Refine
Departments, institutes and facilities
- Fachbereich Informatik (48)
- Fachbereich Angewandte Naturwissenschaften (45)
- Fachbereich Wirtschaftswissenschaften (27)
- Institut für Technik, Ressourcenschonung und Energieeffizienz (TREE) (24)
- Institute of Visual Computing (IVC) (21)
- Institut für funktionale Gen-Analytik (IFGA) (18)
- Institut für Verbraucherinformatik (IVI) (14)
- Fachbereich Ingenieurwissenschaften und Kommunikation (13)
- Internationales Zentrum für Nachhaltige Entwicklung (IZNE) (13)
- Institut für Cyber Security & Privacy (ICSP) (10)
Document Type
- Article (73)
- Conference Object (67)
- Part of a Book (39)
- Working Paper (6)
- Book (monograph, edited volume) (5)
- Doctoral Thesis (2)
- Preprint (2)
- Report (2)
- Contribution to a Periodical (1)
- Lecture (1)
Year of publication
- 2018 (200) (remove)
Language
- English (200) (remove)
Keywords
- ICT (5)
- Dementia (3)
- FPGA (3)
- drug release (3)
- lignin (3)
- osteogenesis (3)
- Exergame (2)
- Folin-Ciocalteu assay (2)
- Gamification (2)
- Hybrids (2)
- Innovation (2)
- Kenya (2)
- Latin America (2)
- Non-linear systems (2)
- Remote laboratory (2)
- Surrogate Modeling (2)
- Virtual Reality (2)
- antioxidant activity (2)
- autonomous driving (2)
- biomass (2)
- biomaterial (2)
- bone regeneration (2)
- caregivers (2)
- emotion recognition (2)
- hydrogel (2)
- ketogenesis (2)
- lignocellulose feedstock (2)
- multivariate data processing (2)
- organic aciduria (2)
- organosolv (2)
- participatory design (2)
- scaffolds (2)
- stem cells (2)
- tissue engineering (2)
- total phenol content (2)
- travel mode choice (2)
- 3-hydroxy-n-butyric acid (1)
- 3D User Interface (1)
- 3D user interface (1)
- Abiotic stress (1)
- Active and Healthy Aging Technologies (1)
- Affective computing (1)
- Agglomerative Hierarchical Cluster Analysis (1)
- Alternatives (1)
- Angiogenesis (1)
- Antimicrobial activity (1)
- Antioxidant activity (1)
- Available Bandwidth (1)
- B2T (1)
- BRICS (1)
- Bandwidth Estimation (1)
- Berufliche e‑Mental Health (1)
- Bihar (1)
- Biomass (1)
- Biomaterial (1)
- Biorefinery (1)
- Blended Learning (1)
- Brazil (1)
- Business English (1)
- Business processes (1)
- Business-to-Thing (1)
- CSR-RUG (1)
- Capacity (1)
- Cathepsins (1)
- Cellulose (1)
- Centrifugation (1)
- Chiapas (1)
- Chlorophyll fluorescence (1)
- Clean Energy and Power Systems (1)
- Climate change (1)
- Co-located work (1)
- Code similarity analysis (1)
- Competency-based teaching (1)
- Complex modulus (1)
- Composites (1)
- Computer Automated Design (1)
- Computer Simulation Techniques (1)
- Consumer (1)
- Corporate Social Responsibility (1)
- CyberGlove (1)
- Cysteine proteases (1)
- DMA (1)
- DNA interaction (1)
- DOSY (1)
- DSC (1)
- Data management (1)
- Data sharing (1)
- Dataflow Programming (1)
- Delph Study (1)
- Delphi-method (1)
- Demands of Older Adults (1)
- Diagnostic bond graphs (1)
- Difference Visualization (1)
- Digital design (1)
- Directive 2014/95/EU (1)
- Domain (1)
- Dynamic mechanical analysis (1)
- E. coli (1)
- E/I balance (1)
- ENaC (1)
- Embedded software (1)
- Environmental Protection (1)
- Erholung (1)
- Expert elicitation (1)
- Explainable artificial intelligence (1)
- Explosives (1)
- Eye Tracking (1)
- FMR1 (1)
- Fault detection and isolation (1)
- Fiber-optic probe (1)
- Fixed spatial data (1)
- Fragile X Syndrome (1)
- Free-Space Loss (FSL) (1)
- Future (1)
- Future Studies (1)
- Future of Robotics (1)
- Future-oriented business models (1)
- GC/MS (1)
- Gamifikation (1)
- Gaze Depth Estimation (1)
- Gaze-contingent depth-of-field (1)
- Gender digital divide (1)
- Generation R (1)
- Generative Design (1)
- German paper production industry (1)
- Ghana (1)
- Globally convergent methods (1)
- Graft material (1)
- Grounded Theory (1)
- Group behavior (1)
- Hand Guidance (1)
- Health Technology Design (1)
- Heparin (1)
- Horner-Wadsworth-Emmons olefination Irreversible inhibition (1)
- Human-Robot-Interaction (HRI) (1)
- IEEE 802.11 (1)
- IOPVs (1)
- IP protection (1)
- Information interaction (1)
- Instrument of Environment Law (1)
- Integration of New Technologies for the Elderly (1)
- Integration of Technologies for Active and Healthy Aging (1)
- Interaction Patterns (1)
- Internet of Things (1)
- Kalman filter (1)
- Kozak-sequence (1)
- LAA (1)
- LTE-U (1)
- Learning App (1)
- Life Cycle Assessment (LCA) (1)
- Light limitation (1)
- Lignin (1)
- Lignocellulose feedstock (1)
- LoRa (1)
- LoRa receiver accuracy (1)
- Local mechanical properties (1)
- Local varieties (1)
- Longley-Rice Irregular Terrain Model (ITM) (1)
- Low-power design (1)
- Low-power education (1)
- MAP (1)
- MAP-Elites (1)
- MCT (1)
- MOCS1 (1)
- MSCs (1)
- Maize varietal output (1)
- Malawi (1)
- Market access (1)
- Measurement (1)
- Megatrends (1)
- Michael acceptors (1)
- Microindentation (1)
- Mixed methods (1)
- Moco deficiency (1)
- Mode switching LTI model (1)
- Mode-dependent ARRs (1)
- Model-based failure prognosis (1)
- Molecular rotation (1)
- Molecular weight (1)
- Molybdenum cofactor (1)
- Multiple Displays (1)
- Mxi-2 (1)
- NEAT (1)
- NGOs (1)
- NMR spectroscopy (1)
- Navigation (1)
- Neuroevolution (1)
- OFDM-based DCSK (1)
- OFDM-based SR-QCSK (1)
- Occupational e‑mental health (1)
- Organic compounds and Functional groups (1)
- Orthogonal chaotic vector shift keying (1)
- Parameter degradation model (1)
- Partial least squares regression (1)
- Participatory Design (1)
- Participatory design studies (1)
- Partworth Utilities (1)
- Path loss model (1)
- Perceived adoption rate (1)
- Performance Analysis (1)
- Plant‐based and animal‐derived organic products (1)
- Pose Estimation (1)
- Poultry (1)
- Poultry spoilage (1)
- Principal Components Analysis (1)
- Privacy (1)
- Protected cultivation (1)
- Ps. fluorescens (1)
- Pulping (1)
- Qualitative Research (1)
- Quality Diversity (1)
- Quality of Service (1)
- Quantum mechanical methods (1)
- Raman spectroscopy (1)
- Random number generator (1)
- Rapid method (1)
- Recovery (1)
- Relative Added Value (1)
- Remaining Useful Life (1)
- Renewable resource (1)
- Robot Perception (1)
- Robotic Governance (1)
- Robotic Natives (1)
- Robotic Revolutions (1)
- S-sulfocysteine (1)
- SLC (1)
- SOFIA (GREAT) (1)
- Seed access (1)
- Seed quality (1)
- Self-Driving Cars (1)
- Shared Autonomous Vehicles (1)
- Side-channel watermarking (1)
- Similarity matrix (1)
- Social Protection (1)
- Social policies (1)
- Sociomateriality (1)
- Software reverse engineering (1)
- Somatogravic Illusion (1)
- Spectrum occupancy (1)
