bluuebunny/crossref_metadata_2025_split huggingface dataset:
Investigating the influence of square size vanes on heat transfer in porous media: an in-depth Nusselt distribution
Authors: Jalili Bahram , Bahmani Musa , Jalili Payam , Liu Dong , Alderremy A A , Ganji Davood Domiri , Vivas-Cortez Miguel 
Published: November 2024

Abstract
This research provides an extensive analysis with various γ on natural convection, thermal entropy generation, fluid flow, and temperature distribution in the porous cavity. The impact of the studied geometrical parameters, Ha, Da, Pr, γ, and ε, on the thermal performance is carefully examined. The finite element method (FEM) is carried out to analyze fluid flow and heat distribution in the present porous media. For an in-depth analysis of the thermal performance, the novel aspects of this research are thought to be important parameters that comprise Ha, Da, Pr, γ, and ε for significant assessments of the average Nusselt number in porous media with varying square size vanes at the corners and effect variable cooled size at the corners of the square porous cavity. In validation, the calculation of the results was adapted accurately to the FEM’s fluid flow, temperature distribution, and average Nusselt number. Numerical results revealed that various γ affected widely in the generation of entropy. Additionally, the hot and cold temperature distribution of fluid flow was significantly impacted by the square-sized vanes in the corners of the porous chamber. The average Nusselt number showed a significant increase, with the Hartman number being the most significant contributor. Moreover, as the Darcy number grew, the average Nusselt number rose apart from γ = 1 in porous media with size vanes 0.2.
High-performance surface defect detection of aluminum substrate based on event camera
Authors: Tang Jing , Gong Zeyu , Fan Yajun 
Published: November 2024

Abstract
Traditional industrial surface defect detection method often employs CCD/CMOS cameras, but they are unable to detect the minute defects on aluminum substrates in highly dynamic industrial scenes due to their nature. Event camera is a novel high-resolution vision sensor that measures per-pixel brightness changes in an asynchronous manner and outputs as event information flow (EIF). Small and weak defects on aluminum substrate can be captured by event camera effectively, but the EIF contains a large amount of noise, making it difficult to perform accurate and high-precision defect detection. To address this problem, we propose a frame aggregation method to realize good event information flow processing, and then use an improved circle detection method to locate the aluminum substrate in each frame, removing abundant event information outside the aluminum substrate. Subsequently, we enhance the event signals under different frames based on optical flow tracking using multiple features, and construct a semi-supervised detector based on pseudo-labels to achieve high-precision defect localization. Finally, considering the small inter-class differences in defects on the surface of aluminum substrates, we construct a defect class corrector based on ensemble learning to enhance the ability to determine defect classes, achieving high-precision automatic quality inspection of aluminum substrate surfaces. The performance of our method is compared with other advanced methods based on event camera data of aluminum substrates in real industrial scenarios. The experimental results show that our method has improved the detection accuracy by ∼10% and the classification accuracy by ∼25% compared to the original state-of-the-art methods.
Fog computing-enabled adaptive prognosis of cutting tool remaining life through multi-source data
Authors: Liang Yuchen , Wang Yuqi , Gu Chengyi , Tang Jie , Pang Xianjuan 
Published: November 2024

Abstract
Predicting cutting tool remaining life is important to sustainable machining. Accurate wear assessment improves efficiency, reduces waste, and lowers costs by minimizing tool failure. Traditional prognosis methods are often crippled by the inability to adapt to diverse working conditions across the machining process lifecycle. This paper introduces a fog computing-enabled adaptive prognosis framework utilizing multi-source data to address these challenges effectively. The key innovations include the following: (1) the proposed system integrates power and vibration data collected from LGMazak VTC-16A and IRON MAN QM200 machines. A standardized data fusion method combines multi-source data to enhance robustness and accuracy. (2) The transformer model is employed to improve prognosis accuracy of cutting tool remaining life; best accuracy of 98.24% and an average accuracy of 97.63% are achieved. (3) Finite element analysis is incorporated to validate the model’s predictions to validate reliability of deep learning model. (4) The fog computing optimization mechanism based on the bees algorithm, which shows fitness value of 0.92 and convergence within 15 iterations. The proposed method reduces total data volume in cloud by 54.12%, prediction time by 33.64%, and time complexity in the cloud layer by 4.62%. The effectiveness of fog computing in improving the operational efficiency and reliability of manufacturing systems is validated through the integration of advanced data analytics and deep learning techniques.
Selection, inheritance, life-history traits, and flight capacity of Grapholita molesta (Lepidoptera: Tortricidae) resistant to lambda-cyhalothrin
Authors: Zhang Xiaohe , Su Sha , Jian Chengzhi , Huang Baojian , Zhang Jilong , Suo Jinbo , Peng Xiong , Chen Maohua 
Published: November 2024

