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Background: Virtual reality combined with spherical treadmills is used across species for studying neural circuits underlying navigation.
New Method: We developed an optical flow-based method for tracking treadmil ball motion in real-time using a single high-resolution camera.
Results: Tracking accuracy and timing were determined using calibration data. Ball tracking was performed at 500 Hz and integrated with an open source game engine for virtual reality projection. The projection was updated at 120 Hz with a latency with respect to ball motion of 30 ± 8 ms.
Comparison: with Existing Method(s) Optical flow based tracking of treadmill motion is typically achieved using optical mice. The camera-based optical flow tracking system developed here is based on off-the-shelf components and offers control over the image acquisition and processing parameters. This results in flexibility with respect to tracking conditions – such as ball surface texture, lighting conditions, or ball size – as well as camera alignment and calibration.
Conclusions: A fast system for rotational ball motion tracking suitable for virtual reality animal behavior across different scales was developed and characterized.
The alternative use of travel time is one of the widely discussed benefits of driverless cars. We therefore conducted 14 co-design sessions to examine how people manage their time, to determine how they perceive the value of time in driverless cars and to derive design implications. Our findings suggest that driverless mobility will affect both people’s use of travel time as well as their time management in general. The participants repeatedly stated the desire of completing tasks while traveling to save time for activities that are normally neglected in their everyday life. Using travel time efficiently requires using car space efficiently, too. We found out that the design concept of tiny houses could serve as common design pattern to deal with the limited space within cars and support diverse needs.
Trust is the lubricant of the sharing economy, especially in peer-to-peer carsharing where you leave a valuable good to a stranger in the hope of getting it backunscathed. Central mechanisms for handling this information gap nowadays are ratings and reviews of other users. The rising of connected car technology opens new possibilities to increase trust by collecting and providing e.g. driving behavior data. At the same time, this means an intrusion into the privacy of the user. Therefore, in this work we explore technological approaches that allow building trust without violating the privacy of individuals. We evaluate to what extent blockchain technology and smart contracts are suitable technologies to meet these challengesby setting upa prototype implementation of a block-chain-based carsharing approach. In this context, we present our research approachand evaluate the prototype in terms of trust and privacy.
Humankind, it can be argued, lives beyond its means and often at the expense of future generations. This paper starkly demonstrates, with the aid of a mathematical model, the imperative for a sustainable existence. In the model, consumption of resources is represented as a closed system, just like our planet. Long-term survival is only possible if consumption is below the ability of the system to regenerate.
While universities are mandated to teach, research and do community outreach, studies reveal that typical university communities live in relative isolation where research is more basic than applied. This study focused on; 1) determining how WWE could be fostered through linkages between universities and external agencies (communities, public and private sectors); 2) establishing how universities’ resources could be optimized to promote research and capacity building for WWE. The dimensions of WWE studied were; 1) Technical & Business Models; 2) Capacity building; and 3) institutional frameworks. Baseline studies were conducted in which qualitative and quantitative data was collected through questionnaires, interviews, documents analysis. Experimentations were carried out whereby Laboratory tests on Bio-methane Potential (BMP) for different biomass types was conducted. A complete chain of briquettes production and consumption has been successfully piloted at St Kizito High School in Namugongo, near Kampala. The 20,000 kg of briquettes produced (from municipal bio-waste) by students monthly are used to cook in three schools whose total population is 2000 students. With an average net profit of $ 3000, the project makes business sense even in absence of social-benefit accounting. Based on start-up capital of $ 12,250, the payback period on investment is 14.7 months. Bio-char (from carbonized waste) and briquette-ash are used as organic fertilizers and biocide in vegetable gardens at the schools. New pathways for municipal waste management based on stakeholder engagement and entrepreneurship are demonstrated; departing from the conventional waste collection and disposal models. This circular enterprise which enhances Food, Agriculture, Biodiversity, Land-use and Energy (FABLE) nexus will scale-up to incorporate non-student communities (youths/women), private waste-collectors and entrepreneurs. The application of entrepreneurial models for engaging students in green enterprises integrates technological, social, economic and governance dimensions for promoting municipal sanitation, environment; energy and food security.
Plant sap-feeding insects are widespread, having evolved to occupy diverse environmental niches despite exclusive feeding on an impoverished diet lacking in essential amino acids and vitamins. Success depends exquisitely on their symbiotic relationships with microbial symbionts housed within specialized eukaryotic bacteriocyte cells. Each bacteriocyte is packed with symbionts that are individually surrounded by a host-derived symbiosomal membrane representing the absolute host-symbiont interface. The symbiosomal membrane must be a dynamic and selectively permeable structure to enable bidirectional and differential movement of essential nutrients, metabolites, and biosynthetic intermediates, vital for growth and survival of host and symbiont. However, despite this crucial role, the molecular basis of membrane transport across the symbiosomal membrane remains unresolved in all bacteriocyte-containing insects. A transport protein was immuno-localized to the symbiosomal membrane separating the pea aphid Acyrthosiphon pisum from its intracellular symbiont Buchnera aphidicola. The transporter, A. pisum nonessential amino acid transporter 1, or ApNEAAT1 (gene: ACYPI008971), was characterized functionally following heterologous expression in Xenopus oocytes, and mediates both inward and outward transport of small dipolar amino acids (serine, proline, cysteine, alanine, glycine). Electroneutral ApNEAAT1 transport is driven by amino acid concentration gradients and is not coupled to transmembrane ion gradients. Previous metabolite profiling of hemolymph and bacteriocyte, alongside metabolic pathway analysis in host and symbiont, enable prediction of a physiological role for ApNEAAT1 in bidirectional host-symbiont amino acid transfer, supplying both host and symbiont with indispensable nutrients and biosynthetic precursors to facilitate metabolic complementarity.
For protection from inhaled pathogens many strategies have evolved in the airways such as mucociliary clearance and cough. We have previously shown that protective respiratory reflexes to locally released bacterial bitter taste substances are most probably initiated by tracheal brush cells (BC). Our single-cell RNA-seq analysis of murine BC revealed high expression levels of cholinergic and bitter taste signaling transcripts (Tas2r108, Gnat3, Trpm5). We directly demonstrate the secretion of acetylcholine (ACh) from BC upon stimulation with the Tas2R agonist denatonium. Inhibition of the taste transduction cascade abolished the increase in [Ca2+](i) in BC and subsequent ACh-release. ACh-release is regulated in an autocrine manner. While the muscarinic ACh-receptors M3R and M1R are activating, M2R is inhibitory. Paracrine effects of ACh released in response to denatonium included increased [Ca2+](i) in ciliated cells. Stimulation by denatonium or with Pseudomonas quinolone signaling molecules led to an increase in mucociliary clearance in explanted tracheae that was Trpm5- and M3R-mediated. We show that ACh-release from BC via the bitter taste cascade leads to immediate paracrine protective responses that can be boosted in an autocrine manner. This mechanism represents the initial step for the activation of innate immune responses against pathogens in the airways.
