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Yams of the most widely differing nature are produced in textile mills. The production stages necessary for this are carried out with the aid of textile machines. Between these individual textile machines - from cards to spinning machines - sliver cans serve as a rule as transport containers, in which the sensitive sliver material is temporarily stored, and presented to the next production stage.
Bond graph modelling was devised by Professor Paynter at the Massachusetts Institute of Technology in 1959 and subsequently developed into a methodology for modelling multidisciplinary systems at a time when nobody was speaking of object-oriented modelling. On the other hand, so-called object-oriented modelling has become increasingly popular during the last few years. By relating the characteristics of both approaches, it is shown that bond graph modelling, although much older, may be viewed as a special form of object-oriented modelling. For that purpose the new object-oriented modelling language Modelica is used as a working language which aims at supporting multiple formalisms. Although it turns out that bond graph models can be described rather easily, it is obvious that Modelica started from generalized networks and was not designed to support bond graphs. The description of bond graph models in Modelica is illustrated by means of a hydraulic drive. Since VHDL-AMS as an important language standardized and supported by IEEE has been extended to support also modelling of non-electrical systems, it is briefly investigated as to whether it can be used for description of bond graphs. It turns out that currently it does not seem to be suitable.
Multidisciplinary systems are described most suitably by bond graphs. In order to determine unnormalized frequency domain sensitivities in symbolic form, this paper proposes to construct in a systematic manner a bond graph from another bond graph, which is called the associated incremental bond graph in this paper. Contrary to other approaches reported in the literature the variables at the bonds of the incremental bond graph are not sensitivities but variations (incremental changes) in the power variables from their nominal values due to parameter changes. Thus their product is power. For linear elements their corresponding model in the incremental bond graph also has a linear characteristic. By deriving the system equations in symbolic state space form from the incremental bond graph in the same way as they are derived from the initial bond graph, the sensitivity matrix of the system can be set up in symbolic form. Its entries are transfer functions depending on the nominal parameter values and on the nominal states and the inputs of the original model. The sensitivities can be determined automatically by the bond graph preprocessor CAMP-G and the widely used program MATLAB together with the Symbolic Toolbox for symbolic mathematical calculation. No particular program is needed for the approach proposed. The initial bond graph model may be non-linear and may contain controlled sources and multiport elements. In that case the sensitivity model is linear time variant and must be solved in the time domain. The rationale and the generality of the proposed approach are presented. For illustration purposes a mechatronic example system, a load positioned by a constant-excitation d.c. motor, is presented and sensitivities are determined in symbolic form by means of CAMP-G/MATLAB.
Although p27 plays a central role in cell cycle regulation, its role in breast cancer prognosis is controversial. Furthermore, the p27 gene CDKN1B carries a polymorphism with unknown functional relevance. This study was designed to evaluate p27 expression and p27 genotyping with respect to early breast cancer prognosis. 279 patients with infiltrating metastasis-free breast cancer were included in this study. p27 expression was determined in tumor tissue specimens from 261 patients by immunohistochemistry. From 108 patients, the CDKN1B genotype was examined by PCR and subsequent direct sequencing. 55.2% of the tumors were considered p27 positive. p27 expression did not correlate with any of the established parameters except for nodal involvement but significantly correlated to prolonged disease-free survival. In 35% of the tumors analyzed, the CDKN1B gene showed a polymorphism at codon 109 (V109G). The V109G polymorphism correlated with greater nodal involvement. In the node-negative subgroup, V109G correlated significantly with a shortened disease-free survival. In conclusion, the determination of the CDKN1B genotype might be a powerful tool for the prognosis of patients with early breast cancer.
Background: Type 2 diabetes mellitus is associated with increased cardiovascular risk. One laboratory marker for cardiovascular risk assessment is high-sensitivity C-reactive protein (hsCRP).
Methods: This cross-sectional study attempted to analyze the association of hsCRP levels with insulin resistance, β-cell dysfunction and macrovascular disease in 4270 non-insulin-treated patients with type 2 diabetes [2146 male, 2124 female; mean age ±SD, 63.9±11.1years; body mass index (BMI) 30.1±5.5kg/m2; disease duration 5.4±5.6years; hemoglobin A1c (HbA1c) 6.8±1.3%]. It consisted of a single morning visit with collection of a fasting blood sample. Observational parameters included several clinical scores and laboratory biomarkers.
Results: Stratification into cardiovascular risk groups according to hsCRP levels revealed that 934 patients had low risk (hsCRP <1mg/L), 1369 patients had intermediate risk (hsCRP 1–3mg/L), 1352 patients had high risk (hsCRP >3–10mg/L), and 610 patients had unspecific hsCRP elevation (>10mg/L). Increased hsCRP levels were associated with other indicators of diabetes-related cardiovascular risk (homeostatic model assessment, intact proinsulin, insulin, BMI, β-cell dysfunction, all p<0.001), but showed no correlation with disease duration or glucose control. The majority of the patients were treated with diet (34.1%; hsCRP levels 2.85±2.39mg/L) or metformin monotherapy (21.1%; 2.95±2.50mg/L hsCRP). The highest hsCRP levels were observed in patients treated with sulfonylurea (17.0%; 3.00±2.43mg/L).
Conclusions: Our results indicate that hsCRP may be used as a cardiovascular risk marker in patients with type 2 diabetes mellitus and should be evaluated in further prospective studies.
The development of mobile robotic systems is a demanding task regarding its complexity, required resources and skills in multiple fields such as software development, artificial intelligence, mechanical design, electrical engineering, signal processing, sensor technology or control theory. This holds true particularly for soccer playing robots, where additional aspects like high dynamics, cooperation and high physical stress have to be dealt with. In robot competitions such as RoboCup, additional skills in the domains of team, project and knowledge management are of importance.
Purpose – To describe the development of a novel polyether(meth)acrylate-based resin material class for stereolithography with alterable material characteristics.
Design/methodology/approach – A complete overview of details to composition parameters, the optimization and bandwidth of mechanical and processing parameters is given. Initial biological characterization experiments and future application felds are depicted. Process parameters are studied in a commercial 3D systems Viper stereolithography system, and a new method to determine these parameters is described herein.
Findings – Initial biological characterizations show the non-toxic behavior in a biological environment, caused mainly by the (meth)acrylate-based core components. These photolithographic resins combine an adjustable low Young’s modulus with the advantages of a non-toxic (meth)acrylate-based process material. In contrast to the mostly rigid process materials used today in the rapid prototyping industry, these polymeric formulations are able to fulfll the extended need for a soft engineering material. A short overview of sample applications is given.
Practical implications – These polymeric formulations are able to meet the growing demand for a resin class for rapid manufacturing that covers a bandwidth from softer to stiffer materials.
Originality/value – This paper gives an overview about the novel developed material class for stereolithography and should be therefore of high interest to people with interest in novel rapid manufacturing materials and technology.
This paper introduces our robotic system named UGAV (Unmanned Ground-Air Vehicle) consisting of two semi-autonomous robot platforms, an Unmanned Ground Vehicle (UGV) and an Unmanned Aerial Vehicles (UAV). The paper focuses on three topics of the inspection with the combined UGV and UAV: (A) teleoperated control by means of cell or smart phones with a new concept of automatic configuration of the smart phone based on a RKI-XML description of the vehicles control capabilities, (B) the camera and vision system with the focus to real time feature extraction e.g. for the tracking of the UAV and (C) the architecture and hardware of the UAV.
The research of autonomous artificial agents that adapt to and survive in changing, possibly hostile environments, has gained momentum in recent years. Many of such agents incorporate mechanisms to learn and acquire new knowledge from its environment, a feature that becomes fundamental to enable the desired adaptation, and account for the challenges that the environment poses. The issue of how to trigger such learning, however, has not been as thoroughly studied as its significance suggest. The solution explored is based on the use of surprise (the reaction to unexpected events), as the mechanism that triggers learning. This thesis introduces a computational model of surprise that enables the robotic learner to experience surprise and start the acquisition of knowledge to explain it. A measure of surprise that combines elements from information and probability theory, is presented. Such measure offers a response to surprising situations faced by the robot, that is proportional to the degree of unexpectedness of such event. The concepts of short- and long-term memory are investigated as factors that influence the resulting surprise. Short-term memory enables the robot to habituate to new, repeated surprises, and to “forget” about old ones, allowing them to become surprising again. Long-term memory contains knowledge that is known a priori or that has been previously learned by the robot. Such knowledge influences the surprise mechanism, by applying a subsumption principle: if the available knowledge is able to explain the surprising event, suppress any trigger of surprise. The computational model of robotic surprise has been successfully applied to the domain of a robotic learner, specifically one that learns by experimentation. A brief introduction to the context of such application is provided, as well as a discussion on related issues like the relationship of the surprise mechanism with other components of the robot conceptual architecture, the challenges presented by the specific learning paradigm used, and other components of the motivational structure of the agent.
This thesis introduces and demonstrates a novel method for learning qualitative models of the world by an autonomous robot. The method makes possible generation of qualitative models that can be used for prediction as well as directing the experiments to improve the model. The qualitative models form the knowledge representation of the robot and consists of qualitative trees and non-deterministic finite automaton. An efficient exploration algorithm that lets the robot collect the most relevant learning samples is also introduced. To demonstrate the use of the methodology, representation and algorithm, two experiments are described. The first experiment is conducted using a mobile robot and a ball, where the robot observes the ball and learns the effect of its actions on the observed attributes of the world. The second experiment is conducted using a mobile robot and five boxes, two non-movable boxes and three movable boxes. The robot experiments actively with the objects and observes the changes in the attributes of the world. The main difference with the two experiments is that the first one tries to learn by observation while the second tries to learn by experimentation. In both experiments the robot learns qualitative models from its actions and observations. Although the primary objective of the robot is to improve itself by being able to predict the outcome of its actions, the models Learned were also used at each step of the learning process to direct the experiments so that the model converges to the final model as quickly as possible.
The automated annotation of data from high throughput sequencing and genomics experiments is a significant challenge for bioinformatics. Most current approaches rely on sequential pipelines of gene finding and gene function prediction methods that annotate a gene with information from different reference data sources. Each function prediction method contributes evidence supporting a functional assignment. Such approaches generally ignore the links between the information in the reference datasets. These links, however, are valuable for assessing the plausibility of a function assignment and can be used to evaluate the confidence in a prediction. We are working towards a novel annotation system that uses the network of information supporting the function assignment to enrich the annotation process for use by expert curators and predicting the function of previously unannotated genes. In this paper we describe our success in the first stages of this development. We present the data integration steps that are needed to create the core database of integrated reference databases (UniProt, PFAM, PDB, GO and the pathway database Ara-Cyc) which has been established in the ONDEX data integration system. We also present a comparison between different methods for integration of GO terms as part of the function assignment pipeline and discuss the consequences of this analysis for improving the accuracy of gene function annotation. The methods and algorithms presented in this publication are an integral part of the ONDEX system which is freely available from http://ondex.sf.net/.
