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Carsharing is an integral part of the transformation toward flexible and sustainable mobility. New carsharing programs are entering the market to challenge large operators by offering innovative services. This study investigates the use of generative machine learning models for creating synthetic data to support carsharing decision–making when data access is limited. To this end, it explores the evaluation, selection, and implementation of leading-edge methods, such as generative adversarial networks (GANs) and variational autoencoders (VAEs), to generate synthetic tabular transaction data of carsharing trips. The study analyzes usage data of an emerging carsharing program that is expanding its services to include free-floating electric vehicles (EVs). The results show that augmenting real training data with synthetic samples improves predictive modeling of upcoming trips by up to 4.63%. These results support carsharing researchers and practitioners in generating and leveraging synthetic mobility data to develop solutions to real-world decision support problems in carsharing.
We study the action of the nonlinear mapping G[z] between real or complex Banach spaces in the vicinity of a given curve with respect to possible linearization, emerging patterns of level sets, as well as existing solutions of G[z]=0. The results represent local generalizations of the standard implicit or inverse function theorem and of Newton's Lemma, considering the order of approximation needed to obtain solutions of G[z]=0.
The main technical tool is given by Jordan chains with increasing rank, used to obtain an Ansatz, appropriate for transformation of the nonlinear system to its linear part. The family of linear mappings is restricted to the case of an isolated singularity.
Geometrically, the Jordan chains define a generalized cone around the given curve, composed of approximate solutions of order 2k with k denoting the maximal rank of Jordan chains needed to ensure k-surjectivity of the linear family. Along these lines, the zero set of G[z] in the cone is calculated immediately, agreeing up to the order of k−1 with the given approximation. Hence, the results may also be interpreted as a version of Tougeron's implicit function theorem or Hensel's Lemma in Banach spaces, essentially restricted to the arc case of a single variable.
Finally, by considering a left shift of the Jordan chains, the Ansatz can be modified in a systematic way to obtain a sequence of refined versions of linearization theorems and Newton Lemmas in Banach spaces.
Intensive research in the field over the past decades highlighted the complexity of aroma partition. Still, no general model for predicting aroma matrix interactions could be described. The vision outlined here is to discover the blueprint for the prediction of aroma partitioning behavior in complex foods by using machine learning techniques. Therefore, known physical relationships governing aroma release are combined with machine learning to predict the 𝐾𝑚𝑔 value of aroma compounds in foods of different compositions. The approach will be optimized on a data set of a specific food product. Afterward, the model should be transferred using explainable artificial intelligence (XAI) to a different food category to validate its applicability. Furthermore, we can transfer our approach to other relevant questions in the food field such as aroma quantification, extraction processes, or food spoilage.
Many modern automated vehicle sensor systems use light detection and ranging (LiDAR) sensors. The prevailing technology is scanning LiDAR, where a collimated laser beam illuminates objects sequentially point-by-point to capture 3D range data. In current systems, the point clouds from the LiDAR sensors are mainly used for object detection. To estimate the velocity of an object of interest (OoI) in the point cloud, the tracking of the object or sensor data fusion is needed. Scanning LiDAR sensors show the motion distortion effect, which occurs when objects have a relative velocity to the sensor. Often, this effect is filtered, by using sensor data fusion, to use an undistorted point cloud for object detection. In this study, we developed a method using an artificial neural network to estimate an object’s velocity and direction of motion in the sensor’s field of view (FoV) based on the motion distortion effect without any sensor data fusion. This network was trained and evaluated with a synthetic dataset featuring the motion distortion effect. With the method presented in this paper, one can estimate the velocity and direction of an OoI that moves independently from the sensor from a single point cloud using only one single sensor. The method achieves a root mean squared error (RMSE) of 0.1187 m s−1 and a two-sigma confidence interval of [−0.0008 m s−1, 0.0017 m s−1] for the axis-wise estimation of an object’s relative velocity, and an RMSE of 0.0815 m s−1 and a two-sigma confidence interval of [0.0138 m s−1, 0.0170 m s−1] for the estimation of the resultant velocity. The extracted velocity information (4D-LiDAR) is available for motion prediction and object tracking and can lead to more reliable velocity data due to more redundancy for sensor data fusion.
Automated vehicles use light detection and ranging (LiDAR) sensors for environmental scanning. However, the relative motion between the scanning LiDAR sensor and objects leads to a distortion of the point cloud. This phenomenon is known as the motion distortion effect, significantly degrading the sensor’s object detection capabilities and generating false negative or false positive errors. In this work, we have introduced ray tracing-based deterministic and analytical approaches to model the motion distortion effect on the scanning LiDAR sensor’s performance for simulation-based testing. In addition, we have performed dynamic test drives at a proving ground to compare real LiDAR data with the motion distortion effect simulation data. The real-world scenarios, the environmental conditions, the digital twin of the scenery, and the object of interest (OOI) are replicated in the virtual environment of commercial software to obtain the synthetic LiDAR data. The real and the virtual test drives are compared frame by frame to validate the motion distortion effect modeling. The mean absolute percentage error (MAPE), the occupied cell ratio (OCR), and the Barons cross-correlation coefficient (BCC) are used to quantify the correlation between the virtual and the real LiDAR point cloud data. The results show that the deterministic approach matches the real measurements better than the analytical approach for the scenarios in which the yaw rate of the ego vehicle changes rapidly.
The effect of ionomer to carbon (I/C) weight ratio and relative humidity (RH) on cathode catalyst degradation was investigated by comprehensive in situ characterization. Membrane electrode assemblies (MEA) with I/C ratios of 0.5, 0.8 and 1.2 were subjected to an accelerated stress test performed at 40, 70 and 100% RH. The results show an increasing loss in electrochemical active surface area (ECSA) for both higher I/C ratios and RH during voltage cycling. To differentiate between ionomer and water connected ECSA, carbon monoxide stripping measurements were performed at varying RH. Before degradation, all MEAs show comparable total ECSA values, while higher I/C ratios lead to a larger fraction of ionomer connected ECSA. After degradation, ECSA measurements of the lowest I/C ratio showed a relatively higher loss of Pt in contact with ionomer than Pt in contact with water, while an opposite trend was observed for higher I/C ratios. H2 /N2 impedance measurements showed drastically increasing protonic catalyst layer resistances for decreasing RH especially at low I/C ratios, which might hinder Pt 2+ ion diffusion towards the membrane, hence decreasing the ECSA loss. Limiting current measurements show increasing molecular O 2 diffusion resistances at end of test for samples with higher I/C ratios and higher ECSA loss.
Die Corona-Pandemie hat tiefe Spuren auch in der empirischen Sozialforschung hinterlassen. Insbesondere qualitativ Forschende sehen die Pandemie als Einschnitt und Zensur. Dieser Artikel versucht dagegen, die Herausforderungen der Pandemie mit Blick auf die arbeitssoziologische Fallstudienforschung als Beschleunigung von Wandlung wie Heterogenität arbeitssoziologischer Forschung zu begreifen. Dies wird anhand der theoretisch-konzeptionellen, methodologischen wie empirischen Ebenen aufgezeigt. Die Pandemie und ihre Folgen führen demnach weniger zu einer substanziellen Krise insbesondere der qualitativen Forschung, als vielmehr zur Reflexion eigener Grundannahmen und Vorgehensweisen auf den genannten Ebenen: Empirisch wie forschungspolitisch wird das eigene Erwartungsmanagement herausgefordert, methodisch wie konzeptionell verlangt der heterogenere Zugang zu Interviewees, Betrieben und die damit verbundenen Veränderungen in den Fallrekonstruktionen Antworten.
The development of Automated Driving Systems (ADS) has the potential to revolutionize the transportation industry, but it also presents significant safety challenges. One of the key challenges is ensuring that the ADS is safe in the event of Foreseeable Misuse (FM) by the human driver. To address this challenge, a case study on simulation-based testing to mitigate FM by the driver using the driving simulator is presented. FM by the human driver refers to potential driving scenarios where the driver misinterprets the intended functionality of ADS, leading to hazardous behavior. Safety of the Intended Functionality (SOTIF) focuses on ensuring the absence of unreasonable risk resulting from hazardous behaviors related to functional insufficiencies caused by FM and performance limitations of sensors and machine learning-based algorithms for ADS. The simulation-based application of SOTIF to mitigate FM in ADS entails determining potential misuse scenarios, conducting simulation-based testing, and evaluating the effectiveness of measures dedicated to preventing or mitigating FM. The major contribution includes defining (i) test requirements for performing simulation-based testing of a potential misuse scenario, (ii) evaluation criteria in accordance with SOTIF requirements for implementing measures dedicated to preventing or mitigating FM, and (iii) approach to evaluate the effectiveness of the measures dedicated to preventing or mitigating FM. In conclusion, an exemplary case study incorporating driver-vehicle interface and driver interactions with ADS forming the basis for understanding the factors and causes contributing to FM is investigated. Furthermore, the test procedure for evaluating the effectiveness of the measures dedicated to preventing or mitigating FM by the driver is developed in this work.
As the adoption of battery electric buses (BEBs) in public transportation systems grows, the need for precise energy consumption forecasting becomes increasingly important. Accurate predictions are essential for optimizing routes, charging schedules, and ensuring adequate operational range. This paper introduces an innovative forecasting methodology that combines a propulsion and auxiliary energy model with a novel concept, the environment generator. This approach addresses the primary challenge in electric bus energy forecasting: estimating future environmental conditions, such as weather, passenger load, and traffic patterns, which significantly impact energy demand. The environment generator plays a crucial role by providing the energy models with realistic input data. This study validates various models with different levels of model complexity against real-world operational data from a case study of over one year with 16 electric buses in Göttingen, Germany. Our analysis thoroughly examines influencing factors on energy consumption, like altitude, temperature, passenger load, and driving patterns. In order to comprehensively understand energy demands under varying operational conditions, the methodology integrates data-driven models and physical simulations into a modular and highly accurate energy predictor. The results demonstrate the effectiveness of our approach in providing more accurate energy consumption forecasts, which is essential for efficient electric bus fleet management. This research contributes to the growing body of knowledge in electric vehicle energy prediction and offers practical insights for transit authorities and operators in optimizing electric bus operations.
Hintergrund:
Nicht nur in stationären pflegerischen Kontexten, sondern auch im Privatbereich wird digitalen Technologien ein hohes Potenzial zugeschrieben. Somit geraten pflegende An- und Zugehörige als Zielgruppe für digitale Angebote in den Fokus. Obwohl pflegende Angehörige heterogene Bedarfslagen und Lebenssituationen aufweisen, sind diese ebenso häufig mit ähnlichen Herausforderungen konfrontiert: unübersichtliche Angebotslandschaften zu Leistungs- und Beratungszugängen sowie ein hoher organisatorischer und zeitlicher Aufwand zur Koordination der Pflege. Um diesen Herausforderungen zu begegnen, stehen auch in Deutschland vermehrt digitale Angebote zur Verfügung, welche bei diesen Tätigkeiten Unterstützung bieten sollen.
Fragestellung:
Im Rahmen der Studie „DiVa – Digitale Versorgungsanwendungen“ wurde der Frage nachgegangen, welche Anforderungen und Wünsche pflegende Angehörige an für sie konzipierte Apps haben. Anhand einer marktreifen Smartphone-App wurde untersucht, in welchem Zusammenhang die App in realen Pflegesettings genutzt wird und ob, und unter welchen Bedingungen, sie von pflegenden Angehörigen als Unterstützung im Pflegealltag wahrgenommen wird.
Methode:
Im Zeitraum 09/2022 – 08/2023 wurde eine frei verfügbare Smartphone-App von 16pflegenden Angehörigen über mehrere Monate genutzt. Mit allen Teilnehmenden wurden jeweils zwei qualitative, leitfadengestützte Interviews durchgeführt (vor und nach der Nutzung der Anwendung). Die Auswertung erfolgte mithilfe der Inhaltsanalyse nach Kuckartz.
