bluuebunny/crossref_metadata_2025_split huggingface dataset:
Familien-Schul-Kooperation zu Beginn der Sekundarstufe I: zum Aufgabenverständnis von Müttern und zur Bedeutung ihrer Passungswahrnehmung
Authors: Ulrich Manuela , Hachfeld Axinja 
Published: March 2024

ZusammenfassungEltern und Lehrpersonen sind gemeinsam für die Schulbildung von Kindern und Jugendlichen verantwortlich. Dabei gilt es, Aufgaben und Erwartungen klar abzusprechen und regelmäßig aufeinander abzustimmen. Angesichts gesellschafts- und bildungssystemischer Veränderungen untersucht die qualitative Studie das Aufgabenverständnis von Müttern, ihre Handlungsgründe sowie ihre Selbst- und Passungswahrnehmung in der schulischen Kooperation zu Beginn der Sekundarstufe I. Die Daten basieren auf fünf halbstandardisierten Fokusgruppeninterviews (N = 25) in Baden-Württemberg. Die Analysen nach der Grounded Theory zeigen, dass die Mütter in den fünf Gruppen ein allgemeines Verständnis teilen, welche konkreten Aufgaben die Familie und/oder die Lehrpersonen übernehmen müssen, um die kindliche Schulbildung zu unterstützen. Auch sind sich die Mütter einig, aufgrund von schulischen Strukturmängeln die individuelle Förderung übernehmen zu müssen. Neben strukturellen Kontextmerkmalen begründen ihre Rollenüberzeugung, Norm- und Zielorientierungen, Aufforderungen der Lehrpersonen, der Unterstützungsbedarf des Kindes, Routinen sowie frühere Erfahrungen der Mütter ihre Handlungsentscheidungen. Wechselbeziehungen zwischen mütterlicher Selbst- und Passungswahrnehmung verweisen auf die Schlüsselrolle der Lehrpersonen im Umgang mit der eigenen Belastungswahrnehmung als Mutter.
Primary closure versus vertical rectus abdominis myocutaneous (VRAM) flap closure of perineal wound following abdominoperineal resection—a systematic review and meta-analysis
Authors: Temperley Hugo C. , Shokuhi Poorya , O’Sullivan Niall J. , Mac Curtain Benjamin , Waters Caitlin , Murray Alannah , Buckley Christina E. , O’Neill Maeve , Mehigan Brian , McCormick Paul H. , Kelly Michael E. , Larkin John O. 
Published: March 2024

Abstract
Purpose/aim
Perianal wound healing and/or complications are common following abdominoperineal resection (APR). Although primary closure is commonly undertaken, myocutaneous flap closure such as vertical rectus abdominis myocutaneous flap (VRAM) is thought to improve wound healing process and outcome. A comprehensive meta-analysis was performed to compare outcomes of primary closure versus VRAM flap closure of perineal wound following APR.

Methods
PubMed, MEDLINE, EMBASE, and Cochrane Central Registry of Controlled Trials were comprehensively searched until the 8th of August 2023. Included studies underwent meta-analysis to compare outcomes of primary closure versus VRAM flap closure of perineal wound following APR. The primary outcome of interest was perineal wound complications, and the secondary outcomes were abdominal wound complications, dehiscence, wound healing time, length of hospital stay, and mortality.

Results
Ten studies with 1141 patients were included. Overall, 853 patients underwent primary closure (74.8%) and 288 patients underwent VRAM (25.2%). Eight studies reported on perineal wound complications after APR: 38.2% (n = 263/688) in the primary closure group versus 32.8% (n = 80/244) in the VRAM group. Perineal complication rates were statistically significantly lower in the VRAM group versus primary closure ((M-H OR, 1.61; 95% CI 1.04–2.49; <p = 0.03).

Conclusion
We highlight the advantage of VRAM flap closure over primary closure for perineal wounds following APR. However, tailoring operative strategy based on patient and disease factors remains important in optimising outcomes.
The Usage of Voice in Sexualized Interactions with Technologies and Sexual Health Communication: An Overview
Authors: Szczuka Jessica M. , Mühl Lisa 
Published: March 2024

Abstract
Purpose of Review
The present overview addresses the importance of voice in human-technology interactions within the sexual realm. It introduces empirical evidence within two key domains: (a) sexualized interactions involving artificial entities and (b) communication about sexuality-related health. Moreover, the review underscores existing research gaps.

