bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cognitive training with adaptive algorithm improves cognitive ability in older people with MCI
Authors: Li Chenxi , Li Meiyun , Shang Yunfeng 
Published: January 2025

AbstractRecent discoveries indicating that the brain retains its ability to adapt and change throughout life have sparked interest in cognitive training (CT) as a possible means to postpone the development of dementia. Despite this, most research has focused on confirming the efficacy of training outcomes, with few studies examining the correlation between performance and results across various stages of training. In particular, the relationship between initial performance and the extent of improvement, the rate of learning, and the asymptotic performance level throughout the learning curve remains ambiguous. In this study, older adults underwent ten days of selective attention training using an adaptive algorithm, which enabled a detailed analysis of the learning curve's progression. Cognitive abilities were assessed before and after CT using the Mini-mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA). The findings indicated that: (1) Initial performance is positively correlated with Learning amount and asymptotic performance level, and negatively correlated with learning speed; (2) Age is negatively correlated with learning speed, while it is positively correlated with the other three parameters. (3) Higher pre-training MMSE scores predicted higher post-training MMSE scores but less improvement; (4) Higher pre-training MoCA scores predicted higher post-training MoCA scores and less improvement; (5) The parameters of the learning curve did not correlate with performance on the MMSE or MoCA. These results indicate that: (1)Selective attention training using adaptive algorithms is an effective tool for cognitive intervention; (2) Older individuals with poor baseline cognitive abilities require more diversified cognitive training; (3) The study supports the compensation hypothesis.
Pivotal role of the optimal dose in allergen immunotherapy
Authors: Werminghaus Pascal , Becker Sven , Klimek Ludger , Cuevas Mandy , Rosewich Martin , Hermanns Frauke , Graessel Anke , de Kam Pieter-Jan , Kramer Matthias F. 
Published: January 2025

Abstract
The transitioning of named patient products (NPPs) of therapy allergens is regulated under the German therapy allergen ordinance (TAO) since 2008. The establishment of a sound dose–response relationship constitutes a pivotal aspect in clinical development programs of drugs in general. Up to now, there are only few comprehensive studies dedicated to the determination of a dose–response relationship in allergen immunotherapy (AIT) because of various challenges. Among these aggravating factors are high placebo effects, variability of trial endpoints and especially for native allergens a narrow therapeutic window and safety profile. The phase II trials of the modified allergen tyrosine associated—monophosphoryl lipid A (MATA MPL) platform for birch and grasses established convincing and significant dose–response relationships decisive for AIT product optimization. The significant dose–response relationship for birch and grass allergoids reached an efficacy plateau and allowed the definition of critical milestones in drug development such as the median effective dose (ED50) for the MATA MPL platform combining modified allergens (allergoids) with microcrystalline tyrosine (MCT) and MPL in an adjuvant system. This marked a pivotal milestone in AIT drug development allowing the definition of the “optimal dose” (optimal risk–benefit ratio) to be taken forward to phase III trial. The MATA MPL platform is characterized by a scientifically sound dose–response relationship across allergens which underlines the pivotal role of a well-defined optimal dose as a success factor for phase III.
Assessment of Surface Water Quality Using Chemometric Tools: A Case Study of Jabi Lake, Abuja, Nigeria
Authors: Adejuwon E. O. , Ogwueleka T. C. , Ogungbemi E. O. , Prabhu R. , Rendon-Nava A. , Yates K. 
Published: January 2025