Ergebnisse:
Die Ergebnisse verdeutlichen eine Diskrepanz zwischen einer allgemein positiven Einschätzung der App und deren Funktionen einerseits und einem geringen Nutzungsverhalten bzw. einer kaum wahrgenommenen Erleichterung andererseits. In diesem Zusammenhang kommt dem Zeitpunkt innerhalb der Pflegebiografie, zu welchem die Teilnehmenden die App nutzen, eine hohe Bedeutung zu. So erleben die informell Pflegenden, die ihre Angehörigen bereits über einen längeren Zeitraum pflegen, durch die Nutzung der App – im Vergleich zu den bereits eingespielten Abläufen und bekannten Informationskanälen im Pflegealltag – kaum Erleichterung. Ein potenzieller Mehrwert und eine Entlastung durch die App werden zu Beginn einer Pflegeübernahme gesehen. Insgesamt wurde die App punktuell genutzt, die Zufriedenheit mit den darin aufbereiteten Informationen war u. a. von der individuellen Pflegesituation abhängig. Die Teilnehmenden weisen auf bisher nicht integrierte, aber wünschenswerte Anpassungen hin, z. B. regionale Informationen.
Schlussfolgerung:
Die Ergebnisse zeigen die Bedeutung des frühzeitigen Wissens um digitale Technologien für die Angehörigenpflege: Anwendungen, welche auf Informationen, Koordination und Organisation abzielen, entfalten ihr erhofftes Unterstützungspotenzial vor allem, wenn sie von Beginn an in den Alltag integriert werden können. Die Befunde belegen zudem, dass es eine zentrale Herausforderung ist, informell Pflegende frühzeitig über die Existenz und Möglichkeiten digitaler Versorgungsanwendungen zu informieren. Als weitere Voraussetzungen für eine breite Akzeptanz von Pflege-Apps wurden u. a. eine vertrauenswürdige Darstellung der Inhalte, deren Individualisierbarkeit und Aktualität genannt. Die Ergebnisse können wertvolle Einblicke in die Gestaltung und Umsetzung digitaler Lösungen für die häusliche Pflege liefern, insbesondere wenn es darum geht, die Bedürfnisse und Erwartungen informell Pflegender zu berücksichtigen.
Scenario-based testing is essential for Highly Automated Driving (HAD) vehicles to determine the safety-related input parameters and their boundaries. The increasing complexity, vehicle functions, and operational design pose new challenges for scenario-based testing, as the number of scenarios is enormous. Therefore, an efficient and systematic process is required in the various stages of scenario-based testing. The contribution of this study is to provide sensitivity information of safety related parameters and support logical scenario reduction. This paper presents an approach that supports to optimize the safety-related parameters boundary towards logical scenario reduction. Additionally, sensitivity analysis is applied by computing Variance- Based Sensitivity Analysis (VBSA) indices and prioritize the input parameters. Two datasets are investigated by VBSA based on the input parameters. One dataset is based on the samples from realworld scenarios and other dataset is derived from the samples considering statistic distributions with a specific parameter range. Moreover, the proposed approach is applied to an exemplary use case and the outcomes are demonstrated.
Sustainability is a critical challenge in modern tourism, exacerbated by climate change and globalization. Thanks to digitization, data-driven approaches constitute a key technology for addressing related issues, such as overtourism. However, the overarching complexity of the touristic data landscape, amplified by the interplay of diverse digital platform ecosystems, poses considerable challenges to both data owners and consumers. To mitigate such issues, knowledge graphs (KGs) have received significant attention. KGs focus on data quality by employing unified data models and continuous data refinements, making them well-suited for data-driven applications. Although promising, many challenges must be addressed to make KGs useful in practice. This paper overviews the state of the art of the field and identifies avenues for future research, explicitly focusing on touristic value and sustainability. Following our results, future research should focus on different areas, notably real-time knowledge graph population, distributed and parallelized processes, and ontologies for dynamic data types.
This paper reviews the recent literature on the “social ranking problem”, that is, the problem of converting group rankings into individual rankings. We introduce and categorize existing social ranking methods and we briefly explain their attributes. Three main categories of social ranking methods are identified: lexicographic social rankings, methods based on voting mechanisms, and those inspired by the theory of coalitional games. An open-source R package called socialranking for computing the majority of the existing social rankings is also presented and discussed.
Computing Shapley values for large cooperative games is an NP-hard problem. For practical applications, stochastic approximation via permutation sampling is widely used. In the context of machine learning applications of the Shapley value, the concept of antithetic sampling has become popular. The idea is to employ the reverse permutation of a sample in order to reduce variance and accelerate convergence of the algorithm. We study this approach for the Shapley and Banzhaf values, as well as for the Owen value which is a solution concept for games with precoalitions. We combine antithetic samples with established stratified sampling algorithms. Finally, we evaluate the performance of these algorithms on four different types of cooperative games.
Motion sickness research has always been shaped by current events. With the advent of highly automated vehicles (HAVs), the topic is currently being revisited as 60% of users of HAV functions are expected to suffer from motion sickness. Failure to address this condition will jeopardize user acceptance of HAV functions. We investigated the vestibular mechanisms of motion misinterpretation and hypothesized that cross-coupled stimuli induce more sensory conflict and lead to higher motion sickness incidence compared to the non-coupled control condition. We conducted an experiment on a dynamic driving simulator with realistic motion profiles and analyzed the influence of cross-coupled motion on motion sickness incidence. Results show no significant difference in motion sickness incidence between cross-coupled and non-coupled motion profiles. Further research is needed to investigate the thresholds of the Coriolis effect and should include the measurement of compensatory or inertial head motion of participants.
Im November/Dezember 2022 führte das Bayerische Zentrum für Tourismus das dritte Jahr in Folge eine Online-Befragung unter Erstsemesterstudierenden an acht bayerischen Universitäten und Hochschulen durch. Die Umfrageergebnisse bieten einen exemplarischen Einblick in berücksichtigte Aspekte bei der Wahl der Hochschule und des Studiengangs, Vorbildfunktionen, Berufs- und Lebensziele, aktuelle Sorgen und Ängste, das Reiseverhalten und Assoziationen zum Thema Reisen der Erstsemesterstudierenden in Bayern.
Im Fokus der Befragung steht insbesondere die Generation Z, allerdings erheben die gewonnenen Daten keinen Repräsentativitätsanspruch für Erstsemesterstudierende in Bayern. Dennoch vermittelt die Gegenüberstellung der Umfrageergebnisse der drei Erhebungsreihen einen Eindruck von den jüngeren Studierendengenerationen sowie von möglichen zukünftigen Entwicklungstendenzen in den untersuchten Lebens- und Themenbereichen.
The Asymmetric Public Goods Game (APGG) C++ framework offers an easy to use environment to study game theoretical questions. Specifically, it is designed to address questions in the domain of asymmetric public goods games.
We hereby publish version 1.1.2 of our software APGG (Release for DOI via Zenodo for paper in JOSS, the Journal of Open Source Software).
The Asymmetric Public Goods Game (APGG) C++ framework offers an easy to use environment to study game theoretical questions. Specifically, it is designed to address questions in the domain of asymmetric public goods games. The modular architecture allows for a vast amount of scenarios and setups for experimenting with different public goods games, using easy to change parameters. Users can experiment with well mixed and structured populations as well as with symmetric and asymmetric payoffs. APGG also features group level payoffs and individual payoffs, and different evolutionary selection mechanisms (Miller et al., 1995) and replication schemes. Results are automatically saved in semantic and descriptive structures and can be easily visualized with the included Python scripts. This paper aims to explain the functionality and the structure of the framework, to show the workflow that APGG follows, to present the different modules that are available, and to show how APGG can be used to run experiments with public goods games on example scenarios.
This paper has the goal to propose an approach to enable reliable planning of BEBs in a traffic simulation which acts as the virtual environment. It was shown that the defaults for the vehicle trajectories from the traffic simulation SUMO, introduce significant errors. With some fine tuning and optimization of the vehicle behavior, reasonable results can be obtained from the traffic simulation. This can be used for planning of new bus networks considering many aspects, like energy demand, impact of traffic on delays and the resulting charging times at terminal stations.
In diesem Beitrag wird ein Manipulatormodell zur Verwendung in einem Entwurfsprozess für die Manipulatormechanik vorgestellt. Das Ziel ist Schwingungen zu minimieren und die Genauigkeit applikationsspezifisch zu entwerfen. Aus geeigneten Modellansätzen der einzelnen Roboterkomponenten, wie der Tragstruktur, den Wälzlagern, der Verkabelung und der Fügestellen wird ein Gesamtmodell einer seriellen Sechs-Achs-Kinematik in Modelica erstellt. Für den Antriebsstrang werden Modellansätze für Kompaktgetriebe, Riementriebe, Wellen und Zahnräder abgeleitet. Eine Validierung erfolgt durch eine Modalanalyse durch Selbstanregung.
During the early stages of the COVID-19 pandemic, stringent measures were implemented in most countries to limit social contact between residents of long-term care facilities (LTCF) and visitors. The objective of this scoping review was to identify and map evidence of direct and indirect consequences of contact restrictions, guided by three conceptual perspectives: (1) stress and learned helplessness (i.e., failure to use coping behaviors even when they are available and actionalble); (2) social contact loss; and (3) ‘total institution’ (i.e., a facility operates following a fixed plan due to spelled-out rules and norms, controlled by institutional representatives). We used the framework for conducting a scoping review by Arksey and O'Malley; included were peer-reviewed manuscripts reporting on the outcomes of contact restrictions from the beginning of the pandemic until the end of 2020. After removing duplicates, 6,656 records were screened and 62 manuscripts included. Results pertaining to the stress and learned helplessness perspective primarily focused on depressive symptoms, showing substantial increases compared to the pre-pandemic period. Studies examining cognitive and functional decline, as well as non-COVID-19 related mortality, were limited in number and presented mixed findings. The majority of study outcomes related to the social contact loss perspective focused on loneliness, but the study designs did not adequately allow for comparisons with the pre-pandemic status. The evidence concerning outcomes related to the 'total Institution' perspective was inconclusive. Although detrimental effects of social isolation in the long-term care context found support particularly in the negative affect domain, other outcome areas did not allow for definitive conclusions due to considerable variations in findings and, in some cases, insufficient statistical power.
Decarbonisation of heat generation has become a priority for district heating network operators. In order to avoid the use of fossil-fired boilers, operators need to know peaks in heat demand in advance. Accurate thermal load forecasting is playing an increasingly important role in this respect. This paper presents the final results of the research project “deepDHC” (deep learning for district heating and cooling) funded by the German Federal Ministry for Economic Affairs and Climate Action (BMWK). The three-year project focused on systematically benchmarking thermal load forecasts for district heating networks, based on state-of-the-art machine learning methods. The analysis covers a variety of machine learning techniques, such as neural networks – including latest deep learning methods – (e.g. LSTM, TFT, ESN, RC), decision trees (random forests, adaptive boosting, XGB) and statistical methods (SARIMAX). In addition, the impact of combining methods by so-called “stacking” was investigated. Training and validation of the machine learning algorithms was based on historical operating data from the district heating network for the city of Ulm in Germany, in combination with historical weather data, and weather forecasts. Thermal load forecasts – typically for three days ahead – are presented and compared against one another. An automatic tuning routine was developed as part of the project, which enables regular re-training of the machine learning algorithms based on the latest operating data from the heating network. Furthermore, a web interface for real-time forecasting was developed and implemented at the power station.
Die Verfügbarkeit von Produktionsdaten ist eine zentrale Herausforderung der zerspanenden Industrie. Herstellern von Maschinen, Maschinenbauteilen und Sensoren fehlt es an Informationen über das Verhalten ihrer Produkte im Einsatz, um Optimierungspotenziale zu erkennen. Im Fokus des Forschungsprojektes Dione-X stehen daher der sichere und souveräne Datenaustausch entlang der Wertschöpfungskette und die Entwicklung von datengetriebenen Geschäftsmodellen.
The electrification of the transportation sector leads to an increased deployment of lithium-ion batteries in vehicles. Today, traction batteries are installed, for example, in electric cars, electric buses, and electric boats. These use-cases place different demands on the battery. In this work, simulated data from 60 electric cars and field data from 82 electric buses and six electric boats from Germany are used to quantify a set of stress factors relevant to battery operation and life expectancy depending on the mode of transportation. For this purpose, the open-source tool SimSES designed initially to simulate battery operation in stationary applications is extended toward analyzing mobile applications. It now allows users to simulate electric vehicles while driving and charging. The analyses of the three means of transportation show that electric buses, for example, consume between 1 and 1.5 kWh/km and that consumption is lowest at ambient temperatures around 20 °C. Electric buses are confronted with 0.4–1 equivalent full cycle per day, whereas the analyzed set of car batteries experience less than 0.18 and electric boats between 0.026 and 0.3 equivalent full cycles per day. Other parameters analyzed include mean state-of-charges, mean charging rates, and mean trip cycle depths. Beyond these evaluations, the battery parameters of the transportation means are compared with those of three stationary applications. We reveal that stationary storage systems in home storage and balancing power applications generate similar numbers of equivalent full cycles as electric buses, which indicates that similar batteries could be used in these applications. Furthermore, we simulate the influence of different charging strategies and show their severe impact on battery degradation stress factors in e-transportation. To facilitate widespread and diverse usage, all profile and analysis data relevant to this work is provided as open data as part of this work.