XPERSIF: a software integration framework & architecture for robotic learning by experimentation
(2008)
The integration of independently-developed applications into an efficient system, particularly in a distributed setting, is the core issue addressed in this work. Cooperation between researchers across various field boundaries in order to solve complex problems has become commonplace. Due to the multidisciplinary nature of such efforts, individual applications are developed independent of the integration process. The integration of individual applications into a fully-functioning architecture is a complex and multifaceted task. This thesis extends a component-based architecture, previously developed by the authors, to allow the integration of various software applications which are deployed in a distributed setting. The test bed for the framework is the EU project XPERO, the goal of which is robot learning by experimentation. The task at hand is the integration of the required applications, such as planning of experiments, perception of parametrized features, robot motion control and knowledge-based learning, into a coherent cognitive architecture. This allows a mobile robot to use the methods involved in experimentation in order to learn about its environment. To meet the challenge of developing this architecture within a distributed, heterogeneous environment, the authors specified, defined, developed, implemented and tested a component-based architecture called XPERSIF. The architecture comprises loosely-coupled, autonomous components that offer services through their well-defined interfaces and form a service-oriented architecture. The Ice middleware is used in the communication layer. Its deployment facilitates the necessary refactoring of concepts. One fully specified and detailed use case is the successful integration of the XPERSim simulator which constitutes one of the kernel components of XPERO.The results of this work demonstrate that the proposed architecture is robust and flexible, and can be successfully scaled to allow the complete integration of the necessary applications, thus enabling robot learning by experimentation. The design supports composability, thus allowing components to be grouped together in order to provide an aggregate service. Distributed simulation enabled real time tele-observation of the simulated experiment. Results show that incorporating the XPERSim simulator has substantially enhanced the speed of research and the information flow within the cognitive learning loop.
We have designed an inexpensive intelligent pedestrian counting system. The pedestrian counting system consists of several counters that can be connected together in a distributed fashion and communicate over the wireless channel. The motion pattern is recorded using a set of passive infrared (PIR) sensors. Each counter has one wireless sensor node that processes the PIR sensor data and transmits it to a base station. Then echo state network, a special kind of recurrent neural network, is used to predict the pedestrian count from the input pattern. The evaluation of the performance of such networks in a novel kind of application is one focus of this work. The counter gave a performance of 80.4% which is better than the commercially available low-priced pedestrian counters. The article reports the experiments we did for analyzing the counterperformance and lists the strengths and limitations of the current implementation. It will also report the preliminary test results obtained by substituting the PIR sensors with low-cost active IR distance sensors which can improve the counter performance further.
Autonomous mobile robots need internal environment representations or models of their environment in order to act in a goal-directed manner, plan actions and navigate effectively. Especially in those situations where a robot can not be provided with a manually constructed model or in environments that change over time, the robot needs to possess the ability of autonomously constructing models and maintaining these models on its own. To construct a model of an environment multiple sensor readings have to be acquired and integrated into a single representation. Where the robot has to take these sensor readings is determined by an exploration strategy. The strategy allows the robot to sense all environmental structures and to construct a complete model of its workspace. Given a complete environment model, the task of inspection is to guide the robot to all modeled environmental structures in order to detect changes and to update the model if necessary. Informally stated, exploration and inspection provide the means for acquiring as much information as possible by the robot itself. Both exploration and inspection are highly integrated problems. In addition to the according strategies, they require for several abilities of a robotic system and comprise various problems from the field of mobile robotics including Simultaneous localization and Mapping (SLAM), motion planning and control as well as reliable collision avoidance. The goal of this thesis is to develop and implement a complete system and a set of algorithms for robotic exploration and inspection. That is, instead of focussing on specific strategies, robotic exploration and inspection are addressed as the integrated problems that they are. Given the set of algorithms a real mobile service robot has to be able to autonomously explore its workspace, construct a model of its workspace and use this model in subsequent tasks e.g. for navigating in the workspace or inspecting the workspace itself. The algorithms need to be reliable, robust against environment dynamics and internal failures and applicable online in real-time on a real mobile robot. The resulting system should allow a mobile service robot to navigate effectively and reliably in a domestic environment and avoid all kinds of collisions. In the context of mobile robotics, domestic environments combine the characteristics of being cluttered, dynamic and populated by humans and domestic animals. SLAM is going to be addressed in terms of incremental range image registration which provides efficient means to construct internal environment representations online while moving through the environment. Two registration algorithms are presented that can be applied on two-dimensional and three-dimensional data together with several extensions and an incremental registration procedure. The algorithms are used to construct two different types of environment representations, memory-efficient sparse points and probabilistic reflection maps. For effective navigation in the robot’s workspace, different path planning algorithms are going to be presented for the two types of environment representations. Furthermore, two motion controllers will be described that allow a mobile robot to follow planned paths and to approach a target position and orientation. Finally this thesis will present different exploration and inspection strategies that use the aforementioned algorithms to move the robot to previously unexplored or uninspected terrain and update the internal environment representations accordingly. These strategies are augmented with algorithms for detecting changes in the environment and for segmenting internal models into individual rooms. The resulting system performed very successfully in the 2008 and 2009 RoboCup@Home competitions.
In this paper, residual sinks are used in bond graph model-based quantitative fault detection for the coupling of a model of a faultless process engineering system to a bond graph model of the faulty system. By this way, integral causality can be used as the preferred computational causality in both models. There is no need for numerical differentiation. Furthermore, unknown variables do not need to be eliminated from power continuity equations in order to obtain analytical redundancy relations (ARRs) in symbolic form. Residuals indicating faults are computed numerically as components of a descriptor vector of a differential algebraic equation system derived from the coupled bond graphs. The presented bond graph approach especially aims at models with non-linearities that make it cumbersome or even impossible to derive ARRs from model equations by elimination of unknown variables. For illustration, the approach is applied to a non-controlled as well as to a controlled hydraulic two-tank system. Finally, it is shown that not only the numerical computation of residuals but also the simultaneous numerical computation of their sensitivities with respect to a parameter can be supported by bond graph modelling.
Background: Bile acids, end products of the pathway for cholesterol elimination, are required for dietary lipid and fatsoluble vitamin absorption and maintain the balance between cholesterol synthesis in the liver and cholesterol excretion. They are composed of a steroid structure and are primarily made in the liver by the oxidation of cholesterol. Cholesterol is also highly abundant in the human ovarian follicle, where it is used in the formation of the sex steroids.
Methodology/Principal Findings: Here we describe for the first time evidence that all aspects of the bile acid synthesis pathway are present in the human ovarian follicle, including the enzymes in both the classical and alternative pathways, the nuclear receptors known to regulate the pathway, and the end product bile acids. Furthermore, we provide functional evidence that bile acids are produced by the human follicular granulosa cells in response to cholesterol presence in the culture media.
Conclusions/Significance: These findings establish a novel pathway present in the human ovarian follicle that has the capacity to compete directly with sex steroid synthesis.
Background: Migration of mature and immature leukocytes in response to chemokines is not only essential during inflammation and host defense, but also during development of the hematopoietic system. Many molecules implicated in migratory polarity show uniform cellular distribution under non-activated conditions, but acquire a polarized localization upon exposure to migratory cues.
Methodology/Principal Findings: Here, we present evidence that raft-associated endocytic proteins (flotillins) are preassembled in lymphoid, myeloid and primitive hematopoietic cells and accumulate in the uropod during migration. Furthermore, flotillins display a polarized distribution during immunological synapse formation. Employing the membrane lipid-order sensitive probe Laurdan, we show that flotillin accumulation in the immunological synapse is concomittant with membrane ordering in these regions.
Conclusions: Together with the observation that flotillin polarization does not occur in other polarized cell types such as polarized epithelial cells, our results suggest a specific role for flotillins in hematopoietic cell polarization. Based on our results, we propose that in hematopoietic cells, flotillins provide intrinsic cues that govern segregation of certain microdomain-associated molecules during immune cell polarization.
This thesis work presents the implementation and validation of image processing problems in hardware to estimate the performance and precision gain. It compares the implementation for the addressed problem on a Field Programmable Gate Array (FPGA) with a software implementation for a General Purpose Processor (GPP) architecture. For both solutions the implementation costs for their development is an important aspect in the validation. The analysis of the flexibility and extendability that can be achieved by a modular implementation for the FPGA design was another major aspect. This work is based upon approaches from previous work, which included the detection of Binary Large OBjects (BLOBs) in static images and continuous video streams [13, 15]. One addressed problem of this work is the tracking of the detected BLOBs in continuous image material. This has been implemented for the FPGA platform and the GPP architecture. Both approaches have been compared with respect to performance and precision. This research project is motivated by the MI6 project of the Computer Vision research group, which is located at the Bonn-Rhein-Sieg University of Applied Sciences. The intent of the MI6 project is the tracking of a user in an immersive environment. The proposed solution is to attach a light emitting device to the user for tracking the created light dots on the projection surface of the immersive environment. Having the center points of those light dots would allow the estimation of the user’s position and orientation. One major issue that makes Computer Vision problems computationally expensive is the high amount of data that has to be processed in real-time. Therefore, one major target for the implementation was to get a processing speed of more than 30 frames per second. This would allow the system to realize feedback to the user in a response time which is faster than the human visual perception. One problem that comes with the idea of using a light emitting device to represent the user, is the precision error. Dependent on the resolution of the tracked projection surface of the immersive environment, a pixel might have a size in cm2. Having a precision error of only a few pixels, might lead to an offset in the estimated user’s position of several cm. In this research work the development and validation of a detection and tracking system for BLOBs on a Cyclone II FPGA from Altera has been realized. The system supports different input devices for the image acquisition and can perform detection and tracking for five to eight BLOBs. A further extension of the design has been evaluated and is possible with some constraints. Additional modules for compressing the image data based on run-length encoding and sub-pixel precision for the computed BLOB center-points have been designed. For the comparison of the FPGA approach for BLOB tracking a similar implementation in software using a multi-threaded approach has been realized. The system can transmit the detection or tracking results on two available communication interfaces, USB and RS232. The analysis of the hardware solution showed a similar precision for the BLOB detection and tracking as the software approach. One problem is the strong increase of the allocated resources when extending the system to process more BLOBs. With one of the applied target platforms, the DE2-70 board from Altera, the BLOB detection could be extended to process up to thirty BLOBs. The implementation of the tracking approach in hardware required much more effort than the software solution. The design of high level problems in hardware for this case are more expensive than the software implementation. The search and match steps in the tracking approach could be realized more efficiently and reliably in software. The additional pre-processing modules for sub-pixel precision and run-length-encoding helped to increase the system’s performance and precision.
A system that interacts with its environment can be much more robust if it is able to reason about the faults that occur in its environment, despite perfect functioning of its internal components. For robots, which interact with the same environment as human beings, this robustness can be obtained by incorporating human-like reasoning abilities in them. In this work we use naive physics to enable reasoning about external faults in robots. We propose an approach for diagnosing external faults that uses qualitative reasoning on naive physics concepts for diagnosis. These concepts are mainly individual properties of objects that define their state qualitatively. The reasoning process uses physical laws to generate possible states of the concerned object(s), which could result into a detected external fault. Since effective reasoning about any external fault requires the information of relevant properties and physical laws, we associate different properties and laws to different types of faults which can be detected by a robot. The underlying ontology of this association is proposed on the basis of studies conducted (by other researchers) on reasoning of physics novices about everyday physical phenomena. We also formalize some definitions of properties of objects into a small framework represented in First-Order logic. These definitions represent naive concepts behind the properties and are intended to be independent from objects and circumstances. The definitions in the framework illustrates our proposal of using different biased definitions of properties for different types of faults. In this work, we also present a brief review of important contributions in the area of naive/qualitative physics. These reviews help in understanding the limitations of naive/qualitative physics in general. We also apply our approach to simple scenarios to asses its limitations in particular. Since this work was done independent of any particular real robotic system, it can be seen as a theoretical proof of the concept of usefulness of naive physics for external fault reasoning in robotics.
