bluuebunny/crossref_metadata_2025_split huggingface dataset:
Relación entre perfil antropométrico, VO2max y potencia en ciclistas de ruta y pista; una revisión narrativa.
Authors: Ramos Grisales Nikol Valeska , Tovar Montaño Juan Guillermo , Gaviria Chavarro Javier , Orejuela Aristizabal Diego Fernando , Rojas Padilla Isabel Cristina 
Published: February 2025

Capacidades como resistencia, fuerza y velocidad son protagonistas en el desempeño del ciclismo y el impacto que pueda generar la antropometría del individuo sobre este deporte, debe considerarse como estrategia para el entrenamiento. El objetivo fue analizar la relación entre el perfil antropométrico y el rendimiento en ciclistas de pista y ruta, con un enfoque en cómo estas características se asocian con el consumo máximo de oxígeno (VO2max), la potencia tanto absoluta como relativa, y la eficiencia aerodinámica. Se llevó a cabo una revisión exhaustiva de la literatura en bases de datos académicas incluyendo PubMed, Scopus y Google Académico. La búsqueda se restringió a estudios publicados entre 1987 y 2022 para asegurar la inclusión de investigaciones actuales. Se revisaron artículos en inglés y en español para abarcar la mayor cantidad posible de literatura disponible sobre el tema. En total, se analizaron 24 artículos que proporcionaron una visión comprensiva de las variables antropométricas y su influencia en el rendimiento de los ciclistas. Para ciclistas de pista, el desarrollo de masa muscular en las piernas es fundamental para generar la potencia explosiva en Sprint y pruebas cortas, requiriendo ejercicios de alta intensidad. En cambio, para ciclistas de ruta, un alto VO2max y bajo porcentaje de grasa corporal son claves para el rendimiento en pruebas largas, y es crucial combinar entrenamientos aeróbicos con estrategias para mejorar la relación potencia-peso y la eficiencia aerodinámica.
Antagonism of Nitrogen Fertilizer and Rhizobium on Growth, Nodulation and Yield Of Peanuts (Arachis hypogaea L.) on Acid Soil
Authors: Setyaningrum Desy , Supriyono Supriyono , Putri Riza Noermala 
Published: February 2025

Acid soil is widely available in Indonesia and is suboptimal, so yields are low. The research examines the effect of antagonism and nitrogen fertilizer on peanuts' growth, nodulation, and yield in sour planting. This study used a factorial complete randomized block design with two factors. The first factor is the dose of Nitrogen fertilizer with four levels: 0, 50, 100, 150 kg.ha-1. The second factor is the source of rhizobium with three levels: without rhizobium, legin rhizobium dose ten g.kg-1 seed, and rhizobium from peanut plantations. They were repeated three times. Nitrogen 50 kg.ha-1 with the source of used peanut rhizobium showed the highest plant height, 15.73 cm. The combination of 100 kg.ha-1 of nitrogen with a source of used peanut rhizobium showed the highest number of plant leaves, namely 675.33 leaves. A nitrogen dose of 50kg.ha-1 produced the highest effective number of nodules and nodules, namely 363.00 and 19.33 nodules. The optimum nitrogen fertilizer dose is 44 kg.ha-1 for nodule growth. 50 kg.ha-1 nitrogen dose produced the highest number of pods and seed weight, namely 48.67 pods and 407.79 g of seeds. Nitrogen fertilizer at the correct dose can increase peanuts' growth, nodulation, and yield in acid soil. However, a dose that is too high may cause antagonism with the nodulation process and reduced yield.
Financial technology: The catalyst for BRICS' economic and financial leap
Authors: M Dhaya , N Sundaram 
Published: February 2025

