bluuebunny/crossref_metadata_2025_split huggingface dataset:
The effects of acetylsalicylic acid on performance, carcass traits, breast meat quality and white striping muscle defects in broiler chickens
Authors: Güngören Gülşah , Simsek Ulku Gulcihan , Güngören Alper , Çiftçi Mehmet , Eröksüz Hatice , Karabulut Burak , Baykalir Yasin , Kahraman Mücahit , Demircioğlu İsmail , Top Şermin 
Published: February 2025

AbstractBACKGROUNDThis research aims to reduce white striping muscle defects induced by vascular inflammation and hypoxia using the anti‐inflammatory, antiplatelet and anti‐atherothrombotic properties of acetylsalicylic acid (ASA). To this end, the effects of different doses (0.3, 0.6, 1, 3 and 6 g L−1) of ASA added to drinking water at 24–48 days on growth performance, carcass traits, footpad dermatitis, white striping and breast meat quality parameters were investigated.RESULTSThe results indicate that 0.3, 1, 3 g L−1 and especially 0.6 g L−1 ASA treatment significantly improved growth performance and meat quality parameters. Also, doses of 0.3, 6 g L−1 and especially 0.6 g L−1 of ASA treatment reduced the incidence of white stripe muscle defects.CONCLUSIONSConsequently, 0.6 g L−1 ASA treatment reduced macrophage infiltrations and myodegeneration caused by growth rate. In addition, this dose increased vascular endothelial growth factor and decreased irisin level in breast muscle. The study also shows that high doses of ASA treatment (3 and 6 g L−1) may make footpad dermatitis more common. This may be due to the fact that ASA can cause side effects such as gizzard ulcers and kidney damage in broiler chickens. © 2025 The Author(s). Journal of the Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.
Integrated Evaluation Approach for Land Sustainable Management and Carrying Capacity of Clustered Mining Area in the Cement City of South India
Authors: Kumar E. , Subramani T. , Gopinathan P. 
Published: February 2025

ABSTRACTIn today's global context, sustainability is a crucial factor for both emerging and established industries, including mining. The sector significantly affects social, economic, and environmental dimensions, creating job opportunities that can boost regional income while also contributing to adverse environmental consequences such as air and water pollution, land degradation, and soil contamination. This study employs dynamic modelling and evaluation techniques to examine the interplay between social, economic, and environmental factors, focusing on the sustainability of mining in Ariyalur district, Tamil Nadu. The findings indicate that Ariyalur district has achieved a nearly optimal state of sustainability, with the sustainable development index rising from 0.880 in 2016–0.921 by 2030. The sustainable development index intends to provide a holistic view on the social, economic, and environmental status of the region. This increase underscores the potential for enhanced carrying capacity in the region, allowing for future mineral production without compromising sustainability. These results provide valuable insights for policymakers and industry stakeholders aiming to balance economic growth with environmental stewardship. The proposed model serves as a framework for evaluating sustainability across various industries, highlighting the importance of integrated approaches in resource management.
Dual‐Inertial Viscosity‐Based Subgradient Extragradient Methods for Equilibrium Problems Over Fixed Point Sets
Authors: ur Rehman Habib , Sitthithakerngkiet Kanokwan , Seangwattana Thidaporn 
Published: February 2025

ABSTRACTThis paper introduces a new algorithmic framework for solving pseudomonotone equilibrium problems and demicontractive fixed‐point problems. Unlike conventional methods that incorporate a single inertial step, our approach employs dual inertia to accelerate convergence while preserving stability. The proposed method combines the viscosity approximation technique with the extragradient method to guarantee strong convergence. Initially, the extragradient method is applied under a Lipschitz continuity assumption on the equilibrium bifunction. Subsequently, this condition is relaxed by adopting a self‐adaptive step size strategy, allowing variable step sizes to be updated iteratively based on the current iterates information. Notably, the algorithm operates without requiring prior knowledge of the Lipschitz constants or any line search procedures. Strong convergence is established under mild condition, and its applicability to variational inequality problems is demonstrated. Numerical experiments validate the effectiveness of the proposed approach, showcasing its capability to handle large‐scale and complex problems efficiently while outperforming traditional single‐inertia methods.
On Ill‐Conditioning of Descent Methods to Recover Initial Data for the Burgers Equation With Small Viscosity
Authors: Gutiérrez Carlos Rubén , Iturriaga Renato , Angel Moreles Miguel 
Published: February 2025

