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We present the concrete realization of a virtual laboratory equipped with a pedagogical agent. Its functionality and media didactics takes into account the results of an usability test on a prototype system, and the students' demand on such an automated assistance as obtained from a preliminary survey. The pedagogical agent mediates between the content and the learner by activating him or her. To provide information about the learner's skills, we propose a pragmatic and simplified competence model that is based on fundamental representations in physics (experiment, figure, text and equation). Moreover, an automated feedback relates the student's self-assessment with the submitted answer to the correctness of the respective task. In consequence, the pedagogical agent enables mental reflection for a crucial review of the own learning process. Interestingly, learning pathways can be envisioned, thus, giving valuable insight into individual strengths and weaknesses.
Global change effects on biodiversity and human wellbeing call for improved long-term environmental data as a basis for science, policy and decision making, including increased interoperability, multifunctionality, and harmonization. Based on the example of two global initiatives, the International Long-Term Ecological Research (ILTER) network and the Group on Earth Observations Biodiversity Observation Network (GEO BON), we propose merging the frameworks behind these initiatives, namely ecosystem integrity and essential biodiversity variables, to serve as an improved guideline for future site-based long-term research and monitoring in terrestrial, freshwater and coastal ecosystems. We derive a list of specific recommendations of what and how to measure at a monitoring site and call for an integration of sites into co-located site networks across individual monitoring initiatives, and centered on ecosystems. This facilitates the generation of linked comprehensive ecosystem monitoring data, supports synergies in the use of costly infrastructures, fosters cross-initiative research and provides a template for collaboration beyond the ILTER and GEO BON communities.
Deep brain stimulation (DBS) is a neurosurgical intervention where electrodes are permanently implanted into the brain in order to modulate pathologic neural activity. The post-operative reconstruction of the DBS electrodes is important for an efficient stimulation parameter tuning. A major limitation of existing approaches for electrode reconstruction from post-operative imaging that prevents the clinical routine use is that they are manual or semi-automatic, and thus both time-consuming and subjective. Moreover, the existing methods rely on a simplified model of a straight line electrode trajectory, rather than the more realistic curved trajectory. The main contribution of this paper is that for the first time we present a highly accurate and fully automated method for electrode reconstruction that considers curved trajectories. The robustness of our proposed method is demonstrated using a multi-center clinical dataset consisting of N = 44 electrodes. In all cases the electrode trajectories were successfully identified and reconstructed. In addition, the accuracy is demonstrated quantitatively using a high-accuracy phantom with known ground truth. In the phantom experiment, the method could detect individual electrode contacts with high accuracy and the trajectory reconstruction reached an error level below 100 μm (0.046 ± 0.025 mm). An implementation of the method is made publicly available such that it can directly be used by researchers or clinicians. This constitutes an important step towards future integration of lead reconstruction into standard clinical care.
Static (one-legged stance) and dynamic (star excursion balance) postural control tests were performed by 14 adolescent athletes with and 17 without back pain to determine reproducibility. The total displacement, mediolateral and anterior-posterior displacements of the centre of pressure in mm for the static, and the normalized and composite reach distances for the dynamic tests were analysed. Intraclass correlation coefficients, 95% confidence intervals, and a Bland-Altman analysis were calculated for reproducibility. Intraclass correlation coefficients for subjects with (0.54 to 0.65), (0.61 to 0.69) and without (0.45 to 0.49), (0.52 to 0.60) back pain were obtained on the static test for right and left legs, respectively. Likewise, (0.79 to 0.88), (0.75 to 0.93) for subjects with and (0.61 to 0.82), (0.60 to 0.85) for those without back pain were obtained on the dynamic test for the right and left legs, respectively. Systematic bias was not observed between test and retest of subjects on both static and dynamic tests. The one-legged stance and star excursion balance tests have fair to excellent reliabilities on measures of postural control in adolescent athletes with and without back pain. They can be used as measures of postural control in adolescent athletes with and without back pain.
Introduction: Annually, 2 million sports-related injuries are reported in Germany of which athletes contribute to a large proportion. Multiple sport injury prevention programs designed to decrease acute and overuse injuries in athletes have been proven effective. Yet, the programs’ components, general or sports-specific, that led to these positive effects are uncertain. Despite not knowing about the superiority of sports-specific injury prevention programs, coaches and athletes alike prefer more specialized rather than generalized exercise programs. Therefore, this systematic review aimed to present the available evidence on how general and sports-specific prevention programs affect injury rates in athletes.
Methods: PubMed and Web of Science were electronically searched throughout April 2018. The inclusion criteria were publication dates Jan 2006–Dec 2017, athletes (11–45 years), exercise-based injury prevention programs and injury incidence. The methodological quality was assessed with the Cochrane Collaboration assessment tools.
Results: Of the initial 6619 findings, 15 studies met the inclusion criteria. In addition, 13 studies were added from reference lists and external sources making a total of 28 studies. Of which, one used sports-specific, seven general and 20 mixed prevention strategies. Twenty-four studies revealed reduced injury rates. Of the four ineffective programs, one was general and three mixed.
