bluuebunny/crossref_metadata_2025_split huggingface dataset:
Aging Skin: A Dermatitis To Which All Flesh Is Heir?
Authors: Murphy George F. 
Published: January 2025

ABSTRACTThe human body is composed mostly of water fortified by a variety of proteins, fats, carbohydrates, vitamins, minerals, and other nutrients, all organized into an elegant structurally complex and functionally efficient machine in which our consciousness resides. This heterogeneous assemblage of essential ingredients is enclosed in a container known as the integument, or simply, the skin. The container is as important as its contents; when itself devoid of structural and functional integrity, it will both leak as well as become infused with potentially harmful external agents. As we age, skin loses its integrity, and over time it is not unreasonable to conceive of the skin as becoming progressively “leaky.” With this deterioration, skin becomes dry, scaly, accessible to microbes, pruritic, and inflamed, the latter setting up the potentially vicious cycle known as “inflammaging.” One major example of the effects of chronological aging on the barrier function of skin involves depletion of filaggrin, a 37‐kD histidine‐rich protein which originates within keratohyaline granules of the epidermis. Some of the consequences of age‐related filaggrin depletion may be inferred by experiments of nature known as ichthyosis vulgaris and atopic dermatitis (AD), the latter with atopy being the most common inflammatory disease worldwide. In AD, loss of function mutations in the FLG gene encoding for the filaggrin precursor, profilaggrin, are associated with skin that, as with aging, is also dry, scaly, accessible to microbes, pruritic and inflamed. In this mini‐review, AD will be compared and contrasted with aging in terms of the consequences of deficient filaggrin barrier function. The goal is to enhance recognition that one of the most clinically symptomatic and visible signs of aging is a subtle yet ubiquitous form of “dermatitis” due to “leaky” skin, one that may be addressed therapeutically with smart combinatorial strategies that restore the molecular basis for skin barrier dysfunction.
Developing and Validating a Scale of Artificial Intelligence Anxiety Among Chinese EFL Teachers
Authors: Liu Xinyu , Liu Yijia 
Published: January 2025

ABSTRACTAs artificial intelligence (AI) technology continues to advance, its influences across various industries have grown, leading to increasing levels of anxiety, including that in education. Nonetheless, in terms of current knowledge, the literature lacks a valid scale to measure AI anxiety among EFL teachers, particularly university EFL teachers. Moreover, the underlying dimensions of this construct have yet to be clarified. Against these gaps, this study aims to develop and validate a scale to assess AI anxiety among university EFL teachers in China. We used qualitative interviews and quantitative surveys combined to identify the key dimensions of AI anxiety of university EFL teachers. In so doing, 251 Chinese EFL teachers completed a newly designed scale. The result of exploratory factor analyses indicated five dimensions and 21 items in the questionnaire. Five dimensions were identified: technical proficiency, job displacement, technological support, student experience and research development. Next, another 415 Chinese EFL teachers participated in validating the scale. The result of confirmatory factor analysis indicated that the scale demonstrated strong reliability, validity and an acceptable model fit. This new scale provides a useful tool for assessing AI anxiety in EFL teachers and highlights the unique challenges they face in adapting to AI, offering a basis for future research and targeted support.
The Role of Gender Differences in Pre‐Service Turkish Physical Education Teachers' Attitudes Towards Teaching Profession: A Meta‐Analysis
Authors: Işıkgöz Mustafa Enes 
Published: January 2025

