored.
Results: Blue light substantially reduced spontaneous pain as assessed by numeric rating scale pain scoring. Similarly, pain quality was significantly altered as assessed by the German counterpart of the McGill Pain Questionnaire. Furthermore, blue light showed antihyperalgesic, antiallodynic, and antihypesthesic effects in contrast to red light or thermal control treatment.
Conclusion: Blue-light phototherapy ameliorates pain intensity and quality in a human experimental pain model and reveals antihyperalgesic, antiallodynic, and antihypesthesic effects. Therefore, blue-light phototherapy may be a novel approach to treat pain in multiple conditions.
Multidisciplinary systems are described most suitably by bond graphs. In order to determine unnormalized frequency domain sensitivities in symbolic form, this paper proposes to construct in a systematic manner a bond graph from another bond graph, which is called the associated incremental bond graph in this paper. Contrary to other approaches reported in the literature the variables at the bonds of the incremental bond graph are not sensitivities but variations (incremental changes) in the power variables from their nominal values due to parameter changes. Thus their product is power. For linear elements their corresponding model in the incremental bond graph also has a linear characteristic. By deriving the system equations in symbolic state space form from the incremental bond graph in the same way as they are derived from the initial bond graph, the sensitivity matrix of the system can be set up in symbolic form. Its entries are transfer functions depending on the nominal parameter values and on the nominal states and the inputs of the original model. The sensitivities can be determined automatically by the bond graph preprocessor CAMP-G and the widely used program MATLAB together with the Symbolic Toolbox for symbolic mathematical calculation. No particular program is needed for the approach proposed. The initial bond graph model may be non-linear and may contain controlled sources and multiport elements. In that case the sensitivity model is linear time variant and must be solved in the time domain. The rationale and the generality of the proposed approach are presented. For illustration purposes a mechatronic example system, a load positioned by a constant-excitation d.c. motor, is presented and sensitivities are determined in symbolic form by means of CAMP-G/MATLAB.
In this paper, residual sinks are used in bond graph model-based quantitative fault detection for the coupling of a model of a faultless process engineering system to a bond graph model of the faulty system. By this way, integral causality can be used as the preferred computational causality in both models. There is no need for numerical differentiation. Furthermore, unknown variables do not need to be eliminated from power continuity equations in order to obtain analytical redundancy relations (ARRs) in symbolic form. Residuals indicating faults are computed numerically as components of a descriptor vector of a differential algebraic equation system derived from the coupled bond graphs. The presented bond graph approach especially aims at models with non-linearities that make it cumbersome or even impossible to derive ARRs from model equations by elimination of unknown variables. For illustration, the approach is applied to a non-controlled as well as to a controlled hydraulic two-tank system. Finally, it is shown that not only the numerical computation of residuals but also the simultaneous numerical computation of their sensitivities with respect to a parameter can be supported by bond graph modelling.
A bond graph representation of switching devices known for a long time has been a modulated transformer with a modulus b(t)∈{0,1}∀t≥0 in conjunction with a resistor R:Ron accounting for the ON-resistance of a switch considered non-ideal. Besides other representations, this simple model has been used in bond graphs for simulation of the dynamic behaviour of hybrid systems. A previous article of the author has proposed to use the transformer–resistor pair in bond graphs for fault diagnosis in hybrid systems. Advantages are a unique bond graph for all system modes, the application of the unmodified standard Sequential Causality Assignment Procedure, fixed computational causalities and the derivation of analytical redundancy relations incorporating ‘Boolean’ transformer moduli so that they hold for all system modes. Switches temporarily connect and disconnect model parts. As a result, some independent storage elements may temporarily become dependent, so that the number of state variables is not time-invariant. This article addresses this problem in the context of modelling and simulation of fault scenarios in hybrid systems. In order to keep time-invariant preferred integral causality at storage ports, residual sinks previously introduced by the author are used. When two storage elements become dependent at a switching time instance ts, a residual sink is activated. It enforces that the outputs of two dependent storage elements become immediately equal by imposing the conjugate3 power variable of appropriate value on their inputs. The approach is illustrated by the bond graph modelling and simulation of some fault scenarios in a standard three-phase switched power inverter supplying power into an RL-load in a delta configuration. A well-developed approach to model-based fault detection and isolation is to evaluate the residual of analytical redundancy relations. In this article, analytical redundancy relation residuals have been computed numerically by coupling a bond graph of the faulty system to one of the non-faulty systems by means of residual sinks. The presented approach is not confined to power electronic systems but can be used for hybrid systems in other domains as well. In further work, the RL-load may be replaced by a bond graph model of an alternating current motor in order to study the effect of switch failures in the power inverter on to the dynamic behaviour of the motor.