ABSTRACTThe identification of the initial condition of a parabolic equation given terminal data is a problem arising in several applications. In this work, we consider the problem for the semilinear parabolic viscous Burgers equation in the vanishing viscosity case. The limiting equation is the nonlinear hyperbolic Burgers equation, for which there is non‐uniqueness backward in time. In both cases, solutions are sought by formulating the identification problem as the minimization of a least squares functional, and gradient descent methods are used for computation. Following this approach, we construct the first and second variations of the functional by the adjoint state approach. We prove that the second variation is continuous with respect to viscosity. Consequently, gradient descent methods of approximation inherit the ill‐conditioning of the nonlinear hyperbolic limit.
A novel cross‐modal data augmentation method based on contrastive unpaired translation network for kidney segmentation in ultrasound imaging
Authors: Guo Shuaizi , Sheng Xiangyu , Chen Haijie , Zhang Jie , Peng Qinmu , Wu Menglin , Fischer Katherine , Tasian Gregory E. , Fan Yong , Yin Shi 
Published: February 2025

AbstractBackgroundKidney ultrasound (US) image segmentation is one of the key steps in computer‐aided diagnosis and treatment planning of kidney diseases. Recently, deep learning (DL) technology has demonstrated promising prospects in automatic kidney US segmentation. However, due to the poor quality, particularly the weak boundaries in kidney US imaging, obtaining accurate annotations for DL‐based segmentation methods remain a challenging and time‐consuming task. This issue can hinder the application of data‐hungry deep learning methods.PurposeIn this paper, we explore a novel cross‐modal data augmentation method aimed at enhancing the performance of DL‐based segmentation networks on the limited labeled kidney US dataset.MethodsIn particular, we adopt a novel method based on contrastive unpaired translation network (CUT) to obtain simulated labeled kidney US images at a low cost from labeled abdomen computed tomography (CT) data and unlabeled kidney US images. To effectively improve the segmentation network performance, we propose an instance‐weighting training strategy that simultaneously captures useful information from both the simulated and real labeled kidney US images. We trained our generative networks on a dataset comprising 4418 labeled CT slices and 4594 unlabeled US images. For segmentation network, we used a dataset consisting of 4594 simulated and 100 real kidney US images for training, 20 images for validation, and 169 real images for testing. We compared the performance of our method to several state‐of‐the‐art approaches using the Wilcoxon signed‐rank test, and applied the Bonferroni method for multiple comparison correction.ResultsThe experimental results show that we can synthesize accurate labeled kidney US images with a Fréchet inception distance of 52.52. Moreover, the proposed method achieves a segmentation accuracy of 0.9360 ± 0.0398 for U‐Net on normal kidney US images, and 0.7719 ± 0.2449 on the abnormal dataset, as measured by the dice similarity coefficient. When compared to other training strategies, the proposed method demonstrated statistically significant superiority, with all p‐values being less than 0.01.ConclusionsThe proposed method can effectively improve the accuracy and generalization ability of kidney US image segmentation models with limited annotated training data.
Featured Cover
Authors: Meng Zeng , Qian Qiaochu , Hao Peng 
Published: February 2025

The cover image is based on the article On the Use of Fidelity Transformation Method for Stress‐Constrained Reliability‐Based Topology Optimization of Continuum Structure With High Accuracy by Peng Hao et al., https://doi.org/10.1002/nme.7602.
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Efficacy and safety of a novel oral hydrogel capsule in adults with overweight or obesity: the pivotal randomized RESET study
Authors: Ard Jamy D. , Ryan Donna H. , O'Neil Patrick M. , Kushner Robert F. , Wyatt Holly R. , Bays Harold E. , Greenway Frank L. , Jakicic John M. , Leonard Sharon , Kenan Yael , Ganon‐Elazar Eti , Wadden Thomas A. 
Published: February 2025

