bluuebunny/crossref_metadata_2025_split huggingface dataset:
Psychosomatische Störungen der Lenden-Becken-Hüft-Region
Authors: Aigner Martin 
Published: January 2025

Zusammenfassung
Die International Association for the Study of Pain definiert Schmerz „als eine unangenehme sensorische und emotionale Erfahrung, die mit tatsächlichem oder drohendem Gewebeschaden verbunden ist oder dieser ähnelt“. Dazu werden folgende Anmerkungen gemacht, die für die psychische Perspektive besonders bedeutend sind: 1) Schmerz ist immer eine persönliche Erfahrung, die in unterschiedlichem Maße von biologischen, psychologischen und sozialen Faktoren beeinflusst wird. 2) Schmerz und Nozizeption sind unterschiedliche Phänomene. Schmerzen können nicht allein aus der Aktivität sensorischer Neuronen abgeleitet werden. 3) Durch ihre Lebenserfahrungen lernen Menschen das Konzept des Schmerzes kennen. Der Bericht einer Person über eine Schmerzerfahrung sollte respektiert werden. 4) Obwohl Schmerzen normalerweise eine adaptive Rolle spielen, können sie negative Auswirkungen auf die Funktion sowie das soziale und psychologische Wohlbefinden haben. 5) Die verbale Beschreibung ist nur eines von mehreren Verhaltensweisen, um Schmerz auszudrücken. 6) Unfähigkeit zu kommunizieren, schließt nicht die Möglichkeit aus, dass ein Mensch Schmerzen erfährt. Die psychiatrisch-psychosomatische Perspektive kann bei einer gestörten Lenden-Becken-Hüft-Region dazu beitragen, die möglichen psychischen Risikofaktoren zu identifizieren oder Zusammenhänge mit der körperlichen Symptomatik zu erkennen und zu behandeln. Insbesondere bei chronischen Schmerzen ist ein Perspektivenwechsel notwendig. Die häufigste Form von Schmerzverhalten ist das Ignorieren von Schmerzen, um Alltagsaktivitäten aufrechtzuerhalten (suppressive Schmerzverarbeitung). Einseitig suppressives Verhalten kann genauso wie das von der Angst, sich zu schädigen, verstärkte Vermeidungsverhalten zu einer Chronifizierung beitragen. Eine Lösung aus der Schmerzspirale kann das flexible Schmerz-Coping darstellen. Durch die vernetzte Betrachtung von Körper und Psyche können psychosomatische Faktoren identifiziert werden, die zur Entstehung oder Aufrechterhaltung der Beschwerden beitragen. Eine entsprechende multidisziplinäre Behandlung kann dann sowohl körperliche als auch psychische Aspekte, wie z. B. Angst, Depression, Somatisierung, Traumatisierung, fehlgeleiteter Schmerzmittelgebrauch, Schlafstörungen, sexuelle Funktionsstörungen oder Suizidalität berücksichtigen, um die Genesung zu unterstützen und um aus der Chronifizierungsspirale des Schmerzes auszusteigen.
Acceptance of online therapy for children and adolescents with digital media use disorders: perspectives from child and adolescent psychiatrists and psychotherapists in Germany
Authors: Busch K. , ten Hoor G. A. , Paschke K. , Thomasius R. , Arnaud N. 
Published: January 2025

