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In order to achieve the highest possible performance, the ray traversal and intersection routines at the core of every high-performance ray tracer are usually hand-coded, heavily optimized, and implemented separately for each hardware platform—even though they share most of their algorithmic core. The results are implementations that heavily mix algorithmic aspects with hardware and implementation details, making the code non-portable and difficult to change and maintain.
In this paper, we present a new approach that offers the ability to define in a functional language a set of conceptual, high-level language abstractions that are optimized away by a special compiler in order to maximize performance. Using this abstraction mechanism we separate a generic ray traversal and intersection algorithm from its low-level aspects that are specific to the target hardware. We demonstrate that our code is not only significantly more flexible, simpler to write, and more concise but also that the compiled results perform as well as state-of-the-art implementations on any of the tested CPU and GPU platforms.
Solar energy is one option to serve the rising global energy demand with low environmental impact. Building an energy system with a considerable share of solar power requires long-term investment and a careful investigation of potential sites. Therefore, understanding the impacts from varying regionally and locally determined meteorological conditions on solar energy production will influence energy yield projections.
Reliable and regional differentiated power forecasts are required to guarantee an efficient and economic energy transition towards renewable energies. Amongst other renewable energy technologies, e.g. wind mills, photovoltaic (PV) systems are an essential component of this transition being cost-efficient and simply to install. Reliable power forecasts are however required for a grid integration of photovoltaic systems, which among other data requires high-resolution spatio-temporal global irradiance data.
In silico Epitope Mapping of Glucose-6-Phosphate Isomerase: A Rheumatoid Arthritis Autoantigen
(2017)
Rheumatoid arthritis-like symptoms can be initiated experimentally in naive K/BxN mice by simultaneously administering the two monoclonal antibodies 11H3 and 46H9. Both antibodies specifically recognize Glucose-6-Phosphate Isomerase (GPI), a known auto antigen in RA patients. Amino acid sequences of the Fv parts of the antibodies were determined by translating the respective hybridoma DNA sequences and served for threedimensional structure modeling of the paratope regions. In silico docking of both Fv antibody structure models to the X-ray structures of the homodimeric murine GPI as well as to the homodimeric human GPI predicted the murine epitope of the 11H3 antibodies to comprise partial amino acid sequences QRVRSGDWKGYTGKS (aa134-148) and AAKDPSAVAK (aa232-241), generating an assembled (conformational) epitope. The 11H3 epitope on human GPI encompasses the matching partial amino acid sequences QRVRSGDWKGYTGKT (aa134-148) and AAKDPSAVAK (aa232-241). The epitope of the 46H9 antibody was determined to consist of the partial murine GPI amino acid sequence RKELQAAGKSPEDLEK (aa446-461) and the human GPI amino acid sequence RKELQAAGKSPEDLER (aa446-461), respectively, resembling consecutive (linear) epitopes. The predicted epitopes were verified by mass spectrometric epitope mapping using synthetic epitope peptides. Peptide QRVRSGDWKGYTGKS[GSMSGS] AAKDPSAAK included a small spacer sequence in between the epitope sequences, mimicking the assembled epitope for the 11H3 antibody. The peptide RKELQAAGKSPEDLEK represented the consecutive epitope for the 46H9 antibody. The determined B-cell epitopes of GPI and their interactions with the monoclonal antibodies provide a detailed structural understanding of immunological disease onset mechanisms in a mouse model of rheumatoid arthritis.
This paper presents the b-it-bots RoboCup@Work team and its current hardware and functional architecture for the KUKA youBot robot. We describe the underlying software framework and the developed capabilities required for operating in industrial environments including features such as reliable and precise navigation, flexible manipulation and robust object recognition.
An Experimental Field-Study on Active and Passive Work Breaks in a Stressful Work Environment
(2017)
Work breaks are known to have positive effects on employees’ health, performance, and safety. However, prior research has focused mainly on their timing, duration, and frequency but less on break activities. Moreover, most studies examined work breaks in rather repetitive and physical demanding work. Thus, we conducted an experimental field study with a sample of employees’ working in a stressful and cognitive demanding working environment and examined how different types of work breaks (boxing, deep relaxation, and usual breaks) affect participants’ mood, cognitive performance, and neuro-physiological state.