Abstract
Grapholita molesta (Busck) (Lepidoptera: Tortricidae) is a globally significant fruit pest traditionally managed using chemical insecticides such as lambda-cyhalothrin. However, repeated applications have led to the development of resistance in field populations. The mechanisms and fitness costs associated with lambda-cyhalothrin resistance in G. molesta remain poorly understood. In this study, we established a lambda-cyhalothrin-resistant strain (RS) of G. molesta through continuous selection with lambda-cyhalothrin in the laboratory for 21 generations, resulting in a 249.6-fold increase in resistance. Bioassay data from the F1 progeny (F1RS and F1SR) of reciprocal crosses between RS and susceptible strain (SS) showed similar degrees of dominance (0.40 for F1RS and 0.32 for F1SR). Significant differences between observed and expected mortalities of backcross individuals suggested that resistance to lambda-cyhalothrin is polygenic. Compared to the SS strain, the RS strain exhibited significantly prolonged periods of larval, prepupal, and pupal stages, as well as a significant decrease in larval weight. In addition, the RS strain showed significant reductions in fecundity, cumulative flight distance, maximum flight distance, cumulative flight time, maximum flight time, and average flight speed. These results suggest that resistance to lambda-cyhalothrin in G. molesta is autosomal, incompletely dominant, and polygenic. Life-history traits such as fecundity and flight capacity were significantly reduced in RS strains compared with the SS strain. These findings provide valuable insights for mitigating lambda-cyhalothrin resistance development and promoting sustainable control of G. molesta in the field.
Evaluation method of progressive failure of loess slope under shallow coal seam mining
Authors: Zhao Bingchao , He Shenglin , Wang Wei , Lu Xiaoxiao , Chen Yaozong , Guo Yaxin 
Published: November 2024

Abstract
When mining coal under a loess gully, the surface slopes may exhibit significant discontinuous failure characteristics such as local failure and landslides. These characteristics, composed of failure and non-failure regions, form an essentially unstable mechanical system. This makes it difficult to obtain a true solution using continuous medium mechanics, greatly increasing the complexity of slope failure evaluation and management. To accurately evaluate the degree of slope failure during mining, clarify its mechanism, and propose appropriate management measures, the Ningtiaota Coal Mine in northern Shanxi was selected as the study area. Based on the unbalanced thrust method and the probability integral settlement prediction theory, and utilizing numerical calculations, we propose a method for evaluating and managing slope failure in coal mining under loess gully. This method describes the changes in slope failure during mining through the deformation failure ratio of the slip surface and quantifies the degree of slope failure at different mining times, revealing the full process stability evolution characteristics of points and surfaces as the critical state of the slope progresses. When the deformation failure ratio of the slip surface is ≥1, it indicates overall slope failure and the beginning of slope sliding instability; when the deformation failure ratio of the slip surface is &lt;1, it indicates local slope failure. Based on this, corresponding management methods are proposed according to the mechanical distribution characteristics of the slope slip surface in different stress areas. The research results were applied in the Ningtiaota Coal Mine in northern Shanxi, yielding positive outcomes.
How do we justify research into enhanced warfighters?
Authors: Evans Nicholas G , Hereth Blake , Gross Michael L , Moreno Jonathan D 
Published: November 2024

