bluuebunny/crossref_metadata_2025_split huggingface dataset:
Healthcare for sex workers—access, barriers, and needs
Authors: Faissner Mirjam , Beckmann Laura , Freistein Katja , Jungilligens Johannes , Braun Esther 
Published: May 2024

Abstract
Background
Stigma has a significant impact on the health of different societal groups and contributes to inequalities in healthcare. Sex work is associated with significant social stigma, which has detrimental effects on sex workers’ access to healthcare. This exploratory study gives first insights into the perspectives of sex workers and counselors in Germany on sex workers’ access, needs, and barriers with respect to healthcare. We focused on an established network of services for sex workers in Bochum.

Methods
We conducted in-depth guideline-based interviews with four counselors at centers that provide social and medical support for sex workers and three sex workers who use these services. Interviews were analyzed using qualitative content analysis.

Results
The main barriers reported with respect to sex workers’ access to healthcare were health insurance, language barriers, bureaucracy, mobility, and discrimination. Sex work stigma within healthcare was reported to intersect with other forms of discrimination, such as racism. Specific needs and barriers were reported regarding mental health, which emerged as an important topic for sex workers. Free and anonymous healthcare offers were evaluated positively. Interviewees noted a lack of services that address the needs of sex workers beyond sexually transmitted infections, such as mental healthcare.

Conclusion
Several barriers to accessing healthcare remain for sex workers, many of which are particularly relevant for migrant sex workers from Eastern European countries. The development of additional antidiscriminatory healthcare services is necessary and should give priority to sex workers’ perspectives.
An adaptive fractional controller design for automatic voltage regulator system: sigmoid-based fractional-order PID controller
Authors: Sahin Ali Kivanc , Cavdar Bora , Ayas Mustafa Sinasi 
Published: May 2024

AbstractThe primary objective of a power system is to provide safe and reliable electrical energy to consumers. This objective is achieved by maintaining the stability of the power system, a multifaceted concept that can be divided into three distinct classes. The focus of this study is on one of these classes, voltage stability. A critical component in maintaining voltage stability is the automatic voltage regulator (AVR) system of synchronous generators. In this paper, a novel control method, the sigmoid-based fractional-order PID (SFOPID), is introduced with the aim of improving the dynamic response and the robustness of the AVR system. The dandelion optimizer (DO), a successful optimization algorithm, is used to optimize the parameters of the proposed SFOPID control strategy. The optimization process for the DO-SFOPID control strategy includes a variety of objective functions, including error-based metrics such as integral of absolute error, integral of squared error, integral of time absolute error, and integral of time squared error, in addition to the user-defined Zwee Lee Gaing’s metric. The effectiveness of the DO-SFOPID control technique on the AVR system has been rigorously investigated through a series of tests and analyses, including aspects such as time domain, robustness, frequency domain, and evaluation of nonlinearity effects. The simulation results are compared between the proposed DO-SFOPID control technique and the fractional-order PID (FOPID) and sigmoid-based PID (SPID) control techniques, both of which have been tuned using different metaheuristic algorithms that have gained significant recognition in recent years. As a result of these comparative analyses, the superiority of the DO-SFOPID control technique is confirmed as it shows an improved performance with respect to the other control techniques. Furthermore, the performance of the proposed DO-SFOPID control technique is validated within an experimental setup for the AVR system. The simulation results show that the proposed DO-SFOPID control technique is highly successful in terms of stability and robustness. In summary, this study provides comprehensive evidence supporting the effectiveness and superiority of the DO-SFOPID control technique on the AVR system through both simulation and experimental results.
Machine learning-based prediction of length of stay (LoS) in the neonatal intensive care unit using ensemble methods
Authors: Erdogan Yildirim Ayse , Canayaz Murat 
Published: May 2024

