bluuebunny/crossref_metadata_2025_split huggingface dataset:
The introduction of a minimum wage in Germany and the effects on physical activity participation
Authors: Dallmeyer Sören , Breuer Christoph 
Published: March 2024

AbstractThe relationship between income and physical activity has been extensively studied. This paper utilizes the introduction of the minimum wage in Germany in 2015 as a quasi-experiment to determine the causal effect of minimum wages on the frequency of physical activity participation. Employing survey data from the German Socio-Economic Panel between 2013 and 2017, regression-adjusted difference-in-difference models combined with matching techniques are estimated. Our findings reveal a notable negative effect immediately after the minimum wage implementation on physical activity frequency. Given that the introduction of the minimum wage did not increase monthly gross income but reduced working hours, it appears that affected individuals exhibit preferences and engage in utility maximization that do not emphasize healthy behaviors. This effect is particularly pronounced among older females in white-collar occupations.
Exosomal encapsulation of miR-3198 promotes proliferation and migration of trophoblasts in preeclampsia
Authors: Li Yuchen , Yu Yanling , Li Dejun , Li Lei 
Published: March 2024

Abstract
Purpose
Preeclampsia (PE) is a vascular remodeling disorder cloesly linked to trophoblast dysfunction, involving defects in their proliferation, migration, and apoptosis. Maternal exosomal microRNAs (miRNAs) have been reported to play pivotal roles in the development of PE. However, the mechanism underlying the role of maternal exosomes in trophoblast dysfunction regarding the development of PE is poorly understood.

Methods
Plasma exosomes from maternal peripheral blood were collected from pregnant women with PE and from those with normal pregnancy. Bioinformatics analysis was used to identify significantly differentially expressed miRNAs under these two conditions. The expression of the miR-3198 gene in plasma exosomes was detected using quantitative real-time polymerase chain reaction. Dual luciferase reporter assay was used to confirm binding of miR-3198 and 3′UTR region of WNT3. Cell proliferation was examined using the Cell Count Kit-8 and EdU assays, and flow cytometry was performed to detect apoptosis and cell cycle. Changes in cell migration were examined using transwell and scratch assays.

Results
Patients with PE showed decreased expression of plasma-derived exosomal miR-3198. The proliferation and migration abilities of HTR-8/SVneo and primary human trophoblast cells were both improved when cocultured with miR-3198-rich exosomes. Exposure to miR-3198-enriched exosomes facilitated cell cycle progression but reduced apoptosis in HTR-8/SVneo cells. Notably, overexpression of miR-3198 partially prevented the inhibitory effects of WNT3 on proliferation and migration in HTR-8/SVneo cells.

Conclusion
Exosomal miR-3198 in the maternal peripheral blood may regulate the biological functions of trophoblasts by targeting WNT3 and influence the development of diseases of placental origin.

Graphical Abstract
Electronic Health Records for Predicting Outcomes to Work-Related Musculoskeletal Disorders: A Scoping Review
Authors: Wassell M. , Vitiello A. , Butler-Henderson K. , Verspoor K. , McCann P. , Pollard H. 
Published: March 2024

Abstract
Purpose
Through electronic health records (EHRs), musculoskeletal (MSK) therapists such as chiropractors and physical therapists, as well as occupational medicine physicians could collect data on many variables that can be traditionally challenging to collect in managing work-related musculoskeletal disorders (WMSDs). The review’s objectives were to explore the extent of research using EHRs in predicting outcomes of WMSDs by MSK therapists.

Method
A systematic search was conducted in Medline, PubMed, CINAHL, and Embase. Grey literature was searched. 2156 unique papers were retrieved, of which 38 were included. Three themes were explored, the use of EHRs to predict outcomes to WMSDs, data sources for predicting outcomes to WMSDs, and adoption of standardised information for managing WMSDs.

Results
Predicting outcomes of all MSK disorders using EHRs has been researched in 6 studies, with only 3 focusing on MSK therapists and 4 addressing WMSDs. Similar to all secondary data source research, the challenges include data quality, missing data and unstructured data. There is not yet a standardised or minimum set of data that has been defined for MSK therapists to collect when managing WMSD. Further work based on existing frameworks is required to reduce the documentation burden and increase usability.