Abstract
State militaries have strong interests in developing enhanced warfighters: taking otherwise healthy service personnel (soldiers, marines, pilots, etc.) and pushing their biological, physiological, and cognitive capacities beyond their individual statistical or baseline norm. However, the ethical and regulatory challenges of justifying research into these kinds of interventions to demonstrate the efficacy and safety of enhancements in the military has not been well explored. In this paper, we offer, in the context of the US Common Rule and Institutional Review Board framework, potential justifications for justifying research into enhancing warfighters on the grounds of (i) individual and group risk reduction; (ii) protection of third parties such as civilians; and (iii) military effectiveness.
Prediction of breast cancer risk for adolescents and young adults with Hodgkin lymphoma
Authors: Roberti Sander , van Leeuwen Flora E , Diallo Ibrahima , de Vathaire Florent , Schaapveld Michael , Leisenring Wendy M , Howell Rebecca M , Armstrong Gregory T , Moskowitz Chaya S , Smith Susan A , Aleman Berthe M P , Krul Inge M , Russell Nicola S , Pfeiffer Ruth M , Hauptmann Michael 
Published: November 2024

Abstract

Background
Although female survivors of Hodgkin lymphoma (HL) have an increased risk of breast cancer (BC), no BC risk prediction model is available. We developed such models incorporating mean radiation dose to the breast or breast quadrant-specific radiation doses.

Methods
Relative risks and age-specific incidence for BC and competing events (mortality or other subsequent cancer) were estimated from 1194 Dutch 5-year HL survivors, treated at ages 11-40 during 1965-2000. Predictors were doses to 10 breast segments or mean breast radiation dose, BC family history, year of and age at HL diagnosis, and ages at menopause and first live birth. Models were independently validated using US Childhood Cancer Survivor Study cohort participants.

Results
Predicted absolute BC risks 25 years after HL diagnosis ranged from 1.0% for survivors diagnosed at ages 20-24 with less than 10 Gy mean breast radiation dose and who were menopausal 5 years after HL diagnosis, to 22.0% for survivors 25-29 years at diagnosis, with at least 25 Gy mean breast dose and no menopause within 5 years. In external validation, the observed/expected BC case ratio was 1.19 (95% confidence interval 0.97 to 1.47) for the breast segment-specific dose model, and 1.29 (1.05 to 1.60) for the mean breast dose model. The areas under the receiver operating characteristic curve were 0.68 (0.63 to 0.74) and 0.68 (0.62 to 0.73), respectively.

Conclusion
Breast segment-specific or mean breast radiation dose with personal and clinical characteristics predicted absolute BC risk in HL survivors with moderate discrimination but good calibration, rendering the models useful for clinical decision-making.
A qualitative account of mothers of pediatric heart transplant recipients’ experience at a pilot mindfulness-based retreat: insights for implementation
Authors: Lin Jia , Selkirk Enid K , Ahola Kohut Sara , Mitchell Joanna , Robertson Taylor , Donma Ani Jamyang , Seifert-Hansen Mirna , Telfer Heather , Anthony Samantha J 
Published: November 2024

Abstract

Objective
To explore participants’ shared experience attending a pilot mindfulness-based retreat (MBR) intervention supporting the psychological well-being of mothers of pediatric heart transplant (HTx) recipients.

Methods
A qualitative description approach was used within a larger hybrid mixed-methods pilot study evaluating the implementation-effectiveness of a 2-day MBR tailored specifically for a pediatric HTx population. A purposive sample of mothers was recruited from a leading Canadian pediatric HTx center, and each represented a primary, female-identifying caregiver, sharing residence with a pediatric HTx recipient of at least 4 months post-transplant. Two focus groups were conducted after and 16 individual interviews 3 months after the MBR to elicit participants’ in-depth experience attending the MBR. Reflexive thematic data analysis led to theme development through an iterative process with consensus among team members.

Results
Sixteen mothers of pediatric HTx recipients (mean patient age 9.8 years; mean time post-transplant 8.2 years) participated in the MBR held in Ontario, Canada. Qualitative findings illuminated mothers’ shared experience attending the MBR, reflecting three themes that describe key intervention elements beyond those affiliated with mindfulness practice alone: “respite,” “readiness,” and “relationships.” Findings highlight acceptability and appropriateness as distinct yet interrelated implementation outcomes.

