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Introduction : Relevance of doing business in Africa
No full textIn recent years, Africa has increasingly become the focus of attention for political decision-makers, managers, and management scholars. This diverse and multi-faceted continent consists of 54 countries, 49 of which make up Sub-Saharan Africa. The countries differ on many levels, such as geographic size and location (landlocked vs. sea access), demographics, economic size and dynamics, level of social development, degree of urbanization, and culture. There is often a tendency to emphasize the manifold challenges African countries face such as political instability, regulatory complexities, lack of skilled labor force, or infrastructural gaps. However, the challenging business conditions should not obscure the fact that Africa is one of the most dynamic regions of the world and has recently gained more attention from international companies for many interwoven reasons (Amankwah-Amoah et al., 2018; Boso et al., 2018; Mol et al., 2017)
Native and cell-derived extracellular matrix exhibit disparate immunogenic and immunomodulatory effects
Get PDFThe extracellular matrix (ECM) represents the natural environment of the cells and consists of various fibrous and non-fibrous proteins. It can be generated by decellularization of native tissue (dECM) or by isolation from cultured cells in vitro (cdECM). In the present study the immunomodulatory effect of dECM from native adipose tissue and cdECM from adipose derived stem cells (cdECM) on monocytes and ASCs encapsulated in gellan gum-ECM hybrid hydrogels was investigated. The monocyte activation test revealed a higher secretion of IL6 and TNFα in monocytes incubated with dECM compared to cdECM. Encapsulated ASCs in gellan gum-ECM-hybrid hydrogels exhibit different cytokine profiles (IL8, IL6, MCP-1, TNFα) when cultured with dECM or cdECM or gellan gum alone. The demonstrated differences in cellular behavior in the present of the two different types of ECM should be considered when using them as a biomaterial for in vitro as well as in vivo applications
Fluorescence lifetime imaging unravels the pathway of glioma cell death upon hypericin-induced photodynamic therapy
Get PDFMalignant primary brain tumors are a group of highly aggressive and often infiltrating tumors that lack adequate therapeutic treatments to achieve long time survival. Complete tumor removal is one precondition to reach this goal. A promising approach to optimize resection margins and eliminate remaining infiltrative so-called guerilla cells is photodynamic therapy (PDT) using organic photosensitizers that can pass the disrupted blood–brain-barrier and selectively accumulate in tumor tissue. Hypericin fulfills these conditions and additionally offers outstanding photophysical properties, making it an excellent choice as a photosensitizing molecule for PDT. However, the actual hypericin-induced PDT cell death mechanism is still under debate. In this work, hypericin-induced PDT was investigated by employing the three distinct fluorescent probes hypericin, resorufin and propidium iodide (PI) in fluorescence-lifetime imaging microscopy (FLIM). This approach enables visualizing the PDT-induced photodamaging and dying of single, living glioma cells, as an in vitro tumor model for glioblastoma. Hypericin PDT and FLIM image acquisition were simultaneously induced by 405 nm laser irradiation and sequences of FLIM images and fluorescence spectra were recorded to analyze the PDT progression. The reproducibly observed cellular changes provide insight into the mechanism of cell death during PDT and suggest that apoptosis is the initial mechanism followed by necrosis after continued irradiation. These new insights into the mechanism of hypericin PDT of single glioma cells may help to adjust irradiation doses and improve the implementation as a therapy for primary brain tumors
GPT-4 shows potential for identifying social anxiety from clinical interview data
Get PDFWhile the potential of Artificial Intelligence (AI) - particularly Natural Language Processing (NLP) models - for detecting symptoms of depression from text has been vastly researched, only a few studies examine such potential for the detection of social anxiety symptoms. We investigated the ability of the large language model (LLM) GPT-4 to correctly infer social anxiety symptom strength from transcripts obtained from semi-structured interviews. N = 51 adult participants were recruited from a convenience sample of the German population. Participants filled in a self-report questionnaire on social anxiety symptoms (SPIN) prior to being interviewed on a secure online teleconference platform. Transcripts from these interviews were then evaluated by GPT-4. GPT-4 predictions were highly correlated (r = 0.79) with scores obtained on the social anxiety self-report measure. Following the cut-off conventions for this population, an F1 accuracy score of 0.84 could be obtained. Future research should examine whether these findings hold true in larger and more diverse datasets
Optimizing PCB stackups for enhanced GaN transistor performance in high-power applications
No full textThis paper explores specialized PCB stackups to enhance GaN transistor performance in applications up to 10kW. Recognizing extensive prior research on GaN in high-power contexts, our study initially investigates layouts, which will be used for developing optimized stackups. Our objective is, to identify stackups that maximize thermal performance while minimizing parasitic effects. The analysis establishes insulated metal substrate and copper inlay PCB stackups with vertical layouts as promising options. These results enable a flexible integration of stackup designs in high-power GaN applications and their synergy with other design objectives
Current status and prospects of automatic sleep stages scoring: Review
