bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fine Mapping and Identification of Causal Alleles at the Ur-11 Locus Controlling Rust Resistance in Common Bean (Phaseolus vulgaris L.)
Authors: Erfatpour Mohammad , Simons Kristin , Roy Jayanta , Figueroa-Cerna Jose , Lee Rian , Beaver James , McClean Phillip , Osorno Juan M. 
Published: October 2024

Abstract

The Middle American rust resistance gene Ur-11 present in common bean (Phaseolus vulgaris L.) confers resistance to all but one known race of the pathogen Uromyces appendiculatus (Pers.) Unger. Even though progress has been made in understanding the host-pathogen interactions between common bean and U. appendiculatus, the causal alleles of the majority of rust resistance loci, including Ur-11, remain unknown. A genome-wide association study (GWAS) was conducted to identify genomic regions associated with resistance to the U. appendiculatus race 31 − 22, which is avirulent to Ur-11 but virulent to other Middle American rust resistance genes. GWAS using genotypic data consisting of approximately 71k SNP markers and phenotypic data based on the median reaction type (1 to 9 scale) of a panel of 350 Middle American breeding lines and cultivars, plus 12 germplasm lines with the Ur-11 locus derived from PI 181996, located Ur-11 on chromosome Pv11. Twenty-seven SNP markers clustered in the 55.16–55.56 Mb region of the P. vulgaris UI111 reference. Multiple DNA sequence alignments detected a missense mutation [c.1,328A > G] in the PvUI111.11G202400 gene model that encodes a leucine-rich repeat-containing protein in response to race 31 − 20. A PCR allele competitive extension marker (PACE) was developed and tested across a panel of ~ 650 Middle American dry bean genotypes. No recombination event was observed for the marker among the tested genotypes; suggesting that the polymorphism on which it is based is very close to or in the Ur-11 gene. This SNP marker will be a useful and reliable marker for marker-assisted selection.
Predicting the Progression from Clinical Normal and Mild Cognitive Impairment to Alzheimer’s Disease using Socio-Demographic, Non-Clinical, and Genetic Data with Multi-Classification Models
Authors: Memon Shoaib Ul Din , Javed Kamran , Qureshi Nameer Ul Haq , Raza Ali , Memon Rehman , Saeed Zubair , Javed Tooba 
Published: October 2024

Abstract

Dementia and cognitive impairment are the leading causes of illness in the elderly. The research objective is to predict whether the subject is Clinical Normal (CN), Mild Cognitive Impairment (MCI), or Dementia, and when the progression from MCI to Dementia occurs within four years by examining socio-demographic, clinical, and genetic factors. The author used Alzheimer’s Disease data, containing socio-demographic, non-clinical assessment, and genetic data. A grid search approach was employed to find the best classification model. Demonstrated that Support Vector Classifier performs significantly better than other classifiers, achieving F1-score of 0.78. The proposed classifier, when combined with genetic factors, improves the overall result of multi-classification, yielding an F1-score of 0.84. The study successfully identified the impact of genetic factors on the progression of dementia. These findings can contribute to lowering the disease burden on individuals, reducing healthcare costs, and aiding in the discovery of dementia-modifying therapies.
A Novel Thermal Hysteresis-RC Pressure Perturbation Dynamic Characteristic Model of Air Spring Considering the Bending Effects and Energy Dissipation Shifts of Hysteresis Loops
Authors: Chen Junjie , Liu Yajie , Xu Jinyuan , Gan Yufeng , Wu Mingyu 
Published: October 2024