Towards self-explaining social robots. Verbal explanation strategies for a needs-based architecture
(2019)
In order to establish long-term relationships with users, social companion robots and their behaviors need to be comprehensible. Purely reactive behavior such as answering questions or following commands can be readily interpreted by users. However, the robot's proactive behaviors, included in order to increase liveliness and improve the user experience, often raise a need for explanation. In this paper, we provide a concept to produce accessible “why-explanations” for the goal-directed behavior an autonomous, lively robot might produce. To this end we present an architecture that provides reasons for behaviors in terms of comprehensible needs and strategies of the robot, and we propose a model for generating different kinds of explanations.
The paper presents the topological reduction method applied to gas transport networks, using contraction of series, parallel and tree-like subgraphs. The contraction operations are implemented for pipe elements, described by quadratic friction law. This allows significant reduction of the graphs and acceleration of solution procedure for stationary network problems. The algorithm has been tested on several realistic network examples. The possible extensions of the method to different friction laws and other elements are discussed.
Namibia’s hunting industry is increasingly threatened by animal rightists and opponent groups whose adversarial mindset is mostly based on emotion orientated information. The fatal consequences if closing hunting tourism in a country like Namibia are expounded in this study by critically investigating the input of well-regulated hunting tourism towards conservation in Namibia. Different factors have to be taken into consideration, regarding the country’s attributes that differ significantly from other countries and their methods to achieve successful conservation management strategies. By conducting an in-depth interview with Mr. Volker Grellmann and by obtaining secondary data from local authorities and organizations, the current research investigates how well-regulated hunting tourism in Namibia is an important part of biodiversity conservation. The results outline that hunting tourism is crucial for the value of wildlife and yields for wildlife to have a greater benefit than livestock and crop farming in Namibia. Likewise, the country takes care of their valuable natural recourse. As a result, natural habitats are induced, and subsequently a steeply growing number of wildlife was recorded over the last 50 years in Namibia. Among others hunting tourism favors the development of rural areas and yields incentives to fight poaching and the illegal trade of wild animal products.
The pyrin inflammasome has evolved as an innate immune sensor to detect bacterial toxin-induced Rho guanosine triphosphatase (Rho GTPase)-inactivation, a process that is similar to the "guard" mechanism in plants. Rho GTPases act as molecular switches to regulate a variety of signal transduction pathways including cytoskeletal organization. Pathogens can modulate Rho GTPase activity to suppress host immune responses such as phagocytosis. Pyrin is encoded by MEFV, the gene that is mutated in patients with familial Mediterranean fever (FMF). FMF is the prototypic autoinflammatory disease characterized by recurring short episodes of systemic inflammation and is a common disorder in many populations in the Mediterranean basin. Pyrin specifically senses modifications in the activity of the small GTPase RhoA, which binds to many effector proteins including the serine/threonine-protein kinases PKN1 and PKN2 and actin-binding proteins. RhoA activation leads to PKN-mediated phosphorylation-dependent pyrin inhibition. Conversely, pathogen virulence factors downregulate RhoA activity in a variety of ways, and these changes are detected by the pyrin inflammasome irrespective of the type of modifications. MEFV pathogenic variants favor the active state of pyrin and elicit proinflammatory cytokine release and pyroptosis. They can be inherited either as a dominant or recessive trait depending on the variant's location and effect on the protein function. Mutations in the C-terminal B30.2 domain are usually considered recessive, although heterozygotes may manifest a biochemical or even a clinical phenotype. These variants are hypomorphic in regard to their effect on intramolecular interactions, but ultimately accentuate pyrin activity. Heterozygous mutations in other domains of pyrin affect residues critical for inhibition or protein oligomerization, and lead to constitutively active inflammasome. In healthy carriers of FMF mutations who have the subclinical inflammatory phenotype, the increased activity of pyrin might have been protective against endemic infections over human history. This finding is supported by the observation of high carrier frequencies of FMF-mutations in multiple populations. The pyrin inflammasome also plays a role in mediating inflammation in other autoinflammatory diseases linked to dysregulation in the actin polymerization pathway. Therefore, the assembly of the pyrin inflammasome is initiated in response to fluctuations in cytoplasmic homeostasis and perturbations in cytoskeletal dynamics.
In an effort to assist researchers in choosing basis sets for quantum mechanical modeling of molecules (i.e. balancing calculation cost versus desired accuracy), we present a systematic study on the accuracy of computed conformational relative energies and their geometries in comparison to MP2/CBS and MP2/AV5Z data, respectively. In order to do so, we introduce a new nomenclature to unambiguously indicate how a CBS extrapolation was computed. Nineteen minima and transition states of buta-1,3-diene, propan-2-ol and the water dimer were optimized using forty-five different basis sets. Specifically, this includes one Pople (i.e. 6-31G(d)), eight Dunning (i.e. VXZ and AVXZ, X=2-5), twenty-five Jensen (i.e. pc-n, pcseg-n, aug-pcseg-n, pcSseg-n and aug-pcSseg-n, n=0-4) and nine Karlsruhe (e.g. def2-SV(P), def2-QZVPPD) basis sets. The molecules were chosen to represent both common and electronically diverse molecular systems. In comparison to MP2/CBS relative energies computed using the largest Jensen basis sets (i.e. n=2,3,4), the use of smaller sizes (n=0,1,2 and n=1,2,3) provides results that are within 0.11--0.24 and 0.09-0.16 kcal/mol. To practically guide researchers in their basis set choice, an equation is introduced that ranks basis sets based on a user-defined balance between their accuracy and calculation cost. Furthermore, we explain why the aug-pcseg-2, def2-TZVPPD and def2-TZVP basis sets are very suitable choices to balance speed and accuracy.