- Sprouting (1)
- Static stiffness (1)
- Stationary network problems (1)
- Stem cells (1)
- Sulfite oxidase (1)
- Sustainability (1)
- Sweet cherry (Prunus avium L.) (1)
- Swim Stroke Analysis (1)
- System health monitoring (1)
- THz astronomy (1)
- Tactile Feedback (1)
- Tactile feedback (1)
- Taxonomy (1)
- Testing Tool (1)
- Throughput (1)
- Tiled displays (1)
- Tissue engineering (1)
- Travel Mode Choice (1)
- U-NII band (1)
- University of Cape Coast (1)
- Urlaub (1)
- Urothione (1)
- User Acceptance (1)
- User Experience (1)
- User Study (1)
- User experiences (1)
- VOC (1)
- Vacation (1)
- Vascular cells (1)
- Vascular grafts (1)
- Vasculature (1)
- Videogame (1)
- Vim3 (1)
- Web Browser Cache (1)
- Wnt/β-catenin (1)
- Xenopus laevis (1)
- Zambia (1)
- acetoacetic acid (1)
- acetone (1)
- action unit recognition (1)
- adl (1)
- agriculture (1)
- airborne (1)
- alternative urban food networks (1)
- angiogenesis (1)
- applications (1)
- autism spectrum disorders (1)
- autophagy (1)
- auxiliary power supply (1)
- behavior and cognition (1)
- bone (1)
- breast cancer (1)
- bulk detection (1)
- cPMP (1)
- car sharing (1)
- cell death (1)
- change agents (1)
- chemosensory cells (1)
- cholinergic (1)
- chymotrypsin (1)
- ciclopirox olamine (1)
- citizens' involvement (1)
- civil society (1)
- client-side component model (1)
- co-located collaboration (1)
- co-production (1)
- cognitive radio (1)
- complexity analysis (1)
- consumption shifting (1)
- control (1)
- convex optimization (1)
- cytokine-induced killer cells (1)
- data glove (1)
- database (1)
- deep learning (1)
- delta-subunit (1)
- dementia (1)
- dependable robots (1)
- devolution (1)
- diagnostic bond graphs (1)
- differentiation (1)
- digital design (1)
- digital receipt (1)
- dimensionality reduction (1)
- domain-specific language (1)
- draw ratio (1)
- e-learning (1)
- efficiency (1)
- electrophysiology (1)
- embedded collaborative learning (1)
- endoplasmic reticulum (ER) stress (1)
- energy efficiency (1)
- energy saving (1)
- environmental impact analysis (1)
- enzyme activity (1)
- epithelial sodium channel (ENaC) (1)
- ethacrynic acid (1)
- exergame (1)
- exergames (1)
- export (1)
- extrusion blow molding (1)
- eye-tracking (1)
- facial expression analysis (1)
- farmers (1)
- fatty acid metabolism (1)
- field study (1)
- fixed causalities generation of analytical redundancy relations (1)
- flow direction (1)
- food consumption (1)
- food security (1)
- forecast (1)
- foveated rendering (1)
- furin (1)
- gas sensors (1)
- gas transport networks (1)
- globally convergent solvers (1)
- grasp motions (1)
- grasping (1)
- grass-based pulp (1)
- gravito-inertial force (1)
- hand guidance (1)
- handprint (1)
- heart rate control (1)
- heart rate modeling (1)
- heart rate prediction (1)
- hepatocellular carcinoma (1)
- high information rate (1)
- high resolution spectroscopy (1)
- holography (1)
- homemade explosives (1)
- human factors (1)
- human wellbeing (1)
- human-robot collaboration (1)
- humanoidrobot (1)
- hybrid dynamics solver (1)
- iPS cells (1)
- ideal switches (1)
- ideation (1)
- immersive systems (1)
- immunotherapy (1)
- improvised explosive devices (1)
- inclusive development (1)
- indirect rebound effects (1)
- infectious disease (1)
- information society (1)
- interaction (1)
- interface design (1)
- interferon γ (1)
- isoleucine (1)
- ketolysis (1)
- ketone body synthesis (1)
- kraft lignin (1)
- leucine (1)
- leucine degradation (1)
- library free detection (1)
- load control (1)
- local political economy (1)
- machine learning (1)
- medical training (1)
- mesenchymal stem cells (1)
- methodical limits of LCA (1)
- miR-15 (1)
- miR-498 (1)
- microsatellite instability (1)
- mobile web (1)
- mode-dependent implicit state space model (1)
- mode-switching linear time-invariant models (1)
- model-driven engineering (1)
- modeling of complex systems (1)
- modelling method (1)
- modular web (1)
- mold temperature (1)
- motion capture (1)
- mouse model (1)
- multi-user VR (1)
- municipality (1)
- nano structured gas sensors (1)
- nanobodies (1)
- organic acid analysis (1)
- orthogonal frequency division multiplexing (1)
- osteoblast (1)
- osteoclast (1)
- pain recognition (1)
- parcel logistics (1)
- participation (1)
- patch clamp (1)
- patent (1)
- pension privatization (1)
- pension reform (1)
- pension schemes (1)
- perception of upright (1)
- performance analysis (1)
- phenomenological approaches (1)
- photovoltaic (1)
- physical sensors (1)
- preference migration (1)
- prehensile motions (1)
- primates (1)
- promotion of organic agriculture (1)
- protease (1)
- prototype theory (1)
- pseudo-random number generator (1)
- public finance (1)
- public sector (1)
- purinergic receptors (1)
- qualitative empirical research (1)
- quality of life (1)
- quality-diversity (1)
- ray tracing (1)
- rebound effects (1)
- regional economies (1)
- relatives (1)
- remote diagnosis (1)
- remote-lab (1)
- resilience (1)
- robot component monitoring (1)
- robot dynamics (1)
- robotic black box (1)
- salt (1)
- scaffold (1)
- security (1)
- serious games (1)
- service robots (1)
- shared autonomous vehicles (1)
- simulation exercises (1)
- single-domain antibody (1)
- social interactions (1)
- social protection (1)
- social robots (1)
- social security administration (1)
- social security financing (1)
- social security policy (1)
- social support (1)
- software variability (1)
- spectrum sensing (1)
- speech recognition (1)
- speech understanding (1)
- state constraints (1)
- static friction (1)
- sustainability assessments (1)
- sustainable development (1)
- sustainable mobility (1)
- therapy (1)
- tiled displays (1)
- topological reduction (1)
- traditional authorities (1)
- training monitoring (1)
- transformative effects (1)
- true random number generator (1)
- ultrasonic sensor (1)
- unfolded protein response (UPR) (1)
- urban food strategy (1)
- urban food supply (1)
- urethra (1)
- urethral brush cells (1)
- user preferences (1)
- user study (1)
- vestibular system (1)
- video lectures (1)
- wearable photovoltaic system (1)
- wearable sensors (1)
- web caching (1)
- web components (1)
- web technology (1)
- xorshift-generator (1)
Scientific or statistical research has long been the domain of dedicated programming languages such as R, SPSS or SAS. A few years other competitors entered the arena, among them Python with its powerful SciPy package. The following article introduces SciPy by applying a small subset of its functionality to a well-known dataset.