Balanites aegyptiaca (Balanitaceae) is a widely grown desert plant with multiuse potential. In the present paper, a crude extract from B. aegyptiaca seeds equivalent to a ratio of 1 : 2000 seeds to the extract was screened for antiplasmodial activity. The determined IC(50) value for the chloroquine-susceptible Plasmodium falciparum NF54 strain was 68.26 μg/μL ± 3.5. Analysis of the extract by gas chromatography-mass spectrometry detected 6-phenyl-2(H)-1,2,4-triazin-5-one oxime, an inhibitor of the parasitic M18 Aspartyl Aminopeptidase as one of the compounds which is responsible for the in vitro antiplasmodial activity. The crude plant extract had a K(i) of 2.35 μg/μL and showed a dose-dependent response. After depletion of the compound, a significantly lower inhibition was determined with a K(i) of 4.8 μg/μL. Moreover, two phenolic compounds, that is, 2,6-di-tert-butyl-phenol and 2,4-di-tert-butyl-phenol, with determined IC(50) values of 50.29 μM ± 3 and 47.82 μM ± 2.5, respectively, were detected. These compounds may contribute to the in vitro antimalarial activity due to their antioxidative properties. In an in vivo experiment, treatment of BALB/c mice with the aqueous Balanite extract did not lead to eradication of the parasites, although a reduced parasitemia at day 12 p.i. was observed.
In the past decade computer models have become very popular in the field of biomechanics due to exponentially increasing computer power. Biomechanical computer models can roughly be subdivided into two groups: multi-body models and numerical models. The theoretical aspects of both modelling strategies will be introduced. However, the focus of this chapter lies on demonstrating the power and versatility of computer models in the field of biomechanics by presenting sophisticated finite element models of human body parts. Special attention is paid to explain the setup of individual models using medical scan data. In order to reach the goal of individualising the model a chain of tools including medical imaging, image acquisition and processing, mesh generation, material modelling and finite element simulation –possibly on parallel computer architectures- becomes necessary. The basic concepts of these tools are described and application results are presented. The chapter ends with a short outlook into the future of computer biomechanics.
In this paper, the performance evaluation of Frequency Modulated Chaotic On-Off Keying (FM-COOK) in AWGN, Rayleigh and Rician fading channels is given. The simulation results show that an improvement in BER can be gained by incorporating the FM modulation with COOK for SNR values less than 10dB in AWGN case and less than 6dB for Rayleigh and Rician fading channels.
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Dialogue University President Hartmut Ihne and Jakob Rhyner, Vice Rector of the United Nations University (UNU), talk about common goals and the concept of regional internationality ...
Studies and Teaching University scores high with the Teaching Quality Pact (Pro-MINT-us), career training and Bachelor studies all in one, three attractive Master’s programmes set up, central e-Learning platform online, International Centre for Sustainable Development already hard at work ...
Research Graduate Institute establishes new Ph.D. culture, research focus on visual computing secures third-party funding, energy harvesting project wins university competition, research on the impact of zero gravity on arteries, security systems protect against car thieves ...
Campus Centre for Science and Technology Transfer, International Welcome Centre - a first stop for foreign students, alumni coordinator keeps in close contact with former students, hackathon brings students from around the world together, H-BRS prepared for the double Abitur year ...
What if ... ... the Bonn-Rhein-Sieg University of Applied Sciences did not exist? Personal answers to an unusual question ...
Region H-BRS- a strong engine for the region, research centre for region’s SMEs looks for investors, companies invest in scholarships, students advise the Alexander- Koenig-Gesellschaft, BusinessCampus opens a third location, concept for medical tourism along the Rhine corridor ...
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In a research project funded by the German Research Foundation, meteorologists, data publication experts, and computer scientists optimised the publication process of meteorological data and developed software that supports metadata review. The project group placed particular emphasis on scientific and technical quality assurance of primary data and metadata. At the end, the software automatically registers a Digital Object Identifier at DataCite. The software has been successfully integrated into the infrastructure of the World Data Center for Climate, but a key was to make the results applicable to data publication processes in other sciences as well.
A robot (e.g. mobile manipulator) that interacts with its environment to perform its tasks, often faces situations in which it is unable to achieve its goals despite perfect functioning of its sensors and actuators. These situations occur when the behavior of the object(s) manipulated by the robot deviates from its expected course because of unforeseeable ircumstances. These deviations are experienced by the robot as unknown external faults. In this work we present an approach that increases reliability of mobile manipulators against the unknown external faults. This approach focuses on the actions of manipulators which involve releasing of an object. The proposed approach, which is triggered after detection of a fault, is formulated as a three-step scheme that takes a definition of a planning operator and an example simulation as its inputs. The planning operator corresponds to the action that fails because of the fault occurrence, whereas the example simulation shows the desired/expected behavior of the objects for the same action. In its first step, the scheme finds a description of the expected behavior of the objects in terms of logical atoms (i.e. description vocabulary). The description of the simulation is used by the second step to find limits of the parameters of the manipulated object. These parameters are the variables that define the releasing state of the object.
Using randomly chosen values of the parameters within these limits, this step creates different examples of the releasing state of the object. Each one of these examples is labelled as desired or undesired according to the behavior exhibited by the object (in the simulation), when the object is released in the state corresponded by the example. The description vocabulary is also used in labeling the examples autonomously. In the third step, an algorithm (i.e. N-Bins) uses the labelled examples to suggest the state for the object in which releasing it avoids the occurrence of unknown external faults.
The proposed N-Bins algorithm can also be used for binary classification problems. Therefore, in our experiments with the proposed approach we also test its prediction ability along with the analysis of the results of our approach. The results show that under the circumstances peculiar to our approach, N-Bins algorithm shows reasonable prediction accuracy where other state of the art classification algorithms fail to do so. Thus, N-Bins also extends the ability of a robot to predict the behavior of the object to avoid unknown external faults. In this work we use simulation environment OPENRave that uses physics engine ODE to simulate the dynamics of rigid bodies.
The ability of detecting people has become a crucial subtask, especially in robotic systems which aim an application in public or domestic environments. Robots already provide their services e.g. in real home improvement markets and guide people to a desired product. In such a scenario many robot internal tasks would benefit from the knowledge of knowing the number and positions of people in the vicinity. The navigation for example could treat them as dynamical moving objects and also predict their next motion directions in order to compute a much safer path. Or the robot could specifically approach customers and offer its services. This requires to detect a person or even a group of people in a reasonable range in front of the robot. Challenges of such a real-world task are e.g. changing lightning conditions, a dynamic environment and different people shapes. In this thesis a 3D people detection approach based on point cloud data provided by the Microsoft Kinect is implemented and integrated on mobile service robot. A Top-Down/Bottom-Up segmentation is applied to increase the systems flexibility and provided the capability to the detect people even if they are partially occluded. A feature set is proposed to detect people in various pose configurations and motions using a machine learning technique. The system can detect people up to a distance of 5 meters. The experimental evaluation compared different machine learning techniques and showed that standing people can be detected with a rate of 87.29% and sitting people with 74.94% using a Random Forest classifier. Certain objects caused several false detections. To elimante those a verification is proposed which further evaluates the persons shape in the 2D space. The detection component has been implemented as s sequential (frame rate of 10 Hz) and a parallel application (frame rate of 16 Hz). Finally, the component has been embedded into complete people search task which explorates the environment, find all people and approach each detected person.
The work presented in this paper focuses on the comparison of well-known and new fault-diagnosis algorithms in the robot domain. The main challenge for fault diagnosis is to allow the robot to effectively cope not only with internal hardware and software faults but with external disturbances and errors from dynamic and complex environments as well. Based on a study of literature covering fault-diagnosis algorithms, I selected four of these methods based on both linear and non-linear models, analysed and implemented them in a mathematical robot-model, representing a four-wheels-OMNI robot. In experiments I tested the ability of the algorithms to detect and identify abnormal behaviour and to optimize the model parameters for the given training data. The final goal was to point out the strengths of each algorithm and to figure out which method would best suit the demands of fault diagnosis for a particular robot.
We present our approach to extend a Virtual Reality software framework towards the use for Augmented Reality applications. Although VR and AR applications have very similar requirements in terms of abstract components (like 6DOF input, stereoscopic output, simulation engines), the requirements in terms of hardware and software vary considerably. In this article we would like to share the experience gained from adapting our VR software framework for AR applications. We will address design issues for this task. The result is a VR/AR basic software that allows us to implement interactive applications without fixing their type (VR or AR) beforehand. Switching from VR to AR is a matter of changing the configuration file of the application. We also give an example of the use of the extended framework: Augmenting the magnetic field of bar magnets in physics classes. We describe the setup of the system and the real-time calculation of the magnetic field, using a GPU.
For the case when the abstraction of instantaneous state transitions is adopted, this paper proposes to start fault detection and isolation in an engineering system from a single time-invariant causality bond graph representation of a hybrid model. To that end, the paper picks up on a long-known proposal to model switching devices by a transformer modulated by a Boolean variable and a resistor in fixed conductance causality accounting for its ON resistance. Bond graph representations of hybrid system models developed in this way have been used so far mainly for the purpose of simulation. The paper shows that they can well constitute an approach to the bond-graph-based quantitative fault detection and isolation of hybrid models. Advantages are that the standard sequential causality assignment procedure can be a used without modification. A single set of analytical redundancy relations valid for all physically feasible system modes can be (automatically) derived from the bond graph. Stiff model equations due to small values of the ON resistance in the switch model may be avoided by symbolic reformulation of equations and letting the ON resistance of some switches tend to zero, turning them into ideal switches.
First, for two examples considered in the literature, it is shown that the approach proposed in this paper can produce the same analytical redundancy relations as were obtained from a hybrid bond graph with controlled junctions and the use of a sequential causality assignment procedure especially for fault detection and isolation purpose. Moreover, the usefulness of the proposed approach is illustrated in two case studies by its application to standard switching circuits extensively used in power electronic systems and by simulation of some fault scenarios. The approach, however, is not confined to the fault detection and isolation of such systems. Analytically validated simulation results obtained by means of the program Scilab give confidence in the approach.
A bond graph representation of switching devices known for a long time has been a modulated transformer with a modulus b(t)∈{0,1}∀t≥0 in conjunction with a resistor R:Ron accounting for the ON-resistance of a switch considered non-ideal. Besides other representations, this simple model has been used in bond graphs for simulation of the dynamic behaviour of hybrid systems. A previous article of the author has proposed to use the transformer–resistor pair in bond graphs for fault diagnosis in hybrid systems. Advantages are a unique bond graph for all system modes, the application of the unmodified standard Sequential Causality Assignment Procedure, fixed computational causalities and the derivation of analytical redundancy relations incorporating ‘Boolean’ transformer moduli so that they hold for all system modes. Switches temporarily connect and disconnect model parts. As a result, some independent storage elements may temporarily become dependent, so that the number of state variables is not time-invariant. This article addresses this problem in the context of modelling and simulation of fault scenarios in hybrid systems. In order to keep time-invariant preferred integral causality at storage ports, residual sinks previously introduced by the author are used. When two storage elements become dependent at a switching time instance ts, a residual sink is activated. It enforces that the outputs of two dependent storage elements become immediately equal by imposing the conjugate3 power variable of appropriate value on their inputs. The approach is illustrated by the bond graph modelling and simulation of some fault scenarios in a standard three-phase switched power inverter supplying power into an RL-load in a delta configuration. A well-developed approach to model-based fault detection and isolation is to evaluate the residual of analytical redundancy relations. In this article, analytical redundancy relation residuals have been computed numerically by coupling a bond graph of the faulty system to one of the non-faulty systems by means of residual sinks. The presented approach is not confined to power electronic systems but can be used for hybrid systems in other domains as well. In further work, the RL-load may be replaced by a bond graph model of an alternating current motor in order to study the effect of switch failures in the power inverter on to the dynamic behaviour of the motor.