Bond graph modelling was devised by Professor Paynter at the Massachusetts Institute of Technology in 1959 and subsequently developed into a methodology for modelling multidisciplinary systems at a time when nobody was speaking of object-oriented modelling. On the other hand, so-called object-oriented modelling has become increasingly popular during the last few years. By relating the characteristics of both approaches, it is shown that bond graph modelling, although much older, may be viewed as a special form of object-oriented modelling. For that purpose the new object-oriented modelling language Modelica is used as a working language which aims at supporting multiple formalisms. Although it turns out that bond graph models can be described rather easily, it is obvious that Modelica started from generalized networks and was not designed to support bond graphs. The description of bond graph models in Modelica is illustrated by means of a hydraulic drive. Since VHDL-AMS as an important language standardized and supported by IEEE has been extended to support also modelling of non-electrical systems, it is briefly investigated as to whether it can be used for description of bond graphs. It turns out that currently it does not seem to be suitable.
For the case when the abstraction of instantaneous state transitions is adopted, this paper proposes to start fault detection and isolation in an engineering system from a single time-invariant causality bond graph representation of a hybrid model. To that end, the paper picks up on a long-known proposal to model switching devices by a transformer modulated by a Boolean variable and a resistor in fixed conductance causality accounting for its ON resistance. Bond graph representations of hybrid system models developed in this way have been used so far mainly for the purpose of simulation. The paper shows that they can well constitute an approach to the bond-graph-based quantitative fault detection and isolation of hybrid models. Advantages are that the standard sequential causality assignment procedure can be a used without modification. A single set of analytical redundancy relations valid for all physically feasible system modes can be (automatically) derived from the bond graph. Stiff model equations due to small values of the ON resistance in the switch model may be avoided by symbolic reformulation of equations and letting the ON resistance of some switches tend to zero, turning them into ideal switches.
First, for two examples considered in the literature, it is shown that the approach proposed in this paper can produce the same analytical redundancy relations as were obtained from a hybrid bond graph with controlled junctions and the use of a sequential causality assignment procedure especially for fault detection and isolation purpose. Moreover, the usefulness of the proposed approach is illustrated in two case studies by its application to standard switching circuits extensively used in power electronic systems and by simulation of some fault scenarios. The approach, however, is not confined to the fault detection and isolation of such systems. Analytically validated simulation results obtained by means of the program Scilab give confidence in the approach.
The purpose of the study is to provide empirical evidence about the under-researched area of university–government relations in building a culture of entrepreneurial initiatives inside the triple helix model in a rural region. The study deploys a qualitative case study research method based on the content analysis of project documentation and further internal documents both from universities and municipalities. The propositions in the research question are guided by the previous literature and were then analyzed through an “open coding” process to iteratively analyze, verify, and validate the results from the documents against the previous literature. Results presented in the case study are related both to the project of a municipality–university innovation partnership, as well as the historic development of the university in its three missions, and, related to the important third mission, themes relevant for the project. In addition, a “toolkit” of relevant project activities is presented against the major identified themes, major project stakeholders, as well as relevant Sustainable Development Goals (SDGs). Universities should look beyond a purely economic contribution and should augment all three missions (teaching, research, engagement) by considering social, environmental, and economic aspects of its activities. Instead of considering a government’s role solely as that of a regulator, a much more creative and purposeful cooperation between university and government is possible for creating a regional culture of entrepreneurial initiatives in a rural region.