The increasing complexity of tasks that are required to be executed by robots demands higher reliability of robotic platforms. For this, it is crucial for robot developers to consider fault diagnosis. In this study, a general non-intrusive fault diagnosis system for robotic platforms is proposed. A mini-PC is non-intrusively attached to a robot that is used to detect and diagnose faults. The health data and diagnosis produced by the mini-PC is then standardized and transmitted to a remote-PC. A storage device is also attached to the mini-PC for data logging of health data in case of loss of communication with the remote-PC. In this study, a hybrid fault diagnosis method is compared to consistency-based diagnosis (CBD), and CBD is selected to be deployed on the system. The proposed system is modular and can be deployed on different robotic platforms with minimum setup.
Renewable resources are gaining increasing interest as a source for environmentally benign biomaterials, such as drug encapsulation/release compounds, and scaffolds for tissue engineering in regenerative medicine. Being the second largest naturally abundant polymer, the interest in lignin valorization for biomedical utilization is rapidly growing. Depending on its resource and isolation procedure, lignin shows specific antioxidant and antimicrobial activity. Today, efforts in research and industry are directed toward lignin utilization as a renewable macromolecular building block for the preparation of polymeric drug encapsulation and scaffold materials. Within the last five years, remarkable progress has been made in isolation, functionalization and modification of lignin and lignin-derived compounds. However, the literature so far mainly focuses lignin-derived fuels, lubricants and resins. The purpose of this review is to summarize the current state of the art and to highlight the most important results in the field of lignin-based materials for potential use in biomedicine (reported in 2014⁻2018). Special focus is placed on lignin-derived nanomaterials for drug encapsulation and release as well as lignin hybrid materials used as scaffolds for guided bone regeneration in stem cell-based therapies.
After replanting apple (Malus domestica Borkh.) on the same site severe growth suppressions, and a decline in yield and fruit quality are observed in all apple producing areas worldwide. The causes of this complex phenomenon, called apple replant disease (ARD), are only poorly understood up to now which is in part due to inconsistencies in terms and methodologies. Therefore we suggest the following definition for ARD: ARD describes a harmfully disturbed physiological and morphological reaction of apple plants to soils that faced alterations in their (micro-) biome due to the previous apple cultures. The underlying interactions likely have multiple causes that extend beyond common analytical tools in microbial ecology. They are influenced by soil properties, faunal vectors, and trophic cascades, with genotype-specific effects on plant secondary metabolism, particularly phytoalexin biosynthesis. Yet, emerging tools allow to unravel the soil and rhizosphere (micro-) biome, to characterize alterations of habitat quality, and to decipher the plant reactions. Thereby, deep insights into the reactions taking place at the root rhizosphere interface will be gained. Counteractions are suggested, taking into account that culture management should emphasize on improving soil microbial and faunal diversity as well as habitat quality rather than focus on soil disinfection.
The epithelial sodium channel (ENaC) is a critical regulator of vertebrate electrolyte homeostasis. ENaC is the only constitutively open ion channel in the degenerin/ENaC protein family, and its expression, membrane abundance, and open probability therefore are tightly controlled. The canonical ENaC is composed of three subunits (, , and ), but a fourth -subunit may replace and form atypical -ENaCs. Using Xenopus laevis as a model, here we found that mRNAs of the - and -subunits are differentially expressed in different tissues and that -ENaC predominantly is present in the urogenital tract. Using whole-cell and single-channel electrophysiology of oocytes expressing Xenopus - or -ENaC, we demonstrate that the presence of the -subunit enhances the amount of current generated by ENaC due to an increased open probability, but also changes current into a transient form. Activity of canonical ENaCs is critically dependent on proteolytic processing of the - and -subunits, and immunoblotting with epitope-tagged ENaC subunits indicated that, unlike -ENaC, the -subunit does not undergo proteolytic maturation by the endogenous protease furin. Furthermore, currents generated by -ENaC were insensitive to activation by extracellular chymotrypsin, and presence of the -subunit prevented cleavage of -ENaC at the cell surface. Our findings suggest that subunit composition constitutes an additional level of ENaC regulation, and we propose that the Xenopus -ENaC subunit represents a functional example that demonstrates the importance of proteolytic maturation during ENaC evolution.
Towards explaining deep learning networks to distinguish facial expressions of pain and emotions
(2018)
Deep learning networks are successfully used for object and face recognition in images and videos. In order to be able to apply such networks in practice, for example in hospitals as a pain recognition tool, the current procedures are only suitable to a limited extent. The advantage of deep learning methods is that they can learn complex non-linear relationships between raw data and target classes without limiting themselves to a set of hand-crafted features provided by humans. However, the disadvantage is that due to the complexity of these networks, it is not possible to interpret the knowledge that is stored inside the network. It is a black-box learning procedure. Explainable Artificial Intelligence (AI) approaches mitigate this problem by extracting explanations for decisions and representing them in a human-interpretable form. The aim of this paper is to investigate the explainable AI method Layer-wise Relevance Propagation (LRP) and apply it to explain how a deep learning network distinguishes facial expressions of pain from facial expressions of emotions such as happiness and disgust.
Background: Local injection of autologous conditioned serum (ACS) is a well-known therapy for inflammatory diseases (IDs). While patients’ blood is incubated to generate ACS (with subsequent centrifugation), immune cells produce high amounts of growth factors and cytokines. This include, amongst others, interleukin-1 receptor antagonist (IL-1ra), interleukins 6 and 10, tumour necrosis factor alpha (TNF-α) and transforming growth factor beta 1 (TGF-β1). The aim of this study was to analyse exosomes release into ACS as well as their cytokine cargo.
In recent years, a variety of methods have been introduced to exploit the decrease in visual acuity of peripheral vision, known as foveated rendering. As more and more computationally involved shading is requested and display resolutions increase, maintaining low latencies is challenging when rendering in a virtual reality context. Here, foveated rendering is a promising approach for reducing the number of shaded samples. However, besides the reduction of the visual acuity, the eye is an optical system, filtering radiance through lenses. The lenses create depth-of-field (DoF) effects when accommodated to objects at varying distances. The central idea of this article is to exploit these effects as a filtering method to conceal rendering artifacts. To showcase the potential of such filters, we present a foveated rendering system, tightly integrated with a gaze-contingent DoF filter. Besides presenting benchmarks of the DoF and rendering pipeline, we carried out a perceptual study, showing that rendering quality is rated almost on par with full rendering when using DoF in our foveated mode, while shaded samples are reduced by more than 69%.
Friction effects impose a requirement for the supplementary amount of torque to be produced in actuators for a robot to move, which in turn increases energy consumption. We cannot eliminate friction, but we can optimize motions to make them more energy efficient, by considering friction effects in motion computations. Optimizing motions means computing efficient joint torques/accelerations based on different friction torques imposed in each joint. Existing friction forces can be used for supporting certain types of arm motions, e.g standing still.
Reducing energy consumption of robot's arms will provide many benefits, such as longer battery life of mobile robots, reducing heat in motor systems, etc.
The aim of this project is extending an already available constrained hybrid dynamic solver, by including static friction effects in the computations of energy optimal motions. When the algorithm is extended to account for static friction factors, a convex optimization (maximization) problem must be solved.
The author of this hybrid dynamic solver has briefly outlined the approach for including static friction forces in computations of motions, but without providing a detailed derivation of the approach and elaboration that will show its correctness. Additionally, the author has outlined the idea for improving the computational efficiency of the approach, but without providing its derivation.