Conclusion
The review outlines the limited research on using EHRs to predict outcomes of WMSDs. It highlights the need for EHR design to address data quality issues and develop a standardised data set in occupational healthcare that includes known factors that potentially predict outcomes to help regulators, research efforts, and practitioners make better informed clinical decisions.
Reconstruction-Aware Kernelized Fuzzy Clustering Framework Incorporating Local Information for Image Segmentation
Authors: Wu Chengmao , Qi Xiao 
Published: March 2024

AbstractKernelized fuzzy C-means clustering with weighted local information is an extensively applied robust segmentation algorithm for noisy image. However, it is difficult to effectively solve the problem of segmenting image polluted by strong noise. To address this issue, a reconstruction-aware kernel fuzzy C-mean clustering with rich local information is proposed in this paper. Firstly, the optimization modeling of guided bilateral filtering is given for noisy image; Secondly, this filtering model is embedded into kernelized fuzzy C-means clustering with local information, and a novel reconstruction-filtering information driven fuzzy clustering model for noise-corrupted image segmentation is presented; Finally, a tri-level alternative and iterative algorithm is derived from optimizing model using optimization theory and its convergence is strictly analyzed. Many Experimental results on noisy synthetic images and actual images indicate that compared with the latest advanced fuzzy clustering-related algorithms, the algorithm presented in this paper has better segmentation performance and stronger robustness to noise, and its PSNR and ACC values increase by about 0.16–3.28 and 0.01–0.08 respectively.
Do institutional dimensions matter at different stages of the entrepreneurial process? A multi-country study
Authors: Alvarez Claudia , Lopez Tatiana , Urbano David 
Published: March 2024

Abstract
Entrepreneurs should navigate through different stages from the conception of an idea until the business is operational. According to these stages, we expected that the context has a different impact on an individual’s decisions. This paper analyses the role of institutional dimensions (regulative, normative, and cultural-cognitive) in the entrepreneurial process (potential, nascent, and new entrepreneurship), using data from the Global Entrepreneurship Monitor and Heritage Foundation, with a sample of 99 countries for the period 2001–2017. Through panel data, the main findings show that (a) regulations regarding new business creation have a stronger influence on new entrepreneurship, (b) social norms have more influence on potential entrepreneurs and individual perceptions regarding their self-capacity and experience to start a new business, and (c) the cultural-cognitive dimension has a stronger influence on nascent entrepreneurship. Policymakers could consider these results to promote and generate target group policies that effectively encourage entrepreneurial activity, which is also distinguished by the level of development among countries.
A comparative evaluation of machine learning ensemble approaches for disease prediction using multiple datasets
Authors: Mahajan Palak , Uddin Shahadat , Hajati Farshid , Moni Mohammad Ali , Gide Ergun 
Published: March 2024

Abstract
Purpose
Machine learning models are used to develop and improve various disease prediction systems. Ensemble learning is a machine learning technique that combines many classifiers to increase performance by making more accurate predictions than a single classifier. Although several researchers have employed ensemble techniques for disease prediction, a comprehensive comparative study of these techniques still needs to be provided.

Methods
Using 16 disease datasets from Kaggle and the UCI Machine Learning Repository, this study compares the performance of 15 variants of ensemble techniques for disease prediction. The comparison was performed using six performance measures: accuracy, precision, recall, F1 score, AUC (Area Under the receiver operating characteristics Curve) and AUPRC (Area Under the Precision-Recall Curve).

Results
Stacking variant of Multi-level stacking showed superior disease prediction performance compared with other bagging and boosting variants, followed by another stacking variant (Classical stacking). Overall, stacking outperformed bagging and boosting for disease prediction. Logit Boost showed the worst performance.