Conclusions
Elements of “respite,” “readiness,” and “relationships” are key components of the MBR experience that offer valuable intervention and clinical considerations related to mothers’ psychological well-being. Aligning intervention acceptability and appropriateness through tailored strategies may aid implementation. Future research considering maternal readiness relative to support intervention participation is warranted.
Engression: extrapolation through the lens of distributional regression
Authors: Shen Xinwei , Meinshausen Nicolai 
Published: November 2024

Abstract
Distributional regression aims to estimate the full conditional distribution of a target variable, given covariates. Popular methods include linear and tree ensemble based quantile regression. We propose a neural network-based distributional regression methodology called ‘engression’. An engression model is generative in the sense that we can sample from the fitted conditional distribution and is also suitable for high-dimensional outcomes. Furthermore, we find that modelling the conditional distribution on training data can constrain the fitted function outside of the training support, which offers a new perspective to the challenging extrapolation problem in nonlinear regression. In particular, for ‘preadditive noise’ models, where noise is added to the covariates before applying a nonlinear transformation, we show that engression can successfully perform extrapolation under some assumptions such as monotonicity, whereas traditional regression approaches such as least-squares or quantile regression fall short under the same assumptions. Our empirical results, from both simulated and real data, validate the effectiveness of the engression method. The software implementations of engression are available in both R and Python.
Approaches to Digital Humanities Pedagogy: a systematic literature review within educational practice
Authors: Georgopoulou Maria Sofia , Troussas Christos , Triperina Evangelia , Sgouropoulou Cleo 
Published: November 2024

Abstract
Over the years, Digital Humanities Pedagogy has swiftly evolved, with a growing emphasis on the intersection between Computing and Humanities. However, in the associated literature, a lack of clarity has been found regarding the adoption of diverse approaches to DH pedagogy in different educational settings. This study tackles this research gap by analyzing the current state of knowledge in the field through a Systematic Literature Review. The aim of this review is to investigate the topic and provide an overview of the approaches currently being employed within educational practice, while also identifying areas that require additional investigation. The time frame of the reviewed studies spans from 2012 to 2022. After distinguishing between studies that deal with DH as a subject of study and those that deal with DH as a field of application, the analysis will focus on the latter category. Specifically, the review will examine the level of education and courses that employ DH educational practice, the types of technology used and their intended purpose, the literacies involved, and the aspects of digital resources and practices that are critically studied. By shedding light on the diverse practices employed in different educational settings, the findings reveal a notable gap in primary and secondary education and a lack of critical analysis toward digital resources and practices, suggesting important new directions for future research.
Behavioral Interventions for Tobacco Cessation in Low- and Middle-Income Countries: A Systematic Review and Meta-analysis
Authors: Nadkarni Abhijit , Gaikwad Leena , Sequeira Miriam , Javeri Pranay , Benoy Deepthy , Pacheco Marimilha Grace , Velleman Richard , Murthy Pratima , Naughton Felix 
Published: November 2024

Abstract

Introduction
An estimated 78% of the total deaths attributable to smoking tobacco use occurred in low- and middle-income countries (LMICs) in 2019. In addition, smokeless tobacco increases the risk of all-cause mortality, all cancers, including upper aero-digestive tract cancer, stomach cancer, ischemic heart disease and stroke, with 88% of the mortality burden being borne by the South-East Asian region. Evidence-based interventions from high-income countries (HICs) are not easily transferable to LMICs, as patterns of tobacco use, health beliefs associated with tobacco use, and awareness of specific health risks vary substantially.

Methods
We synthesized the effectiveness of behavioral interventions for tobacco cessation in LMICs through a systematic review and meta-analysis. Interventional studies which delivered individual behavioral intervention and assessed abstinence from tobacco use were included. We examined the pooled intervention effect at 6 months postintervention follow-up.

Results
For continuous abstinence at 6 months, the intervention was superior to the active comparator (RR 2.32; 95% CI 1.78 to 3.02) and usual care (RR 4.39; 95% CI 2.38 to 8.11). For point prevalence abstinence at six months, the intervention was superior to the active comparator (RR 1.76; 95% CI 1.28 to 2.44), and usual care (RR 2.37; 95% CI 1.47 to 3.81). The statistical heterogeneity was substantial to considerable for all comparisons. Only six studies had an overall low risk of bias. Publication bias was observed for all comparisons except for 6-month continuous outcomes.

Conclusions
Implementation research is needed to understand factors for programme sustainability and equity of the impact of behavioral interventions in reducing tobacco use in LMICs.

