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In the RoboCup@Home domestic service robot competition, complex tasks such as "get the cup from the kitchen and bring it to the living room" or "find me this and that object in the apartment" have to be accomplished. At these competitions the robots may only be instructed by natural language. As humans use qualitative concepts such as "near" or "far", the robot needs to cope with them, too. For our domestic robot, we use the robot programming and plan language Readylog, our variant of Golog. In previous work we extended the action language Golog, which was developed for the high-level control of agents and robots, with fuzzy concepts and showed how to embed fuzzy controllers in Golog. In this paper, we demonstrate how these notions can be fruitfully applied to two domestic service robotic scenarios. In the first application, we demonstrate how qualitative fluents based on a fuzzy set semantics can be deployed. In the second program, we show an example of a fuzzy controller for a follow-a-person task.
A Gamified Information System (GIS) implements game concepts and elements, such as affordances and game design principles to motivate people. Based on the idea to develop a GIS to increase the motivation of software developers to perform software quality tasks, the research work at hand aims at investigating relevant requirements from that target group. Therefore, 14 interviews with software development experts are conducted and analyzed. According to the results, software developers prefer the affordances points, narrative storytelling in a multiplayer and a round-based setting. Furthermore, six design principles for the development of a GIS are derived.
Virtual Reality (VR) offers novel possibilities for remote training regardless of the availability of the actual equipment, the presence of specialists, and the training locations. Research shows that training environments that adapt to users' preferences and performance can promote more effective learning. However, the observed results can hardly be traced back to specific adaptive measures but the whole new training approach. This study analyzes the effects of a combined point and leveling VR-based gamification system on assembly training targeting specific training outcomes and users' motivations. The Gamified-VR-Group with 26 subjects received the gamified training, and the Non-Gamified-VR-Group with 27 subjects received the alternative without gamified elements. Both groups conducted their VR training at least three times before assembling the actual structure. The study found that a level system that gradually increases the difficulty and error probability in VR can significantly lower real-world error rates, self-corrections, and support usages. According to our study, a high error occurrence at the highest training level reduced the Gamified-VR-Group's feeling of competence compared to the Non-Gamified-VR-Group, but at the same time also led to lower error probabilities in real-life. It is concluded that a level system with a variable task difficulty should be combined with carefully balanced positive and negative feedback messages. This way, better learning results, and an improved self-evaluation can be achieved while not causing significant impacts on the participants' feeling of competence.
Gamification and gamified information systems (GIS) apply video game elements to encourage the work on boring and everyday tasks. Meanwhile, several research works provide evidence that gamification increases efficiency and effectivity of such tasks. The paper at hand investigates the health care sector, which is challenged with cost pressure and suffers in process efficiency. We hypothesize that GIS may improve the efficiency and quality of care processes. By applying an interview-based content analysis, the paper at hand evaluates gamification elements in an assisted living environment and provides three research contributions. First, insights into relevant GIS affordances and application examples for assisted living facilities are given. Second, assisted living experts evaluate GIS design guidelines. Both the relevant affordances and design principles comprise a basis for the development of a GIS for social workers in assisted living facilities. Third, potential adoption barriers and design guidelines for GIS in assisted living are presented.
We report on the synthesis and CO gas-sensing properties of mesoporous tin(IV) oxides (SnO2). For the synthesis cetyltrimethylammonium bromide (CTABr) was used as a structure-directing agent; the resulting SnO2 powders were applied as films to commercially available sensor substrates by drop coating. Nitrogen physisorption shows specific surface areas up to 160 m2·g-1 and mean pore diameters of about 4 nm, as verified by TEM. The film conductance was measured in dependence on the CO concentration in humid synthetic air at a constant temperature of 300 °C. The sensors show a high sensitivity at low CO concentrations and turn out to be largely insensitive towards changes in the relative humidity. We compare the materials with commercially available SnO2-based sensors.
Gas sensor investigation based on a catalytically activated thin-film thermopile for H2O2 detection
(2010)
In aseptic filling systems, hydrogen peroxide vapour is commonly used for the reduction of microbial contaminations in carton packages. In this process, the germicidal efficiency of the vapour depends especially on the H₂O₂ concentration. To monitor the H₂O₂ concentration, a calorimetric H₂O₂ gas sensor based on a catalytically activated thin-film thermopile is investigated. Two different sensor layouts, namely a circular and a linear form, as well as two various material pairs such as tungsten/nickel and gold/nickel, have been examined for the realization of a thin-film thermopile. Additionally, manganese oxide and palladium particles have been compared as responsive catalysts towards H₂O₂. The thin-film sensors have been investigated at various H₂O₂ concentrations, gas temperatures and flow rates.