In this project, the proposed approach for extending the originally formulated algorithm has been completely derived and evaluated in order to show its feasibility. The evaluation is conducted in simulation environment with one DOF robot arm, and it shows correct results from the computation of motions. Furthermore, this project presents the derivation of the outlined method for improving the computational efficiency of the extended solver.
From September 2016 to February 2017, I did an internship at the University of Cape Coast, Ghana (UCC) as part of my studies in Business Administration at Hochschule Bonn-Rhein-Sieg, University of Applied Sciences, Germany (H-BRS). At H-BRS, an internship of five or six months (or, alternatively, one exchange semester) is an obligatory part of the curriculum so students get hands-on experience even before they enter the job market. My internship was also part of the intercontinental partnership between UCC and H-BRS, which has resulted in many different projects.
Daryoush Daniel Vaziri illustrates that the use of mixed methods designs may support the induction of more subtle and complete theories about older adults’ use of technologies for the support of active and healthy aging. The results show that older adults’ social contexts and environments considerably affect their perspectives, practices and attitudes with respect to health, quality of life, well-being and technology use for active and healthy aging support. Results were collected with older adults aged 60+ as well as relevant secondary stakeholders like caregivers, policy makers or health insurance companies.
Speech understanding is a fundamental feature for many applications focused on human-robot interaction. Although many techniques and several services for speech recognition and natural language understanding have been developed in the last years, specific implementation and validation on domestic service robots have not been performed. In this paper, we describe the implementation and the results of a functional benchmark for speech understanding in service robotics that has been developed and tested in the context of different robot competitions: RoboCup@Home, RoCKIn@Home and within the European Robotics League on Service Robots. Different approaches used by the teams in the competitions are presented and the evaluation results obtained in the competitions are discussed.
Through the “Act to Strengthen the Non-financial Reporting by Corporations in their Management and Group Management Reports” (Gesetz zur Stärkung der nichtfinanziellen Berichterstattung der Unternehmen in ihren Lage- und Konzernlageberichten) (CSR Directive Transposition Act, „CSR-RUG“) of 11 April 2017[1], the German Bundestag implemented Directive 2014/95/EU (“CSR Directive”)[2] into German law. Following the European impetus, the CSR-RUG enriches the traditional repertoire of forms of action under environmental law by a further instrument. Already the regulatory context gives an idea of its atypical nature: The centrepiece of the CSR-RUG is the amendment of and addition to the Third Book of the German Commercial Code (Handelsgesetzbuch, “HGB”), which deals with the “trading books” of undertakings, i.e., accounting and reporting requirements. Since the reporting year 2017, large capital market-oriented corporations must report extensively within the framework of their annual management reports on their activities and effects in certain areas of “Corporate Social Responsibility”. This also includes environmental matters. The transparency and publicity this entails is intended to generate positive stimuli for more responsible, sustained and not least of all environmentally friendly entrepreneurial action.
Following a brief presentation of the European legal bases and their implementation in Germany (I.), we will classify the provisions within the underlying concept of Corporate Social Responsibility (II.) and analyse and systemise the governance effects of non-financial reporting (III.). A few remarks on selected aspects of the chosen approach and its implementation (IV.) as well as an outlook summarising our conclusions (V.) will complete this article. By detailing the German approach to transposing the CSR Directive, this paper intends to provide an example of the challenges member state legislators face when complying with modern governance concepts such as Corporate Social Responsibility by way of non-financial reporting obligations.
[1] Federal Law Gazette, Part I 2017, 802 et seq.
[2] Directive 2014/95/EU of the European Parliament and of the Council 22 October 2014 amending Directive 2013/34/EU as regards disclosure of non-financial and diversity information by certain large undertakings and groups, OJ EU No. L 330, p. 1.
This paper presents the outcomes of an exploratory field study that examined the social impact of an ICT-based suite of exergames for people with dementia and their caregivers. Qualitative data was collected over a period of 8 months, during which time we studied the daily life of 14 people with dementia and their informal and professional caregivers. We focus on the experiential aspects of the system and examine its social impact when integrated into the daily routines of both people with dementia themselves and their professional and family caregivers. Our findings indicate that relatives were able to regain leisure time, whilst people with dementia were able to recapture certain aspects of their social and daily activities that might otherwise have been lost to them. Results suggest that the system enhanced social-interaction, invigorated relationships, and improved the empowerment of people with dementia and their caregivers to face daily challenges.
Dementia not only affects the cognitive capabilities, especially memory and orientation, but also physical capabilities, which are associated with a decrease of physical activities. Here, ICT can play a major role to improve health, quality of life and wellbeing in older adults suffering from dementia and related stakeholders, such as relatives, professional and informal caregivers. The aim of the presented system is to increase physical and cognitive capabilities of people with dementia and their caregivers to support them in daily life activities, reduce the strain of the caregivers and improve both their wellbeing.
As a result of ageing societies, the prevalence of dementia, and accordingly the need of care is increasing rapidly. Here, the use of ICT-based technologies may facilitate and promote a self-sustaining life-style for people with dementia and their caregivers. The presented poster describes early findings from the project MobiAssist and outlines the ICT-based training system. The system aims to increase the physical and cognitive capabilities of people with dementia, relief the caregivers and improve wellbeing of involved parties.
Smallholder farmers as a backbone for the implementation of the Sustainable Development Goals
(2018)
Motion capture, often abbreviated mocap, generally aims at recording any kind of motion -- be it from a person or an object -- and to transform it to a computer-readable format. Especially the data recorded from (professional and non-professional) human actors are typically used for analysis in e.g. medicine, sport sciences, or biomechanics for evaluation of human motion across various factors. Motion capture is also widely used in the entertainment industry: In video games and films realistic motion sequences and animations are generated through data-driven motion synthesis based on recorded motion (capture) data.
Although the amount of publicly available full-body-motion capture data is growing, the research community still lacks a comparable corpus of specialty motion data such as, e.g. prehensile movements for everyday actions. On the one hand, such data can be used to enrich (hand-over animation) full-body motion capture data - usually captured without hand motion data due to the drastic dimensional difference in articulation detail. On the other hand, it provides means to classify and analyse prehensile movements with or without respect to the concrete object manipulated and to transfer the acquired knowledge to other fields of research (e.g. from 'pure' motion analysis to robotics or biomechanics).
Therefore, the objective of this motion capture database is to provide well-documented, free motion capture data for research purposes.
The presented database GraspDB14 in sum contains over 2000 prehensile movements of ten different non-professional actors interacting with 15 different objects. Each grasp was realised five times by each actor. The motions are systematically named containing an (anonymous) identifier for each actor as well as one for the object grasped or interacted with.
The data were recorded as joint angles (and raw 8-bit sensor data) which can be transformed into positional 3D data (3D trajectories of each joint).
In this document, we provide a detailed description on the GraspDB14-database as well as on its creation (for reproducibility).
Chapter 2 gives a brief overview of motion capture techniques, freely available motion capture databases for both, full body motions and hand motions, and a short section on how such data is made useful and re-used. Chapter 3 describes the database recording process and details the recording setup and the recorded scenarios. It includes a list of objects and performed types of interaction. Chapter 4 covers used file formats, contents, and naming patterns. We provide various tools for parsing, conversion, and visualisation of the recorded motion sequences and document their usage in chapter 5.