AbstractWater pollution has become a growing threat to human society and natural ecosystems in recent decades. It increases the need to understand surface water quality assessment better using chemometric tools within aquatic systems. This study sampled the water quality of 21 parameters at multiple sampling points in Jabi Lake during wet and dry seasons (August–December 2021) using various statistical methods including cluster analysis, principal component analysis/factorial analysis, discriminant analysis, and box plot analysis. These samples were examined for physicochemical parameters employing standard techniques. The study revealed significant seasonal variations in water quality. During the wet season, key measurements included total dissolved solids (100.40 mg/l), dissolved oxygen (13.72 mg/l), and electrical conductivity (97.14 µs/cm). The dry season showed higher levels of most parameters, with total dissolved solids at 137.91 mg/l and electrical conductivity at 230.93 µs/cm. Statistical analysis identified strong correlations between various parameters, notably between phosphate and total hardness in the wet season (r = 0.978, α = 0.05) and between pH and temperature in the dry season (r = 0.995, α = 0.05). The study identified four principal components explaining 98.5–100% of the variance, representing various pollution sources including organic waste, domestic sewage, and natural factors. The findings indicated that dry season water samples were more polluted, with some parameters exceeding World Health Organisation standards, suggesting potential health risks. The research demonstrated the effectiveness of multivariate statistical techniques in analysing complex water quality data and provided valuable insights for water resource management, particularly regarding seasonal variations' impact on water quality.
Advancing modified biochar for sustainable agriculture: a comprehensive review on characterization, analysis, and soil performance
Authors: Fakhar Ali , Galgo Snowie Jane C. , Canatoy Ronley C. , Rafique Mazhar , Sarfraz Rubab , Farooque Aitazaz Ahsan , Khan Muhammad Israr 
Published: January 2025

AbstractBiochar is a carbon-rich material produced through the pyrolysis of various feedstocks. It can be further modified to enhance its properties and is referred to as modified biochar (MB). The research interest in MB application in soil has been on the surge over the past decade. However, the potential benefits of MB are considerable, and its efficiency can be subject to various influencing factors. For instance, unknown physicochemical characteristics, outdated analytical techniques, and a limited understanding of soil factors that could impact its effectiveness after application. This paper reviewed the recent literature pertaining to MB and its evolved physicochemical characteristics to provide a comprehensive understanding beyond synthesis techniques. These include surface area, porosity, alkalinity, pH, elemental composition, and functional groups. Furthermore, it explored innovative analytical methods for characterizing these properties and evaluating their effectiveness in soil applications. In addition to exploring the potential benefits and limitations of utilizing MB as a soil amendment, this article delved into the soil factors that influence its efficacy, along with the latest research findings and advancements in MB technology. Overall, this study will facilitate the synthesis of current knowledge and the identification of gaps in our understanding of MB.
Graphical Abstract
Data-driven analysis in 3D concrete printing: predicting and optimizing construction mixtures
Authors: Schossler Rodrigo Teixeira , Ullah Shafi , Alajlan Zaid , Yu Xiong 
Published: January 2025

AbstractAccurately predicting 3D concrete printing (3DCP) properties through the utilization of machine learning holds promise for advancing cost-effective, eco-friendly construction practices that prioritize safety, reliability, and environmental sustainability. In this study, a comprehensive exploration of seven regression models was undertaken, complemented by the application of Bayesian optimization techniques to forecast critical metrics such as compressive strength, pump speed, and carbon footprint within the realm of 3DCP technology. Drawing upon a compilation of various 3DCP mixtures sourced from existing literature, an intricate carbon footprint calculation methodology was devised, resulting in the establishment of a bespoke database tailored to the study’s objectives. The performance evaluation of the developed models was conducted through the analysis of key statistical indicators, including R2, RMSE, MAE, and Pearson correlation. To enhance the robustness and generalizability of the models, a rigorous tenfold cross-validation strategy coupled with a strategic introduction of noise was employed during the validation process. The incorporation of Shapley Additive Explanations (SHAP) analysis provided insightful interpretability into the predictive capabilities of the models, enabling a nuanced understanding of the underlying relationships between input variables and target outputs. Furthermore, the application of multi-objective optimization techniques facilitated judicious decision-making processes, enabling the identification of optimal 3DCP mixture compositions that concurrently enhance performance metrics, reduce operational costs, and mitigate CO₂ emissions.
An interaction-fair semi-decentralized trajectory planner for connected and autonomous vehicles
Authors: Liu Zhengqin , Lei Jinlong , Yi Peng , Hong Yiguang 
Published: January 2025

