bluuebunny/crossref_metadata_2025_split huggingface dataset:
Improving Symptom‐Based Medical Diagnosis Using Ensemble Learning Approaches
Authors: Aissaoui Ferhi Leila , Ben Amar Manel , Masmoudi Atef , Choubani Fethi , Bouallegue Ridha 
Published: February 2025

ABSTRACTSymptoms‐based health checkers are emerging as digital tools in modern healthcare offering patients the ability to self‐assess their health status by inputting symptoms and receiving diagnostic suggestions. These systems rely on machine learning models to accurately predict medical conditions based on symptom data. In this study, we explore the effectiveness of various machine learning algorithms with a particular focus on ensemble learning methods to improve the accuracy and reliability of health checkers. We evaluate multiple models—Decision Trees, Support Vector Machines (SVM), Logistic Regression, and their ensemble variations (Bagging, Stacking)—across three distinct datasets: the ‘Reference Dataset,’ ‘Cough‐DDX Dataset’ and ‘Cough‐DDX2 Dataset.’ Our results demonstrate that ensemble learning models, especially Bagging with Decision Trees and SVM, significantly outperform individual models in terms of accuracy, precision, recall, and F1 score. We also tested clinical use cases and achieved excellent results highlighting the real‐world applicability and clinical potential of our approaches.
Egg Windowing and Plastic Culture System in Caiman latirostris Embryos, Improving Hatching Success and Offer Potential Management Applications
Authors: Cainelli Julieta , Cordero Trinidad , Marcó María Virginia Parachú , Hilevski Samuel , Siroski Pablo 
Published: February 2025

ABSTRACTThe shell of crocodilian eggs is highly fragile, especially during the early stages of development, making them susceptible to cracking during laying or collection, often resulting in embryo mortality. While numerous studies have explored various techniques for artificially incubating eggs to improve hatching success, particularly concerning issues with eggshells, there is limited information available on this topic for crocodilians. The objective of this research was to assess the hatching and survival success of cracked eggs using the windowing method and ex ovo incubation of Caiman latirostris (C. latirostris) embryos in a culture vessel. We used fertile eggs with cracked shells for the windowing eggs (WE) and ex ovo incubation (EE) treatments, and fertile noncracked eggs shell as control treatment. To ensure contamination‐free incubation, all eggs were cleaned with alcohol. In the WE treatment, an eggshell section was removed, while in the EE treatment, embryos were removed from the eggshells. Each treatment was incubated in a culture vessel containing an aqueous antimicrobial solution at 31 ± 1°C. After 38 days of incubation in the culture vessel, the hatching success rates were as follows: 66.67% for WE, 0% for EE, and 100% for the control. Subsequently, the survival of hatchlings from the WE and control groups was 100%. The results suggest that incubation in artificial culture vessels enhances the viability and hatching success of C. latirostris cracked eggs. It works as an effective antimicrobial barrier maintaining sterile conditions and does not interfere with embryonic development. Moreover, the WE method offers unique possibilities for the monitoring of developmental studies and other manipulations of crocodilian embryos. However, the EE method is not advisable, as it does not reproduce the conditions inside the egg.
Associations between the timing of 24 h physical activity and diabetes mellitus: results from a nationally representative sample of the US population
Authors: Xiao Qian , Feng Qiuyu , Rutter Martin K. , Albalak Gali , Wang Heming , Noordam Raymond 
Published: February 2025

Abstract

Aims/hypothesis
Growing evidence suggests that timing may be an important aspect of physical activity that influences cardiometabolic health. However, the current literature is inconclusive regarding the time of day that physical activity offers the greatest metabolic advantages. We investigated associations between hourly physical activity levels and diabetes mellitus and glycaemic biomarkers in a cross-sectional and nationally representative sample of US adults.

Methods
We studied 7074 adults (mean age 48 years; 52% women) from the National Health and Nutrition Examination Survey (2011–2014). Physical activity was measured by actigraphy. A monitor-independent movement summary (MIMS) unit was used to derive the total activity level (divided into quintiles) for hourly windows that were defined relative to sleep timing and according to clock time. The primary outcome was prevalent diabetes, and secondary outcomes included fasting glucose, fasting insulin, HOMA-IR and 2 h OGTT results.