Die Corona-Pandemie forderte im Zeitraffer Veränderungen (nicht nur) von der Arbeitswelt. Für die qualitative (Arbeits-)Forschung ist dies thematisch wie methodologisch herausfordernd. Ausgehend von der These, dass sich insbesondere qualitative Forschungsmethoden notwendig durch eine gewisse Fluidität auszeichnen, wird am Beispiel eigener partizipativer Forschung aufgezeigt, dass Forschungsmethoden durchaus virtuell durchgeführt werden können – und in Zukunft ggf. sogar müssen.
Ageing and digitalization are two major developments of the 21st century. Particularly, smartphone ownership increased to about over 80 % globally. Meanwhile, smartphones also gained great popularity among older adults, nonetheless, many still show fear of contact. The multi-national project Easierphone aims at empowering older adults and other vulnerable persons to effectively use smartphones. A senior-friendly app, Easierphone, simplifies smartphones while replacing the common android interface with an easier-to-use one. In addition, the Easierphone app enables two smartphones to be connected remotely to facilitate virtual assistance. A participative design is applied to conduct tests with older adults in three different pilots, in three different countries. Semi-structured interviews, try-out of the app, individual follow-up discussions and co-creation workshops are conducted to collect data. The Easierphone app to date is received positively by potential end-users. Many of the diverse functionalities of the app could be improved with feedback from test participants. The development process is an iterative one, in between each pilot, to achieve best possible adjustments to the app. The preliminary results indicate that fear of contact still prevails, nonetheless. The simplified interface seems to provide a basis for older adults to use their smartphones with more confidence.
Im Rahmen des Forschungsprojektes AIR – AI-basierter Recommender für nachhaltigen Tourismus – wurden Gästebefragungen in Form von Face to Face-Interviews in allen sechs Use Cases durchgeführt. Diese Form der Bedarfsanalyse soll dazu dienen, Informationen über die Demographie der Gäste, touristische Verhaltensmuster, Gründe für die Zielauswahl und Wahrnehmung des Zielgebiets und das Informationsverhalten zu erhalten. Die Ergebnisse der Befragungen im Use Case Nordsee Schleswig-Holstein - Sylt werden in diesem Bericht dargestellt.
Im Rahmen des Forschungsprojektes AIR – AI-basierter Recommender für nachhaltigen Tourismus – wurden Gästebefragungen in Form von Face to Face-Interviews in allen sechs Use Cases durchgeführt. Diese Form der Bedarfsanalyse soll dazu dienen, Informationen über die Demographie der Gäste, touristische Verhaltensmuster, Gründe für die Zielauswahl und Wahrnehmung des Zielgebiets und das Informationsverhalten zu erhalten. Die Ergebnisse der Befragungen im Use Case Nordsee Schleswig-Holstein - Speicherkoog werden in diesem Bericht dargestellt.
Im Rahmen des Forschungsprojektes AIR – AI-basierter Recommender für nachhaltigen Tourismus – wurden Gästebefragungen in Form von Face to Face-Interviews in allen sechs Use Cases durchgeführt. Diese Form der Bedarfsanalyse soll dazu dienen, Informationen über die Demographie der Gäste, touristische Verhaltensmuster, Gründe für die Zielauswahl und Wahrnehmung des Zielgebiets und das Informationsverhalten zu erhalten. Die Ergebnisse der Befragungen im Use Case Nordsee Schleswig-Holstein - Büsum werden in diesem Bericht dargestellt.
Dieser Beitrag untersucht, unter welchen Bedingungen Digitalisierung in der Pflege wirksam werden kann. Davon wird auch abhängen, ob eine Finanzierungsbereitschaft entsteht. Es wird aufgezeigt, dass Digitalisierung keine Effekte erbringt, wenn nicht zugleich die Offenheit besteht, vorhandene Strukturen und Abläufe zu hinterfragen und Zuständigkeiten neu zu ordnen. Es werden auch zwei Vorschläge für schrittweise Zuständigkeitsverschiebungen
vorgestellt.
CARE REGIO ist ein vom Bayerischen Staatsministerium für Gesundheit und Pflege gefördertes Verbundprojekt mit einer Laufzeit von insgesamt fünf Jahren. Der Verbund wurde vom Ministerium beauftragt, Bayerisch Schwaben als Leitregion für Pflege Digital zu etablieren, so dass technische und digitale Neuerungen in der Pflegepraxis schneller Einzug finden. Dadurch sollen Pflegebedürftige und Pflegende in ihrem Alltag unterstützt werden. Aus diesem Grund werden Plattformen und Formate geschaffen, mit denen ein Informationsaustausch zwischen den einzelnen Akteur*innen im Gesundheitswesen stattfinden kann. Dies erfolgt mit dem Ziel, Best-Practice-Anwendungen zu fördern und diese in der Pflegepraxis umzusetzen. Dabei liegt der Fokus bei den Endnutzer*innen, deren Partizipation bei der Umsetzung und Evaluation erwünscht ist.
Im Rahmen des Forschungsprojektes AIR – AI-basierter Recommender für nachhaltigen Tourismus – wurden Gästebefragungen in Form von Face to Face-Interviews in allen sechs Use Cases durchgeführt. Diese Form der Bedarfsanalyse soll dazu dienen, Informationen über die Demographie der Gäste, touristische Verhaltensmuster, Gründe für die Zielauswahl und Wahrnehmung des Zielgebiets, das Informationsverhalten sowie die Offenheit für Lenkungssysteme zu erhalten. Die Ergebnisse der Befragungen im Use Case Nordsee Schleswig-Holstein - St. Peter-Ording werden in diesem Bericht dargestellt.
Battery systems are extensively used in smart energy systems in many different applications, such as Frequency Containment Reserve or Self-Consumption Increase. The behavior of a battery in a particular operation scenario is usually summarized using different key performance indicators (KPIs). Some of these indicators such as efficiency indicate how much of the total electric power supplied to the battery is actually used. Other indicators, such as the number of charging-discharging cycles or the number of charging-discharging swaps, are of relevance for deriving the aging and degradation of a battery system. Obtaining these indicators is very time-demanding: either a set of lab experiments is run, or the battery system is simulated using a battery simulation model. This work instead proposes a machine learning (ML) estimation of battery performance indicators derived from time series input data. For this purpose, a random forest regressor has been trained using the real data of electricity grid frequency evolution, household power demand, and photovoltaic power generation. The results obtained in the research show that the required KPIs can be estimated rapidly with an average relative error of less than 10%. The article demonstrates that the machine learning approach is a suitable alternative to obtain a very fast rough approximation of the expected behavior of a battery system and can be scaled and adapted well for estimation queries of entire fleets of battery systems
A Methodology to Model the Rain and Fog Effect on the Performance of Automotive LiDAR Sensors
(2023)
In this work, we introduce a novel approach to model the rain and fog effect on the light detection and ranging (LiDAR) sensor performance for the simulation-based testing of LiDAR systems. The proposed methodology allows for the simulation of the rain and fog effect using the rigorous applications of the Mie scattering theory on the time domain for transient and point cloud levels for spatial analyses. The time domain analysis permits us to benchmark the virtual LiDAR signal attenuation and signal-to-noise ratio (SNR) caused by rain and fog droplets. In addition, the detection rate (DR), false detection rate (FDR), and distance error derror of the virtual LiDAR sensor due to rain and fog droplets are evaluated on the point cloud level. The mean absolute percentage error (MAPE) is used to quantify the simulation and real measurement results on the time domain and point cloud levels for the rain and fog droplets. The results of the simulation and real measurements match well on the time domain and point cloud levels if the simulated and real rain distributions are the same. The real and virtual LiDAR sensor performance degrades more under the influence of fog droplets than in rain.
The discourse around digitalisation has become detached from the lived reality of the world of work. This discourse is dominated by vague, nebulous promises about new models of work on the one hand and dire warnings of a mass replacement of human labour on the other. Drawing on the work of Erich Fromm, we argue that this creates a risk of regression, as people turn to ‘traditional’ authority figures or a fatalistic solutionism that places unconditional faith in technology. We instead propose an alternative approach rooted in people’s actual experiences that looks for ways that digital technology can be used to support and augment, rather than replace, human labour.
Background: Sexually transmitted infections (STIs) represent a global health risk. Adolescents are at increased risk of infection for several reasons such as lack of knowledge, risky sexual behaviors, and lack of behavioral sills (eg, to negotiate safer sex). Given the fact that adolescents often use digital media and that serious games are considered to have the potential to change knowledge, attitudes and behavior, serious games represent an opportunity for the prevention of STIs.
Objective: The aim of this systematic review was to identify and systematically summarize the dimensions that have been investigated in primary studies on serious games targeting STI prevention among adolescents.
Methods: A systematic review was conducted in PubMed and Web of Science. Studies published from 2009 to 2021 were included that assessed the effectiveness of serious games on adolescent sexual health. A total of 18 studies met the inclusion criteria and were categorized according to dimensions of effectiveness and user experience.
Results: Various dimensions of effectiveness and aspects of user experience were investigated in the primary studies. In total, 9 dimensions of effectiveness were observed: sexual behavior, behavioral intentions, knowledge, attitudes and beliefs, self-efficacy and personal limitations, character traits and future orientation, environmental and individual risk factors, risk perception and risk assessment, as well as normative beliefs and (social) norms. Furthermore, several dimensions related to user experience were investigated in primary studies, that is, motivation, acceptability, trustworthiness, comprehensibility, handling and control, perceived effectiveness, as well as satisfaction.
Conclusions: This review provides an overview of serious games interventions that are vastly different in approach, content, and even platform. In previous studies, knowledge has already been comprehensively assessed, and a positive influence of serious games on knowledge about sexual topics is evident. The results clearly show that adolescents’ sexual knowledge has been increased by the serious games interventions. However, methodological and content differences in the surveys make it difficult to draw conclusions about the effectiveness related to changes in attitudes and behavior.
The COVID-19 pandemic has necessitated support for continued learning in frontline practitioners through online digital mediums that are convenient and fast to maintain physical distancing. Nurses are already neglected professionals for support in training for infection control, leadership, and communication in Pakistan and other developing countries. For that reason, we aimed to deliver a WhatsApp-based intervention for continued learning in nurses who are currently working in both private and public sector. A 12-week intervention was delivered to 208 nurses (102 in the control group and 106 in the intervention group) who had been employed in the clinical setting during data collection. The analysis reveals that nurses in the intervention group show significantly better results for learning in “infection prevention and control” and “leadership and communication.” Results of a content analysis based on participant's feedback also confirm that the WhatsApp-based intervention is a valuable tool for education. This study highlights the effectiveness of online-based digital interventions as a convenient training tool for awareness and management of infectious diseases, leadership, and communication during COVID-19 and beyond. Furthermore, this study emphasizes that group interventions with other healthcare practitioners and the role of on-going longer WhatsApp-based interventions can become integral tools to support continued learning and patient safety practices.
Das vorliegende „DNVF Memorandum Gesundheitskompetenz (Teil 2) – Operationalisierung und Messung von Gesundheitskompetenz aus Sicht der Versorgungsforschung“ des Deutschen Netzwerks Versorgungsforschung e.V. (DNVF) stellt die Fortführung des Memorandums „DNVF Memorandum Gesundheitskompetenz (Teil 1) – Hintergrund, Gegenstand und Fragestellungen in der Versorgungsforschung“ dar. Neben den allgemeinen Anforderungen an die Messung der Gesundheitskompetenz, beschäftigt sich dieses Memorandum auch mit den speziellen Anforderungen, wie die Abgrenzung zu verwandten Konstrukten, den Unterschieden zwischen performanzbasierten und Selbsteinschätzungsverfahren, den Unterschieden zwischen generischen und spezifischen Instrumenten, dem Einsatz von Screeninginstrumenten sowie der Messung der Gesundheitskompetenz bei speziellen Personengruppen. Weiterhin werden Besonderheiten bei der Messung der digitalen Gesundheitskompetenz, Potenziale qualitativer und partizipativer Forschungszugänge sowie forschungsethische Gesichtspunkte bei der Messung der Gesundheitskompetenz erarbeitet. Ein besonderer Wert wird auf den Praxisbezug gelegt, der am Ende der jeweiligen Abschnitte mit einem Fazit für die Versorgungsforschung aufgegriffen wird. Abschließend wird einen Blick auf Herausforderungen und Forschungsdesiderate im Zusammenhang mit der Messung von Gesundheitskompetenz im Rahmen der Versorgungsforschung geworfen.
