bluuebunny/crossref_metadata_2025_split huggingface dataset:
A case of ‘de-immigrantization’: when sexual minority individuals lose immigrant status
Authors: Reese Jonathan , Santos Ana Sofia , Palma Tomás A. 
Published: September 2023

AbstractIndividuals generally hold multiple, and sometimes stereotypically contrasted, group memberships which may change depending on uncontrollable contextual factors. For instance, if someone is a foreigner, there exist certain social stereotypes regarding their nationality which may influence others’ conceptualizations. However, how might an intersection of memberships, such as being both foreign and gay, affect natives’ perceptions of them when these stereotypes may not converge? Across four experiments, the stereotypes attributed to generalized and specific groups were examined to better understand intersectional prototypicalities. Results indicated certain cases in which immigrants may be “de-immigrantized”, or, perceived as less stereotypically immigrant. More specifically, Portuguese participants viewed gay immigrants as less prototypically immigrant, but did not view lesbian immigrants as less prototypically immigrant, bringing into question the complexity of double minority conceptualizations. Additionally, individuals from nationalities with a higher perceived percentage of gays or lesbians in their population (e.g., Brazil and France) were generally viewed as less prototypically immigrant than individuals from nationalities with a lower perceived percentage of gays or lesbians in their population (e.g., India and Japan). Conclusions provide support for intersectional theories and yield additional insights into the categorization of multiple minority groups on the basis of sexuality and nationality.
Considering a Bifactor Model of Children’s Subjective Well-Being Using a Multinational Sample
Authors: Savahl Shazly , Casas Ferran , Adams Sabirah 
Published: September 2023

AbstractIn the current study, we consider the viability of a bifactor model of children’s subjective well-being (SWB) by contributing to the discussion on the dimensionality of children’s SWB. We specify a general factor of SWB and four group factors (context-free cognitive life satisfaction, domain-based cognitive life satisfaction, positive affect, and negative affect) using structural equation modelling and parceling. We used data from the Children’s Worlds International Survey of Children’s Well-Being (N = 92 782). Our analysis strategy included confirmatory factor analysis and bifactor analysis. We found a good fit for the specified bifactor model, with all items loading onto a general factor and group factors. For the bifactor analysis, after controlling for the general factor, the loadings on the group factors were substantially lower, and did not meet the criteria of acceptability for bifactor indices thresholds. The common variance of the items is largely explained by the general factor; thus, the specification of the group factors cannot be justified. Further, we found an excellent fit for a model using the parceling approach. From a measurement perspective, the construct of children’s SWB can potentially be measured as a unidimensional construct. Thus, it may be feasible to report a total score for children’s SWB, as opposed to scores on the individual subscales (group factors). Applied researchers can thus confidently use SWB as a unidimensional construct or follow the parceling approach in the structural equation model context.
Possible Consequences of the Criminalization of Sex Work in Spain, Inferred from COVID-19 Lockdown Measures
Authors: Meneses-Falcón Carmen , Rúa-Vieites Antonio 
Published: September 2023

Abstract
Introduction
In this paper, we explore the possible consequences of the criminalization of sex work in Spain through an analysis of the measures adopted during the COVID-19 lockdown, which were tantamount to a prohibition of prostitution.

Methods
We interviewed 69 female sex workers (19 of them trafficking victims) from the lowest stratum and six escorts from the upper stratum of prostitution, during the period from March 2020 to May 2021. We also conducted an ethnographic study in a hotel operating in the middle to upper stratum of commercial sex work.

Results
The months of home confinement showed that the prohibition of sex work affected women in more precarious and vulnerable situations more adversely, worsening their living and working conditions compared to before the pandemic, whereas the impact on the escorts was far less.

