bluuebunny/crossref_metadata_2025_split huggingface dataset:
Diversity, Equity und Inclusion Management – Umsetzung in der Praxis
Authors: Becker Martina , Gurtner Andrea 
Published: July 2024

ZusammenfassungEine inklusive Organisationskultur hat sich als wichtige Impulsgeberin für die Transformation von Unternehmen erwiesen und führt zu gesteigerter Innovation und Kreativität. Um eine solche zu schaffen, müssen Organisationen den vielfältigen Bedürfnissen ihrer Mitarbeitenden gerecht werden. Diversity, Equity und Inclusion Management (DEI-Management) ist ein strategischer Ansatz, der die Inklusion einer vielfältigen Belegschaft anstrebt. Während DEI-Management besonders in größeren Organisationen oft im strategischen Personalmanagement verankert ist, sind solche Ansätze seltener bei kleinen und mittleren Unternehmen (KMU) anzutreffen. Die vorliegende Studie untersucht die Implementierung von DEI-Konzepten in Unternehmen unterschiedlicher Größe. Basierend darauf wird ein sechsstufiger Prozess vorgestellt, der Organisationen bei der Implementierung eines DEI-Managements unterstützen kann.
Personalentwicklung in der hybriden Arbeitswelt
Authors: Breny-Müller Christa , Gurtner Andrea 
Published: July 2024

ZusammenfassungPersonalentwicklung mittels traditioneller, betrieblicher und schulischer Angebote muss vor dem Hintergrund der Transformation zu einer zunehmend hybriden Arbeitswelt auf den Prüfstand gestellt und gegebenenfalls angepasst werden. Dabei werden neue Kriterien für die Gestaltung der Personalentwicklung relevant. Führungskräfte sind gefordert neben der Vielfalt von Mitarbeitenden auch ergänzende Aspekte wie Transparenz, Coaching und verfügbare Zeitfenster zu berücksichtigen. In der hybriden Arbeitsweise verändern sich Weiterbildungsformen, kürzere und virtuelle Weiterbildungen gewinnen an Bedeutung. Die Personalentwicklung wird mit neuen Aspekten angereichert und bleibt aber eine gemeinsame Aufgabe von Führungskraft und Mitarbeiter:in.
Digitale Transformation = mehr Nachhaltigkeit in der Logistik?
Authors: Grunder Nils Lorenz , Pešková Marie , Gees Thomas 
Published: July 2024

ZusammenfassungIm Zuge der Corona-Pandemie wurde ersichtlich, dass das Konzept der „Green Logistics“ an Bedeutung gewinnen wird, weil im E-Commerce Just-in-time-Bestellungen anhaltend bedeutend sein werden. Die Forderung nach Nachhaltigkeit setzt die Wirtschaft generell aber speziell die Logistikbranche vor die Herausforderung, ressourceneffizient zu produzieren oder Dienstleistungen zu erbringen. Kann mit dem Einsatz von digitalen Technologien die erforderliche Ressourceneffizienz verbessert werden? Der Beitrag geht am Beispiel der Transport- und Lagerungslogistik dem Zusammenhang von digitaler Transformation und Nachhaltigkeit nach und zeigt mit einer empirischen Untersuchung in der Schweizer Logistik auf, wie man den Effekt messen kann. Erste Erhebungen weisen auf Branchenebene darauf hin, dass es einen positiven Effekt vom Einsatz digitaler Technologien auf die die ökologische und ökonomische Nachhaltigkeit gibt.
Higher order corrections to KPV: The nonabelian brane stack perspective
Authors: Schreyer Simon 
Published: July 2024

Abstract
In this work, we study the decay of $$ \overline{D3} $$

D
3

¯

-branes in the setup of Kachru, Pearson, and Verlinde (KPV) at higher order in α′ from the perspective of a nonabelian $$ \overline{D3} $$