The Learning Culture Survey (LCS) is a questionnaire-based research, investigating students’ perceptions of and expectations towards Higher Education (HE). The aim of this survey is to improve our understanding about the sources of cultural conflicts in educational scenarios. This understanding, shell help us to predict potential conflict situations and develop supportive measures.
After three years of development, the LCS was initialized in 2010 in South Korea and Germany. During the following years, the investigations were extended to further countries. The results, on the one hand, provided insights about the cultural context of HE in general and on the other hand, about specific (national / regional) characteristics of learners in HE. Most issues targeted with the questionnaire were directly linked to value systems. Thus, we expected from the beginning that the collected data would keep valid over longer periods of time. However, we had no evidence regarding the actual persistence of learning culture. For a study, designed to being implemented on a global scope and providing input for further applications, persistence is a basic condition to justify related investigations.
To answer the question on persistence, we repeated the LCS in our university every four years, between 2010 to 2018/19. Besides a small number of slight changes, explainable out of their situational context, the overall results kept consistent over the investigated years. In this paper, after an introduction of the LCS’ concept, setting and its general results from the past years, we present the insights from our most recently finalized longitudinal study on learning culture.
The need for innovation around the control functions of inverters is great. PV inverters were initially expected to be passive followers of the grid and to disconnect as soon as abnormal conditions happened. Since future power systems will be dominated by generation and storage resources interfaced through inverters these converters must move from following to forming and sustaining the grid. As “digital natives” PV inverters can also play an important role in the digitalisation of distribution networks. In this short review we identified a large potential to make the PV inverter the smart local hub in a distributed energy system. At the micro level, costs and coordination can be improved with bidirectional inverters between the AC grid and PV production, stationary storage, car chargers and DC loads. At the macro level the distributed nature of PV generation means that the same devices will support both to the local distribution network and to the global stability of the grid. Much success has been obtained in the former. The later remains a challenge, in particular in terms of scaling. Yet there is some urgency in researching and demonstrating such solutions. And while digitalisation offers promise in all control aspects it also raises significant cybersecurity concerns.
Small, Medium and Micro Enterprises (SMMEs) are widely recognised as playing a pivotal role in economic development and job creation. This is particularly so in Africa, where SMMEs are responsible for 80% of all formal jobs. While this is recognised by various African continental and national developments plans, the nefarious practice of late payment, by especially governments, not only stunt the growth of SMMEs, but often-time leads to business failure. This article investigates the impact of late payment, with a specific focus on South Africa and touches on international good practice that may be employed to address this phenomenon.
Tell Your Robot What To Do: Evaluation of Natural Language Models for Robot Command Processing
(2019)
The use of natural language to indicate robot tasks is a convenient way to command robots. As a result, several models and approaches capable of understanding robot commands have been developed, which however complicates the choice of a suitable model for a given scenario. In this work, we present a comparative analysis and benchmarking of four natural language understanding models - Mbot, Rasa, LU4R, and ECG. We particularly evaluate the performance of the models to understand domestic service robot commands by recognizing the actions and any complementary information in them in three use cases: the RoboCup@Home General Purpose Service Robot (GPSR) category 1 contest, GPSR category 2, and hospital logistics in the context of the ROPOD project.
Large display environments are highly suitable for immersive analytics. They provide enough space for effective co-located collaboration and allow users to immerse themselves in the data. To provide the best setting - in terms of visualization and interaction - for the collaborative analysis of a real-world task, we have to understand the group dynamics during the work on large displays. Among other things, we have to study, what effects different task conditions will have on user behavior.
In this paper, we investigated the effects of task conditions on group behavior regarding collaborative coupling and territoriality during co-located collaboration on a wall-sized display. For that, we designed two tasks: a task that resembles the information foraging loop and a task that resembles the connecting facts activity. Both tasks represent essential sub-processes of the sensemaking process in visual analytics and cause distinct space/display usage conditions. The information foraging activity requires the user to work with individual data elements to look into details. Here, the users predominantly occupy only a small portion of the display. In contrast, the connecting facts activity requires the user to work with the entire information space. Therefore, the user has to overview the entire display.
We observed 12 groups for an average of two hours each and gathered qualitative data and quantitative data. During data analysis, we focused specifically on participants' collaborative coupling and territorial behavior.
We could detect that participants tended to subdivide the task to approach it, in their opinion, in a more effective way, in parallel. We describe the subdivision strategies for both task conditions. We also detected and described multiple user roles, as well as a new coupling style that does not fit in either category: loosely or tightly. Moreover, we could observe a territory type that has not been mentioned previously in research. In our opinion, this territory type can affect the collaboration process of groups with more than two collaborators negatively. Finally, we investigated critical display regions in terms of ergonomics. We could detect that users perceived some regions as less comfortable for long-time work.
Synthesis of Substituted Hydroxyapatite for Application in Bone Tissue Engineering and Drug Delivery
(2019)
Due to increased emissions of palladium nanoparticles in recent years, it is important to develop analytical techniques to characterize these particles. The synthesis of defined and stable particles plays a key role in this process, as there are not many materials commercially available yet which could act as reference materials. Polyvinylpyrrolidone- (PVP-) stabilized palladium nanoparticles were synthesized through the reduction of palladium chloride by tetraethylene glycol (TEG) in the presence of KOH. Four different methods were used for particle size analysis of the palladium nanoparticles. Palladium suspensions were analyzed by scanning electron microscopy (SEM), small angle X-ray scattering (SAXS), single-particle ICP-MS (SP-ICP-MS), and X-ray diffraction (XRD). Secondary particles between 30 nm and 130 nm were detected in great compliance with SAXS and SP-ICP-MS. SEM analysis showed that the small particulates tend to form agglomerates.
In the field of service robots, dealing with faults is crucial to promote user acceptance. In this context, this work focuses on some specific faults which arise from the interaction of a robot with its real world environment due to insufficient knowledge for action execution.
In our previous work [1], we have shown that such missing knowledge can be obtained through learning by experimentation. The combination of symbolic and geometric models allows us to represent action execution knowledge effectively. However we did not propose a suitable representation of the symbolic model.
In this work we investigate such symbolic representation and evaluate its learning capability. The experimental analysis is performed on four use cases using four different learning paradigms. As a result, the symbolic representation together with the most suitable learning paradigm are identified.