Many people do not consume as much healthy food as recommended. Nudging has been identified as a promising intervention strategy to increase the consumption of healthy food. The present study analyzed the effects of three body shape nudges (thin, thick, or Giacometti artwork) on food ordering and assessed the mediating role of being aware of the nudge. Students (686) and employees (218) of a German university participated in an online experimental study. After randomization, participants visited a realistic online cafeteria and composed a meal for themselves. Under experimental conditions, participants were exposed to one out of three nudges while choosing dishes: (1) thin body shape, (2) thick body shape, and (3) the Giacometti artwork nudge. The Giacometti nudge resulted in more orders for salad among employees. The thin and thick body shape nudges did not change dish orders. Awareness of the nudge mediated the numbers of calories ordered when using the Giacometti or thin body shape nudges. These findings provide useful insights for health interventions in occupational and public health sectors using nudges. Our study contributes to the research on the Giacometti nudge by showing its effectiveness when participants are aware (it is effective under conditions where it is consciously perceived).
Climate change is transforming the risks individuals and households face, with potentially profound socioeconomic consequences such as increased poverty, inequality, and social instability. Social protection is a policy tool that governments use to help individuals and households manage risks linked to income and livelihoods, and to achieve societal outcomes such as reducing poverty and inequality. Despite its potential as a policy response to climate change, the integration of social protection within the climate policy agenda is currently limited. While the concept of risk is key to both sectors, different understandings of the nature and scope of climate change impacts and their implications, as well as of the adequacy of social protection instruments to address them, contribute to the lack of policy and practice integration.
Our goal is to bridge this cognitive gap by highlighting the potential of social protection as a policy response to climate change. Using a comprehensive climate risk lens, we first explore how climate change drives risks that are within the realm of social protection, and their implications, including likely future trends in demand for social protection. Based on this analysis, we critically review existing arguments for what social protection can do and evidence of what it currently does to manage risks arising from climate change. From the analysis, a set of reconceptualised roles emerge for social protection to strategically contribute to climate-resilient development.
The promotion of sustainable packaging is part of the European Green Deal and plays a key role in the EU’s social and political strategy. One option is the use of renewable resources and biomass waste as raw materials for polymer production. Lignocellulose biomass from annual and perennial industrial crops and agricultural residues are a major source of polysaccharides, proteins, and lignin and can also be used to obtain plant-based extracts and essential oils. Therefore, these biomasses are considered as potential substitute for fossil-based resources. Here, the status quo of bio-based polymers is discussed and evaluated in terms of properties related to packaging applications such as gas and water vapor permeability as well as mechanical properties. So far, their practical use is still restricted due to lower performance in fundamental packaging functions that directly influence food quality and safety, the length of shelf life, and thus the amount of food waste. Besides bio-based polymers, this review focuses on plant extracts as active packaging agents. Incorporating extracts of herbs, flowers, trees, and their fruits is inevitable to achieve desired material properties that are capable to prolong the food shelf life. Finally, the adoption potential of packaging based on polymers from renewable resources is discussed from a bioeconomy perspective.
