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We analyze short-term effects of free hospitalization insurance for the poorest quintile of the population in the province of Khyber Pakhtunkhwa, Pakistan. First, we exploit that eligibility is based on an exogenous poverty score threshold and apply a regression discontinuity design. Second, we exploit imperfect rollout and compare insured and uninsured households using propensity score matching. With both methods we fail to detect significant effects on the incidence of hospitalization. Whereas the program did not meaningfully increase the quantity of health care consumed, insured households more often choose private hospitals, indicating a shift towards higher perceived quality of care.
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.
Despite the increasing interest in single family offices (SFOs) as an investment owned by an entrepreneurial family, research on SFOs is still in its infancy. In particular, little is known about the capital structures of SFOs or the roots of SFO heterogeneity regarding financial decisions. By drawing on a hand-collected sample of 104 SFOs and private equity (PE) firms, we compare the financing choices of these two investor types in the context of direct entrepreneurial investments (DEIs). Our data thereby provide empirical evidence that SFOs are less likely to raise debt than PE firms, suggesting that SFOs follow pecking-order theory. Regarding the heterogeneity of the financial decisions of SFOs, our data indicate that the relationship between SFOs and debt financing is reinforced by the idiosyncrasies of entrepreneurial families, such as higher levels of owner management and a higher firm age. Surprisingly, our data do not support a moderating effect for the emphasis placed on socioemotional wealth (SEW).
A main factor hampering life in space is represented by high atomic number nuclei and energy (HZE) ions that constitute about 1% of the galactic cosmic rays. In the frame of the “STARLIFE” project, we accessed the Heavy Ion Medical Accelerator (HIMAC) facility of the National Institute of Radiological Sciences (NIRS) in Chiba, Japan. By means of this facility, the extremophilic species Haloterrigena hispanica and Parageobacillus thermantarcticus were irradiated with high LET ions (i.e., Fe, Ar, and He ions) at doses corresponding to long permanence in the space environment. The survivability of HZE-treated cells depended upon either the storage time and the hydration state during irradiation; indeed, dry samples were shown to be more resistant than hydrated ones. With particular regard to spores of the species P. thermantarcticus, they were the most resistant to irradiation in a water medium: an analysis of the changes in their biochemical fingerprinting during irradiation showed that, below the survivability threshold, the spores undergo to a germination-like process, while for higher doses, inactivation takes place as a consequence of the concomitant release of the core’s content and a loss of integrity of the main cellular components. Overall, the results reported here suggest that the selected extremophilic microorganisms could serve as biological model for space simulation and/or real space condition exposure, since they showed good resistance to ionizing radiation exposure and were able to resume cellular growth after long-term storage.
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.
Der Faktor Vernunft
(2022)
Collaboration among multiple users on large screens leads to complicated behavior patterns and group dynamics. To gain a deeper understanding of collaboration on vertical, large, high-resolution screens, this dissertation builds on previous research and gains novel insights through new observational studies. Among other things, the collected results reveal new patterns of collaborative coupling, suggest that territorial behavior is less critical than shown in previous research, and demonstrate that workspace awareness can also negatively affect the effectiveness of individual users.
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.
Cathepsin K (CatK) is a target for the treatment of osteoporosis, arthritis, and bone metastasis. Peptidomimetics with a cyanohydrazide warhead represent a new class of highly potent CatK inhibitors; however, their binding mechanism is unknown. We investigated two model cyanohydrazide inhibitors with differently positioned warheads: an azadipeptide nitrile Gü1303 and a 3-cyano-3-aza-β-amino acid Gü2602. Crystal structures of their covalent complexes were determined with mature CatK as well as a zymogen-like activation intermediate of CatK. Binding mode analysis, together with quantum chemical calculations, revealed that the extraordinary picomolar potency of Gü2602 is entropically favoured by its conformational flexibility at the nonprimed-primed subsites boundary. Furthermore, we demonstrated by live cell imaging that cyanohydrazides effectively target mature CatK in osteosarcoma cells. Cyanohydrazides also suppressed the maturation of CatK by inhibiting the autoactivation of the CatK zymogen. Our results provide structural insights for the rational design of cyanohydrazide inhibitors of CatK as potential drugs.