This paper proposes a novel approach to the generation of state equations from a bond graph (BG) of a mode switching linear time invariant model. Fast state transitions are modelled by ideal or non-ideal switches. Fixed causalities are assigned following the Standard Causality Assignment Procedure such that the number of storage elements in integral causality is maximised. A system of differential and algebraic equations (DAEs) is derived from the BG that holds for all system modes. It is distinguished between storage elements with mode independent causality and those that change causality due to switch state changes.
This study aims to highlight the significance of social protection as an autonomous strategy for migration policies and research. It focuses particularly on the German strategies for combating the causes of flight and migration. By managing migration flows, stabilizing societies and encouraging economic development, social protection can play an important role in reducing migration flows. At the same time, social protection can act as a stabilizer in the countries of origin and accelerate economic growth as well as supporting individual decisions to return to the countries of origin.
Enterprises demand universities not to limit education to theoretical knowledge, but instead, to prepare students for future challenges in the job. While demanding a focus on current technologies and practices appears reasonable, it contradicts academia’s general focus on sustainable knowledge. This “conflict-ofinterest” can be bridged through extra-curricular professional training. MOOCs are hyped as solution because they allow to simultaneously addressing masses of students. However, with the increasing number of learners, anonymity in education increases and first-level support decreases. Within the extracurricular online program erp4students we found that individual support is considered most relevant to successfully complete professional training.
The technological development of the digital computer and new options to collect, store and transfer mass data have changed the world in the last 40 years. Moreover, due to the ongoing progress of computer power, the establishment of the Internet as critical infrastructure and the options of ubiquitous sensor systems will have a dramatic impact on economies and societies in the future. We give a brief overview about the technological basics especially with regard to the exponential growth of big data and current turn towards sensor-based data collection. From this stance, we reconsider the various dimensions of personal data and and market mechanisms that have an impact of data usage and protection.
Continued growth in international experiences for U.S. co++6llege students is a favorable trend. However, the most substantial increase has occurred with of short-term study abroad programs. Many of these programs include extensive travel instead of involving a single site. There is great danger that if not properly managed, these types of international educational experience will default into little more than an organized group tour.
In these types of programs it is challenging to induce student participants to engage meaningfully with local residents as the traveling group tends to form into its own portable society. In addition, the current state of wireless communications means that students participating in these types of programs can easily stay plugged into their home social networks which further reduces meaningful interactions in the cultures being visited.
Incorporating well designed research projects into short-term study abroad programs holds the potential to offset some of the inherent limitations of such programs. Research projects can serve both to prepare the students for the trip and promote meaningful cross-cultural interaction while the program is underway.
In this paper, the authors provide suggestions based on their experiences with short-term travel abroad programs which incorporated student research. Several potential problems are identified and suggestions are given for project design.
Raman-microspectroscopy was used for the non-destructive characterization and differentiation of six different meat spoilage associated microorganisms, namely Brochothrix thermosphacta DSM 20171, Micrococcus luteus, Pseudomonas fluorescens DSM 4358, Escherichia coli Top10 and K12 and Pseudomonas fluorescens DSM 50090. To evaluate and classify the Raman-spectroscopic data at species and strain level an adequate preprocessing and subsequent principal component analysis was used. The same procedure was extended to an independent test data set, which could be successfully assigned to the correct bacterial species and even to the right strain. The evaluation was not only successful in differentiation of gram-positive and gram-negative bacteria but also the discrimination between the different bacterial species and strains was possible. This means that the training data set, the preprocessing method and the evaluation of the data lead to a robust principal component analysis. Even the correct assignment of unknown samples is possible. The results show that Raman-microspectroscopy in combination with an appropriate chemometric treatment can be a good tool for a rapid examination and classification of microbial cultures.
Diese Arbeit beschäftigt sich mit der Effizienz der Seitenkanal-Kryptanalyse. In Teil II dieser Arbeit demonstrieren wir, wie die Laufzeit der wichtigsten Analysewerkzeuge mit Hilfe der CUDA Plattform erheblich gesteigert werden kann. Zweitens untersuchen wir neue Ansätze der profilierenden Seitenkanal-Kryptanalyse. Der Forschungszweig des maschinellen Lernens kann für deutliche Verbesserungen adaptiert werden, wurde jedoch wenig dahingehend untersucht. In Teil III dieser Arbeit präsentieren wir zwei neue Methoden, die einige Gemeinsamkeiten jedoch auch einige Unterschiede aufbieten, sodass sich Prüfergebnisse in einem vollständigeren Bild zeigen lassen. Darüber hinaus schlagen wir in Teil IV eine Seitenkanalanwendung zum Schutz geistigen Eigentums (IP) vor. In Teil V beschäftigen wir uns tiefergehend mit praktischer Seitenkanal-Kryptanalyse, indem wir Attacken auf einen Sicherheitsmikrokontroller durchführen, der Anwendung in einer, in Deutschland weit verbreiteten, EC Karte findet.