Background: The outbreak of the novel coronavirus disease (COVID-19) has posed multiple challenges to healthcare systems. Evidence suggests that mental well-being is badly affected due to compliance with preventative measures in containing the COVID-19 pandemic. This study aims to explore the role of positive mental health (subjective sense of wellbeing) to cope with fears related to COVID-19 and general anxiety disorder in the Pashtun community in Pakistan.
Methods: A cross-sectional survey was conducted among 501 respondents from Khyber Pakhtunkhwa participating in an online-based study. We performed correlational analysis, hierarchical linear regression and structural equational modeling (SEM) to analyze the role of mental health in reducing fears and general anxiety disorder.
Results: The results of the SEM show that positive mental health has direct effects in reducing the fear related to COVID-19 (β = − 0.244, p < 0.001) and general anxiety (β = − 0.210, p < 0.001). Fears of COVID-19 has a direct effect on increasing general anxiety (β = 0.480). In addition, positive mental health also has an indirect effect (β = − 0.117, p < 0.001) on general anxiety (R2 = 0.32, p < 0.001) through reducing fear of coronavirus.
Conclusion: Based on these findings, there is a need to develop community health policies emphasizing on promotive and preventive mental health strategies for people practicing social/physical distancing.
In light of the current public health challenges, calls for more inter- and transdisciplinarity in the public health workforce are increasing, particularly to respond to complex and intersecting health challenges, such as those presented by the climate crisis, emerging infectious diseases, or military conflict. Although widely used, it is unclear how the concepts of multi-, inter-, and transdisciplinarity are applied with respect to the public health workforce. We conducted a scoping review and qualitative content analysis to provide an overview of how the concepts of multi-, inter-, and transdisciplinarity are defined and applied in the academic literature about the public health workforce. Of the 1957 records identified, 324 articles were included in the review. Of those, 193, 176, and 53 mentioned the concepts of multi-, inter-, and transdisciplinarity, respectively. Overall, 44 articles provided a definition. Whilst definitions of multidisciplinarity were scarce, definitions of inter- and transdisciplinarity were more common and richer, highlighting the aim of the collaboration and the blurring and dissolution of disciplinary boundaries. A better understanding of the application of multi-, inter-, and transdisciplinarity is an important step to implementing these concepts in practice, including in institutional structures, academic curricula, and approaches in tackling public health challenges.
Although previous studies have focused on the adverse effects of the COVID-19 pandemic on various professional groups (particularly in the health and nursing care sector), this study aims to close a research gap by assessing perspectives of students and young professionals in epidemiology and public health in Germany in terms of shifts in workload, work content, and related challenges caused by the pandemic. We conducted a cross-sectional survey between mid-February and mid-March 2022. Quantitative data were analyzed via standardized mean differences. Qualitative data based on answers to open-ended questions were analyzed via a qualitative content analysis. Overall, 172 individuals participated in this survey. Results indicate that students felt burdened the most by lack of exchange with other students and lecturers. Study participants employed in public health experienced changes in their employment because they had changes in their work content and administration, which was accompanied by a high burden due to the workload. Multiple demands that can have an impact on both acquired skills and mental health during the professional qualification phase were mentioned by the participants. Therefore, more in-depth analyses are needed to investigate the impact the pandemic will have on the (future) public health workforce in the long run.
The Public Health Service (PHS) in Germany has had difficulties in recruiting enough qualified staff for years, but there is limited research on what factors drive decisions to (not) join the PHS workforce. We explored reasons for this perceived (lack of) attractiveness. We conducted two cross-sectional surveys among medical students (MS), public health students and students from other PHS-relevant fields (PH&ONM) in Germany before (2019/2020) and during the COVID-19 pandemic (2021). Both waves surveyed self-reported reasons for why students did (not) consider working in the PHS as attractive and how this could be improved, using open-question items. Qualitative and quantitative content analyses were conducted according to Mayring. In total, 948 MS and 445 PH&ONM provided valid written responses. Reasons for considering the PHS as attractive were, among others, the perception of a good work-life balance, high impact, population health focus, and generally interesting occupations. Suggestions to increase attractiveness included reducing
bureaucracy, modernization/digitalization, and more acknowledgement of non-medical professionals. Among MS, reasons against were too little clinical/patient-related activities, low salary, and occupations regarded as boring. Our findings indicate areas for improvement for image, working conditions in, and institutional structures of the PHS in Germany to increase its attractiveness as an employer among young professionals.
As in many European countries, the Public Health Service (PHS) in Germany has had considerable difficulties in attracting well-qualified personnel for decades. Despite ongoing political and societal debate, limited empirical research on possible causes and explanations is available. To identify areas of action, we explored reasons for the (lack of) interest in working in the PHS by conducting two cross-sectional surveys among 3019 medical students (MS), public health students, and students from other PHS-relevant fields (PH&ONM) in Germany right before (wave 1, 2019/2020) and during the COVID-19 pandemic (wave 2, 2021). While interest in working in the PHS among MS was low, it was considerably higher among PH&ONM. The prevalent underestimation of the importance of public health and low levels of knowledge about the PHS were identified as potential barriers. Although core activities of the PHS were often considered attractive, they were repeatedly not attributed to the PHS. A negative perception of the PHS (e.g., it being too bureaucratic) was prevalent among students with and without PHS interest, indicating that both a negative image and potentially structural deficits need to be overcome to increase attractiveness. Based on the findings, we propose approaches on how to sustainably attract and retain qualified personnel.
Limitations in the global anaesthesia workforce contribute to the emigration of skilled anaesthesiologists from lower-income to higher-income countries, jeopardizing workforce balance and patient outcomes in Pakistan. This study aimed to explore the challenges experienced by anaesthesiologists in Punjab, Pakistan’s most populous province, and the potential changes to encourage their retention. We conducted a qualitative study, conducting semi-structured interviews with 25 purposively sampled consultant anaesthesiologists working in Punjab and analysing data thematically. Reported professional challenges and reasons consultant anaesthesiologists chose to work abroad differed between public and private sectors, each sector providing distinct challenges that compromised anaesthesia workforce numbers and quality. Key concerns were security, promotion/incentive structures, and gender inequalities in public hospitals versus inadequate salary and facilities, surgeon dependency, and the lack of out-of-theatre practice in private hospitals that minimized the scope and earnings of anaesthesiologists within Pakistan. Our findings help contextualise Pakistan’s anaesthesia workforce crisis, indicating public-sector improvements could include increasing security in hospital premises, performance-based incentives, and qualification-dependent promotion, while private-sector improvements could include decreasing surgeon dependency, fixing salary percent-
ages by surgical case, and encouraging direct patient-anaesthesiologist relationships. National and subnational interventions to promote anaesthesiology, along with public awareness campaigns, could additionally raise its profile and encourage retention.
Background: Oral diseases are one of the major public health problems worldwide and affect the population of all age groups. This qualitative study aimed to explore the perceptions and practices of caregivers at care centres and boarding religious schools responsible for managing children’s oral health.
Methods: A qualitative ethnomethodological approach was used to collect data from the caregivers at the children’s religious schools and foster care centres. A purposive sampling technique was used to conduct focus group discussions comprising 4–7 caregivers from five foster care centres and religious schools located in Lahore, Pakistan.
An interview guide was developed based on results from previous studies. An inductive approach was used to analyse data on broader oral health concepts to generate themes in this qualitative research. A three-step thematic analysis was applied to develop codes that were merged to generate categories and to conclude into themes from the transcribed data. Five focus group discussions were conducted at two foster care centres (FG1 & FG2) and three religious schools (FG3, FG4 & FG5). Foster care centres had children of both gender within the same premises; however, religious schools had segregated settings.
Results: The following four themes emerged from the thematic analysis: development of the desired living environment and responsibilities of the caregivers, preexisting traditional personal knowledge of the caregivers determine children’s oral health, use of religio-cultural driven and convenience-based oral hygiene practices, and ethnomedicine, spiritual healing, and self-medication. Development and the existing living environment of the foster care centres and religious schools appeared important to manage the matters of the boarding children.
Conclusions: This qualitative study concludes that the oral health of the children at foster care centres and at religious schools depends upon the personal reasoning and pre-existing religio-cultural knowledge of the caregivers rather than on specialized oral health-oriented approaches. The foster care centres are more involved in supervising the children to maintain oral hygiene and oral health compared to religious schools.
Background: Effective communication and collaboration among health professionals are essential prerequisites for patient-centered care. However, interprofessional teams require suitable structures and tools to efficiently use their professional competencies in the service of high-quality care appropriate to the patient’s life situation. In this context, digital tools potentially enhance interprofessional communication and collaboration and lead to an organizationally, socially, and ecologically sustainable health care system. However, there is a lack of studies systematically assessing the critical factors for successfully implementing tools for digitally supported interprofessional communication and collaboration in the health care setting. Furthermore, an operationalization of this concept is missing.
Objective: The aim of the proposed scoping review is to (1) identify factors influencing the development, implementation, and adoption processes of digital tools for interprofessional communication in the health care sector and (2) analyze and synthesize the (implicit) definition, dimensions, and concepts of digitally supported communication and collaboration among health care professionals in the health care setting. Studies focusing on digital communication and collaboration practices among health care professionals, including medical doctors and qualified medical assistants, in any health care setting will be included in this review.
Methods: To address these objectives, an in-depth analysis of heterogeneous studies is needed, which is best achieved through a scoping review. Within this proposed scoping review, which adheres to the Joanna Briggs Institute methodology, 5 databases (SCOPUS, CINAHL, PubMed, Embase, and PsycInfo) will be searched for studies assessing digital communication and collaboration among various health care professionals in different health care settings. Studies focusing on health care providers or patient interaction through digital tools and non–peer-reviewed studies will be excluded.
Results: Key characteristics of the studies included will be summarized through descriptive analysis, using diagrams and tables. We will synthesize and map the data and conduct a qualitative in-depth thematic analysis of definitions and dimensions of interprofessional digital communication and collaboration among health care and nursing professionals.
Conclusions: Results from this scoping review may help in establishing digitally supported collaborations between various stakeholders in the health care setting and successfully implementing new forms of interprofessional communication and collaboration. This could facilitate the transition to better coordinated care and encourage the development of digital frameworks.
Background and objectives: Anxiety disorders are the most prevalent mental disorders worldwide. Virtual reality (VR) treatment approaches have increasingly been studied. Before clinical implementation, it is necessary to evaluate the treatment effect of VR applications. The objective is to evaluate the treatment effect of virtual reality applications in the treatment of anxiety disorders compared to conventional therapy.
Methods: A systematic literature review with meta-analysis was conducted. Four databases were used to identify randomized controlled trials published between April 2011 and April 2021 which compare VR applications with non-VR interventions or waiting lists. Study characteristics, pre- and post-treatment data were extracted. Hedges g was calculated as effect size. Primary outcome was anxiety symptoms.
Results: Data from 17 studies from 827 participants was extracted. The studies examined specific phobia (n = 9), social anxiety disorder (n = 4), agoraphobia (n = 2) and panic disorder (n = 2). 16 out of 17 studies used head-mounted displays as VR application. A non-significant effect size with significant heterogeneity was observed in favor of the use of VR applications in anxiety symptoms (g, 0.33; 95%-CI, −0.20–0.87). Compared to passive control groups, VR applications are associated significant with lower anxiety symptoms (g, 1.29; 95%-CI, 0.68–1.90).
Limitations: The study and patient characteristics varied between the individual studies which is reflected in a high statistical heterogeneity of the effect sizes.
Conclusions: The added value of VR applications over waiting-list or psychoeducation only control groups is obvious. VR applications can be used as part of the treatment of anxiety disorders, especially when conventional therapy is unavailable.
Background: Hypertension is a highly relevant public health challenge. Digital interventions may support improving adherence to anti-hypertensive medications and alter health behavior. Therefore, this protocol describes a study that aims to assess the effectiveness of mHealth and educational support through peer counseling (Ed-counselling) to control blood pressure in hypertensive patients when compared to standard care.
