Universität Potsdam

Das Handbuch Organisationssoziologie liefert einen umfassenden Überblick über die Entwicklung, den Stand und die Zukunft der Organisationssoziologie als wissenschaftliche Disziplin. Dabei geht es sowohl um die systematische Aufnahme relevanter Theoriestränge, Methoden und Konzepte als auch um die Wechselbeziehungen, Überschneidungen und Komplementaritäten zu Nachbardisziplinen, die in einem Dialog aufgenommen werden. Das Handbuch vermittelt so einen eigenständigen Zugriff auf die Organisationssoziologie und bündelt gleichzeitig dessen Wissen auf dem neuesten Stand. Darüber soll es zu einem Standardwerk zur Organisationssoziologie im deutschsprachigen Raum werden.

The post-COVID The Great Online Transition requires more support for teaching with information and communications technology (ICT) than ever. The present study investigated teachers' psychological (perceived preparedness for distance education) and beha-vioural (frequency of teacher-student contact) adaptations to distance education in relation to job (training, collaboration, and equipment) and personal (self-efficacy) resources in the area of ICT during the first wave of school closings in 2020. We surveyed 1103 teachers in German-speaking regions via newsletters and X (formerly Twitter). Results from the recursive path model showed that all job resources were positively associated with teachers' perceived preparedness, but the actual frequency of contact was only significantly related to ICT collaboration. Lastly, ICT self-efficacy mediated the associations between job resources and teachers' adaptations. Our findings highlighted policymaking and school administration applications in which focus should be placed on fostering ICT resources, particularly collaboration. ARTICLE HISTORY

We explore the spatial and temporal variations in denudation rates in the northern Pamir—Tian Shan region using ¹⁰Be‐derived denudation rates from modern (n = 110) and buried sediment (2.0–2.7 Ma; n = 3), and long‐term exhumation rates from published apatite fission track (AFT; n = 705) and apatite (U‐Th‐Sm)/He (AHe; n = 211) thermochronology. We found moderate correlations between denudation rates and topographic metrics and weak correlations between denudation rates and annual rainfall, highlighting complex linkages among tectonics, climate, and surface processes that vary locally. The ¹⁰Be data show a spatial trend of decreasing modern denudation rates from west to east, suggesting that deformation and precipitation control denudation in the northern Pamir and western Tian Shan. Farther east, the denudational response of the landscape to Quaternary glaciations is more pronounced and reflected in our data. Modern ¹⁰Be denudation rates are generally higher than the long‐term AFT and AHe exhumation rates across the studied area. In the Kyrgyz Tian Shan, on average, the highest ¹⁰Be denudation rates are recorded in the Terskey range, south of Lake Issyk‐Kul. Here, modern denudation rates are higher than ¹⁰Be‐derived paleo‐denudation rates, which are comparable in magnitude with the long‐term exhumation rates inferred from AFT and AHe. We propose that denudation in the region, particularly in the Terskey range, remained relatively steady during the Neogene and early Pleistocene. Denudation increased due to glacial‐interglacial cycles in the Quaternary, but this occurred after the onset and intensification of the Northern Hemisphere glaciations at 2.7 Ma.

Background Socially assistive devices (care robots, companions, smart screen assistants) have been advocated as a promising tool in elderly care in Western healthcare systems. Ethical debates indicate various challenges. One of the most prevalent arguments in the debate is the double-benefit argument claiming that socially assistive devices may not only provide benefits for autonomy and well-being of their users but might also be more efficient than other caring practices and might help to mitigate scarce resources in healthcare. Against this background, we used a subset of comparative empirical studies from a comprehensive systematic review on effects and perceptions of human-machine interaction with socially assistive devices to gather and appraise all available evidence supporting this argument from the empirical side. Methods Electronic databases and additional sources were queried using a comprehensive search strategy which generated 9851 records. Studies were screened independently by two authors. Methodological quality of studies was assessed. For 39 reports using a comparative study design, a narrative synthesis was performed. Results The data shows positive evidential support to claim that some socially assistive devices (Paro) might be able to contribute to the well-being and autonomy of their users. However, results also indicate that these positive findings may be heavily dependent on the context of use and the population. In addition, we found evidence that socially assistive devices can have negative effects on certain populations. Evidence regarding the claim of efficiency is scarce. Existing results indicate that socially assistive devices can be more effective than standard of care but are far less effective than plush toys or placebo devices. Discussion We suggest using the double-benefit argument with great caution as it is not supported by the currently available evidence. The occurrence of potentially negative effects of socially assistive devices requires more research and indicates a more complex ethical calculus than suggested by the double-benefit argument.

