bluuebunny/crossref_metadata_2025_split huggingface dataset:
Validity of one‐time assessments for identifying prodromal Alzheimer's disease in adults with Down syndrome
Authors: Krinsky‐McHale Sharon J. , Kovacs Cynthia M. , Lee Joseph H. , Listwan Tracy A. , Pang Deborah I. , Schupf Nicole , Tycko Benjamin , Zigman Warren B. , Silverman Wayne 
Published: February 2025

AbstractIntroductionNew Alzheimer's disease (AD) treatments have created an urgent need for accurate early diagnosis of high‐risk adults with Down syndrome (DS), distinguishing prodromal DS‐AD symptoms from lifelong cognitive impairments. Often, clinicians will need to evaluate dementia status during a single assessment, and here we describe empirically supported methods effective under such circumstances.MethodsArchived data collected between 1987 and 2017 included longitudinal findings for 144 individuals maintaining cognitive stability and 126 developing prodromal DS‐AD. Response operating characteristic analyses compared groups, defined by the presence/absence of prodromal DS‐AD, for a single assessment.ResultsGroups differed on all measures without adjusting for developmental history, 0.717 < areas under the curve < 0.859, Ps < 0.0001. The balance between sensitivity and specificity improved slightly when developmental histories were considered.DiscussionThe present study demonstrated that one‐time assessments can inform clinical judgments when diagnosing adults at risk for DS‐AD. Knowledge of developmental history is valuable but non‐essential.Highlights
Non‐overlapping distributions were observed for preclinical and prodromal Alzheimer's disease (AD) groups.
Receiver operating characteristic area under the curve analyses were in the acceptable to excellent range for all measures.
Performance was sensitive to both the severity of intellectual disability and the stage of Down syndrome‐AD progression.
Episodic memory tests were sensitive to the transition from preclinical to prodromal AD.
Performance results at a single time point can inform dementia status decisions.
Natural language processing in Alzheimer's disease research: Systematic review of methods, data, and efficacy
Authors: Shakeri Arezo , Farmanbar Mina 
Published: February 2025

AbstractINTRODUCTIONAlzheimer's disease (AD) prevalence is increasing, with no current cure. Natural language processing (NLP) offers the potential for non‐invasive diagnostics, social burden assessment, and research advancements in AD.METHODA systematic review using Preferred Reporting Items for Systematic Reviews and Meta‐Analyses guidelines explored NLP applications in AD, focusing on dataset types, sources, research foci, methods, and effectiveness. Searches were conducted across six databases (ACM, Embase, IEEE, PubMed, Scopus, and Web of Science) from January 2020 to July 2024.RESULTSOf 1740 records, 79 studies were selected. Frequently used datasets included speech and electronic health records (EHR), along with social media and scientific publications. Machine learning and neural networks were primarily applied to speech, EHR, and social media data, while rule‐based methods were used to analyze literature datasets.DISCUSSIONNLP has proven effective in various aspects of AD research, including diagnosis, monitoring, social burden assessment, biomarker analysis, and research. However, there are opportunities for improvement in dataset diversity, model interpretability, multilingual capabilities, and addressing ethical concerns.Highlights
This review systematically analyzed 79 studies from six major databases, focusing on the advancements and applications of natural language processing (NLP) in Alzheimer's disease (AD) research.
The study highlights the need for models focusing on remote monitoring of AD patients using speech analysis, offering a cost‐effective alternative to traditional methods such as brain imaging and aiding clinicians in both prediagnosis and post‐diagnosis periods.
The use of pretrained multilingual models is recommended to improve AD detection across different languages by leveraging diverse speech features and utilizing publicly available datasets.
Beyond Income Disparities: Perceived Health and Education Inequities Drive Actions to Reduce Economic Inequality
Authors: Soler‐Martínez Francisco Miguel , García‐Sánchez Efraín , Willis Guillermo B. 
Published: February 2025

ABSTRACTPerceiving income disparities has a limited impact on attitudes towards reducing economic inequality. In this research, we proposed a novel and alternative strategy by focusing on other aspects intrinsically related to economic inequality, such as unequal access to health and education resources. We investigated whether recognizing inequality in health and education, beyond income disparities, could motivate people to reduce economic inequality. In four preregistered studies (NStudy1 = 513, NStudy2 = 1536, NStudy3 = 443, NStudy4 = 400), we showed that perceived economic inequality in health and education, over and above perceived income disparities, leads to greater intolerance towards inequality and increased support for redistributive policies and collective actions. Our findings suggest that heightened awareness of economic inequality in aspects meaningful for individuals’ lives, such as health or education, may foster support for redistributive policies and engagement in collective actions to mitigate such disparities.
Fuzzy Clustering of Circular Time Series With Applications to Wind Data
Authors: López‐Oriona Ángel , Sun Ying , Crujeiras Rosa María 
Published: February 2025