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.
Therapeutic Treatments for Osteoporosis-Which Combination of Pills Is the Best among the Bad?
(2022)
Osteoporosis is a chronical, systemic skeletal disorder characterized by an increase in bone resorption, which leads to reduced bone density. The reduction in bone mineral density and therefore low bone mass results in an increased risk of fractures. Osteoporosis is caused by an imbalance in the normally strictly regulated bone homeostasis. This imbalance is caused by overactive bone-resorbing osteoclasts, while bone-synthesizing osteoblasts do not compensate for this. In this review, the mechanism is presented, underlined by in vitro and animal models to investigate this imbalance as well as the current status of clinical trials. Furthermore, new therapeutic strategies for osteoporosis are presented, such as anabolic treatments and catabolic treatments and treatments using biomaterials and biomolecules. Another focus is on new combination therapies with multiple drugs which are currently considered more beneficial for the treatment of osteoporosis than monotherapies. Taken together, this review starts with an overview and ends with the newest approaches for osteoporosis therapies and a future perspective not presented so far.
Background: Since presenteeism is related to numerous negative health and work-related effects, measures are required to reduce it. There are initial indications that how an organization deals with health has a decisive influence on employees’ presenteeism behavior.
Aims: The concept of health-promoting collaboration was developed on the basis of these indications. As an extension of healthy leadership it includes not only the leader but also co-workers. In modern forms of collaboration, leaders cannot be assigned sole responsibility for employees’ health, since the leader is often hardly visible (digital leadership) or there is no longer a clear leader (shared leadership). The study examines the concept of health-promoting collaboration in relation to presenteeism. Relationships between health-promoting collaboration, well-being and work ability are also in focus, regarding presenteeism as a mediator.
Methods: The data comprise the findings of a quantitative survey of 308 employees at a German university of applied sciences. Correlation and mediator analyses were conducted.
Results: The results show a significant negative relationship between health-promoting collaboration and presenteeism. Significant positive relationships were found between health-promoting collaboration and both well-being and work ability. Presenteeism was identified as a mediator of these relationships.
Conclusion: The relevance of health-promoting collaboration in reducing presenteeism was demonstrated and various starting points for practice were proposed. Future studies should investigate further this newly developed concept in relation to presenteeism.
It is challenging to provide users with a haptic weight sensation of virtual objects in VR since current consumer VR controllers and software-based approaches such as pseudo-haptics cannot render appropriate haptic stimuli. To overcome these limitations, we developed a haptic VR controller named Triggermuscle that adjusts its trigger resistance according to the weight of a virtual object. Therefore, users need to adapt their index finger force to grab objects of different virtual weights. Dynamic and continuous adjustment is enabled by a spring mechanism inside the casing of an HTC Vive controller. In two user studies, we explored the effect on weight perception and found large differences between participants for sensing change in trigger resistance and thus for discriminating virtual weights. The variations were easily distinguished and associated with weight by some participants while others did not notice them at all. We discuss possible limitations, confounding factors, how to overcome them in future research and the pros and cons of this novel technology.
Technical aspects are brought into focus thinking of inclusion opportunities and exclusion risks in digital learning scenarios. However, focussing on technical limitations is not sufficient. This contribution describes another important field of inclusion, namely psychological personality traits. In a longitudinal study at the Hochschule Bonn-Rhein-Sieg (H-BRS), University of Applied Sciences, we accompanied a civil law lecture of a bachelor's degree programme, which had been digitalized because of COVID-19, with empirical Scholarship of Teaching and Learning methods for two semesters. N=55 students from the first measured semester and N=35 from the second one rated different digital teaching methods used in the developed digital learning scenario. Their personality traits according to the five-factor model were measured by using a validated psychometric short-scale (BFI-10). Moderate to large empirical effects of the students' personality traits on the assessments of different digital teaching methods, used in the digital learning scenario, could be observed. Neuroticism values influences the perceptions of the course difficulty and the preference for using an instant messenger as a central communication platform, where students can interact with fellows and lecturers in a way the students are used to in their daily life. High conscientiousness predicts a more regular execution of the weekly tasks given throughout the semester, while higher values in extraversion are associated with a preference for synchronous video conference sessions and active webcams. Higher agreeableness is associated with rating the learning atmosphere as more constructive while low values are associated with perceiving more negative consequences due to the reduced contact to fellows based on COVID-19 restrictions. Correlations between the dimension openness and any ratings of digital teaching methods could not be observed. With this insight into our students' personality traits, we were able to match the digital teaching methods used in our digital learning scenario to the psychological needs of our students, which resulted in a higher inclusion level and a reduction of exclusion risks.