Methods: We chose a double-blinded pragmatic randomized-controlled with factorial design for this investigation. The trial is going to recruit 1648 hypertensive patients with coronary artery disease at the age of 21 to 70 years. All participants will already be on anti-hypertensive medication and own a smartphone. They will be randomized into four groups with each having 412 participants. The first group will only receive standard care; while the second group, in addition to standard care, will receive monthly Ed-counselling (educational booklets with animated infographics and peer counseling); the third group will receive daily written and voice reminders and an education-led video once weekly together with standard care; while the fourth one gets both interventions given to second and third groups respectively. All groups will be followed-up for 1 year (0, 6, and 12 months). The primary outcome will be the change in systolic blood pressure while secondary outcomes include health-related quality of life and changes in medication adherence. For measuring changes in systolic blood pressure (SBP) and adherence scores difference at 0, 6, and 12 months between and within the group, parametric (ANOVA/repeated measure ANOVA) and non-parametric tests (Kruskal-Wallis test/Friedman test) will be used. By using the general estimating equation (GEE) with negative binomial regression, at 12 months, the covariates affecting primary and secondary outcomes will be determined and controlled. The analysis will be intention-to-treat. All the outcomes will be analyzed at 0, 6, and 12 months; however, the final analysis will be at 12 months from baseline.
Discussion: Besides adding up to existing evidence in the literature on the subject, our designed modules using mHealth technology can help in reducing hypertension-related morbidity and mortality in developing countries.
Die Anforderungen an soziale Dienstleistungen steigen und gesellschaftliche sowie strukturelle Entwicklungen fordern zunehmend effizientes Arbeiten. Vor allem in Frauenhäusern, die mit knappen Ressourcen arbeiten, spielt die Frage nach der Qualität und Effizienz eine große Rolle. In vielen, auch sozialen Organisationen werden hierfür Qualitätsmanagementsysteme eingeführt. Es ist daher notwendig zu verstehen, wie Qualitätsmanagement systematisch konzipiert wird. Das Ziel der vorliegenden Masterarbeit ist es, zu beantworten, wie sich Qualitätsmanagement in die Frauenhausarbeit integrieren lässt und welche konkreten Praktiken des Qualitätsmanagements in Frauenhäusern aktuell angewandt werden.
Zur Beantwortung der Forschungsfrage, wurde die Total-Quality-Management-Philosophie und der Regelkreis des Qualitätsmanagements: Qualitätsplanung -lenkung, -prüfung und -darlegung, als Rahmen zur systematischen Umsetzung hinzugezogen. Schwerpunkt der Arbeit ist eine quantitative Untersuchung zum Qualitätsmanagement in Frauenhäusern deutschlandweit. Anhand eines Online-Fragebogens wurden 111 Frauenhäuser zum aktuellen Stand ihres Qualitätsmanagements, den konkreten Praktiken, notwendigen Rahmenbedingungen und Wünschen zur Umsetzung eines umfassenden Qualitätsmanagements befragt.
Die Ergebnisse der Erhebung zeigen, dass lediglich 14 von 111 Frauenhäuser ein Qualitätsmanagementkonzept integriert und die angewandten Qualitätsmanagement-Praktiken meist keine Steuerungsfunktion haben. Das Interesse an Qualitätsmanagement und einheitlichen Standards ist groß. Gleichzeitig fehlt es an Wissen zu Qualitätsmanagement sowie finanziellen, personellen und zeitlichen Ressourcen, für die umfassende Auseinandersetzung.
Mit den Handlungsempfehlungen für das Frauenhaus Kempten dient die vorliegende Arbeit als Handreichung zur Erarbeitung eines umfassenden Qualitätsmanagementkonzeptes. Weiterführende Forschung zum Qualitätsmanagement für Frauenhäuser könnte auf ein praxisorientiertes allgemeines Konzept für Frauenhäuser ausgerichtet sein.
Die Welt der Automobilindustrie befindet sich in einem kontinuierlichen Wandel. Aktuell findet eine große Entwicklung in Richtung Connected, Autonomous, Shared, Electric (CASE) statt, welche völlig neue Auswirkungen auf den kompletten Lebenszyklus des Automobils hat. Das Fahrzeug entwickelt sich weiter in Richtung eines fahrenden Computers und die Anzahl der Programmzeilen von Fahrzeugfunktionen steigt. Dadurch und durch die Vernetzung von Fahrzeugen ergeben sich neue Gefahren durch Angriffe auf Fahrzeugsysteme, welchen durch Einsatz passender Cybersecurity-Maßnahmen entgegengewirkt werden muss. Diese Abschlussarbeit soll sich mit den aktuell geltenden und kommenden Normen und Verordnungen hinsichtlich Cybersecurity beschäftigen, besonders im Hinblick auf das autonome Fahren, und aufzeigen, wie sich Cybersecurity in der Automobilbranche auf Ebene der Sensorik umsetzen lässt. Die aufgezeigten Maßnahmen sollen am Beispiel eines Lidar-Systems verdeutlicht werden.
In dem Vortrag „Klimaneutralität - was ist jetzt zu tun?“, werden Wege zu einem klimaneutralen Deutschland vorgestellt. Im ersten Teil erfolgt die Definition des Begriffs Klimaneutralität. Für eine quantitative Einordnung wird der Begriff mit der Treibhausgasbilanz verknüpft. Anschließend werden die Treibhausgasemissionsmengen des Jahres 2022 aufgezeigt und unterschiedlichen Sektoren zugeordnet sowie nach unterschiedlichen Entstehungsprozessen gegliedert. Hieraus wird die Notwendigkeit zur Transformation der einzelnen Sektoren hergeleitet. Anhand der so genannten „Big 5-Studien“, werden wissenschaftlich fundierte Konzepte vorgestellt, die Wege zu einem klimaneutralen Deutschland aufzeigen. Kurz werden auch lokale Lösungskonzepte bzw. Pläne zur Verbesserung der Nachhaltigkeit für das Oberallgäu sowie die kreisfreie Stadt Kempten benannt. Im Anschluss daran, wird die Rolle der E-Mobilität sowie der Wärmepumpen als Teillösungen für die Mobilitäts- bzw. Wärmewende vorgestellt und diskutiert. Abschließend wird diskutiert, welche Aspekte die Gesellschaft davon abhalten die notwendigen Transformationen in der erforderlichen Geschwindigkeit umzusetzen.
Digitalisierung als Widerfahrnis.: Autonomie und Agency in der Medienaneignung älterer Menschen
(2023)
Da die unterschiedlichen (weil subjektiven) alltäglichen Erfahrungen älterer Menschen mit digitaler Technik bislang zu wenig berücksichtigt werden, nimmt sich dieser Beitrag dem Spannungsfeld der Dichotomie zwischen positiv erlebter Selbstbestimmung und negativ erlebter Fremdbestimmung durch digitale Assistenzangebote im häuslichen Umfeld an. Dabei wird der Widerfahrnischarakter des Erlebens von Technologie und des eigenen Umgangs damit in den Vordergrund der Betrachtung gerückt. Wissend um vielfältige vorangegangene Betrachtungen mit dem Fokus auf Potenziale der Digitalisierung für ältere Menschen mit Blick auf die Förderung von Selbstbestimmung, wird in diesem Beitrag bewusst die Medienzuwendung älterer Menschen als zumindest teilweise fremdgeleitetes Handeln in den Blick genommen, um einen kontrastierenden Gegenpol in der Diskussion anzubieten.
Eine Umfrage des Bayerischen Zentrums für Tourismus ermöglicht eine erste Bilanz darüber, ob und wie Bayern von der Generation Z bereist wird, welche Assoziationen Bayern als Reisedestination weckt und welche Gründe aus Sicht der Reisenden von Morgen für oder gegen einen Bayernurlaub sprechen.
In Zusammenarbeit mit der GfK wurde die bevölkerungsrepräsentative Umfrage im Januar und Februar 2023 unter über 3.000 Frauen und Männern zwischen 18 und 74 Jahren in Deutschland durchgeführt. Angelehnt an die definitorische Abgrenzung der Generation Z als alle zwischen 1995 und 2010 geborenen Personen gehören 489 Proband*innen der Gesamtstichprobe der Generation Z an und waren zum Zeitpunkt der Umfrage zwischen 18 und 28 Jahren alt. Eine gesonderte Datenauswertung ermöglicht es, die Generation Z und Bayern als Reiseland in einen gemeinsamen Kontext zu setzen und in dieser Hinsicht erste Ansätze generationsspezifischer Unterschiede zu identifizieren.
Im Zentrum dieser Arbeit steht die Gruppe der Senioren (im Alter von 60 bis 85 Jahren), die sich in diesem Alter für einen neuen Wohnort innerhalb Deutschlands entscheiden. Die Arbeit betrachtet das Thema der Altersbinnenmigration, also den Umzug im Seniorenalter innerhalb Deutschlands, am Beispiel von Bad Wörishofen und Memmingen. Dabei wird das Thema der Altersbinnenmigration aus gesellschaftlicher und individueller Perspektive betrachtet. Die gesellschaftliche Perspektive greift dabei den Blickwinkel der „Radikalisierung der Moderne“ von Giddens auf und analysiert, wie sich die Dimensionen „Entbettung“, „Reflexivität“ und „Globalisierung“ auf gesellschaftlicher Ebene (Makroebene) zeigen. Daran anschließend folgt der Perspektivenwechsel auf die individuelle Ebene (Mikroebene). Es wird beschrieben, wie diese drei Dimensionen auf das Leben der Senioren wirken. Verfolgt wird dabei der Gedanken, dass Strukturen (gesellschaftliche Bedingungen) und Handeln (individuelle Perspektive) in wechselseitiger Verbindung stehen: Strukturen beeinflussen Handeln (ermöglichend oder einschränkend) und Handeln lässt Strukturen verändern. Die Altersbinnenmigration wird in dieser Arbeit als Handlung interpretiert, die auf die gesellschaftliche Situation (Strukturen) eine Reaktion ist. Mögliche Veränderungen der Strukturen, als Konsequenz aus der Handlung, werden abschließend bedacht.
Die Umstände und Gründe für die Handlung der Altersbinnenmigration werden im Rahmen von quantitativen Befragungen in Bad Wörishofen und Memmingen unter 60- bis 85-Jährigen untersucht. Besonderes Augenmerk liegt dabei auch auf dem Vergleich dieser Gruppe, mit den 60- bis 85-jährigen Personen in den beiden Untersuchungsorten, die im Alter nicht zugezogen sind. Dabei sind zentrale Aspekte wie die Lebenszufriedenheit, das Altersbild, die Definition von Heimat sowie die Eigenschaften eines idealen Wohnortes von Interesse. Durch die Befragungen in Bad Wörishofen und Memmingen konnten 1.200 (Bad Wörishofen) und 865 (Memmingen) ausgefüllte Fragebögen gewonnen werden, die Einblick in die Gruppe der Altersbinnenmigranten und der gleichaltrigen Nicht-Altersbinnenmigranten geben. Dabei zeigt sich, dass Altersbinnenmigranten schon in ihrem Leben zuvor Kontingenz erfahren haben und im Seniorenalter eine Idylle von Natur, kurzen Wegen und medizinischer Versorgung wünschen. Soziale Beziehungen spielen bei der Ortswahl eine untergeordnete Rolle. So werden diese auch bei der Beschreibung des idealen Wohnortes nachrangig genannt. Im Gegensatz dazu sind Freunde für Nicht-Altersbinnenmigranten am idealen Wohnort deutlich wichtiger. Mit Hilfe der Daten werden Cluster von Altersbinnenmigranten gebildet; also Gruppen von sich, in den Motiven und soziodemographischen Merkmalen, ähnlich seienden Altersbinnenmigranten. Diese Erkenntnisse können – mit Blick zurück auf die Strukturebene – für Gesellschaft und (Stadt-)Politik hilfreich sein, um mit dieser (größer werdenden) Gruppe der zugezogenen Senioren umzugehen.
Diese Arbeit hat einen explorativen Charakter, ihr Anspruch sind keine repräsentativen Aussagen. Vielmehr soll diese Arbeit Einsichten in die Gruppe der Altersbinnenmigranten geben. Sie soll auch ein Anstoß sein, das Thema Altersbinnenmigration im Rahmen der Diskussion zum Thema „Gestaltung des Rentenalters“ mitzudenken.zeige weniger
Background
Published research on senior care facilities in Pakistan is scarce and no large-scale study has been conducted to assess factors affecting well-being of older adults in these facilities. This study, therefore, investigated the effects of relocation autonomy, loneliness, and satisfaction with services along with socio-demographic characteristics on physical, psychological, and social well-being of older residents living in senior care facilities of Punjab, Pakistan.