D
3

¯

-brane stack. We extend the leading order analysis of KPV by including higher order commutators as well as higher derivative corrections. Recently, the KPV setup has been studied at higher order in α′ from the NS5-brane perspective. It was found that in order to control α′ corrections the quantity gsM2 determining the amount of warping in the Klebanov-Strassler throat has to be much larger than expected. This leads to serious issues when using the $$ \overline{D3} $$

D
3

¯

-branes as an uplift to dS. The benefit of the analysis in this work is that the $$ \overline{D3} $$

D
3

¯

-brane perspective is controlled when the distance between the branes inside the brane stack is substringy which is a regime not controlled on the NS5-brane side. As a main result, we find that the strong bound gsM2 ~ $$ \mathcal{O} $$
O
(100) obtained on the NS5-brane also holds in the regime accessible from the $$ \overline{D3} $$

D
3

¯

-brane perspective. We also show that the novel way of uplifting proposed in the recent work on α′ corrections to the KPV setup can only work for small warped throats.
Traditional radiography versus computed tomography to assess reduced distal radius fractures
Authors: Dankelman Lente H. M. , Barvelink Britt , Verhofstad Michael H. J. , Wijffels Mathieu M. E. , Colaris Joost W. 
Published: July 2024

Abstract
Introduction
This study compares computed tomography (CT) with plain radiography in its ability to assess distal radius fracture (DRF) malalignment after closed reduction and cast immobilization.

Methods
Malalignment is defined as radiographic fracture alignment beyond threshold values according to the Dutch guideline encompassing angulation, inclination, positive ulnar variance and intra-articular step-off or gap. After identifying 96 patients with correct alignment on initial post-reduction radiographs, we re-assessed alignment on post-reduction CT scans.

Results
Significant discrepancies were found between radiographs and CT scans in all measurement parameters. Notably, intra-articular step-off and gap variations on CT scans led to the reclassification of the majority of cases from correct alignment to malalignment. CT scans showed malalignment in 53% of cases, of which 73% underwent surgery.

Conclusion
When there is doubt about post-reduction alignment based on radiograph imaging, additional CT scanning often reveals malalignment, primarily due to intra-articular incongruency.
Continual learning approaches to hand–eye calibration in robots
Authors: Bahadir Ozan , Siebert Jan Paul , Aragon-Camarasa Gerardo 
Published: July 2024

AbstractThis study addresses the problem of hand–eye calibration in robotic systems by developing Continual Learning (CL)-based approaches. Traditionally, robots require explicit models to transfer knowledge from camera observations to their hands or base. However, this poses limitations, as the hand–eye calibration parameters are typically valid only for the current camera configuration. We, therefore, propose a flexible and autonomous hand–eye calibration system that can adapt to changes in camera pose over time. Three CL-based approaches are introduced: the naive CL approach, the reservoir rehearsal approach, and the hybrid approach combining reservoir sampling with new data evaluation. The naive CL approach suffers from catastrophic forgetting, while the reservoir rehearsal approach mitigates this issue by sampling uniformly from past data. The hybrid approach further enhances performance by incorporating reservoir sampling and assessing new data for novelty. Experiments conducted in simulated and real-world environments demonstrate that the CL-based approaches, except for the naive approach, achieve competitive performance compared to traditional batch learning-based methods. This suggests that treating hand–eye calibration as a time sequence problem enables the extension of the learned space without complete retraining. The adaptability of the CL-based approaches facilitates accommodating changes in camera pose, leading to an improved hand–eye calibration system.
Mitigating implicit and explicit bias in structured data without sacrificing accuracy in pattern classification
Authors: Hoitsma Fabian , Nápoles Gonzalo , Güven Çiçek , Salgueiro Yamisleydi 
Published: July 2024