Abstract
Online therapies have the potential to improve access to psychological services for individuals in need while alleviating the burden on healthcare systems. However, child and adolescent psychiatrists and psychotherapists (CAPPs) rarely integrate these services into their daily practice. This exploratory study investigates CAPPs’ acceptance of online therapy, with a focus on treating children and adolescents with digital media use disorders (DMUD). The study aimed to examine attitudes toward online therapy for DMUD treatment and to identify barriers and facilitating factors to its implementation. A cross-sectional online survey (5–10 min) was distributed to 1000 members of a German practitioner network, with 142 respondents completing it in full. Attitudes toward online therapy were assessed using adapted versions of the Attitude towards Telemedicine in Psychiatry and Psychotherapy (ATiPP) questionnaire. Barriers and facilitating factors were explored using open-ended questions. Descriptive statistics, correlations, and regressions were used to analyze the closed-ended questions, while responses to open-ended questions were categorized. CAPPs reported considerable experience with DMUD, but less experience with online therapy. Attitudes towards online therapy were generally neutral, with less favorable views on its use for DMUD treatment. Key barriers to implementation in outpatient care included technical challenges, lack of personal contact or control, and concerns about data security. Facilitators included access to adequate technical resources, user-friendly and evidence-based programs, interactive tools, and opportunities for regular face-to-face interactions. The results highlight the need to develop online therapy solutions that align practitioners’ needs and acceptance. However, further qualitative and quantitative research with more representative samples is essential for a more comprehensive understanding of this topic.
Digital forgetting in large language models: a survey of unlearning methods
Authors: Blanco-Justicia Alberto , Jebreel Najeeb , Manzanares-Salor Benet , Sánchez David , Domingo-Ferrer Josep , Collell Guillem , Eeik Tan Kuan 
Published: January 2025

Abstract
Large language models (LLMs) have become the state of the art in natural language processing. The massive adoption of generative LLMs and the capabilities they have shown have prompted public concerns regarding their impact on the labor market, privacy, the use of copyrighted work, and how these models align with human ethics and the rule of law. As a response, new regulations are being pushed, which require developers and service providers to evaluate, monitor, and forestall or at least mitigate the risks posed by their models. One mitigation strategy is digital forgetting: given a model with undesirable knowledge or behavior, the goal is to obtain a new model where the detected issues are no longer present. Digital forgetting is usually enforced via machine unlearning techniques, which modify trained machine learning models for them to behave as models trained on a subset of the original training data. In this work, we describe the motivations and desirable properties of digital forgetting when applied to LLMs, and we survey recent works on machine unlearning. Specifically, we propose a taxonomy of unlearning methods based on the reach and depth of the modifications done on the models, we discuss and compare the effectiveness of machine unlearning methods for LLMs proposed so far, and we survey their evaluation. Finally, we describe open problems of machine unlearning applied to LLMs and we put forward recommendations for developers and practitioners.
Accelerating machine learning queries with linear algebra query processing
Authors: Sun Wenbo , Katsifodimos Asterios , Hai Rihan 
Published: January 2025

Abstract
The rapid growth of large-scale machine learning (ML) models has led numerous commercial companies to utilize ML models for generating predictive results to help business decision-making. As two primary components in traditional predictive pipelines, data processing, and model predictions often operate in separate execution environments, leading to redundant engineering and computations. Additionally, the diverging mathematical foundations of data processing and machine learning hinder cross-optimizations by combining these two components, thereby overlooking potential opportunities to expedite predictive pipelines. In this paper, we propose an operator fusion method based on GPU-accelerated linear algebraic evaluation of relational queries. Our method leverages linear algebra computation properties to merge operators in machine learning predictions and data processing, significantly accelerating predictive pipelines by up to 317x. We perform a complexity analysis to deliver quantitative insights into the advantages of operator fusion, considering various data and model dimensions. Furthermore, we extensively evaluate linear algebra query processing and operator fusion utilizing the widely-used Star Schema and TPC-DI benchmarks. Through comprehensive evaluations, we demonstrate the effectiveness and potential of our approach in improving the efficiency of data processing and machine learning workloads on modern hardware.
Electrospinning vs Fluorescent Organic Nano-Dots: A Comparative Review of Nanotechnologies in Organoluminophores Utilization
Authors: Hancharova Marharyta , Dupla Aleksandra , Cabaj Joanna , Zając Dorota 
Published: January 2025

Abstract
This review explores the pivotal roles of two advanced nanotechnologies—electrospinning (ES) and fluorescent organic nano-dots (FONs) in the development and application of organoluminophores (OLs). As demand intensifies for innovative OL-based systems in fields such as biomedical imaging, drug delivery, materials engineering, sensing, and energy, ES and FONs present complementary yet distinct technological pathways. Each method offers unique advantages in optimizing material properties, compatibility, and optical performance, positioning them at the forefront of OL-based research. ES enables precise control over material structure, enhancing performance for scalable industrial applications. FONs deliver superior optical properties, particularly for bio-imaging, through environmentally friendly synthesis. This comparative analysis critically examines the strengths and limitations of both techniques, including aspects of synthesis complexity, material adaptability, functional enhancement, and industrial utilization. Furthermore, recent advancements, ongoing challenges, and future prospects within this rapidly evolving field are discussed, providing a comprehensive perspective on the potential of these luminescent technologies to drive next-generation OL applications.