Do remittances and social assistance transfers have different impacts on household’s expenditure patterns? While two separate strands of literature have looked at how social assistance or remittances have been spent, few studies have compared them directly. Using data from a household survey conducted in Moldova in 2011, this paper assesses the impact both types of transfers have on household expenditure patterns. Contrary to the common assumption that money is fungible, we find that social assistance and remittances have different impacts on expenditure patterns (having controlled for potential endogeneity). In other words, where the income comes from can determine how it is spent. As such, different sources of income may have different poverty impacts. In our sample, the two types of transfers are received by different, but slightly overlapping population groups. The fact that the two transfers are spent in different ways means that, to some extent, social assistance and remittances are complements rather than substitutes.
Mutations in SELENBP1, encoding a novel human methanethiol oxidase, cause extraoral halitosis
(2017)
This study deals with the in-situ detection of volume fractions of melt in labradorite and basalt at 0.3 GPa pressure and temperatures ranging from 400–1500 °C. Methods used were frequency dependent electrical conductivity (EC) and energy dispersive X-ray diffraction (EDX). These techniques allowed melt fraction determination under in-situ pressure and temperature conditions, while optical analysis (SEM) was performed on quenched samples. EC allowed detecting melt frac- tions as low as 0.03 due to changes in dielectric properties. Increasing melt fractions caused the formerly isolated melt bubbles to interconnect along grain boundaries, thus increasing the bulk conductivity. Electrical conductivity thus provides a measure for both, the formation of melt (dielectric property) and the degree of interconnection of melt (bulk conductivity). Energy dispersive X-ray diffraction experiments (EDX) provided an additional measure for the volume fraction of melt. EDX diffraction data were used to calculate the volume fraction of melt on the basis of the peak to background ratio. In a final step the experimental data (SEM, EC, EDX) were compared with geometric models of melt distribution, namely the Archie-, cube-, tube-, Hashin-Shtrikman HS + and HS - model. The electrical "polarisability" data closely fit the HS + model, while bulk conductivity data were found to be less sensitive for melt fraction detection.
Traditionally automotive UI focusses on the ergonomic design of controls and the user experience in the car. Bringing networked sensors into the car, connected cars can provide additional information to car drivers and owners, for and beyond the driving task. While there already are technological solutions, such as mobile applications commercially available, research on users’ information demands in such applications is scarce. We conducted four focus groups to uncover what kind of information users might be interested in to see on a second dashboard. Our findings show that besides control screens of todays’ dashboards, people are also interested in connected car services providing context information for a current driving situation and allowing strategic planning of driving safety or supporting car management when not driving. Our use cases inform the design of content for secondary dashboards for and especially beyond the driving context with a user perspective.
Background and Objectives: In advanced β-cell dysfunction, proinsulin is increasingly replacing insulin as major component of the secretion product. It has been speculated that proinsulin has at least the same adipogenic potency than insulin, leading to an increased tendency of lipid tissue formation in patients with late stage β-cell dysfunction. Methods and Results: Mesenchymal stem cells obtained from liposuction material were grown in differentiation media containing insulin (0.01 μmol), proinsulin (0.01 μmol) or insulin+proinsulin (each 0.005 μmol). Cell culture supernatants were taken from these experiments and an untreated control at weeks 1, 2, and 3, and were stored at -80°C until analysis. Cell differentiation was microscopically supervised and adiponectin concentrations were measured as marker for differentiation into mature lipid cells. This experiment was repeated three times. No growth of lipid cells and no change in adiponectin values was observed in the negative control group (after 7/14/12 days: 3.2±0.5/3.3±0.1/4.4±0.5 ng/ml/12 h). A continuous differentiation into mature adipocytes (also confirmed by Red-Oil-staining) and a corresponding increase in adiponectin values was observed in the experiments with insulin (3.6±1.9/5.1±1.4/13.3±1.5 ng/ml/12 h; p<0.05 week 1 vs. week 3) and proinsulin (3.3±1.2/3.5±0.3/12.2±1.2 ng/ml/12 h; p<0.05). Comparable effects were seen with the insulin/proinsulin combination. Conclusions: Proinsulin has the same adipogenic potential than insulin in vitro. Proinsulin has only 10∼20% of the glucose-lowering effect of insulin. It can be speculated that the adipogenic potential of proinsulin may be a large contributor to the increased body weight problems in patients with type 2 diabetes and advanced β-cell dysfunction.