Results
Physical activity levels in late morning and late afternoon were associated with lower adjusted odds of diabetes. Specifically, in late morning (8:01–9:00 h after the sleep midpoint), the highest quintile of activity was associated with a 35% decrease (OR 0.65; 95% CI 0.44, 0.96) in the odds of diabetes when compared with the lowest quintile, while in late afternoon (11:01–17:00 h after the sleep midpoint), the highest quintiles were associated with 56% and 36% lower odds (OR 0.44; 95% CI 0.29, 0.69 and OR 0.64; 95% CI 0.43, 0.95). Higher night-time activity was associated with higher odds of diabetes. Similar patterns of results were observed with OGTT data and across subgroups of age, gender, race/ethnicity, chronotype and sleep duration.

Conclusions/interpretation
Our findings suggest that the timing of physical activity may modulate its metabolic effects.

Graphical Abstract
Dissociation of intake and incentive sensitization during intermittent- and continuous-access heroin self-administration in rats
Authors: Rakowski Elizabeth A. , King Christopher P. , Thompson Brady M. , Santos Gabriel , Holmes Esther , Solberg Woods Leah C. , Polesskaya Oksana , Palmer Abraham A. , Meyer Paul J. 
Published: February 2025

Abstract

Rationale
Opioid misuse is a prominent public health concern, although patterns of use may confer different vulnerability to relapse. Continuous-access (ContA) self-administration has traditionally been used in preclinical models to study drug-motivated behaviors and produces robust escalation of intake and tolerance development. Alternatively, studies using intermittent access (IntA), where self-administration occurs in discrete drug-available periods, suggest that overall intake may be dissociable from subsequent increases in motivation (i.e., incentive sensitization). However, IntA paradigms have focused primarily on psychostimulants like cocaine and methamphetamine and have not been as comprehensively studied with opioids.

Objective
We compared two paradigms of heroin self-administration, ContA and IntA, to assess their effect on heroin intake and motivation.

Methods
Male and female rats were trained to self-administer heroin, then were transitioned to either ContA or IntA paradigms. Following self-administration, rats were tested in progressive-ratio, behavioral economics threshold probe, and conditioned reinforcement tests to measure motivation-related behaviors.

Results
Both patterns of intake evoked similar heroin-directed motivation during progressive-ratio and conditioned reinforcement tests, despite lower overall intake throughout IntA for male rats. Females had similar responding between treatments in self-administration and progressive-ratio even though IntA rats had less time to earn infusions. During threshold probe, IntA-trained subjects showed more inelastic responding (lower α values), suggesting a greater degree of dependence-like behavior.

Conclusions
These results suggest the importance of dissociating heroin intake from incentive sensitization and emphasize the significance of sex differences as a modifier of heroin consumption and motivation.
Exploring transcriptomic signatures in sudden unexplained death (SUD) cases
Authors: Neubauer Jacqueline , Dørum Guro , Haas Cordula 
Published: February 2025

Abstract

Background
Molecular autopsy in sudden unexplained death (SUD) has successfully identified pathogenic variants in cardiovascular genes in a substantial proportion of cases, contributing to prevention strategies in family members. However, many SUD cases remain genetically unresolved, prompting investigations into other omics technologies to better understand the pathogenic mechanisms leading to a sudden death event. In this study, whole transcriptome sequencing was performed on heart samples from 43 SUD cases and 17 heart-healthy controls, with the aim to identify disease-specific transcriptome signatures in sudden unexplained death.

Results
PCA based on the top 500 genes with the highest variance among the samples showed no clear separation between SUD and controls or among the three SUD subgroups. DESeq2 identified 1,676 differentially expressed genes between SUD and controls with significantly upregulated genes involved in biological processes such as angiogenesis, blood vessel development, vasculogenesis and cell adhesion. Pathway analysis of the differentially expressed genes showed that most were downregulated and involved in amide/peptide biosynthesis and fatty acid metabolism. Additional analysis of SUD subgroups revealed unique gene expression patterns and highlighted differentially expressed genes within each subgroup.