Recent Findings
Theories and first empirical studies underline the importance of voice within sexualized interactions with voice assistants or conversational agents as social cues. However, research on voice usage in sexual health-related contexts reveals contradicting results, mainly because these technologies ask users to vocalize potentially sensitive topics.

Summary
Although the utilization of voice in technology is steadily advancing, the question of whether voice serves as the optimal medium for social interactions involving sexually related artificial entities and sexual health-related communication remains unanswered. This uncertainty stems from the fact that certain information must be conveyed verbally, which could also be communicated through alternative means, such as text-based interactions.
Organised crime movement across local communities: A network approach
Authors: Campana Paolo , Meneghini Cecilia 
Published: March 2024

AbstractThis paper explores the structure of organised crime movement across local communities and the drivers underpinning such movement. Firstly, it builds on network analysis to offer a novel methodological approach to empirically and quantitatively study the movement of organised crime offenders across geographical areas. The paper then applies this approach to evidence from Cambridgeshire in the United Kingdom. It reconstructs the movement of organised crime members across local areas based on a large-scale police dataset that includes 41 months of recorded crime events. It identifies organised crime “turf” and “target” areas and then explores the drivers of movement from the former to the latter using Exponential Random Graph Models. Findings confirm that geographical distance matters; however, socio-demographic, urban, economic and crime-related characteristics of communities play a key role. Organised crime group members target urban communities with higher than average illegal market opportunities (proxied by drug-related activity). The work also finds the effect of socio-demographic homophily between turf and target communities, suggesting that organised crime group members might target territories that are similar to their own. While a high level of deprivation makes a community more likely to send organised crime members, its impact on a community’s probability of being a receiver is less clear. Finally, the paper offers a way to identify communities (local areas) at risk of being targeted by criminal organisations, thus providing practitioners with a tool for early interventions.
Case report. Birt-Hogg-Dubé – wat moet de uroloog ermee?
Authors: Helgers Rianne J. A. , Waltman Ghislaine C. , Goudkade Danny , Gómez García Encarna B. , de Vries Michiel , Jacobs Rens A. L. , Delaere Filip J. M. 
Published: March 2024

SamenvattingHet Birt-Hogg-Dubé-syndroom is een zeldzame autosomaal dominante erfelijke aandoening, die wordt veroorzaakt door een mutatie in het folliculine (FLCN)-gen, gekenmerkt door fibrofolliculomen, en een verhoogde kans op niertumoren, longcysten en een spontane pneumothorax. Genetische counseling voor een mutatie op het FLCN-gen is aangewezen indien er aan bepaalde criteria wordt voldaan. Familieleden komen vanaf 20-jarige leeftijd in aanmerking voor genetisch onderzoek. Bij deze patiënten staat preventie van een pneumothorax centraal door niet te gaan diepzeeduiken en roken. Beeldvorming van de nieren is aangewezen vanwege de verhoogde kans op een niercelcarcinoom. Bij de eerste presentatie dient een MRI-scan gemaakt te worden. Nadien is jaarlijkse opvolging met echografie voldoende. Mocht een niertumor moeten worden geopereerd, dan gebeurt dit bij voorkeur niersparend vanwege de verhoogde kans op een (contralateraal) recidief.
Robotic welding system for adaptive process control in gas metal arc welding
Authors: Biber A. , Sharma R. , Reisgen U. 
Published: March 2024