AbstractUsing biased data to train Artificial Intelligence (AI) algorithms will lead to biased decisions, discriminating against certain groups or individuals. Bias can be explicit (one or several protected features directly influence the decisions) or implicit (one or several protected features indirectly influence the decisions). Unsurprisingly, biased patterns are difficult to detect and mitigate. This paper investigates the extent to which explicit and implicit against one or more protected features in structured classification data sets can be mitigated simultaneously while retaining the data’s discriminatory power. The main contribution of this paper concerns an optimization-based bias mitigation method that reweights the training instances. The algorithm operates with numerical and nominal data and can mitigate implicit and explicit bias against several protected features simultaneously. The trade-off between bias mitigation and accuracy loss can be controlled using parameters in the objective function. The numerical simulations using real-world data sets show a reduction of up to 77% of implicit bias and a complete removal of explicit bias against protected features at no cost of accuracy of a wrapper classifier trained on the data. Overall, the proposed method outperforms the state-of-the-art bias mitigation methods for the selected data sets.
Efficacy of cannabis-based medicine in the treatment of Tourette syndrome: a systematic review and meta-analysis
Authors: Serag Ibrahim , Elsakka Mona Mahmoud , Moawad Mostafa Hossam El din , Ali Hossam Tharwat , Sarhan Khalid , Shayeb Sally , Nadim Islam , Abouzid Mohamed 
Published: July 2024

Abstract
Background
Tourette syndrome (TS) is a neurodevelopmental disorder characterized by motor and phonic tics. It is a condition that affects between 0.3% and 0.7% of children, and its pathophysiology remains largely elusive. TS is associated with structural and functional alterations in corticostriatal circuits and neurochemical imbalances. Even though TS is currently incurable, there are established treatment options available, including behavioral therapy and neuroleptics. The use of cannabis-based medicine for tic management is an emerging therapeutic strategy, although its efficacy is still under investigation. It is hypothesized to interact with the endogenous cannabinoid system, but further research is required to ascertain its safety and effectiveness in TS.

Aim
In our systematic review and meta-analysis, we aim to assess the effectiveness of cannabis-based medicine in the treatment of TS.

Methods
We searched PubMed, Cochrane, Scopus, and Web of Sciences until February 2024. We included clinical trials and cohort studies investigating the efficacy of cannabis-based medicine in the treatment of TS. Data extraction focused on baseline characteristics of the included studies and efficacy outcomes, including scores on the Yale Global Tic Severity Scale (YGTSS), Premonitory Urge for Tics Scale (PUTS), and Yale-Brown Obsessive Compulsive Scale (Y-BOCS). We conducted the meta-analysis using Review Manager version 5.4. software. We compared the measurements before and after drug intake using mean difference (MD) and 95% confidence interval (CI).

Results
In total, 357 articles were identified for screening, with nine studies included in the systematic review and 3 in the meta-analysis. These studies involved 401 adult patients with TS treated with cannabis. YGTSS revealed a significant reduction in total scores (MD = -23.71, 95% CI [-43.86 to -3.55], P = 0.02), PUTS revealed a significant decrease in scores (MD = -5.36, 95% CI [-8.46 to -2.27], P = 0.0007), and Y-BOCS revealed no significant difference in score reduction (MD = -6.22, 95% CI [-12.68 to 0.23], P = 0.06).

Conclusion
The current study indicates promising and potentially effective outcomes with the use of cannabis-based medicine in mitigating the severity of tics and premonitory urges. However, there is a need for larger, placebo-controlled studies with more representative samples to validate these findings.
Deep learning in pulmonary nodule detection and segmentation: a systematic review
Authors: Gao Chuan , Wu Linyu , Wu Wei , Huang Yichao , Wang Xinyue , Sun Zhichao , Xu Maosheng , Gao Chen 
Published: July 2024

Abstract
Objectives
The accurate detection and precise segmentation of lung nodules on computed tomography are key prerequisites for early diagnosis and appropriate treatment of lung cancer. This study was designed to compare detection and segmentation methods for pulmonary nodules using deep-learning techniques to fill methodological gaps and biases in the existing literature.

Methods
This study utilized a systematic review with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, searching PubMed, Embase, Web of Science Core Collection, and the Cochrane Library databases up to May 10, 2023. The Quality Assessment of Diagnostic Accuracy Studies 2 criteria was used to assess the risk of bias and was adjusted with the Checklist for Artificial Intelligence in Medical Imaging. The study analyzed and extracted model performance, data sources, and task-focus information.