AbstractLately, there has been a lot of interest in game-theoretic approaches to the trajectory planning of autonomous vehicles (AVs). But most methods solve the game independently for each AV while lacking coordination mechanisms, and hence result in redundant computation and fail to converge to the same equilibrium, which presents challenges in computational efficiency and safety. Moreover, most studies rely on the strong assumption of knowing the intentions of all other AVs. This paper designs a novel autonomous vehicle trajectory planning approach to resolve the computational efficiency and safety problems in uncoordinated trajectory planning by exploiting vehicle-to-everything (V2X) technology. Firstly, the trajectory planning for connected and autonomous vehicles (CAVs) is formulated as a game with coupled safety constraints. We then define the interaction fairness of the planned trajectories and prove that interaction-fair trajectories correspond to the variational equilibrium (VE) of this game. Subsequently, we propose a semi-decentralized planner for the vehicles to seek VE-based fair trajectories, in which each CAV optimizes its individual trajectory based on neighboring CAVs’ information shared through V2X, and the roadside unit takes the role of updating multipliers for collision avoidance constraints. The approach can significantly improve computational efficiency through parallel computing among CAVs, and enhance the safety of planned trajectories by ensuring equilibrium concordance among CAVs. Finally, we conduct Monte Carlo experiments in multiple situations at an intersection, where the empirical results show the advantages of SVEP, including the fast computation speed, a small communication payload, high scalability, equilibrium concordance, and safety, making it a promising solution for trajectory planning in connected traffic scenarios. To the best of our knowledge, this is the first study to achieve semi-distributed solving of a game with coupled constraints in a CAV trajectory planning problem.
An infant case of autoimmune enteropathy: pivotal role of ultrasound in the management
Authors: Calvaruso Antonino , Baldazzi Michelangelo , Guida Fiorentina , Greco Laura , Di Vincenzo Anna Olga , Vivacqua Donatella , Marcolin Laura , Rossi Eugenio , Minelli Rocco , Albertini Elisa , Lovato Luigi , Lanari Marcello 
Published: January 2025

AbstractAutoimmune enteropathy (AIE) is a rare cause of chronic intractable diarrhea. We report the case of a 2-month-old infant who presented with intractable diarrhea and significant weight loss. Once clinical stability was achieved, endoscopy allowed AIE to be diagnosed. Ultrasound studies (US) correlated clinical and laboratory findings with the gastrointestinal inflammatory state during the course of the disease. This approach facilitates an appropriate and timely therapeutic strategy, with immunosuppressive treatment currently representing the primary therapeutic option.
Dissecting casual effects of diet on the risk of inflammatory bowel disease and the potential mediation by gut microbiota: a Mendelian randomization study
Authors: Liu Tianqi , Zhou Lanqi , Lv Jiayao , Qu Yizhe , Shi Lin 
Published: January 2025

Abstract
Background
Diet plays a fundamental role in maintaining intestinal health. Here, we investigated whether there is the causal association of diet with inflammatory bowel disease (IBD), and the potential effect of gut microbiota on these relationships, by using two-sample Mendelian randomization (MR) analyses.

Materials and methods
Genetic instruments for 29 dietary intake variables and 139 food-liking traits were obtained from the UK-Biobank. The GWAS statistics on IBD and its two subtypes, ulcerative colitis (UC) and Crohn's disease (CD), were obtained from the IEU database. GWAS of gut microbiome was obtained from the MiBioGen alliance. Associations were assessed by inverse-variance weighted method, MR-Egger, weighted median, simple mode and weighted mode. Gut microbiome was assessed for the mediated effect on the associations of dietary variables with IBD.

Results
We identified causal associations between 21 dietary factors (including 3 dietary intake and 18 food-liking traits) with IBD, UC and/or CD. These dietary variables affected 22 bacteria genera, and among them, 9 were causally associated with the IBD risk. Notably, Ruminococcus_torques_group, a symbiotic bacterium possessing anti-inflammatory properties, significantly mediated the relationship between various food-liking traits (e.g., liking for acquired taste, strong flavor, blue cheese and beans) and IBD risks. Ruminococcaceae UCG003 showed a significant mediating efficacy in the relation of liking for sharp flavor and CD.