Conclusion
Gene expression analysis of SUD heart tissue is a promising approach to identify cardiac disease-related pathways to further understand the pathological mechanisms leading to a sudden death event. However, due to the heterogeneity of the SUD cases and the unclear phenotype, further studies in larger cohorts are needed.
Which technical difficulty score can best predict postoperative outcomes after minimally invasive liver resections?
Authors: Bolm Louisa , Nebbia Martina , Catalano Onofrio , Lionetto Gabriella , von Bresinsky Johanna , Duhn Jannis , Arya Shahrzad , Ventin Marco , Straesser Julia , Ferrone Cristina R. 
Published: February 2025

Abstract

Background
To assess technical difficulty scores for laparoscopic liver resections (LLR) in a large well-characterized cohort of low to high difficulty LLR.

Methods
Patients undergoing LLR and open liver resection (OLS) (2007–2022) at Massachusetts General Hospital were included. Patients were classified according to the technical difficulty scores Ban difficulty score, IWATE criteria, Hasegawa score, IMM score, and Southhampton score (SHH) and calibration of these scores in predicting postoperative outcome parameters was assessed.

Results
301 patients underwent LLR. Median age was 59 years and 58.5% of the patients were female. Median lesion size was 42.2 mm, median operative time was 197.7 min, and median estimated blood loss was 400.5 ml. According to the different scoring systems, 18.9% (SHH) to 52.2% (IWATE) of the LLR were high difficulty. Overall intraoperative events according to the modified Satava classification grade II (6.6%) and grade III (2.7%) were low as was postoperative 90 days major morbidity (5.3%) and mortality (1.0%). The respective scores’ calibration for predicting non-textbook outcomes, intraoperative events, operative time, major postoperative morbidity, blood transfusion rates, and length of hospital stay was moderate to good for the respective scores and best for the IWATE criteria.

Discussion
Even high technical difficulty LLR can be performed with low postoperative morbidity and mortality rates. The scores evaluated performed well in predicting major liver surgery outome parameters. Among the different difficulty scoring systems, the IWATE criteria performed best.
Post-ocr text correction for Bulgarian historical documents
Authors: Beshirov Angel , Dobreva Milena , Dimitrov Dimitar , Hardalov Momchil , Koychev Ivan , Nakov Preslav 
Published: February 2025

Abstract
The digitization of historical documents is crucial for preserving the cultural heritage of the society. An essential step in this process is converting scanned images to text using Optical Character Recognition (OCR), which can enable further search, information extraction, etc. Unfortunately, this is a challenging problem as standard OCR tools are not tailored to deal with historical orthography or challenging layouts. Thus, it is standard to apply an additional text correction step on the OCR output when dealing with such documents. In this work, we focus on Bulgarian, and we create the first benchmark dataset for evaluating the OCR text correction for historical Bulgarian documents written in the first standardized Bulgarian orthography: the Drinov orthography from the 19th century. We further develop a method for automatically generating synthetic data in this orthography, as well as in the subsequent Ivanchev orthography, by leveraging vast amounts of contemporary literature Bulgarian texts. We then use state-of-the-art LLMs and encoder-decoder framework which we augment with diagonal attention loss and copy and coverage mechanisms to improve the post-OCR text correction. The proposed method reduces the errors introduced during the recognition. It improves the quality of the documents by 25%, which is an increase of 16% compared to the state-of-the-art on the ICDAR 2019 Bulgarian dataset. We release our data and code at https://github.com/angelbeshirov/post-ocr-text-correction.
Foraging with your eyes: a novel task to study cognitive strategies involved in (visual) foraging behaviour
Authors: Green Matthew , Segen Vladislava , Korstjens Amanda , Meso Andrew Isaac , Thomas Tessa , Wiener Jan M. 
Published: February 2025