Methods
This cross-sectional study collected data from 270 older residents living in 18 senior care facilities across 11 districts of Punjab, Pakistan from November 2019 to February 2020 using multistage random sampling. Existing reliable and valid scales were used to collect information from older adults related to relocation autonomy (Perceived Control Measure Scale), loneliness (de Jong-Gierveld Loneliness Scale), satisfaction with service quality (Service Quality Scale), physical and psychological well-being (General Well-Being Scale), and social well-being (Duke Social Support Index). A psychometric analysis of these scales was carried out followed by three separate multiple regression analyses to predict physical, psychological, and social well-being from socio-demographic variables and key independent variables (relocation autonomy, loneliness, and satisfaction with service quality).
Results
The results of multiple regression analyses showed that the models predicting physical (R2 = 0.579), psychological (R2 = 0.654), and social well-being (R2 = 0.615) were statistically significant (p < 0.001). Number of visitors was a significant predictor of physical (b = 0.82, p = 0.01), psychological (b = 0.80, p < 0.001), and social (b = 2.40, p < 0.001) well-being. Loneliness significantly predicted physical (b = -0.14, p = 0.005), psychological (b = -0.19, p < 0.001), and social (b = -0.36, p < 0.001) well-being. Control over relocation process significantly predicted physical (b = 0.56, p < 0.001) and psychological (b = 0.36, p < 0.001) well-being. Satisfaction with services significantly predicted physical (b = 0.07, p < 0.001) and social (b = 0.08, p < 0.001) well-being.
Conclusion
Pragmatic, equitable and cost-effective interventions are needed to improve the wellbeing of older residents living in senior care facilities. Friendly behavior of mobilizing staff and adjusted residents to facilitate new residents, therapeutic interventions such as relocation support programs, reminiscence therapy and intergenerational support, and increasing their exposure and connection to the outside world, can raise their physical, psychological, and social well-being.
Disentangling Human-AI Hybrids: Conceptualizing the Interworking of Humans and AI-Enabled Systems
(2023)
Artificial intelligence (AI) offers great potential in organizations. The path to achieving this potential will involve human-AI interworking, as has been confirmed by numerous studies. However, it remains to be explored which direction this interworking of human agents and AI-enabled systems ought to take. To date, research still lacks a holistic understanding of the entangled interworking that characterizes human-AI hybrids, so-called because they form when human agents and AI-enabled systems closely collaborate. To enhance such understanding, this paper presents a taxonomy of human-AI hybrids, developed by reviewing the current literature as well as a sample of 101 human-AI hybrids. Leveraging weak sociomateriality as justificatory knowledge, this study provides a deeper understanding of the entanglement between human agents and AI-enabled systems. Furthermore, a cluster analysis is performed to derive archetypes of human-AI hybrids, identifying ideal–typical occurrences of human-AI hybrids in practice. While the taxonomy creates a solid foundation for the understanding and analysis of human-AI hybrids, the archetypes illustrate the range of roles that AI-enabled systems can play in those interworking scenarios.
Age and gender in gerontechnology development: Emphasizing the need for an intersectional approach
(2023)
Background
The challenges of the digital divide emerge with new technologies being created to address the needs of the increasing older population. This divide is influenced by the social dimensions of age and gender, often resulting in impaired participation of the affected demographic groups. Gerontechnological designs in which inadequate attention is paid to gender and old age easily run the risk of reproducing gender-specific and age-specific stereotypes. An approach to counteracting the digital exclusion of technology users is the introduction of co-creative methods of participatory design (PD). As there are diverse challenges when putting these methods into practice regarding their claim to be more socially inclusive and democratizing technology development, it is necessary to investigate the effect that age and gender could play when considering PD in gerontechnology.
Objective
This article aims to shed light on the intersection of age and gender as dimensions of horizontal inequalities in gerontechnology development to support the further development of co-creation practices.
Conclusion
The PD approaches can be regarded as suitable methodologies to descript age and gender in technology development as long as they are enhanced by a critical awareness of gendered and ageist patterns in society and technology development. The intersectional approach can contribute to further understanding of how current gerontechnology development practices promote the reinforcement and challenging of dominant discourses on old age and gender.
Etwa 30 Jahre sind seit der Gründungsphase sowohl von Public Health als auch der Pflegewissenschaft in Deutschland vergangen. Die Konstituierung bzw. Etablierung dieser Disziplinen ging mit einem im internationalen Vergleich großen Nachholbedarf einher und stellte in gewisser Hinsicht ein Projekt nachholender Modernisierung nach angloamerikanischen Vorbildern dar [1, 2]. Die eingeschlagenen Entwicklungswege dieser beiden Disziplinen in Bezug auf Forschung, Lehre und Praxis waren gleichwohl unterschiedlich und wurden auch kritisch reflektiert [2]. Im Kern ging es jedoch zunächst um eine jeweils fachspezifische Profilierung und damit einhergehende Abgrenzung voneinander.
Background
Quality of life questionnaires are often used in the assessment of rehabilitation of hearing-impaired patients with a cochlear implant. However, a prospective study with a systematic retrospective evaluation of the preoperative quality of life after surgery has not yet been conducted and may reveal a change in internal standards, such as a response shift, due to the implantation and hearing rehabilitation.
Methods
The Nijmegen Cochlear Implant Questionnaire (NCIQ) was used for assessing hearing related quality of life. It has three general domains (physical, psychological and social) and six subdomains. Seventeen patients were tested before (t0) and retrospectively (then-test; pre-t1) and acutely postoperative (post-t1) after cochlear implantation. Observed changes, then-test changes, response shifts and effect sizes were calculated. Non-parametric statistical methods were used.
Results
The NCIQ total score was 52.32 ± 18.69 (mean, standard deviation) for t0, 59.29 ± 14.06 for pre-t1 and 67.65 ± 26.02 for post-t1 questioning. The observed change was statistically significant in all domains but in speech production. Response shift was statistically significant in the total score and in part of the domains. The effect sizes for the response shift were moderate (> 0.5) in the total score, psychological, social general scores and subdomains.
Conclusions
In this study we found that response shift does exist in adults with severe to profound hearing loss undergoing cochlear implantation. By advising the participants to deactivate the implant for the then-test, recall bias and noise were minimized. The clinical significance of the response shift was present in the total score and in the social and psychological domains.
Trial Registration
This study was retrospectively registered with the German Clinical Trial Register, TRN DRKS00029467, on 07/08/2022.
Die Digitalisierung nimmt im Bereich der Gesundheitsförderung und Prävention einen immer höheren Stellenwert ein. Gleichzeitig hat das Präventionsgesetz zu einer Stärkung von Interventionen der Gesundheitsförderung und Prävention in Settings beigetragen. In einem lebenswelt- bzw. settingorientierten Ansatz werden Maßnahmen der Prävention und Gesundheitsförderung sowohl auf das Verhalten als auch die Verhältnisse ausgerichtet. Obwohl im Setting der „Arbeitswelt“ in den vergangenen Jahren der Einsatz eines digitalen betrieblichen Gesundheitsmanagements zugenommen hat, werden die Potenziale der Digitalisierung nur unzureichend genutzt. Dies gilt insbesondere für die Gesundheitsförderung und Prävention bei Pflegefachkräften.
Daher wird in diesem Diskussionsbeitrag der Fokus auf Gesundheitsförderung und Prävention in Einrichtungen der stationären Langzeitpflege gelegt. Da die strukturierte Implementierung digitaler Applikationen in Pflegeeinrichtungen eine Innovation innerhalb der Organisation darstellt, könnte dieses Momentum dazu genutzt werden, zugleich Strukturen und Prozesse gesundheitsförderlich zu gestalten. Dabei wird die Gesundheitsförderung durch Digitalisierung als organisationale Aufgabe mit einer bedarfssensiblen und diversitätsorientierten Ausrichtung verstanden. Somit kann die Digitalisierung ein Vehikel darstellen, um die Etablierung gesundheitsfördernder Einrichtungen in der Langzeitpflege substanziell voranzubringen.
Background
Healthcare professionals around the globe suffered severely during the COVID-19 pandemic. The present study aims to explore the lived experiences of nurses caring for COVID-19 patients in Pakistan.
Methods
The study is a qualitative exploration of the lived experiences caring for patients with COVID-19 in Pakistan. This research was conducted in two government hospitals there. Face-to-face in-depth interviews were conducted amongst 30 nurses who had been selected using purposive sampling technique. Thematic analysis was applied to extract the themes from respondents’ answers.
Results
By using thematic analysis, social response, impacts on physical and mental health, and experience of handling COVID-19 patients were extracted as major themes.
Conclusions
The findings of this research are of immense importance in showing the impact of COVID-19 on mental and physical health, along with the social and personal consequences for nurses providing care to COVID-19 patients.
Given its promising role in public health to address hard to reach population groups, game-based interventions (i.e., Games for Health, G4H) have experienced growing interest in recent years. Therefore, it is surprising that they have played only a minor role during the COVID-19 pandemic. Hence, the aim of this paper is to reflect the opportunities and challenges of G4H especially during the pandemic but also with regard to future health crises. As commercial video games (i.e., those that primarily aim to entertain its users) were often used to deal with the containment measures during the COVID-19 pandemic, we call for greater cooperation with commercial game makers to distribute health-related messages via entertainment games. With regard to G4H we see a need to (i) strengthen the intervention theory underlying game-based applications, (ii) to enhance the appeal of games in order to maintain the interest of users in the long term, and (iii) to improve the evidence base using appropriate study designs. Finally, we argue for (iv) greater user involvement, both in terms of developing game-based approaches and as co-researchers in solving complex health problems.
Oxygen scavengers are used to reduce the oxygen permeation of packaging (active barrier) and to absorb oxygen from its direct environment, e.g., a headspace of packaged food. Few oxygen scavenger coatings have been developed. Therefore, in this study, a novel oxygen scavenger coating has been developed. It is based on inorganic–organic polymers (ORMOCER®). The oxygen absorption reaction is activated by UV light. The scavenger was synthesized, coated on aluminum foil, subsequently dried and afterwards laminated with a polyethylene sealing layer. UV light activates the oxygen scavenging reaction. The oxygen absorption capacity, measured at 23 °C and 0% r.h., was 242 ± 8 mg oxygen/g scavenger coating. When the oxygen scavenger coating layer was laminated by using a two-component polyurethane laminating adhesive, the absorption capacity was hardly reduced, with a measured absorption capacity of 223 ± 18 mg oxygen/g scavenger coating. In an experimental packaging sample with the oxygen scavenger coating with a thickness (dry) of 3 µm and 18 µm, near-zero mbar oxygen partial pressure was reached by the non-laminated oxygen scavenger coatings within two days, and within about 20 days when laminated with a polyurethane laminating adhesive and a PE-layer on the oxygen scavenger layer. The oxygen partial pressure was kept near zero mbar for 500 days, whereas in the experimental packaging without oxygen scavenger, the oxygen partial pressure increased to 110 mbar during this time. The developed oxygen scavenger based on inorganic–organic polymers can be applied as wet chemical coating on various surfaces with standard application procedures. Application scenarios are oxygen-sensitive goods such as food, pharmaceutical products and cosmetics.
Objective
The objective of this study was to deliver an intervention to improve health awareness for infection prevention, hygiene, and sanitation to assess its impact. Furthermore, it aimed to identify the risk of multimorbidity in women of reproductive years from low socio-economic background.
Methods
A randomized control trial was conducted in Pakistan among women aged 15–45 years. Overall, 820 women participated in the baseline survey; 388 women were part of the control group and 360 of the intervention group. A digital health literacy intervention was delivered by 91 trained community health workers. Data were analyzed using descriptive statistics and multivariate logistic regression.
Results
About 35.9% of women suffered from multimorbidity. The intervention group showed higher odds of confidence in managing health with respect to skill and technique acquisition (AOR = 2.21; 95% CI 1.01–4.84), self-monitoring and insight (AOR = 2.97; 95% CI 1.29–6.80) as well as sanitation and hygiene (AOR = 1.42; 95% CI 1.07–1.93). Two primary outcomes related to hand hygiene and protective behavior against infection did not show any significant improvement. The secondary outcomes of the study related to impact on overall health-related quality of life, social integration and support, and emotional well-being also did not show any significant improvement.
Conclusions
Digital health literacy interventions and multimorbidity management for women of reproductive years at the primary level are a way forward to alleviate communicable and non-communicable disease burden in developing countries like Pakistan. These efforts are also critical to improve maternal and child health in developing regions.