ABSTRACTThe aim of this study is to estimate the role of gender differences in the teaching profession in a meta‐analytic way, based on empirical findings analysing Turkish pre‐service physical education teachers' attitudes towards the teaching profession. For this purpose, studies, that were published in Türkiye between 2015 and 2023 were searched by following the PRISMA Protocol. As a final search we reached 65 studies and 28 of them met the criteria for inclusion in the meta‐analysis. The data analysis was made with JASP 0.16.4.0 software. As a result of the analysis, it was found that the effect of gender difference on the attitudes of Turkish pre‐service physical education teachers towards the teaching profession was weak (g = −0.159, 95% CI [−0.262, −0.055]). Also, the effect size distribution of the examined studies was found to be heterogeneous (Q = 112.350; p < 0.001; I2 = 81.178), and it was confirmed that there was no publication bias by Egger's (z = −0.853; p > 0.05) and Rosenthal's FSN (N = 438,000, p < 0.001) tests. In conclusion, the results of this meta‐analysis indicate that the impact of gender on the attitudes of Turkish pre‐service physical education teachers towards the teaching profession is relatively weak and appears to favour women. It is recommended that further research be conducted to ascertain whether this gender‐based difference in attitudes will evolve over time. Additionally, it would be prudent for higher education institutions and education policymakers to implement measures to mitigate the influence of gender stereotypes in the teaching profession.
A Novel Hyper‐Tuned Multilayer Perceptron With Effective Stochastic Learning Strategies for Missing Values Imputation
Authors: Siddiqi Muhammad Hameed , Alruwaili Madallah , Alhwaiti Yousef , Alanazi Saad , Khan Faheem 
Published: January 2025

ABSTRACTA vast amount of data in many different formats is produced and stored daily, offering machine learning a valuable resource to enhance its predictive capabilities. However, the pervasiveness of inaccuracies in real‐world data presents a significant barrier that can seriously limit the effectiveness of learning algorithms. The ensemble models and hyper‐tuned multi‐layer perceptron (MLP) with need‐based hidden neuron layers are effective frameworks for data imputation. Addressing the issue of missing data is a complex and demanding task, and much remains to be explored in developing effective and precise methods for predicting and imputing missing values across different datasets. The study offers important perspectives on using algorithms in machine learning to predict and impute gaps in data in recently updated datasets. The findings indicate that finely tuned MLP classifiers notably improve prediction accuracy and dependability compared to models with a static or reduced number of neurons. Furthermore, the study highlights the promising potential of ensemble models within the error‐correcting output code (ECOC) framework as an effective approach for this task. It also suggests future research directions to refine further and strengthen machine learning‐based imputation methods regarding precision and stability. ECOC framework includes all kinds of MLP classifiers and regressors such as binary classifiers, multi‐class classifiers, or regression models. MLP models predict complex relationships in modern datasets. Hugging Face, COSMIC, SKlearn, and Kaggle have relevant and updated datasets. The weighted average recognition (96%) shows that the proposed MLP‐based stochastic learning strategies achieved better results.
Hybridizing Machine Learning Algorithms With Numerical Models for Accurate Wind Power Forecasting
Authors: Abad‐Santjago Álvaro , Peláez‐Rodríguez C. , Pérez‐Aracil J. , Sanz‐Justo J. , Casanova‐Mateo C. , Salcedo‐Sanz S. 
Published: January 2025

ABSTRACTAn accurate prediction of wind power generation is crucial for optimizing the integration of wind energy into the power grid, ensuring energy reliability. This research focuses on enhancing the accuracy of wind power generation forecasts by combining data from mesoscale and reanalysis models with Machine Learning (ML) approaches. We utilized WRF forecast data alongside ERA5 reanalysis data to estimate wind power generation for a wind farm located at Valladolid, Spain. The study evaluated the performance of ML models based on WRF and ERA5 data individually, as well as a combined model using inputs from both datasets. The hybrid model combining WRF and ERA5 data with ML resulted in a 15% improvement in root mean square error (RMSE) and a 10% increase in compared with standalone models, providing a more reliable 1‐h forecast of wind power generation. Additionally, the availability of data over time was addressed: WRF provides the advantage of projecting data into the future, whereas ERA5 offers retrospective data.
Automatic Code Summarization Using Abbreviation Expansion and Subword Segmentation
Authors: Liang Yu‐Guo , Fan Gui‐Sheng , Yu Hui‐Qun , Li Ming‐Chen , Huang Zi‐Jie 
Published: January 2025