Abstract
In this study we introduce a new gaze-contingent visual foraging task in which participants searched through an environment by looking at trees displayed on a computer screen. If the looked-at tree contained a fruit item, the item became visible and was collected. In each trial, the participant’s task was to forage for a defined number of fruit items. In two experiments, fruit items were either randomly distributed about the trees (dispersed condition) or organised in one large patch (patchy condition). In the second experiment, we addressed the role of memory for foraging by including a condition that did not require memorising which trees had already been visited by changing their appearance (tree fading). Foraging performance was superior in the patchy as compared to the dispersed condition and benefited from tree-fading. In addition, with further analyses on search behaviour, these results suggest (1) that participants were sensitive to the distribution of resources, (2) that they adapted their search/foraging strategy accordingly, and (3) that foraging behaviour is in line with predictions derived from foraging theories, specifically area-restricted search, developed for large scale spatial foraging. We therefore argue that the visual search task presented shares characteristics and cognitive mechanisms involved in successful large-scale search and foraging behaviour and can therefore be successfully employed to study these mechanisms.
Convergence of ease-controlled random reshuffling gradient algorithms under Lipschitz smoothness
Authors: Seccia Ruggiero , Coppola Corrado , Liuzzi Giampaolo , Palagi Laura 
Published: February 2025

Abstract
In this work, we consider minimizing the average of a very large number of smooth and possibly non-convex functions, and we focus on two widely used minibatch frameworks to tackle this optimization problem: incremental gradient (IG) and random reshuffling (RR). We define ease-controlled modifications of the IG/RR schemes, which require a light additional computational effort but can be proved to converge to a stationary point under weak and standard assumptions. In particular, we define two algorithmic schemes in which the IG/RR iteration is controlled by using a watchdog rule and a derivative-free linesearch that activates only sporadically to adjust the stepsize so to guarantee convergence. The two schemes differ in the watchdog rule and the linesearch, which are performed using either a monotonic or a non-monotonic rule. The two schemes allow controlling the updating of the stepsize used in the main IG/RR iteration, avoiding the use of pre-set rules that may drive the stepsize to zero too fast, reducing the effort in designing effective updating rules of the stepsize. We perform computational analysis using different deep neural architectures and a benchmark of varying-size datasets. We compare our implementation with both a full batch gradient method (i.e. L-BFGS) and a fair implementation of IG/RR methods, proving that our algorithms require a similar computational effort compared to the other online algorithms and that the control on the learning rate may allow a faster decrease of the objective function.
Sobolev Regularity for the Bergman Projection on Relatively Compact Domains in Hermitian Manifolds
Authors: Harrington Phillip S. 
Published: February 2025

Abstract
Generalizing a result of Berndtsson and Charpentier, we provide sufficient conditions for

$$L^2$$

L
2

Sobolev regularity of the Bergman projection acting on

$$L^2$$

L
2

sections of a holomorphic line bundle restricted to a relatively compact domain with Lipschitz boundary in a Hermitian manifold. We provide examples to show that our methods work for domains in Hopf manifolds endowed with a suitable Hermitian metric.
Impacts of Municipal and Industrial Organic Waste Components on the Kinetics and Potentials of Biomethane Production via Anaerobic Digestion
Authors: Qiu Yaojing , Lower Lillian , Rondon Berrio Vanessa , Cunniffe Julia , Kolar Praveen , Cheng Jay , Sagues William Joe 
Published: February 2025

Abstract
Extensive biomass characterization, biomethane potential reactions, and kinetic modeling was performed on a variety of municipal and industrial organic wastes, including household, grocery and commercial wastes, as well as ethanol plant residues, to elucidate the effects of individual biomass components on the kinetics and total production of biomethane via mesophilic anaerobic digestion. Municipal solid waste with high cellulose (25%), lipid (10%), and starch contents (5%) achieved the highest cumulative methane production of 526 mL/g-VS, but had the longest lag phase due to the high lignin content. Vinasse residue from industrial ethanol production exhibited the lowest cumulative methane production of 302 mL/g-VS, likely due to the low cellulose (16%) and lipid contents (5%) as well as the high percentage of impurities including potassium (12%). Despite having the 3rd highest volatile solids, Vinasse had the lowest total methane production. The two feedstocks with the lowest ash contents had the highest cumulative methane productions, highlighting the potential impact of ash on methane productivity. Additionally, five kinetic models were selected and evaluated in this study based on their prior successful applications in anaerobic digestion studies. Among them, the Modified Logistic model best fit methane production from municipal solid waste with longer lag phases, while the First-order and Modified Gompertz models were more suited to industrial waste with minimal lag phases, with the Modified Gompertz model proving to be the most versatile across the five municipal and industrial organic waste feedstocks.