Results
After screening, we included nine studies meeting our inclusion criteria. These studies were published between 2019 and 2023 and predominantly used public datasets, with the Lung Image Database Consortium Image Collection and Image Database Resource Initiative and Lung Nodule Analysis 2016 being the most common. The studies focused on detection, segmentation, and other tasks, primarily utilizing Convolutional Neural Networks for model development. Performance evaluation covered multiple metrics, including sensitivity and the Dice coefficient.

Conclusions
This study highlights the potential power of deep learning in lung nodule detection and segmentation. It underscores the importance of standardized data processing, code and data sharing, the value of external test datasets, and the need to balance model complexity and efficiency in future research.

Clinical relevance statement
Deep learning demonstrates significant promise in autonomously detecting and segmenting pulmonary nodules. Future research should address methodological shortcomings and variability to enhance its clinical utility.

Key Points

Deep learning shows potential in the detection and segmentation of pulmonary nodules.

There are methodological gaps and biases present in the existing literature.

Factors such as external validation and transparency affect the clinical application.
External validation of the barcelona magnetic resonance imaging predictive model for detecting significant prostate cancer including men receiving 5-alpha reductase inhibitors
Authors: Morote Juan , Borque-Fernando Ángel , Esteban Luis M. , Picola Natàlia , Muñoz-Rodriguez Jesús , Paesano Nahuel , Ruiz-Plazas Xavier , Muñoz-Rivero Marta V. , Celma Ana , Manuel Gemma García-de , Miró Berta , Abascal José M. , Servian Pol 
Published: July 2024

Abstract
Purpose
To validate the Barcelona-magnetic resonance imaging predictive model (BCN-MRI PM) for clinically significant prostate cancer (csPCa) in Catalonia, a Spanish region with 7.9 million inhabitants. Additionally, the BCN-MRI PM is validated in men receiving 5-alpha reductase inhibitors (5-ARI).

Materials and methods
A population of 2,212 men with prostate-specific antigen serum level > 3.0 ng/ml and/or a suspicious digital rectal examination who underwent multiparametric MRI and targeted and/or systematic biopsies in the year 2022, at ten participant centers of the Catalonian csPCa early detection program, were selected. 120 individuals (5.7%) were identified as receiving 5-ARI treatment for longer than a year. The risk of csPCa was retrospectively assessed with the Barcelona-risk calculator 2 (BCN-RC 2). Men undergoing 5-ARI treatment for less than a year were excluded. CsPCa was defined when the grade group was ≥ 2.

Results
The area under the curve of the BCN-MRI PM in 5-ARI naïve men was 0.824 (95% CI 0.783–0.842) and 0.849 (0.806–0.916) in those receiving 5-ARI treatment, p 0.475. Specificities at 100, 97.5, and 95% sensitivity thresholds were to 2.7, 29.3, and 39% in 5-ARI naïve men, while 43.5, 46.4, and 47.8%, respectively in 5-ARI users. The application of BCN-MRI PM would result in a reduction of 23.8% of prostate biopsies missing 5% of csPCa in 5-ARI naïve men, while reducing 25% of prostate biopsies without missing csPCa in 5-ARI users.

Conclusions
The BCN-MRI PM has achieved successful validation in Catalonia and, notably, for the first time, in men undergoing 5-ARI treatment.
Contraceptive counselling and uptake of contraception among women with cardiovascular diseases: a systematic review and meta-analysis
Authors: Feyissa Tesfaye Regassa , Akter Shahinoor , Harris Melissa L. 
Published: July 2024