As robots are becoming ubiquitous and more capable, the need for introducing solid robot software development methods is pressing to increase robots' task spectrum. This thesis is concerned with improving software engineering of robot perception systems. The presented research employs a model-based approach to provide the means to represent knowledge about robotics software. The thesis is divided into three parts, namely research on the specification, deployment and adaptation of robot perception systems.
Human butyrylcholinesterase (BChE) is a glycoprotein capable of bioscavenging toxic compounds such as organophosphorus (OP) nerve agents. For commercial production of BChE, it is practical to synthesize BChE in non-human expression systems, such as plants or animals. However, the glycosylation profile in these systems is significantly different from the human glycosylation profile, which could result in changes in BChE's structure and function. From our investigation, we found that the glycan attached to ASN241 is both structurally and functionally important due to its close proximity to the BChE tetramerization domain and the active site gorge. To investigate the effects of populating glycosylation site ASN241, monomeric human BChE glycoforms were simulated with and without site ASN241 glycosylated. Our simulations indicate that the structure and function of human BChE are significantly affected by the absence of glycan 241.
“Building Bridges Across Continents” (BBAC) is an intercultural and student-centered project that seeks to promote international communication and helps students develop competencies in entrepreneurship, international trade and global cultural awareness. The project, which is in its fourth phase of implementation, connects students from the United States, Germany, Ghana and Kenya with the help of Information Communication Technologies (ICT) in order to work on a common research assignment for a period of ten calendar weeks. The main ICTs used in the project are Skype, Facebook, wiki, email and WhatsApp. This paper describes and analyzes the background, structure, and results of the project.
Higher Education Institutions (HEIs) should, on the one hand, provide theoretical and practical knowledge to students and, on the other hand, make valuable contributions to theoretical knowledge and provide new insights by means of research. However, HEIs have to face changing and increasing demands with respect to what they are expected to achieve. Education and research issues are no longer enough, what matters today is the so called “third mission”. A specific example for implementing a third mission is the cooperation between HEIs and business incubators. With this in mind, a local consortium consisting of regional HEIs, e.g. Bonn-Rhein-Sieg University of Applied Sciences, as well as public and private institutions and partners initiated and established an incubator hub for the region Bonn/Rhein-Sieg in 2016, called “Digital Hub Region Bonn”. This conference contribution reports on our experience with regards to this cooperation approach resulting from the above- mentioned case. Furthermore the pros and cons as well as some issues of this kind of cooperation will be discussed. Last but not least this paper initiates the opportunity to share and compare the experiences of other university business incubators in Africa as well as in Germany. As we will describe, the financial investment of HEIs in a joint-incubator with other public as well as private partners offers substantial benefits, such as mutual know-how transfer from HEIs to the economy and vice versa. This strengthens entrepreneurial mindsets and activities and contributes to the development and growth of the local economy. Consequently, this cooperation sometimes creates challenges at various levels, for example due to differing interests between HEIs and business partners. This conference contribution offers approaches to solve these issues and to support private public partnership in business incubation.
Current global challenges such as climate change, lack of resources, desertification, land degradation as well as loss of biodiversity can ultimately be due to human actions. Reasons are excessive production and consumption of goods and services, along with using and consuming natural resources, causing emissions and waste products. Demand in the form of consumption and supply in the form of production are closely intertwined.
The detection of human skin in images is a very desirable feature for applications such as biometric face recognition, which is becoming more frequently used for, e.g., automated border or access control. However, distinguishing real skin from other materials based on imagery captured in the visual spectrum alone and in spite of varying skin types and lighting conditions can be dicult and unreliable. Therefore, spoofing attacks with facial disguises or masks are still a serious problem for state of the art face recognition algorithms. This dissertation presents a novel approach for reliable skin detection based on spectral remission properties in the short-wave infrared (SWIR) spectrum and proposes a cross-modal method that enhances existing solutions for face verification to ensure the authenticity of a face even in the presence of partial disguises or masks. Furthermore, it presents a reference design and the necessary building blocks for an active multispectral camera system that implements this approach, as well as an in-depth evaluation. The system acquires four-band multispectral images within T = 50ms. Using a machine-learning-based classifier, it achieves unprecedented skin detection accuracy, even in the presence of skin-like materials used for spoofing attacks. Paired with a commercial face recognition software, the system successfully rejected all evaluated attempts to counterfeit a foreign face.