This article examines similarities and differences in the attitudes and social representations of destination managers towards implementing sustainable tourism between the mountain regions of the Alps and the Dinarides. Bearing in mind the transnational impacts (i.e., environmental, economic and social) of the tourism industry the research methodology adopted an international perspective by sending a questionnaire to tourism organizations in fourteen different countries in the Alps and the Dinarides. The research is interdisciplinary in nature, because it integrates knowledge from sustainability and management science with tourism geography and social psychology. The findings confirm that social representations of sustainable tourism differ significantly in the two mountain regions.
Background: To protect renewable packaging materials against autoxidation and decomposition when substituting harmful synthetic stabilizers with bioactive and bio-based compounds, extracts from Aesculus hippocastanum L. seeds were evaluated. The study objectives were to determine the antioxidant efficacy of bioactive compounds in horse chestnut seeds with regard to different seed fractions, improve their extraction, and to evaluate waste reuse. Methods: Different extraction techniques for field samples were evaluated and compared with extracts of industrial waste samples based on total phenolic content and total antioxidant capacity (2,2’-azino-bis(3-ethylbenzthiazoline-6-sulphonic acid) (ABTS)). The molecular weight distribution and absorbance in ultraviolet range (UV) of seed coat extracts were determined, and the possibility of extracts containing proanthocyanidins was examined. Results: Seed coat extracts show a remarkable antioxidant activity and a high UV absorbance. Passive extractions are efficient and much less laborious. Applying waste product seed coats leads to a reduced antioxidant activity, total phenolic content, and UV absorbance compared to the field sample counterparts. In contrast to peeled seed extracts, all seed coat extracts contain proanthocyanidins. Discussion: Seed coats are a potential source of bioactive compounds, particularly regarding sustainable production and waste reuse. With minimum effort, highly bioactive extracts with high potential as additives can be prepared.
The application of Raman and infrared (IR) microspectroscopy is leading to hyperspectral data containing complementary information concerning the molecular composition of a sample. The classification of hyperspectral data from the individual spectroscopic approaches is already state-of-the-art in several fields of research. However, more complex structured samples and difficult measuring conditions might affect the accuracy of classification results negatively and could make a successful classification of the sample components challenging. This contribution presents a comprehensive comparison in supervised pixel classification of hyperspectral microscopic images, proving that a combined approach of Raman and IR microspectroscopy has a high potential to improve classification rates by a meaningful extension of the feature space. It shows that the complementary information in spatially co-registered hyperspectral images of polymer samples can be accessed using different feature extraction methods and, once fused on the feature-level, is in general more accurately classifiable in a pattern recognition task than the corresponding classification results for data derived from the individual spectroscopic approaches.
This study sought to examine the relationship between the components of SMEs social capital and firm performance. Using the social capital theory and the resource-based view as the theoretical foundations and census, 1,532 SMEs were selected in the Accra Metropolis for the study. Empirical results from 717 SMEs, utilising the hierarchical linear regression model, revealed that owner/manger’s network relationships are beneficial to the firm depending on when the relationships are closed or opened. Moreover, the study found that social capital has a significant impact on the sales and market performance of small and medium-sized enterprises. The results also brought to the fore the fact that most social networks of SME entrepreneurs are family, friends and relatives, which most times can only be used for expressive purposes and not for instrumental gain. The practical implications of the results are also discussed.
Bond graph software can simulate bond graph models without the user needing to manually derive equations. This offers the power to model larger and more complex systems than in the past. Multibond graphs (those with vector bonds) offer a compact model which further eases handling multibody systems. Although multibond graphs can be simulated successfully, the use of vector bonds can present difficulties. In addition, most qualitative, bond graph–based exploitation relies on the use of scalar bonds. This article discusses the main methods for simulating bond graphs of multibody systems, using a graphical software platform. The transformation between models with vector and scalar bonds is presented. The methods are then compared with respect to both time and accuracy, through simulation of two benchmark models. This article is a tutorial on the existing methods for simulating three-dimensional rigid and holonomic multibody systems using bond graphs and discusses the difficulties encountered. It then proposes and adapts methods for simulating this type of system directly from its bond graph within a software package. The value of this study is in giving practical guidance to modellers, so that they can implement the adapted method in software.
This work introduces a semi-Lagrangian lattice Boltzmann (SLLBM) solver for compressible flows (with or without discontinuities). It makes use of a cell-wise representation of the simulation domain and utilizes interpolation polynomials up to fourth order to conduct the streaming step. The SLLBM solver allows for an independent time step size due to the absence of a time integrator and for the use of unusual velocity sets, like a D2Q25, which is constructed by the roots of the fifth-order Hermite polynomial. The properties of the proposed model are shown in diverse example simulations of a Sod shock tube, a two-dimensional Riemann problem and a shock-vortex interaction. It is shown that the cell-based interpolation and the use of Gauss-Lobatto-Chebyshev support points allow for spatially high-order solutions and minimize the mass loss caused by the interpolation. Transformed grids in the shock-vortex interaction show the general applicability to non-uniform grids.
Treatment options for acute myeloid leukemia (AML) remain extremely limited and associated with significant toxicity. Nicotinamide phosphoribosyltransferase (NAMPT) is involved in the generation of NAD+ and a potential therapeutic target in AML. We evaluated the effect of KPT-9274, a p21-activated kinase 4/NAMPT inhibitor that possesses a unique NAMPT-binding profile based on in silico modeling compared with earlier compounds pursued against this target. KPT-9274 elicited loss of mitochondrial respiration and glycolysis and induced apoptosis in AML subtypes independent of mutations and genomic abnormalities. These actions occurred mainly through the depletion of NAD+, whereas genetic knockdown of p21-activated kinase 4 did not induce cytotoxicity in AML cell lines or influence the cytotoxic effect of KPT-9274. KPT-9274 exposure reduced colony formation, increased blast differentiation, and diminished the frequency of leukemia-initiating cells from primary AML samples; KPT-9274 was minimally cytotoxic toward normal hematopoietic or immune cells. In addition, KPT-9274 improved overall survival in vivo in 2 different mouse models of AML and reduced tumor development in a patient-derived xenograft model of AML. Overall, KPT-9274 exhibited broad preclinical activity across a variety of AML subtypes and warrants further investigation as a potential therapeutic agent for AML.
When developing robot functionalities, finite state machines are commonly used due to their straightforward semantics and simple implementation. State machines are also a natural implementation choice when designing robot experiments, as they generally lead to reproducible program execution. In practice, the implementation of state machines can lead to significant code repetition and may necessitate unnecessary code interaction when reparameterisation is required. In this paper, we present a small Python library that allows state machines to be specified, configured, and dynamically created using a minimal domain-specific language. We illustrate the use of the library in three different use cases - scenario definition in the context of the RoboCup@Home competition, experiment design in the context of the ROPOD project, as well as specification transfer between robots.
