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In this paper, the radio frequency (RF) behavior of mechanically stressed coaxial and for the first time also twisted-pair transmission lines is investigated over their service life. The main goal is to enable predictive maintenance for cables in moving applications and avoid preventive replacement. This also reduces the use of high-cost resources. For this purpose, stranded and solid-core variants of coaxial and twisted-pair type cables are mechanically loaded on the two-pulley apparatus according to EN 50396. Their RF transmission (S21) behavior is measured using a vector network analyzer and presented over bending cycles. For the first time, the phase response of mechanically loaded transmission lines is evaluated with respect to their service life. Two significant causes for the increasing attenuation and altered phase response are identified: breakage in foil screen and increasing surface roughness on the copper conductors. The identified causes are supported with literature evidence. Through measurements and theoretical calculations, it is proven that the phase is much more suitable for an assessment of the remaining service life than the amplitude. The findings can be used to implement a cable monitoring system in industrial environments which monitors the lines in-situ and reminds the user to replace them, whenever a certain wear-level is reached.
Background: Improving movement control might be a promising treatment goal during chronic non-specific low back pain (CLBP) rehabilitation. The objective of the study is to evaluate the effect of a single bout of game-based real-time feedback intervention on trunk movement in patients with CLBP.
Methods: Thirteen CLBP patients (8female;41 ± 16 years;173 ± 10 cm;78 ± 22 kg) were included in this randomized cross-over pilot trial. During one laboratory session (2 h), participants performed three identical measurements on trunk movement all including: first, maximum angle of lateral flexion was assessed. Secondly, a target trunk lateral flexion (angle: 20°) was performed. Main outcome was maximum angle ([°]; MA). Secondary outcomes were deviation [°] from the target angle (angle reproduction; AR) and MA of the secondary movement planes (rotation; extension/flexion) during lateral flexion. The outcomes were assessed by an optical 3D-motion-capture-system (2-segment-trunk-model). The measurements were separated by 12-min of intervention and/or resting (randomly). The intervention involved a sensor-based trunk exergame (guiding an avatar through virtual worlds). After carryover effect-analysis, pre-to-post intervention data were pooled between the two sequences followed by analyses of variances (paired t-test).
Results: No significant change from pre to post intervention for MA or AR for any segment occurred for the main movement plane, lateral flexion (p > .05). The upper trunk segment showed a significant decrease of the MA for trunk extension/flexion from pre to post intervention ((4.4° ± 4.4° (95% CI 7.06–1.75)/3.5° ± 1.29° (95% CI 6.22–0.80); p = 0.02, d = 0.20).
Conclusions: A single bout of game-based real-time feedback intervention lead to changes in the secondary movement planes indicating reduced evasive motion during trunk movement.
The number of additive manufacturing methods and materials is growing rapidly, leaving gaps in the knowledge of specific material properties. A relatively recent addition is the metal-filled filament to be printed similarly to the fused filament fabrication (FFF) technology used for plastic materials, but with additional debinding and sintering steps. While tensile, bending, and shear properties of metals manufactured this way have been studied thoroughly, their fatigue properties remain unexplored. Thus, the paper aims to determine the tensile, fatigue, and impact strengths of Markforged 17-4 PH and BASF Ultrafuse 316L stainless steel to answer whether the metal FFF can be used for structural parts safely with the current state of technology. They are compared to two 316L variants manufactured via selective laser melting (SLM) and literature results. For extrusion-based additive manufacturing methods, a significant decrease in tensile and fatigue strength is observed compared to specimens manufactured via SLM. Defects created during the extrusion and by the pathing scheme, causing a rough surface and internal voids to act as local stress risers, handle the strength decrease. The findings cast doubt on whether the metal FFF technique can be safely used for structural components; therefore, further developments are needed to reduce internal material defects.
The data presented here contain information on cheating behavior from experiments and general self-reported attitudes related to honesty-related social norms and trust, together with individual-level demographic variables. Our sample included 493 university students in five countries, namely, Germany, Vietnam, Taiwan, China, and Japan. The experiment was monetarily incentivized based on the performance on a matrix task. The participants also answered a survey questionnaire. The dataset is valuable for academic researchers in sociology, psychology, and economics who are interested in honesty, norms, and cultural differences.