Conclusion
The findings of this study can help researchers select an appropriate ensemble approach for future studies focusing on accurate disease prediction.
Addressing Ethical Concerns in Implementing Mindfulness-Based Interventions in Educational Setting
Authors: Berger Rony , Tarrasch Ricardo , Lieblich Maty 
Published: March 2024

AbstractThe burgeoning interest in mindfulness and the way it has been stripped from its Buddhist ontological roots and popularized in the West has recently raised ethical concerns regarding its application in various domains, and more specifically in the educational field. We will address in this article three main ethical concerns regarding implementing mindfulness-based interventions (MBIs) in the educational field. Firstly, how do we help educators and students cultivate personal awareness while at the same time being conscious of the needs of others and promote a pro-social orientation? Secondly, how do we ethically implement MBIs in the current neoliberal social, cultural, and political context? Thirdly, how do we implement MBIs in a culturally sensitive manner respecting the ethics of other ethnic groups and other societies? We will attempt to offer solutions to those issues by exemplifying how MBIs are integrated with compassion-based interventions (e.g., mindful self-compassion (MSC)) and social-emotional learning (understanding and managing emotions, building positive relationships, and making responsible decisions) among educators and students in Jewish and Arab schools in Israel. We will discuss three MBI programs that incorporate strategies addressing social ailments such as stereotyping and prejudicial attitudes and promote pro-social behavior as well as share research findings regarding their efficacy. Additionally, we will outline ways in which these mindfulness-based programs were adapted to suit different populations. Finally, we will conclude by pointing to future means to address these issues.
Quality of life assessment and therapeutic adherence in Mexican patients with type 2 diabetes
Authors: Pérez-Ortiz Alejandro , Becerra-Gálvez Ana Leticia , Mancilla-Díaz Juan Manuel , de la Hoz Perla Irán Fernández , Lugo-González Isaías Vicente , Cancino-Romero y Mario Francisco 
Published: March 2024

Abstract

Background
Patients with diabetes mellitus experience physical health needs, but also psychological health needs, as some studies have suggested that addressing the psychological variables associated with diabetes mellitus may improve the biochemical parameters of the disease.

Objectives
To assess the quality of life (QoL) and therapeutic adherence (TA) in Mexican patients with controlled and uncontrolled type 2 diabetes mellitus (T2DM), as well as related QoL sociodemographic and clinical variables.

Methods
201 people with T2DM answered a battery of psychological tests to assess TA (Therapeutic Adherence Survey or TAS-15), QoL (WHOQOL-BREF-16) and disease-related quality of life (DRQoL-27), aside from an expressly designed questionnaire that gathered sociodemographic data and took information from medical records into consideration. The average age of the participants was 65.12 ± 11.617 years and 57.2% were female, who have suffered from diabetes for 13.4 years on average ± 8.088 and an average 158.84 mg/dL ± 61.913 fasting plasma glucose.

Results
The correlation analyses revealed that a higher perception of QoL, the lower the perception that having diabetes affected QoL (p<0.01); the higher the TA, the lower the QoL (p<0.01); and the higher the TA, the lower the perception that having diabetes affected QoL (p<0.01). The participants with an uncontrolled T2DM exhibited a better QoL than those that manage their glucose levels (p = 0.015). The participants’ level of education had a positive effect on QoL (β = 0.163, IC 95%: 0.429─3.415, p = 0.012), whereas the DRQoL had a negative effect (β = -0.546, IC 95%: -0.127─-0.080, p = 0.001).

Conclusions
If the TA of patients with T2DM increases, the overall QoL as well as the DRQoL will improve. Hence, these variables must be considered as therapeutic targets in clinical practice.
Generalized fuzzy difference method for solving fuzzy initial value problem
Authors: Soroush S. , Allahviranloo T. , Azari H. , Rostamy-Malkhalifeh M. 
Published: March 2024

AbstractWe are going to explain the fuzzy Adams–Bashforth methods for solving fuzzy differential equations focusing on the concept of g-differentiability. Considering the analysis of normal, convex, upper semicontinuous, compactly supported fuzzy sets in $$R^n$$

R
n

and also convergence of the methods, the general expression of solutions is obtained. Finally, we demonstrate the importance of our method with some illustrative examples. These examples are provided aiming to solve the fuzzy differential equations.
Quantum Antitrust – A Unified Exclusionary Abuse Theory
Authors: Solano Díaz Pablo 
Published: March 2024