Emotion and gender recognition from facial features are important properties of human empathy. Robots should also have these capabilities. For this purpose we have designed special convolutional modules that allow a model to recognize emotions and gender with a considerable lower number of parameters, enabling real-time evaluation on a constrained platform. We report accuracies of 96% in the IMDB gender dataset and 66% in the FER-2013 emotion dataset, while requiring a computation time of less than 0.008 seconds on a Core i7 CPU. All our code, demos and pre-trained architectures have been released under an open-source license in our repository at https://github.com/oarriaga/face classification.
Quantifying Interference in WiLD Networks using Topography Data and Realistic Antenna Patterns
(2019)
Avoiding possible interference is a key aspect to maximize the performance in Wi-Fi based Long Distance networks. In this paper we quantify self-induced interference based on data derived from our testbed and match the findings against simulations. By enhancing current simulation models with two key elements we significantly reduce the deviation between testbed and simulation: the usage of detailed antenna patterns compared to the cone model and propagation modeling enhanced by license-free topography data. Based on the gathered data we discuss several possible optimization approaches such as physical separation of local radios, tuning the sensitivity of the transmitter and using centralized compared to distributed channel assignment algorithms. While our testbed is based on 5 GHz Wi-Fi, we briefly discuss the possible impact of our results to other frequency bands.
The aim of this study was to investigate whether beneficial vacation effects can be strengthened and prolonged with a smartphone-based intervention. In a four-week longitudinal study among 79 Finnish teachers, we investigated the development of recovery, well-being, and job performance before, during, and after a one-week vacation in three groups: non-users (n = 51), passive (n = 18) and active (n = 10) users. Participants were instructed to actively use a recovery app (called Holidaily) and complete five digital questionnaires. Most recovery experiences and well-being indicators increased during the vacation. Job performance and concentration capacity showed no significant time effects. Among active app users, creativity at work increased from baseline to after the vacation, whereas among non-users it decreased and among passive users it decreased a few days after the vacation but increased again one and a half weeks after the vacation. The fading of beneficial vacation effects on negative affect seems to have been slower among active app users. Only few participants used the app actively. Still, results suggest that a smartphone-based recovery intervention may support beneficial vacation effects.
Innovation has been touted to be the central catalyst of entrepreneurship. This view has dominated research in start-ups as well as small and medium enterprises. Therefore, the relationship between innovation and firm performance has been a subject of interest to many researchers and policy makers. Through a longitudinal approach, this study investigated the influence of product innovation on the performance of Haco Tiger Brands, a medium sized fast-moving consumer goods (FMCG) company in Kenya’s East Africa market. The study looked at the product innovation activities within the company for a period of 7 years for a total of 35 products across the five major brand categories of the company. Using a secondary data capture form, data on sales revenues for both the company and innovated products for the past 7 years was obtained. Data on the innovated products launch time and type of innovation was also obtained. Using time series and linear regression analysis, the results indicate that the total company sales revenues less innovation grew at a slower rate of 50% as compared to growth when product innovation sales revenues were included in the total company sales revenues accounting for a faster sales growth rate of 76%. The influence of product innovation on performance was statistically significant (p<0.05) accounting for 92.19% variation in performance. These findings provide irrefutable empirical basis that product innovations have significant revenue growth rates, hence the need for managers of medium sized companies to invest in research and development to sustain product innovation and spur growth. The results sit well within theory and other empirical studies with additional contribution to methodology. Based on the study limitations, further areas for research have been suggested.
Process-dependent thermo-mechanical viscoelastic properties and the corresponding morphology of HDPE extrusion blow molded (EBM) parts were investigated. Evaluation of bulk data showed that flow direction, draw ratio, and mold temperature influence the viscoelastic behavior significantly in certain temperature ranges. Flow induced orientations due to higher draw ratio and higher mold temperature lead to higher crystallinities. To determine the local viscoelastic properties, a new microindentation system was developed by merging indentation with dynamic mechanical analysis. The local process-structure-property relationship of EBM parts showed that the cross-sectional temperature distribution is clearly reflected by local crystallinities and local complex moduli. Additionally, a model to calculate three-dimensional anisotropic coefficients of thermal expansion as a function of the process dependent crystallinity was developed based on an elementary volume unit cell with stacked layers of amorphous phase and crystalline lamellae. Good agreement of the predicted thermal expansion coefficients with measured ones was found up to a temperature of 70 °C.
Surrogate models are used to reduce the burden of expensive-to-evaluate objective functions in optimization. By creating models which map genomes to objective values, these models can estimate the performance of unknown inputs, and so be used in place of expensive objective functions. Evolutionary techniques such as genetic programming or neuroevolution commonly alter the structure of the genome itself. A lack of consistency in the genotype is a fatal blow to data-driven modeling techniques: interpolation between points is impossible without a common input space. However, while the dimensionality of genotypes may differ across individuals, in many domains, such as controllers or classifiers, the dimensionality of the input and output remains constant. In this work we leverage this insight to embed differing neural networks into the same input space. To judge the difference between the behavior of two neural networks, we give them both the same input sequence, and examine the difference in output. This difference, the phenotypic distance, can then be used to situate these networks into a common input space, allowing us to produce surrogate models which can predict the performance of neural networks regardless of topology. In a robotic navigation task, we show that models trained using this phenotypic embedding perform as well or better as those trained on the weight values of a fixed topology neural network. We establish such phenotypic surrogate models as a promising and flexible approach which enables surrogate modeling even for representations that undergo structural changes.
Renewable energies play an increasingly important role for energy production in Europe. Unlike coal or gas powerplants, solar energy production is highly variable in space and time. This is due to the strong variability of cloudsand their influence on the surface solar irradiance. Especially in regions with large contribution from photovoltaicpower production, the intermittent energy feed-in to the power grid can be a risk for grid stability. Therefore goodforecasts of temporal and spatial variability of surface irradiance are necessary to be able to properly regulate thepower supply.