Conclusion: The general and mixed programs positively affect injury rates. Sports-specific programs are uninvestigated and despite wide discussion regarding the definition, no consensus was reached. Defining such terminology and investigating the true effectiveness of such IPPs is a potential avenue for future research.
Sustainable software products - Towards assessment criteria for resource and energy efficiency
(2018)
Many authors have proposed criteria to assess the “environmental friendliness” or “sustainability” of software products. However, a causal model that links observable properties of a software product to conditions of it being green or (more general) sustainable is still missing. Such a causal model is necessary because software products are intangible goods and, as such, only have indirect effects on the physical world. In particular, software products are not subject to any wear and tear, they can be copied without great effort, and generate no waste or emissions when being disposed of. Viewed in isolation, software seems to be a perfectly sustainable type of product. In real life, however, software products with the same or similar functionality can differ substantially in the burden they place on natural resources, especially if the sequence of released versions and resulting hardware obsolescence is taken into account. In this article, we present a model describing the causal chains from software products to their impacts on natural resources, including energy sources, from a life-cycle perspective. We focus on (i) the demands of software for hardware capacities (local, remote, and in the connecting network) and the resulting hardware energy demand, (ii) the expectations of users regarding such demands and how these affect hardware operating life, and (iii) the autonomy of users in managing their software use with regard to resource efficiency. We propose a hierarchical set of criteria and indicators to assess these impacts. We demonstrate the application of this set of criteria, including the definition of standard usage scenarios for chosen categories of software products. We further discuss the practicability of this type of assessment, its acceptability for several stakeholders and potential consequences for the eco-labeling of software products and sustainable software design.
Companies have made considerable progress in assessing the sustainability of their processes and products, including the information and communication technology (ICT) sector. However, it is surprising that little attention has been given to the sustainability performance of software products. For this article, we chose a case study approach to explore the extent, to which software manufacturers have considered sustainability criteria for their products. We selected a manufacturer of sustainability management software on the assumption that they would be more likely to integrate elements of sustainability performance in their products. In the case study, we applied a previously developed set of criteria for sustainable software (SCSS) using a questionnaire and experiments, to assess a web-based sustainability management software product regarding its sustainability performance. The assessment finds that despite a sustainability conscious manufacturer, a systematic assessment of sustainability regarding software products is missing in the case study. This implies that sustainability assessment for software products is still novel, corresponding knowledge is missing and suitable tools are not yet being widely applied in the industry. The SCSS presents a suitable approach to close this gap, but it does require further refinement, for example regarding its applicability to web-based software on external servers.
Containerization is one of the most important topics for modern data centers and web developers. Since the number of containers on one- and multi-node systems is growing, knowledge about the energy consumption behavior of single web-service containers is essential in order to save energy and, of course, money. In this article, we are going to show how the energy consumption behavior of single containerized web services/web apps changes while creating replicas of the service in order to scale and balance the web service.
Radar target simulator with complex-valued delay line modeling based on standard radar components
(2018)
With increasing radar activities in the automotive, industrial and private sector, there is a need to test radar sensors in their environment. A radar target simulator can help testing radar systems repeatably. In this paper, the authors present a concept of low-cost hardware for radar target simulation. The theoretical foundations are derived and analyzed. An implementation of a demonstrator operating in the 24 GHz ISM band is shown for which the dynamical range simulation was implemented in a FPGA with fast sampling ADCs and DACs. By using a FIR filtering approach a fine discretization of the range could be reached which will furthermore allow an inherent and automatic Doppler simulation by moving the target.
Life-threatening cardiomyopathy is a severe, but common, complication associated with severe trauma or sepsis. Several signaling pathways involved in apoptosis and necroptosis are linked to trauma- or sepsis-associated cardiomyopathy. However, the underling causative factors are still debatable. Heparan sulfate (HS) fragments belong to the class of danger/damage-associated molecular patterns liberated from endothelial-bound proteoglycans by heparanase during tissue injury associated with trauma or sepsis. We hypothesized that HS induces apoptosis or necroptosis in murine cardiomyocytes. By using a novel Medical-In silico approach that combines conventional cell culture experiments with machine learning algorithms, we aimed to reduce a significant part of the expensive and time-consuming cell culture experiments and data generation by using computational intelligence (refinement and replacement). Cardiomyocytes exposed to HS showed an activation of the intrinsic apoptosis signal pathway via cytochrome C and the activation of caspase 3 (both p < 0.001). Notably, the exposure of HS resulted in the induction of necroptosis by tumor necrosis factor α and receptor interaction protein 3 (p < 0.05; p < 0.01) and, hence, an increased level of necrotic cardiomyocytes. In conclusion, using this novel Medical-In silico approach, our data suggest (i) that HS induces necroptosis in cardiomyocytes by phosphorylation (activation) of receptor-interacting protein 3, (ii) that HS is a therapeutic target in trauma- or sepsis-associated cardiomyopathy, and (iii) indicate that this proof-of-concept is a first step toward simulating the extent of activated components in the pro-apoptotic pathway induced by HS with only a small data set gained from the in vitro experiments by using machine learning algorithms.