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Zusammenfassung Im Beitrag wird die Weiterbildungsarbeit im Rahmen der betrieblichen Sozialberatung untersucht. Als empirische Basis dient eine qualitative Querschnittstudie, in der 16 Experteninterviews mit Fachkräften der betrieblichen Sozialberatung in Deutschland geführt wurden. Die Studie erweitert den Stand der Forschung zur betrieblichen Weiterbildung, indem sie Einblick in die Heterogenität der Veranstaltungsarten und Veranstaltungsthemen sowie in das Handeln betrieblicher Sozialberatender bei der Entwicklung und Durchführung von Weiterbildungsangeboten gibt.

Fluvial floods endure as one of the most catastrophic weather-induced disasters worldwide, leading to numerous fatalities each year and significantly impacting socio-economic development and the environment. Hence, the research and development of new methods and algorithms focused on improving fluvial flood prediction and devising robust flood management strategies are essential. This study explores and assesses the potential application of 1D-Convolution Neural Networks (1D-CNN) for spatial prediction of fluvial flood in the Quang Nam province, a high-frequency tropical cyclone area in central Vietnam. To this end, a geospatial database with 4156 fluvial flood locations and 12 flood indicators was considered. The ADAM algorithm and the MSE loss function were used to train the 1D-CNN model, whereas popular performance metrics, such as Accuracy (Acc), Kappa, and AUC, were used to measure the performance. The results indicated remarkable performance by the 1D-CNN model, achieving high prediction accuracy with metrics such as Acc = 90.7%, Kappa = 0.814, and AUC = 0.963. Notably, the proposed 1D-CNN model outperformed benchmark models, including DeepNN, SVM, and LR. This achievement underscores the promise and innovation brought by 1D-CNN in the realm of susceptibility mapping for fluvial floods.

Solid polymer electrolytes are promising candidates for implementation in next-generation all-solid-state batteries (ASSBs) which could replace conventional batteries used today. However, the materialization of ASSBs on a mass scale is restricted by the low ionic conductivity and high interfacial resistance of solid electrolytes. In this work, succinonitrile (SN) with lithium (trifluoromethylsulphonyl)imide (LiTFSI) and Al-doped Li7La3Zr2O12 (Al-LLZO) nanoparticles were used to improve the ionic conductivity of a polyethylene oxide-based composite electrolyte. The Al-LLZO nanoparticles were synthesized by a facile synthesis process at low temperatures, which contributed to an enhancement in the ionic conductivity. A solid polymer electrolyte with 7.5 wt% of Al-LLZO and 15 wt% of SN achieved a high ionic conductivity of 4.17 × 10−4 Scm−1 at room temperature and a large value of 0.451 for the lithium-ion transport number at 60 °C. By adding 10 wt% SN and 10 wt% of Al-LLZO in the LiFePO4 cathode, the cell could operate at 25 °C with a specific capacity of 130 mAh g−1 and 89% capacity retention after 200 cycles at current density of 20 mA g−1. This study therefore proposes a solution to improve the ionic conductivity of solid polymer electrolytes in all-solid-state batteries.

Purpose: A systematic literature review has neglected for years in both national and international vocational educational and training (VET) policy research. Recently, scholarly interest in and the need for such a review has increased rapidly. This review introduces the application of the systematic literature review method, with a focus on research work completed in European VET policy. Approach: To investigate the value and applicability of the systematic literature review method in European VET policy research, we conducted a pilot study following the guidelines and procedures presented by Gessler and Siemer. Findings: First, the process of conducting a literature review and its major methodological steps are described, followed by a descriptive analysis of the sample and characteristics of the studies reviewed. Second, initial insights into the research methodology and the topics that emerged during its application are presented. Altogether, we documented a first attempt to systematize research on European VET policy, including lessons learned from conducting a systematic literature review. Conclusion: The review revealed that although research on international European VET policy research has increased in recent years, hardly any systematization of the current research has been proposed. Instead, most research has been limited to identifying specific country-related factors. By comparison, we propose a systematic approach to reviewing research on European VET policy, being well aware of the strengths and limitations of the proposed method and the results. Thus, this systematic review presents a substantial starting point and research agenda for further studies on this topic.

All-solid-state batteries have gained significant attention as promising candidates to replace liquid electrolytes in lithium-ion batteries for high safety, energy storage performance, and stability under elevated temperature conditions. However, the low ionic conductivity and unsuitability of lithium metal in solid polymer electrolytes is a critical problem. To resolve this, we used a cubic garnet oxide electrolyte (Li7La3Zr2O12 – LLZO) and ionic liquid in combination with a polymer electrolyte to produce a composite electrolyte membrane. By applying a solid polymer electrolyte on symmetric stainless steel, the composite electrolyte membrane shows high ionic conductivity at elevated temperatures. The effect of LLZO in suppressing lithium dendrite growth within the composite electrolyte was confirmed through symmetric lithium stripping/plating tests under various current densities showing small polarization voltages. The full cell with lithium iron phosphate as the cathode active material achieved a highest specific capacity of 137.4 mAh g−1 and a high capacity retention of 98.47% after 100 cycles at a current density of 50 mA g−1 and a temperature of 60°C. Moreover, the specific discharge capacities were 137 and 100.8 mAh g−1 at current densities of 100 and 200 mA g−1, respectively. This research highlights the capability of solid polymer electrolytes to suppress the evolution of lithium dendrites and enhance the performance of all-solid-state batteries.

With various information sources (e.g., from IoT sensors to social media), it is difficult to provide users with trustworthy services in ambient environment. The aim of this paper is i) to design trust ontology for representing semantics of the ambient services and ii ) to compute trust measures among users by using a personalized trust ontology. In particular, given a large amount of data collected from ambient sensors, efficient trust computation and reasoning are required for the stability and reliability. Thereby, we propose trust ontology-based framework for deriving personalized ontologies for individual users according to their preference, perspective, and purpose. To evaluate the proposed model, we have figured out a method how the degree of trust is estimated based on the trust ontology. Furthermore, we have proved that the proposed method is reliable with a case study on a social media (Twitter) for a particular domain (restaurant).

Since trust among entities can change according to various conditions, it is necessary for ambient services to determine when and how the trust has to be updated. Therefore, our contribution in this paper is to present: 1) a new definition of trust that can be extended to various domains; 2) a novel method based on social events and patterns to trigger trust refreshment in ambient services; and 3) a web application framework (called SocioScope) for collecting and analyzing data from multiple data sources. Finally, the case study suggests that this proposal could be applied to trust-aware ambient and recommendation systems.