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Purpose To investigate how completing vocational re-training influenced income and employment days of working-age people with disabilities in the first 8 years after program admission. The investigation also included the influence of vocational re-training on the likelihood of receiving an earnings incapacity pension and on social security benefit receipt. Methods This retrospective cohort study with 8 years follow up was based on data from 2399 individuals who had completed either a 1-year vocational re-training program (n = 278), or a 2-year vocational re-training program (n = 1754) or who were admitted into re-training but never completed the program (n = 367). A propensity score-based method was used to account for observed differences and establish comparability between program graduates and program dropouts. Changes in outcomes were examined using the inverse probability-weighted regression adjustment method. Results After controlling for other factors, over the 8 years after program admission, graduates of 1-year re-training, on average, were employed for an additional 405 days, 95% CI [249 days, 561 days], and had earned €24,260 more than without completed re-training, 95% CI [€12,805, €35,715]. Two-year program completers, on average, were employed for 441 additional days, 95% CI [349 days, 534 days], and had earned €35,972 more than without completed re-training, 95% CI [€27,743, €44,202]. The programs also significantly reduced the number of days on social-security and unemployment benefits and lowered the likelihood of an earnings incapacity pension. Conclusion Policies to promote the labor market re-integration of persons with disabilities should consider that vocational re-training may be an effective tool for sustainably improving work participation outcomes.
CSR-Erfolgssteuerung
(2019)
Das Lehrbuch behandelt den CSR-Reformprozess, der Unternehmen zur globalen Sorgfaltspflicht (Due Diligence) auffordert. Die CSR-Berichterstattungpflicht, die Vergaberechtsreform und die Aufforderung zur Implementierung von Risikomanagementsystemen treffen dabei nicht nur große, sondern insbesondere auch mittlere und kleine Unternehmen (KMU). Das Buch soll daher die CSR-Relevanz für Unternehmen aller Größen transparent machen und Umsetzungsblockaden und -hemmnisse abbauen.
Die unterschiedlichen Facetten der digitalen Zukunft zu beleuchten – sei es die aktive Gestaltungsaufgabe der Politik, die ethischen und moralischen Anpassungen durch Digitalisierung in der Gesellschaft oder die technische und wirtschaftliche Verantwortung – und in Bezug zueinander zu setzen, ist Aufgabe und Ziel dieser Publikation. Im Zuge der digitalen Transformation ist zudem der Ruf nach einer neuen Kultur für Gesellschaft, Politik und Wirtschaft geboten.
Unternehmensberatungen stellen mit ihrem Leistungsportfolio einen bedeutenden Wirtschaftsfaktor dar. Die digitale Transformation und die sehr spezifischen Marktstrukturen der Gesundheitswirtschaft verlangen nach differenzierten Beratungsansätzen, die zugleich ein großes Beratungsfeld eröffnen und so das Wachstum und die Attraktivität von Unternehmensberatungen in diesem Segment stärken. Das Buch zeigt Themenfelder und Erfolgsfaktoren bei Beratungsprojekten auf. Dabei wird der Ansatz der Komplementärberatung in den Mittelpunkt gestellt, um den vielfältigen Change-Anforderungen bei der digitalen Transformation im Gesundheitswesen ganzheitlich gerecht zu werden.
Verbraucherpolitik
(2020)
The Peren-Clement index (PCI) is a methodology to analyze country-specific risk for businesses engaged in international trade and direct investment. This index, established in 1998, provides a guideline when deciding which foreign markets offer the possibility for additional business engagement and investment, and to what extent existing engagement or investment can be increased or should be reduced.
This work presents the preliminary research towards developing an adaptive tool for fault detection and diagnosis of distributed robotic systems, using explainable machine learning methods. Autonomous robots are complex systems that require high reliability in order to operate in different environments. Even more so, when considering distributed robotic systems, the task of fault detection and diagnosis becomes exponentially difficult.
To diagnose systems, models representing the behaviour under investigation need to be developed, and with distributed robotic systems generating large amount of data, machine learning becomes an attractive method of modelling especially because of its high performance. However, with current day methods such as artificial neural networks (ANNs), the issue of explainability arises where learnt models lack the ability to give explainable reasons behind their decisions.