AbstractNow that the judgments in Servizio Elettrico Nazionale and Unilever have made sense of previous case-law, a unified analytical framework can be predicated for all exclusionary abuses. It is made up of two limbs (artificiality/conduct deviating from competition on the merits and potential exclusionary effect/capability of foreclosing). The two limbs are two sides of the same coin, which consists of ascertaining whether the plausible rationale (in the sense of nature and economy) behind a dominant company’s conduct is to derive an advantage that equally efficient competitors cannot either derive by doing the same (first limb–artificiality) or offset by other means (second limb–potential effect). This exclusionary rationale, which is a cognitive state in the dominant company’s mind rather than an ontological reality, is objectivised by holistically judging the dominant company’s conduct against the backdrop of the relative efficiency of its competitors, which is the link between both limbs: if the inherent features of the company’s conduct and all the relevant circumstances surrounding it allow equally efficient competitors to either derive a similar advantage or to defeat its exclusionary effect by some other means, the conduct does not make anticompetitive sense (exclusion is not its plausible rationale). Owing to the very Darwinian nature of competition law, relative efficiency is the common “quantum” and, therefore, a useful yardstick for abuse from the historical, legal, teleological and practical perspectives, as well as from the points of view of causality and reality. Finally, plausibility would be the single standard of proof that could be rebutted by disproving either of the two limbs (in an Intel II-like fashion), either by providing an alternative non-exclusionary explanation that breaks the casual link or by putting forward an objective justification. All other tests and standards merely reflect the extent to which either the artificiality or the potential effects of the conduct can be presumed based on economic judgement or experience (as happened in merger control following CK Telecoms)–thus reconciling per se rules, consisting of an Art. 101-like cursory analysis, with a more economic approach.
Development of a diagnostic model for pre-washout screening of primary aldosteronism
Authors: Wang Q. , Dong H. , LI H.-W. , Zheng Z.-H. , Liu Y.-Z. , Hua Y.-H. , Xiong Y.-J. , Zhang H.-M. , Song L. , Zou Y.-B. , Jiang X.-J. 
Published: March 2024

Abstract
Purpose
Primary aldosteronism (PA) diagnosis is affected by antihypertensive drugs that are commonly taken by patients with suspected PA. In this study, we developed and validated a diagnostic model for screening PA without drug washout.

Methods
We retrospectively analyzed 1095 patients diagnosed with PA or essential hypertension. Patients were randomly grouped into training and validation sets at a 7:3 ratio. Baseline characteristics, plasma aldosterone concentration (PAC), and direct renin concentration (DRC) before and after drug washout were separately recorded, and the aldosterone-to-renin ratio (ARR) was calculated.

Results
PAC and ARR were higher and direct renin concentration was lower in patients with PA than in patients with essential hypertension. Furthermore, the differences in blood potassium and sodium concentrations and hypertension grades between the two groups were significant. Using the abbreviations potassium (P), ARR (A), PAC (P), sodium (S), and hypertension grade 3 (3), the model was named PAPS3. The PAPS3 model had a maximum score of 10, with the cutoff value assigned as 5.5; it showed high sensitivity and specificity for screening PA in patients who exhibit difficulty in tolerating drug washout.

Conclusion
PA screening remains crucial, and standard guidelines should be followed for patients to tolerate washout. The PAPS3 model offers an alternative to minimize risks and enhance diagnostic efficiency in PA for those facing washout challenges. Despite its high accuracy, further validation of this model is warranted through large-scale clinical studies.
Hydrodynamic resistance of pore–throat structures and its effect on shale oil apparent permeability
Authors: Wang Wendong , Zhang Qian , Xu Jilong , Zheng Da , Liu Lifeng , Su Yuliang 
Published: March 2024

AbstractOil transport is greatly affected by heterogeneous pore–throat structures present in shale. It is therefore very important to accurately characterize pore–throat structures. Additionally, it remains unclear how pore–throat structures affect oil transport capacity. In this paper, using finite element (FE) simulation and mathematical modeling, we calculated the hydrodynamic resistance for four pore–throat structure. In addition, the influence of pore throat structure on shale oil permeability is analyzed. According to the results, the hydrodynamic resistance of different pore throat structures can vary by 300%. The contribution of additional resistance caused by streamline bending is also in excess of 40%, even without slip length. Furthermore, Pore–throat structures can affect apparent permeability by more than 60% on the REV scale, and this influence increases with heterogeneity of pore size distribution, organic matter content, and organic matter number. Clearly, modeling shale oil flow requires consideration of porous–throat structure and additional resistance, otherwise oil recovery and flow capacity may be overestimated.
Revitalising smallholder agriculture: the impact of technical training in rural Lebanon
Authors: Balestri Sara 
Published: March 2024