Abstract

The dynamic characteristics of air springs are mightily hysteresis nonlinear, stemming from the complex structure of the rubber bellows, material nonlinearity, and pressure dependence. This paper aims to precisely capture the dynamic characteristics of air springs, particularly characterizing the pronounced bending effects at the extremes of the hysteresis loop under high amplitudes(>10mm). The friction between the cord and the rubber, the bellows viscoelasticity, and the pressure fluctuations are considered comprehensively. A novel piecewise methodology for characterizing the hysteresis loops is proposed by introducing the resistor-capacitor (RC) operator and pressure parameter. The frequency-dependent Quadratic Parabola Fractional Derivative Kelvin-Voigt Pressure Perturbation Model (QKPPM) is integrated to formulate the RC Pressure Perturbation Hysteresis Nonlinear Model of Rubber Bellows (RCPPM-RB), depicting the evolution laws of model parameters in response to the changes in amplitude, frequency and pressure of rubber bellows. Subsequently, the Thermal Hysteresis-RC Pressure Perturbation dynamic characteristic Model of air spring (TH-RCPPM) under variable working pressure is established. The test results demonstrate that the static hysteresis loops show a maximum relative error of less than 1.6%, with a hysteresis area error of 8.1%. Furthermore, the dynamic hysteresis loop and dynamic stiffness values only have maximum relative errors of 7.1% and 5.4%, respectively. The accuracy and broad applicability of the novel model proposed are verified by experiments. The research results present an innovative approach for accurately modeling the dynamic characteristics of air springs and a fresh idea for the precise characterization of the dynamic characteristics of air springs.
Morphological diversity of the sensilla of the larval mouthparts among three species of Corydalidae (Insecta, Megaloptera) with reference to their possible functions
Authors: LI YU TONG , DAI YU MENG , CAO CHENG QUAN 
Published: October 2024

Abstract

Sensory structures on the mouthparts surface of three species of Corydalidae (Insecta, Megaloptera), Acanthacorydalis asiatica, Neoneuromus ignobilis and Protohermes similis, have been studied using Scanning Electron Microscopy. They were studied to morphologically characterize and compare the sensory structures present on the mouthparts. The identified sensilla types were sensilla basiconica (SB), fin-like sensilla (FLS), sensilla trichodea (ST), sensilla peg (SP), sensilla styloconica (SS), sensilla chaetica (SCh), and forficate sensilla (FS). The potential functions of these sensilla were discussed in relation to their morphology and location. Additionally, cuticular process (CP), small spine-shaped projections (sp) and cuticular pores (cp) were identified in the sensory regions of the studied species. Morphological comparisons revealed significant diversity in the sensilla of larval mouthparts among the three species, but there may be similarities in function.
A methodological review of solicited diaries as a qualitative tool in health research in low- and middle-income countries
Authors: Akinreni Temidayo 
Published: October 2024

Abstract

Diaries have served as a vehicle to document personal narratives and as a research tool. However, diaries remain relatively underutilized in most research disciplines, particularly in the field of global health. This review aimed to explore the application, utility, and methodological potential of diaries as a qualitative data collection tool in the health sector within low- and middle-income countries. We applied a search string across several databases, which yielded 1,796 articles that were screened for eligibility. Eleven articles, covering topics including menstrual health, HIV, and mental illness, met our criteria and were included in this review. Across studies, authors highlighted a need to provide instructions in a diary’s early pages and make diaries appealing to the participants by incorporating color. Researchers and participants described diaries as an appropriate tool for conducting research especially among vulnerable populations (e.g. children) or on sensitive or stigmatized topics (e.g. HIV and menstrual health). Some participants said that diary entry clashed with existing obligations, leading to time conflicts and increased workload. Challenges related to diary comprehension suggests a need for researchers to engage more pointedly with participants to co-design diaries in a manner that facilitates understandability (e.g. language, use of audio/video recording among low literacy population) and age-appropriateness. An undercurrent across studies entailed a tension between what researchers desire from diaries (insights regarding a phenomenon of interest captured in a relatively timely manner) versus the original purpose of diaries (a space for individuals to note a variety of topics at a self-appointed pace). Studies generally under-report process insights from participants. Most studies stem from 2020 onward suggesting that this qualitative approach may continue to expand in the future. Our review organizes pertinent diary characteristics into a framework that may facilitate reporting of diary usage in global health research.
Improved Energy Equations and Thermal Functions for Diatomic Molecules: A Generalized Fractional Derivative Approach
Authors: Eyube E. S. , Makasson C. R. , Omugbe E. , Onate C. A. , Inyang E. P. , Tahir A. M. , Ojar J. U. , Najoji S. D. 
Published: October 2024

