bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fully Automatic Deep Learning Model for Spine Refracture in Patients with OVCF: A Multi‐Center Study
Authors: Zhu Xuetao , Liu Dejian , Liu Lian , Guo Jingxuan , Li Zedi , Zhao Yixiang , Wu Tianhao , Liu Kaiwen , Liu Xinyu , Pan Xin , Qi Lei , Zhang Yuanqiang , Cheng Lei , Chen Bin 
Published: July 2024

BackgroundThe reaserch of artificial intelligence (AI) model for predicting spinal refracture is limited to bone mineral density, X‐ray and some conventional laboratory indicators, which has its own limitations. Besides, it lacks specific indicators related to osteoporosis and imaging factors that can better reflect bone quality, such as computed tomography (CT).ObjectiveTo construct a novel predicting model based on bone turn‐over markers and CT to identify patients who were more inclined to suffer spine refracture.MethodsCT images and clinical information of 383 patients (training set = 240 cases of osteoporotic vertebral compression fractures (OVCF), validation set = 63, test set = 80) were retrospectively collected from January 2015 to October 2022 at three medical centers. The U‐net model was adopted to automatically segment ROI. Three‐dimensional (3D) cropping of all spine regions was used to achieve the final ROI regions including 3D_Full and 3D_RoiOnly. We used the Densenet 121‐3D model to model the cropped region and simultaneously build a T‐NIPT prediction model. Diagnostics of deep learning models were assessed by constructing ROC curves. We generated calibration curves to assess the calibration performance. Additionally, decision curve analysis (DCA) was used to assess the clinical utility of the predictive models.ResultsThe performance of the test model is comparable to its performance on the training set (dice coefficients of 0.798, an mIOU of 0.755, an SA of 0.767, and an OS of 0.017). Univariable and multivariable analysis indicate that T_P1NT was an independent risk factor for refracture. The performance of predicting refractures in different ROI regions showed that 3D_Full model exhibits the highest calibration performance, with a Hosmer–Lemeshow goodness‐of‐fit (HL) test statistic exceeding 0.05. The analysis of the training and test sets showed that the 3D_Full model, which integrates clinical and deep learning results, demonstrated superior performance with significant improvement (p‐value < 0.05) compared to using clinical features independently or using only 3D_RoiOnly.ConclusionT_P1NT was an independent risk factor of refracture. Our 3D‐FULL model showed better performance in predicting high‐risk population of spine refracture than other models and junior doctors do. This model can be applicable to real‐world translation due to its automatic segmentation and detection.
Development and Validation of a Machine Learning Algorithm to Predict the Risk of Blood Transfusion after Total Hip Replacement in Patients with Femoral Neck Fractures: A Multicenter Retrospective Cohort Study
Authors: Zhu Jieyang , Xu Chenxi , Jiang Yi , Zhu Jinyu , Tu Mengyun , Yan Xiaobing , Shen Zeren , Lou Zhenqi 
Published: July 2024

ObjectiveTotal hip arthroplasty (THA) remains the primary treatment option for femoral neck fractures in elderly patients. This study aims to explore the risk factors associated with allogeneic blood transfusion after surgery and to develop a dynamic prediction model to predict post‐operative blood transfusion requirements. This will provide more accurate guidance for perioperative humoral management and rational allocation of medical resources.MethodsWe retrospectively analyzed data from 829 patients who underwent total hip arthroplasty for femoral neck fractures at three third‐class hospitals between January 2017 and August 2023. Patient data from one hospital were used for model development, whereas data from the other two hospitals were used for external validation. Logistic regression analysis was used to screen the characteristic subsets related to blood transfusion. Various machine learning algorithms, including logistic regression, SVA (support vector machine), K‐NN (k‐nearest neighbors), MLP (multilayer perceptron), naive Bayes, decision tree, random forest, and gradient boosting, were used to process the data and construct prediction models. A 10‐fold cross‐validation algorithm facilitated the comparison of the predictive performance of the models, resulting in the selection of the best‐performing model for the development of an open‐source computing program.ResultsBMI (body mass index), surgical duration, IBL (intraoperative blood loss), anticoagulant history, utilization rate of tranexamic acid, Pre‐Hb, and Pre‐ALB were included in the model as well as independent risk factors. The average area under curve (AUC) values for each model were as follows: logistic regression (0.98); SVA (0.91); k‐NN (0.87) MLP, (0.96); naive Bayes (0.97); decision tree (0.87); random forest (0.96); and gradient boosting (0.97). A web calculator based on the best model is available at: (https://nomo99.shinyapps.io/dynnomapp/).ConclusionUtilizing a computer algorithm, a prediction model with a high discrimination accuracy (AUC > 0.5) was developed. The logistic regression model demonstrated superior differentiation and reliability, thereby successfully passing external validation. The model's strong generalizability and applicability have significant implications for clinicians, aiding in the identification of patients at high risk for postoperative blood transfusion.
No End to Hypergamy when Considering the Full Married Population
Authors: Urbina Daniela R. , Frye Margaret , Lopus Sara 
Published: July 2024