Sunlight-driven H2 generation is a central technology to tackle our impending carbon-based energy collapse. Colloidal photocatalysts consisting of plasmonic and catalytic nanoparticles are promising for H2 production at solar irradiances, but their performance is hindered by absorption and multiscattering events. Here we present a two-dimensional bimetallic catalyst by incorporating platinum nanoparticles into a well-defined supercrystal of gold nanoparticles. The bimetallic supercrystal exhibited an H2 generation rate of 139mmolgcat−1h−1\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$139\,{\mathrm{mmol}}\,{\mathrm{g}}_{\mathrm{cat}}^{-1}\,{\mathrm{h}}^{-1}$$\end{document} via formic acid dehydrogenation under visible light illumination and solar irradiance. This configuration makes it possible to study the interaction between the two metallic materials and the influence of this in catalysis. We observe a correlation between the intensity of the electric field in the hotspots and the boosted catalytic activity of platinum nanoparticles, while identifying a minor role of heat and gold-to-platinum charge transfer in the enhancement. Our results demonstrate the benefits of two-dimensional configurations with optimized architecture for liquid-phase photocatalysis.

Antimicrobial polymers are a promising alternative to conventional antibiotics in the fight against antimicrobial resistance. Cationic bottle brush copolymers have shown to be superior to linear topologies in previous studies. Herein, the aspect ratio of such polymers is varied creating differently shaped confined unimolecular structures with varying degrees of side chain mobility. Using reversible addition‐fragmentation chain‐transfer (RAFT) polymerization, bottle brushes are produced in a one‐pot procedure. The morphology is confirmed by atomic force microscopy. The hydrophobicity, as determined via high performance‐liquid chromatography (HPLC) analysis, is drastically influenced by the topology. Using Fourier‐transform infrared (FTIR) spectroscopy, it is found that polymers with a high side chain mobility and increased global hydrophilicity, are less hydrated, and have stronger intramolecular hydrogen bonds. A phase segregated morphology leading to unimolecular micellization is assumed. Biological tests reveal increased antimicrobial activity for such segregated polymers. Their excellent hemocompatibility results in highly selective antimicrobial polymers whose adaptability seems to be a key feature in their excellent performance. This study highlights the tremendous importance of structural control in antimicrobial polymers.

State-of-the-art Entity Matching approaches rely on transformer architectures, such as BERT, for generating highly contextualized embeddings of terms. The embeddings are then used to predict whether pairs of entity descriptions refer to the same real-world entity. BERT-based EM models demonstrated to be effective, but act as black-boxes for the users, who have limited insight into the motivations behind their decisions. In this paper, we perform a multi-facet analysis of the components of pre-trained and fine-tuned BERT architectures applied to an EM task. The main findings resulting from our extensive experimental evaluation are (1) the fine-tuning process applied to the EM task mainly modifies the last layers of the BERT components, but in a different way on tokens belonging to descriptions of matching/non-matching entities; (2) the special structure of the EM datasets, where records are pairs of entity descriptions, is recognized by BERT; (3) the pair-wise semantic similarity of tokens is not a key knowledge exploited by BERT-based EM models; (4) fine-tuning SBERT, a pre-trained version of BERT on the sentence similarity task, i.e., a task close to EM, does not allow the model to largely improve the effectiveness and to learn different forms of knowledge. Approaches customized for EM, such as Ditto and SupCon, seem to rely on the same knowledge as the other transformer-based models. Only the contrastive learning training allows SupCon to learn different knowledge from matching and non-matching entity descriptions; (5) the fine-tuning process based on a binary classifier does not allow the model to learn key distinctive features of the entity descriptions.