AbstractNeonatal medical data holds critical information within the healthcare industry, and it is important to analyze this data effectively. Machine learning algorithms offer powerful tools for extracting meaningful insights from the medical data of neonates and improving treatment processes. Knowing the length of hospital stay in advance is very important for managing hospital resources, healthcare personnel, and costs. Thus, this study aims to estimate the length of stay for infants treated in the Neonatal Intensive Care Unit (NICU) using machine learning algorithms. Our study conducted a two-class prediction for long and short-term lengths of stay utilizing a unique dataset. Adopting a hybrid approach called Classifier Fusion-LoS, the study involved two stages. In the initial stage, various classifiers were employed including classical models such as Logistic Regression, ExtraTrees, Random Forest, KNN, Support Vector Classifier, as well as ensemble models like AdaBoost, GradientBoosting, XGBoost, and CatBoost. Random Forest yielded the highest validation accuracy at 0.94. In the subsequent stage, the Voting Classifier—an ensemble method—was applied, resulting in accuracy increasing to 0.96. Our method outperformed existing studies in terms of accuracy, including both neonatal-specific length of stay prediction studies and other general length of stay prediction research. While the length of stay estimation offers insights into the potential suitability of the incubators in the NICUs, which are not universally available in every city, for patient admission, it plays a pivotal role in delineating the treatment protocols of patients. Additionally, the research provides crucial information to the hospital management for planning such as beds, equipment, personnel, and costs.
Klimawandelbedingte psychosoziale Belastungen und wahrgenommene Anpassungskapazitäten bei Landwirtinnen und Landwirten
Authors: Wittmann Michael , Mano Raphael , Meyer-Habighorst Christiane , André Denise , Fünfgeld Hartmut 
Published: May 2024

ZusammenfassungDie Folgen des Klimawandels auf die menschliche Gesundheit umfassen nicht nur physische, sondern auch psychosoziale Belastungen. Dieser Beitrag untersucht diese Belastungsdimension und die entsprechenden individuell wahrgenommenen Anpassungskapazitäten von Landwirtinnen und Landwirten im Rahmen einer empirischen Fallstudie im südlichen Baden-Württemberg. Die Ergebnisse der Untersuchung zeigen, dass leichte bis starke klimawandelbedingte psychosoziale Belastungen vorliegen, die sich in Gefühlen von Hilf‑, Macht- und Hoffnungslosigkeit, Resignation und Wunschdenken äußern. Sowohl adaptive als auch maladaptive Anpassungsmuster an diese Belastungen sind feststellbar. Die wahrgenommenen Anpassungsmuster ergänzen und beeinflussen sich oftmals gegenseitig, wobei maladaptive Anpassungsstrategien oft unterbewusst stärker direkt auf die Emotionen der Landwirtinnen und Landwirte einwirken, während adaptive Anpassungen als Reaktion auf solche Belastungen meist indirekten Einfluss ausüben. Dabei wirken adaptive Maßnahmen nicht nur belastungsmildernd, sondern tragen teilweise ihrerseits zur psychosozialen Belastung der Landwirtinnen und Landwirte bei. Die Studie zeigt, dass Klimawandelanpassungsforschung und -praxis von einem inklusiven Gesundheitsbegriff profitieren kann, welcher individuelle, kognitive Prozesse der subjektiven Wahrnehmung stärker berücksichtigt.
Experimental Study on Strength Enhancement and Porosity Variation of 3D-Printed Gypsum Rocks: Insights on Vacuum Infiltration Post-Processing
Authors: Shao Yulong , Kim Jineon , Yang Jingwei , Song Jae-Joon , Moon Juhyuk 
Published: May 2024