Diese etablierte Formelsammlung enthält und erklärt mathematische Formeln innerhalb ökonomischer Zusammenhänge, wie sie in den Wirtschaftswissenschaften und in der wirtschaftswissenschaftlichen Praxis unbedingt notwendig sind. Das Verständnis der Formeln und deren praktische Anwendung werden durch nützliche Hilfen und erklärliche Beispiele sinnvoll unterstützt, so dass der Kontext wirtschaftsmathematischer Formeln klar und verständlich dargestellt wird. Diese Formelsammlung ist ein unverzichtbares Tool für Studierende der Wirtschaftswissenschaften, aber auch ein nützliches Nachschlagewerk für Verantwortliche aus Wirtschaft, Politik und Lehre. Die Inhalte wurden für die 4. Auflage teilweise überarbeitet und ergänzt.
MOTIVATION
The majority of biomedical knowledge is stored in structured databases or as unstructured text in scientific publications. This vast amount of information has led to numerous machine learning-based biological applications using either text through natural language processing (NLP) or structured data through knowledge graph embedding models (KGEMs). However, representations based on a single modality are inherently limited.
RESULTS
To generate better representations of biological knowledge, we propose STonKGs, a Sophisticated Transformer trained on biomedical text and Knowledge Graphs (KGs). This multimodal Transformer uses combined input sequences of structured information from KGs and unstructured text data from biomedical literature to learn joint representations in a shared embedding space. First, we pre-trained STonKGs on a knowledge base assembled by the Integrated Network and Dynamical Reasoning Assembler (INDRA) consisting of millions of text-triple pairs extracted from biomedical literature by multiple NLP systems. Then, we benchmarked STonKGs against three baseline models trained on either one of the modalities (i.e., text or KG) across eight different classification tasks, each corresponding to a different biological application. Our results demonstrate that STonKGs outperforms both baselines, especially on the more challenging tasks with respect to the number of classes, improving upon the F1-score of the best baseline by up to 0.084 (i.e., from 0.881 to 0.965). Finally, our pre-trained model as well as the model architecture can be adapted to various other transfer learning applications.
AVAILABILITY
We make the source code and the Python package of STonKGs available at GitHub (https://github.com/stonkgs/stonkgs) and PyPI (https://pypi.org/project/stonkgs/). The pre-trained STonKGs models and the task-specific classification models are respectively available at https://huggingface.co/stonkgs/stonkgs-150k and https://zenodo.org/communities/stonkgs.
SUPPLEMENTARY INFORMATION
Supplementary data are available at Bioinformatics online.
Current research in augmented, virtual, and mixed reality (XR) reveals a lack of tool support for designing and, in particular, prototyping XR applications. While recent tools research is often motivated by studying the requirements of non-technical designers and end-user developers, the perspective of industry practitioners is less well understood. In an interview study with 17 practitioners from different industry sectors working on professional XR projects, we establish the design practices in industry, from early project stages to the final product. To better understand XR design challenges, we characterize the different methods and tools used for prototyping and describe the role and use of key prototypes in the different projects. We extract common elements of XR prototyping, elaborating on the tools and materials used for prototyping and establishing different views on the notion of fidelity. Finally, we highlight key issues for future XR tools research.