Background:
There is a complex relationship between health and religiosity. People may use religion to cope with difficulties and uncertainties in their life – such as induced by the COVID-19 pandemic.
Aims:
The purpose of this study is to investigate the relationship between religious coping, care burden and psychological distress among caregivers during COVID-19 in Pakistan.
Method:
We conducted a cross-sectional survey in Pakistan. We used the Religious Coping Scale (RCOPE), Care Burden Scale (CB), and Depression, Anxiety and Stress Scale (DASS-21) to measure psychological stress from 303 caregivers. Data were analyzed using a hierarchical linear regression model for each of the three outcome variables, which are depression, anxiety, and stress. This analysis allows to investigate whether adding variables significantly improves a model’s ability to predict the criterion variable.
Results:
The findings reveal that emotional care burden, physical care burden, negative religious coping, and social care burden explain a significant amount of the variance of three components of psychological distress among caregivers.
Conclusions:
Health experts, psychologists, and policymakers can make better strategies to combat pandemics like COVID-19 by incorporating religious coping methods.
This paper is a summary of the creation and data usage of an autonomous model vehicle which was recreated in CarMaker[1]. The simulation data come to use when following students of this semester project will develop algorithms and simulations which are impractical to test or train in real life. This paper starts with a summary of the background information around the model vehicle and the software CarMaker[1], then reproduces the construction process, digs deeper in ROS[6] and finishes with the extraction of the data.
Das Ambient Medicine® Forum, ursprünglich ins Leben gerufen vom Heinz Nixdorf-Lehrstuhl für Medizinische Elektronik der Technischen Universität München (Prof. Dr. B. Wolf), wird seit nun mehr als fünfzehn Jahren zu aktuellen Themen der Medizinelektronik und telematischen Medizin durchgeführt. Das diesjährige Forum wird von der Hochschule Kempten in Zusammenarbeit mit CARE REGIO und dem Steinbeis-Transferzentrum für Medizinische Elektronik und Lab on Chip-Systeme und der Technischen Universität München sowie weiteren Partnern veranstaltet.
Das 7. Ambient Medicine® Forum widmet sich den neusten Entwicklungen im Bereich Digitalisierung und Technik in der Pflege. Namhafte Referentinnen und Referenten werden in den vier Themensessions „Pflege im Aufbruch“, „Gesellschaft und Pflege“, „Im Fokus: Digitale Assistenzsysteme“ und „Daten für eine bessere Pflege?“ Fachvorträge halten. Ergänzt werden die Vorträge durch eine Industrie- und Posterausstellung. Dort werden Assistenzsysteme und Lösungen
für selbstbestimmtes Wohnen sowie für Prävention, Therapie und Rehabilitation vorgestellt. Digitale, datengestützte Anwendungen für die Pflege sind ebenfalls ausgestellt.
The catalyst coated membrane represents the heart of a polymer electrolyte fuel cell (PEMFC) and is produced by directly applying a catalyst suspension on the membrane or a decal transfer foil. Understanding the rheology of catalyst inks is crucial to optimize the printed microstructure of the catalyst layer and hence the performance of the fuel cell. The suspension consists of platinum on carbon powder, ionomer dispersion (perfluorosulfonic acid ionomer) and solvents. Its rheology is directly affected by various material properties of all ink components. Therefore, measuring the flow curves represents a suitable tool for quality control at the beginning of the production line.
An artifact appearing during the cathodic transient of cyclic voltammograms (CVs) of low-loaded platinum on carbon (Pt/C) electrodes in proton exchange membrane fuel cells (PEMFCs) was examined. The artifact appears as an oxidation peak overlapping the reduction peak associated to the reduction of platinum oxide (PtOx). By varying the nitrogen (N2) purge in the working electrode (WE), gas pressures in working and counter electrode, upper potential limits and scan rates of the CVs, the artifact magnitude and potential window could be manipulated. From the results, the artifact is assigned to crossover hydrogen (H2X) accumulating in the WE, once the electrode is passivated towards hydrogen oxidation reaction (HOR) due to PtOx coverage. During the cathodic CV transient, PtOx is reduced and HOR spontaneously occurs with the accumulated H2X, resulting in the overlap of the PtOx reduction with the oxidation peak. This feature is expected to occur predominantly in CV analysis of low-loaded electrodes made of catalyst material, whose oxide is inactive towards HOR. Further, it is only measurable while the N2 purge of the WE is switched off during the CV measurement. For higher loaded electrodes, the artifact is not observed as the electrocatalysts are not fully inactivated towards HOR due to incomplete oxide coverage, and/or the currents associated with the oxide reduction are much larger than the spontaneous HOR of accumulated H2X. However, owing to the forecasted reduction in noble metal loadings of catalyst in PEMFCs, this artifact is expected to be observed more often in the future.
We present a model of the cathode catalyst layer morphology before and after loading a porous catalyst support with Pt and ionomer. Support nanopores and catalyst particles within pores and on the support surface are described by size distributions, allowing for qualitative processes during the addition of a material phase to be dependent on the observed pore and particle size. A particular focus is put on the interplay of pore impregnation and blockage due to ionomer loading and the consequences for the Pt/ionomer interface, ionomer film thickness and protonic binding of particles within pores. We used the model to emulate six catalyst/support combinations from literature with different porosity, surface area and pore size distributions of the support as well as varying particle size distributions and ionomer/carbon ratios. Besides providing qualitatively and quantitatively accurate predictions, the model is able to explain why the protonically active catalyst surface area has been reported to not increase monotonically with ionomer addition for some supports, but rather decrease again when the optimum ionomer content is exceeded. The proposed model constitutes a fast translation from manufacturing parameters to catalyst layer morphology which can be incorporated into existing performance and degradation models in a straightforward way.
In this work, flatbed screen printing is evaluated regarding its capability to produce catalyst layers of PEM fuel cells. In the field of printed electronics, screen printing is regarded as robust and high-throughput coating technology. The possibility of in-plane structuring could be an additional degree of freedom, enabling more complex designs of catalyst layers in the future. In this study, process parameters are varied to investigate their effect on resulting layer thickness, homogeneity, and Pt-loading. With the usage of different screens, the Pt-loading can be adjusted. Additionally, two different pastes with and without water content are investigated. The catalyst paste without water showed a better process stability during printing and performed best under dry conditions (RH = 40%) and worst under wet conditions (RH = 100%) during electrochemical in-situ testing. Overall, the reproducibility of the CCM production process was verified. The viscosity of the catalyst paste with 19.55 wt% water in solvent was higher compared to the paste without water. Furthermore, a carbon paste (Pt-free) is developed in a similar viscosity range as the catalyst pastes. The main challenge of screen printing process development lies in the paste optimization to prevent evaporation effects over time, ensuring sufficient wetting of the paste on the substrate and sufficient fuel cell performance.
Lithium-ion cells are subject to degradation due to a multitude of cell-internal aging effects, which can significantly influence the economics of battery energy storage systems (BESS). Since the rate of degradation depends on external stress factors such as the state-of-charge, charge/discharge-rate, and depth of cycle, it can be directly influenced through the operation strategy. In this contribution, we propose a model predictive control (MPC) framework for designing aging aware operation strategies. By simulating the entire BESS lifetime on a digital twin, different aging aware optimization models can be benchmarked and the optimal value for aging cost can be determined. In a case study, the application of generating profit through arbitrage trading on the EPEX SPOT intraday electricity market is investigated. For that, a linearized model for the calendar and cyclic capacity loss of a lithium iron phosphate cell is presented. The results show that using the MPC framework to determine the optimal aging cost can significantly increase the lifetime profitability of a BESS, compared to the prevalent approach of selecting aging cost based on the cost of the battery system. Furthermore, the lifetime profit from energy arbitrage can be increased by an additional 24.9% when using the linearized calendar degradation model and by 29.3% when using both the linearized calendar and cyclic degradation model, compared to an energy throughput based aging cost model. By examining price data from 2019 to 2022, the case study demonstrates that the recent increases in prices and price fluctuations on wholesale electricity markets have led to a substantial increase of the achievable lifetime profit.
We give conditions for local diagonalization of analytic operator families acting between real or complex Banach spaces.The transformations are constructed from an operator Töplitz matrix obtained from Jordan chains of increasing length. The basic assumption is given by stabilization of the Jordan chains at length k in the sense that no root elements with finite rank above k are allowed to exist. Jordan chains with infinite rank may appear. These assumptions ensure finite pole order equal to k of the generalized inverse. The Smith form arises immediately.
Smooth continuation of kernels and ranges towards appropriate limit spaces is considered using associated families of analytic projection functions.
No Fredholm properties or other finiteness assumptions, besides the pole order, are assumed. Real and complex Banach spaces are treated without difference by elementary analysis of the system of undetermined coefficients.
Formal power series solutions of the system of undetermined coefficients are constructed, which are turning into convergent solutions, as soon as analyticity of the operator family and continuity of the projections is assumed. Along these lines, results concerning linear Artin approximation follow immediately, which are well known in finite dimensions. The main technical tool is given by a defining equation of Nakayama Lemma type.
In general, current systems for the Digital Factory implement a product-process-resource (PPR) data model in a monolithic rich-client/server architecture with a single database persistence layer. Common data objects are the product bills of material, descriptions of the production processes, or the resource structure, e.g. bill of equipment. The main drawback of the current monolithic architecture is the slow rate of development, which prevents fast adoption of the software to the new production planning process (i.e., due to new technologies for the transformation of the automotive industry with the goal of electrification) is not possible. Furthermore, time-consuming and error-prone export-import operations characterize the collaboration of the engineering supply chain. Mercedes-Benz has created a new IT system architecture for their Digital Factory. The core idea of this architecture is a module-based approach. Each planning step has its own module, e.g. product analysis, layout planning or cost calculation. One single module consists of a server-based business logic, a web-based user interface and its own database. Each module is the source of master data objects that originate from the corresponding planning step and refers to data objects from predecessor planning steps. The single modules communicate mostly via KAFKA. The usage of a model based application engine allows the fast creation of different modules. Best-of-breed third-party systems for specific planning steps can be integrated into the system architecture. Web technologies allow suppliers to access the Mercedes-Benz systems directly for a fully integrated supplier collaboration. Roll-out has started and has already led to significant efficiencies.
Green information systems are often praised for their potential to foster sustainability in citizens’ daily lives and meet their needs. With this focus on citizens, districts that use smart technologies provide a litmus test, the results of which will indicate how to design smart green information systems that better meet the needs and desires of citizens. To date, however, guidelines on how to design such green information systems in urban areas or actively involve citizens in this process are few and far between. In recognition and remedy of this shortage, the study draws on the design science research paradigm to develop seven design principles for citizen-centric green information systems that can be used in sustainable smart districts. These principles are evaluated in 15 semi-structured interviews and a prototype of a mobile district app for a citizen-centric green information system is instantiated. By taking this citizen-centric perspective, the paper fosters the active involvement of humans in the design of sustainable urban environments.
Wie kaum ein anderer Wirtschaftsbereich wurde im Jahr 2020 der Tourismus von der Covid-19-Pandemie getroffen. Am Beispiel der touristischen Übernachtungen und ausgehend von einer Beschreibung des zeitlichen Verlaufs der getroffenen Maßnahmen zur Bekämpfung der Pandemie, zeigt und erklärt der vorliegende Beitrag, wie sich diese Betroffenheit in Bayern regional und zeitlich unterscheidet.
Der Tagesausflugsverkehr im Münchner Umland, insbesondere in den südlich von München liegenden Landkreisen, führt seit Jahren in Spitzenzeiten zu Belastungen in den Ausflugsregionen. Angesichts der Bedeutung Münchens als Quellgebiet für den Tagesausflugsverkehr in Bayern und des prognostizierten Einwohnerzuwachses in den nächsten Jahren hat die dwif-Consulting GmbH im Auftrag des Bayerischen Zentrums für Tourismus anhand ihres Tagesreisenmonitors die Tagesreisen der Münchnerinnen und Münchner ermittelt. Mit dieser Auswertung basierend auf den Jahren 2017 bis 2019 sollen zum einen die Quantitäten der Tagesreisen innerhalb und außerhalb der Stadt München und zum anderen die wirtschaftlichen Effekte des Tagestourismus für die Landeshauptstadt und die angrenzenden Tourismusregionen herausgearbeitet werden. Des Weiteren gilt es, auch die Bedeutung der Region als Freizeit- und Naherholungsgebiet für die Münchner Bevölkerung aufzuzeigen.