Text is one of the key sources of information for social sciences and humanities which, with the rise and development of computational technologies, has been mostly available via digital libraries, archives and websites. It enables researchers to increasingly deal with large scale text corpora that require the use of advanced software tools to process them and extract information. Computational linguistics - a discipline that has emerged on the border of computer science, linguistics and statistics - has achieved certain results in automated text analysis and information extraction, e.g., tools for part-of-speech tagging, grammar parsing, semantic role labelling, sentiment analysis and anaphora resolution have been developed and successfully used in many scientific projects. However, there still exists a gap between technology available and the needs of social sciences: named entity recognizers are incapable of identifying actors, sentiment analysis just provides the overall mood of an expression but is not able to identify the evaluation of information by the utterer, topic modeling tools can only assign a topic to a document, but fall short of measuring its frame.
Large, high-resolution displays demonstrated their effectiveness in lab settings for cognitively demanding tasks in single user and collaborative scenarios. The effectiveness is mostly reached through inherent displays' properties - large display real estate and high resolution - that allow for visualization of complex datasets, and support of group work and embodied interaction. To raise users' efficiency, however, more sophisticated user support in the form of advanced user interfaces might be needed. For that we need profound understanding of how large, tiled displays impact users work and behavior. We need to extract behavioral patterns for different tasks and data types. This paper reports on study results of how users, while working collaboratively, process spatially fixed items on large, tiled displays. The results revealed a recurrent pattern showing that users prefer to process documents column wise rather than row wise or erratic.
Large, high-resolution displays are highly suitable for creation of digital environments for co-located collaborative task solving. Yet, placing multiple users in a shared environment may increase the risk of interferences, thus causing mental discomfort and decreasing efficiency of the team. To mitigate interferences coordination strategies and techniques were introduced. However, in a mixed-focus collaboration scenarios users switch now and again between loosely and tightly collaboration, therefore different coordination techniques might be required depending on the current collaboration state of team members. For that, systems have to be able to recognize collaboration states as well as transitions between them to ensure a proper adjustment of the coordination strategy. Previous studies on group behavior during collaboration in front of large displays investigated solely collaborative coupling states, not transitions between them though. To address this gap, we conducted a study with 12 participant dyads in front of a tiled display and let them solve two tasks in two different conditions (focus and overview). We looked into group dynamics and categorized transitions by means of changes in proximity, verbal communication, visual attention, visual interface, and gestures. The findings can be valuable for user interface design and development of group behavior models.
Serine/threonine kinase 4 (STK4) deficiency is an autosomal recessive genetic condition that leads to primary immunodeficiency (PID) typically characterized by lymphopenia, recurrent infections and Epstein Barr Virus (EBV) induced lymphoproliferation and -lymphoma. State-of-the-art treatment regimens consist of prevention or treatment of infections, immunoglobulin substitution (IVIG) and restoration of the immune system by hematopoietic stem cell transplantation. Here, we report on two patients from two consanguineous families of Turkish (patient P1) and Moroccan (patient P2) decent, with PID due to homozygous STK4 mutations. P1 harbored a previously reported frameshift (c.1103 delT, p.M368RfsX2) and P2 a novel splice donor site mutation (P2; c.525+2 T>G). Both patients presented in childhood with recurrent infections, CD4 lymphopenia and dysregulated immunoglobulin levels. Patient P1 developed a highly malignant B cell lymphoma at the age of 10 years and a second, independent Hodgkin lymphoma 5 years later. To our knowledge she is the first STK4 deficient case reported who developed lymphoma in the absence of detectable EBV or other common viruses. Lymphoma development may be due to the lacking tumor suppressive function of STK4 or the perturbed immune surveillance due to the lack of CD4+ T cells. Our data should raise physicians' awareness of [1] lymphoma proneness of STK4 deficient patients even in the absence of EBV infection and [2] possibly underlying STK4 deficiency in pediatric patients with a history of recurrent infections, CD4 lymphopenia and lymphoma and unknown genetic make-up. Patient P2 experienced recurrent otitis in childhood, but when she presented at the age of 14, she showed clinical and immunological characteristics similar to patients suffering from Autoimmune Lymphoproliferative Syndrome (ALPS): elevated DNT cell number, non-malignant lymphadenopathy and hepatosplenomegaly, hematolytic anemia, hypergammaglobulinemia. Also patient P1 presented with ALPS-like features (lymphadenopathy, elevated DNT cell number and increased Vitamin B12 levels) and both were initially clinically diagnosed as ALPS-like. Closer examination of P2, however, revealed active EBV infection and genetic testing identified a novel STK4 mutation. None of the patients harbored typically ALPS-associated mutations of the Fas receptor mediated apoptotic pathway and Fas-mediated apoptosis was not affected. The presented case reports extend the clinical spectrum of STK4 deficiency.
While Anglo-Saxon HEIs focus on a strong educational background and personal development of students, the German system, in particular Universities of Applied Sciences, emphasize employability through the transfer of job-related professional and soft skills. In this context, learning by practical application of skills has become an important instrument. Concepts for linking theory and application include research-based learning, practical internships or service learning – methods, which also maintain high standards of academic education.
Introduction
(2018)
This handbook describes the processes and success factors of marketoriented university services to the non-academic world, and the processes to integrate these services into teaching. It aims to highlight benchmark examples from Africa and Germany in order to outline motivational factors, influencing aspects, as well as drivers and barriers to applied university services in developing countries.
Major progress occurred in understanding inborn errors of ketone body transport and metabolism between the International Congresses on Inborn Errors of Metabolism in Barcelona (2013) and Rio de Janeiro (2017). These conditions impair either ketogenesis (presenting as episodes of hypoketotic hypoglycemia) or ketolysis (presenting as ketoacidotic episodes); for both groups, immediate intravenous glucose administration is the most critical and (mHGGCS, HMGCS2) effective treatment measure.
3-Hydroxy-3-methylglutaryl-coenzyme A lyase (HMGCL, HMGCL) deficiency is a rare inborn error of ketogenesis. Even if the ketogenic enzyme is fully disrupted, an elevated signal for the ketone body acetoacetic acid is a frequent observation in the analysis of urinary organic acids, at least if derivatization is performed by methylation. We provide an explanation for this phenomenon and trace it back to degradation of the derivatized 3-hydroxy-3-methylglutaric acid and high temperature of the injector of the gas chromatograph.
Pozzolanic properties of Pennisetum purpureum grass ash were tested on Portland cement. Results show that the ash can be blended with cements without compromising binding strength of the cement. It was found that Portland cement could be blended with Pennisetum purpureum up to a ratio of 3:2 compromising compressive strength of mortar.Mortar with lower cement replacement took longer to set as evidenced by lower compressive strength within the 28-day aging time. Mortar with higher cement replacement had lower water absorption capacity, an indication that the test pozzolan was of smaller particulate size. XRF analysis and the FTIR spectrum showed that the ash has a higher content of silica. The XRD pattern of the ash showed that the ash was predominantly amorphous. SEM images showed that the ash produced at 600 o C had residual carbon material.
The paper contributes to the debate on the political economy of implementation of propoor social policy. It argues for a broadening of the debate, which is dominated by technocratic arguments, emphasizing the lack of financial resources, technology or skills as the major barriers for effective implementation. Describing the dynamic interplay of ‘formal’ operational programme structures and ‘informal’ traditional institutions in delivering the CT-OVC – the largest and oldest cash transfer programme in Kenya – it argues for the need to look more closely into the local political economy as an important mediating arena for implementing social policies. Implementation is heavily contingent upon the local social, political and institutional context that influences and shapes its outcomes. These processes are highly dynamic and ambivalent evolving between ‘formal’ and ‘informal’ structures and institutions. They may change over time and place, challenging the implicit assumption that programmes are evenly implemented across geographic and political entities.