Background: Coniferous woods (Abies nordmanniana (Stev.) Spach, Abies procera Rehd, Picea abies (L.) H.Karst, and Picea pungens Engelm.) could contain useful secondary metabolites to produce sustainable packaging materials, e.g., by substitution of harmful petrol-based additives in plastic packaging. This study aims to characterise the antioxidant and light-absorbing properties and ingredients of different coniferous wood extracts with regard to different plant fragments and drying conditions. Furthermore, the valorisation of used Christmas trees is evaluated. Methods: Different drying and extraction techniques were applied with the extracts being characterised by determining the total phenolic content (TPC), total antioxidant capacity (TAC), and absorbance in the ultraviolet range (UV). Gas chromatography coupled with mass spectrometry (GC-MS) and an acid–butanol assay (ABA) were used to characterise the extract constituents. Results: All the extracts show a considerably high UV absorbance while interspecies differences did occur. All the fresh and some of the dried biomass extracts reached utilisable TAC and TPC values. A simplified extraction setup for industrial application is evaluated; comparable TAC results could be reached with modifications. Conclusion: Coniferous woods are a promising renewable resource for preparation of sustainable antioxidants and photostabilisers. This particularly applies to Christmas trees used for up to 12 days. After extraction, the biomass can be fully valorised by incorporation in paper packaging.
The complex nature of multifactorial diseases, such as Morbus Alzheimer, has produced a strong need to design multitarget-directed ligands to address the involved complementary pathways. We performed a purposive structural modification of a tetratarget small-molecule, that is contilisant, and generated a combinatorial library of 28 substituted chromen-4-ones. The compounds comprise a basic moiety which is linker-connected to the 6-position of the heterocyclic chromenone core. The syntheses were accomplished by Mitsunobu- or Williamson-type ether formations. The resulting library members were evaluated at a panel of seven human enzymes, all of which being involved in the pathophysiology of neurodegeneration. A concomitant inhibition of human acetylcholinesterase and human monoamine oxidase B, with IC50 values of 5.58 and 7.20 μM, respectively, was achieved with the dual-target 6-(4-(piperidin-1-yl)butoxy)-4H-chromen-4-one (7).
Multiple myeloma is the second most common hematological malignancy. Despite all the progress made in treating multiple myeloma, it still remains an incurable disease. Patients are left with a median survival of 4-5 years. The combined treatment of multiple myeloma with histone deacetylase inhibitors and cytokine-induced killer cells provides a promising targeted treatment option for patients. This study investigated the impact of a combined treatment compared to treatment with histone deacetylase inhibitors. The experiments revealed that a treatment with histone deacetylase (HDAC) inhibitors could reduce cell viability to 59% for KMS 18 cell line and 46% for the U-266 cell line. The combined treatment led to a decrease of cell viability to 33% for KMS 18 and 27% for the U-266 cell line, thus showing a significantly better efficacy than the single treatment.
Citizen participation is deemed to be crucial for sustainability and resilience planning. However, generational equity has been missing from recent academic discussions regarding sustainability and resilience. Therefore, the purpose of this paper is to reintroduce the topic of the existence or absence of an intergenerational consensus on the example of a rural community and its perceived brand image attributes and development priorities. The research is based on primary data collected through an online survey, with a sample size of N = 808 respondents in Neunkirchen-Seelscheid, Germany. The data were analyzed using the Kruskal–Wallis test for the presence and/or absence of consensus among the five generations regarding brand image attributes and development priorities. The findings point to divergence between what the median values indicate as the most relevant brand image attributes and development priorities among the citizens and the areas where the Kruskal–Wallis test shows that an intergenerational consensus either does or does not exist. The results imply the need for new concepts and applied approaches to citizen participation for sustainability and resilience, where intergenerational dialogue and equity-building take center stage. In addition to the importance of the theory of citizen participation for sustainability and resilience, our results provide ample evidence for how sustainability and resilience planning documents could potentially benefit from deploying the concept of intergenerational equity. The present research provides sustainability and political science with new conceptual and methodological approaches for taking intergenerational equity into account in regional planning processes in rural and other areas.
