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Die rasante Entwicklung der Sensortechnik im Endverbraucherbereich lässt einen klinischen Nutzen der verfügbaren dezentral erhobenen Daten aus dem Patientenalltag zur Überwachung des individuellen Gesundheitszustands vermuten. Zur Überprüfung dieser Vermutung ist die Bereitstellung einer entsprechenden Plattform in den klinischen Alltag erforderlich. Hierzu wird die bwHealthApp entwickelt, mit der sowohl die aktuelle Bandbreite als auch die Evolution der Sensortechnik auf die klinische Anwendung abbildbar ist. Mit dem flexiblen Entwurf lässt sich der klinische Nutzen für die personalisierte Medizin evaluieren. Außerdem bietet die bwHealthApp einen an Machbarkeit orientierten Diskussionsbeitrag zu offenen rechtlichen, regulatorischen und ethischen Fragestellungen der Digitalisierung in der Medizin in Deutschland.
The livestock sector is growing steadily and is responsible for around 18% of global greenhouse‐gas‐emissions, which is more than the global transport sec-tor (Steinfeld et al. 2006). This paper examines the potential of social marketing to reduce meat consumption. The aim is to understand consumers’ motivation in diet choices and to learn what opportunities social marketing can provide to counteract negative environmental and health trends. The authors believe that research to answer this question should start in metropolitan areas, be-cause measures should be especially effective there. Based on the Theory of Planned Behaviour (TPB, Ajzen 1991) and the Technology‐Acceptance‐Model by Huijts et al. (2012), an online‐study with participants from the metropolitan region (n = 708) was conducted in which central socio‐psychological constructs for a meat consumption reduction were examined. It was shown that attitude, personal norm and habit have a critical influence on the intention to reduce meat consumption. A segmentation of consumers based on these factors led to three consumer clusters: vegetarians/flexitarians, potential flexitarians and convinced meat eaters. Potential flexitarians are an especially relevant target group for the development of social‐marketing‐measures to reduce meat consumption. In co‐creation‐workshops with potential flexitarians from the metropolitan region, barriers and benefits of reducing meat consumption were identified. The factors of environmental protection, animal welfare and desire for variety turn out to be the most relevant motivational factors. Based on these factors, consumers proposed a variety of social marketing measures, such as applications and labels to inform about the environmental impact of meat products.
Wie kann die Digitalisierung in der Bauzulieferbranche erfolgreich gemeistert werden? Die Fülle und Komplexität der Fragen dazu lassen sich auf zwei zentrale Kernfragen reduzieren: Was sind die richtigen Inhalte und wesentlichen Werttreiber der Digitalisierung? Und wie muss zukünftig mit der steigenden Informationsflut, der rasant wachsenden Komplexität und der abnehmenden Planbarkeit umgegangen werden?
In diesem Beitrag wird ein Framework vorgestellt, das Bauzulieferern hilft, ihr digitales Zielbild mit seinen Werttreibern systematisch aus dem Kundennutzen abzuleiten. Das Framework berücksichtigt die Besonderheiten der Bauzulieferindustrie, kann aber mit leichten Anpassungen auch auf andere Branchen angewendet werden. Aufbauend auf dem Zielbild können Unternehmen definieren, welche technischen, personellen und organisatorischen Veränderungen für dessen Umsetzung erforderlich sind. Um flexibel mit den dynamischen Veränderungen in ihrem Ökosystem und kulturellen Herausforderungen umgehen zu können, werden zudem fünf Einflussgrößen identifiziert, die Unternehmen bei der Entwicklung der dafür benötigten Evolutionskompetenz berücksichtigen müssen.