Abstract

Due to the need for accurate analysis of interactions in diatomic molecules using analytical models, this work develops expressions for ro-vibrational energy models embedding fractional parameters. These expressions are derived by solving the Schrödinger equation for a variant of the Tietz potential using the generalized fractional Nikiforov-Uvarov solution method and a Pekeris-type approximation scheme. The canonical partition function for the system is employed to formulate thermodynamic models, including Helmholtz free energy, mean thermal energy, entropy, and isochoric heat capacity. The analytical equations are applied to diatomic molecules such as CO (X (C(2) 1 Π u), and NaK (c 3 ∑ +). The percentage average absolute deviations for the pure vibrational energies of these molecules are 0.2185%, 0.0630%, 0.6984%, 0.0975%, 0.7433%, 0.1988%, 0.1684%, and 0.2645%, relative to the experimental data. The study reveals a linear decrease in Helmholtz free energy and an initial increase in heat capacity as the temperature of the system rises. The results obtained are consistent with existing literature on diatomic systems.
WITHDRAWN: Analysis of the difference between urban and rural areas in job satisfaction of primary health care workers
Authors: liu sicheng , Yang Ming , Sun Jiayi , Xu Yuan , Fang Guixia , Yang Jinxia 
Published: October 2024

Abstract

Background: The purpose of this study is to investigate the influencing factors of job satisfaction and urban-rural differences among grassroots health workers in Anhui Province, and to provide a basis for the formulation of relevant health policies.
Methods: A multi-stage sampling method was used to survey 8135 primary health care workers in Anhui Province. Data were analyzed using chi-square test, t-test, and logistic regression analysis to analyze the influencing factors of job satisfaction of primary health personnel and its urban-rural differences in Anhui Province. In addition, Fairlie decomposition analysis was used to quantify the contribution levels of different influencing factors.
Results: Out of 8135 primary health workers, 3161 (38.9%) primary health workers were dissatisfied with their jobs. The percentage of job dissatisfaction was higher among rural primary health workers (39.8%) than urban primary health workers (36.7%).Fairliedecomposition analysis showed that 13.12% of the urban-rural difference in job satisfaction could be explained mainly with gender (24.00%), average annual income (-12.22%), overtime pay (8.94%), job-reward match (- 15.76%), unit-family support (-4.24%), and burnout (15.07%) differences.
Conclusion: The results of the study will help the Chinese government to provide a basis for improving the job satisfaction of primary health care personnel, narrowing the gap between urban and rural primary health care personnel's job satisfaction, formulating relevant health policies, and promoting the better development of primary health care.
The feasibility of using individual-level loyalty card data for disease surveillance: A pilot study on COVID-19
Authors: Dolan Elizabeth , Goulding James , Lang Alexandra R , Tata Laila J , Skatova Anya 
Published: October 2024