PosturePairsDB19
(2019)
Bone tissue engineering is an ever-changing, rapidly evolving, and highly interdisciplinary field of study, where scientists try to mimic natural bone structure as closely as possible in order to facilitate bone healing. New insights from cell biology, specifically from mesenchymal stem cell differentiation and signaling, lead to new approaches in bone regeneration. Novel scaffold and drug release materials based on polysaccharides gain increasing attention due to their wide availability and good biocompatibility to be used as hydrogels and/or hybrid components for drug release and tissue engineering. This article reviews the current state of the art, recent developments, and future perspectives in polysaccharide-based systems used for bone regeneration.
Incoming solar radiation is an important driver of our climate and weather. Several studies (see for instance Frank et al. 2018) have revealed discrepancies between ground-based irradiance measurements and the predictions of regional weather models. In the realm of electricity generation, accurate forecasts of solar photovoltaic (PV)energy yield are becoming indispensable for cost-effective grid operation: in Germany there are 1.6 million PVsystems installed, with a nominal power of 46 GW (Bundesverband Solarwirtschaft 2019). The proliferation of PV systems provides a unique opportunity to characterise global irradiance with unprecedented spatiotemporalresolution, which in turn will allow for highly resolved PV power forecasts.
The Peren-Clement index (PCI) is a methodology to analyze country-specific risk for businesses engaged in international trade and direct investment. This index, established in 1998, provides a guideline when deciding which foreign markets offer the possibility for additional business engagement and investment, and to what extent existing engagement or investment can be increased or should be reduced.
Computer graphics research strives to synthesize images of a high visual realism that are indistinguishable from real visual experiences. While modern image synthesis approaches enable to create digital images of astonishing complexity and beauty, processing resources remain a limiting factor. Here, rendering efficiency is a central challenge involving a trade-off between visual fidelity and interactivity. For that reason, there is still a fundamental difference between the perception of the physical world and computer-generated imagery. At the same time, advances in display technologies drive the development of novel display devices. The dynamic range, the pixel densities, and refresh rates are constantly increasing. Display systems enable a larger visual field to be addressed by covering a wider field-of-view, due to either their size or in the form of head-mounted devices. Currently, research prototypes are ranging from stereo and multi-view systems, head-mounted devices with adaptable lenses, up to retinal projection, and lightfield/holographic displays. Computer graphics has to keep step with, as driving these devices presents us with immense challenges, most of which are currently unsolved. Fortunately, the human visual system has certain limitations, which means that providing the highest possible visual quality is not always necessary. Visual input passes through the eye’s optics, is filtered, and is processed at higher level structures in the brain. Knowledge of these processes helps to design novel rendering approaches that allow the creation of images at a higher quality and within a reduced time-frame. This thesis presents the state-of-the-art research and models that exploit the limitations of perception in order to increase visual quality but also to reduce workload alike - a concept we call perception-driven rendering. This research results in several practical rendering approaches that allow some of the fundamental challenges of computer graphics to be tackled. By using different tracking hardware, display systems, and head-mounted devices, we show the potential of each of the presented systems. The capturing of specific processes of the human visual system can be improved by combining multiple measurements using machine learning techniques. Different sampling, filtering, and reconstruction techniques aid the visual quality of the synthesized images. An in-depth evaluation of the presented systems including benchmarks, comparative examination with image metrics as well as user studies and experiments demonstrated that the methods introduced are visually superior or on the same qualitative level as ground truth, whilst having a significantly reduced computational complexity.
Survival of patients with pediatric acute lymphoblastic leukemia (ALL) after allogeneic hematopoietic stem cell transplantation (allo-SCT) is mainly compromised by leukemia relapse, carrying dismal prognosis. As novel individualized therapeutic approaches are urgently needed, we performed whole-exome sequencing of leukemic blasts of 10 children with post–allo-SCT relapses with the aim of thoroughly characterizing the mutational landscape and identifying druggable mutations. We found that post–allo-SCT ALL relapses display highly diverse and mostly patient-individual genetic lesions. Moreover, mutational cluster analysis showed substantial clonal dynamics during leukemia progression from initial diagnosis to relapse after allo-SCT. Only very few alterations stayed constant over time. This dynamic clonality was exemplified by the detection of thiopurine resistance-mediating mutations in the nucleotidase NT5C2 in 3 patients’ first relapses, which disappeared in the post–allo-SCT relapses on relief of selective pressure of maintenance chemotherapy. Moreover, we identified TP53 mutations in 4 of 10 patients after allo-SCT, reflecting acquired chemoresistance associated with selective pressure of prior antineoplastic treatment. Finally, in 9 of 10 children’s post–allo-SCT relapse, we found alterations in genes for which targeted therapies with novel agents are readily available. We could show efficient targeting of leukemic blasts by APR-246 in 2 patients carrying TP53 mutations. Our findings shed light on the genetic basis of post–allo-SCT relapse and may pave the way for unraveling novel therapeutic strategies in this challenging situation.
Pan-African University (PAU) is an initiative of the African Union Commission (AUC) that started in 2008 with the objective to promote higher education, science and technology on the African continent at a high academic level. The Pan-African University Institute of Water and Energy Sciences (including Climate Change) (PAUWES) is one of the five hubs of the Pan African University (PAU) and hosted at the University of Tlemcen in Algeria. PAUWES offers graduate students access to leading academic research and the latest theoretical and hands-on training in areas vital to the future of Africa’s development in water, energy and the challenge of climate change.
Opportunities for Sustainable Mobility: Re-thinking Eco-feedback from a Citizen's Perspective
(2019)
In developed nations, a growing emphasis is being placed on the promotion of sustainable behaviours amongst individuals, or ‘citizen-consumers’. In HCI, various eco-feedback tools have been designed as persuasive instruments, with a strong normative appeal geared to encouraging citizens to conduct a more sustainable mobility. However, many critiques have been formulated regarding this ‘paternalistic’ stance. In this paper, we switched the perspective from a designer’s to a citizen’s point of view and explored how people would use eco-feedback tools to support sustainable mobility in their city. In the study, we conducted 14 interviews with citizens who had used eco-feedback previously. The findings indicate new starting points that could inform future eco-feedback tools. These encompass: (1) better information regarding how sustainable mobility is measured and monitored; (2) respect for individual mobility situations and preferences; and (3) the scope for participation and the sharing of responsibility between citizens and municipal city services.