Vor dem Hintergrund der Covid-19-Pandemie hat sich das Home-Office in Deutschland seit dem Jahr 2020 weit verbreitet und wird seitdem bei vielen Arbeitgebern als neue Arbeitsmethode genutzt. Der Einsatz von Home-Office kann verschiedene positive als auch negative Effekte auf die Beschäftigten und den Arbeitgeber sowie die Gesellschaft allgemein haben. Damit von möglichst vielen positiven Effekten profitiert werden kann, ist ein gutes Home-Office Konzept erforderlich. Welche Anforderungen an ein solches Konzept bestehen und welche Voraussetzungen grundlegend mit der Nutzung von Home-Office verbunden sind, wird in dem Beitrag aufgezeigt. Dabei werden von technischen bis hin zu sozialen Aspekten Anforderungen verschiedener Arten berücksichtigt, welche durch eine durch den Autor durchgeführte Studie gebildet worden sind. Im Fokus dieses Beitrages sollen die kritischen Erfolgsfaktoren für das ideale Arbeiten im Home-Office stehen, also die Anforderungen, welche ausschlaggebend für die erfolgreiche Umsetzung eines Home-Office Konzeptes sind und Einfluss auf die wahrgenommenen Effekte des Home-Office haben. Die im Beitrag aufgeführte Studie des Autors wurde im Rahmen der Abschlussarbeit von Herrn Jeske durchgeführt, auf welcher der Beitrag basiert.
Modern GPUs come with dedicated hardware to perform ray/triangle intersections and bounding volume hierarchy (BVH) traversal. While the primary use case for this hardware is photorealistic 3D computer graphics, with careful algorithm design scientists can also use this special-purpose hardware to accelerate general-purpose computations such as point containment queries. This article explains the principles behind these techniques and their application to vector field visualization of large simulation data using particle tracing.
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.
Education for Sustainable Development (ESD, SDG 4) and human well-being (SDG 3) are among the central subjects of the Sustainable Development Goals (SDGs). In this article, based on the Questionnaire for Eudaimonic Well-Being (QEWB), we investigate to what extent (a) there is a connection between EWB and practical commitment to the SDGs and whether (b) there is a deficit in EWB among young people in general. We also want to use the article to draw attention to the need for further research on the links between human well-being and commitment for sustainable development. A total of 114 students between the ages of 18 and 34, who are either engaged in (extra)curricular activities of sustainable development (28 students) or not (86 students), completed the QEWB. The students were interviewed twice: once regarding their current and their aspired EWB. Our results show that students who are actively engaged in activities for sustainable development report a higher EWB than non-active students. Furthermore, we show that students generally report deficits in EWB and wish for an improvement in their well-being. This especially applies to aspects of EWB related to self-discovery and the sense of meaning in life. Our study suggests that a practice-oriented ESD in particular can have a positive effect on the quality of life of young students and can support them in working on deficits in EWB.
Operating an ozone-evolving PEM electrolyser in tap water: A case study of water and ion transport
(2022)
While PEM water electrolysis could be a favourable technique for in situ sanitization with ozone, its application is mainly limited to the use of ultrapure water to achieve a sufficient long-time stability. As additional charge carriers influence the occurring transport phenomena, we investigated the impact of different feed water qualities on the performance of a PEM tap water electrolyser for ozone evolution. The permeation of water and the four most abundant cations (Na+, K+, Ca2+, Mg2+) is characterised during stand-by and powered operation at different charge densities to quantify underlying transport mechanisms. Water transport is shown to linearly increase with the applied current (95 ± 2 mmol A−1 h−1) and occurs decoupled from ion permeation. A limitation of ion permeation is given by the transfer of ions in water to the anode/PEM interface. The unstabilized operation of a PEM electrolyser in tap water leads to a pH gradient which promotes the formation of magnesium and calcium carbonates and hydroxides on the cathode surface. The introduction of a novel auxiliary cathode in the anolytic compartment has shown to suppress ion permeation by close to 20%.