Um das Mobilitätsverhalten in Bayern während der Corona-Pandemie (2020/2021) abzubilden, hat das Bayerische Zentrum für Tourismus für jeden Landkreis und jede kreisfreie Stadt aggregierte und anonymisierte Mobilfunkdaten zu eingehenden und ausgehenden Mobilitätsbewegungen sowie diejenigen innerhalb eines Kreises für jeden Monat des Jahres 2020 und des ersten Halbjahres 2021 ausgewertet. Die so ermittelte Gesamtmobilität der einzelnen Landkreise und kreisfreien Städte wird mit dem entsprechenden Wert des jeweiligen Monats des Jahres 2019 verglichen.
Wie bewerten bayerische Tourismusakteure den Tagesausflugsverkehr und das Thema Besucherlenkung im Jahr 2021? Dazu hat das Bayerische Zentrum für Tourismus Mitglieder der vier bayerischen Tourismusverbände im November und Dezember letzten Jahres befragt. Der Blick richtet sich dabei auf Probleme, die durch den Tagesausflugsverkehr verursacht wurden, aber auch darauf, welche Besucherlenkungsmaßnahmen bereits Wirkung gezeigt haben. Auch wurde versucht, eine Bilanz gegenüber dem Sommer 2020 zu ziehen. Über die Erfahrungen, die Lessons learned und den zukünftigen Handlungsbedarf, den die bayerischen Touristiker bei diesem Thema sehen, haben wir ebenfalls gesprochen. Die Antworten der 26 Teilnehmer haben wir hier in einem Stimmungsbild zusammengefasst.
Urlaub in Bayern
(2023)
Wer ist heute Gast in Bayern? Wer ist heute nicht Gast in Bayern und warum nicht? Antworten auf diese Fragen liefert eine bevölkerungsrepräsentative Umfrage des Bayerischen Zentrums für Tourismus, durchgeführt von GfK im Januar und Februar 2023. Die Studie beleuchtet unter anderem, warum Urlaub in Bayern verbracht wird, welche Art von Urlaub gemacht wird und was die Proband*innen mit Bayern assoziieren.
Ein Blick in die Mobilität der Zukunft: Die bayerische Gemeinde Bad Birnbach überbrückt seit Oktober 2019 die letzte Meile zwischen dem 1,8 Kilometer entfernten Bahnhof, der Rottal Terme und dem Ortskern mit autonom fahrenden Shuttlebussen. Auch in den anderen Bundesländern werden bereits vergleichbare Projekte umgesetzt.
Besucher von Großstädten verlagern ihre Besuche immer häufiger auch an Orte und in Viertel abseits klassischer touristischer Sehenswürdigkeiten. Dieses Phänomen wird als New Urban Tourism beschrieben. Durch diese neue Form des Tourismus verschwimmt die Grenze zwischen Tourismusraum und Freizeitraum von Einheimischen.
Mobilität hat für die Generation Z einen hohen Stellenwert. Wie bewegen sich junge Erwachsene, die zwischen den Jahren 1995 und 2010 geboren wurden? Der folgende Beitrag betrachtet das erdgebundene Mobilitätsverhalten der Generation Z im Alltag und deren Ansprüche an die zukünftige Mobilität und das Tagesausflugsverhalten hinsichtlich unterschiedlicher Kriterien.
Die jüngste Generation im Berufsleben ist die Generation Z. Sie stellt Arbeitgeber zum Teil vor neue Herausforderungen, da sich die Werte und Erwartungen zu vorherigen Generationen unterscheiden. Auch die Tourismusbranche steht vor der Aufgabe, bei dieser Generation als attraktiver Arbeitgeber sichtbar zu sein und die Generation Z als Arbeitnehmer zu gewinnen.
Punching is a process that is sensitive to a multitude of parameters. The estimation of part and punch quality is often based on expert knowledge and trial-and-error methods, mostly carried out as a separate offline process analysis. In a previous study, we developed an optical inline monitoring system with subsequent image processing which showed promising results in terms of capturing every manufactured part, but was limited by slow image processing. Here, we present a more efficient image processing technique based on neural networks. For our approach, we manually identify the burnish parts in images based on criteria established via an expert survey in order to generate a training dataset. We then employ a combination of region-based and boundary-based losses to optimize the neural network towards a segmentation of the burnish surface which allows for an accurate measurement of the burnish height. The hyperparameter optimization is based on custom evaluation metrics that reflect the requirements of the burnish surface identification problem as well. After comparing different neural network architectures, we focus on optimizing the backbone of the UNet++ structure for our task. The promising results demonstrate that neural networks are indeed capable of an inline segmentation that can be used for measuring the burnish surface of punching parts.
Die vom Bayerischen Zentrum für Tourismus durchgeführte Umfrage (Mai 2021) konnte Erkenntnisse über den Stellenwert der Besucherlenkung in bayerischen Kommunen gewinnen. Schwerpunkte der Befragung waren die Wichtigkeit von Besucherlenkung, aktuelle und geplante Besucherlenkungsmaßnahmen sowie das Thema Datenerfassung.
KI-Anwendung in der Energietechnik: Einsatz maschineller Lernverfahren für die Wärmelastprognose
(2021)
Maschinelles Lernen gilt als eines der vielversprechendsten Teilgebiete der künstlichen Intelligenz (KI). Sein Einsatz hat in den vergangenen Jahren zu enormen Fortschritten sowohl in der Bild- und Texterkennung als auch bei Zeitreihenprognosen geführt.
Der Vortrag demonstriert dies am Beispiel von Wärmelastprognosen für die Fernwärmebranche. Dabei werden maschinelle Lernverfahren genutzt, um den Wärmebedarf in Fernwärme-netzen über mehrere Tage im Voraus hochgenau vorherzusagen. Auf diese Weise können Energieversorger den Einsatz ihrer Wärmeerzeugungsanlagen optimal planen. Beispielsweise können bei vorhersehbaren Lastspitzen Wärmespeicher frühzeitig mit erneuerbar erzeugter Wärme gefüllt und so der Betrieb fossiler Spitzenlastkraftwerke vermieden werden. Als Folge kann der Betreiber sowohl CO2-Emissionen als auch Emissions-, Brennstoff- sowie An- und Abfahrkosten einsparen.
Der Vortrag basiert auf Ergebnissen aus mehreren Forschungsprojekten, die an der Hochschule Kempten seit 2016 gemeinsam mit Fernwärmeversorgern durchgeführt wurden. Dabei wurden maschinelle Lernverfahren sehr unterschiedlicher Komplexität systematisch untersucht und bewertet – von „einfachen“ bis hin zu anspruchsvollen Verfahren aus dem Bereich des sogenannten „Deep Learning“. Die Wärmelastprognosen werden unter Verwendung historischer Betriebs- und Wetterdaten sowie von Wetterprognosen vollautomatisiert erstellt und dem Betreiber über eine Web-Schnittstelle zur Verfügung gestellt, die auch im Vortrag gezeigt wird.
Die vorgestellte Methode bietet erhebliche Einsparpotenziale für den Anlagenbetreiber. Sie ist zudem auch auf andere Branchen mit ähnlichen Zielgrößen bzw. Fragestellungen übertragbar.
Der Beitrag beschreibt die Generation Z, wobei ein besonderes Interesse am Reiseverhalten und an den Reisevorlieben dieser Generation besteht. Zur Einführung wird die Generation Z allgemeiner beschrieben: Neben einer Definition der
Geburtenjahrgänge, die der Generation Z zuzurechnen sind, wird auf das Aufwachsen in und mit der Digitalisierung eingegangen. Zudem werden die Werte und Ziele dieser Personengruppe aufgezeigt, um anschließend auf das Reiseverhalten und daraus resultierenden Erkenntnissen für die Tourismusbranche einzugehen.
Nach Umfragen im Mai, Juli und Oktober 2020 hat das Bayerische Zentrum für Tourismus im März 2021 eine vierte Befragungswelle zum Reiseverhalten der Deutschen in Zeiten von Corona durchgeführt. Die repräsentative Online-Befragung wirft sowohl einen Blick auf das Reiseverhalten nach Lockerung der Reisebeschränkungen 2020, auf das bisherige Reiseverhalten 2021 als auch auf das Reisen 2021. Dabei geht es um Reiseabsichten, Urlaubsziele und Urlaubsgestaltung sowie die Gründe, 2021 nicht verreisen zu wollen.
Nach Umfragen im Mai und Juli hat das BZT im Oktober eine dritte Befragungswelle zum Reiseverhalten der Deutschen in Zeiten von Corona durchgeführt. Die repräsentative Online-Befragung wirft sowohl einen Blick auf bisherige Reiseerfahrungen nach Lockerung der Reisebeschränkungen als auch auf die Personen, die im Sommer nicht verreist sind. Weiterhin liegt der Fokus der Umfrage auf der bevorstehenden Wintersaison zwischen November und April. Es geht um Reiseabsichten, Urlaubsziele und Urlaubsgestaltung sowie die Gründe, nicht verreisen zu wollen.
Im Juli 2020 hat das BZT eine zweite, repräsentative Online-Befragung zum Reiseverhalten der Deutschen in Zeiten von Corona durchgeführt. Dabei wurden zum einen die Erfahrungen der Reisenden zu den ersten Urlauben nach Lockerung der Reisebeschränkungen im Mai und Juni 2020 in Deutschland abfragt. Zum anderen standen die Reisepläne innerhalb Europas, Reisegestaltung und Erwartungen der Reisenden im Zentrum der Untersuchung.
Welche Gründe halten die Deutschen vom Reisen ab? Welche Urlaubsmotive haben sie? Welche Maßnahmen müssen aus Sicht der Reisenden in den Urlaubsregionen erfüllt sein? Antworten auf diese Fragen gibt eine deutschlandweit repräsentative Online-Befragung des Bayerischen Zentrums für Tourismus, die im Mai 2020 von GfK durchgeführt wurde
Winterurlaub 2022/2023
(2023)
Wie konkret sehen die privaten Reisepläne zwischen Dezember 2022 und April 2023 vor dem Hintergrund der derzeitigen wirtschaftlichen und politischen Lage aus? Welche Erwartungen haben Reisende, die den Winterurlaub im Schnee verbringen möchten und wo wird gespart? Diesen Fragen geht das Bayerische Zentrum für Tourismus (BZT) in seiner Umfrage unter der deutschsprachigen Bevölkerung im Alter von 18 bis 74 Jahren in Deutschland, durchgeführt von GfK, nach.
Reisen im Sommer 2022
(2022)
Das Bayerische Zentrum für Tourismus hat das Reiseverhalten während der Corona-Pandemie durch vier bevölkerungsrepräsentative Online-Befragungen zwischen Mai 2020 und März 2021 begleitet. Im April/Mai 2022 wurde erneut eine Umfrage durchgeführt, die das Reisen im Jahr 2022 beleuchtet. Es geht um bisherige Reisen in den ersten vier Monaten des Jahres und um die Reiseabsichten für Mai bis Oktober 2022. Dabei werden neben den Fragen nach Reiseziel, Reisemonat, Unterkunft und Verkehrsmittel auch Erkenntnisse zu Entscheidungskriterien der Unterkunft wie auch zur Wahl des Urlaubsziels gewonnen.
Reisen und Nachhaltigkeit
(2022)
Was versteht die Bevölkerung unter Nachhaltigkeit? Und was bedeutet ihr nachhaltiges Reisen? Eine repräsentative Umfrage des Bayerischen Zentrums für Tourismus (BZT), durchgeführt von GfK im September 2022 unter mehr als 2.000 Frauen und Männern in Deutschland, gibt Einsichten zum Verständnis von Nachhaltigkeit und nachhaltigem Reisen sowie dem Alltagshandeln in Bezug auf Nachhaltigkeit. Besonders interessant vor dem Hintergrund aktueller Diskussionen um den Ausbau erneuerbarer Energien: Über 50 Prozent stören sich in einer Urlaubsregion weder an Solarparks noch an Windrädern.
Die Studie beleuchtet die Tourismusakzeptanz der bayerischen Bevölkerung. Neben der Bewertung der Auswirkungen des Tourismus für den Wohnort, für die Region und die Befragten persönlich wurden auch touristische Weiterentwicklungsmöglichkeiten abgefragt. Zudem gibt die Umfrage Einsichten in die Zufriedenheit mit verschiedenen Lebenssituationen und wie der Tourismus in den Regionen darauf einwirkt.