Contemporary software is inherently distributed. The principles guiding the design of such software have been mainly manifested by the service-oriented architecture (SOA) concept. In a SOA, applications are orchestrated by software services generally operated by distinct entities. Due to the latter fact, service security has been of importance in such systems ever since. A dominant protocol for implementing SOA-based systems is SOAP, which comes with a well-elaborated security framework. As an alternative to SOAP, the architectural style representational state transfer (REST) is gaining traction as a simple, lightweight and flexible guideline for designing distributed service systems that scale at large. This paper starts by introducing the basic constraints representing REST. Based on these foundations, the focus is afterwards drawn on the security needs of REST-based service systems. The limitations of transport-oriented protection means are emphasized and the demand for specific message-oriented safeguards is assessed. The paper then reviews the current activities in respect to REST-security and finds that the available schemes are mostly HTTP-centered and very heterogeneous. More importantly, all of the analyzed schemes contain vulnerabilities. The paper contributes a methodology on how to establish REST-security as a general security framework for protecting REST-based service systems of any kind by consistent and comprehensive protection means. First adoptions of the introduced approach are presented in relation to REST message authentication with instantiations for REST-ful HTTP (web/cloud services) and REST-ful constraint application protocol (CoAP) (internet of things (IoT) services).
We present a systematization of usable security principles, guidelines and patterns to facilitate the transfer of existing knowledge to researchers and practitioners. Based on a literature review, we extracted 23 principles, 11 guidelines and 47 patterns for usable security and identified their interconnection. The results indicate that current research tends to focus on only a subset of important principles. The fact that some principles are not yet addressed by any design patterns suggests that further work on refining these patterns is needed. We developed an online repository, which stores the harmonized principles, guidelines and patterns. The tool enables users to search for relevant guidance and explore it in an interactive and programmatic manner. We argue that both the insights presented in this article and the web-based repository will be highly valuable for students to get a good overview, practitioners to implement usable security and researchers to identify areas of future research.
Healing of large bone defects requires implants or scaffolds that provide structural guidance for cell growth, differentiation, and vascularization. In the present work, an agarose-hydroxyapatite composite scaffold was developed that acts not only as a 3D matrix, but also as a release system. Hydroxyapatite (HA) was incorporated into the agarose gels in situ in various ratios by a simple procedure consisting of precipitation, cooling, washing, and drying. The resulting gels were characterized regarding composition, porosity, mechanical properties, and biocompatibility. A pure phase of carbonated HA was identified in the scaffolds, which had pore sizes of up to several hundred micrometers. Mechanical testing revealed elastic moduli of up to 2.8 MPa for lyophilized composites. MTT testing on Lw35human mesenchymal stem cells (hMSCs) and osteosarcoma MG-63 cells proved the biocompatibility of the scaffolds. Furthermore, scaffolds were loaded with model drug compounds for guided hMSC differentiation. Different release kinetic models were evaluated for adenosine 5′-triphosphate (ATP) and suramin, and data showed a sustained release behavior over four days.
In the literature on occupational stress and recovery from work, several facets of thinking about work during off-job time have been conceptualized. However, research on the focal concepts is currently rather diffuse. In this study we take a closer look at the five most well-established concepts: (1) psychological detachment, (2) affective rumination, (3) problem-solving pondering, (4) positive work reflection, and (5) negative work reflection. More specifically, we scrutinized (1) whether the five facets of work-related rumination are empirically distinct, (2) whether they yield differential associations with different facets of employee well-being (burnout, work engagement, thriving, satisfaction with life, and flourishing), and (3) to what extent the five facets can be distinguished from and relate to conceptually similar constructs, such as irritation, worry, and neuroticism. We applied structural equation modeling techniques to cross-sectional survey data from 474 employees. Our results provide evidence for (1) five correlated, yet empirically distinct facets of work-related rumination. (2) Each facet yields a unique pattern of association with the eight aspects of employee well-being. For instance, detachment is strongly linked to satisfaction with life and flourishing. Affective rumination is linked particularly to burnout. Problem-solving pondering and positive work reflection yield the strongest links to work engagement. (3) The five facets of work-related rumination are distinct from related concepts, although there is a high overlap between (lower levels of) psychological detachment and cognitive irritation. Our study contributes to clarifying the structure of work-related rumination and extends the nomological network around different types of thinking about work during off-job time and employee well-being.
In the literature on occupational stress and recovery from work several facets of thinking about work in off-job time have been conceptualized. However, research on the focal concepts is currently rather disintegrated. In this study we take a closer look at the five most established concepts, namely (1) psychological detachment, (2) affective rumination, (3) problem-solving pondering, (4) positive work reflection, and (5) negative work reflection. More specifically, we scrutinized (1) whether the five facets of work-related rumination are empirically distinct, (2) whether they yield differential associations with different facets of employee well-being (burnout, work engagement, thriving, satisfaction with life, and flourishing), and (3) to what extent the five facets can be distinguished from and relate to conceptually similar constructs, such as irritation, worry, and neuroticism. We applied structural equation modeling techniques to cross-sectional survey data from 474 employees. Our results provide evidence that (1) the five facets of work-related rumination are highly related, yet empirically distinct, (2) that each facet contributes uniquely to explain variance in certain aspects of employee well-being, and (3) that they are distinct from related concepts, albeit there is a high overlap between (lower levels of) psychological detachment and cognitive irritation. Our study contributes to clarify the structure of work-related rumination and extends the nomological network around different types of thinking about work in off-job time and employee well-being.
We present a novel, multilayer interaction approach that enables state transitions between spatially above-screen and 2D on-screen feedback layers. This approach supports the exploration of haptic features that are hard to simulate using rigid 2D screens. We accomplish this by adding a haptic layer above the screen that can be actuated and interacted with (pressed on) while the user interacts with on-screen content using pen input. The haptic layer provides variable firmness and contour feedback, while its membrane functionality affords additional tactile cues like texture feedback. Through two user studies, we look at how users can use the layer in haptic exploration tasks, showing that users can discriminate well between different firmness levels, and can perceive object contour characteristics. Demonstrated also through an art application, the results show the potential of multilayer feedback to extend on-screen feedback with additional widget, tool and surface properties, and for user guidance.
The initial phase in real world engineering optimization and design is a process of discovery in which not all requirements can be made in advance, or are hard to formalize. Quality diversity algorithms, which produce a variety of high performing solutions, provide a unique chance to support engineers and designers in the search for what is possible and high performing. In this work we begin to answer the question how a user can interact with quality diversity and turn it into an interactive innovation aid. By modeling a user's selection it can be determined whether the optimization is drifting away from the user's preferences. The optimization is then constrained by adding a penalty to the objective function. We present an interactive quality diversity algorithm that can take into account the user's selection. The approach is evaluated in a new multimodal optimization benchmark that allows various optimization tasks to be performed. The user selection drift of the approach is compared to a state of the art alternative on both a planning and a neuroevolution control task, thereby showing its limits and possibilities.