Discrimination of Stressed and Non-Stressed Food-Related Bacteria Using Raman-Microspectroscopy
(2022)
As the identification of microorganisms becomes more significant in industry, so does the utilization of microspectroscopy and the development of effective chemometric models for data analysis and classification. Since only microorganisms cultivated under laboratory conditions can be identified, but they are exposed to a variety of stress factors, such as temperature differences, there is a demand for a method that can take these stress factors and the associated reactions of the bacteria into account. Therefore, bacterial stress reactions to lifetime conditions (regular treatment, 25 °C, HCl, 2-propanol, NaOH) and sampling conditions (cold sampling, desiccation, heat drying) were induced to explore the effects on Raman spectra in order to improve the chemometric models. As a result, in this study nine food-relevant bacteria were exposed to seven stress conditions in addition to routine cultivation as a control. Spectral alterations in lipids, polysaccharides, nucleic acids, and proteins were observed when compared to normal growth circumstances without stresses. Regardless of the involvement of several stress factors and storage times, a model for differentiating the analyzed microorganisms from genus down to strain level was developed. Classification of the independent training dataset at genus and species level for Escherichia coli and at strain level for the other food relevant microorganisms showed a classification rate of 97.6%.
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.
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).
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.
In (dynamic) adaptive mesh refinement (AMR) an input mesh is refined or coarsened to the need of the numerical application. This refinement happens with no respect to the originally meshed domain and is therefore limited to the geometrical accuracy of the original input mesh. We presented a novel approach to equip this input mesh with additional geometry information, to allow refinement and high-order cells based on the geometry of the original domain. We already showed a limited implementation of this algorithm. Now we evaluate this prototype with a numerical application and we prove its influence on the accuracy of certain numerical results. To be as practical as possible, we implement the ability to import meshes generated by Gmsh and equip them with the needed geometry information. Furthermore, we improve the mapping algorithm, which maps the geometry information of the boundary of a cell into the cell's volume. With these preliminary steps done, we use out new approach in a simulation of the advection of a concentration along the boundary of a sphere shell and past the boundary of a rotating cylinder. We evaluate the accuracy of our approach in comparison to the conventional refinement of cells to answer our research question: How does the performance and accuracy of the hexahedral curved domain AMR algorithm compare to linear AMR when solving the advection equation with the linear finite volume method? To answer this question, we show the influence of curved AMR on our simulation results and see, that it is even able to outperform far finer linear meshes in terms of accuracy. We also see that the current implementation of this approach is too slow for practical usage. We can therefore prove the benefits of curved AMR in certain, geometry-related application scenarios and show possible improvements to make it more feasible and practical in the future.
Aim of this study is to investigate the effects of user experience (UX) on shopping mall customers’ intention to use a social robot. Therefore, we used a Wizard of Oz approach that enabled data collection in situ. Quantitative data was obtained from a questionnaire completed by shopping mall customers who interacted with a social robot. Data was used in a regression analysis, where user experience factors served as predictors for robot use in retail. The regression model explains up to 23.2% of the variance in customers’ intention to use a social robot. In addition, we collected qualitative data on human-robot-interactions and used the data to complement the interpretation of statistical results. Our findings suggest that only hedonic qualities significantly contribute to the prediction of customers’ intention, that shopping mall customers are reluctant to grant pragmatic qualities to social robots, and that UX evaluation in HRI requires additional predictors.
We introduce canonical weight normalization for convolutional neural networks. Inspired by the canonical tensor decomposition, we express the weight tensors in so-called canonical networks as scaled sums of outer vector products. In particular, we train network weights in the decomposed form, where scale weights are optimized separately for each mode. Additionally, similarly to weight normalization, we include a global scaling parameter. We study the initialization of the canonical form by running the power method and by drawing randomly from Gaussian or uniform distributions. Our results indicate that we can replace the power method with cheaper initializations drawn from standard distributions. The canonical re-parametrization leads to competitive normalization performance on the MNIST, CIFAR10, and SVHN data sets. Moreover, the formulation simplifies network compression. Once training has converged, the canonical form allows convenient model-compression by truncating the parameter sums.
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.