This research attempts to ascertain how fintech contributes to the financial development and economic expansion of the BRICS nations. Samples were gathered between 2002 and 2021 using panel data analysis with fixed effects as the research approach. OLS regression was used for analysis. Variables are collected from World Development Indicators and data analysis is done using Gretl software. Three hypotheses are put out in the study and are validated based on the data collected. As per the first hypothesis, fintech is having a beneficial impact on the GDP which is used as a gauge for the nation's economic growth. A second hypothesis posits that fintech impacts the overall money supply which serves as a gauge for financial progress. The third hypothesis states that fintech impacts bank deposits relative to GDP; the second metric chosen to measure financial development is not favorable according to the results. The impact of fintech on financial development and economic growth shows positive impacts. Fintech can enhance the overall economic growth of emerging economies. Maximum utilization of upcoming technology can result in financial development. Emerging economies can benefit from the use of financial technologies to further their financial and economic development. The analysis highlights how crucial technology is to the financial industry.
Semantic Drawn Robot Language : a method to extract robotic programs from physically drawn symbols
Authors: pedersen jens , Sieder-Semlitsch Jakob 
Published: February 2025

Abstract

This paper builds on top of existing research that have developed methods and software to instruct industrial robot arms through physical drawings made on work-pieces. Previous research has presented two principal findings: 1) a calibration and implementation method for a visual system that isolates drawings, creates a digital twin, and allows operators to augment it with fabrication information through a software. And 2) a symbol training pipeline, where symbols can be digitally drawn, labelled, stored in a database, and used to train a Machine Learning pipeline to classify physical drawings. In building on top of these findings, this research presents a method to convert physically drawn symbols by using computer vision algorithms and kMeans clustering to convert them into robotic fabrication instructions. The method consists of two computational layers, where images are first segmented and classified, before geometric information is extracted and converted into robotic fabrication sequences. The developed method is demonstrated through the manufacturing of a wall section using a full-scale robotic setup, consisting of an ABB IRB 6620, equipped with a webcam and 5.6 KW spindle with a 20 mm routing bit.
How uncertainties could affect the establishment of tumour control probability profiles in radiopharmaceutical therapy?
Authors: Dieudonné Arnaud 
Published: February 2025

Abstract

Purpose
This study examines the impact of uncertainties in absorbed dose and response evaluations on establishing tumour control probability (TCP) profiles in radiopharmaceutical therapy (RPT).
Methods
Using three simulated TCP models with varying slopes (γ50), the impact of uncertainties of up to 30% in absorbed dose and response classification errors were studied. Logistic regressions on 100 simulated datasets assessed the accuracy of TCP parameters.
Results
The results show that dose uncertainties significantly affect TCP models but can be mitigated by increasing the sample size. Errors in response classification have a smaller impact. Parameters like x50 (dose for 50% tumour control) were more accurately predicted than γ50 (radiosensitivity). Accuracy improves notably when sample sizes exceed 300 and dose uncertainties remain below 15%.
Conclusion
The findings highlight the importance of estimating uncertainties and increasing sample size to improve TCP model reliability in clinical studies.
MCL-1 as a molecular switch between myofibroblastic and pro-angiogenic features of breast cancer- associated fibroblasts
Authors: Souazé Frédérique , Lefebvre Chloé , Giowachini Philippine , Derrien Jennifer , Naour Maxime , Corre Isabelle , Douillard Elise , Guillonneau François , Campone Mario , Juin Philippe 
Published: February 2025