Graphical Abstract
Thermal Transport in Long-Range Interacting Harmonic Chains Perturbed by Long-Range Conservative Noise
Authors: Andreucci Francesco , Lepri Stefano , Mejía-Monasterio Carlos , Ruffo Stefano 
Published: January 2025

Abstract
We study non-equilibrium properties of a chain of N oscillators with both long-ranged harmonic interactions and long-range conservative noise that exchange momenta of particle pairs. We derive exact expressions for the (deterministic) energy-current auto-correlation at equilibrium, based on the kinetic approximation of the normal mode dynamics. In all cases the decay is algebraic in the thermodynamic limit. We distinguish four distinct regimes of correlation decay depending on the exponents controlling the range of deterministic and stochastic interactions. Surprisingly, we find that long-range noise breaks down the long-range correlations characteristic of low dimensional models, suggesting a normal regime in which heat transport becomes diffusive. For finite systems, we do also derive exact expressions for the finite-size corrections to the algebraic decay of the correlation. In certain regimes, these corrections are considerably large, rendering hard the estimation of transport properties from numerical data for the finite chains. Our results are tested against numerical simulations, performed with an efficient algorithm.
Impaired visual and verbal statistical learning in children with Dyslexia in a transparent orthography
Authors: Mateus-Moreno Angélica , Lara-Diaz Maria Fernanda , Adrover-Roig Daniel , Aguilar-Mediavilla Eva , Jiménez-Fernández Gracia 
Published: January 2025

Abstract
Recent research suggests that performance on Statistical Learning (SL) tasks may be lower in children with dyslexia in deep orthographies such as English. However, it is debated whether the observed difficulties may vary depending on the modality and stimulus of the task, opening a broad discussion about whether SL is a domain-general or domain-specific construct. Besides, little is known about SL in children with dyslexia who learn transparent orthographies, where the transparency of grapheme-phoneme correspondences might reduce the reliance on implicit learning processes. The present study investigates the impact of SL in Spanish, a transparent orthography, among 50 children aged 9 to 12 years, with and without dyslexia. For this purpose, we used four SL tasks to evaluate two modalities (auditory/visual) and two stimulus type (verbal/nonverbal) and evaluated both accuracy and response times on each condition. The findings reveal that children with dyslexia in Spanish exhibit lower performance on SL tasks (accuracy) compared to the control group, regardless of the modality and stimulus type used. However, children with dyslexia struggle the most with tasks that involve visual material. This indicates that children with dyslexia in transparent orthographies have particular difficulties in extracting distributional probabilistic information in the absence of explicit learning instructions. Notably, difficulties were more pronounced in visual tasks involving verbal stimuli. The present results help to better understand the underlying mechanisms involved in reading acquisition in children with dyslexia.
Current drawbacks and future perspectives in the diagnosis and treatment of male factor infertility, with a focus on FSH treatment: an expert opinion
Authors: Santi D. , Corona G. , Salonia A. , Ferlin A. 
Published: January 2025

Abstract

Purpose
Infertility is defined as the inability to conceive after 1 year of unprotected intercourse, affecting approximately 15–20% of couples in Western countries. It is a shared problem within the couple; when the main issue lies with one of the partners, it is preferable to refer to “male factor” or “female factor” infertility rather than simply male or female infertility. Despite male factor infertility accounting for half of all couple infertility cases, the clinical approach to the male partner is not uniformly standardized across international guidelines.

Methods
To provide an expert overview, we have comprehensively reviewed and critically analyzed the most up-to-date literature on this sensitive topic, leading to the development of a proposal for tailored assessment of the diagnostic-therapeutic pathway and preventive strategies. The diagnostic approach also considers that infertile men are objectively less healthy than their fertile counterparts of the same age and ethnicity.

Results
This article discusses the diagnostic flow, the classification of male factor infertility, the definition of idiopathic infertility, the involvement of general health, and treatment recommendations, emphasizing follicle-stimulating hormone treatment in selected groups of patients.