There are several recent works which had proposed an automatic computer-aided diagnosis (CAD) deep learning (DL) model to diagnose coronavirus disease 2019 (COVID-19) using chest x-ray images (CXR) to propose a high-accuracy CAD method to detect COVID-19 automatically. In this study, seven different models including Convolutional Neural Network (CNN) models such as VGG-16 and vision transformer (ViT) models, are proposed. The different proposed models are trained with a three-class balanced dataset consisting of 3,000 CXR images consisting of 1,000 CXR images for each class of COVID-19, Normal, and Lung-Opacity. A publicly available dataset to train and test the models is used from Kaggle-COVID-19-Radiography-Dataset. From the experiments, the accuracy of the VGG16 model is 93.44% and ViT's is 92.33%. Besides, the binary classification between two classes of COVID-19 and Normal CXR with a limited number of just 100 images for each class, using a transfer learning technique, with a validation accuracy of 97.5% is proposed.
Trends of environmental awareness, combined with a focus on personal fitness and health, motivate many people to switch from cars and public transport to micromobility solutions, namely bicycles, electric bicycles, cargo bikes, or scooters. To accommodate urban planning for these changes, cities and communities need to know how many micromobility vehicles are on the road. In a previous work, we proposed a concept for a compact, mobile, and energy-efficient system to classify and count micromobility vehicles utilizing uncooled long-wave infrared (LWIR) image sensors and a neuromorphic co-processor. In this work, we elaborate on this concept by focusing on the feature extraction process with the goal to increase the classification accuracy. We demonstrate that even with a reduced feature list compared with our early concept, we manage to increase the detection precision to more than 90%. This is achieved by reducing the images of 160 × 120 pixels to only 12 × 18 pixels and combining them with contour moments to a feature vector of only 247 bytes.
Cysticfibrosis (CF) arises from mutations in the CF transmembrane conductance regulator (CFTR) gene, resulting in progressiveand life-limiting respiratory disease. R751L is a rare CFTR mutation that is poorly characterized. Our aims were to describe theclinical and molecular phenotypes associated with R751L. Relevant clinical data were collected from three heterozygote individu-als harboring R751L (2 patients with G551D/R751L and 1 with F508del/R751L). Assessment of R751L-CFTR function was made inprimary human bronchial epithelial cultures (HBEs) andXenopusoocytes. Molecular properties of R751L-CFTR were investigatedin the presence of known CFTR modulators. Although sweat chloride was elevated in all three patients, the clinical phenotypeassociated with R751L was mild. Chloride secretion in F508del/R751L HBEs was reduced compared with non-CF HBEs and asso-ciated with a reduction in sodium absorption by the epithelial sodium channel (ENaC). However, R751L-CFTR function inXenopusoocytes, together with folding and cell surface transport of R751L-CFTR, was not different from wild-type CFTR. Overall,R751L-CFTR was associated with reduced sodium chloride absorption but had functional properties similar to wild-type CFTR.This is thefirst report of R751L-CFTR that combines clinical phenotype with characterization of functional and biological proper-ties of the mutant channel. Our work will build upon existing knowledge of mutations within this region of CFTR and, importantly,inform approaches for clinical management. Elevated sweat chloride and reduced chloride secretion in HBEs may be due to al-ternative non-CFTR factors, which require further investigation.
Cancer is a complex disease where resistance to therapies and relapses often pose a serious clinical challenge. The scenario is even more complicated when the cancer type itself is heterogeneous in nature, e.g., lymphoma, a cancer of the lymphocytes which constitutes more than 70 different subtypes. Indeed, the treatment options continue to expand in lymphomas. Herein, we provide insights into lymphoma-specific clinical trials based on cytokine-induced killer (CIK) cell therapy and other pre-clinical lymphoma models where CIK cells have been used along with other synergetic tumor-targeting immune modules to improve their therapeutic potential. From a broader perspective, we will highlight that CIK cell therapy has potential, and in this rapidly evolving landscape of cancer therapies its optimization (as a personalized therapeutic approach) will be beneficial in lymphomas.
Introduction: Matrix metalloproteinases (MMPs) are important in tissue remodelling. Here we investigate the role of collagenase-3 (MMP-13) in antibody-induced arthritis.