AbstractChanging process conditions such as distortion, varying seam preparation or gap width during welding is a major challenge in automated gas metal arc welding (GMAW). While human welders can adjust the process during welding (e.g. welding speed, torch orientation), an automated welding system needs sensors to detect and actuators to adjust the process. Adjusting the process in response to changing process conditions is usually referred to as adaptive welding. The aim of this work is to build a robotic welding system capable of automatically adapting the welding process using some of the approaches of a human welder. To enable adaptive process control, a robotic welding system is built. It consists of four main components: a six-axis industrial robot for mechanical guidance of the welding torch, a welding power source, a monochrome visual camera as an image sensor and a process controller that combines the three components. The camera captures images of the weld pool during welding and processes the images to provide geometrical information such as the width of the weld pool and the position of the weld pool front. Changes in the weld pool geometry are quantified, and an adjustment strategy is generated in the process control unit in real time. Process adjustments can be mechanical (e.g. welding speed, torch orientation) and electrical by adjusting synergic process settings (wire feed speed, arc length, process dynamics). Validation tests demonstrate the functionality of the welding system. Two use cases were investigated. Firstly, a deposited weld bead was examined, and variations in the width of the weld pool were induced by varying the welding speed. The second application was a seam tracking application. The path is pre-programmed, and the specimen is positioned with an offset to the path. Compensation for the offset is implemented.
Multi-level and Metrics Evaluation Approach for Data-Driven Based Sensor Models
Authors: Li Hexuan , Bamminger Nadine , Wan Li , Eichberger Arno 
Published: March 2024

AbstractNowadays, with increased sensor perception performance for Advanced Driver Assistance Systems (ADAS), scenario-based simulation is becoming more frequent to manage the complexity of reality in terms of cost and time. The perception system provides the basis for the vehicle guidance algorithms calculation, but the simulation of ADAS sensors is a challenging task in virtual testing. Literature reports the magnitude of relevant modelling approaches and data-driven models becoming increasingly important. A basic method is to fit the sensor output in the virtual environment with high-fidelity measurements of real-world scenarios, thus a direct relation can be established between real and synthetic sensor data. To prove the suitability of a method, it is necessary to quantify the gap between simulation and reality to determine the performance of different models. In this work, authors address this problem and visualize the gap by introducing a multi-level evaluation approach that combines Model Generalization Ability Evaluation and Case Implicit Performance Evaluation. The former directly evaluates the model’s overall performance, while the latter is used for specific cases in simulation. The study shows that this combined evaluation approach provides an in-depth framework for evaluating sensor models to make the differences apparent.
Thermal degradation of emerging pollutants in municipal solid wastes and agro wastes: effectiveness of catalysts and pretreatment for the conversion of value added products
Authors: Chandrasekran Geetha , Ahalya N. , Pamila R. , Madhu P. , Vidhya L. , Vinodha S. , Pratiwi Arby’in , Bain Ali , Lalvani J. Isaac JoshuaRamesh 
Published: March 2024

AbstractIn this study, emerging soil pollutants in the form of municipal solid waste (MSW) and agricultural waste were converted into biofuel via thermal degradation process. Among various waste-to-energy conversion processes, the pyrolysis of biomass is considered the most significant due to its maximum biofuel yield than other conversion techniques. Individual and co-pyrolysis of MSW and sugarcane residue (SR) as well as its treated variant (TSR) were performed in a lab-setup fixed-bed reactor with and without catalyst. The effect of acid pretreatment and catalytic effects on the pyrolysis process was assessed in terms of product yields and characterization. The acidic pretreatment of SR and catalyst in the pyrolysis process alters the process yield and its composition. The maximum oil yield of 50.5 wt% was achieved by catalytic co-pyrolysis of MSW + TSR + HZSM5, whereas the maximum gas yield of 38.1 wt% was achieved by catalytic co-pyrolysis of MSW + SR + HZSM5. This suggests that intrinsic minerals present in the biomass and MSW, particularly alkali and alkaline earth metals, have a catalytic effect on the devolatilization of organic material and the char cracking event. The pretreatment of biomass showed considerable improvement in the properties of the produced pyrolysis oil and char. Compared to the pyrolysis oil and char obtained from MSW + SR, the oil and char obtained from MSW + TSR + HZSM5 showed a small increment in their heating values. Pretreatment and the catalytic co-pyrolysis process influenced the structure of the pyrolysis oils, increasing the production of phenolic compounds and aromatic hydrocarbons. The amount of gas components in pyrolysis gas, such as CH4, CO2, and CO also changed more according to the feedstock used for the process. Overall, the HZSM-5 catalyst and co-pyrolysis of MSW with pretreated SR enhanced the pyrolysis conversion of waste municipal solids and agricultural wastes into energy-rich products.
Analysis of decarbonization path in New York state and forecasting carbon emissions using different machine learning algorithms
Authors: Ekaterina Glukhova , Li Jia 
Published: March 2024