Abstract

Breast cancer-associated fibroblasts (bCAFs) comprise inflammatory CAFs (iCAFs), characterized by the secretion of pro-inflammatory cytokines, and myofibroblastic CAFs (myCAFs), distinguished by their high production of extracellular matrix and their immunosuppressive properties. We previously showed that targeting the anti-apoptotic protein MCL-1 in primary culture of bCAF derived directly from human samples reduces their myofibroblastic characteristics. We herein show by single-cell RNA-sequencing analysis of bCAFs that MCL-1 knock down induces a phenotypic shift from wound-myCAF to IL-iCAF, characterized by the upregulation of genes associated with inflammation as well as angiogenesis-related genes. In vitro, genetic and pharmacologic MCL-1 inhibition increases VEGF secretion by bCAFs, enhancing endothelial cell tubulogenesis. In a chicken chorioallantoic membrane (CAM) model in ovo, co-engraftment of breast cancer cells and bCAFs with reduced MCL-1 expression leads to heightened peritumoral vascular density, driven by VEGF. Mechanistically, the pro-angiogenic phenotype revealed by MCL-1 inhibition is dependent on BAX-BAK activity. It results in NF-κB activation, inhibition of which by a IKKβ inhibitor suppresses the transcription of VEGF and pro-inflammatory factors triggered by MCL-1 inhibition in bCAFs. Chemotherapy induces a downregulation of MCL-1 in bCAFs and it promotes a pro-angiogenic phenotype, counteracted by overexpressed MCL-1. Overall, these findings uncover a novel regulatory function of MCL-1 in determining bCAF subpopulation differentiation and highlight its role in modulating their pro-angiogenic properties, in response to treatment in particular.
Machine learning models for predicting medium-term heart failure prognosis: Discrimination and calibration analyses
Authors: Nishino Takuya , Kato Katsuhito , Tara Shuhei , Hayashi Daisuke , Seki Tomohisa , Takiguchi Toru , Kubota Yoshiaki , Yamamoto Takeshi , Maruyama Mitsunori , Kodani Eitaro , Kobayashi Nobuaki , Shirakabe Akihiro , Otsuka Toshiaki , Yokobori Shoji , Kondo Yukihiro , Asai Kuniya 
Published: February 2025

Abstract

The number of patients with heart failure (HF) is increasing with the aging population, shifting care from hospitals to clinics. Although predicting medium-term prognosis after discharge can enhance care and reduce readmissions, yet no established model has been evaluated for both discrimination and calibration. This multicenter study developed and validated machine learning (ML) models—including logistic regression, random forests, extreme gradient boosting, and light gradient boosting— to predict 180-day mortality or emergency hospitalization in 4,904 HF patients with HF. Patients were randomly split into training and validation sets (8:2), and models were trained and evaluated accordingly. All models showed acceptable performance based on the area under the precision-recall curve, good calibration according to the calibration slope and Brier score, and effective risk stratification. The SHapley Additive exPlanations algorithm identified nursing care needs as a key predictor alongside established laboratory values for HF prognosis. ML models effectively predict the 180-day prognosis patients with HF, with nursing care needs highlighting the importance of multidisciplinary collaboration. Clinical Trial Registration: URL: https://www.umin.ac.jp/ctr; unique identifier: UMIN000054854
Global dynamics for a class of nonautonomous mosquito models with time delay and switching control strategy
Authors: Yu Qingwen , Wang Dongshu , Cheng Yaqiong 
Published: February 2025

Abstract

Mosquitoes serve as the primary vectors for several life-threatening pathogens, including malaria, dengue fever, and Zika virus. To effectively control the transmission of these diseases, a variety of integrated vector management strategies are currently employed to reduce mosquito population densities. This paper focuses on the sterile insect technique (SIT) and incompatible insect technique (IIT), which involves the release of sterile male mosquitoes to suppress wild mosquito populations, and delves into the impact of different release strategies on mosquito population dynamics. We established a switched mosquito population suppression model with time delay. We first investigate the existence and stability of the switching ordinary differential equation model, and derive some criteria for determining whether T-periodic solutions are stable or unstable. By taking the initial function as a solution to the delay-free model, we obtain sufficient conditions for existence of a unique or exactly two periodic solutions. Furthermore, we gain necessary and sufficient conditions for nonexis-tence of periodic solutions. Finally, the numerical results have been shown to further highlighted the effectiveness of our proposed model.
Evaluation of CanCM3 and CanCM4 models from the North American Multi-Model Ensemble (NMME) for drought prediction in arid and semi-arid basins of Iran
Authors: Moghasemi Mehdi , Zohrabi Narges , Fathian Hossein , Shahbazi Alireza Nikbakht , Yeganegi Mohammadreza 
Published: February 2025