Methods: For this study we employed the K/BxN serum-induced arthritis model. Arthritis was induced in C57BL/6 wild type (WT) and MMP-13-deficient (MMP-13–/–) mice by intraperitoneal injection of 200 μl of K/BxN serum. Arthritis was assessed by measuring the ankle swelling. During the course of the experiments, mice were sacrificed every second day for histological examination of the ankle joints. Ankle sections were evaluated histologically for infiltration of inflammatory cells, pannus tissue formation and bone/cartilage destruction. Semi-quantitative PCR was used to determine MMP-13 expression levels in ankle joints of untreated and K/BxN serum-injected mice.
Results: This study shows that MMP-13 is a regulator of inflammation. We observed increased expression of MMP-13 in ankle joints of WT mice during K/BxN serum-induced arthritis and both K/BxN serum-treated WT and MMP-13–/– mice developed progressive arthritis with a similar onset. However, MMP-13–/– mice showed significantly reduced disease over the whole arthritic period. Ankle joints of WT mice showed severe joint destruction with extensive inflammation and erosion of cartilage and bone. In contrast, MMP-13–/– mice displayed significantly decreased severity of arthritis (50% to 60%) as analyzed by clinical and histological scoring methods.
Conclusions: MMP-13 deficiency acts to suppress the local inflammatory responses. Therefore, MMP-13 has a role in the pathogenesis of arthritis, suggesting MMP-13 is a potential therapeutic target.
Comparación de perfiles de ansiedad matemática entre estudiantes mexicanos y estudiantes alemanes
(2017)
Se determinan los perfiles de ansiedad matemática de estudiantes mexicanos y estudiantes alemanes por medio de la aplicación de un cuestionario desarrollado ex profeso. La ansiedad matemática se define en términos de tres descriptores: creencias, actitudes y emociones. Los autores definen un Índice de Ansiedad Matemática, al aplicarlo encuentran que los estudiantes alemanes presentan un valor mayor de dicho Índice, lo que significa que tienen una mayor nivel de ansiedad matemática. Las diferencias en los valores del Índice de Ansiedad Matemática se interpretan en términos de diferencias culturales. La interpretación parece ser consistente con las diferencias culturales y se ajusta a los resultados obtenidos.
Comparative study of 3D object detection frameworks based on LiDAR data and sensor fusion techniques
(2022)
Estimating and understanding the surroundings of the vehicle precisely forms the basic and crucial step for the autonomous vehicle. The perception system plays a significant role in providing an accurate interpretation of a vehicle's environment in real-time. Generally, the perception system involves various subsystems such as localization, obstacle (static and dynamic) detection, and avoidance, mapping systems, and others. For perceiving the environment, these vehicles will be equipped with various exteroceptive (both passive and active) sensors in particular cameras, Radars, LiDARs, and others. These systems are equipped with deep learning techniques that transform the huge amount of data from the sensors into semantic information on which the object detection and localization tasks are performed. For numerous driving tasks, to provide accurate results, the location and depth information of a particular object is necessary. 3D object detection methods, by utilizing the additional pose data from the sensors such as LiDARs, stereo cameras, provides information on the size and location of the object. Based on recent research, 3D object detection frameworks performing object detection and localization on LiDAR data and sensor fusion techniques show significant improvement in their performance. In this work, a comparative study of the effect of using LiDAR data for object detection frameworks and the performance improvement seen by using sensor fusion techniques are performed. Along with discussing various state-of-the-art methods in both the cases, performing experimental analysis, and providing future research directions.