Conclusion
We provide expert opinion on current drawbacks and future perspectives in this field, with practical advice for the clinical practice of general practitioners and expert in reproductive medicine.
Healer’s Art in the Online Era: Successes, Challenges, and Implications
Authors: Manger Jeannette K. , McManamon Alyssa C. , Todd Amber , Stolfi Adrienne , Parmelee Dean X. , Andarsio Evangeline 
Published: January 2025

Abstract

Purpose
Healer’s Art (HART), a health professional elective course, shifted to online platforms during the pandemic year (2020–2021). Because HART focuses on affective domain aspects of such education, the question arose of its validity and efficacy in the online format. This study aimed to identify challenges and experiences of online versus in-person HART learners.

Methods
The authors compared students’ end-of-course evaluations between in-person and online cohorts across 3 years. The evaluations included Likert scale responses compared between cohorts with Fisher’s exact tests. Novel questions with narrative responses in the online cohort’s evaluation captured information on challenges with the online platform. Narrative responses were analyzed using constant comparative analysis.

Results
No difference was found between in-person (n = 654) and online cohorts (n = 570) in ratings of good/excellent for the overall course (1111/1203, 92.4%), course faculty (1184/1214, 97.5%), and small group experience (1142/1208, 94.5%). Thematic analysis of narrative responses indicated that online HART engagement supported student development of community, professional identity formation, self-care, and relationships.

Conclusions
The findings suggest that HART effectively supports affective domain learning in medical and health professional students whether delivered in-person or online. The authors share challenges and successes of online HART, thus increasing the delivery versatility of this course.
Local Permutation Polynomials of Maximum Degree Over Prime Finite Fields
Authors: Gutierrez Jaime , Jiménez Urroz Jorge 
Published: January 2025

Abstract
Let q be a power of a prime p,

$$\mathbb {F}_q$$

F
q

be the finite field with q elements, and

$$\mathbb {F}_q[x_1,\ldots , x_n]$$

F
q

[

x
1

,
…
,

x
n

]

be the ring of polynomials in n variables over

$$\mathbb {F}_q$$

F
q

. The construction and study of local permutation polynomials of

$$\mathbb {F}_q[x_1,\ldots , x_n]$$

F
q

[

x
1

,
…
,

x
n

]

is recently increasing interest among the experts. In this work, we study local permutation polynomials of maximum degree

$$n(q-2)$$

n
(
q
-
2
)

defined over the prime finite field

$$\mathbb {F}_p$$

F
p

. In particular, we explicitly construct families of such polynomials when

$$p\ge 5$$

p
≥
5

and

$$n \le p-1$$

n
≤
p
-
1

; and for any q of the form

$$q=p^{pr}$$

q
=

p

pr

when

$$r\ge 1$$

r
≥
1

and

$$p \ge 3$$

p
≥
3

.
Artificial intelligence’s (AI’s) role in enhancing tax revenue, institutional quality, and economic growth in selected BRICS-plus countries
Authors: Saba Charles Shaaba , Monkam Nara 
Published: January 2025

Abstract
The BRICS countries, comprising Brazil, Russia, India, China, and South Africa, aim to achieve United Nations Sustainable Development Goal 8, which emphasizes sustainable economic growth. This study adds to the empirical literature by examining the impact of tax revenue and institutional quality on economic growth, incorporating the role of artificial intelligence (AI) in selected BRICS-Plus countries (the above-mentioned five countries) from 2012 to 2022. Utilizing the innovative Cross-Sectional Augmented Autoregressive Distributed Lag estimation technique, the analysis reveals a long-run equilibrium relationship among the variables. The study employs a modified Cobb–Douglas production function for its theoretical framework. The results indicate bidirectional causality between tax revenue and AI, economic growth and institutional quality, as well as institutional quality and tax revenue. Based on these findings, the study recommends that BRICS governments and policymakers enhance the integration of AI into tax systems to promote growth in both the short and long terms. However, it also advises caution regarding the interaction between AI and institutional quality, which did not support economic growth. While the AI and tax revenue interaction shows promise for fostering growth, robust measures are necessary to mitigate potential negative effects from AI’s interaction with institutional quality. Consequently, the study advocates for the development of AI-friendly institutional policies in BRICS countries, considering the dynamic and rapidly evolving AI sector.
Technology and the Labour Process: Insights from Indian E-Commerce Warehouses
Authors: Nataraj Manikantha , Taylor Philip , Briken Kendra 
Published: January 2025