The concept of Circular Economy (CE) is becoming increasingly important in the pursuit of more sustainable societies. CE strategies are being applied in the sustainable management of a plethora of areas, such as energy, water, food and eco-industrial parks. The present paper focuses on the question of how CE principles can support the sustainable management of water in the agricultural sector around the world, considering different legislative environments, water resources management guidelines, environmental stressors, and CE practices. Considering these practices and circumstances, seven countries were compared: Brazil, Germany, Japan, Mexico, Morocco, Portugal, and Taiwan. Together, CE experts in the seven countries developed a set of 44 criteria to assess each of these areas. Broader establishment and respect of water resources legislation was found to be strongly correlated with lower agricultural water use. While the application of CE practices was found to not be correlated with lower consumption, this is still novel in most countries. Based on the studied countries, it can be concluded that a global CE agenda has not been reached for water resources. Further application and variety of practices is required to better represent the impact of CE on a national scale, but local success stories could support the wider application of CE in agriculture. The findings and the framework of the study can be applied to other countries in directing CE strategies for more sustainable water use in agriculture. Increasing CE implementation, motivated by legislation and better management can help ensure water security throughout nations.
Die umlagefinanzierte gesetzliche Rentenversicherung kann angesichts der demografischen Entwicklung eine auskömmliche Versorgung im Alter bald nicht mehr sichern. Indem die Bürger:innen über eine kapitalgedeckte Alterssicherung am Unternehmensvermögen mittelbar beteiligt werden, könnte die Rentenlücke zumindest teilweise geschlossen werden. Das Unternehmensvermögen sollte bei einem neuen Reformanlauf auch vollständig in die Erbschaftsteuer einbezogen werden; dabei darf aber der Fortbestand der Unternehmen nicht gefährdet werden. Die Erbschaftsteuer auf Unternehmensvermögen könnte dabei als Finanzierungsquelle für eine kapitalgedeckte Altersgrundsicherung dienen.
Disconnection in a left-hemispheric temporo-parietal network impairs multiplication fact retrieval
(2023)
Arithmetic fact retrieval has been suggested to recruit a left-lateralized network comprising perisylvian language areas, parietal areas such as the angular gyrus (AG), and non-neocortical structures such as the hippocampus. However, the underlying white matter connectivity of these areas has not been evaluated systematically so far. Using simple multiplication problems, we evaluated how disconnections in parietal brain areas affected arithmetic fact retrieval following stroke. We derived disconnectivity measures by jointly considering data from n = 73 patients with acute unilateral lesions in either hemisphere and a white-matter tractography atlas (HCP-842) using the Lesion Quantification Toolbox (LQT). Whole-brain voxel-based analysis indicated a left-hemispheric cluster of white matter fibers connecting the AG and superior temporal areas to be associated with a fact retrieval deficit. Subsequent analyses of direct gray-to-gray matter disconnections revealed that disconnections of additional left-hemispheric areas (e.g., between the superior temporal gyrus and parietal areas) were significantly associated with the observed fact retrieval deficit. Results imply that disconnections of parietal areas (i.e., the AG) with language-related areas (i.e., superior and middle temporal gyri) seem specifically detrimental to arithmetic fact retrieval. This suggests that arithmetic fact retrieval recruits a widespread left-hemispheric network and emphasizes the relevance of white matter connectivity for number processing.
Background: In recent years, the volume of medical knowledge and health data has increased rapidly. For example, the increased availability of electronic health records (EHRs) provides accurate, up-to-date, and complete information about patients at the point of care and enables medical staff to have quick access to patient records for more coordinated and efficient care. With this increase in knowledge, the complexity of accurate, evidence-based medicine tends to grow all the time. Health care workers must deal with an increasing amount of data and documentation. Meanwhile, relevant patient data are frequently overshadowed by a layer of less relevant data, causing medical staff to often miss important values or abnormal trends and their importance to the progression of the patient’s case.
Objective: The goal of this work is to analyze the current laboratory results for patients in the intensive care unit (ICU) and classify which of these lab values could be abnormal the next time the test is done. Detecting near-future abnormalities can be useful to support clinicians in their decision-making process in the ICU by drawing their attention to the important values and focus on future lab testing, saving them both time and money. Additionally, it will give doctors more time to spend with patients, rather than skimming through a long list of lab values.