We present the performance of the upGREAT heterodyne array receivers on the SOFIA telescope after several years of operations. This instrument is a multi-pixel high resolution (R≳107) spectrometer for the Stratospheric Observatory for Far-Infrared Astronomy (SOFIA). The receivers use 7-pixel subarrays configured in a hexagonal layout around a central pixel. The low frequency array receiver (LFA) has 2×7 pixels (dual polarization), and presently covers the 1.83–2.07THz frequency range, which allows to observe the [CII] and [OI] lines at 158μm and 145μm wavelengths. The high frequency array (HFA) covers the [OI] line at 63μm and is equipped with one polarization at the moment (7 pixels, which can be upgraded in the near future with a second polarization array). The 4.7THz array has successfully flown using two separate quantum-cascade laser local oscillators from two different groups. NASA completed the development, integration and testing of a dual-channel closed-cycle cryocooler system, with two independently operable He compressors, aboard SOFIA in early 2017 and since then, both arrays can be operated in parallel using a frequency separating dichroic mirror. This configuration is now the prime GREAT configuration and has been added to SOFIA’s instrument suite since observing cycle 6.
3D user interfaces for virtual reality and games: 3D selection, manipulation, and spatial navigation
(2018)
In this course, we will take a detailed look at different topics in the field of 3D user interfaces (3DUIs) for Virtual Reality and Gaming. With the advent of Augmented and Virtual Reality in numerous application areas, the need and interest in more effective interfaces becomes prevalent, among others driven forward by improved technologies, increasing application complexity and user experience requirements. Within this course, we highlight key issues in the design of diverse 3DUIs by looking closely into both simple and advanced 3D selection/manipulation and spatial navigation interface design topics. These topics are highly relevant, as they form the basis for most 3DUI-driven application, yet also can cause major issues (performance, usability, experience. motion sickness) when not designed properly as they can be difficult to handle. Within this course, we build on top of a general understanding of 3DUIs to discuss typical pitfalls by looking closely at theoretical and practical aspects of selection, manipulation, and navigation and highlight guidelines for their use.
Influence of design of extrusion blow molding (EBM) in terms of extrusion direction set-up and draw ratio as well as process conditions (mold temperature) on storage modulus of high density polyethylene EBM containers was analyzed with dynamic mechanical analysis. All three parameters - mold temperature, flow direction and draw ratio - are statistically significant and lead to relative and absolute evaluation of storage modulus. Furthermore, flow induced changes in crystallinity was analyzed by differential scanning calorimetry. Obtained data on deformation properties can be employed for more sophisticated finite element simulations with the aim to reach more sustainable extrusion blow molding production.
Quantifying the spectrum occupancy in an outdoor 5 GHz WiFi network with directional antennas
(2018)
WiFi-based Long Distance networks are seen as a promising alternative for bringing broadband connectivity to rural areas. A key factor for the profitability of these networks is using license free bands. This work quantifies the current spectrum occupancy in our testbed, which covers rural and urban areas alike. The data mining is conducted on the same WiFi card and in parallel with an operational network. The presented evaluations reveal tendencies for various aspects: occupancy compared to population density, occupancy fluctuations, (joint)-vacant channels, the mean channel vacant duration, different approaches to model/forecast occupancy, and correlations among related interfaces.
This paper analyzes the complex effects and risks of social protection programmes in Ghana and Kenya on poor people’s human wellbeing, voice and empowerment and interactions with the social protection regulatory framework and policy instruments. For this purpose, it adopts a comprehensive Inclusive Development framework to systematically explore the complex effects of cash transfers and health insurance at the individual, household and community level. The findings highlight the positive provisionary and preventive effects of social protection, but also illustrate that the poorest are still excluded and that promotive effects, in the form of enhanced productivity, manifest themselves mainly for the people who are less resource poor. They can build more effectively upon an existing asset base, capabilities, power and social relations to counter the exclusionary mechanisms of the system, address inequity concerns and offset the transaction costs of accessing and benefitting from social protection. The inclusive development framework enables to lay these complex effects and interactions bear, and points to areas that require more longitudinal and mixed methodology research.
This paper documents the reversal of pension privatization and the reforms that took place in the 1990s and 2000s in Poland. The report analyses the political economy of different reform proposals, and the characteristics of the new pension system, including laws enacted, coverage, benefit adequacy, financing and contribution rates, governance and social security administration, social dialogue, positive impacts and other key issues of Poland’s pension system.
Poland
(2018)
Poland belongs to the first wave of pension reformers in Central and Eastern Europe. The Polish pension reform of the late 1990s can serve as a case study for the challenges faced when implementing a radical paradigmatic pension reform towards a privatized DC scheme. This report analyses the background of the original reform, discusses its political, social and economic impact and explains the reasons for later reform reversals. The report stresses that the two re-reform waves, which took place in 2011 and 2013, were mainly driven by fiscal considerations. Since the current system maintains the DC scheme applied to both public and private tiers, the recent reversal of privatization will not improve benefit levels.
Adoption of Modern Maize Varieties in India: Insights Based on Expert Elicitation Methodology
(2018)
Digitisation has brought a major upheaval to the mobility sector, and in the future, self-driving cars will probably be one of the transport modes. This study extends transport and user acceptance research by analysing in greater depth how the new modes of autonomous private cars, autonomous carsharing and autonomous taxis fit into the existing traffic mix from today's perspective. It focuses on accounting for relative added value. For this purpose, user preference theory was used as a base for an online survey (n=172) on the relative added value of the new autonomous traffic modes. Results show that users see advantages in the autonomous modes for driving comfort and time utilization whereas, in comparison to conventional cars, in many other areas – especially in terms of driving pleasure and control – they see no advantages or even relative disadvantages. Compared to public transport, the autonomous modes offer added values in almost all characteristics. This analysis at the partwor th level provides a more detailed explanation for user acceptance of automated driving.
Shared Autonomous Vehicles: Potentials for a Sustainable Mobility and Risks of Unintended Effects
(2018)
Automated and connected cars could significantly reduce congestion and emissions through a more efficient flow of traffic and a reduction in the number of vehicles. An increase in demand for driving with autonomous vehicles is also conceivable due to higher comfort and improved quality of time using driverless cars. So far, empirical evidence supporting this hypothesis is missing. To analyze the influence of autonomous driving on mobility behavior and to uncover user preferences, which serve as an indicator for future travel mode choices, we conducted an online survey with a paired comparison of current and future travel modes with 302 German participants. The results do not confirm the hypothesis that ownership will become an outdated model in the future. Instead they suggest that private cars, whether traditional or fully automated, will remain the preferred travel mode. At the same time, carsharing will benefit from full automation more than private cars. However, findings indicate that the growth of carsharing will mainly be at the expense of public transport, showing that more effort should be placed in making public transportation more attractive if sustainable mobility is to be developed.
Innovations in the mobility industry such as automated and connected cars could significantly reduce congestion and emissions by allowing the traffic to flow more freely and reducing the number of vehicles according to some researchers. However, the effectiveness of these sustainable product and service innovations is often limited by unexpected changes in consumption: some researchers thus hypothesize that the higher comfort and improved quality of time in driverless cars could lead to an increase in demand for driving with autonomous vehicles. So far, there is a lack of empirical evidence supporting either one or other of these hypotheses. To analyze the influence of autonomous driving on mobility behavior and to uncover user preferences, which serve as indicators for future travel mode choices, we conducted an online survey with a paired comparison of current and future travel modes with 302 participants in Germany. The results do not confirm the hypothesis that ownership will become an outdated model in the future. Instead they suggest that private cars, whether conventional or fully automated, will remain the preferred travel mode. At the same time, carsharing will benefit from full automation more than private cars. However, the findings indicate that the growth of carsharing will mainly be at the expense of public transport, showing that more emphasis should be placed in making public transport more attractive if sustainable mobility is to be developed.