AbstractThe state of New York admitted 143 million metric tons of carbon emissions from fossil fuels in 2020, prompting the ambitious goal set by the CLCPA to achieve carbon neutrality. The paper focused on analyzing and predicting carbon emissions using four different machine-learning algorithms. It examined emissions from fossil fuel combustion from 1990 to 2020 and validated four different algorithms to choose the most effective one for predicting emissions from 2020 to 2050. The analysis covered various economic sectors including transportation, residential, commercial, industrial, and electric power. By analyzing policies, the paper forecasted emissions for 2030 and 2050, leading to the identification of different pathways to reach carbon neutrality. The research concluded that in order to achieve neutrality, radical measures must be taken by the state of New York. Additionally, the paper compared the most recent data for 2021 with the forecasts, showing that significant measures need to be implemented to achieve the goal of carbon neutrality. Despite some studies assuming a trend of decreased emissions, the research revealed different results. The paper presents three pathways, two of which follow the ambitious plan to reach carbon neutrality. As a result, the emission amount by 2050 for the different pathways was projected to be 31.1, 22.4, and 111.95 of MMt CO2 e, showcasing the need for urgent action to combat climate change.
Impact of metagenomic next-generation sequencing on clinical decision-making at an academic medical center, a retrospective study, Iowa, 2020–2022
Authors: Olthoff Michael , Kobayashi Takaaki , Parsons Meredith G. , Ford Bradley , Prasidthrathsint Kunatum , Non Lemuel , Salinas Jorge L. , Diekema Daniel J. , Ince Dilek 
Published: March 2024

Abstract
We assessed the impact of metagenomic next-generation sequencing (mNGS) on patient care using previously established criteria. Among 37 patients receiving mNGS testing, 16% showed results that had a positive clinical impact. While mNGS results may offer valuable supplementary information, results should be interpreted within the broader clinical context and evaluation.
Large eddy simulation of flow over a circular cylinder with a neural-network-based subgrid-scale model
Authors: Kim Myunghwa , Park Jonghwan , Choi Haecheon 
Published: March 2024

A neural-network-based large eddy simulation is performed for flow over a circular cylinder. To predict the subgrid-scale (SGS) stresses, we train two fully connected neural network (FCNN) architectures with and without fusing information from two separate single-frame networks (FU and nFU, respectively), where the input variable is either the strain rate (SR) or the velocity gradient (VG). As the input variables, only the grid-filtered variables are considered for the SGS models of G-SR and G-VG, and both the grid- and test-filtered variables are considered for the SGS models of T-SR and T-VG. The training data are the filtered direct numerical simulation (fDNS) data at

$Re_d=3900$

based on the free-stream velocity and cylinder diameter. Using the same grid resolution as that of the training data, the performances of G-SR and G-VG (grid-filtered inputs) and T-SR-FU and T-VG-FU (grid- and test-filtered inputs with fusion) are better than those of the dynamic Smagorinsky model and T-SR-nFU and T-VG-nFU (grid- and test-filtered inputs without fusion). These FCNN-based SGS models are applied to untrained flows having different grid resolutions from that of training data. Although the performances of G-SR and G-VG are degraded, T-SR-FU and T-VG-FU still provide good performances. Finally, T-SR-FU and T-VG-FU trained at

$Re_d = 3900$

are applied to higher-Reynolds-number flows (

$Re_d = 5000$

and 10 000) and their results are also in good agreements with those of fDNS and previous experiment, indicating that adding the test-filtered variables and fusion increases the prediction capability even for untrained Reynolds number flows.
Constrained optimal stopping under a regime-switching model
Authors: Arai Takuji , Takenaka Masahiko 
Published: March 2024