ABSTRACTAutomatic code summarization refers to generating concise natural language descriptions for code snippets. It is vital for improving the efficiency of program understanding among software developers and maintainers. Despite the impressive strides made by deep learning‐based methods, limitations still exist in their ability to understand and model semantic information due to the unique nature of programming languages. We propose two methods to boost code summarization models: context‐based abbreviation expansion and unigram language model‐based subword segmentation. We use heuristics to expand abbreviations within identifiers, reducing semantic ambiguity and improving the language alignment of code summarization models. Furthermore, we leverage subword segmentation to tokenize code into finer subword sequences, providing more semantic information during training and inference, thereby enhancing program understanding. These methods are model‐agnostic and can be readily integrated into existing automatic code summarization approaches. Experiments conducted on two widely used Java code summarization datasets demonstrated the effectiveness of our approach. Specifically, by fusing original and modified code representations into the Transformer model, our Semantic Enhanced Transformer for Code Summarizsation (SETCS) serves as a robust semantic‐level baseline. By simply modifying the datasets, our methods achieved performance improvements of up to 7.3%, 10.0%, 6.7%, and 3.2% for representative code summarization models in terms of BLEU‐4, METEOR, ROUGE‐L and SIDE, respectively.
Zirconia spacer electrodes improve microstructural uniformity of flash sintered zirconia ceramics
Authors: Prajzler Vladimír , Todd Richard I. 
Published: January 2025

AbstractThe sample‐electrode contact often represents the most problematic part of the flash sintering circuit. We demonstrate that adding 3 mol% yttria‐stabilized zirconia (3YSZ) spacer electrodes between a 3YSZ powder compact and steel electrodes positively impacts the final density and microstructure in AC flash sintering. The 3YSZ spacer electrodes, with intrinsically low thermal conductivity, were also heated by Joule heating alongside the 3YSZ sample, reducing the temperature gradient at the specimen‐electrode interface and limiting heat loss from the specimen. A reference 3YSZ sample, which was sintered with stainless steel electrodes only, reached 98.2% of relative density with a notable grain size difference between the central (∼290 nm) and near‐electrode parts (∼160 nm). The addition of 3YSZ spacer electrodes improved the final density to 98.9 % and reduced the grain size difference between the central (∼300 nm) and near‐electrode parts (∼220 nm) almost by half compared to the reference sample.
Derivation of Economic Values for Breeding Objective Traits of Chinese Holstein Dairy Cows Using a Bio‐Economic Model
Authors: Shi R. , van der Linden A. , Oosting S. , Wang Y. , Ducro B. 
Published: January 2025

ABSTRACTHolstein cattle account for the largest proportion of dairy cattle in China. The current China Performance Index (CPI) consists mainly of production traits. To derive economic values (EV) of additional traits for balanced breeding programs, a bio‐economic model is necessary. Landless and intensive dairy farms are dominant in China, wherein all feed is purchased, and in‐farm technicians and veterinarians are employed. Therefore, in the present study, a tailored bio‐economic model was developed using the parameters of a typical dairy farm in North China. The typical farm had 1500 cows and 1400 youngstock, with a replacement rate of 33.5% per year and a productive life of 1090 days. The bio‐economic model was on a per cow per year basis and described the revenues and costs from different animal categories. The EVs of 17 traits, including production, calving, fertility, longevity, and health traits, were derived and used to develop a more balanced selection index. Results showed that the bio‐economic model can represent the typical dairy farm system in North China. The EVs of production traits were 2.39 Chinese Yuan (CNY), 32.85 CNY, and 89.60 CNY per kg milk yield, fat yield and protein yield, respectively. The EVs of production traits were two to three times higher than those in some European countries, due to the higher prices on milk volume and milk solids in China. The EVs of health traits ranged from −0.45 CNY to −11.95 CNY and were nearly half of those in other countries, due to the lower in‐farm veterinarian labour costs. The EVs of most other functional traits were in line with the published values of other countries with similar economic assumptions in the model. Using the calculated EVs, a more balanced selection index was derived by including functional traits. This index had higher relative weight (46.8%) on functional traits than the current CPI (12.5%). With the high milk prices, it is still most profitable to allow for a decline in functional traits, although the decline is considerably smaller with the developed balanced index than with the CPI. Collectively, the bio‐economic model and EVs provided the foundations for implementing balanced breeding programs in the Chinese Holstein population.
Associations Between Socioeconomic, Spatial and Educational Factors and Midlife Periodontal Disease Risk: Evidence From ‘High School and Beyond’
Authors: Warren John Robert , Himmelstern Jessie , Muller Chandra , Grodsky Eric , Demmer Ryan 
Published: January 2025