Synthesis of serving policies for objects flow in the system with refillable storage component
(2017)
Current robot platforms are being employed to collaborate with humans in a wide range of domestic and industrial tasks. These environments require autonomous systems that are able to classify and communicate anomalous situations such as fires, injured persons, car accidents; or generally, any potentially dangerous situation for humans. In this paper we introduce an anomaly detection dataset for the purpose of robot applications as well as the design and implementation of a deep learning architecture that classifies and describes dangerous situations using only a single image as input. We report a classification accuracy of 97 % and METEOR score of 16.2. We will make the dataset publicly available after this paper is accepted.
Today, more than 70 million tons of lignin are produced by the pulp and paper industry every year. However, the utilization of lignin as a source for chemical synthesis is still limited due to the complex and heterogeneous lignin structure. The purpose of this study was a selective photodegradation of industrially available kraft lignin in order to obtain appropriate fragments and building block chemicals for further utilization, e.g. polymerization. Thus, kraft lignin obtained from soft wood black liquor by acidification was dissolved in sodium hydroxide and irradiated at a wavelength of 254 nm with and without the presence of titanium dioxide in various concentrations. Analyses of the irradiated products via SEC showed decreasing molar masses and decreasing polydispersity indices over time. At the end of the irradiation period the lignin was depolymerised to form fragments as small as the lignin monomers. TOC analyses showed minimal mineralisation due to the depolymerisation process.
This work presents the analysis of data recorded by an eye tracking device in the course of evaluating a foveated rendering approach for head-mounted displays (HMDs). Foveated rendering methods adapt the image synthesis process to the user’s gaze and exploiting the human visual system’s limitations to increase rendering performance. Especially, foveated rendering has great potential when certain requirements have to be fulfilled, like low-latency rendering to cope with high display refresh rates. This is crucial for virtual reality (VR), as a high level of immersion, which can only be achieved with high rendering performance and also helps to reduce nausea, is an important factor in this field. We put things in context by first providing basic information about our rendering system, followed by a description of the user study and the collected data. This data stems from fixation tasks that subjects had to perform while being shown fly-through sequences of virtual scenes on an HMD. These fixation tasks consisted of a combination of various scenes and fixation modes. Besides static fixation targets, moving tar- gets on randomized paths as well as a free focus mode were tested. Using this data, we estimate the precision of the utilized eye tracker and analyze the participants’ accuracy in focusing the displayed fixation targets. Here, we also take a look at eccentricity-dependent quality ratings. Comparing this information with the users’ quality ratings given for the displayed sequences then reveals an interesting connection between fixation modes, fixation accuracy and quality ratings.
The Sparse Matrix Vector Multiplication is an important operation on sparse matrices. This operation is the most time consuming operation in iterative solvers and therefore an efficient execution of that operation is of great importance for many applications. Numerous different storage formats that store sparse matrices efficiently have already been established. Often, these storage formats utilize the sparsity pattern of a matrix in an appropiate manner. For one class of sparse matrices the nonzero values occur in small dense blocks and appropriate block storage formats are well suited for such patterns. But on the other side, these formats perform often poor on general matrices without an explicit / regular block structure. In this paper, the newly developed sparse matrix format DynB is introduced. The aim is to efficiently use several optimization approaches and vectorization with current processors, even for matrices without an explicit block structure of nonzero elements. The DynB matrix format uses 2D rectangular blocks of variable size, allowing fill-ins per block of explicit zero values up to a user controllable threshold. We give a simple and fast heuristic to detect such 2D blocks in a sparse matrix. The performance of the Sparse Matrix Vector Multiplication for a selection of different block formats and matrices with different sparsity structures is compared. Results show that the benefit of blocking formats depend – as to be expected – on the structure of the matrix and that variable sized block formats like DynB can have advantages over fixed size formats and deliver good performance results even for general sparse matrices.