In service robotics, tasks without the involvement of objects are barely applicable, like in searching, fetching or delivering tasks. Service robots are supposed to capture efficiently object related information in real world scenes while for instance considering clutter and noise, and also being flexible and scalable to memorize a large set of objects. Besides object perception tasks like object recognition where the object’s identity is analyzed, object categorization is an important visual object perception cue that associates unknown object instances based on their e.g. appearance or shape to a corresponding category. We present a pipeline from the detection of object candidates in a domestic scene over the description to the final shape categorization of detected candidates. In order to detect object related information in cluttered domestic environments an object detection method is proposed that copes with multiple plane and object occurrences like in cluttered scenes with shelves. Further a surface reconstruction method based on Growing Neural Gas (GNG) in combination with a shape distribution-based descriptor is proposed to reflect shape characteristics of object candidates. Beneficial properties provided by the GNG such as smoothing and denoising effects support a stable description of the object candidates which also leads towards a more stable learning of categories. Based on the presented descriptor a dictionary approach combined with a supervised shape learner is presented to learn prediction models of shape categories.
Experimental results, of different shapes related to domestically appearing object shape categories such as cup, can, box, bottle, bowl, plate and ball, are shown. A classification accuracy of about 90% and a sequential execution time of lesser than two seconds for the categorization of an unknown object is achieved which proves the reasonableness of the proposed system design. Additional results are shown towards object tracking and false positive handling to enhance the robustness of the categorization. Also an initial approach towards incremental shape category learning is proposed that learns a new category based on the set of previously learned shape categories.
Human mesenchymal stem cells (hMSCs) are considered a promising cell source for regenerative medicine, because they have the potential to differentiate into a variety of lineages among which the mesoderm-derived lineages such adipo- or osteogenesis are investigated best. Human MSCs can be harvested in reasonable to large amounts from several parts of the patient’s body and due to this possible autologous origin, allorecognition can be avoided. In addition, even in allogenic origin-derived donor cells, hMSCs generate a local immunosuppressive microenvironment, causing only a weak immune reaction. There is an increasing need for bone replacement in patients from all ages, due to a variety of reasons such as a new recreational behavior in young adults or age-related diseases. Adipogenic differentiation is another interesting lineage, because fat tissue is considered to be a major factor triggering atherosclerosis that ultimately leads to cardiovascular diseases, the main cause of death in industrialized countries. However, understanding the differentiation process in detail is obligatory to achieve a tight control of the process for future clinical applications to avoid undesired side effects. In this review, the current findings for adipo- and osteo-differentiation are summarized together with a brief statement on first clinical trials.
The biological effects of bilirubin, still poorly understood, are concentration-dependent ranging from cell protection to toxicity. Here we present data that at high nontoxic physiological concentrations, bilirubin inhibits growth of proliferating human coronary artery smooth muscle cells by three events. It impairs the activation of Raf/ERK/MAPK pathway and the cellular Raf and cyclin D1 content that results in retinoblastoma protein hypophosphorylation on amino acids S608 and S780. These events impede the release of YY1 to the nuclei and its availability to regulate the expression of genes and to support cellular proliferation. Moreover, altered calcium influx and calpain II protease activation leads to proteolytical degradation of transcription factor YY1. We conclude that in the serum-stimulated human vascular smooth muscle primary cell cultures, bilirubin favors growth arrest, and we propose that this activity is regulated by its interaction with the Raf/ERK/MAPK pathway, effect on cyclin D1 and Raf content, altered retinoblastoma protein profile of hypophosphorylation, calcium influx, and YY1 proteolysis. We propose that these activities together culminate in diminished 5 S and 45 S ribosomal RNA synthesis and cell growth arrest. The observations provide important mechanistic insight into the molecular mechanisms underlying the transition of human vascular smooth muscle cells from proliferative to contractile phenotype and the role of bilirubin in this transition.
One of the most common problems in Regenerative Medicine is the regeneration of damaged bone with the aim of repairing or replacing lost or damaged bone tissue by stimulating the natural regenerative process. Particularly in the fields of orthopedic, plastic, reconstructive, maxillofacial and craniofacial surgery there is need for successful methods to restore bone. From a regenerative point of view two different bone replacement problems can be distinguished: large bone defects and small bone defects. Currently, no perfect system exists for the treatment of large bone defects.
After more than twenty years of research, the molecular events of apoptotic cell death can be succinctly stated; different pathways, activated by diverse signals, increase the activity of proteases called caspases that rapidly and irreversibly dismantle condemned cell by cleaving specific substrates. In this time the ideas that apoptosis protects us from tumourigenesis and that cancer chemotherapy works by inducing apoptosis also emerged. Currently, apoptosis research is shifting away from the intracellular events within the dying cell to focus on the effect of apoptotic cells on surrounding tissues. This is producing counterintuitive data showing that our understanding of the role of apoptosis in tumourigenesis and cancer therapy is too simple, with some interesting and provocative implications. Here, we will consider evidence supporting the idea that dying cells signal their presence to the surrounding tissue and, in doing so, elicit repair and regeneration that compensates for any loss of function caused by cell death. We will discuss evidence suggesting that cancer cell proliferation may be driven by inappropriate or corrupted tissue-repair programmes that are initiated by signals from apoptotic cells and show how this may dramatically modify how we view the role of apoptosis in both tumourigenesis and cancer therapy.
This article concerns with the accessibility of Business process modelling tools (BPMo tools) and business process modelling languages (BPMo languages). Therefore the reader will be introduced to business process management and the authors' motivation behind this inquiry. Afterwards, the paper will reflect problems when applying inaccessible BPMo tools. To illustrate these problems the authors distinguish between two different categories of issues and provide practical examples. Finally the article will present three approaches to improve the accessibility of BPMo tools and BPMo languages.
The Report starts with an interview between Eric Bettermann, Director of the German radio station Deutsche Welle, and University President Hartmut Ihne, which deals with responsibility in education and our University’s activities in the area of development cooperation. The chapters “Studies & Research”, “Research”, “Campus” , “The Region and International Issues” cover a wide spectrum of topics that are not rigidly defined because many topics might just as readily be assigned to other chapters.
In the latest edition, some special pages have been dedicated to the topic of “Taking a break”, i.e. to research semesters and sabbaticals, to breaks as a scientific focal point or to absolutely normal coffee breaks. Breaks are an essential part of our lives.
Annual Report 2011 - 2012
(2013)
In this paper we present the steps towards a well-designed concept of a 5VR6 system for school experiments in scientific domains like physics, biology and chemistry. The steps include the analysis of system requirements in general, the analysis of school experiments and the analysis of input and output devices demands. Based on the results of these steps we show a taxonomy of school experiments and provide a comparison between several currently available devices which can be used for building such a system. We also compare the advantages and shortcomings of 5VR6 and 5AR6 systems in general to show why, in our opinion, 5VR6 systems are better suited for school-use.
Molecular modeling is an important subdomain in the field of computational modeling, regarding both scientific and industrial applications. This is because computer simulations on a molecular level are a virtuous instrument to study the impact of microscopic on macroscopic phenomena. Accurate molecular models are indispensable for such simulations in order to predict physical target observables, like density, pressure, diffusion coefficients or energetic properties, quantitatively over a wide range of temperatures. Thereby, molecular interactions are described mathematically by force fields. The mathematical description includes parameters for both intramolecular and intermolecular interactions. While intramolecular force field parameters can be determined by quantum mechanics, the parameterization of the intermolecular part is often tedious. Recently, an empirical procedure, based on the minimization of a loss function between simulated and experimental physical properties, was published by the authors. Thereby, efficient gradient-based numerical optimization algorithms were used. However, empirical force field optimization is inhibited by the two following central issues appearing in molecular simulations: firstly, they are extremely time-consuming, even on modern and high-performance computer clusters, and secondly, simulation data is affected by statistical noise. The latter provokes the fact that an accurate computation of gradients or Hessians is nearly impossible close to a local or global minimum, mainly because the loss function is flat. Therefore, the question arises of whether to apply a derivative-free method approximating the loss function by an appropriate model function. In this paper, a new Sparse Grid-based Optimization Workflow (SpaGrOW) is presented, which accomplishes this task robustly and, at the same time, keeps the number of time-consuming simulations relatively small. This is achieved by an efficient sampling procedure for the approximation based on sparse grids, which is described in full detail: in order to counteract the fact that sparse grids are fully occupied on their boundaries, a mathematical transformation is applied to generate homogeneous Dirichlet boundary conditions. As the main drawback of sparse grids methods is the assumption that the function to be modeled exhibits certain smoothness properties, it has to be approximated by smooth functions first. Radial basis functions turned out to be very suitable to solve this task. The smoothing procedure and the subsequent interpolation on sparse grids are performed within sufficiently large compact trust regions of the parameter space. It is shown and explained how the combination of the three ingredients leads to a new efficient derivative-free algorithm, which has the additional advantage that it is capable of reducing the overall number of simulations by a factor of about two in comparison to gradient-based optimization methods. At the same time, the robustness with respect to statistical noise is maintained. This assertion is proven by both theoretical considerations and practical evaluations for molecular simulations on chemical example substances.
Realism and plausibility of computer controlled entities in entertainment software have been enhanced by adding both static personalities and dynamic emotions. Here a generic model is introduced which allows the transfer of findings from real-life personality studies to a computational model. This information is used for decision making. The introduction of dynamic event-based emotions enables adaptive behavior patterns. The advantages of this new model have been validated with a four-way crossroad in a traffic simulation. Driving agents using the introduced model enhanced by dynamics were compared to agents based on static personality profiles and simple rule-based behavior. It has been shown that adding an adaptive dynamic factor to agents improves perceivable plausibility and realism. It also supports coping with extreme situations in a fair and understandable way.
This paper examines how students learn to collaborate in English by participating in an intercultural project that focuses on teaching students to work together on a digital writing project using various online tools, and participated in this digital collaboration project. Mixed groups of students, two French and two German, used several synchronous and asynchronous tools to communicate with their counterparts (Facebook, WordPress blog, WIMS e-learning platform, email, videoconferencing). Students had to produce an article together, comparing French and German attitudes about a topic they negotiated freely in their groups. Before publishing their post, students were expected to peer-review the article written by their group. Once published, the stage consisted of voting for the best posts on the e-learning platform, WIMS. A videoconference was also organized to create cohesion between the participants. The result of the student evaluations, together with the administrative, technical vastly differing university setups is presented.