AbstractObjectiveThe objective of this study was to investigate the efficacy and safety of the Epitomee capsule versus placebo as an adjunct to high‐intensity lifestyle intervention in participants with overweight or obesity.MethodsThe Randomized Evaluation of Efficacy and Safety of the Epitomee Capsule Trial (RESET) was a prospective, double‐blind, placebo‐controlled pivotal trial in adults with baseline BMI of 27.0 to 40.0 kg/m2. The co‐primary endpoints at week 24 were percentage change from baseline in body weight for the Epitomee and placebo groups and proportion of Epitomee‐treated patients achieving ≥5% weight loss compared with a 35% threshold. The primary safety endpoint was the incidence of device‐related serious adverse events.ResultsA total of 138 participants received Epitomee and 141 received placebo. Mean (SD) change in body weight from baseline was −6.6% (6.5%) with Epitomee and −4.6% ( 4.7%) with placebo; least‐squares means were −6.1% (0.6%) and −4.2% (0.6%), respectively (p = 0.0054). Fifty‐six percent of Epitomee‐treated participants attained ≥5% weight loss from baseline, which was significantly greater than the 35% predefined threshold (p < 0.0001). Twenty‐seven percent of Epitomee‐treated and eleven percent of placebo‐treated participants achieved ≥10% weight loss. Adverse event rates were similar between the groups. No device‐related serious adverse events occurred.ConclusionsThe Epitomee capsule is a safe and efficacious nonpharmacological option for weight management with potential broad application in participants with overweight or obesity.
Associations between decreases in adiposity and reductions in HbA1c and insulin use in the Look AHEAD cohort
Authors: Palmer Rebecca , Neiberg Rebecca H. , Beavers Kristen M. , Kahn Steven E. , Houston Denise K. , Wagenknecht Lynne , Johnson Karen C. , Pownall Henry J. , Espeland Mark A. ,   For the Action for Health in Diabetes (Look AHEAD) Aging Study Group
Published: February 2025

AbstractObjectiveThe objective of this study was to elucidate associations between adiposity reduction and changes in HbA1c and insulin use among adults with type 2 diabetes and overweight or obesity.MethodsChanges in BMI, waist circumference, and total percent fat mass were obtained over 8 years among 1316 individuals (aged 45–76 years) enrolled in the Look AHEAD (Action for Health in Diabetes) clinical trial of weight loss. Generalized linear models were used to assess relationships between 5% decreases in adiposity measures with glycated hemoglobin (HbA1c) and insulin use over time.ResultsA 5% reduction in total percent fat was associated with 0.15% (95% CI: 0.12%–0.18%) lower mean HbA1c. Similarly, 5% reductions in waist circumference and BMI were also associated with slightly lower mean HbA1c: 0.16% (95% CI: 0.13%–0.19%) and 0.13% (95% CI: 0.11%–0.16%), respectively. These reductions were associated with lower odds of insulin use over time, ranging from 21% lower odds for a 5% reduction in percent body fat to 32% lower odds for 5% reductions in waist circumference and BMI. Associations were evident across subgroups defined by sex, diabetes duration, obesity status, and intervention assignment.ConclusionsReductions in adiposity are associated with stabilized and slightly lower HbA1c and a marked reduction in the need for insulin therapy. These benefits generalize across clinical subgroups.
Phenol formaldehyde‐flax fabric (PF‐F) hybrid composites reinforced with cellulose nanofiber (CNF)—mechanical, morphology, electrical conductivity, electronic structure, optoelectronic, and charge transfer properties
Authors: Ravindran Lakshmipriya , Joseph Saju , Ponnan Sathiyanathan , Kalarikkal Nandakumar , Sreekala M. S. , Thomas Sabu 
Published: February 2025

AbstractFor developing an eco‐friendly world, a sustainable solution has encouraged to use natural fibers. Among the various options, lignocellulose fiber‐reinforced composites have captured the interest of material experts and engineers. These remarkable materials offer plentiful supply, inherent sustainability, easily degradability, and affordability, making them an attractive choice for a multitude of uses. Herein, we prepared a series of hybrid cellulose nanofiber (CNF)‐reinforced phenolic composites. Flax fabric was coated with CNF followed by phenolic resin coating was made in this work to check the mechanical, morphological behavior, electrical conductivity, electronic structure, opto‐electronic, and charge transfer properties. We found that 0.5 CNF showed better tensile properties, greater AC conductivity, dielectric constant, and dielectric loss compared with other composites. The electronic structure, opto‐electronic, and charge transfer properties of the PF‐resin/nanocellulose polymer nanocomposite have been systematically examined using density functional theory (DFT). The findings indicate that the PF‐resin/cellulose nanocomposite undergoes intramolecular charge transfer (CT) in response to an external electric field. The negative binding energy exhibited between the DFT optimized PF‐resin/cellulose nanocomposite shows the complex is stable and energy‐favorable.Highlights
The impact of CNF on the properties PF‐F hybrid composites was investigated.
The mechanical performance has been improved by the addition of CNF.
The incorporation of CNF improved the fracture toughness of the composites.
The fabricated composite has negative binding energy from DFT studies.
A promising high‐performance electroactive polymer and structural material.
Victimization Experienced by LGBTQIA+ Students in Academic Institutions: A Qualitative Exploration in India
Authors: Sarika Kumari , Maji Sucharita 
Published: February 2025