The labor market is dynamic and frequently calls for new skills, knowledge, and abilities. The changing needs of industry place a higher demand on institutions of higher learning to monitor trends in labor needs, identify skill gaps, and to use industry insights for developing programs and curricula that mold human resources to create value for employers and society at large. While several institutions of higher learning are responsive to industry needs through curricula reviews and the development of new programs, little attention is given to pedagogical issues that affect the delivery of knowledge and the development of skills intended by various education programs. Consequently, teachers are entrusted with the freedom to decide the teaching methods that are appropriate under each circumstance. Despite the changing face of the labor market, not much energy has been channeled towards adjusting teaching methods for effective delivery of skills required by students. The failure to adjust teaching methods for training graduates has led to what is commonly known as ‘halfbaked graduates’. In other words, graduates who lack the skills and abilities necessary for placement in the industry. However, the success of an institution of higher learning is illustrated by its ability to train people who perfectly match the needs of the industry.
Culture is the constellation of shared believes, mores, values, and traditions that define the behavior of people and it is unique to each community at local and national levels. Culture determines the languages spoken by the people, their attitude towards others, and their behavior. While the family is the immediate point through which culture is learned by children, socialization at institutions such as religious organizations, places of worship, schools, and the society’s dispute resolution system reinforce culture. Unlike the Internet, traditional media in the forms of local and national print and audio-visual content tend to reinforce cultural beliefs, values, and practices of specific communities. The uniqueness of culture creates market penetration challenges to entrepreneurs in international markets. Therefore, intercultural communication is a necessary skill for reducing cultural liability and increasing the success of entrepreneurial ventures.
Small Molecules Enhance Scaffold-Based Bone Grafts via Purinergic Receptor Signaling in Stem Cells
(2018)
The need for bone grafts is high, due to age-related diseases, such as tumor resections, but also accidents, risky sports, and military conflicts. The gold standard for bone grafting is the use of autografts from the iliac crest, but the limited amount of accessible material demands new sources of bone replacement. The use of mesenchymal stem cells or their descendant cells, namely osteoblast, the bone-building cells and endothelial cells for angiogenesis, combined with artificial scaffolds, is a new approach. Mesenchymal stem cells (MSCs) can be obtained from the patient themselves, or from donors, as they barely cause an immune response in the recipient. However, MSCs never fully differentiate in vitro which might lead to unwanted effects in vivo. Interestingly, purinergic receptors can positively influence the differentiation of both osteoblasts and endothelial cells, using specific artificial ligands. An overview is given on purinergic receptor signaling in the most-needed cell types involved in bone metabolism-namely osteoblasts, osteoclasts, and endothelial cells. Furthermore, different types of scaffolds and their production methods will be elucidated. Finally, recent patents on scaffold materials, as wells as purinergic receptor-influencing molecules which might impact bone grafting, are discussed.
Improving the Performance of Parallel SpMV Operations on NUMA Systems with Adaptive Load Balancing
(2018)
For a parallel Sparse Matrix Vector Multiply (SpMV) on a multiprocessor, rather simple and efficient work distributions often produce good results. In cases where this is not true, adaptive load balancing can improve the balance and performance. This paper introduces a low overhead framework for adaptive load balancing of parallel SpMV operations. It uses statistical filters to gather relevant runtime performance data and detects an imbalance situation. Three different algorithms were compared that adaptively balance the load with high quality and low overhead. Results show that for sparse matrices, where the adaptive load balancing was enabled, an average speedup of 1.15 (regarding the total execution time) could be achieved with our best algorithm over 4 different matrix formats and two different NUMA systems.
Solar energy plants are one of the key options to serve the rising global energy need with low environmental impact. Aerosols reduce global solar radiation due to absorption and scattering and therewith solar energy yields. Depending on the aerosol composition and size distribution they reduce the direct component of the solar radiation and modify the direction of the diffuse component compared to standard atmospheric conditions without aerosols.
This case study is based on Azuri Health Ltd, a small company in Kenya that specializes mainly in the manufacture of dried fruit and flours. The company was started in 2010 and currently has 15 employees. It buys fruits, especially mangoes from farmers, processes them and markets them in- and outside of Kenya as dried fruits. This value addition enhances the shelf life of the products which would otherwise spoil within a few days after ripening.
The exchange program enables students to travel from their home countries to a partner university in the German-African University project. Students from the University of Nairobi in Kenya and University of Cape Coast in Ghana travel to the Hochschule Bonn-Rhein-Sieg University of Applied Sciences and stay for three months attending classes and participating in academic activities together with German students. Similarly, students from Hochschule Bonn-Rhein-Sieg, University of Applied Sciences, travel to either West or East Africa and are hosted for three months by universities participating in the project. The program enables Kenyan students to accustom themselves to the German way of life and student-centered learning and disciplines. The program integrates fieldwork into the learning activities making education both a skill-imparting and fun process.
General Chair Message
(2018)
Robot deployment in realistic environments is challenging despite the fact that robots can be quite skilled at a large number of isolated tasks. One reason for this is that robots are rarely equipped with powerful introspection capabilities, which means that they cannot always deal with failures in an acceptable manner; in addition, manual diagnosis is often a tedious task that requires technicians to have a considerable set of robotics skills. In this paper, we discuss our ongoing efforts to address some of these problems. In particular, we (i) present our early efforts at developing a robotic black box and consider some factors that complicate its design, (ii) explain our component and system monitoring concept, and (iii) describe the necessity for remote monitoring and experimentation as well as our initial attempts at performing those. Our preliminary work opens a range of promising directions for making robots more usable and reliable in practice.
Robot deployment in realistic dynamic environments is a challenging problem despite the fact that robots can be quite skilled at a large number of isolated tasks. One reason for this is that robots are rarely equipped with powerful introspection capabilities, which means that they cannot always deal with failures in a reasonable manner; in addition, manual diagnosis is often a tedious task that requires technicians to have a considerable set of robotics skills.
Companies investing in the occupied Palestinian territories are faced with a dilemma. Undoubtedly, the creation of jobs helps to put young Palestinians to work. Experience shows that especially young males are less likely to radicalise and commit crimes when having an occupation. However, negative press coverage due to the disputed status of the territory can force companies to withdraw. CSR activities can help to demonstrate that a company has a genuine interest in its employees and community at large. Our article looks into one particular case of an Israeli company that had to withdraw their operation due to public pressure, mainly Western media. We give recommendations how such failure could have been avoided by using the right kind of CSR activities that address the needs of the Palestinians.
In 2018, in the US alone, it is estimated that 268,670 people will be diagnosed with breast cancer, and that 41,400 will die from it. Since breast cancers often become resistant to therapies, and certain breast cancers lack therapeutic targets, new approaches are urgently required. A cell-stress response pathway, the unfolded protein response (UPR), has emerged as a promising target for the development of novel breast cancer treatments. This pathway is activated in response to a disturbance in endoplasmic reticulum (ER) homeostasis but has diverse physiological and disease-specific functions. In breast cancer, UPR signalling promotes a malignant phenotype and can confer tumours with resistance to widely used therapies. Here, we review several roles for UPR signalling in breast cancer, highlighting UPR-mediated therapy resistance and the potential for targeting the UPR alone or in combination with existing therapies.