Graphical Abstract
Lattice Boltzmann model and its GPU acceleration for transient flow in channel and pressurized pipe combined water delivery system
Authors: Meng Wanwan , Yang Shuqing , Lu Xuheng , Peng Yongqin , Diao Wei , Zhang Chunze 
Published: February 2025

Abstract
The open channel and pressurized pipe combined water delivery systems usually have long pipelines, many overflow structures, and especially with two different flow regimes, making the transient simulations complicated and time-consuming. A graphics processing unit (GPU)-accelerated lattice Boltzmann model (LBM) is proposed to solve the above problem. The LBM model for water hammer in pipes is improved by introducing the one dimensional with two lattice velocities discrete model (D1Q2). Compared with the existing the one dimensional with three lattice velocities discrete model, the D1Q2 model has reduced the occupation of computational resources, and the boundary processing has become simple. By simulating the transient process of a pipe network system, the results are in good agreement with those of the method of characteristics (MOC), and the speedup ratio reaches 60.5. Then, the water hammer LBM model and shallow water LBM model are coupled to simulate the transient process of the open channel and pressurized pipe combined water delivery system, and its GPU parallel computing scheme is achieved. Practical application shows that the results agree well with those of MOC, and the maximum speedup ratio reaches 92.96, indicating the great application potential of the proposed model.
Navigating the participatory turn in agricultural and food research: Best practice from citizen science
Authors: Ajates Raquel , Benyei Petra , Avery Helen , Butkeviciene Egle , Czeglédi Alexandra , Desclaux Dominique , Hager Gerid , Heinisch Barbara , Hoebe Peter N. , van Noordwijk Toos C. G. E. , Barzman Marco 
Published: February 2025

Abstract
Food systems have enormous impacts on people and the planet, with agriculture and food research becoming strategic for many countries. However, the way this research is conducted and the rise of new agri-food technologies have ethical and socio-economic implications. To address these, many scholars are gaining interest in participatory methods, such as citizen science, but are unfamiliar with the latest debates on ethical and methodological issues surrounding non-academic stakeholder engagement. In this perspective paper, we revisit the European Citizen Science Association’s (ECSA) Ten Principles of Citizen Science under the specific lens of agri-food research. The discussion presented is based on a review of the state of the art from academic literature, secondary data from agri-food citizen science projects, and the reflections of 11 scientist and practitioners, members of ECSA’s Agri-Food Working Group. The findings reflect theoretical, methodological, and practical implications for navigating the participatory turn in agriculture and food research.
Research on characterization methods for track irregularities
Authors: Xin Lifeng , Xu Lei , Zhang Jiaxin , Pei Menglin , Mao Jianfeng , Wang Dangxiong 
Published: February 2025

Abstract
The characterization of track irregularities is crucial in railway dynamics, as track irregularities are the primary source of internal excitation in railway systems. In this paper, three mathematical models are proposed to characterize the track irregularities under different circumstances. The first model is a novel explicit track spectrum function, which performs better in reflecting the inherent periodic components of track irregularities than the existing track spectra. On this foundation, the second model, a parameterized track spectrum random model, is proposed to represent the vast measured track irregularities from the probabilistic perspective. Finally, the third model, an imprecise track spectrum interval model based on a neighborhood uniform sampling Bootstrap method, is presented to identify the confidential interval of the track spectra when the track irregularity data are limited. Three examples are illustrated to demonstrate the feasibility of the three track irregularity models in characterizing the track irregularities in different conditions. This research can help capture the railway deformation status and optimize track maintenance strategies.