Implications
Our review is an important step towards understanding the effectiveness of behavior interventions for tobacco cessation suited for LMICs and which are responsive to the contextual needs of such countries.
Enterovirus D68: Genomic and Clinical Comparison of 2 Seasons of Increased Viral Circulation and Discrepant Incidence of Acute Flaccid Myelitis—Maryland, USA
Authors: Fall Amary , Abdullah Omar , Han Lijie , Norton Julie M , Gallagher Nicholas , Forman Michael , Morris C Paul , Klein Eili , Mostafa Heba H 
Published: November 2024

Abstract

Background
Enterovirus D68 (EV-D68) is associated with severe respiratory disease and acute flaccid myelitis (AFM). The 2022 outbreaks showed increased viral circulation and hospital admissions, but the expected rise in AFM cases did not occur. We analyzed EV-D68 genomes and infection outcomes from 2022 (a year without a national increase in AFM cases) and 2018 (a year with a national surge in AFM cases) to understand how viral genomic changes might influence disease outcomes.

Methods
Residual respiratory samples that tested positive for rhinovirus/enterovirus at the Johns Hopkins Health System between 2018 and 2022 were collected for EV-D68 polymerase chain reaction, genotyping, and whole genome sequencing. Clinical and metadata were collected in bulk from the electronic medical records.

Results
A total of 351 EV-D68 cases were identified, with most cases in children aged &lt;5 years. Infections in 2018 were associated with higher odds of hospital admissions and intensive care unit care. Of 272 EV-D68 genomes, subclades B3 and A2/D1 were identified with B3 predominance (95.2%). A comparative analysis of the 2018 and 2022 whole genomes identified a cluster of amino acids (554D, 650T, 918T, 945N, 1445I, 1943I) that was associated with higher odds of severe outcomes.

Conclusions
Our results show significant differences in the clinical outcomes of EV-D68 infections in 2018 and 2022 and highlight a 2018 cluster of genomic changes associated with these differences. Seasonal viral genomic surveillance—with in vitro characterization of the significance of these changes to viral fitness, immune responses, and neuropathogenesis—should shed light on the viral determinants of AFM.
Proinsulin C-peptide is a major source of HLA-DQ8 restricted hybrid insulin peptides recognized by human islet-infiltrating CD4+ T cells
Authors: Bhattacharjee Pushpak , Pakusch Miha , Lacorcia Matthew , Tresoldi Eleonora , Rubin Alan F , Foster Abby , King Laura , Chiu Chris Y , Kay Thomas W H , Karas John A , Cameron Fergus J , Mannering Stuart I 
Published: November 2024

Abstract
Type 1 diabetes (T1D) is an autoimmune disease that develops when T cells destroy the insulin-producing beta cells that reside in the pancreatic islets. Immune cells, including T cells, infiltrate the islets and gradually destroy the beta cells. Human islet-infiltrating CD4+ T cells recognize peptide epitopes derived from proinsulin, particularly C-peptide. Hybrid insulin peptides (HIPs) are neoepitopes formed by the fusion of two peptides derived from beta cell granule proteins and are known to be the targets of pathogenic CD4+ T cells in the non-obese diabetic (NOD) mouse and human islet-infiltrating CD4+ T cells. Proinsulin is widely recognized as a central antigen in T1D, but its role in forming HIPs is unclear. We developed a method to functionally screen TCRs derived from human islet-infiltrating CD4+ T cells and applied this to the identification of new proinsulin-derived HIPs. We generated a library of 4,488 candidate HIPs formed by fusion of proinsulin fragments and predicted to bind to HLA-DQ8. This library was screened against 109 islet-infiltrating CD4+ T cell receptors (TCRs) isolated from four organ donors who had T1D. We identified 13 unique HIPs recognized by nine different TCRs from two organ donors. HIP-specific T cell avatars responded specifically to a peptide extract from human islets. These new HIPs predominantly stimulated CD4+ T cell proliferation in peripheral blood mononuclear cells from individuals with T1D in contrast to HLA-matched controls. This is the first unbiased functional, islet-infiltrating T cell based, screen to identify proinsulin-derived HIPs. It has revealed many new HIPs and a central role of proinsulin C-peptide in their formation.