Abstract

Background: While regional-level self-medication sales data has been shown to enhance disease surveillance, individual-level sales data remains unexplored. This pilot study evaluates the feasibility of linking individual loyalty card data with health data to improve COVID-19 forecasting accuracy. The primary aims were to test a data-sharing protocol, evaluate the data's quality and representativeness, and explore initial signals.
Methods: A data-sharing protocol was developed, considering public preferences for sharing loyalty card data for health research. Participants used Tesco Clubcard’s data portability function to share data and completed an online health survey. Descriptive analysis was primarily used due to the small sample size, and a post-hoc sample size calculation was later conducted to assess statistical power for future studies. Recruitment occurred online from 18/01/2022 to 04/02/2022, targeting 200 participants.
Results: A total of 197 participants shared loyalty card and health survey data, resulting in 893,414 transactions across 65,310 unique items purchased from 2015-2022. Participants averaged 4,653 transactions (SD 5,256) over 5.5 years (SD 836 days), with 81% purchasing medications (44 per individual, SD 68). Importantly, 56.35% disclosed pre-existing health conditions, 43.65% confirmed prescription medication use, and 42.13% specified these prescriptions. Despite variability in transaction frequency, trends in self-medication purchases aligned with participants’ reported health conditions. Gender differences were observed in purchasing behaviour, and elderly and younger populations were underrepresented. Medication purchases aligned with COVID-19 symptom spikes during the OMICRON variant, particularly for throat-related remedies. Seasonal buying patterns corresponded with higher mortality periods, and a notable connection was observed between peak deaths before the pandemic (winter 2018/2019) and medication purchases among participants with regular prescriptions.
Conclusion: This study demonstrates the feasibility of integrating individual-level loyalty card data with health information for disease monitoring, presenting a protocol adaptable for larger studies. Key considerations include refining the protocol to ensure inclusivity by addressing age group underrepresentation, health disparities, and digital exclusion. Additionally, resolving discrepancies between self-reported and actual behaviours, and managing data quality variability are essential. Researchers should also focus on gender influences and linking medication purchases to specific health conditions. By addressing these factors, personal loyalty card data could enhance public health surveillance.
Fe-phosphates in Jezero Crater: Chemical, Structural, and Spectral Evidence for an Ancient Habitable Environment on Mars
Authors: Kizovski Tanya , Schmidt Mariek , O'Neil Lauren , Jones Michael , Tosca Nicholas , Klevang David , Hurowitz Joel , Adcock Christopher , Hausrath Elisabeth , Siebach Kirsten , Wolf Uriah , Sharma Sunanda , Vanbommel Scott , McCubbin Francis , Cloutis Edward , Cable Morgan , Liu Yang , Clark Benton , Treiman Allan , Tice Michael , Catling David , Maki Justin , Bosak Tanja , Weiss Benjamin , Fairén Alberto , Christian John , Knight Abigail , Randazzo Nicolas , Jørgensen Peter , Lawson Peter , Wade Lawrence , Heirwegh Chris , Elam William , Allwood Abigail 
Published: October 2024

Abstract

Phosphorus is an essential component for life, and in-situ identification of phosphate minerals that formed in aqueous conditions directly contributes toward one of the main goals of the Mars 2020 Perseverance rover: to seek signs of ancient habitable environments. In Jezero crater, proximity science analyses within a conglomerate outcrop, “Onahu” demonstrate the presence of rare Fe3+-bearing phosphate minerals (likely beraunite, metavivianite, ferrolaueite, and/or santabarbaraite) embedded in a carbonate-rich matrix. While Fe-phosphates have been previously inferred on Mars, this work presents the most definitive in-situ identification of martian Fe-phosphate minerals to date, using textural, chemical, spectral, and diffraction analyses of discrete green-blue grains. The Fe-phosphate minerals’ textural context along with comparisons to Earth analogs suggest they likely formed after oxidation of the Fe2+-phosphate vivianite — the most common Fe-phosphate on Earth, often associated with microbial activity and organics. The Fe3+-phosphate assemblage after vivianite, and the presence of two distinct matrix domains in Onahu indicate that the conglomerate and corresponding sample collected by Perseverance (Otis_Peak) preserve a record of evolving habitable paleoenvironmental conditions on Mars. Once returned to Earth, analysis of the Fe-phosphates in the Otis_Peak sample will provide new insights into ancient habitable environments, and, if analogous to terrestrial vivianite-rich environments, potential links with microbial activity.
Tumor suppressor NME1/NM23-H1 modulates DNA binding of NF-κB RelA
Authors: Shahabi Shandy , Maurya Mano , Subramaniam Shankar , Ghosh Gourisankar 
Published: October 2024

Abstract

The dimeric NF-κB family of transcription factors activates transcription by binding sequence-specifically to DNA response elements known as κB sites, located within the promoters and enhancers of their target genes. While most NF-κB remain inactive in the cytoplasm of unstimulated cells, a small amount of RelA, one of its members, persists in the nucleus, ensuring low-level expression of genes essential for homeostasis. Several cofactors have been identified that aid in DNA binding of RelA. In this study, we identify NME1 (nucleoside diphosphate kinase 1) as a cofactor that enhances RelA's ability to bind κB sites within the promoters of a subset of its target genes, promoting their expression under both unstimulated and stimulated conditions. Depletion of NME1 influences activation or repression of several genes that are unresponsive to TNFα, despite containing κB sites in their promoters but not in clusters. This suggests that clustering of kB sites may be necessary for RelA-dependent transcription complex assembly. NME1 appears to act as a cofactor for other transcription factors to regulate these genes. NME1 does not directly contact κB DNA but interacts with RelA, with this interaction being further strengthened in the presence of κB DNA. Notably, NME1 alone has a marginal effect in enhancing RelA’s DNA binding, suggesting that NME1 likely cooperate with other cofactors to regulate DNA binding and transcription through RelA. These observations underscore the intricate assembly of transcription complexes centered on NF-κB.
Soil type (World Reference Base) map of Europe based on Ensemble Machine Learning and multiscale EO data
Authors: Minarik Robert , Hengl Tomislav , Simoes Rolf , Isik Mustafa Serkan , Ho Yu-Feng , Tian Xuemeng 
Published: October 2024