Tamoxifen therapy of invasive breast cancer has been associated with increased levels of endothelin-1 (ET-1) so that an endothelin-1 receptor (ETR) blockade has been suggested as a new therapeutic approach. This study analyzed the relationship between Tamoxifen and ET-1 signalling in invasive breast cancer. Using paraffinized tissue from 50 randomly chosen cases of invasive and in-situ ductal carcinoma from our archive, the expression of ETRs was analyzed by immune histology. ETRs were regularly detectable in normal breast tissue, but rarely in adjacent tumor areas (3/50 cases). By immunoprecipitation, a complex was found consisting of ET-1, estrogen receptors and Tamoxifen. Consequently, transcription of several target genes of ET-1 and estrogen receptors was detectable (interleukin-6, wnt-11 and a vimentin spliceform). In particular, the combination of Tamoxifen, ET-1, and estrogen receptors induced further increasing levels of these target genes. Some of these genes have been found upregulated in metastatically spreading breast cancer cells. We conclude: i) ETRs do not play a role in invasive or in-situ ductal breast cancer; ii) estrogen receptors and Tamoxifen build a complex with ET-1; and iii) upregulated transcription of target genes by ET-1–estrogen receptor–Tamoxifen complex may negatively influence breast cancer prognosis. These results indicate a role for ET-1 in Tamoxifen treated breast cancer patients leading to a potentially worsening prognosis.
Increased endothelin-1 decreases PKC alpha (PKCα), resulting in high miRNA 15a levels in kidney tumors. Breast cancer cells treated with ET-1, β-estrogen, Tamoxifen, Tamoxifen + β-estrogen and Tamoxifen + ET-1 were analysed regarding miRNA 15a expression. Significantly increased miRNA 15a levels were found after ET-1, becoming further increased in Tamoxifen + ET-1 treated cells. Our group already showed that miRNA 15a induces MAPK p38 splicing resulting in a truncated product called Mxi-2, whose function has yet to be defined in tumors. We described for the first time in ET-1 induced tumor cells that Mxi-2 builds a complex with Ago2, a miRNA binding protein, which is important for the localization of miRNAs to the 3′UTR of target genes. Furthermore, we show that Mxi-2/Ago2 is important for the interaction with the miRNA 1285 which binds to the 3′end of the tumor suppressor gene p53, being responsible for the downregulation of p53. Tissue arrays from breast cancer patients were performed, analysing Mxi-2, p53 and PKCα. Since the Mxi-2 levels increase in Tamoxifen + ET-1 treated cells, we claim that increasing ET-1 levels in Tamoxifen treated breast cancer patients are responsible for decreasing p53 levels. In summary, ET-1 decreases nuclear PKCα levels, while increasing the amount of miRNA 15a. This causes high levels of Mxi-2, necessary for complex formation with Ago2. The newly identified Mxi-2/Ago2 complex interacting with miRNA 1285 leads to increased 3′UTR p53 interaction, resulting in decreased p53 levels and subsequent tumor progression. This newly identified mechanism is a possible explanation for the development of ET-1 induced tumors.
The reciprocal translocation t(12;21)(p13;q22), the most common structural genomic alteration in B-cell precursor acute lymphoblastic leukaemia in children, results in a chimeric transcription factor TEL-AML1 (ETV6-RUNX1). We identified directly and indirectly regulated target genes utilizing an inducible TEL-AML1 system derived from the murine pro B-cell line BA/F3 and a monoclonal antibody directed against TEL-AML1. By integration of promoter binding identified with chromatin immunoprecipitation (ChIP)-on-chip, gene expression and protein output through microarray technology and stable labelling of amino acids in cell culture, we identified 217 directly and 118 indirectly regulated targets of the TEL-AML1 fusion protein. Directly, but not indirectly, regulated promoters were enriched in AML1-binding sites. The majority of promoter regions were specific for the fusion protein and not bound by native AML1 or TEL. Comparison with gene expression profiles from TEL-AML1-positive patients identified 56 concordantly misregulated genes with negative effects on proliferation and cellular transport mechanisms and positive effects on cellular migration, and stress responses including immunological responses. In summary, this work for the first time gives a comprehensive insight into how TEL-AML1 expression may directly and indirectly contribute to alter cells to become prone for leukemic transformation.
Generating and visualizing large areas of vegetation that look natural makes terrain surfaces much more realistic. However, this is a challenging field in computer graphics, because ecological systems are complex and visually appealing plant models are geometrically detailed. This work presents Silva (System for the Instantiation of Large Vegetated Areas), a system to generate and visualize large vegetated areas based on the ecological surrounding. Silva generates vegetation on Wang-tiles with associated reusable distributions enabling multi-level instantiation. This paper presents a method to generate Poisson Disc Distributions (PDDs) with variable radii on Wang-tile sets (without a global optimization) that is able to generate seamless tilings. Because Silva has a freely configurable generation pipeline and can consider plant neighborhoods it is able to incorporate arbitrary abiotic and biotic components during generation. Based on multi-levelinstancing and nested kd-trees, the distributions on the Wang-tiles allow their acceleration structures to be reused during visualization. This enables Silva to visualize large vegetated areas of several hundred square kilometers with low render times and a small memory footprint.
Introduction: Matrix metalloproteinases (MMPs) are important in tissue remodelling. Here we investigate the role of collagenase-3 (MMP-13) in antibody-induced arthritis.
Methods: For this study we employed the K/BxN serum-induced arthritis model. Arthritis was induced in C57BL/6 wild type (WT) and MMP-13-deficient (MMP-13–/–) mice by intraperitoneal injection of 200 μl of K/BxN serum. Arthritis was assessed by measuring the ankle swelling. During the course of the experiments, mice were sacrificed every second day for histological examination of the ankle joints. Ankle sections were evaluated histologically for infiltration of inflammatory cells, pannus tissue formation and bone/cartilage destruction. Semi-quantitative PCR was used to determine MMP-13 expression levels in ankle joints of untreated and K/BxN serum-injected mice.
Results: This study shows that MMP-13 is a regulator of inflammation. We observed increased expression of MMP-13 in ankle joints of WT mice during K/BxN serum-induced arthritis and both K/BxN serum-treated WT and MMP-13–/– mice developed progressive arthritis with a similar onset. However, MMP-13–/– mice showed significantly reduced disease over the whole arthritic period. Ankle joints of WT mice showed severe joint destruction with extensive inflammation and erosion of cartilage and bone. In contrast, MMP-13–/– mice displayed significantly decreased severity of arthritis (50% to 60%) as analyzed by clinical and histological scoring methods.
Conclusions: MMP-13 deficiency acts to suppress the local inflammatory responses. Therefore, MMP-13 has a role in the pathogenesis of arthritis, suggesting MMP-13 is a potential therapeutic target.
The title of the annual report 2013 "Shaping change: The University Addresses Society‘s Probing Challenges" reveals the great importance placed on social, economic and technological changes at the university.
This key aspect thus runs through the contents of the 90-page annual report like a common thread, without losing track of the enormous variety of research and teaching at Bonn-Rhein-Sieg University. Whether the exploration of gaps in robot safety during a European Intensive Programme, a report about the Philipines crisis region from a graduate who has worked as an organizer for Care International, or the chapter "What does change look like?" – The annual report provides the full spectrum of opportunities, activities and findings of university members.
A principal step towards solving diverse perception problems is segmentation. Many algorithms benefit from initially partitioning input point clouds into objects and their parts. In accordance with cognitive sciences, segmentation goal may be formulated as to split point clouds into locally smooth convex areas, enclosed by sharp concave boundaries. This goal is based on purely geometrical considerations and does not incorporate any constraints, or semantics, of the scene and objects being segmented, which makes it very general and widely applicable. In this work we perform geometrical segmentation of point cloud data according to the stated goal. The data is mapped onto a graph and the task of graph partitioning is considered. We formulate an objective function and derive a discrete optimization problem based on it. Finding the globally optimal solution is an NP-complete problem; in order to circumvent this, spectral methods are applied. Two algorithms that implement the divisive hierarchical clustering scheme are proposed. They derive graph partition by analyzing the eigenvectors obtained through spectral relaxation. The specifics of our application domain are used to automatically introduce cannot-link constraints in the clustering problem. The algorithms function in completely unsupervised manner and make no assumptions about shapes of objects and structures that they segment. Three publicly available datasets with cluttered real-world scenes and an abundance of box-like, cylindrical, and free-form objects are used to demonstrate convincing performance. Preliminary results of this thesis have been contributed to the International Conference on Autonomous Intelligent Systems (IAS-13).
Business process infrastructures like BPMS (Business Process Management Systems) and WfMS (Workflow Management Systems) traditionally focus on the automation of processes predefined at design time. This approach is well suited for routine tasks which are processed repeatedly and which are described by a predefined control flow. In contrast, knowledge-intensive work is more goal and data-driven and less control-flow oriented. Knowledge workers need the flexibility to decide dynamically at run-time and based on current context information on the best next process step to achieve a given goal. Obviously, in most practical scenarios, these decisions are complex and cannot be anticipated and modeled completely in a predefined process model. Therefore, adaptive and dynamic process management techniques are necessary to augment the control-flow oriented part of process management (which is still a need also for knowledge workers) with flexible, context-dependent, goaloriented support.
The contribution of the most common reciprocal translocation in childhood B-cell precursor leukemia t(12;21)(p13;q22) to leukemia development is still under debate. Direct as well as secondary indirect effects of the TEL-AML1 fusion protein are commonly recorded by using cell lines and patient samples, often bearing the TEL-AML1 fusion protein for decades. To identify direct targets of the fusion protein a short-term induction of TEL-AML1 is needed. We here describe in detail the experimental procedure, quality controls and contents of the ChIP, mRNA expression and SILAC datasets associated with the study published by Linka and colleagues in the Blood Cancer Journal [1] utilizing a short term induction of TEL-AML1 in an inducible precursor B-cell line model.
We investigated graphene structures grafted with fullerenes. The size of the graphene sheets ranges from 6400 to 640,000 atoms. The fullerenes (C60 and C240) are placed on top of the graphene sheets, using different impact velocities we could distinguish three types of impact. Furthermore, we investigated the changes of the vibrational properties. The modified graphene planes show additional features in the vibronic density of states.
We are happy to present you the special issue on Best Practice in Robot Software Development of the Journal on Software Engineering for Robotics! The spark for this special issue came during the eighth workshop on Software Development and Integration in Robotics (SDIR) at the 2013 IEEE International Conference on Robotics and Automation. The workshop focused on Robot Software Architectures, and the fruitful discussions made it clear that the design, development, and deployment of robot software is always an interplay between competing aspects. These are often couched in antagonistic pairs, such as dependability versus performance, and prominently include quality attributes as well as functional, nonfunctional, and application requirements.
Gas chromatography with flame-ionization detection (FID) and gas chromatography-mass spectrometry (GC/MS) with electron impact ionization (EI) and chemical ionization (PCI and NCI) were successfully used for separation and identification of commercially available longchain primary alkyl amines. The investigated compounds were used as corrosion inhibiting and antifouling agents in a water-steam circuit of energy systems in the power industry. Solidphase extraction (SPE) with octadecyl bonded silica (C18) sorbents followed by gas chromatography were used for quantification of the investigated Primene JM-T™ alkyl amines in boiler water, condensate and superheated steam samples from the power plant. Amine formulations from Kotamina group favor formation of protective layers on internal surfaces and keep them free from corrosion and scale. Alkyl amines contained in those formulations both render the environment alkaline and limit the corrosion impact of ionic and gaseous impurities by formation of protective layers. Moreover, alkyl amines limit scaling on heating surfaces of boilers and in turbine, ensuring failure-free operation. Application of alkyl amine formulation enhances heat exchange during boiling and condensation processes. Alkyl amines with branched structure are more thermally stable than linear alkyl amines, exhibit better adsorption and effectiveness of surface shielding. As a result, application of thermostable long-chain branched alkyl amines increases the efficiency of anti-corrosive protection. Moreover, the concentration of ammonia content in water and in steam was also considerably decreased.