This paper presents current trends in methods for data collection from distributed systems, inductive logic programming (ILP); an explainable machine learning method, and fault detection and diagnosis.
In the field of service robots, dealing with faults is crucial to promote user acceptance. In this context, this work focuses on some specific faults which arise from the interaction of a robot with its real world environment due to insufficient knowledge for action execution.
In our previous work [1], we have shown that such missing knowledge can be obtained through learning by experimentation. The combination of symbolic and geometric models allows us to represent action execution knowledge effectively. However we did not propose a suitable representation of the symbolic model.
In this work we investigate such symbolic representation and evaluate its learning capability. The experimental analysis is performed on four use cases using four different learning paradigms. As a result, the symbolic representation together with the most suitable learning paradigm are identified.
In Sensor-based Fault Detection and Diagnosis (SFDD) methods, spatial and temporal dependencies among the sensor signals can be modeled to detect faults in the sensors, if the defined dependencies change over time. In this work, we model Granger causal relationships between pairs of sensor data streams to detect changes in their dependencies. We compare the method on simulated signals with the Pearson correlation, and show that the method elegantly handles noise and lags in the signals and provides appreciable dependency detection. We further evaluate the method using sensor data from a mobile robot by injecting both internal and external faults during operation of the robot. The results show that the method is able to detect changes in the system when faults are injected, but is also prone to detecting false positives. This suggests that this method can be used as a weak detection of faults, but other methods, such as the use of a structural model, are required to reliably detect and diagnose faults.
Quantifying Interference in WiLD Networks using Topography Data and Realistic Antenna Patterns
(2019)
Ein Prüf- und Zertifizierungsstandard zur gesellschaftlichen Verantwortung von Organisationen
(2019)
Nach einem breiten Konsens in Gesellschaft, Politik und Wissenschaft lässt sich die gegenwärtige Art zu wirtschaften so nicht fortsetzen. Ein weltweit gültiger Zertifizierungsstandard, der einen einheitlichen und politisch neutralen Ordnungsrahmen zur gesellschaftlichen Verantwortung von Organisationen gegenüber Mensch und Natur zum Ziel hat, kann helfen, die sich dynamisch verändernden und jeweils notwendigen Anforderungen zu messen, deren Einhaltung (auch komparativ) nachzuweisen und ggf. notwendige Korrekturen zu definieren. Die internationale Norm DIN EN ISO/IEC 26000:2010 bietet einen grundsätzlich geeigneten Orientierungsrahmen zu gesellschaftlich verantwortlichem Handeln für Organisationen.
Synthesis of Substituted Hydroxyapatite for Application in Bone Tissue Engineering and Drug Delivery
(2019)
BWL-Klausuren für Dummies
(2019)
Gas Chromatography
(2019)
Gas chromatography (GC) is one of the most important types of chromatography used in analytical chemistry for separating and analyzing chemical organic compounds. Today, gas chromatography is one of the most widespread investigation methods of instrumental analysis. This technique is used in the laboratories of chemical, petrochemical, and pharmaceutical industries, in research institutes, and also in clinical, environmental, and food and beverage analysis. This book is the outcome of contributions by experts in the field of gas chromatography and includes a short history of gas chromatography, an overview of derivatization methods and sample preparation techniques, a comprehensive study on pyrazole mass spectrometric fragmentation, and a GC/MS/MS method for the determination and quantification of pesticide residues in grape samples.
The paper presents the topological reduction method applied to gas transport networks, using contraction of series, parallel and tree-like subgraphs. The contraction operations are implemented for pipe elements, described by quadratic friction law. This allows significant reduction of the graphs and acceleration of solution procedure for stationary network problems. The algorithm has been tested on several realistic network examples. The possible extensions of the method to different friction laws and other elements are discussed.