ABSTRACTIn environmental science, practitioners often deal with data recorded sequentially along time, such as time series of wind direction or wind speed. In this context, clustering of time series is a useful tool to carry out exploratory analyses. While most of the proposals are focused on real‐valued time series, very few works consider circular time series, despite the frequent appearance of these objects in many disciplines. In this manuscript, a dissimilarity for circular time series is introduced and used in combination with a soft clustering method. The metric relies on a measure of serial dependence considering circular arcs, thus taking advantage of the directional character inherent to the series range. The clustering approach is able to group together time series generated from similar stochastic processes. Some simulations show that the method exhibits a reasonable clustering effectiveness, outperforming alternative techniques in many contexts. Two interesting applications involving time series of wind direction in Saudi Arabia show the potential of the proposed approach.
Analytical Study on the Predictability of Controlled Rocking Frame and Podium Systems
Authors: Zaki Marawan , Zhong Chiyun , Christopoulos Constantin 
Published: February 2025

ABSTRACTWhile rocking systems are increasingly researched and developed as a promising approach to achieving seismic resilience, several studies have identified the unpredictability of their dynamic response as an obstacle to their wider adoption. Despite a significant body of literature which has identified and studied the chaotic behaviour of unenhanced rocking frames, other studies have shown that practical applications of controlled rocking systems demonstrate a more predictable response that is similar to that of more conventional yielding systems. This paper examines the differences between these two bodies of work and identifies parameters shown to improve rocking predictability. Subsequently, a perturbation study conducted on a controlled rocking podium system subjected to historic ground motions is employed to study the influence of each parameter on the predictability of such systems. The results reveal that adding supplemental damping, increasing the contribution of the superstructure properties on the rocking system behaviour and limiting the rocking rotation effectively reduce the sensitivity of rocking systems to perturbations in the rocking parameters. In addition, adding auxiliary stiffness was found to be a viable method to improve the stability of these systems but did not significantly enhance predictability.
Numerical Study on Flow and Thermal Characteristics of High‐Voltage Molten Salt Electric Heater Applied in Large‐Scale Energy Storage
Authors: Qiu Yujie , Yu Miao , Liu Keliang , Wu Dazhuan , Shi Yuegang 
Published: February 2025

ABSTRACTThe overheating phenomenon is a common issue in molten salt electric heaters (MSEHs), significantly limiting their application in large‐scale energy storage systems. To address this, a three‐dimensional analysis model of a high‐voltage resistance MSEH is developed using ANSYS Fluent. This study focuses on the overheating issue in the molten salt, investigating the fluid flow and temperature distribution within the electric heater. A multi‐zone heating method is proposed, and the heating proportions of different zones are examined in detail. Based on this, the influence of structural parameters is analyzed. The results demonstrate that the multi‐zone heating method eliminates the overheating phenomenon in the MSEH and improves temperature uniformity. The maximum temperature of the MSEH decreases from 622.6°C to a maximum of 583.4°C with the multi‐zone heating method. The optimal heating proportion of 80‐20/2.0 results in a maximum temperature that is only 14.9°C higher than the outlet temperature. The analysis of structural parameters offers valuable guidance for MSEH design. This study successfully suppresses local overheating in the MSEH, efficiently evaluates heating capacity, and ensures system safety. Therefore, this work provides significant insights for MSEH design and promotes its application in large‐scale energy storage systems.
Integrating Anticipatory Governance and Causal Layered Analysis: A Novel Theoretical Framework for Long‐Term Socioeconomic Development Forecasting
Authors: Ngo Quoc Dung , Hoang Vu Hiep , Tran Thi Van Hoa 
Published: February 2025

ABSTRACTThis research advances the theoretical foundation of futures studies by developing an innovative methodological framework that integrates anticipatory governance (AG) and causal layered analysis (CLA). Contemporary challenges in long‐term Socioeconomic development forecasting necessitate more sophisticated analytical approaches capable of addressing increasing complexity and uncertainty. Through systematic synthesis of AG's governance mechanisms with CLA's multi‐layered analytical framework, this study establishes a comprehensive methodology for understanding and shaping future trajectories. The research employs a sophisticated mixed‐methods approach, combining quantitative economic analysis with qualitative societal assessment across multiple analytical layers. The findings reveal significant theoretical and practical implications through the framework's enhanced capability for simultaneous consideration of immediate governance requirements and deeper societal transformations. The integrated framework demonstrates particular utility in scenario development, yielding four distinct future trajectories ranging from low growth to transformative change. The preferred scenario, characterized by adaptive change, projects substantial economic advancement whilst maintaining social cohesion and environmental sustainability. This research contributes to both theoretical advancement and practical application in futures studies, providing policymakers with sophisticated tools for navigating complex socioeconomic challenges. The framework's emphasis on combining systematic governance approaches with deep cultural analysis establishes a foundation for more nuanced understanding of development trajectories in emerging economies.
Regional Resource Evaluation and Distribution for Onshore Carbon Dioxide Storage and Utilization in Uzbekistan
Authors: Kamolov Azizbek , Turakulov Zafar , Norkobilov Adham , Variny Miroslav , Fallanza Marcos 
Published: February 2025