Arachidonic acid 15-lipoxygenases (ALOX15) play a role in mammalian erythropoiesis but they have also been implicated in inflammatory processes. Seven intact Alox genes have been detected in the mouse reference genome and the mouse Alox15 gene is structurally similar to the orthologous genes of other mammals. However, mouse and human ALOX15 orthologs have different functional characteristics. Human ALOX15 converts C 20 polyenoic fatty acids like arachidonic acid mainly to the n-6 hydroperoxide. In contrast, the n-9 hydroperoxide is the major oxygenation product formed by mouse Alox15. Previous experiments indicated that Leu353Phe exchange in recombinant mouse Alox15 humanized the catalytic properties of the enzyme. To investigate whether this functional humanization might also work in vivo and to characterize the functional consequences of mouse Alox15 humanization we generated Alox15 knock-in mice ( Alox15-KI ), in which the Alox15 gene was modified in such a way that the animals express the arachidonic acid 15-lipoxygenating Leu353Phe mutant instead of the arachidonic acid 12-lipoxygenating wildtype enzyme. These mice develop normally, they are fully fertile but display modified plasma oxylipidomes. In young individuals, the basic hematological parameters were not different when Alox15-KI mice and outbred wildtype controls were compared. However, when growing older male Alox15-KI mice develop signs of dysfunctional erythropoiesis such as reduced hematocrit, lower erythrocyte counts and attenuated hemoglobin concentration. These differences were paralleled by an improved ex vivo osmotic resistance of the peripheral red blood cells. Interestingly, such differences were not observed in female individuals suggesting gender specific effects. In summary, these data indicated that functional humanization of mouse Alox15 induces defective erythropoiesis in aged male individuals. Graphical Abstract

Short term prediction of earthquake magnitude, time, and location is currently not possible. In some cases, however, documented observations have been retrospectively considered as precursory. Here we present seismicity transients starting approx. 8 months before the 2023 MW 7.8 Kahramanmaraş earthquake on the East Anatolian Fault Zone. Seismicity is composed of isolated spatio-temporal clusters within 65 km of future epicentre, displaying non-Poissonian inter-event time statistics, magnitude correlations and low Gutenberg-Richter b-values. Local comparable seismic transients have not been observed, at least since 2014. Close to epicentre and during the weeks prior to its rupture, only scarce seismic activity was observed. The trends of seismic preparatory attributes for this earthquake follow those previously documented in both laboratory stick-slip tests and numerical models of heterogeneous earthquake rupture affecting multiple fault segments. More comprehensive earthquake monitoring together with long-term seismic records may facilitate recognizing earthquake preparation processes from other regional deformation transients.

The answer to improving student learning cannot be to simply spend more time studying (more time in school, more homework, more after-school programs, more summer school, etc.). Decades of cognitive psychology research have shown that classroom instructional time and student self-regulated learning time could be used more efficiently if they incorporate spaced and interleaved retrieval practice. But it is not always easy to translate research to real-life practice. In this paper, we outline the barriers and potential pitfalls in the implementation of time-saving and memory-enhancing strategies in the classroom. We suggest ways to implement these effective strategies, both in instructional design and in students’ own self-regulated study. In particular, we focus on how instructors can support students, not only by modeling effective learning practices in the classroom, but by focusing on ways to empower learners to transfer these strategies into their own study sessions. Finally, we direct researchers’ and practitioners’ attention to future directions that integrate cognitive, metacognitive, and motivational approaches to enhancing student learning.

Plain Language Summary Cumulonimbus clouds are responsible for many severe weather events and control the water cycle in the atmosphere. Although they are of great importance for both weather forecasting and climate projections, the initiation of these clouds is poorly represented by the numerical models, partially due to our lack of understanding the complex mechanisms controlling the transition from shallow to deep convection. Two possible mechanisms have been proposed to explain the initiation of deep convection: the moistening of the mid–troposphere by the non–precipitating clouds, and the positive feedback of the cold pools induced by the precipitating shallow cumuli. However, recent studies showed that the former is too slow of a process to fully explain the deep initiation, while the later is not able to explain the first phase of the transition. Here, we identify another mechanism, namely the interaction between the passive cloud volumes and the convective updrafts, and argue based on theoretical arguments and numerical experiments why it might play an important role in the rapid transition from shallow to deep convection.

We develop a general perturbative theory of finite-coupling quantum thermometry up to second order in probe-sample interaction. By assumption, the probe and sample are in thermal equilibrium, so the probe is described by the mean-force Gibbs state. We prove that the ultimate thermometric precision can be achieved – to second order in the coupling – solely by means of local energy measurements on the probe. Hence, seeking to extract temperature information from coherences or devising adaptive schemes confers no practical advantage in this regime. Additionally, we provide a closed-form expression for the quantum Fisher information, which captures the probe's sensitivity to temperature variations. Finally, we benchmark and illustrate the ease of use of our formulas with two simple examples. Our formalism makes no assumptions about separation of dynamical timescales or the nature of either the probe or the sample. Therefore, by providing analytical insight into both the thermal sensitivity and the optimal measurement for achieving it, our results pave the way for quantum thermometry in setups where finite-coupling effects cannot be ignored.