Purpose – The aim of the study is to investigate the implementation of corporate sustainability (CS) in the German real estate sector.
Design/methodology/approach – The authors begin by outlining the framework set by the European Union and the German Federal Government for companies wanting to be classified as sustainable. After this, the relevance of sustainability for German real estate companies is discussed. Their empirical section contains an international comparison. Finally, they present an analysis checking the implementation of CS for the main 135 German real estate companies.
Findings – The present analysis shows that German real estate companies compare well with their international counterparts, in 2012 representing 15 per cent of all real estate firms reporting on the basis of the Global Reporting Initiative. However, of the 135 companies in Germany surveyed, only a small proportion classify themselves as CS and CSR (corporate social responsibility) enterprises. This number could be rapidly increased by better documentation of companies’ commitment to sustainability.
Practical implications – The study’s importance lies in the overview it provides of CS activities in the German real estate industry. In addition, it provides hints on how companies can improve their documentation to classify as CSR enterprises. Although the analysis concentrates on Germany, the results are also relevant for companies in other European countries.
The objective of this research project is to develop a user-friendly and cost-effective interactive input device that allows intuitive and efficient manipulation of 3D objects (6 DoF) in virtual reality (VR) visualization environments with flat projections walls. During this project, it was planned to develop an extended version of a laser pointer with multiple laser beams arranged in specific patterns. Using stationary cameras observing projections of these patterns from behind the screens, it is planned to develop an algorithm for reconstruction of the emitter’s absolute position and orientation in space. Laser pointer concept is an intuitive way of interaction that would provide user with a familiar, mobile and efficient navigation though a 3D environment. In order to navigate in a 3D world, it is required to know the absolute position (x, y and z position) and orientation (roll, pitch and yaw angles) of the device, a total of 6 degrees of freedom (DoF). Ordinary laser-based pointers when captured on a flat surface with a video camera system and then processed, will only provide x and y coordinates effectively reducing available input to 2 DoF only. In order to overcome this problem, an additional set of multiple (invisible) laser pointers should be used in the pointing device. These laser pointers should be arranged in a way that the projection of their rays will form one fixed dot pattern when intersected with the flat surface of projection screens. Images of such a pattern will be captured via a real-time camera-based system and then processed using mathematical re-projection algorithms. This would allow the reconstruction of the full absolute 3D pose (6 DoF) of the input device. Additionally, multi-user or collaborative work should be supported by the system, would allow several users to interact with a virtual environment at the same time. Possibilities to port processing algorithms into embedded processors or FPGAs will be investigated during this project as well.
Might the gravity levels found on other planets and on the moon be sufficient to provide an adequate perception of upright for astronauts? Can the amount of gravity required be predicted from the physiological threshold for linear acceleration? The perception of upright is determined not only by gravity but also visual information when available and assumptions about the orientation of the body. Here, we used a human centrifuge to simulate gravity levels from zero to earth gravity along the long-axis of the body and measured observers' perception of upright using the Oriented Character Recognition Test (OCHART) with and without visual cues arranged to indicate a direction of gravity that differed from the body's long axis. This procedure allowed us to assess the relative contribution of the added gravity in determining the perceptual upright. Control experiments off the centrifuge allowed us to measure the relative contributions of normal gravity, vision, and body orientation for each participant. We found that the influence of 1 g in determining the perceptual upright did not depend on whether the acceleration was created by lying on the centrifuge or by normal gravity. The 50% threshold for centrifuge-simulated gravity's ability to influence the perceptual upright was at around 0.15 g, close to the level of moon gravity but much higher than the threshold for detecting linear acceleration along the long axis of the body. This observation may partially explain the instability of moonwalkers but is good news for future missions to Mars.
Automated parameterization of intermolecular pair potentials using global optimization techniques
(2014)
In this work, different global optimization techniques are assessed for the automated development of molecular force fields, as used in molecular dynamics and Monte Carlo simulations. The quest of finding suitable force field parameters is treated as a mathematical minimization problem. Intricate problem characteristics such as extremely costly and even abortive simulations, noisy simulation results, and especially multiple local minima naturally lead to the use of sophisticated global optimization algorithms. Five diverse algorithms (pure random search, recursive random search, CMA-ES, differential evolution, and taboo search) are compared to our own tailor-made solution named CoSMoS. CoSMoS is an automated workflow. It models the parameters’ influence on the simulation observables to detect a globally optimal set of parameters. It is shown how and why this approach is superior to other algorithms. Applied to suitable test functions and simulations for phosgene, CoSMoS effectively reduces the number of required simulations and real time for the optimization task.
Nitrile-type inhibitors are known to interact with cysteine proteases in a covalent-reversible manner. The chemotype of 3-cyano-3-aza-β-amino acid derivatives was designed in which the N-cyano group is centrally arranged in the molecule to allow for interactions with the nonprimed and primed binding regions of the target enzymes. These compounds were evaluated as inhibitors of the human cysteine cathepsins K, S, B, and L. They exhibited slow-binding behavior and were found to be exceptionally potent, in particular toward cathepsin K, with second-order rate constants up to 52 900 × 103 M–1 s–1.
Sustainability is a key issue in current research activities and programs. In this conjunction three major functions of research have been identified: Basic research, knowledge reservoirs, and knowledge transfer. With regard to a transmission to the private sector, knowledge transfer is the most important factor. In this process, universities of applied sciences can play an important part as they typically have a long-standing experience in linking science and business in their teaching and research. Another important agent in the process of knowledge transfer are networks and clusters. Their strength lies integrating the different competencies of its partners and using them to a mutual benefit.
The International Centre for Sustainable Development (IZNE) – with a major focus on responsible business and sustainable food – takes the advantage of being part of a University of Applied Sciences (Bonn-Rhein-Sieg, BRSU), and being a member of several regional and international clusters and networks. These co-operations aim to establish and strengthen linkages between science and business, in particular by investigating research needs for business and business relevant research activities. Moreover, IZNE established and expanded regional and international co-operations of its own to get more transparency about regional and international value-added chains in the food sector and the issue of responsible business.
Design of a declarative language for task-oriented grasping and tool-use with dextrous robotic hands
(2014)
Apparently simple manipulation tasks for a human such as transportation or tool use are challenging to replicate in an autonomous service robot. Nevertheless, dextrous manipulation is an important aspect for a robot in many daily tasks. While it is possible to manufacture special-purpose hands for one specific task in industrial settings, a generalpurpose service robot in households must have flexible hands which can adapt to many tasks. Intelligently using tools enables the robot to perform tasks more efficiently and even beyond the designed capabilities. In this work a declarative domain-specific language, called Grasp Domain Definition Language (GDDL), is presented that allows the specification of grasp planning problems independently of a specific grasp planner. This design goal resembles the idea of the Planning Domain Definition Language (PDDL). The specification of GDDL requires a detailed analysis of the research in grasping in order to identify best practices in different domains that contribute to a grasp. These domains describe for instance physical as well as semantic properties of objects and hands. Grasping always has a purpose which is captured in the task domain definition. It enables the robot to grasp an object in a taskdependent manner. Suitable representations in these domains have to be identified and formalized for which a domain-driven software engineering approach is applied. This kind of modeling allows the specification of constraints which guide the composition of domain entity specifications. The domain-driven approach fosters reuse of domain concepts while the constraints enable the validation of models already during design time. A proof of concept implementation of GDDL into the GraspIt! grasp planner is developed. Preliminary results of this thesis have been published and presented on the IEEE International Conference on Robotics and Automation (ICRA).
This review is divided into two interconnected parts, namely a biological and a chemical one. The focus of the first part is on the biological background for constructing tissue-engineered vascular grafts to promote vascular healing. Various cell types, such as embryonic, mesenchymal and induced pluripotent stem cells, progenitor cells and endothelial- and smooth muscle cells will be discussed with respect to their specific markers. The in vitro and in vivo models and their potential to treat vascular diseases are also introduced. The chemical part focuses on strategies using either artificial or natural polymers for scaffold fabrication, including decellularized cardiovascular tissue. An overview will be given on scaffold fabrication including conventional methods and nanotechnologies. Special attention is given to 3D network formation via different chemical and physical cross-linking methods. In particular, electron beam treatment is introduced as a method to combine 3D network formation and surface modification. The review includes recently published scientific data and patents which have been registered within the last decade.
Improving the study entry supports students in a decisive phase of their university education. Implementing improvements is a change process and can only be successful if the relevant stakeholders are addressed and convinced. In the described Teaching Quality Pact project evaluation data is used as a mean to discuss in the university the situation of the study programs. As these discussions were based on empirical data rather than on opinion, it was possible to achieve an open discussion about measures that are implemented. The open discussion is maintained during the project when results of the measures taken are analyzed.
Low power dissipation is a current topic in digital design, and therefore, it should be covered in a state-of-the-art electrical engineering curriculum. This paper describes how low-power design can be addressed within a digital design course. Doing so would be beneficial for both topics because low-power design is not detached from the systems perspective, and the digital design course would be enriched by references to current challenges and applications. Thus, the presented course should serve as an example of how a course can be developed to also teach students about sustainable engineering.
It has become increasingly clear that caspases, far from being merely cell death effectors, have a much wider range of functions within the cell. These functions are as diverse as signal transduction and cytoskeletal remodeling, and caspases are now known to have an essential role in cell proliferation, migration, and differentiation. There is also evidence that apoptotic cells themselves can direct the behavior of nearby cells through the caspase-dependent secretion of paracrine signaling factors. In some processes, including the differentiation of skeletal muscle myoblasts, both caspase activation in differentiating cells as well as signaling from apoptotic cells has been reported. Here, we review the non-apoptotic outcomes of caspase activity in a range of different model systems and attempt to integrate this knowledge.
Social cash transfers (SCTs) are considered a priority in least-developed countries, where the gap between the need for basic social protection and existing provisions is greatest. This study represents one of the first comprehensive treatments of the impact of social cash transfers in low-income sub-Saharan Africa, and the first for Zambia's oldest SCT scheme. The results, based on propensity score matching and fully efficient odds-weighted regression, and data from the Kalomo SCT pilot scheme, confirm positive SCT effects on per capita consumption expenditure. We also discover threshold effects with SCT mostly impacting food expenditure among poorer beneficiary households and non-food expenditure among wealthier beneficiaries.
Analytical pyrolysis technique hyphenated to gas chromatography/mass spectrometry (Py-GC/MS) has extended the range of possible tools for characterization of synthetic polymers/copolymers. Pyrolysis involves thermal fragmentation of the analytical sample at elevated temperature between 500 and 1400 °C. In the presence of an inert gas, reproducible decomposition products characteristic for the original polymer/copolymer sample are formed. The pyrolysis products are chromatographically separated by using a fused silica capillary column and subsequently identified by interpretation of the obtained mass spectra or by using mass spectra libraries. The analytical technique eliminate the need for pre-treatment by performing analyses directly on the solid or liquid polymer sample.