AbstractTo address the lack of clarity regarding contraceptive counselling and uptake of contraception among women with cardiovascular disease (CVD), this study aimed to conduct a systematic review and meta-analysis on contraceptive counselling and the subsequent uptake of contraception among women with CVD. A search across six databases identified 1228 articles, with 11 studies (2580 participants) included. The pooled prevalence of contraceptive counselling was 63%, varying from 36 to 94% in individual studies. Inconsistent delivery and documentation of counselling were noted, along with a lack of knowledge about pregnancy complications and misconceptions regarding CVD severity. For contraceptive uptake (n = 5), the pooled prevalence was 64% (95% confidence interval, 45 to 82%). Women with CVD were also found to use less effective methods as well as methods not recommended for their condition (e.g., combined hormonal methods among participants with absolute or relative contraindications). Improving contraceptive counselling and choices for women with CVD can not only enhance knowledge and decision-making for women with CVD in line with their reproductive goals and preferences but reduce high-risk unintended pregnancies and adverse pregnancy outcomes.
Graphical Abstract
A morphoscopic exploration of cranial sexual dimorphism among modern South Africans using computed tomography scans
Authors: Krüger Gabriele Christa , Jantz Richard L. , van der Walt Elizabeth , Lockhat Zarina I. , L’Abbé Ericka N. 
Published: July 2024

AbstractContinual re-evaluation of standards for forensic anthropological analyses are necessary, particularly as new methods are explored or as populations change. Indian South Africans are not a new addition to the South African population; however, a paucity of skeletal material is available for analysis from medical school collections, which has resulted in a lack of information on the sexual dimorphism in the crania. For comparable data, computed tomography scans of modern Black, Coloured and White South Africans were included in addition to Indian South Africans. Four cranial morphoscopic traits, were assessed on 408 modern South Africans (equal sex and population distribution). Frequencies, Chi-squared tests, binary logistic regression and random forest modelling were used to assess the data. Males were more robust than females for all populations, while White South African males were the most robust, and Black South African females were the most gracile. Population differences were noted among most groups for at least two variables, necessitating the creation of populations-specific binary logistic regression equations. Only White and Coloured South Africans were not significantly different. Indian South Africans obtained the highest correct classifications for binary logistic regression (94.1%) and random forest modelling (95.7%) and Coloured South Africans had the lowest correct classifications (88.8% and 88.0%, respectively). This study provides a description of the patterns of sexual dimorphism in four cranial morphoscopic traits in the current South African population, as well as binary logistic regression functions for sex estimation of Black, Coloured, Indian and White South Africans.
Influence of sustained mild dehydration on thermoregulatory and cognitive functions during prolonged moderate exercise
Authors: Watanabe Hironori , Kadokura Yuma , Sugi Taisuke , Saito Kiyoshi , Nagashima Kei 
Published: July 2024

Abstract
Purpose
The current study investigated whether sustained mild dehydration affects thermoregulatory function and cognitive performance during prolonged exercise.

Methods
Twelve young adults performed a test consisting of three sets of 20-min exercise with 2-min intervals under euhydrated (control, CON) and mildly dehydrated conditions (MDEH) at an ambient temperature of 30 °C and 60% relative humidity. MDEH was established by restricting water intake for 24 h, resulting in urine specific gravity of ≥ 1.020. Heart rate (HR), mean arterial blood pressure (MAP), skin blood flow (SkBF), sweat rate (SR) on the chest and forearm, and ear canal and mean skin surface temperatures (Tear and mean Tskin, respectively) were continuously recorded. For each exercise set, thermal and humid sensations and thermal discomfort were assessed using visual analog scales (VAS), and the rating of perceived exertion (RPE) was estimated. Cognitive performance on the Go/No-Go (easy) and incongruent Stroop (difficult) tasks was assessed before and after the test.

Results
No differences were observed in HR, MAP, SkBF, SR, Tear, and mean Tskin between the CON and MDEH. Thermal and humidity sensations, thermal discomfort, and RPE were higher in MDEH than in CON. Moreover, response time to the Stroop task was prolonged in MDEH.

Conclusion
These findings suggest that sustained mild dehydration does not affect autonomic thermoregulation during exercise. Augmented thermal perception and perceived exertion, which are necessary for behavioral thermoregulation, were noted; however, cognitive function may be attenuated under MDEH.