ABSTRACT
This study evaluates the potential of two models within the North American Multi-Model Ensemble system, i.e., CanCM3 and CanCM4, for improving drought risk management through reliable prediction. By employing the standardized precipitation evapotranspiration index and gridded datasets (Global Precipitation Climatology Center and Climatic Research Unit), this study assesses their drought forecast capabilities across four semi-arid to arid basins in Iran. The results reveal that both models effectively capture drought events at short lead times (0.5 months), achieving correlation coefficients exceeding 0.93. The performance decline at longer lead times (3.5 months) is less severe in spring and autumn, maintaining correlations of &gt;0.6 compared to summer. A critical success index (CSI) analysis further highlights the models' skill in detecting summer drought events at a 1.5-month lead time (CSI &gt; 0.94), underscoring their utility for critical agricultural and water resource planning. Seasonal analysis shows CanCM4 outperforming CanCM3, particularly regarding the CSI and correlation stability. These findings offer a novel contribution to understanding the applicability of CanCM3 and CanCM4 for drought forecast purposes in arid and semi-arid basins and underline their value for enhancing drought early warning systems and supporting efficient resource allocation to mitigate drought impacts.
Patterns of Skills Review in Smartphone Cognitive Behavioral Therapy for Depression: Observational Study of Intervention Content Use
Authors: Bernstein Emily E , Daniel Katharine E , Miyares Peyton E , Hoeppner Susanne S , Bentley Kate H , Snorrason Ivar , Fisher Lauren B , Greenberg Jennifer L , Weingarden Hilary , Harrison Oliver , Wilhelm Sabine 
Published: February 2025

Background
Smartphones could enhance access to effective cognitive behavioral therapy (CBT). Users may frequently and flexibly access bite-size CBT content on personal devices, review and practice skills, and thereby achieve better outcomes.

Objective
We explored the distribution of actual interactions participants had with therapeutic content in a trial of smartphone CBT for depression and whether interactions were within assigned treatment modules or revisits to prior module content (ie, between-module interactions).

Methods
We examined the association between the number of within- and between-module interactions and baseline and end-of-treatment symptom severity during an 8-week, single-arm open trial of a therapist-guided CBT for depression mobile health app.

Results
Interactions were more frequent early in treatment and modestly declined in later stages. Within modules, most participants consistently made more interactions than required to progress to the next module and tended to return to all types of content rather than focus on 1 skill. By contrast, only 15 of 26 participants ever revisited prior module content (median number of revisits=1, mode=0, IQR 0-4). More revisits were associated with more severe end-of-treatment symptom severity after controlling for pretreatment symptom severity (P<.05).

Conclusions
The results suggest that the frequency of use is an insufficient metric of engagement, lacking the nuance of what users are engaging with and when during treatment. This lens is essential for developing personalized recommendations and yielding better treatment outcomes.

Trial Registration
ClinicalTrials.gov NCT05386329; https://clinicaltrials.gov/study/NCT05386329?term=NCT05386329
Pathways to Sustainable Health Care Development: Study on the Carbon Reduction Potential of Telemedicine in China
Authors: Li Zhi , Xiang Lianrui , Ning Jing , Li Wenbo , Huang Yong , Xiao Xue 
Published: February 2025

Background
Carbon emissions are a global concern due to their significant greenhouse effect. The health care sector’s greenhouse gas (GHG) emissions must be controlled. Telemedicine in China continued to grow between 2020 and 2022, offering a promising solution for reducing carbon emissions in the country’s health sector.

Objective
This study explores the potential of telemedicine for reducing GHG emissions and saving energy through a life cycle assessment.

Methods
This study used the Chinese Environmentally Extended Input-Output database, which is based on input-output models, to quantify the GHG emissions and energy consumption associated with care outpatient and telemedicine from a life cycle perspective. Data collected from the West China Second University Hospital of Sichuan University between 2020 and 2022 were incorporated into the analyses.

Results
The findings indicated that telemedicine could reduce GHG emissions by 36 tCO2e. The GHG emissions per telemedicine session were only 19.14 kgCO2e and are expected to decrease from 2025 to 2030. Replacing in-person treatments with telemedicine can lead to an average reduction of 85.51 kgCO2e emissions.