Abstract
In the context of innovation in and the application of information and communication technology (ICT), this article seeks to understand how ICT-enabled tools, including algorithmic processing interfaces, cloud computing software, QR codes and barcodes, have become a new managerial equipment for organising, controlling, and disciplining the labour force in the warehouses of e-commerce enterprises in India. This article engages with labour process theory which accords analytical importance to technology in organising work, for managerial control and disciplinary regimes in furtherance of capital accumulation. The evidence here derives from four month’s field work in 2022–23 from Bangalore in south India. Data were generated from 74 semi-structured interviews with employees of, principally, Amazon and Flipkart. The major findings are that an integrated, digitised control system operating in tandem with direct human supervision, ensures the simultaneous processing of products orders and the monitoring of workers’ performance. Further, it investigates how they contribute to work intensification and exacerbated job-related insecurities and vulnerabilities. The outcome is extreme work intensity and the creation of new forms of worker insecurity and vulnerability.
"Theory of Pore Conflation" and "Shubhjyot's equation" in the treatment of Brilliant green dye-contaminated water using Jamun leaves biochar
Authors: Sutar Shubham , Jadhav Jyoti 
Published: January 2025

Abstract
This study investigates the adsorption of Brilliant Green (BG) dye onto biochar derived from Syzygium cumini (Jamun) leaves (JLB). Biochar was produced via pyrolysis at 800 °C and examined employing various methods, including Scanning electron microscopy (SEM–EDX), Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), Brunauer–Emmett–Teller (BET) analysis, Raman spectroscopy, Zeta potential and X-ray photoelectron spectroscopy (XPS). The optimum parameters for BG dye adsorption, determined by batch adsorption studies, were a temperature of 80 °C, an initial dye concentration of 500 mg L−1, a contact period of 30 min, and an agitation speed of 400 RPM. The maximum adsorption capacity of JLB for BG was 243.90 mg g−1. It was found that the adsorption process adhered to the Freundlich isotherm model and pseudo-second-order kinetics, revealing heterogeneous adsorption with chemisorption. A novel "Theory of Pore Conflation" was proposed to explain enhanced adsorption at higher temperatures, supported by SEM and FTIR analyses. Additionally, a new equation termed "Shubhjyot's equation" was introduced to account for time dependency in adsorption capacity calculations. The thermodynamic analysis demonstrated that the process is endothermic and spontaneous. Isopropanol was the most effective organic solvent for desorption studies, demonstrating biochar regeneration potential for up to five cycles. Phytotoxicity and cyto-genotoxicity assessments demonstrated the environmental safety of JLB compared to BG dye. The use of JLB production offers a way to repurpose agricultural waste, contributing to circular economy principles. This extensive study demonstrates JLB's promise as an effective, economical, and environmentally safe adsorbent for wastewater treatment that eliminates textile dyes.

Graphical Abstract
The place of school-based strategies for universal, selective and indicated prevention for depression
Authors: Birrell Louise , Grummitt Lucinda , Christensen Helen , Teesson Maree 
Published: January 2025

Abstract
In response to the question, ‘What is the place of universal, selective and indicated prevention strategies for depression and other mood disorders?’ posed by Hickie et al. (2024), we examine the role of school-based strategies for universal and targeted (including selective and indicated) prevention of depression. Schools represent a unique opportunity for systematic evidence-based depression prevention, targeting key developmental risk periods before peak depression onset. However, the realisation of this potential has been challenging particularly for universal approaches. We summarise the evidence for each of these tiers of prevention, including recent large-scale trials of universal prevention in high-income countries. Targeted approaches show more consistent preventive effects on depression however hold significant implementation challenges in the school context. We provide recommendations about the next steps for the field including a continuum of support across all levels of prevention outlined above and broadening current strategies to focus on the school contexts and structural factors in which prevention programs are delivered, as well as teacher mental health.