Methods: We used Structured Query Language to extract 25 lab values for mechanically ventilated patients in the ICU from the MIMIC-III and eICU data sets. Additionally, we applied time-windowed sampling and holding, and a support vector machine to fill in the missing values in the sparse time series, as well as the Tukey range to detect and delete anomalies. Then, we used the data to train 4 deep learning models for time series classification, as well as a gradient boosting–based algorithm and compared their performance on both data sets.
Results: The models tested in this work (deep neural networks and gradient boosting), combined with the preprocessing pipeline, achieved an accuracy of at least 80% on the multilabel classification task. Moreover, the model based on the multiple convolutional neural network outperformed the other algorithms on both data sets, with the accuracy exceeding 89%.
Conclusions: In this work, we show that using machine learning and deep neural networks to predict near-future abnormalities in lab values can achieve satisfactory results. Our system was trained, validated, and tested on 2 well-known data sets to ensure that our system bridged the reality gap as much as possible. Finally, the model can be used in combination with our preprocessing pipeline on real-life EHRs to improve patients’ diagnosis and treatment.
For a detailed discussion of process mining, the objective of this paper is the analysis of the successful implementation of process mining in the practical fields of supply chain management. The research comprises the investigation of use cases in companies that are already actively using process mining.
Purpose: This research aims to highlight the applicability of process mining in the supply chain management business field.
Research Methodology: In order to examine the applicability of process mining in supply chain management a research study was conducted among experts in this business field. Further, theoretical findings were compared to the results and evaluated.
Results: Process Mining can be applied very well in the SCM area. The advantages that arise primarily reflect significant potential benefits and improved process throughput times. The information that can be gained from the operational areas supported by process mining is suitable for reliable decisions, both in the tactical and strategic areas.
Limitations: The results on the application of process mining show a certain generalization and have to be adapted and adjusted to the respective application case.
Contribution: This study is useful, especially for the purchasing and logistics business area.
Der Automobilhandel befindet sich in einer momentanen Phase des Umbruchs. Der Trend zum Kauferlebnis online, verstärkt durch die Pandemie, und die durch die Dieselproblematik entfachte Diskussion zum Emissionsausstoß und Fahrverboten für Verbrennungsmotoren im Fahrzeugbereich, treibt den Wandel zu elektrischen Antriebstechnologien an. Durch diese Umstellung ergeben sich neue Möglichkeiten für das Fahrzeug im Bereich der Digitalisierung. Die branchenübergreifende Digitalisierung findet sich auch in den neuen Vertriebssystemen der Automobilhersteller wieder. Hierbei ist zudem eine Veränderung der Absatzkanäle zu beobachten. Der Kunde weicht beim Autokauf davon ab, exklusiv zu dem Händler seines Vertrauens zu gehen und sich hier durch den gesamten Verkaufsprozess hinweg betreuen zu lassen. Vielmehr verschieben sich einzelne Teilbereiche in das Internet. So müssen etablierte Prozesse neugestaltet werden, um weiterhin im Markt und im Wettbewerb bestehen zu können.
Das Ziel dieser Arbeit ist die Beantwortung zweier Forschungsfragen. Zum einen soll der Status-Quo der Digitalisierung von Vertriebsinstrumenten im Autohaus untersucht werden. Konkret geht es dabei um die Frage, in welcher Art und Weise die Digitalisierung den Vertrieb beeinflusst und welche Effekte sich daraus ergeben. Zum anderen stellt sich die Frage wie die Digitalisierung in Form des Internets, als Absatzkanal für die Automobilindustrie geeignet ist, und ob derart komplexe Produkte wie ein Neufahrzeug über diesen Kanal abgesetzt werden können. Weiterhin soll betrachtet werden, welche Veränderungen in den Vertriebsstrukturen das beim stationären Autohändler verursacht.
Die Arbeit befasst sich ausschließlich mit der Digitalisierung bei Vertragshändlern mit Volumenzielen im Neuwagen-Bereich. Damit sind die Luxus- oder Premiummarken ausgeschlossen. Außerdem wird im Autohaus in zwei Kundenkategorien unterschieden. Es gibt die Großabnehmer und die Einzelkunden. Die Großabnehmer sind Unternehmen, die durch eine vordefinierte Anzahl an Mindestabnahmen einen besonderen Status und Konditionen genießen. Die Einzelkunden sind private Abnehmer oder gewerbliche Kunden, die die Mindestabnahme nicht erreichen. Die Arbeit beschränkt sich ausschließlich auf die Analyse und Auswirkungen der Veränderungen im Segment der Einzelkunden.