ABSTRACTBackgroundPeriodontal disease (PD) is a prevalent, preventable and treatable oral infection associated with substantial morbidity globally. There is little information from population‐representative cohort studies about the sociodemographic, educational and other early life factors that stratify PD risk.MethodsWe used data from the U.S. ‘High School and Beyond’ (HS&B:80) study, which has followed a nationally representative sample of 26,820 people from high school in 1980 through midlife in 2021. Data from the 1980s include information about education, early life circumstances, spatial location and demographic attributes. Data from 13,080 sample members who responded in 2021 include indicators of self‐reported PD diagnosis.ResultsPeople with higher degrees and course grades have a lower risk of midlife PD. Rural adolescents and those who attended private schools are also at lower risk. We find little evidence of heterogeneity in correlates of midlife PD by gender or race/ethnicity.ConclusionsThe quantity and characteristics of people's schooling and their location of residence are associated with midlife PD.
A Note on the Use of Categorical Subscores
Authors: Gorney Kylie , Sinharay Sandip 
Published: January 2025

AbstractAlthough there exists an extensive amount of research on subscores and their properties, limited research has been conducted on categorical subscores and their interpretations. In this paper, we focus on the claim of Feinberg and von Davier that categorical subscores are useful for remediation and instructional purposes. We investigate this claim by examining (a) the agreement between true and observed subscore classifications and (b) the agreement between subscore classifications across parallel forms of a test. Results show that the categorical subscores of Feinberg and von Davier are often inaccurate and/or inconsistent, pointing to a lack of justification for using them for remediation or instructional purposes.
Fracture Resistance and Wear Behavior of Ultra‐Thin Occlusal Veneers Made From Translucent Zirconia Ceramics Bonded to Different Tooth Substrates
Authors: Fulde Nele , Wille Sebastian , Kern Matthias 
Published: January 2025

ABSTRACTObjectiveInvestigation of the mechanical properties of occlusal veneers made from zirconia with varying translucency, bonded to different tooth substrates.Materials and MethodsSixty‐four extracted molars were divided into two groups: preparation within enamel (E) or extending into dentin (D). Veneers were milled from four zirconia ceramics (n = 8): 5Y‐TZP (HT), a multilayer of 5 and 3Y‐TZP (GT), 3Y‐TZP (LT), and 4Y‐TZP (MT). After bonding, specimens underwent thermocycling (7500 cycles; 5°C–55°C) and chewing simulation (1,200,000 cycles; 10 kg), followed by investigation of the wear behavior using optical and laser scanning microscopy. Specimens were then loaded to examine fracture resistance.ResultsAll specimens except one in the HT group survived artificial aging. Zirconia wear was below the resolution of the 3D scanner, with no significant difference in antagonist vertical loss across materials (p > 0.05). Fracture resistance was significantly higher in E‐LT compared with E‐HT (p = 0.003). No significant differences (p > 0.05) were observed in fracture resistance between materials bonded to dentin, or between the materials within different substrates.ConclusionsVeneers made of 3 and 4Y‐TZP zirconia showed promising in vitro performance and fracture resistance, regardless of the tooth substrate. All zirconia ceramics exhibited favorable wear behavior.Clinical SignificanceAs tooth wear rates increase, the use of minimally invasive occlusal veneers is becoming more important. The goal is to create restorations that are both esthetically pleasing and mechanically durable, while keeping them thin to minimize occlusal preparation and still ensure sufficient fracture resistance. Ultra‐thin (0.3 mm in the fissures/0.6 mm at the cusps) occlusal veneers made of 4Y‐TZP, multilayer and 3Y‐TZP zirconia ceramics survived chewing simulation corresponding 5‐years. All zirconia restorations showed wear‐resistant behavior.
From local knowledge and science to policy: Lessons learned from Fiji's valuable grouper fisheries
Authors: Sadovy de Mitcheson Yvonne , Batibasaga Aisake , Hatten Chloe E. R. , Mangubhai Sangeeta 
Published: January 2025