Miscanthus crops possess very attractive properties such as high photosynthesis yield and carbon fixation rate. Because of these properties, it is currently considered for use in second-generation biorefineries. Here we analyze the differences in chemical composition between M. x giganteus, a commonly studied Miscanthus genotype, and M. nagara, which is relatively understudied but has useful properties such as increased frost resistance and higher stem stability. Samples of M. x giganteus (Gig35) and M. nagara (NagG10) have been separated by plant portion (leaves and stems) in order to isolate the corresponding lignins. The organosolv process was used for biomass pulping (80% ethanol solution, 170 °C, 15 bar). Biomass composition and lignin structure analysis were performed using composition analysis, Fourier-transform infrared (FTIR), ultraviolet-visible (UV-Vis) and nuclear magnetic resonance (NMR) spectroscopy, thermogravimetric analysis (TGA), size exclusion chromatography (SEC) and pyrolysis gas-chromatography/mass spectrometry (Py-GC/MS) to determine the 3D structure of the isolated lignins, monolignol ratio and most abundant linkages depending on genotype and harvesting season. SEC data showed significant differences in the molecular weight and polydispersity indices for stem versus leaf-derived lignins. Py-GC/MS and hetero-nuclear single quantum correlation (HSQC) NMR revealed different monolignol compositions for the two genotypes (Gig35, NagG10). The monolignol ratio is slightly influenced by the time of harvest: stem-derived lignins of M. nagara showed increasing H and decreasing G unit content over the studied harvesting period (December–April).
Composite nanoparticles (NPs) consisting of lignin and different polysaccharide (PS) derivatives were prepared. In this synergistic approach, the PS derivative acts as biocompatible matrix that forms spherical NPs while lignin is a functional compound with therapeutic potential (e.g., antioxidative, antimicrobial, antiviral). Organosolv lignin and three different PS derivatives (cellulose acetate/CA, cellulose acetate phthalate/CAPh, xylan phenyl carbonate/XPC) were used in this study. Nanocomposites with particle sizes in the range of about 200–550 nm containing both types of biopolymers are accessible by dialysis of organic PS/lignin solutions against water. In particular, XPC and CAPh, which both contain aromatic substituents, were found to be suitable for incorporation of lignin within the PS nanomatrix. The present work paves the way for future studies in which the pharmaceutical potential and biocompatibility of composite NPs of lignin and PS derivatives with tailored properties are investigated.
Salts and proteins comprise two of the basic molecular components of biological materials. Kosmotropic/chaotropic co-solvation and matching ion water affinities explain basic ionic effects on protein aggregation observed in simple solutions. However, it is unclear how these theories apply to proteins in complex biological environments and what the underlying ionic binding patterns are. Using the positive ion Ca2+ and the negatively charged membrane protein SNAP25, we studied ion effects on protein oligomerization in solution, in native membranes and in molecular dynamics (MD) simulations. We find that concentration-dependent ion-induced protein oligomerization is a fundamental chemico-physical principle applying not only to soluble but also to membrane-anchored proteins in their native environment. Oligomerization is driven by the interaction of Ca2+ ions with the carboxylate groups of aspartate and glutamate. From low up to middle concentrations, salt bridges between Ca2+ ions and two or more protein residues lead to increasingly larger oligomers, while at high concentrations oligomers disperse due to overcharging effects. The insights provide a conceptual framework at the interface of physics, chemistry and biology to explain binding of ions to charged protein surfaces on an atomistic scale, as occurring during protein solubilisation, aggregation and oligomerization both in simple solutions and membrane systems.
Rosenbrock–Wanner methods for systems of stiff ordinary differential equations are well known since the seventies. They have been continuously developed and are efficient for differential-algebraic equations of index-1, as well. Their disadvantage that the Jacobian matrix has to be updated in every time step becomes more and more obsolete when automatic differentiation is used. Especially the family of Rodas methods has proven to be a standard in the Julia package DifferentialEquations. However, the fifth-order Rodas5 method undergoes order reduction for certain problem classes. Therefore, the goal of this paper is to compute a new set of coefficients for Rodas5 such that this order reduction is reduced. The procedure is similar to the derivation of the methods Rodas4P and Rodas4P2. In addition, it is possible to provide new dense output formulas for Rodas5 and the new method Rodas5P. Numerical tests show that for higher accuracy requirements Rodas5P always belongs to the best methods within the Rodas family.