Preleukemic clones carrying BCR-ABLp190 oncogenic lesions are found in neonatal cord blood, where the majority of preleukemic carriers do not convert into precursor B-cell acute lymphoblastic leukemia (pB-ALL). However, the critical question of how these preleukemic cells transform into pB-ALL remains undefined. Here we model a BCR-ABLp190 preleukemic state and show that limiting BCR-ABLp190 expression to hematopoietic stem/progenitor cells (HS/PC) in mice (Sca1-BCR-ABLp190) causes pB-ALL at low penetrance, which resembles the human disease. pB-ALL blast cells were BCR-ABL-negative and transcriptionally similar to pro-B/pre-B cells, suggesting disease onset upon reduced Pax5 functionality. Consistent with this, double Sca1-BCR-ABLp190+Pax5+/- mice developed pB-ALL with shorter latencies, 90% incidence, and accumulation of genomic alterations in the remaining wild-type Pax5 allele. Mechanistically, the Pax5-deficient leukemic pro-B cells exhibited a metabolic switch towards increased glucose utilization and energy metabolism. Transcriptome analysis revealed that metabolic genes (IDH1, G6PC3, GAPDH, PGK1, MYC, ENO1, ACO1) were upregulated in Pax5-deficient leukemic cells, and a similar metabolic signature could be observed in human leukemia. Our studies unveil the first in vivo evidence that the combination between Sca1-BCR-ABLp190 and metabolic reprogramming imposed by reduced Pax5 expression is sufficient for pB-ALL development. These findings might help to prevent conversion of BCR-ABLp190 preleukemic cells.
We present a novel forearm-and-glove tactile interface that can enhance 3D interaction by guiding hand motor planning and coordination. In particular, we aim to improve hand motion and pose actions related to selection and manipulation tasks. Through our user studies, we illustrate how tactile patterns can guide the user, by triggering hand pose and motion changes, for example to grasp (select) and manipulate (move) an object. We discuss the potential and limitations of the interface, and outline future work.
In presence of conflicting or ambiguous visual cues in complex scenes, performing 3D selection and manipulation tasks can be challenging. To improve motor planning and coordination, we explore audio-tactile cues to inform the user about the presence of objects in hand proximity, e.g., to avoid unwanted object penetrations. We do so through a novel glove-based tactile interface, enhanced by audio cues. Through two user studies, we illustrate that proximity guidance cues improve spatial awareness, hand motions, and collision avoidance behaviors, and show how proximity cues in combination with collision and friction cues can significantly improve performance.
The use of wearable devices or “wearables” in the physical activity domain has been increasing in the last years. These devices are used as training tools providing the user with detailed information about individual physiological responses and feedback to the physical training process. Advantages in sensor technology, miniaturization, energy consumption and processing power increased the usability of these wearables. Furthermore, available sensor technologies must be reliable, valid, and usable. Considering the variety of the existing sensors not all of them are suitable to be integrated in wearables. The application and development of wearables has to consider the characteristics of the physical training process to improve the effectiveness and efficiency as training tools. During physical training, it is essential to elicit individual optimal strain to evoke the desired adjustments to training. One important goal is to neither overstrain nor under challenge the user. Many wearables use heart rate as indicator for this individual strain. However, due to a variety of internal and external influencing factors, heart rate kinetics are highly variable making it difficult to control the stress eliciting individually optimal strain. For optimal training control it is essential to model and predict individual responses and adapt the external stress if necessary. Basis for this modeling is the valid and reliable recording of these individual responses. Depending on the heart rate kinetics and the obtained physiological data, different models and techniques are available that can be used for strain or training control. Aim of this review is to give an overview of measurement, prediction, and control of individual heart rate responses. Therefore, available sensor technologies measuring the individual heart rate responses are analyzed and approaches to model and predict these individual responses discussed. Additionally, the feasibility for wearables is analyzed.
Triple-negative breast cancer (TNBC) lacks targeted therapies and has a worse prognosis than other breast cancer subtypes, underscoring an urgent need for new therapeutic targets and strategies. IRE1 is an endoplasmic reticulum (ER) stress sensor, whose activation is predominantly linked to the resolution of ER stress and, in the case of severe stress, to cell death. Here we demonstrate that constitutive IRE1 RNase activity contributes to basal production of pro-tumorigenic factors IL-6, IL-8, CXCL1, GM-CSF, and TGFβ2 in TNBC cells. We further show that the chemotherapeutic drug, paclitaxel, enhances IRE1 RNase activity and this contributes to paclitaxel-mediated expansion of tumor-initiating cells. In a xenograft mouse model of TNBC, inhibition of IRE1 RNase activity increases paclitaxel-mediated tumor suppression and delays tumor relapse post therapy. We therefore conclude that inclusion of IRE1 RNase inhibition in therapeutic strategies can enhance the effectiveness of current chemotherapeutics.
Consolidating Principles and Patterns for Human-centred Usable Security Research and Development
(2018)
We present an evaluation of usable security principles and patterns to facilitate the transfer of existing knowledge to researchers and practitioners. Based on a literature review we extracted 23 common usable security principles and 47 usable security patterns 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 and patterns. The tool enables users to search for relevant patterns and explore them in an interactive and programmatic manner. We argue that both the insights presented in this paper and the repository will be highly valuable for students for getting a good overview, practitioners for implementing usable security and researchers for identifying areas of future research.
More and more low-power wide-area networks (LPWANs) are being deployed and planning the gateway locations plays a significant role for the network range, performance and profitability. We choose LoRa as one LPWAN technology and evaluated the accuracy of the Received Signal Strength Indication (RSSI) of different chipsets in a laboratory environment. The results show the chipsets report significantly different RSSI. To estimate the range of a LPWAN beforehand, path loss models have been proposed. Compared to previous work, we evaluated the Longley-Rice Irregular Terrain Model which makes use of real-world elevation data to predict the path loss. To verify the results of that prediction, an extensive measurements campaign in a semi-urban area in Germany has been conducted. The results show that terrain data can increase the prediction accuracy.
In this paper we propose an architecture to integrate classical planning and real autonomous mobile robots. We start by providing with a high level description of all necessary components to set the goals, generate plans and execute them on real robots and monitor the outcome of their actions. At the core of our method and to deal with execution issues we code the agent actions with automatas. We prove the flexibility of the system by testing on two different domains: industrial (Basic Transportation Test) and domestic (General Purpose Service Robot) in the context of the international RoboCup competition. Additionally we benchmark the scalability of the planning system in two domains on a set of planning problems with increasing complexity. The proposed framework is open source1 and can be easily extended.
Transition point prediction in a multicomponent lattice Boltzmann model: Forcing scheme dependencies
(2018)
This policy brief is part of a wider research project entitled ‘Building the Economic Case for Investments in Social Protection’. The research aims at demonstrating the potential impacts of social protection on inclusive growth. The project is a collaborative effort between the Maastricht Graduate School of Governance at the University of Maastricht and United Nations University-MERIT, NL; the Global Development Institute at the University of Manchester, UK; the School of Social Science at the University of Makerere, Uganda; and the Expanding Social Protection Programme of the Ugandan Ministry of Gender, Labour and Social Development. This project is part of the research agenda of the Knowledge Platform Inclusive Development Policies and funded by the Ministry of Foreign Affairs of the Netherlands through the NWO-WOTRO programme.
For the last 20 years, solid-phase microextraction (SPME) in headspace (HS) mode has been used as a valuable sample preparation technique for identifying degradation products in polymers and the determination of residual monomers and other light-boiling substances in polymeric materials. For more than 10 years, our laboratory has been involved in projects focused on the application of HS-SPME-gas chromatography–mass spectrometry (GC–MS) for the characterization of polymeric materials from many branches of manufacturing and building industries. This article describes the application of this technique for identifying volatile organic compounds (VOCs), additives, and degradation products in industrial rubber, car labeling reflection foil, and bone cement materials. The obtained analytical results were then used for troubleshooting and remedial action of the technological processes as well as for the health protection of producers and users.