Conclusion
Our study reveals the causal impacts of dietary factors on the risk of IBD and its subtypes, and provides novel insights on the potential of modulating intestinal microbiota as novel therapeutic targets between diet and IBD prevention.
Determinants of Market Participation among Milk Producers in Kyrgyzstan
Authors: Nurullaev Akhmadjon , Park Eunchun , Ahrendsen Bruce , Speelman Stijn , Connor Lawson 
Published: January 2025

Abstract
Numerous studies have been conducted to comprehend the economic importance of market participation for producers. However, a significant gap remains, particularly in Central Asia. This study assesses market participation drivers for Kyrgyzstan’s milk producers using the Life in Kyrgyzstan dataset, encompassing a comprehensive nationwide farm-level survey. Findings reveal that household assets boost market entry and sales volume, whereas distance from markets discourages participation but can increase sales for active sellers, reflecting transportation cost strategies. The insights inform policy interventions benefiting rural small-scale milk producers in Central Asian countries that share similar cultural backgrounds.
Major Internal Fires in Dutch Hospitals: A Scoping Review
Authors: van Stekelenburg Brett C.A. , Klokman Vincent W. , Tan Edward C.T.H. , Barten Dennis G. 
Published: January 2025

Abstract

Objectives
Fires are among the most feared incidents that can occur in a hospital. Hospital fires will disrupt care continuity, may require the evacuation of patients and have the potential to result in injuries or even deaths. The aim of this study is to gain insight into hospital fires in the Netherlands over a 20-year period.

Methods
Systematic scoping review of news articles mentioning hospital fires in the Netherlands retrieved from the LexisNexis database, Google, Google News, PubMed, and EMBASE between 2000 and 2020. Hospital fires were included if they were associated with the closure of hospital departments or intervention units and/or evacuations. The cause, location, involved departments, need for evacuation, and the number of casualties were evaluated.

Results
Twenty-four major hospital fires were identified. More than half of these were caused by technical failures, and in 6 cases (25%), the fires were attributed to patients. In 71% of the incidents, acute care departments were affected by the fire. Twenty fires (83%) resulted in the evacuation of patients. In 2 cases, the fire resulted in the death of a patient.

Conclusions
Patient-attributed fires are a significant cause of major hospital fires in the Netherlands. Prevention and mitigation measures should be implemented accordingly.
Who Can Help Me? Citizens’ Help-Seeking on Weibo During the Shanghai Lockdown
Authors: Guo Difan , Liu Shaoqiang , Sun Yao 
Published: January 2025

Abstract

Objective
In the context of the Omicron-induced lockdown in Shanghai, this paper investigated the appeals for assistance by citizens on Weibo, aiming to understand their principal challenges and immediate needs.

Methods
This paper collected Weibo posts (N = 1040) containing the keyword “Shanghai Anti-epidemic Help” during the citywide lockdown. The online help requests from Shanghai citizens were analyzed across 7 dimensions, including the help sought, level of urgency, help recipient, the intended beneficiary of the help, expression, position, and emotion.

Results
The study found that the most common requests for assistance were related to social isolation, specifically in the areas of home and community (34.81%), isolation (10.86%), and personal freedom (7.31%). Of all help requests, 11.83% were deemed very urgent. Most of the Weibo posts sent out a plea for help to Internet users (56.06%), primarily requesting help for themselves (26.25%) or their families (27.60%).

Conclusions
The study found that personal freedom, food, and medical care were the most frequently sought help from the public, and most of the public’s positions and emotions were pessimistic. The relevant findings revealed the public’s needs and status during the city closure, providing a reference for emergency preparedness in public health events or emergencies.
The Investigation of Quality of Life and Post-traumatic Stress Disorder Levels of Midwifery Students Experiencing an Earthquake
Authors: Yıldırım Emine , Güdücü Neriman 
Published: January 2025

Abstract

Objectives
The knowledge of students’ quality of life and post-traumatic stress disorder levels, investigation of the relationship between them, and taking measures are essential in terms of guiding the necessary interventions. This study was conducted to determine the quality of life and post-traumatic stress disorder levels of midwifery students experiencing an earthquake.