Conclusions
In the future, the widespread adoption of telemedicine could help achieve carbon neutrality in the health care sector. Telemedicine is crucial for establishing the sustainable development of the health care sector.
Screening Workers for Occupational Exposure to Respirable Crystalline Silica: Development and Usability of an Electronic Data Capture Tool
Authors: Hore-Lacy Fiona , Dimitriadis Christina , Hoy Ryan F , Jimenez-Martin Javier , Sim Malcolm R , Fisher Jane , Glass Deborah C , Walker-Bone Karen 
Published: February 2025

Abstract

Background
Cases of the occupational lung disease silicosis have been identified in workers processing artificial stone in the stone benchtop industry (SBI). In the Australian state of Victoria, the Regulator commissioned a screening program for all workers in this industry.

Objective
To facilitate systematic data collection, including high-quality exposure assessment, an electronic data capture tool (EDCT) was developed.

Methods
A multidisciplinary team developed an EDCT using Research Electronic Data Capture (REDCap; Vanderbilt University). The needs of the EDCT were (1) data entry by multiple clinicians and the workers attending for screening and (2) systematic collection of data for clinical and research purposes. The comprehensibility and utility of the tool were investigated with a sample of workers, and the EDCT was subsequently refined.

Results
The EDCT was used in clinical practice, with capacity for data extraction for research. Testing of comprehension and utility was undertaken with 15 workers, and the refined version of the Occupational Silica Exposure Assessment Tool (OSEAT) was subsequently developed.

Conclusions
The refined OSEAT has been determined to be comprehensible to workers and capable of collecting exposure data suitable for assessment of risk of silicosis. It was developed for workers in the SBI in Australia and is adaptable, including translation into other languages. It can also be modified for SBI workers in other countries and for use by workers from other industries (mining, construction) at risk of silica exposure, including in lower-income settings.
Educating Health Professions Students About Older Adults: Results From the Age-Friendly Students Senior Connection
Authors: Reilly Jo Marie , Chandramohan Devika , Yonashiro-Cho Jeanine 
Published: February 2025

Introduction: The Age-Friendly Student Senior Connection (AFSSC) is a graduate-level interprofessional (IP) health student service-learning effort launched early in the COVID-19 pandemic to connect older adults to students providing both social support and health resources to seniors through dyad phone calls between IP health students and community-dwelling elderly. Our study aimed to examine changes in students’ attitudes toward older adults after participation in the program.
Methods: IP graduate health students were paired with community-dwelling older adults to engage in weekly remote interactions over a 6 to10-week period. Students completed a postparticipation online survey that included an open-ended qualitative question about program impact on challenging or reinforcing their preconceived notions about older adults. We used descriptive statistics to characterize participants, and conducted thematic content analysis to inductively explore student-reported lessons learned.
Results: Students reported that program participation challenged their preconceived notions of older adults and aging. Commonly identified themes included resilience, continued activity, and social interactions among older adults, observations about health conditions, and the early impact of the COVID-19 pandemic on older adults.
Conclusions: Study findings demonstrate the positive effects of the AFSSC on health professions students' attitudes toward and perceptions of older adults. Student participation in intergenerational service-learning programs may reduce negative elderly stereotypes by challenging preconceived notions and improving student understanding and appreciation of older adults.
Social Media as a Setting for Accounting Research
Authors: Booker Adam , Curtis Asher , Ke Bin 
Published: February 2025

ABSTRACT
We describe social media as a setting for accounting research. Social media provides a setting in which accounting researchers can observe how firms and stakeholders access and share information on public forums. We review the literature and provide a framework based on incentives and consequences for accessing and sharing financial news on social media. To aid future research, we offer institutional background on several social media platforms along with guidance on using social media data for accounting research, which is accompanied by code in our Online Appendix. Finally, throughout the paper, we provide avenues for future research using social media platforms as a setting for accounting research.
Data Availability: All data are available from the sources described in the text.
JEL Classifications: M40.