ABSTRACTAddressing the escalating threat of climate change requires a global response, with significant actions from every nation. Uzbekistan, a member of the Paris Agreement, is actively pursuing sustainable development by reducing greenhouse gas emissions and promoting renewable energy. However, the country's Green Economy strategies currently lack Carbon Capture, Storage, and Utilization (CCUS) technology. A feasibility assessment is crucial to evaluating CCSU's potential for achieving net‐zero emissions, benefiting both the public and scientific communities by informing policy decisions, and providing valuable data. The primary aim of this study is to evaluate Uzbekistan's potential for carbon dioxide (CO2) storage and utilization (CSU) in the near and mid‐term. To achieve this, this work proposes a methodology for efficient CO2 source‐sink matching to facilitate the deployment of CCUS technologies in Uzbekistan. Resource evaluation and spatial analysis methods are used to estimate the total CSU capacity of the region and the geographical distribution of CO2 sources in two large‐scale emitting sectors, specifically from the power and cement plants. According to the results, Uzbekistan has an annual CSU capacity of 1171 million tons CO2, which is several times higher than the annual CO2 emission rate. Additionally, CSU resources are primarily located in the eastern, western, and southern regions of the country, whereas CO2 sink locations near the capital city and its surrounding areas are limited compared to their abundance of CO2 sources. Overall, although the country has ample CO2 storage capacity for CCUS deployment, the prospects for its chemical utilization remain limited in scale. © 2025 Society of Chemical Industry and John Wiley & Sons, Ltd.
Prevalence of HSV‐1/HSV‐2 and CMV Infections in Infertile Men and Their Impact on Sperm Parameters: A Cross‐Sectional Study in Iran
Authors: Salar Seyed Mansour , Edalat Fahime , Letafati Arash , Kalantar Seyed Mehdi , Javanmardi Fatemeh , najafi Ahmad , vakili Mahmoud , Moattari Afagh 
Published: February 2025

ABSTRACTBackground and AimsViral infections are significant contributors to infertility. This study aimed to determine the prevalence of Herpes Simplex Virus 1 and 2 (HSV‐1/HSV‐2) and cytomegalovirus (CMV) infections in men with infertility, compared to a control group of fertile men.MethodsA cross‐sectional study was conducted with seminal fluid samples from 100 fertile and 100 infertile men, aged 20–40 years, referred to Yazd Infertility Center. DNA extraction was done using the AmpliSens kit, and the presence of CMV and HSV‐1/HSV‐2 was determined via real‐time PCR. Sperm parameters (count, quick & slow, motility, morphology, and volume) were also assessed and compared to the control group.ResultsCMV infection was found in 16% of fertile and 10% of infertile men. HSV‐1/HSV‐2 prevalence was significantly higher in infertile men (32%) compared to fertile men (8%). Abnormal sperm count was significantly associated with HSV status (p = 0.001), as was abnormal morphology (p = 0.021), while abnormal quick & slow, motility and volume showed no significant association. Data analysis indicated no correlation between sperm parameters—including sperm quick & slow, motility, count, morphology, and semen volume—and CMV infection.ConclusionHSV infection is linked to sperm‐specific parameters, particularly count and morphology. These findings enhance our understanding of viral‐induced male infertility and underscore the need for targeted approaches to manage HSV‐1/HSV‐2‐related infertility.
Demystifying cervical endometriosis: A case series and systematic review
Authors: Verma Shailja , Reis Ines , Potdar Neelam 
Published: February 2025