It is shown that the electrochemical kinetics of alkaline methanol oxidation can be reduced by setting certain fast reactions contained in it to a steady state. As a result, the underlying system of Ordinary Differential Equations (ODE) is transformed to a system of Differential-Algebraic Equations (DAE). We measure the precision characteristics of such transformation and discuss the consequences of the obtained model reduction.
In this paper, we provide a participatory design study of a mobile health platform for older adults that provides an integrative perspective on health data collected from different devices and apps. We illustrate the diversity and complexity of older adults’ perspectives in the context of health and technology use, the challenges which follow on for the design of mobile health platforms that support active and healthy ageing (AHA) and our approach to addressing these challenges through a participatory design (PD) process. Interviews were conducted with older adults aged 65+ in a two-month study with the goal of understanding perspectives on health and technologies for AHA support. We identified challenges and derived design ideas for a mobile health platform called “My-AHA”. For researchers in this field, the structured documentation of our procedures and results, as well as the implications derived provide valuable insights for the design of mobile health platforms for older adults.
Miscanthus x giganteus Stem Versus Leaf-Derived Lignins Differing in Monolignol Ratio and Linkage
(2019)
As a renewable, Miscanthus offers numerous advantages such as high photosynthesis activity (as a C4 plant) and an exceptional CO2 fixation rate. These properties make Miscanthus very attractive for industrial exploitation, such as lignin generation. In this paper, we present a systematic study analyzing the correlation of the lignin structure with the Miscanthus genotype and plant portion (stem versus leaf). Specifically, the ratio of the three monolignols and corresponding building blocks as well as the linkages formed between the units have been studied. The lignin amount has been determined for M. x giganteus (Gig17, Gig34, Gig35), M. nagara (NagG10), M. sinensis (Sin2), and M. robustus (Rob4) harvested at different time points (September, December, and April). The influence of the Miscanthus genotype and plant component (leaf vs. stem) has been studied to develop corresponding structure-property relationships (i.e., correlations in molecular weight, polydispersity, and decomposition temperature). Lignin isolation was performed using non-catalyzed organosolv pulping and the structure analysis includes compositional analysis, Fourier transform infradred (FTIR), ultraviolet/visible (UV-Vis), hetero-nuclear single quantum correlation nuclear magnetic resonsnce (HSQC-NMR), thermogravimetric analysis (TGA), and pyrolysis gaschromatography/mass spectrometry (GC/MS). Structural differences were found for stem and leaf-derived lignins. Compared to beech wood lignins, Miscanthus lignins possess lower molecular weight and narrow polydispersities (<1.5 Miscanthus vs. >2.5 beech) corresponding to improved homogeneity. In addition to conventional univariate analysis of FTIR spectra, multivariate chemometrics revealed distinct differences for aromatic in-plane deformations of stem versus leaf-derived lignins. These results emphasize the potential of Miscanthus as a low-input resource and a Miscanthus-derived lignin as promising agricultural feedstock.
The number of studies on work breaks and the importance of this subject is growing rapidly, with research showing that work breaks increase employees’ wellbeing and performance and workplace safety. However, comparing the results of work break research is difficult since the study designs and methods are heterogeneous and there is no standard theoretical model for work breaks. Based on a systematic literature search, this scoping review included a total of 93 studies on experimental work break research conducted over the last 30 years. This scoping review provides a first structured evaluation regarding the underlying theoretical framework, the variables investigated, and the measurement methods applied. Studies using a combination of measurement methods from the categories “self-report measures,” “performance measures,” and “physiological measures” are most common and to be preferred in work break research. This overview supplies important information for ergonomics researchers allowing them to design work break studies with a more structured and stronger theory-based approach. A standard theoretical model for work breaks is needed in order to further increase the comparability of studies in the field of experimental work break research in the future.
The media is considered to be the fourth pillar in a democratic country. It acts as an effective control mechanism to check the other branches of the government. But this is only consequential when the media functions in an independent and transparent fashion with trained and neutral professionals who are aware of the accountability and consequences of their work. All these factors together would further the country as a democratic institution. Traditionally, it was legacy media responsible for a one-to-many communication process. Their goal was to provide information to the citizens. But this changed with development in technology and the use of social media in daily life. The internet brought with it new media formats which are easily accessible but also unstructured. These lowered barriers of entry in the media enabled citizens to become active participants in the communication process. As a result, these citizens developed a different relationship with the already existing media wherein they were not only the receivers to information but also co-producers. Real-time information allows users to communicate with each other and in turn widely generate public opinion on internet platforms. A many-to-many communication style emerged. While on the one hand, this type of discourse could be an opportunity for citizens to exercise their fundamental freedom of speech and expression, it is on the other hand, proving to have a detrimental effect in two parts: Lack of neutrality, polarized views and pre-existing misconceptions on the part of citizens as well as algorithms and formation of echo-chambers on the part of technology. Some questions arise in this scenario about the capability of citizen journalists, the duties they should adhere to along with the enjoyment of their rights and freedoms, the risks involved in an unchecked method of communication and the effect of citizen journalism in the democratic process.
Mass Spectrometry: Pyrolysis
(2019)
Lignocellulose feedstock (LCF) provides a sustainable source of components to produce bioenergy, biofuel, and novel biomaterials. Besides hard and soft wood, so-called low-input plants such as Miscanthus are interesting crops to be investigated as potential feedstock for the second generation biorefinery. The status quo regarding the availability and composition of different plants, including grasses and fast-growing trees (i.e., Miscanthus, Paulownia), is reviewed here. The second focus of this review is the potential of multivariate data processing to be used for biomass analysis and quality control. Experimental data obtained by spectroscopic methods, such as nuclear magnetic resonance (NMR) and Fourier-transform infrared spectroscopy (FTIR), can be processed using computational techniques to characterize the 3D structure and energetic properties of the feedstock building blocks, including complex linkages. Here, we provide a brief summary of recently reported experimental data for structural analysis of LCF biomasses, and give our perspectives on the role of chemometrics in understanding and elucidating on LCF composition and lignin 3D structure.