AbstractThis paper provides new evidence about the impact of an agricultural development initiative focused on the cherry sector and implemented in rural areas of the Bekaa Valley (Lebanon). The initiative aims to enhance economic opportunities of smallholder farmers by strengthening technical skills, fostering sustainable productions and developing market linkages. Using original micro data from a sample of 118 smallholder cherry farmers, we explore, through a Difference-in-Differences approach, whether the development initiative, based on the provision of extension services and accompaniment through technical training, impacts on a broad set of alternative agricultural outcomes—namely, total cherry production, average market price, management competency and the adoption of improved agricultural practices. The results show that beneficiary small-scale farmers achieve better performances in three outcomes out of the four considered, with the adoption of improved and sustainable agricultural practices as the most remarkable result. Conversely, the management of the agricultural economic activity does not experience any statistically significant variation connected to the initiative implementation. The analysis of a limited source of treatment heterogeneity discloses the primary role of technical training, rather than other kinds of material support, to explain the main results.
Further Results on the [k]-Roman Domination in Graphs
Authors: Valenzuela-Tripodoro Juan Carlos , Mateos-Camacho Maria Antonia , Cera Lopez Martin , Álvarez-Ruiz Maria Pilar 
Published: March 2024

AbstractIn 2016, Beeler et al. defined the double Roman domination as a variation of Roman domination. Sometime later, in 2021, Ahangar et al. introduced the concept of [k]-Roman domination in graphs and settled some results on the triple Roman domination case. In 2022, Amjadi et al. studied the quadruple version of this Roman-domination-type problem. Given any labeling of the vertices of a graph, AN(v) stands for the set of neighbors of a vertex v having a positive label. In this paper we continue the study of the [k]-Roman domination functions ([k]-RDF) in graphs which coincides with the previous versions when $$2\le k \le 4$$

2
≤
k
≤
4

. Namely, f is a [k]-RDF if $$f(N[v])\ge k+|AN(v)|$$

f
(
N
[
v
]
)
≥
k
+
|
A
N
(
v
)
|

for all v. We prove that the associate decision problem is NP-complete even when restricted to star convex and comb convex bipartite graphs and we also give sharp bounds and exact values for several classes of graphs.
Dynamic Responses of Layered Viscoelastic Half-Medium with Twin Tunnel Under Harmonic Load
Authors: Yüksel Yusuf Ziya , Akbaş Şeref Doğuşcan 
Published: March 2024

Abstract
Purpose
This paper presents dynamic analysis of layered viscoelastic half medium which includes twin rectangular tunnel under harmonic load. Viscoelastic half medium is considered and modelled with using Kelvin–Voigt viscoelastic model and two dimensional (2-D) continua.

Methods
The considered problem is solved by using finite element method. The energy expressions of the system are obtained and equation of motion are obtained by using Lagrange procedure. Infinite region far from twin tunnel is modelled by using infinite elements with 8 nodes and finite region is modelled by using 16 nodes finite elements. The dynamic equations for finite and infinite elements are solved by using Newmark-Beta method in time domain. Finite and infinite element models with different layers and twin tunnel are generated and numerical solutions are obtained by using an algorithm by authors.

Results
In order to achieve verify the used models and methods, some special results are obtained and compared with results from a finite element software. In numerical studies, effects of location of twin tunnel on dynamical responses of the system under harmonic load are obtained in figures and discussed in detail. Dynamic tunnel-medium interaction is discussed in the obtained results.

Conclusions
The numerical results show that tunnel location plays important role on the dynamic responses of half medium and dynamic responses change significantly with tunnel-medium interaction. In field near to the tunnel, the dynamic responses are more affected. Important practical implication is that computational cost for this kind of problems could be reduced, more realistic results could be obtained and all boundary conditions could be considered by used model with infinite elements. The used model and method are very useful and practical for dynamic analysis of tunnel structures.