Get PDFThe scoring of sleep stages is one of the essential tasks in sleep analysis. Since a manual procedure requires considerable human and financial resources, and incorporates some subjectivity, an automated approach could result in several advantages. There have been many developments in this area, and in order to provide a comprehensive overview, it is essential to review relevant recent works and summarise the characteristics of the approaches, which is the main aim of this article. To achieve it, we examined articles published between 2018 and 2022 that dealt with the automated scoring of sleep stages. In the final selection for in-depth analysis, 125 articles were included after reviewing a total of 515 publications. The results revealed that automatic scoring demonstrates good quality (with Cohen's kappa up to over 0.80 and accuracy up to over 90%) in analysing EEG/EEG + EOG + EMG signals. At the same time, it should be noted that there has been no breakthrough in the quality of results using these signals in recent years. Systems involving other signals that could potentially be acquired more conveniently for the user (e.g. respiratory, cardiac or movement signals) remain more challenging in the implementation with a high level of reliability but have considerable innovation capability. In general, automatic sleep stage scoring has excellent potential to assist medical professionals while providing an objective assessment
Twitter and citations
Get PDFSocial media, especially Twitter, plays an increasingly important role among researchers in showcasing and promoting their research. Does Twitter affect academic citations? Making use of Twitter activity about columns published on VoxEU, a renowned online platform for economists, we develop an instrumental variable strategy to show that Twitter activity about a research paper has a causal effect on the number of citations that this paper will receive. We find that the existence of at least one tweet, as opposed to none, increases citations by 16-25%. Doubling overall Twitter engagement boosts citations by up to 16%
Automatisierung von Kabelverteilern (Teil 1) : Flexibilitätsmaßnahmen im Niederspannungsnetz
No full textDer Erfolg der Energiewende in Deutschland setzt eine zunehmende Anzahl an dezentralen elektrischen Erzeugungsanlagen (EZA) voraus. Diese dezentralen EZA, wie Photovoltaikanlagen oder Blockheizkraftwerke, bringen für Verteilnetzbetreiber große Herausforderungen mit sich. Im Rahmen des geförderten Forschungsprojekts „Demonstrator Automatisierte Kabelverteil (KV) als Alternative zum regelbaren Ortsnetztransformator (DEMO rONT-Alternative)“ wurde ein neuer Ansatz für die Lösung der bestehenden Problematik erforscht. Dieser besteht in der aktiven Änderung der Topologie der Netzgebiete je nach elektrischer Last und PV-Einspeisung (Trennstellenverlagerung)
Two-dimensional pose estimation of industrial robotic arms in highly dynamic collaborative environments
Get PDFIn modern collaborative production environments where industrial robots and humans are supposed to work hand in hand, it is mandatory to observe the robot’s workspace at all times. Such observation is even more crucial when the robot’s main position is also dynamic e.g. because the system is mounted on a movable platform. As current solutions like physically secured areas in which a robot can perform actions potentially dangerous for humans, become unfeasible in such scenarios, novel, more dynamic, and situation aware safety solutions need to be developed and deployed.
This thesis mainly contributes to the bigger picture of such a collaborative scenario by presenting a data-driven convolutional neural network-based approach to estimate the two-dimensional kinematic-chain configuration of industrial robot-arms within raw camera images. This thesis also provides the information needed to generate and organize the mandatory data basis and presents frameworks that were used to realize all involved subsystems. The robot-arm’s extracted kinematic-chain can also be used to estimate the extrinsic camera parameters relative to the robot’s three-dimensional origin. Further a tracking system, based on a two-dimensional kinematic chain descriptor is presented to allow for an accumulation of a proper movement history which enables the prediction of future target positions within the given image plane. The combination of the extracted robot’s pose with a simultaneous human pose estimation system delivers a consistent data flow that can be used in higher-level applications.
This thesis also provides a detailed evaluation of all involved subsystems and provides a broad overview of their particular performance, based on novel generated, semi automatically annotated, real datasets
Process characterization of the transesterification of rapeseed oil to biodiesel using design of experiments and infrared spectroscopyen
Get PDFFor optimization of production processes and product quality, often knowledge of the factors influencing the process outcome is compulsory. Thus, process analytical technology (PAT) that allows deeper insight into the process and results in a mathematical description of the process behavior as a simple function based on the most important process factors can help to achieve higher production efficiency and quality. The present study aims at characterizing a well-known industrial process, the transesterification reaction of rapeseed oil with methanol to produce fatty acid methyl esters (FAME) for usage as biodiesel in a continuous micro reactor set-up. To this end, a design of experiment approach is applied, where the effects of two process factors, the molar ratio and the total flow rate of the reactants, are investigated. The optimized process target response is the FAME mass fraction in the purified nonpolar phase of the product as a measure of reaction yield. The quantification is performed using attenuated total reflection infrared spectroscopy in combination with partial least squares regression. The data retrieved during the conduction of the DoE experimental plan were used for statistical analysis. A non-linear model indicating a synergistic interaction between the studied factors describes the reactor behavior with a high coefficient of determination (R²) of 0.9608. Thus, we applied a PAT approach to generate further insight into this established industrial process