The international partnership of space agencies has agreed to proceed forward to the Moon sustainably. Activities on the Lunar surface (0.16 g) will allow crewmembers to advance the exploration skills needed when expanding human presence to Mars (0.38 g). Whilst data from actual hypogravity activities are limited to the Apollo missions, simulation studies have indicated that ground reaction forces, mechanical work, muscle activation, and joint angles decrease with declining gravity level. However, these alterations in locomotion biomechanics do not necessarily scale to the gravity level, the reduction in gastrocnemius medialis activation even appears to level off around 0.2 g, while muscle activation pattern remains similar. Thus, it is difficult to predict whether gastrocnemius medialis contractile behavior during running on Moon will basically be the same as on Mars. Therefore, this study investigated lower limb joint kinematics and gastrocnemius medialis behavior during running at 1 g, simulated Martian gravity, and simulated Lunar gravity on the vertical treadmill facility. The results indicate that hypogravity-induced alterations in joint kinematics and contractile behavior still persist between simulated running on the Moon and Mars. This contrasts with the concept of a ceiling effect and should be carefully considered when evaluating exercise prescriptions and the transferability of locomotion practiced in Lunar gravity to Martian gravity.
Rehabilitative body weight supported gait training aims at restoring walking function as a key element in activities of daily living. Studies demonstrated reductions in muscle and joint forces, while kinematic gait patterns appear to be preserved with up to 30% weight support. However, the influence of body weight support on muscle architecture, with respect to fascicle and series elastic element behavior is unknown, despite this having potential clinical implications for gait retraining. Eight males (31.9 ± 4.7 years) walked at 75% of the speed at which they typically transition to running, with 0% and 30% body weight support on a lower-body positive pressure treadmill. Gastrocnemius medialis fascicle lengths and pennation angles were measured via ultrasonography. Additionally, joint kinematics were analyzed to determine gastrocnemius medialis muscle–tendon unit lengths, consisting of the muscle's contractile and series elastic elements. Series elastic element length was assessed using a muscle–tendon unit model. Depending on whether data were normally distributed, a paired t-test or Wilcoxon signed rank test was performed to determine if body weight supported walking had any effects on joint kinematics and fascicle–series elastic element behavior. Walking with 30% body weight support had no statistically significant effect on joint kinematics and peak series elastic element length. Furthermore, at the time when peak series elastic element length was achieved, and on average across the entire stance phase, muscle–tendon unit length, fascicle length, pennation angle, and fascicle velocity were unchanged with respect to body weight support. In accordance with unchanged gait kinematics, preservation of fascicle–series elastic element behavior was observed during walking with 30% body weight support, which suggests transferability of gait patterns to subsequent unsupported walking.
With a steady increase of regulatory requirements for business processes, automation support of compliance management is a field garnering increasing attention in Information Systems research. Several approaches have been developed to support compliance checking of process models. One major challenge for such approaches is their ability to handle different modeling techniques and compliance rules in order to enable widespread adoption and application. Applying a structured literature search strategy, we reflect and discuss compliance-checking approaches in order to provide an insight into their generalizability and evaluation. The results imply that current approaches mainly focus on special modeling techniques and/or a restricted set of types of compliance rules. Most approaches abstain from real-world evaluation which raises the question of their practical applicability. Referring to the search results, we propose a roadmap for further research in model-based business process compliance checking.
Breast cancer resistance protein (BCRP) is expressed in various tissues, such as the gut, liver, kidney and blood brain barrier (BBB), where it mediates the unidirectional transport of substrates to the apical/luminal side of polarized cells. Thereby BCRP acts as an efflux pump, mediating the elimination or restricting the entry of endogenous compounds or xenobiotics into tissues and it plays important roles in drug disposition, efficacy and safety. Bcrp knockout mice (Bcrp−/−) have been used widely to study the role of this transporter in limiting intestinal absorption and brain penetration of substrate compounds. Here we describe the first generation and characterization of a mouse line humanized for BCRP (hBCRP), in which the mouse coding sequence from the start to stop codon was replaced with the corresponding human genomic region, such that the human transporter is expressed under control of the murine Bcrp promoter. We demonstrate robust human and loss of mouse BCRP/Bcrp mRNA and protein expression in the hBCRP mice and the absence of major compensatory changes in the expression of other genes involved in drug metabolism and disposition. Pharmacokinetic and brain distribution studies with several BCRP probe substrates confirmed the functional activity of the human transporter in these mice. Furthermore, we provide practical examples for the use of hBCRP mice to study drug-drug interactions (DDIs). The hBCRP mouse is a promising model to study the in vivo role of human BCRP in limiting absorption and BBB penetration of substrate compounds and to investigate clinically relevant DDIs involving BCRP.