ABSTRACTVictimization is a common experience encountered by sexual and gender minorities across domains of life, including academic institutions. The present study aims to explore the forms and consequences of victimization experienced by LGBTQIA+ students, along with the coping strategies adopted by them to deal with such experiences. To address these research objectives, the present study adopts a qualitative approach. In‐depth semi‐structured interviews are conducted with thirty‐three college students (age 19–32 years, M = 24.24 years) belonging to diverse gender identities and sexual orientation, predominantly from middle and upper socioeconomic backgrounds. The qualitative data was analyzed through thematic analysis (a hybrid of inductive and theoretical thematic analysis) method. The analysis led to the generation of the following themes: bullying, interpersonal and environmental microaggression, queer battle fatigue, avoidance/approach coping, disclosure dilemma, and campus climate. The result shows that LGBTQIA+ students experience diverse forms of victimization at both, the school and college/university levels. However, bullying is more common in schools whereas microaggression is more prevalent at the college/university level. Victimization leads to negative mental health and inhibited/partial disclosures. Additionally, the experiences of victimization are aggravated through negative campus climate and unhealthy coping. The implications of the research are discussed.
Development and Psychometric Evaluation of the Epilepsy Self‐Management Scale for Teachers
Authors: Kos Fulya Merve , Bektas Murat , Ayar Dijle 
Published: February 2025

ABSTRACTThis study was conducted to develop a measurement tool to achieve epilepsy self‐management in teachers and examine its Turkish psychometric properties. This descriptive, comparative, correlational, and methodological study was conducted between May and August 2022 with 346 teachers between the ages of 24 and 67 working in public schools selected by simple random sampling method among the primary schools in the province where the research was conducted. In the descriptive data analysis, numbers, percentages, and averages were used in the psychometric analysis of the scale, content validity analysis, factor analysis, Cronbach's α, item‐total correlation, and split‐half method. The average age of the teachers included in the study was 31.14 + 2.27, of which 68% (n = 234) were women. In total, 90% of the teachers (n = 312) stated that they did not have the correct intervention information about epilepsy. The scale, which is a 5‐point Likert type, consists of 23 items and three subdimensions. The scale's total Cronbach's α coefficient is 0.83, and the subdimension Cronbach's α values are, respectively, the first subdimension is 0.78, the second subdimension is 0.91, and the third subdimension is 0.65. Item‐total score correlations ranged between 0.31 and 0.81 (p < 0.05). As a result of the exploratory factor analysis found that the three‐dimensional scale explained 42% of the total variance, and the item factor loads varied between 0.38 and 0.89. As a result of the confirmatory factor analysis, the fit indices were > 0.90, and the RMSEA value was < 0.08. The primary purpose of this study is to develop the Epilepsy Self‐Management Scale for Teachers.
Unterwasser‐Pumpspeicherkraftwerke im Tagebauloch, Teil 1: So gelingt die Energiewende
Authors: Riße Henry , Hollerbach Michael , Luther Gerhard , Schmidt-Böcking Horst 
Published: February 2025