Survival of patients with pediatric acute lymphoblastic leukemia (ALL) after allogeneic hematopoietic stem cell transplantation (allo-SCT) is mainly compromised by leukemia relapse, carrying dismal prognosis. As novel individualized therapeutic approaches are urgently needed, we performed whole-exome sequencing of leukemic blasts of 10 children with post–allo-SCT relapses with the aim of thoroughly characterizing the mutational landscape and identifying druggable mutations. We found that post–allo-SCT ALL relapses display highly diverse and mostly patient-individual genetic lesions. Moreover, mutational cluster analysis showed substantial clonal dynamics during leukemia progression from initial diagnosis to relapse after allo-SCT. Only very few alterations stayed constant over time. This dynamic clonality was exemplified by the detection of thiopurine resistance-mediating mutations in the nucleotidase NT5C2 in 3 patients’ first relapses, which disappeared in the post–allo-SCT relapses on relief of selective pressure of maintenance chemotherapy. Moreover, we identified TP53 mutations in 4 of 10 patients after allo-SCT, reflecting acquired chemoresistance associated with selective pressure of prior antineoplastic treatment. Finally, in 9 of 10 children’s post–allo-SCT relapse, we found alterations in genes for which targeted therapies with novel agents are readily available. We could show efficient targeting of leukemic blasts by APR-246 in 2 patients carrying TP53 mutations. Our findings shed light on the genetic basis of post–allo-SCT relapse and may pave the way for unraveling novel therapeutic strategies in this challenging situation.
Mobile navigation apps are among the most used mobile applications and are often used as a baseline to evaluate new mobile navigation technologies in field studies. As field studies often introduce external factors that are hard to control for, we investigate how pedestrian navigation methods can be evaluated in virtual reality (VR). We present a study comparing navigation methods in real life (RL) and VR to evaluate if VR environments are a viable alternative to RL environments when it comes to testing these. In a series of studies, participants navigated a real and a virtual environment using a paper map and a navigation app on a smartphone. We measured the differences in navigation performance, task load and spatial knowledge acquisition between RL and VR. From these we formulate guidelines for the improvement of pedestrian navigation systems in VR like improved legibility for small screen devices. We furthermore discuss appropriate low-cost and low-space VR-locomotion techniques and discuss more controllable locomotion techniques.
Die Nachfrage nach nachhaltigen und ökologischen Bau- und Dämmstoffen wächst, besonders im Hinblick auf den fortschreitenden Klimawandel und die knapper werdenden fossilen Ressourcen. Eine mögliche Alternative zu traditionellen Baustoffen stellen dabei nachwachsende Rohstoffe dar, denn diese sind im Vergleich zu fossilen Ressourcen CO2-neutral. [1,2]
Dysregulation of IL12 Signaling As a Novel Cause of an Autoimmune Lymphoproliferative like Syndrome
(2014)
The Concept of Purpose, Travelling, and Connectivity: Three Pillars of Organization and Leadership
(2020)
Application developers constitute an important part of a digital platform’s ecosystem. Knowledge about psychological processes that drive developer behavior in platform ecosystems is scarce. We build on the lead userness construct which comprises two dimensions, trend leadership and high expected benefits from a solution, to explain how developers’ innovative work behavior (IWB) is stimulated. We employ an efficiencyoriented and a social-political perspective to investigate the relationship between lead userness and IWB. The efficiency-oriented view resonates well with the expected benefit dimension of lead userness, while the social-political view might be interpreted as a reflection of trend leadership. Using structural equation modeling, we test our model with a sample of over 400 developers from three platform ecosystems. We find that lead userness is indirectly associated with IWB and the performance-enhancing view to be the stronger predictor of IWB. Finally, we unravel differences between paid and unpaid app developers in platform ecosystems.
High-precision, multidimensional holes are required in many technical applications. Due to its undercut shape, these kind of holes are usually manufactured from two sides of the work piece including a time-consuming co-axial alignment. Compared to current state of the art, a one-sided drilling strategy has numerous advantages regarding flexibility, precision and process efficiency. In this work, a helical drilling optic and an ultrashort pulse laser are utilized to fabricate a rotationally symmetric multidimensional-shaped hole in one single process step. The influences of single pulse energy, pulse repetition rate, rotation speed of laser beam as well as the drilling time on ablation depth are investigated. By varying the pulse energy and pulse density, the deposited energy per unit length on the single helical path can be adapted and thus the ablation depth can be scaled. With the adapted laser energy deposition, a T-shaped hole with a uniformed depth of about 80 mu m inlet is fabricated. Morphological analysis on the hole wall show excellent drilling quality without recast layers or heat-affected zones and roughness Rq < 0.35 mu m.