Methods
This descriptive and correlational study was conducted with 363 midwifery students who had experienced the Kahramanmaras, Türkiye earthquake. Data were obtained using a Descriptive Information Form, the PTSD-Brief Scale, and the World Health Organization Quality of Life Scale (WHOQOL-BREF).

Results
The rate of post-traumatic stress disorder in the sample studied (n = 363), which consisted of midwifery students who would work in the field of health, was 21.5% 2 months after the earthquake. The multiple linear regression analysis indicated that factors predicting post-traumatic stress disorder following the earthquake were quality of life score related to physical and environmental domains, damage status of the house, presence of family history of depression, and smoking status.

Conclusions
This study, which was conducted 2 months following the earthquakes, showed that living spaces had an impact on the occurrence of post-traumatic stress disorder symptoms.
Fight or Flight: Emergency Health Care Workers’ Willingness to Work during Crises and Disasters. A Cross-Sectional Multicenter Study in the Netherlands
Authors: Engels Lindsy M.J. , Barten Dennis G. , Boumans Thimo J.T. , Gaakeer Menno I. , Latten Gideon H.P. , Mehagnoul Jannet , Tapirdamaz Özlem , van Osch Frits , Mortelmans Luc 
Published: January 2025

Abstract

Objective
Expanding staff levels is a strategy for hospitals to increase their surge capacity. The aim of this study was to evaluate whether emergency health care workers (HCWs) are willing to work during crises or disasters, and which working conditions influence their decisions.

Methods
HCWs in the emergency departments (EDs) and intensive care units (ICUs) of 5 Dutch hospitals were surveyed about various disaster scenarios. For each scenario, HCWs were asked about their willingness to work (WTW) and which conditions would influence their decision. Knowledge, perceived risk, and danger were assessed per scenario.

Results
A total of 306 out of 630 HCWs completed the survey. Influenza epidemics, SARS-CoV-2 pandemics, and natural disasters were associated with the highest WTW rates (69.0%, 63.7%, and 53.3%, respectively). WTW rate was lowest in nuclear incident (4.6%) and dirty bomb (3.3%) scenarios. WTW rate was higher in physicians than in nurses. Male ED HCWs, single HCWs, and childless HCWs were more often willing to work. Personal protective equipment (PPE) and the safety of HCWs’ families were the most important working conditions. Perceived knowledge scored lowest in the dirty bomb, biological, and nuclear incident scenarios. These scenarios were rated highest with respect to perceived danger.

Conclusions
WTW depends on disaster type, profession, and department. The provision of PPE and the safety of HCWs’ families were found to be the predominant favorable working conditions.
Pathways to care for psychosis in rural Uganda: Mixed-methods study of individuals with psychosis, family members, and local leaders
Authors: Lee Yang Jae , Nakaziba Kayera Sumaya , Waimon Sophie , Agwang Grace , Menon Kailash , Samuel Sam , Dyas Aaron Damon , Nkolo Travor , Ingabire Haba , Wykoff Jason , Hobbs Olivia , Kazungu Rauben , Basiimwa Job , Rosenheck Robert , Ashaba Scholastic , Tsai Alexander C. 
Published: January 2025

Abstract

Background
Low- and middle-income countries (LMICs) bear a disproportionate burden of mental illness, with limited access to biomedical care. This study examined pathways to care for psychosis in rural Uganda, exploring factors influencing treatment choices.

Methods
We conducted a mixed-methods study in Buyende District, Uganda, involving 67 in-depth interviews and 4 focus group discussions (data collection continued until thematic saturation was reached) with individuals with psychotic disorders, family members, and local leaders. Structured questionnaires were administered to 41 individuals with psychotic disorders.

Results
Three main themes emerged: (1) Positive attitudes towards biomedical providers, (2) Barriers to accessing biomedical care (3) Perceived etiologies of mental illness that influenced care-seeking behaviors. While 81% of participants eventually accessed biomedical care, the median time to first biomedical contact was 52 days, compared to 7 days for any care modality.

Conclusions
Despite a preference for biomedical care, structural barriers and diverse illness perceptions led many to seek pluralistic care pathways. Enhancing access to biomedical services and integrating traditional and faith healers could improve mental health outcomes in rural Uganda.