AbstractBackgroundCervical endometriosis (CE) is an uncommon diagnosis with a paucity of evidence on its management.ObjectiveTo examine 10 years of data to identify CE cases and to conduct a systematic review to evaluate evidence for managing CE.Search StrategyCases of CE were obtained retrospectively via a pathology coding system. Literature search was performed using Ovid MEDLINE, EMBASE, and Cochrane Library (1949–2022).Selection CriteriaStudies on diagnoses and management of CE were included, and those with retrospective diagnosis of CE on histology and no further management were excluded.Data Collection and AnalysisAn Excel spreadsheet was used for data collection. Two independent authors went through individual cases, extracting and analyzing data.Main ResultsIn case series, women presented with intermenstrual bleeding (IMB)/post‐coital bleeding (PCB) n‐25, (30%), followed by abnormal uterine bleeding (AUB) n‐24, (29%), dysmenorrhea n‐12, 12%, and/or dyspareunia (12%). In all, 44% had an initial cervical biopsy confirming CE diagnosis and 48% had CE on hysterectomy specimen. Main reasons for hysterectomy were AUB (36%) and fibroids/adenomyosis (28%). In the systematic review, 1737 studies were identified from databases, 181 were assessed for eligibility, and 14 studies discussed individual case reports and case series specifically on treating CE. Nine full‐text and abstract studies were available to identify potential treatment options for CE. Treatments were based predominantly on presentation at time of diagnosis.ConclusionFindings from case series suggest that CE was the main diagnosis in women who had a hysterectomy for AUB or had a cervical biopsy for PCB/IMB. Investigations should be considered to rule out CE to have the potential for conservative alternative treatment rather than major surgery. There is no clear guidance on managing CE and good‐quality studies are required to provide conclusive treatment options.
Research on 5G Signal Frequency Offset Estimation Method Based on Fully Connected Layer Network
Authors: Xu Ouyang , Ma Junkai , Xu Dan , Chen Jin 
Published: February 2025

ABSTRACTFor the problem that carrier frequency offset in the 5G communication system leads to the inability of the demodulation end to correctly recover the original information sequence, a 5G signal frequency offset estimation method based on the fully connected layer network is proposed. The transmission signal adopts the 64QAM high‐order modulation mode, establishing the nonlinear mapping relationship between the IQ two‐channel signals and the frequency offset. The frequency offset value is estimated by training the model, and the frequency offset compensation is performed at the receiving end for demodulation. After simulation tests, it can achieve a 100% correct rate of frequency offset estimation under the condition of a 20 dB signal‐to‐noise ratio, and the estimation accuracy is 0.1 Hz.
Evaluating athletic field cutting height and playability
Authors: Thoms Adam W. , Dickson Kyley H. , Lindsey Alex J. , Messer Zackary W. 
Published: February 2025

AbstractSports field managers are often requested to lower height‐of‐cut (HOC) on playing surfaces by coaches so that players can run faster, but data are lacking to prove this. A study was performed at the University of Tennessee and Iowa State University to investigate the effects of HOC on Kentucky bluegrass (Poa pratensis L.) field performance and athletic field playability characteristics. Three HOCs (2.54, 5.08, and 7.62 cm) were maintained throughout the growing season and were subjected to 10 simulated games. Percent green cover was tracked after every simulated game with digital image analysis, while surface hardness was measured before games and after every five games. Traction values were tested before and after the simulated games. Percent green cover did not differ by HOC but did decline with increasing games from 98% to 49%. Surface hardness increased with increasing traffic but were never over 100 GMAX. The 2.54‐cm HOC resulted in greater force on the metatarsophalangeal joint (MTP) before and after traffic compared to the 7.62‐cm HOC. Traction values were minimally affected by the HOC and traffic. Forces applied to the MTP from the surface did increase with more games. Overall, there was minimal impact from Kentucky bluegrass being mowed at either 2.54, 5.08, and 7.62 cm on turfgrass wear, surface hardness, rotational resistance, and traction.
“Unveiling the ‘Empty Pool/Pull’”: Gambling Disorder's Impact on the Sense of Belonging to the Jewish Ultra‐Orthodox Community
Authors: Vana Noa , Gavriel‐Fried Belle , Itzhaki‐Braun Yael 
Published: February 2025

ABSTRACTClosed religious communities cultivate a robust communal identity, shared faith, values, and norms among their members, providing them with social and emotional support. Deviance carries significant consequences, specifically disintegrating members’ sense of belonging. Gambling disorder (GD) is characterized by harmful gambling behaviors that negatively affect individuals’ lives. While gambling is a prevalent recreational activity, within closed religious communities, addiction, including GD, is viewed as a violation of religious teachings, values, and communal norms. This study explores GD's impact on the sense of belonging of Jewish Ultra‐Orthodox men and their spouses in Israel. This research employed constructivist grounded theory, interviewing twenty‐two men with GD and eleven spouses and uncovered two complementary themes. The first, “Depleting versus replenishing of the personal aspects of sense of belonging,” elucidates GD's different effects on the men and spouses’ sense of belonging. The second, “Paying the toll,” illuminates the emotional experiences and actions of the men and the spouses in reaction to societal conditional negative regard directed at them, disintegrating the sense of belonging of the men, but also that of the spouses who did not deviate from communal norms. The paper introduces the novel concept of “an empty pool/pull,” portraying these individuals’ limbo state. The “empty pool” represents the depletion of faith, adherence to religious commandments, and communal values for the men, while the “empty pull” signifies the inclination of the men and the spouses to conform amid the community's unfulfilled promise of protection. The study advocates for further research and offers clinical insights for therapists.