The identification of energetic materials in containments is an important challenge for analytical methods in the field of safety and security. Opening a package without knowledge of its contents and the resulting hazards is highly involved with risks and should be avoided whenever possible. Therefore, preferable methods work non-destructive with minimal interaction and are capable of identifying target substances in a containment quickly and reliably. Most spectroscopic methods find their limits, if the target substance is shielded by a covering material. To solve this problem, a combined laser drilling method with subsequent identification of the target substance by means of Raman spectroscopic measurements through microscopic bore holes of the covering material is presented. A pulsed laser beam is used for both the drilling process and as an excitation source for Raman measurements in the same optical setup. Results show the ability of this new method to gain high-quality spectra even when performed through microscopic small bore channels. With the laser parameters chosen right, the method can even be performed on highly sensitive explosives like triacetone triperoxide (TATP). Another advantageous effect arises in an observed reduction in unwanted fluorescence signal in the spectral data, resulting from the confocal-like measurement setup with the bore hole acting as aperture.
Contextual information is widely considered for NLP and knowledge discovery in life sciences since it highly influences the exact meaning of natural language. The scientific challenge is not only to extract such context data, but also to store this data for further query and discovery approaches. Classical approaches use RDF triple stores, which have serious limitations. Here, we propose a multiple step knowledge graph approach using labeled property graphs based on polyglot persistence systems to utilize context data for context mining, graph queries, knowledge discovery and extraction. We introduce the graph-theoretic foundation for a general context concept within semantic networks and show a proof of concept based on biomedical literature and text mining. Our test system contains a knowledge graph derived from the entirety of PubMed and SCAIView data and is enriched with text mining data and domain-specific language data using Biological Expression Language. Here, context is a more general concept than annotations. This dense graph has more than 71M nodes and 850M relationships. We discuss the impact of this novel approach with 27 real-world use cases represented by graph queries. Storing and querying a giant knowledge graph as a labeled property graph is still a technological challenge. Here, we demonstrate how our data model is able to support the understanding and interpretation of biomedical data. We present several real-world use cases that utilize our massive, generated knowledge graph derived from PubMed data and enriched with additional contextual data. Finally, we show a working example in context of biologically relevant information using SCAIView.
Novel methods for contingency analysis of gas transport networks are presented. They are motivated by the transition of our energy system where hydrogen plays a growing role. The novel methods are based on a specific method for topological reduction and so-called supernodes. Stationary Euler equations with advanced compressor thermodynamics and a gas law allowing for gas compositions with up to 100% hydrogen are used. Several measures and plots support an intuitive comparison and analysis of the results. In particular, it is shown that the newly developed methods can estimate locations and magnitudes of additional capacities (injection, buffering, storage etc.) with a reasonable performance for networks of relevant composition and size.
Purpose – The aim of the study is to investigate the implementation of corporate sustainability (CS) in the German real estate sector.
Design/methodology/approach – The authors begin by outlining the framework set by the European Union and the German Federal Government for companies wanting to be classified as sustainable. After this, the relevance of sustainability for German real estate companies is discussed. Their empirical section contains an international comparison. Finally, they present an analysis checking the implementation of CS for the main 135 German real estate companies.
Findings – The present analysis shows that German real estate companies compare well with their international counterparts, in 2012 representing 15 per cent of all real estate firms reporting on the basis of the Global Reporting Initiative. However, of the 135 companies in Germany surveyed, only a small proportion classify themselves as CS and CSR (corporate social responsibility) enterprises. This number could be rapidly increased by better documentation of companies’ commitment to sustainability.
Practical implications – The study’s importance lies in the overview it provides of CS activities in the German real estate industry. In addition, it provides hints on how companies can improve their documentation to classify as CSR enterprises. Although the analysis concentrates on Germany, the results are also relevant for companies in other European countries.