In this paper, application examples of the analytical pyrolysis hyphenated to gas chromatography/mass spectrometry for the identification of different polymeric materials in the plastic and automotive industry, dentistry and occupational safety are demonstrated. For the first time results of identification of commercially light-curing dental filling material and a car wrapping foil by pyrolysis-GC/MS are presented.
Exposure to microgravity conditions causes cardiovascular deconditioning in astronauts during spaceflight. Until now, no specific drugs are available for countermeasure, since the underlying mechanism is largely unknown. Endothelial cells (ECs) and smooth muscle cells (SMCs) play key roles in various vascular functions, many of which are regulated by purinergic 2 (P2) receptors. However, their function in ECs and SMCs under microgravity conditions is still unclear. In this study, primary ECs and SMCs were isolated from bovine aorta and verified with specific markers. We show for the first time that the P2 receptor expression pattern is altered in ECs and SMCs after 24 h exposure to simulated microgravity using a clinostat. However, conditioned medium compensates this change in specific P2 receptors, for example, P2X7. Notably, P2 receptors such as P2X7 might be the important players during the paracrine interaction. Additionally, ECs and SMCs secreted different cytokines under simulated microgravity, leading into a pathogenic proliferation and migration. In conclusion, our data indicate P2 receptors might be important players responding to gravity changes in ECs and SMCs. Since some artificial P2 receptor ligands are applied as drugs, it is reasonable to assume that they might be promising candidates against cardiovascular deconditioning in the future.
It is a euphemism to say that humans use tools. Humans possess a vast repertoire of tools they use every day. In fact, as language or bipedal locomotion, tool use is a hallmark of humans. Tool use has also been often viewed as an important step during evolution (van Schaik et al., 1999) or even as a marker of the evolution of human intelligence (Wynn, 1985). So a fundamental issue is, what are the cognitive and neural bases of human tool use? The present series of papers in this special topic represents the newest additions to that research topic.
Abstract Classical ballet requires dancers to exercise significant muscle control and strength both while stationary and when moving. Following the Royal Academy of Dance (RAD) syllabus, 8 male and 27 female dancers (aged 20.2 + 1.9 yr) in a full-time university undergraduate dance training program were asked to stand in first position for 10 seconds and then perform 10 repeats of a demi-plié exercise to a counted rhythm. Accelerometer records from the wrist, sacrum, knee and ankle were compared with the numerical scores from a professional dance instructor. The sacrum mounted sensor detected lateral tilts of the torso in dances with lower scores (Spearman’s rank correlation coefficient r = -0.64, p < 0.005). The 5RMS6 acceleration amplitude of wrist mounted sensor was linearly correlated to the movement scores (Spearman’s rank correlation coefficient r = 0.63, p < 0.005). The application of sacrum and wrist mounted sensors for biofeedback during dance training is a realistic, low cost option.
Matrix metalloproteinases (MMPs) are matrix-degrading enzymes that are over-expressed in joints of rheumatoid arthritis (RA) patients. However, the contribution of specific MMPs for the development of arthritic joints is unknown. This study is aimed at studying the role of matrix metalloproteinase-9 (MMP-9) in mice, using the K/BxN serum-transfer model of RA. Arthritis was induced in Balb/c mice by injecting K/BxN serum. Development of arthritis was followed in these mice by measuring ankle thickness and clinical index score. MMP-9 expression in the joints of mice killed at various time points during the disease progression was determined by gelatin zymography using ankle lysates. We found that MMP-9 expression increased with the severity of arthritis. Importantly MMP-9 deficient mice injected with K/BxN serum showed a milder form of arthritis in comparison to the control C57BL/6 mice injected with K/BxN serum. We therefore conclude that MMP-9 promotes arthritis in mice.
The central theme of the 2014 Annual Report is human thinking.
In an interview, University President Hartmut Ihne and 3Sat moderator Gert Scobel discuss the concept of thought: "Should we be allowed to give up our autonomy voluntarily?"
Our university’s Language Centre Director James Chamberlain examines to what extent thinking varies in different languages.
Professor Paul Plöger from the Department of Computer Science explains why robots have tremendous problems understanding complex relationships in open environments.
Rather than focusing solely on our university’s future, the Annual Report links the fascinating theme to the enormous variety of life, research and tuition offered by H-BRS.
Advanced driver assistance systems (ADAS) are technology systems and devices designed as an aid to the driver of a vehicle. One of the critical components of any ADAS is the traffic sign recognition module. For this module to achieve real-time performance, some preprocessing of input images must be done, which consists of a traffic sign detection (TSD) algorithm to reduce the possible hypothesis space. Performance of TSD algorithm is critical.
One of the best algorithms used for TSD is the Radial Symmetry Detector (RSD), which can detect both Circular [7] and Polygonal traffic signs [5]. This algorithm runs in real-time on high end personal computers, but computational performance of must be improved in order to be able to run in real-time in embedded computer platforms.
To improve the computational performance of the RSD, we propose a multiscale approach and the removal of a gaussian smoothing filter used in this algorithm. We evaluate the performance on both computation times, detection and false positive rates on a synthetic image dataset and on the german traffic sign detection benchmark [29].
We observed significant speedups compared to the original algorithm. Our Improved Radial Symmetry Detector is up to 5.8 times faster than the original on detecting Circles, up to 3.8 times faster on Triangle detection, 2.9 times faster on Square detection and 2.4 times faster on Octagon detection. All of this measurements were observed with better detection and false positive rates than the original RSD.
When evaluated on the GTSDB, we observed smaller speedups, in the range of 1.6 to 2.3 times faster for Circle and Regular Polygon detection, but for Circle detection we observed a decreased detection rate than the original algorithm, while for Regular Polygon detection we always observed better detection rates. False positive rates were high, in the range of 80% to 90%.
We conclude that our Improved Radial Symmetry Detector is a significant improvement of the Radial Symmetry Detector, both for Circle and Regular polygon detection. We expect that our improved algorithm will lead the way to obtain real-time traffic sign detection and recognition in embedded computer platforms.
Extraction of text information from visual sources is an important component of many modern applications, for example, extracting the text from traffic signs on a road scene in an autonomous vehicle. For natural images or road scenes this is a unsolved problem. In this thesis the use of histogram of stroke widths (HSW) for character and noncharacter region classification is presented. Stroke widths are extracted using two methods. One is based on the Stroke Width Transform and another based on run lengths. The HSW is combined with two simple region features– aspect and occupancy ratios– and then a linear SVM is used as classifier. One advantage of our method over the state of the art is that it is script-independent and can also be used to verify detected text regions with the purpose of reducing false positives. Our experiments on generated datasets of Latin, CJK, Hiragana and Katakana characters show that the HSW is able to correctly classify at least 90% of the character regions, a similar figure is obtained for non-character regions. This performance is also obtained when training the HSW with one script and testing with a different one, and even when characters are rotated. On the English and Kannada portions of the Chars74K dataset we obtained over 95% correctly classified character regions. The use of raycasting for text line grouping is also proposed. By combining it with our HSW-based character classifier, a text detector based on Maximally Stable Extremal Regions (MSER) was implemented. The text detector was evaluated on our own dataset of road scenes from the German Autobahn, where 65% precision, 72% recall with a f-score of 69% was obtained. Using the HSW as a text verifier increases precision while slightly reducing recall. Our HSW feature allows the building of a script-independent and low parameter count classifier for character and non-character regions.
This book chapter describes application examples of gas chromatography/mass spectrometry and pyrolysis – gas chromatography/mass spectrometry in failure analysis for the identification of chemical materials like mineral oils and nitrile rubber gaskets. Furthermore, failure cases demanding identification of polymers/copolymers in fouling on the compressor wall of a car air conditioner and identification of fouling on the surface of a bearing race from the automotive industry are demonstrated. The obtained analytical results were then used for troubleshooting and remedial action of the technological process.
Virtual reality environments are increasingly being used to encourage individuals to exercise more regularly, including as part of treatment in those with mental health or neurological disorders. The success of virtual environments likely depends on whether a sense of presence can be established, where participants become fully immersed in the virtual environment. Exposure to virtual environments is associated with physiological responses, including cortical activation changes. Whether the addition of a real exercise within a virtual environment alters sense of presence perception, or the accompanying physiological changes, is not known. In a randomized and controlled study design, trials of moderate-intensity exercise (i.e. self-paced cycling) and no-exercise (i.e. automatic propulsion) were performed within three levels of virtual environment exposure. Each trial was 5-min in duration and was followed by post-trial assessments of heart rate, perceived sense of presence, EEG, and mental state. Changes in psychological strain and physical state were generally mirrored by neural activation patterns. Furthermore these change indicated that exercise augments the demands of virtual environment exposures and this likely contributed to an enhanced sense of presence.
Annual Report 2013 - 2014
(2015)
The steadily decreasing prices of display technologies and computer graphics hardware contribute to the increasing popularity of multiple-display environments, like large, high-resolution displays. It is therefore necessary that educational organizations give the new generation of computer scientists an opportunity to become familiar with this kind of technology. However, there is a lack of tools that allow for getting started easily. Existing frameworks and libraries that provide support for multi-display rendering are often complex in understanding, configuration and extension. This is critical especially in educational context where the time that students have for their projects is limited and quite short. These tools are also rather known and used in research communities only, thus providing less benefit for future non-scientists. In this work we present an extension for the Unity game engine. The extension allows – with a small overhead – for implementation of applications that are apt to run on both single-display and multi-display systems. It takes care of the most common issues in the context of distributed and multi-display rendering like frame, camera and animation synchronization, thus reducing and simplifying the first steps into the topic. In conjunction with Unity, which significantly simplifies the creation of different kinds of virtual environments, the extension affords students to build mock-up virtual reality applications for large, high-resolution displays, and to implement and evaluate new interaction techniques and metaphors and visualization concepts. Unity itself, in our experience, is very popular among computer graphics students and therefore familiar to most of them. It is also often employed in projects of both research institutions and commercial organizations; so learning it will provide students with qualification in high demand.
Sustainable development needs sustainable production and sustainable consumption. During the last decades the encouragement of sustainable production has been the focus of research and policy makers under the implicit assumption that the observable increasing ‘green’ values of consumers would also entail a growing sustainable consumption. However, it has been found that the actual purchasing behaviour often deviates from ‘green’ attitudes. This phenomenon is called the attitude-behaviour gap. It is influenced by individual, social and situational factors. The main purchasing barriers for sustainable (organic) food are price, lack of immediate availability, sensory criteria, lack or overload of information as well as the low-involvement feature of food products in conjunction with well-established consumption routines, lack of transparency and trust towards labels and certifications.