AbstractThree-dimensional printing (3DP) technology has shown great potential in rock mechanics and mining engineering due to its ability to create complex and customized objects with high precision and accuracy. At present, an emerging research focus is improving the mechanical properties of 3D-printed samples, which originally has low strength and stiffness, to match those of natural rocks. The objective of this study was to investigate the effectiveness of different post-treatments on the strength enhancement of 3D-printed gypsum samples. To achieve this goal, 3D-printed gypsum samples were subjected to different post-treatments including dipped infiltration treatment and vacuum infiltration treatment using different infiltrants: water, saltwater, ColorBond, and StrengthMax. Subsequently, each sample was subjected to ultrasonic wave velocity testing and uniaxial compression experiments to characterize their mechanical properties, CT scans to investigate their microstructural characteristics. Additionally, X-ray Diffraction (XRD) and Scanning Electron Microscope (SEM) tests were conducted to explore the underlying reasons for changes in macroscopic strength. Finally, the physical characteristics and mechanical properties of untreated and post-processed 3D-printed gypsum samples were compared with natural rocks. The results showed that the strength of samples treated with water and saltwater was much lower than that of those treated with ColorBond and StrengthMax, while the porosity was the opposite. In water-treated and saltwater-treated samples, water or saltwater treatment can alter particle characteristics, but weak adhesive bonding and numerous pores result in low mechanical strength. Samples treated with Colorbond or StrengthMax exhibit improved strength due to effective gap filling and cohesive structure formation, with StrengthMax-treated samples showing higher strength despite having more pores than Colorbond-treated ones. Moreover, the physical and mechanical properties of these treated samples matched a wider range of natural rock types compared to the untreated samples.
Investigating Load Arches and the Uplift Capacity of Rock Anchors: A Numerical Approach
Authors: Grindheim Bjarte , Trinh Nghia , Li Charlie C. , Høien Are Håvard 
Published: May 2024

AbstractRock anchors, which can withstand substantial forces and are essential for securing the foundations of the built environment, can fail due to steel tensile failure, bond detachment, or rock mass fracturing through uplift. In this study, uplift failure of the rock mass surrounding rock anchors was simulated using both physical and numerical models. The physical models used a specially designed testing rig with predefined sizes and different joint layouts to simulate rock mass uplift failure. The numerical models were calibrated using the physical models and used to investigate scenarios involving increased complexity and greater depths. This paper presents the load distribution within rock masses with orthogonal joints when exposed to an anchor load. Extensive analysis of the numerical models revealed that symmetrical load arches were induced in rock masses that contained a joint set oriented parallel to the loading direction. However, joints that were obliquely oriented relative to the anchor axis induced asymmetrical load arching. The greatest displacement occurred in the direction parallel to the joint set with the smallest angle to the anchor loading axis. Large-scale models with zero or near-zero in situ horizontal stress revealed that the load capacity in a rock mass with continuous vertical joints was relatively low, especially when compared to rock masses with discontinuous vertical joints. It was observed that the uplift capacity of the rock mass around an anchor decreased if the load arches of adjacent anchors overlapped; consequently, a decrease in anchor spacing was found to correspond to a decrease in uplift capacity.
Occipital artery to vertebral artery bypass for treatment of bilateral vertebral artery occlusion with QMRA as an adjunct to diagnostic assessment
Authors: Zitek Hynek , Hejcl Ales , Sadeh Morteza , Charbel Fady T. , Sames Martin 
Published: May 2024

Abstract

Purpose
Stroke, the second leading cause of death globally, often involves ischemia in the vertebrobasilar territory. This condition is underexplored, despite significant morbidity and mortality risks. The purpose of this study is to present a case of occipital artery to V3 segment vertebral artery bypass, emphasizing the role of quantitative magnetic resonance angiography (qMRA) in assessing flow and guiding surgical intervention.

Methods
A 66-year-old man with bilateral vertebral artery occlusion presented acute symptoms. qMRA was employed to evaluate flow dynamics and determine the feasibility of a flow augmentation bypass surgery. The occipital artery to left vertebral artery bypass (OA-to-VA) was performed, utilizing an inverted hockey-stick incision and an antegrade inside-out technique. The patency of the bypass was confirmed using both Doppler probe and Indocyanine green.

Results
Postoperative assessments, including computed tomography angiography (CTA) and qMRA, demonstrated the patency of the bypass with improved flow in the basilar artery and left vertebral artery. The patient's condition remained stable postoperatively, with residual peripheral palsy of the left facial nerve.