AbstractPacific Island communities are heavily dependent on fisheries for subsistence and livelihoods. Yet, despite their importance, coastal fisheries are poorly managed and commercial pressures increasingly threaten them. Groupers (Epinephelidae) are exceptionally vulnerable to overexploitation due to aspects of their biology while their economic value makes them a prime target for commerce. Fiji has a significant grouper fishery and is a useful case study to assess a data‐poor, economically valuable sector to evaluate management measures, options, and needs. Data from multiple sources over three decades were integrated with original research involving fisher interviews, market surveys, stock assessments, and underwater census to assess the status of the country's grouper fishery. Catch rates are declining and trade now includes a high percentage of immature groupers, with aggregating species (mainly Epinephelus polyphekadion, Epinephelus fuscoguttatus, Plectropomus areolatus, Plectropomus leopardus) particularly at risk. Estimated annual grouper landings are increasing and now exceed 1000 mt. There is an urgent need to update Fiji's grouper size limits which are grossly inadequate. To build public support and increase awareness, government and nongovernmental organizations should invest in the national 4FJ Fish Smart campaign. Key management recommendations for groupers are (1) improved spatial and temporal protection of spawning aggregations and (2) increased minimum‐size restrictions for capture and sale. Findings apply broadly to valuable and vulnerable coastal fin‐fisheries in reef ecosystems across many Pacific Island countries and highlight the importance of using multiple data sources and approaches to understand and manage important data‐poor fisheries.
Efficacy of Radiofrequency Ablation as a Treatment for High‐Risk Gastric Intestinal Metaplasia: A Randomized, Self‐Control Study
Authors: Pittayanon Rapat , Tiankanon Kasenee , Faknak Natee , Lerttanatum Nathawadee , Sanpavat Anapat , Klaikaew Naruemon , Rerknimitr Rungsun 
Published: January 2025

ABSTRACTBackgroundGuidelines recommend endoscopic surveillance for gastric cancer without therapeutic intervention every 3 years in patients with high‐risk gastric intestinal metaplasia (GIM). This study aimed to evaluate the efficacy of radiofrequency ablation (RFA) in eradicating high‐risk GIM.MethodsThis randomized self‐control trial was conducted between June 2020 and February 2023. Patients with histology‐verified high‐risk GIM were enrolled. The endoscopist performed a biopsy on both the left and right sides of the stomach (five each) by targeting the suspected GIM area where available; otherwise, a random biopsy was taken. Patients were randomized to receive a unilateral RFA on either the left or right side. A repeated RFA on the assigned side was performed every 2–3 months for a total of two to three times. The primary outcome was complete resolution of GIM at 1 year after RFA.ResultsForty‐six patients with a mean age of 66 ± 8 years were analyzed. The complete resolution rate of overall GIM lesions after RFA was significantly higher (49/142; 34/5%) than that in the observation group (29/127; 22.8%, RR = 0.84, 0.73–0.98, p = 0.03). For the subgroup analysis, the complete resolution rate after RFA revealed a significantly higher value than observation only in the incomplete GIM group (24/87; 27.6% vs. 11/82; 13.4%, RR = 0.83, 0.71–0.97, p = 0.02). The percentage of patients with extensive GIM regression after RFA (15/25; 60%) was higher than in the observation group (9/25; 36%) but did not meet statistical significance (RR = 0.62, 0.35–1.09, p = 0.09).ConclusionIn high‐risk GIM, RFA can significantly eradicate incomplete GIM when compared with observation alone.