ZusammenfassungDie Energiewende in Deutschland steht vor einer großen Herausforderung: Der geplante Zuwachs von Windenergie und Photovoltaik verstärkt die Schwankungen im Stromnetz. Das Ziel, Treibhausgas‐Emissionen bis Mitte des Jahrhunderts vollständig zu vermeiden, erfordert einen massiven Ausbau an Kurzzeit‐Stromspeichern, so dass Photovoltaik‐ und Windanlagen möglichst nicht abgeschaltet werden müssen. Derzeit werden drei Speicherkonzepte diskutiert: grüner Wasserstoff, Batterien und Pumpspeicherkraftwerke. Die Wasserstofferzeugung per Elektrolyse als chemische Speicher eignet sich eher für die Langzeitspeicherung, zudem müssten die Elektrolyseanlagen in Deutschland massiv erweitert werden. Die elektrochemische Speicherung in Akkumulatoren, zum Beispiel Lithium‐Ionenbatterien, steht in Konkurrenz mit der E‐Mobilität. Zudem sind die global verfügbaren Rohstoffe begrenzt, und die Zyklenzahl ist limitiert. Bei Pumpspeicher‐Kraftwerken gibt es diese Probleme nicht. Sie sind seit gut hundert Jahren bewährt, benötigen kaum Personal und Wartung und erreichen Wirkungsgrade bis an die 80 %. Allerdings fehlt es an geeigneten Standorten für den Ausbau herkömmlicher Pumpspeicher‐Kraftwerke. Als Alternative bieten stillgelegte Tagebaugruben die Chance, mit innovativen Unterwasser‐Pumpspeicherkraftwerken zügig große Speicherkapazitäten aufzubauen. Dieser Teil 1 des Zweiteilers stellt das Projekt im „Hambacher Loch“ als ein Beispiel für solche smarten Lösungen vor. Teil 2 widmet sich dann dem Zweispeichermodell und zwei Bauformen von Pumpspeicher‐Kraftwerken in Tagebaulöchern.
Non‐Linear Dose–Response Relationship for Metformin in Japanese Patients With Type 2 Diabetes: Analysis of Irregular Longitudinal Data by Interpretable Machine Learning Models
Authors: Akimoto Hayato , Nagashima Takuya , Minagawa Kimino , Hayakawa Takashi , Takahashi Yasuo , Asai Satoshi 
Published: February 2025

ABSTRACTThe dose–response relationship between metformin and change in hemoglobin A1c (HbA1c) shows a maximum at 1500–2000 mg/day in patients with type 2 diabetes (T2D) in the U.S. In Japan, there is little evidence on the HbA1c‐lowering effect of high‐dose metformin because the maintenance and maximum doses of metformin were raised in 2010. The aim of this study was to investigate whether there is saturation of the dose–response relationship for metformin in Japanese T2D patients. Longitudinal clinical information of T2D patients was extracted from electronic medical records. Supervised machine learning models with random effect were constructed to predict change in HbA1c: generalized linear mixed‐effects models (GLMM) with/without a feature selection and combining tree‐boosting with Gaussian process and mixed‐effects models (GPBoost). GPBoost was interpreted by SHapley Additive exPlanations (SHAP) and partial dependence. GPBoost had better predictive performance than GLMM with/without feature selection: root mean square error was 0.602 (95%CI 0.523–0.684), 0.698 (0.629–0.774) and 0.678 (0.609–0.753), respectively. Interpretation of GPBoost by SHAP and partial dependence suggested that the relationship between the daily dose of metformin and change in HbA1c is non‐linear rather than linear, and the HbA1c‐lowering effect of metformin reaches a maximum at 1500 mg/day. Interpretation of GPBoost, a non‐linear supervised machine‐learning algorithm, suggests that there is saturation of the dose–response relationship of metformin in Japanese patients with T2D. This finding may be useful for decision‐making in pharmacotherapy for T2D.
Self‐Assembly of a Conjugate of Lipoic Acid With a Collagen‐Stimulating Pentapeptide Showing Cytocompatibility and Wound Healing Properties, and Chemical and Photolytic Disassembly
Authors: de Mello Lucas R. , Castelletto Valeria , Cavalcanti Leide , Seitsonen Jani , Hamley Ian W. 
Published: February 2025

ABSTRACTLipoic acid is a biocompatible compound with antioxidant activity that is of considerable interest in cosmetic formulations, and the disulfide group in the N‐terminal ring confers redox activity. Here, we study the self‐assembly and aspects of the bioactivity of a lipopeptide (peptide amphiphile) comprising the KTTKS collagen‐stimulating pentapeptide sequence conjugated to an N‐terminal lipoic acid chain, lipoyl‐KTTKS. Using SAXS, SANS and cryo‐TEM, lipoyl‐KTTKS is found to form a population of curly fibrils (wormlike micelles) above a critical aggregation concentration. Upon chemical reduction, the fibrils (and β‐sheet structure) are disrupted because of the breaking of the disulfide bond, which produces dihydrolipoic acid. Lipoyl‐KTTKS also undergoes photo‐degradation in the presence of UV radiation. Through cell assays using fibroblasts, we found that lipoyl‐KTTKS has excellent cytocompatibility across a wide concentration range, stimulates collagen production, and enhances the rate of cell coverage in a simple in vitro scratch assay of ‘wound healing’. Lipoyl‐KTTKS thus has several notable properties that may be useful for the development of cosmetics, cell scaffolds or tissue engineering materials.