Conclusion
In conclusion, the presented case illustrates the efficacy of the OA-to-VA bypass in addressing symptomatic bilateral vertebral artery occlusion. The study underscores the pivotal role of qMRA in pre- and postoperative assessments, providing noninvasive flow quantification for diagnostic considerations and long-term follow-up in patients with vertebrobasilar insufficiency.
HIV Screening Among Young Black Men Who Have Sex with Women in New Orleans, LA
Authors: Ratnayake Aneeka , Gomes Gérard , Kissinger Patricia J. 
Published: May 2024

AbstractThere are significant disparities in HIV acquisition, with Black individuals facing disproportionately more new diagnoses. Per Centers for Disease Control and Prevention (CDC), all people aged 13–64 should be tested at least once in their lifetime, and men at increased risk (e.g., those who have male sexual contact, multiple partners, have partners with multiple partners, or share drug injection equipment) should be tested annually. The study included young Black men who have sex with women (MSW), aged 15–26, and who live in New Orleans, LA. Survey data was used to elicit the frequency and factors associated with three self-reported outcomes: (1) history of ever HIV testing, (2) HIV screening in the last year among those who were recommended per CDC, and (3) HIV positivity. Of the 1321 men included, 694/1321 men (52.5%) reported ever having been HIV tested. There were 708/1321 (54.2%) men who met the recommendation for annual screening and 321/708 (45.3%) of these eligible men reported being tested in the previous year. Of those ever tested, 44/694 (6.3%) self-reported testing positive. In logistic regression analysis, older age (OR: 1.27, p < 0.001), prior STI testing (OR: 6.45, p < 0.001), and prior incarceration (OR:1.70, p = 0.006) were positively associated with having ever received an HIV test, and ever having a male partner (OR: 3.63, p = 0.014) was associated with HIV positivity. Initiatives to improve HIV testing rates among young Black men who have sex with women are needed to reduce the burden of HIV and help the End the Epidemic initiative.
Sample intelligence-based progressive hedging algorithms for the stochastic capacitated reliable facility location problem
Authors: Aydin Nezir , Murat Alper , Mordukhovich Boris S. 
Published: May 2024

AbstractSelecting facility locations requires significant investment to anticipate and prepare for disruptive events like earthquakes, floods, or labor strikes. In practice, location choices account for facility capacities, which often cannot change during disruptions. When a facility fails, demand transfers to others only if spare capacity exists. Thus, capacitated reliable facility location problems (CRFLP) under uncertainty are more complex than uncapacitated versions. To manage uncertainty and decide effectively, stochastic programming (SP) methods are often employed. Two commonly used SP methods are approximation methods, i.e., Sample Average Approximation (SAA), and decomposition methods, i.e., Progressive Hedging Algorithm (PHA). SAA needs large sample sizes for performance guarantee and turn into computationally intractable. On the other hand, PHA, as an exact method for convex problems, suffers from the need to iteratively solve numerous sub-problems which are computationally costly. In this paper, we developed two novel algorithms integrating SAA and PHA for solving the CRFLP under uncertainty. The developed methods are innovative in that they blend the complementary aspects of PHA and SAA in terms of exactness and computational efficiency, respectively. Further, the developed methods are practical in that they allow the specialist to adjust the tradeoff between the exactness and speed of attaining a solution. We present the effectiveness of the developed integrated approaches, Sampling Based Progressive Hedging Algorithm (SBPHA) and Discarding SBPHA (d-SBPHA), over the pure strategies (i.e. SAA). The validation of the methods is demonstrated through two-stage stochastic CRFLP. Promising results are attained for CRFLP, and the method has great potential to be generalized for SP problems.
Exploring explainable AI in the tax domain
Authors: Górski Łukasz , Kuźniacki Błażej , Almada Marco , Tyliński Kamil , Calvo Madalena , Asnaghi Pablo Matias , Almada Luciano , Iñiguez Hilario , Rubianes Fernando , Pera Octavio , Nigrelli Juan Ignacio 
Published: May 2024