Conclusion
If commercial sex work in Spain were totally or partially criminalized, sex work would not stop taking place, and nor would the demand for paid sex cease to exist. Rather, they would be driven underground, worsening the quality of life, and both health and working conditions in the practice of commercial sex work for women. On top of that, the implementation of such a policy would reduce or eliminate sex workers’ relationships or collaborations with the police.
Lattice sums for double periodic polyanalytic functions
Authors: Drygaś Piotr , Mityushev Vladimir 
Published: September 2023

AbstractIn 1892, Lord Rayleigh estimated the effective conductivity of rectangular arrays of disks and proved, employing the Eisenstein summation, that the lattice sum $$S_2$$

S
2

is equal to $$\pi $$
π
for the square array. Further, it became clear that such equality can be treated as a necessary condition of the macroscopic isotropy of composites governed by the Laplace equation. This yielded the description of two-dimensional conducting composites by the classic elliptic functions, including the conditionally convergent Eisenstein series. In 1935, Natanzon used a polyharmonic function to solve the plane elasticity problem. This paper is devoted to the extension of the classic lattice sums to the lattice sums for double periodic (pseudoperiodic) polyanalytic functions. The exact relations and computationally effective formulae between the polyanalytic and classic lattice sums are established. Polynomial representations of the lattice sums are obtained. They are a source of new exact formulae for the lattice sums.
Variants of the CASP9 gene as candidate markers for primary response to anti-TNF therapy in Crohn’s disease patients
Authors: Lykowska-Szuber Liliana , Walczak Michal , Stawczyk-Eder Kamila , Krela-Kazmierczak Iwona , Eder Piotr , Zakerska-Banaszak Oliwia , Dobrowolska Agnieszka , Skrzypczak-Zielinska Marzena 
Published: September 2023

AbstractAnti-tumor necrosis factor (TNF) therapy is used to induce and maintain remission in Crohn’s disease (CD) patients. However, primary non-responders to initial treatment constitute 20–40% of cases. The causes of this phenomenon are still unknown. We aim to investigate the impact of the caspase 9 (CASP9) gene variants on the variable reactions of CD patients to anti-TNF therapy. The study group included 196 diagnosed and clinically characterized CD Polish patients following anti-TNF therapy. The sequence of the CASP9 gene was analyzed using next-generation and Sanger sequencing and was analyzed with the response to biological treatment. Using the RT-qPCR analysis, we estimated the CASP9 gene mRNA level in colon biopsies material from inflamed and non-inflamed tissue (21 CD patients: 14 responders and seven non-responders to anti-TNF therapy and six controls), as well as in vitro in a peripheral blood mononuclear cells (PBMCs) from CD patients (seven responders and seven non-responders to anti-TNF therapy) and eight controls. Our findings indicated association of variants rs1052571 and rs4645978 with response to anti-TNF monoclonal antibodies (mAbs). Moreover, we observed tendency for reduced expression after incubation with anti-TNF in the group of CD patients, in contrast to the control group. Our results suggest that response to anti-TNF therapy in CD patients may be an effect of variants of the CASP9 gene as a key effector of the internal pathway of apoptosis; however, further population and functional research are necessary.
Efficient Nanosystem for Nanomedicine Applications Based on Molecular Communications
Authors: Abd El-atty Saied M. , Attia Eman S. , Khalaf Ashraf A. M. , Abd El-Samie Fathi E. , Shawki Farid 
Published: September 2023

AbstractThe authors propose an efficient nanosystem based on molecular communication technology. Molecular communication via diffusion (MCvD) is a promising trend for exchanging biochemical signals between a nanotransmitter (NT) and a nanoreceiver (NR) in aqueous media over short distances. Nanosystem-based MCvD has recently received a lot of attention in advanced targeted nanomedicine applications such as targeted drug delivery and healthcare monitoring (disease/diagnosis/analysis). However, the random nature of molecular diffusion causes counting noise, which significantly degrades the performance of the nanosystem-based molecular communication. In this paper, a reliable and simple denoising technique, namely Savitzky–Golay (SG) filter, is developed in the nanosystem-based MCvD to provide high accuracy of molecular information reception. The performance of the proposed nanosystem is evaluated in terms of bit error rate (BER) and correlation efficiency. The results reveal that the nanosystem-based MCvD using the proposed SG filter outperforms the MCvD using current denoising techniques such as moving average filter, wavelet denoising and I-filter. Actually, it was found that the SG filter increases the gain efficiency in terms of the correlation coefficient by more than 60% in comparison to the I-filter at low and high signal-to-noise ratios (SNRs), whereas in comparison to wavelet denoising, the SG filter achieves more than 10% enhancement in gain efficiency at low SNRs.
Within Groups Designs: Inferences Based on A Robust Nonparametric Measure of Effect Size
Authors: Wilcox Rand R. 
Published: September 2023