Data-Driven Robot Fault Detection and Diagnosis Using Generative Models: A Modified SFDD Algorithm
(2019)
This paper presents a modification of the data-driven sensor-based fault detection and diagnosis (SFDD) algorithm for online robot monitoring. Our version of the algorithm uses a collection of generative models, in particular restricted Boltzmann machines, each of which represents the distribution of sliding window correlations between a pair of correlated measurements. We use such models in a residual generation scheme, where high residuals generate conflict sets that are then used in a subsequent diagnosis step. As a proof of concept, the framework is evaluated on a mobile logistics robot for the problem of recognising disconnected wheels, such that the evaluation demonstrates the feasibility of the framework (on the faulty data set, the models obtained 88.6% precision and 75.6% recall rates), but also shows that the monitoring results are influenced by the choice of distribution model and the model parameters as a whole.
„Auf uns hört ja keiner“
(2019)
Background: We evaluated the Wellion Galileo GLU/KET blood and ketone (ß-Hydroxybutyrate, ß-OHB) meter to demonstrate that it meets ISO15107:2015 regulatory approval criteria. Research Design and Methods: A total of 100 subjects (52 female, age: 30 to 84 years, diabetes: 10 type 1/90 type 2) with blood glucose levels distributed over the entire measurement range as required by the ISO15197 protocol were tested (double determinations with 3 strip lots and two devices). A similar test protocol was followed to test ß-OHB strip performance (reference devices: YSI 2300plus for glucose and STANBIO ß-HOB LiquiColor TestKit for ß-OHB). Precision was tested for glucose with 3 blood glucose concentrations (ß-OHB: 2 control solutions). Results: All glucose test-strip lots met the strict ISO acceptance criteria. Mean absolute relative difference (MARD) was 4.9% and all data pairs were in zone A of the consensus error grid. The ß-OHB test-strips also met the pre-defined acceptance criteria. Within-run and between-run precision was calculated to be 2.3% and 0.7% for the glucose strips (3.7%/0.8% for the ketone strips). Conclusions: When tested according to the ISO15197:2015 guideline, the device showed very accurate measurement performance for glucose and ß-OHB testing and fully met regulatory accuracy approval criteria.
Background: Virtual reality combined with a spherical treadmill is used across species for studying neural circuits underlying navigation and learning.
New method: We developed an optical flow-based method for tracking treadmill ball motion in real time using a single high-resolution camera.
Results: Tracking accuracy and timing were determined using calibration data. Ball tracking was performed at 500 Hz and integrated with an open source game engine for virtual reality projection. The projection was updated at 120 Hz with a latency with respect to ball motion of 30 ± 8 ms. The system was tested for behavior with fruit flies. The application and source code are available at https://github.com/ivan-vishniakou/neural-circuits-vr.
Comparison with existing method(s): Optical flow-based tracking of treadmill motion is typically achieved using optical mice. The camera-based optical flow tracking system developed here is based on off-the-shelf components and offers control over the image acquisition and processing parameters. This results in flexibility with respect to tracking conditions – such as ball surface texture, lighting conditions, or ball size – as well as camera alignment and calibration.
Conclusions: A fast system for rotational ball motion tracking suitable for virtual reality behavior with fruit flies was developed and characterized.
Walking has always been considered as the gold standard for navigation in Virtual Reality research. Though full rotation is no longer a technical challenge, physical translation is still restricted through limited tracked areas. While rotational information has been shown to be important, the benefit of the translational component is still unclear with mixed results in previous work. To address this gap, we conducted a mixed-method experiment to compare four levels of translational cues and control: none (using the trackpad of the HTC Vive controller to translate), upper-body leaning (sitting on a "NaviChair", leaning the upper-body to locomote), whole-body leaning/stepping (standing on a platform called NaviBoard, leaning the whole body or stepping one foot off the center to navigate), and full translation (physically walking). Results showed that translational cues and control had significant effects on various measures including task performance, task load, and simulator sickness. While participants performed significantly worse when they used a controller with no embodied translational cues, there was no significant difference between the NaviChair, NaviBoard, and actual walking. These results suggest that translational body-based motion cues and control from a low-cost leaning/stepping interface might provide enough sensory information for supporting spatial updating, spatial awareness, and efficient locomotion in VR, although future work will need to investigate how these results might or might not generalize to other tasks and scenarios.