Im Gegensatz etwa zur klassischen Werbung handelt es sich beim Event-Marketing um ein dynamisches Kommunikationsinstrument, das laufend Trends und Neuerungen mit sich bringt. Die vielfältigen Einsatzmöglichkeiten und Potenziale des Event-Marketing ermöglichen es, entsprechend dem momentanen Zeitgeist relevante Zielgruppen zu erreichen, markenrelevante Wirklichkeiten und Erlebniswelten zu generieren, Emotionen und Sympathiewerte zu erzeugen und auf diese Weise eine Bindung zwischen Marke bzw. Unternehmen und Rezipienten herzustellen.
Companies are becoming aware of the potential risks arising from sustainability aspects in supply chains. These risks can affect ecological, economic or social aspects. One important element in managing those risks is improved transparency in supply chains by means of digital transformation. Innovative technologies like blockchain technology can be used to enforce transparency. In this paper, we present a smart contract-based Supply Chain Control Solution to reduce risks. Technological capabilities of the solution will be compared to a similar technology approach and evaluated regarding their benefits and challenges within the framework of supply chain models. As a result, the proposed solution is suitable for the dynamic administration of complex supply chains.
Companies compete more and more as integrated supply chains rather than as individual firms. The success of the entire supply chain determines the economic well-being of the individual company. With management attention shifting to supply chains, the role of management accounting naturally must extend to the cross-company layer as well. This book demonstrates how management accounting can make a significant contribution to supply chain success.It targets students who are already familiar with the fundamentals of accounting and now want to extend their expertise in the field of cross company (or network) management accounting. Practitioners will draw valuable insights from the text as well.
Investigation of tympanic membrane influences on middle-ear impedance measurements and simulations
(2020)
This study simulates acoustic impedance measurements in the human ear canal and investigates error influences due to improperly accounted evanescence in the probe’s near field, cross-section area changes, curvature of the ear canal, and pressure inhomogeneities across the tympanic membrane, which arise mainly at frequencies above 10 kHz. Evanescence results from strongly damped modes of higher order, which can only be found in the near field of the sound source and are excited due to sharp cross-sectional changes as they occur at the transition from the probe loudspeaker to the ear canal. This means that different impedances are measured depending on the probe design. The influence of evanescence cannot be eliminated completely from measurements, however, it can be reduced by a probe design with larger distance between speaker and microphone. A completely different approach to account for the influence of evanescence is to evaluate impedance measurements with the help of a finite element model, which takes the precise arrangement of microphone and speaker in the measurement into account. The latter is shown in this study exemplary on impedance measurements at a tube terminated with a steel plate. Furthermore, the influences of shape changes of the tympanic membrane and ear canal curvature on impedance are investigated.
Purpose: Gliomas are the most common and aggressive type of brain tumors due to their infiltrative nature and rapid progression. The process of distinguishing tumor boundaries from healthy cells is still a challenging task in the clinical routine. Fluid attenuated inversion recovery (FLAIR) MRI modality can provide the physician with information about tumor infiltration. Therefore, this paper proposes a new generic deep learning architecture, namely DeepSeg, for fully automated detection and segmentation of the brain lesion using FLAIR MRI data.
Methods: The developed DeepSeg is a modular decoupling framework. It consists of two connected core parts based on an encoding and decoding relationship. The encoder part is a convolutional neural network (CNN) responsible for spatial information extraction. The resulting semantic map is inserted into the decoder part to get the full-resolution probability map. Based on modified U-Net architecture, different CNN models such as residual neural network (ResNet), dense convolutional network (DenseNet), and NASNet have been utilized in this study.
Results: The proposed deep learning architectures have been successfully tested and evaluated on-line based on MRI datasets of brain tumor segmentation (BraTS 2019) challenge, including s336 cases as training data and 125 cases for validation data. The dice and Hausdorff distance scores of obtained segmentation results are about 0.81 to 0.84 and 9.8 to 19.7 correspondingly.
Conclusion: This study showed successful feasibility and comparative performance of applying different deep learning models in a new DeepSeg framework for automated brain tumor segmentation in FLAIR MR images. The proposed DeepSeg is open source and freely available at https://github.com/razeineldin/DeepSeg/.