Abstract

The paper describes the production of a high spatial resolution (30 m) soil type map for the pan-EU based on the IUSS's World Reference Base classification system and Ensemble Machine Learning with a large set of covariates. 19,680 legacy soil survey points collated from multiple national and European projects were harmonized and combined to produce a consistent set of training points with a total of 185 classes. The training points were overlaid by 130 covariate layers containing climatic variables (CHELSA Bioclimatic variables), Landsat-based long-term (2000-2022) biophysical indices, multiscale terrain variables (at 30, 60, 120, 240, 480 and 960 m resolutions) and parent material variables. Predictions of soil-type probabilities were produced by fitting an ensemble model based on Random Forest and LightGBM. The results of the variable importance analysis indicate that the model is mainly driven by relief and climate factors. The accuracy assessment reveals a moderate decrease in the logarithmic loss of the model from 4.41 to 2.76 (about 37 %) compared to the dummy model. Visually, the produced predictions match existing coarse resolution (1 km) pan-EU products, but then reveal significantly more detail, especially in areas with complex topography. The intended uses of the 30 m resolution maps include: (1) to help distinguish different soil regions (cross between soil types and climatic variables), (2) to assist in predictive soil mapping of soil properties with limited laboratory data, (3) to serve as a covariate in agronomy and forest species distribution models, e.g. to map yields and for species distribution mapping. The data and code used are publicly available under an open license from https://doi.org/10.5281/zenodo.13838408 and https://github.com/AI4SoilHealth/.
Using deep learning models to decode emotional states in horses
Authors: Phelipon Romane , Lansade Lea , Razzaq Misbah 
Published: October 2024

Abstract

In this work, we present various machine learning models to predict emotional states in horses. We manually label the images to learn the task in a supervised manner. We perform data exploration and use different cropping methods, mainly based on Yolo and Faster R-CNN, to create two new datasets: 1) the cropped body, and 2) the cropped head dataset. We build different models based on convolutional neural networks (CNNs) using (un)cropped datasets and compare their performances to accurately predict emotions. The cropped head dataset yields the best results despite lacking important region of interests like a tail, which experts use to annotate images. Furthermore, we update our models using various techniques, such as transfer learning and fine-tuning to further improve their performance. The best performance is achieved through a model based on stacking principals, which gave a boost to the overall performance with an accuracy of 87%, precision of 79%, and recall of 97%. Finally, we employ three interpretation methods to understand the internal workings of our models. Different interpretation methods seem to highlight different features of the same model. We found that only LIME appears to detect some of the features that are used by experts to annotate emotional states.
Half-Quantized Quantum Hall Plateaus in the Confined Geometry of Graphene
Authors: Kumar Manohar , Pandey Preeti , Manna Sourav , Frei Kristiana , Saji Jerin , Denis Anne , Savin Alexander , Watanabe Kenji , Taniguchi Takashi , Hakonen Pertti , Das Ankur 
Published: October 2024

Abstract

Since the ground-breaking discovery of the quantum Hall effect, half-quantized quantum Hall
plateaus have been some of the most studied and sought-after states. Their importance stems
not only from the fact that they transcend the composite fermion framework used to explain
fractional quantum Hall states (such as Laughlin states). Crucially, they hold promise for hosting
non-Abelian excitations, which are essential for developing topological qubits — key components
for fault-tolerant quantum computing. In this work, we show that these coveted half-quantized
plateaus can appear in more than one unexpected way. We report the observation of fractional
states with conductance quantization at νH = 5/2 arising due to charge equilibration in the
confined region of a quantum point contact in monolayer graphene.