Nowadays, customers as well as retailers look for increased sustainability. Recommerce markets-which offer the opportunity to trade-in and resell used products-are constantly growing and help to use resources more efficiently. To manage the additional prices for the trade-in and the resell of used product versions challenges retailers as substitution and cannibalization effects have to be taken into account. An unknown customer behavior as well as competition with other merchants regarding both sales and buying back resources further increases the problem's complexity. Reinforcement learning (RL) algorithms offer the potential to deal with such tasks. However, before being applied in practice, self-learning algorithms need to be tested synthetically to examine whether and which work in different market scenarios. In this paper, we evaluate and compare different state-of-the-art RL algorithms within a recommerce market simulation framework. We find that RL agents outperform rule-based benchmark strategies in duopoly and oligopoly scenarios. Further, we investigate the competition between RL agents via self-play and study how performance results are affected if more or less information is observable (cf. state components). Using an ablation study, we test the influence of various model parameters and infer managerial insights. Finally, to be able to apply self-learning agents in practice, we show how to calibrate synthetic test environments from observable data to be used for effective pre-training.

Characterising spatial patterns in water temperature is important for monitoring aquatic habitats and understanding physical and biogeochemical processes to support environmental management decisions. As freshwater bodies exhibit high spatial and temporal variability, high-resolution 3D temperature data are essential to understand local anomalies. The acquisition of simultaneously high spatial and temporal datasets in the field has so far been limited by costs and/or workload associated with commonly used monitoring systems. We present a new, low-cost, spatially and temporally flexible 3D water temperature monitoring system, Surface Measures to Depth (SMeTD). SMeTD can be used to provide information on the relation of water surface temperature to changes with depth, characterise water temperature in 3D and ground truth remotely sensed thermal infrared data. The systems performance was tested under laboratory conditions and under controlled conditions in the field. This revealed an accuracy comparable to established but more expensive monitoring systems. Field testing of SMeTD involved 1-min data collection of 3D water temperature for a full diurnal cycle in a lake. The 3D temperature patterns were supported by a thermal infrared image of the lakes surface. The field dataset demonstrated higher water temperatures and higher water temperature variation at the surface compared to deeper layers. SMeTD can be used to observe a broad range of hydrological processes in natural and artificial aquatic environments and help to understand processes involved with energy budgets, infiltration, limnology, or groundwater surface water exchange.

The importance of pedogenesis in understanding soil distribution patterns in current and past geologic periods is well established, but field identification of pedogenic features is always a big challenge in pedostratigraphic units because of post burial alterations. An ~ 8 m landform presents a complete pedostratigraphic section at Chobe Enclave alluvial plain, northern Botswana. This study investigated pedological indices including morphological, physico-chemical, geochemical and mineralogical properties of the landform, with the aim of reconstructing the palaeoenvironments and palaeoclimate during the evolution of the landform. SiO2 is the dominant elemental oxide (40.6–98.9 wt%) followed by CaO (0.02–29.6 wt%), Fe2O3 (0.48–2.64 wt%), MgO (0.14–1.81 wt%) and Al2O3 (0.29–0.93 wt%). The clay-sized minerals present are quartz, calcite, sepiolite and kaolinite. The carbonates had strong positive correlation with Sr (R² = 0.935), while Fe2O3 had weak positive correlation with TiO2 (R² = 0.0187). Gradual obliteration of the sedimentary layers and the formation of indurated illuvial horizon indicate secondary recrystallisation of the palustrine carbonates. There is evidence of two cyclic intervals that produced specific two pedostratigraphic levels and two soil orders—Entisols and Calcisols, and therein pedofeatures and geochemical variations suggest long-term climate change, i.e. from wet to dry in the Chobe Enclave in the late Quaternary. This study has presented a new calibration of the Chobe Enclave landform to include pedogenic horizons instead of a sedimentary bed of palustrine carbonate deposit lying over fine sediments in a fluvial system, as previously documented.