AbstractThe paper deals with a robust, projection-type measure of effect size when comparing$$J>1$$J>1dependent groups. The measure of effect size is scale invariant and does not assume or require that the underlying multivariate distribution is elliptically contoured. By design the measure of effect size is equal to zero when the corresponding measures of location are equal. A simple method is suggested for testing the hypothesis that this effect size is zero. The method is readily extended to comparingK-variate distributions associated with two independent groups. One of the main goal is to report simulation results on how well the method performs in terms of controlling the Type I error probability. The method, when comparing independent groups, is used to reveal new insights into the connection between depression and cortisol levels.
Revisiting the ‘Whys’ and ‘Hows’ of the Warm-Up: Are We Asking the Right Questions?
Authors: Afonso José , Brito João , Abade Eduardo , Rendeiro-Pinho Gonçalo , Baptista Ivan , Figueiredo Pedro , Nakamura Fábio Yuzo 
Published: September 2023

AbstractThe warm-up is considered beneficial for increasing body temperature, stimulating the neuromuscular system and overall preparing the athletes for the demands of training sessions and competitions. Even when warm-up–derived benefits are slight and transient, they may still benefit preparedness for subsequent efforts. However, sports training and competition performance are highly affected by contextual factors (e.g., how is the opponent acting?), and it is not always clear what should be the preferred warm-up modalities, structure and load for each athlete and context. Further, we propose that the warm-up can also be used as a pedagogical and training moment. The warm-up may serve several different (albeit complementary) goals (e.g., rising body temperature, neuromuscular activation, attentional focus) and be performed under a plethora of different structures, modalities, and loads. The current commentary highlights the warm-up period as an opportunity to teach or improve certain skills or physical capacities, and not only as a preparation for the subsequent efforts. Moreover, the (justified) call for individualized warm-ups would benefit from educating athletes about exploring different warm-up tasks and loads, providing a broad foundation for future individualization of the warm-up and for more active, engaged, and well-informed participation of the athletes in deciding their own warm-up practices.
Continuous Glucose Monitoring in Endurance Athletes: Interpretation and Relevance of Measurements for Improving Performance and Health
Authors: Flockhart Mikael , Larsen Filip J. 
Published: September 2023

AbstractBlood glucose regulation has been studied for well over a century as it is intimately related to metabolic health. Research in glucose transport and uptake has also been substantial within the field of exercise physiology as glucose delivery to the working muscles affects exercise capacity and athletic achievements. However, although exceptions exist, less focus has been on blood glucose as a parameter to optimize training and competition outcomes in athletes with normal glucose control. During the last years, measuring glucose has gained popularity within the sports community and successful endurance athletes have been seen with skin-mounted sensors for continuous glucose monitoring (CGM). The technique offers real-time recording of glucose concentrations in the interstitium, which is assumed to be equivalent to concentrations in the blood. Although continuous measurements of a parameter that is intimately connected to metabolism and health can seem appealing, there is no current consensus on how to interpret measurements within this context. Well-defined approaches to use glucose monitoring to improve endurance athletes’ performance and health are lacking. In several studies, blood glucose regulation in endurance athletes has been shown to differ from that in healthy controls. Furthermore, endurance athletes regularly perform demanding training sessions and can be exposed to high or low energy and/or carbohydrate availability, which can affect blood glucose levels and regulation. In this current opinion, we aim to discuss blood glucose regulation in endurance athletes and highlight the existing research on glucose monitoring for performance and health in this population.
Does Videoconferencing-Based Cognitive Behavioral Therapy for Anxious Youth Work? A Systematic Review of the Literature
Authors: Vu Bich-Phuong , Dang Hoang-Minh , Andersen Per Normann 
Published: September 2023