The phenomenon of the deviation between purchase attitudes and actual buying behaviour of responsible consumers is called the attitude-behaviour gap. It is influenced by individual, social and situational factors. The main purchasing barriers for sustainable (organic) food are price, lack of immediate availability, sensory criteria, lack or overload of information as well as the low-involvement feature of food products in conjunction with well-established consumption routines, lack of transparency and trust towards labels and certifications. The last three barriers are mainly of a psychological nature. Especially the low-involvement feature of food products due to daily purchase routines and relatively low prices tends to result in fast, automatic and subconscious decisions based on a so-called human mental system 1, derived from Daniel Kahneman’s (Nobel-Prize laureate in Behavioural Economics) model in behavioural psychology. In contrast, the human mental system 2 is especially important for the transformations of individual behaviour towards a more sustainable consumption. Decisions based on the human mental system 2 are slow, logical, rational, conscious and arduous. This so-called dual action model also influences the reliability of responses in consumer surveys. It seems that the consumer behaviour is the most unstable and unpredictable part of the entire supply chain and requires special attention. Concrete measures to influence consumer behaviour towards sustainable consumption are highly complex. Reviews of interdisciplinary research literature on behavioural psychology, behavioural economics and consumer behaviour and an empirical analysis of selected countries worldwide with a view to sustainable food are presented. The example of Denmark serves as a ‘best practice’ case study to illustrate how sustainable food consumption can be encouraged. It demonstrates that common efforts and a shared responsibility of consumers, business, interdisciplinary researchers, mass media and policy are needed. It takes pioneers of change who succeed in assembling a ‘critical mass’ willing to increase its ‘sustainable’ behaviour. Considering the strong psychological barriers of consumers and the continuing low market share of organic food, proactive policy measures would be conducive to foster the personal responsibility of the consumers and offer incentives towards a sustainable production. Also, further self-obligations of companies (Corporate Social Responsibility – CSR) as well as more transparency and simplification of reliable labels and certifications are needed to encourage the process towards a sustainable development.
Reducing energy consumption is one of the most pursued economic and ecologic challenges concerning societies as a whole, individuals and organizations alike. While politics start taking measures for energy turnaround and smart home energy monitors are becoming popular, few studies have touched on sustainability in office environments so far, though they account for almost every second workplace in modern economics. In this paper, we present findings of two parallel studies in an organizational context using behavioral change oriented strategies to raise energy awareness. Next to demonstrating potentials, it shows that energy feedback needs must fit to the local organizational context to succeed and should consider typical work patterns to foster accountability of consumption.
Reducing energy consumption is one of the most pursued economic and ecologic challenges concerning societies as a whole, individuals and organizations alike. While politics start taking measures for energy turnaround and smart home energy monitors are becoming popular, few studies have touched on sustainability in office environments so far, though they account for almost every second workplace in modern economics. In this paper, we present findings of two parallel studies in an organizational context using behavioral change oriented strategies to raise energy awareness. Next to demonstrating potentials, it shows that energy feedback needs must fit to the local organizational context to succeed and should consider typical work patterns to foster accountability of consumption.
Although much effort is made to prevent risks arising from food, food-borne diseases are an ever present-threat to the consumers’ health. The consumption of fresh food that is contaminated with pathogens like fungi, viruses or bacteria can cause food poisoning that leads to severe health damages or even death. The outbreak of Shiga Toxin-producing enterohemorrhagic E. coli (EHEC) in Germany and neighbouring countries in 2011 has shown this dramatically. Nearly 4.000 people were reported of being affected and more than 50 people died during the so called EHEC-crisis. As a result the consumers’ trust in the safety of fruits and vegetables decreased sharply.
Although much effort is made to prevent risks arising from food, food-borne diseases are an ever-present threat to the consumers’ health. The consumption of fresh food that is contaminated with pathogens like fungi, viruses or bacteria can cause food poisoning that leads to severe health damages or even death. The outbreak of Shiga Toxin-producing enterohemorrhagic E. coli (EHEC) in Germany and neighbouring countries in 2011 has shown this dramatically. Nearly 4.000 people were reported of being affected and more than 50 people died during the so called EHEC-crisis. As a result the consumers’ trust in the safety of fruits and vegetables decreased sharply.
Rural areas often lack affordable broadband Internet connectivity, mainly due to the CAPEX and especially OPEX of traditional operator equipment [HEKN11]. This digital divide limits the access to knowledge, health care and other services for billions of people. Different approaches to close this gap were discussed in the last decade [SPNB08]. In most rural areas satellite bandwidth is expensive and cellular networks (3G,4G) as well as WiMAX suffer from the usually low population density making it hard to amortize the costs of a base station [SPNB08].
An Empirical Evaluation of the Received Signal Strength Indicator for fixed outdoor 802.11 links
(2015)
For the evaluation of the received signal strength indication (RSSI) a different methodology compared to previous publications is introduced in this paper by exploiting a spectral scan feature of recent Qualcomm Atheros WiFi NICs. This method is compared to driver reports and to an industrial grade spectrum analyzer. During the conducted outdoor experiments a decreased scattering of the RSSI compared to previous publications is observed. By applying well-known mathematical tests for normality it is possible to show that the RSSI does not follow a normal distribution in a line-of-sight outdoor environment. The evaluated spectral scan features offers additional possibilities to develop interference classifiers which is an important step for frequency allocation in long-distance 802.11 networks.
Sweet sorghum (Sorghum bicolor (L.) moench), a crop that is grown by subsistence farmers in Zimbabwe was used to extract silica gel in order to assess its possible use as a raw material for the production of silica-based products. The gel was prepared from sodium silicate extracted from sweet sorghum bagasse ash by sodium hydroxide leaching. Results show that maximum yield can be obtained at pH 5 and with 3 M sodium concentration. The silica gel prepared at optimum pH 5 had a bulk density of 0.5626 g/cm3 and anestimated porosity of 71.87%. Silica gel aged over 10 h had improved moisture adsorption properties. X-ray fluorescence (XRF) determinations show that the silica content in the ash is 40.1%. Characterization of sweet sorghum ash and silica gels produced at pH 5, 7 and 8.5 by Fourier Transform Infrared spectroscopy gave absorption bands similar to those reported by other researchers.Transmission electron micrographs show that silica prepared under optimum conditions is amorphous and consisted of irregular particles. Sweet sorghum proved to be a potential low cost raw material for the production of silica gel.
Hox genes are an evolutionary highly conserved gene family. They determine the anterior-posterior body axis in bilateral organisms and influence the developmental fate of cells. Embryonic stem cells are usually devoid of any Hox gene expression, but these transcription factors are activated in varying spatial and temporal patterns defining the development of various body regions. In the adult body, Hox genes are among others responsible for driving the differentiation of tissue stem cells towards their respective lineages in order to repair and maintain the correct function of tissues and organs. Due to their involvement in the embryonic and adult body, they have been suggested to be useable for improving stem cell differentiations in vitro and in vivo. In many studies Hox genes have been found as driving factors in stem cell differentiation towards adipogenesis, in lineages involved in bone and joint formation, mainly chondrogenesis and osteogenesis, in cardiovascular lineages including endothelial and smooth muscle cell differentiations, and in neurogenesis. As life expectancy is rising, the demand for tissue reconstruction continues to increase. Stem cells have become an increasingly popular choice for creating therapies in regenerative medicine due to their self-renewal and differentiation potential. Especially mesenchymal stem cells are used more and more frequently due to their easy handling and accessibility, combined with a low tumorgenicity and little ethical concerns. This review therefore intends to summarize to date known correlations between natural Hox gene expression patterns in body tissues and during the differentiation of various stem cells towards their respective lineages with a major focus on mesenchymal stem cell differentiations. This overview shall help to understand the complex interactions of Hox genes and differentiation processes all over the body as well as in vitro for further improvement of stem cell treatments in future regenerative medicine approaches.
A major challenge modern society has to face is the increasing need for tissue regeneration due to degenerative diseases or tumors, but also accidents or warlike conflicts. There is great hope that stem cell-based therapies might improve current treatments of cardiovascular diseases, osteochondral defects or nerve injury due to the unique properties of stem cells such as their self-renewal and differentiation potential. Since embryonic stem cells raise severe ethical concerns and are prone to teratoma formation, adult stem cells are still in the focus of research. Emphasis is placed on cellular signaling within these cells and in between them for a better understanding of the complex processes regulating stem cell fate. One of the oldest signaling systems is based on nucleotides as ligands for purinergic receptors playing an important role in a huge variety of cellular processes such as proliferation, migration and differentiation. Besides their natural ligands, several artificial agonists and antagonists have been identified for P1 and P2 receptors and are already used as drugs. This review outlines purinergic receptor expression and signaling in stem cells metabolism. We will briefly describe current findings in embryonic and induced pluripotent stem cells as well as in cancer-, hematopoietic-, and neural crest-derived stem cells. The major focus will be placed on recent findings of purinergic signaling in mesenchymal stem cells addressed in in vitro and in vivo studies, since stem cell fate might be manipulated by this system guiding differentiation towards the desired lineage in the future.
Polyether and polyether/ester based TPU (thermoplastic polyurethanes) were investigated with wide-angle XRD (X-ray diffraction) and SAXS (small angle X-ray scattering). Furthermore, SAXS measurements were performed in the temperature range of 30 °C to 130 °C. Polyether based polymers exhibit only one broad diffraction signal in a region of 2 θ 15° to 25°. In case of polyurethanes with ether/ester modification, the broad diffraction signal arises with small sharp diffraction signals. SAXS measurements of polymers reveal the size and shape of the crystalline zones of the polymer. Between 30 °C and 130 °C the size of the crystalline zone changes significantly. The size decreases in most of investigated TPU. In the case of Desmopan 9365D an increase of the particle size was observed.
Mesenchymal stem cells (MSCs) are an attractive cell source for Regenerative Dentistry in particular due to their ability to differentiate towards osteoblasts, among other lineages. Tooth and jaw bone loss are frequent sequelae of traumatic and pathological conditions in both the young and the elderly and must be met by appropriate prosthetic replacements. For successful osseointegration of the dental implant a sufficient bone level is necessary. Besides the utilization of bone autografts or synthetic biomaterials, medical research is more and more focused on the utilization of MSCs. Compared to cells obtained from liposuction material, ectomesenchymal stem cells derived from the head area e.g. out of dental follicles or particulate, non-vascularized bone chips show a higher differentiation potential towards osteoblasts.
It is know that mesenchymal stem cells (MSCs) actively secretemultiple biologically-active factors during their process of differentiation which gives rise to a variey of cytotypes including bone and fatcells. It is also acknowledged that the chemokines secreted throughoutMSC differentiation may play an important role in the development and growth of tumor cells, although literature data appear somewhat indeterminate due to the contradictory evidence often found.
Over the past two decades many governments of low and middle income countries have started to introduce social protection measures or to extend the coverage and improve the functioning of public social protection systems. These reforms are a "global phenomenon" and can be observed in many African, Asian and Latin American countries. This paper focuses on international determinants for policy change within social protection by assessing the state of the art of both policy diffusion and policy transfer studies. Empirical studies of policy transfer and diffusion in the field of social protection are furthermore assessed in light of the theoretical background.
The paper examines the effectiveness of transgovernmental policy networks as a governance structure for policy diffusion. The analysis is based on a survey including 50 social protection policy maker and technical practitioner who are country delegates to transgovernmental policy networks within the policy area of social protection. The paper provides anecdotal empirical evidence that policy networks contribute to policy diffusion by inducing mutual learning processes.
Solar energy is one option to serve the rising global energy demand with low environmental Impact [1]. 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. Clouds are moving on a short term timescale and have a high influence on the available solar radiation, as they absorb, reflect and scatter parts of the incoming light [2]. However, modeling photovoltaic (PV) power yields with a spectral resolution and local cloud information gives new insights on the atmospheric impact on solar energy.