Generation and Characterization of a Novel Multidrug Resistance Protein 2 Humanized Mouse Line
(2012)
The multidrug resistance protein (MRP) 2 is predominantly expressed in liver, intestine, and kidney, where it plays an important role in the excretion of a range of drugs and their metabolites or endogenous compounds into bile, feces, and urine. Mrp knockout [Mrp2(−/−)] mice have been used recently to study the role of MRP2 in drug disposition. Here, we describe the first generation and initial characterization of a mouse line humanized for MRP2 (huMRP2), which is nulled for the mouse Mrp2 gene and expresses the human transporter in the organs and cell types where MRP2 is normally expressed. Analysis of the mRNA expression for selected cytochrome P450 and transporter genes revealed no major changes in huMRP2 mice compared with wild-type controls. We show that human MRP2 is able to compensate functionally for the loss of the mouse transporter as demonstrated by comparable bilirubin levels in the humanized mice and wild-type controls, in contrast to the hyperbilirubinemia phenotype that is observed in MRP2(−/−) mice. The huMRP2 mouse provides a model to study the role of the human transporter in drug disposition and in assessing the in vivo consequences of inhibiting this transporter by compounds interacting with human MRP2.
Compared with rodents and many other animal species, the human cytochrome P450 (P450) Cyp2c gene cluster varies significantly in the multiplicity of functional genes and in the substrate specificity of its enzymes. As a consequence, the use of wild-type animal models to predict the role of human CYP2C enzymes in drug metabolism and drug-drug interactions is limited. Within the human CYP2C cluster CYP2C9 is of particular importance, because it is one of the most abundant P450 enzymes in human liver, and it is involved in the metabolism of a wide variety of important drugs and environmental chemicals. To investigate the in vivo functions of cytochrome P450 Cyp2c genes and to establish a model for studying the functions of CYP2C9 in vivo, we have generated a mouse model with a deletion of the murine Cyp2c gene cluster and a corresponding humanized model expressing CYP2C9 specifically in the liver. Despite the high number of functional genes in the mouse Cyp2c cluster and the reported roles of some of these proteins in different biological processes, mice deleted for Cyp2c genes were viable and fertile but showed certain phenotypic alterations in the liver. The expression of CYP2C9 in the liver also resulted in viable animals active in the metabolism and disposition of a number of CYP2C9 substrates. These mouse lines provide a powerful tool for studying the role of Cyp2c genes and of CYP2C9 in particular in drug disposition and as a factor in drug-drug interaction.
Table of Contents Introduction 1. Generative Manufacturing Processes 2. Classification of Generative Manufacturing Processes 3. Application of Generative Processes on the Fabrication of Ceramic Parts 3.1 Extrusion 3.2 3D-Printing 3.3 Sintering – Laser Sintering 3.4 Layer-Laminate Processes 3.5 Stereolithography (sometimes written: Stereo Lithography) 4. Layer Milling 5. Conclusion - Vision
Disruption experiments targeted at the Bacillus licheniformis degSU operon and GFP-reporter analysis provided evidence for promoter activity immediately upstream of degU. pMutin mediated concomitant introduction of the degU32 allele – known to cause hypersecretion in Bacillus subtilis – resulted in a marked increase in protease activity. Application of 5-fluorouracil based counterselection through establishment of a phosphoribosyltransferase deficient Δupp strain eventually facilitated the marker-free introduction of degU32 leading to further protease enhancement achieving levels as for hypersecreting wild strains in which degU was overexpressed. Surprisingly, deletion of rapG – known to interfere with DegU DNA-binding in B. subtilis – did not enhance protease production neither in the wild type nor in the degU32 strain. The combination of degU32 and Δupp counterselection in the type strain is not only equally effective as in hypersecreting wild strains with respect to protease production but furthermore facilitates genetic strain improvement aiming at biological containment and effectiveness of biotechnological processes.