Opinion statementWhile videoconferencing has become a common tool for remote communication in health-related services such as psychotherapy, scientific evidence for its outcomes is scarce in the population of youth with problematic anxiety. This paper reviews the primary and secondary outcomes of cognitive behavioral therapies (CBT) delivered via videoconferencing for youth with subclinical or clinical anxiety. Quantitative and qualitative studies focusing on youth (aged 7 to 20), anxiety, CBT, and videoconferencing were systematically searched on Embase, PubMed, PsycINFO, and ERIC databases. Eight studies met the inclusion criteria, of which seven were extracted for quantitative data. Out of the seven studies, only one study was quasi-experimental with an in-person CBT comparison group, while another study was a small-scaled randomized controlled trial with a waitlist control group. The pooled sample size was 213 children and adolescents. Significant changes in primary (i.e., anxiety symptoms and severity) and secondary outcome measures (e.g., global functioning and life interference) at post-treatment of videoconferencing-based CBT were reported, but lacking a control group in a majority of the studies reduces the finding’s validity. Satisfaction, treatment completion rate, and therapist’s fidelity were rarely reported but found to be high in some studies. None of the studies reported negative effects specific to videoconferencing-based CBT. The current evidence for this topic is somewhat limited in terms of quantity and quality. Replication studies in low- and middle-income countries are also lacking. More well-designed trials are needed to provide more conclusive evidence for the videoconferencing modality, which may help scale up psychological interventions for a highly prevalent problem such as youth anxiety in remote or low-income areas.
Evolving Interest with Feature Co-action Network for CTR Prediction
Authors: Yuan Zhiyang , Zheng Wenguang , Yang Peilin , Hao Qingbo , Xiao Yingyuan 
Published: September 2023

AbstractRecently, many deep learning-based models have been successfully applied to click-through rate prediction. However, most previous models focus only on feature-level interactions between a single user behavior and the target item or only treat the user’s historical behavior as a sequence to uncover the hidden interests behind it when mining user interests. This can lead to user interest that evolves over time dynamically being ignored or the interest shown by a single user’s behavior not being exploited. Based on the above problems, we propose evolving interest with feature co-action network (EIFCN). Specifically, we first design user dynamic interest network to treat the user’s historical behavior as a sequence of information, and tap into the user’s hidden interests over time. In this part, we use a multi-head self-attention mechanism to initially process the data and then pass it into the deep learning network. Then a feature co-action network is designed to mine the user’s single behavior and the displayed feature-level interactions of the target item. Experimental results show that the EIFCN model performs better than other models.
Deep Learning-Based Bloom Filter for Efficient Multi-key Membership Testing
Authors: Chen Haitian , Wang Ziwei , Li Yunchuan , Yang Ruixin , Zhao Yan , Zhou Rui , Zheng Kai 
Published: September 2023

AbstractMulti-key membership testing plays a crucial role in computing systems and networking applications, encompassing web search, mail systems, distributed databases, firewalls, and network routing. Traditional approaches, such as the Bloom filter, encounter limitations within this specific context. Addressing these challenges, we propose the Multi-key Learned Bloom Filter (MLBF), a hybrid method that combines machine learning techniques with the Bloom filter. The MLBF introduces a value-interaction-based multi-key classifier and a multi-key Bloom filter. Furthermore, we introduce an Interval-based MLBF approach, which categorizes keys into specific intervals based on data distribution to minimize the False Positive Rate (FPR). Additionally, MLBF incorporates an out-of-distribution (OOD) detection component to identify data shifts. Through extensive experimental evaluations on three authentic datasets, we demonstrate the superiority of the proposed MLBF in terms of FPR and query efficiency.
Combining Graph Contrastive Embedding and Multi-head Cross-Attention Transfer for Cross-Domain Recommendation
Authors: Xiao Shuo , Zhu Dongqing , Tang Chaogang , Huang Zhenzhen 
Published: September 2023