AbstractWe investigate an optimal stopping problem for the expected value of a discounted payoff on a regime-switching geometric Brownian motion under two constraints on the possible stopping times: only at exogenous random times, and only during a specific regime. The main objectives are to show that an optimal stopping time exists as a threshold type and to derive expressions for the value functions and the optimal threshold. To this end, we solve the corresponding variational inequality and show that its solution coincides with the value functions. Some numerical results are also introduced. Furthermore, we investigate some asymptotic behaviors.
Legal entrepreneurship and the evolution of multidimensional advocacy in social movements: the case of marriage equality
Authors: Bailey Christine M. , Collins Paul M. , Rhodes Jesse H. , Rice Douglas 
Published: March 2024

AbstractThe emergence and dissemination of new legal ideas can play an important role in sparking change in the way activists in marginalized communities understand their rights and pursue their objectives. How and why do the legal beliefs of such communities evolve? We argue that the vigorous advocacy of new legal ideas by entrepreneurs and the harnessing of specialized media to help disseminate those ideas are important mechanisms in this evolution. We use the rise of marriage equality as a central legal priority in the mainstream American LGBTQ+ rights movement as a case study to illustrate this phenomenon. Using a mixed-methods analysis of Evan Wolfson’s legal advocacy and an examination of The Advocate, we investigate how Wolfson developed and disseminated legal ideas about same-sex marriage. We show how this advocacy eventually dominated discussion of the issue among elite LGBTQ+ legal actors and the nation’s largest LGBTQ+ publication. However, Wolfson’s advocacy tended to emphasize LGBTQ+ integration into “mainstream” American culture and prioritized the interests and values of relatively privileged subgroups within the LGBTQ+ community. Our research informs our understanding of the interplay between legal advocacy and media reporting in the development of LGBTQ+ rights claims and the strategies adopted to achieve them.
Triangulation, incommensurability, and conditionalization
Authors: Liron Amir , Nissan-Rozen Ittay 
Published: March 2024

AbstractWe present a new justification for methodological triangulation (MT), the practice of using different methods to support the same scientific claim. Unlike existing accounts, our account captures cases in which the different methods in question are associated with, and rely on, incommensurable theories. Using a nonstandard Bayesian model, we show that even in such cases, a commitment to the minimal form of epistemic conservatism, captured by the rigidity condition that stands at the basis of Jeffrey’s conditionalization, supports the practice of MT.
Adaptive-to-maladaptive gradient of emotion regulation tendencies are embedded in the functional–structural hybrid connectome
Authors: Kim Wonyoung , Kim M. Justin 
Published: March 2024

AbstractBackgroundEmotion regulation tendencies are well-known transdiagnostic markers of psychopathology, but their neurobiological foundations have mostly been examined within the theoretical framework of cortical–subcortical interactions.MethodsWe explored the connectome-wide neural correlates of emotion regulation tendencies using functional and diffusion magnetic resonance images of healthy young adults (N = 99; age 20–30; 28 females). We first tested the importance of considering both the functional and structural connectome through intersubject representational similarity analyses. Then, we employed a canonical correlation analysis between the functional–structural hybrid connectome and 23 emotion regulation strategies. Lastly, we sought to externally validate the results on a transdiagnostic adolescent sample (N = 93; age 11–19; 34 females).ResultsFirst, interindividual similarity of emotion regulation profiles was significantly correlated with interindividual similarity of the functional–structural hybrid connectome, more so than either the functional or structural connectome. Canonical correlation analysis revealed that an adaptive-to-maladaptive gradient of emotion regulation tendencies mapped onto a specific configuration of covariance within the functional–structural hybrid connectome, which primarily involved functional connections in the motor network and the visual networks as well as structural connections in the default mode network and the subcortical–cerebellar network. In the transdiagnostic adolescent dataset, stronger functional signatures of the found network were associated with higher general positive affect through more frequent use of adaptive coping strategies.ConclusionsTaken together, our study illustrates a gradient of emotion regulation tendencies that is best captured when simultaneously considering the functional and structural connections across the whole brain.