AbstractThis paper analyses whether current explainable AI (XAI) techniques can help to address taxpayer concerns about the use of AI in taxation. As tax authorities around the world increase their use of AI-based techniques, taxpayers are increasingly at a loss about whether and how the ensuing decisions follow the procedures required by law and respect their substantive rights. The use of XAI has been proposed as a response to this issue, but it is still an open question whether current XAI techniques are enough to meet existing legal requirements. The paper approaches this question in the context of a case study: a prototype tax fraud detector trained on an anonymized dataset of real-world cases handled by the Buenos Aires (Argentina) tax authority. The decisions produced by this detector are explained through the use of various classification methods, and the outputs of these explanation models are evaluated on their explanatory power and on their compliance with the legal obligation that tax authorities provide the rationale behind their decision-making. We conclude the paper by suggesting technical and legal approaches for designing explanation mechanisms that meet the needs of legal explanation in the tax domain.
Influence of density and chemical additives on paper mechanical properties
Authors: Asta Nadia , Kaplan Magdalena , Kulachenko Artem , Östlund Sören , Wågberg Lars 
Published: May 2024

AbstractIn this work we have investigated the effect of surface modification of fibres on the overall mechanical properties of high-density papers. Paper sheets were prepared by a combination of heat-pressing and polyelectrolyte Layer-by-Layer (LbL) modification of different softwood fibres. LbLs of Polyallylamine Hydrochloride (PAH) and Hyaluronic Acid (HA) were adsorbed onto unbleached kraft fibres and bleached Chemo-ThermoMechanical Pulp (CTMP) to improve the strength of the fibre–fibre joints in papers made from these fibres. Additionally, different sheet-making procedures were used to prepare a range of network densities with different degrees of fibre–fibre interaction in the system. The results demonstrate that interfacial adhesion within fibre–fibre joints plays a pivotal role in the network's performance, even at higher paper densities. Hygroexpansion measurements and fracture zone imaging with Scanning Electron Microscopy (SEM) further support the claim that stronger interactions between the fibres allow for a better utilisation of the inherent fibre properties. Surface treatments and network densification significantly improved the paper sheets' mechanical properties. Specifically, LbL-treatments alone increased specific stiffness up to 60% and specific strength by over 100%. This improvement is linked to the build-up of residual stresses during drying. Due to a high interaction between the fibres during water removal the fibres become constrained, leading to increased stretching of fibre segments. Strengthened fibre joints intensify this constraint, further increasing the stretch and, consequently, the paper's strength.
Automation of the meshing process of geological data
Authors: Lo Sui Bun , Hassan Oubay , Jones Jason , Liu Xiaolong , Himmelberg Nevan C , Thornton Dean 
Published: May 2024

AbstractThis work proposes a novel meshing technique that is able to extract surfaces from processed seismic data and integrate surfaces that were constructed using other extraction techniques. Contrary to other existing methods, the process is fully automated and does not require any user intervention. The proposed system includes an approach for closing the gaps that arise from the different techniques used for surface extraction. The developed process is able to handle non-manifold domains that result from multiple surface intersections. Surface and volume meshing that comply with user specified mesh control techniques are implemented to ensure the desired mesh quality. The integrated procedures provide a unique facility to handle geotechnical models and accelerate the generation of quality meshes for geophysics modelling. The developed procedure enables the creation of meshes for complex reservoir models to be reduced from weeks to a few hours. Various industrial examples are shown to demonstrate the practicable use of the developed approach to handle real life data.
Strengths, Struggles, and Strategies: How Adults with Serious Mental Illness Navigate Long-Term Romantic Relationships
Authors: Stein Catherine H. , Redondo Rachel A. , Simon Sharon , Silverman Zachary J. 
Published: May 2024

AbstractMarried individuals and those in committed romantic relationships generally report having better mental health outcomes than their single or divorced counterparts. However, studies of romantic relationships for adults with mental illness have often ignored rewarding aspects of romantic relationships and have focused primarily on relationship difficulties. In this study, 23 adults with serious mental illness in long-term romantic relationships described their relationship strengths and struggles in small focus group discussions. Content analysis was used to characterize themes from participant accounts. Overall, participants described deep emotional bonds with their partners, a mutual willingness to work on their relationship, and good communication skills as relationship strengths. Mental health symptoms and internalized stigma were identified as major contributors to relationship struggles. Participants spontaneously identified intentional strategies that they used to navigate mental health challenges in their relationship that included self-directed, partner-directed, and couple-directed actions. Implications of findings for research and practice are discussed.