AbstractCross-domain recommendation (CDR) has become an important research direction in the field of recommender systems due to the increasing demand for personalized recommendations across different domains. However, CDR faces multiple challenges, including data sparsity, popularity bias, and long-tail problems. To address these challenges, we propose a novel framework that combines graph contrastive embedding and multi-head cross-attention transfer for cross-domain recommendation, called GCE-MCAT. Specifically, in the pre-training process, we generate more uniform user and item embeddings through contrastive learning, effectively solving the problem of inconsistent data embedding space distribution and recommendation popularity bias. Moreover, we propose a multi-head cross-attention transfer mechanism that allows the model to extract user common and specific domain features from multiple perspectives and perform cross-domain bidirectional knowledge transfer. Finally, we propose a cross-domain feature fusion mechanism that dynamically assigns weights to common user features and specific domain features. This enables the model to more effectively learn common user interests. We evaluate the proposed framework on three real-world CDR datasets and show that GCE-MCAT consistently and significantly improves recommendation performance compared to state-of-the-art methods. In particular, the proposed framework has demonstrated remarkable effectiveness in addressing long-tail distribution and enhancing recommendation novelty, providing users with more diversified recommendations and reducing popularity bias.
A Survey of Personalized News Recommendation
Authors: Meng Xiangfu , Huo Hongjin , Zhang Xiaoyan , Wang Wanchun , Zhu Jinxia 
Published: September 2023

AbstractPersonalized news recommendation is an important technology to help users obtain news information they are interested in and alleviate information overload. In recent years, news recommendation has been increasingly widely studied and has achieved remarkable success in improving the news reading experience of users. In this paper, we provide a comprehensive overview of personalized news recommendation approaches. Firstly, we introduce personalized news recommendation systems according to different needs and analyze the characteristics. And then, a three-part research framework on personalized news recommendation is put forward. Based on the framework, the knowledge and methods involved in each part are analyzed in detail, including news datasets and processing techniques, prediction models, news ranking and display. On this basis, we focus on news recommendation methods based on different types of graph structure learning, including user–news interaction graph, knowledge graph and social relationship graph. Lastly, the challenges of the current news recommendation are analyzed and the prospect of the future research direction is presented.
Exploring the Ecology: Beyond Cameron and Khanna
Authors: Kowalski Patricia , Taylor Annette Kujawski 
Published: September 2023

AbstractIn reviewing the Cameron and Khanna project, we find much to be commended. The large diverse sample of researchers and the collection of widespread student misconceptions will help focus students and instructors in the introductory course on teaching and learning the science of psychology. The recommendations we make provide a guide for looking beyond student belief and recognizing factors potentially contributing to and supporting misconceptions. Because teaching psychological science in the introductory psychology course is challenging, it is likely that misconceptions result from misinterpretations of the evidence. Investigating how textbooks and instructors’ perceptions of claims perpetuate misconceptions would be an important contribution toward improving the teaching of psychology. Assessing student misconceptions about psychological science would document the prevalence of science misconceptions, would permit the investigation of change in knowledge and scientific attitudes with the introductory psychology course, and would provide a basis for studying links between misconceptions about psychology and misunderstanding (or lack of appreciation) of the very nature of science.
We (Still!) Need to Talk About Valence: Contemporary Issues and Recommendations for Affective Science
Authors: Walle Eric A. , Dukes Daniel 
Published: September 2023

AbstractValence is central to the experience of emotion. However, to the detriment of affective science, it is often ill-defined and poorly operationalized. Being more precise about what is meant by valence would make for more readily comparable emotion stimuli, methodologies, and results, and would promote consideration of the diversity, complexity, and function of discrete emotions. This brief review uses prior literature and an informal survey of affective scientists to illustrate disagreements in conceptualizing valence. Next, we describe issues of valence in affective science, particularly as they pertain to the emotion process, the functions of emotion, and precision in empirical research. We conclude by providing recommendations for the future of valence in affective science.