Genetically humanized mice for proteins involved in drug metabolism and toxicity and mice engrafted with human hepatocytes are emerging as promising in vivo models for improved prediction of the pharmacokinetic, drug–drug interaction, and safety characteristics of compounds in humans. This is an overview on the genetically humanized and chimeric liver-humanized mouse models, which are illustrated with examples of their utility in drug metabolism and toxicity studies. The models are compared to give guidance for selection of the most appropriate model by highlighting advantages and disadvantages to be carefully considered when used for studies in drug discovery and development.
1. Drug metabolizing enzymes and transporters play important roles in the absorption, metabolism, tissue distribution and excretion of various compounds and their metabolites and thus can significantly affect their efficacy and safety. Furthermore, they can be involved in drug–drug interactions which can result in adverse responses, life-threatening toxicity or impaired efficacy. Significant species differences in the interaction of compounds with drug metabolizing enzymes and transporters have been described.
2. In order to overcome the limitation of animal models in accurately predicting human responses, a large variety of mouse models humanized for drug metabolizing enzymes and to a lesser extent drug transporters have been created.
3. This review summarizes the literature describing these mouse models and their key applications in studying the role of drug metabolizing enzymes and transporters in drug bioavailability, tissue distribution, clearance and drug–drug interactions as well as in human metabolite testing and risk assessment.
4. Though such humanized mouse models have certain limitations, there is great potential for their use in basic research and for testing and development of new medicines. These limitations and future potentials will be discussed.
GHEtool is a Python package that contains all the functionalities needed to deal with borefield design. It is developed for both researchers and practitioners. The core of this package is the automated sizing of borefield under different conditions. The sizing of a borefield is typically slow due to the high complexity of the mathematical background. Because this tool has a lot of precalculated data, GHEtool can size a borefield in the order of tenths of milliseconds. This sizing typically takes the order of minutes. Therefore, this tool is suited for being implemented in typical workflows where iterations are required.
GHEtool also comes with a graphical user interface (GUI). This GUI is prebuilt as an exe-file because this provides access to all the functionalities without coding. A setup to install the GUI at the user-defined place is also implemented and available at: https://www.mech.kuleuven.be/en/tme/research/thermal_systems/tools/ghetool.
To train end users how to interact with digital systems is indispensable to ensure a strong computer security. 'Competence Developing Game'-based approaches are particularly suitable for this purpose because of their motivation-and simulation-aspects. In this paper the Competence Developing Game 'GHOST' for cybersecurity awareness trainings and its underlying patterns are described. Accordingly, requirements for an 'Competence Developing Game' based training are discussed. Based on these requirements it is shown how a game can fulfill these requirements. A supplementary game interaction design and a corresponding evaluation study is shown. The combination of training requirements and interaction design is used to create a 'Competence Developing Game'-based training concept. A part of these concept is implemented into a playable prototype that serves around one hour of play respectively training time. This prototype is used to perform an evaluation of the game and training aspects of the awareness training. Thereby, the quality of the game aspect and the effectiveness of the training aspect are shown.
Searching optimal continuous-thrust trajectories is usually a difficult and time-consuming task. The solution quality of traditional optimal-control methods depends strongly on an adequate initial guess because the solution is typically close to the initial guess, which may be far from the (unknown) global optimum. Evolutionary neurocontrol attacks continuous-thrust optimization problems from the perspective of artificial intelligence and machine learning, combining artificial neural networks and evolutionary algorithms. This chapter describes the method and shows some example results for single- and multi-phase continuous-thrust trajectory optimization problems to assess its performance. Evolutionary neurocontrol can explore the trajectory search space more exhaustively than a human expert can do with traditional optimal-control methods. Especially for difficult problems, it usually finds solutions that are closer to the global optimum. Another fundamental advantage is that continuous-thrust trajectories can be optimized without an initial guess and without expert supervision.
Low-thrust space propulsion systems enable flexible high-energy deep space missions, but the design and optimization of the interplanetary transfer trajectory is usually difficult. It involves much experience and expert knowledge because the convergence behavior of traditional local trajectory optimization methods depends strongly on an adequate initial guess. Within this extended abstract, evolutionary neurocontrol, a method that fuses artificial neural networks and evolutionary algorithms, is proposed as a smart global method for low-thrust trajectory optimization. It does not require an initial guess. The implementation of evolutionary neurocontrol is detailed and its performance is shown for an exemplary mission.