AbstractThe worldwide expansion of female educational opportunities in recent decades has prompted demographers to assess the frequency with which women marry up (hypergamy) or down (hypogamy) with regard to education. A series of articles documented dramatic and nearly universal declines in hypergamy over time and across female educational advantage. However, this previous work investigated hypergamy only in the context of unequal educational pairings, excluding couples with equal levels of education (homogamy) from their analyses. Here, we argue that the prevalence of hypergamy should instead be assessed in relation to all marriages. We apply this approach to the case of Latin America, where women have made important gains in schooling relative to men. Using census microdata spanning 105 birth cohorts in 16 countries, we demonstrate that, rather than declining, hypergamy has increased in most countries over time and remains relatively stable across female educational advantage. Meanwhile, the prevalence of educational homogamy has declined considerably in most countries and across the axis of female educational advantage, an important trend that emerges only when homogamy is incorporated into the analysis.
Sedimentary dolomite in Western Australia and the dolomite problem: Genesis of channel and playa uranium deposits
Authors: Drummond Justin B. R. , Pufahl Peir K. , James Noel P. , Layton‐Matthews Daniel , Kyser T. Kurt 
Published: July 2024

ABSTRACTQuaternary to Recent sedimentary dolomite in groundwater calcrete and saltmarsh sediments of Lake Way and Lake Maitland, Western Australia, provide new information about the formation of low‐temperature dolomite. Dolomite can form through numerous pathways depending on the depositional and diagenetic environment. Many pathways involve microbial processes and/or the presence of a nucleation substrate which help overcome kinetic barriers preventing precipitation in the laboratory. Petrographic, mineralogical, hydrogeochemical and stable isotopic data in this study reveal the importance of Mg‐clays as nucleation sites for dolomite precipitation in a range of aquifer environments. There is also a close association between authigenic Mg‐clays, dolomite and the potassium–uranyl–vanadate ore mineral carnotite in channel and playa uranium deposits. It is interpreted that evaporation‐driven precipitation of dolomite establishes a positive feedback loop promoting the dissociation of aqueous uranyl–carbonate complexes and concomitant increase in carnotite saturation. Critical to this model is the presence of authigenic Mg‐clays because they facilitate dolomite precipitation and promote carnotite nucleation by concentrating potassium ions on clay surfaces via adsorption. This Mg‐clay–dolomite–carnotite relationship is widespread throughout Western Australian channel and playa uranium deposits and has been observed in similar deposits in Namibia and Botswana. In addition to this economic implication, Mg‐clay mediated nucleation of dolomite potentially has global relevance as a precipitation mechanism for low temperature dolomite in sedimentary deposits where detrital and/or authigenic Mg‐clays are present. Maturation of sedimentary dolomite from disordered high‐calcian dolomite to ordered low‐calcian dolomite occurs very early in the meteoric realm making it resistant to alteration during burial diagenesis. Diagenetic resistance may be further increased by early meteoric silicification related to the degradation of associated Mg‐clays. These findings indicate that Mg‐clay associated sedimentary dolomite has potential to retain a primary isotopic signature indicative of its origin, making it a useful recorder of palaeoenvironmental conditions.
Measuring and reducing implicit prejudice against Black women and people with intersectional identities
Authors: Phills Curtis E. 
Published: July 2024

AbstractThis paper addresses a critical gap in measuring and reducing implicit prejudice: biases against Black women and people with intersectional identities. Though social psychologists have published many methods to measure and interventions to reduce implicit prejudice against Black people, these methods often target biases against Black people or Black men rather than Black women. Thus, these methods may leave Black women out because the mental representations of Black women and Black men differ and the mental representation of Black people is more similar to the mental representation of Black men than Black women. This paper advocates for an intersectional approach to measuring and reducing implicit prejudice that accounts for the unique prejudices faced by Black women. Specifically, this paper argues that researchers should tailor their methods to account for how the mental representations of Black women and Black men differ including differences in stereotypic content and ambivalence. The paper concludes by acknowledging the difficulties related to developing long‐lasting interventions, the need to move beyond reducing implicit prejudice, and the value of studying the men and women of additional racial and ethnic groups and other intersections like sexual orientation and socioeconomic status.
Hidden diversity of Aegla (Decapoda, Anomura) in a priority area for conservation
Authors: Mollmann Victor H. S. , Bartholomei‐Santos Marlise L. , Fernandes Gracieli , Puli Gislaine , Mossolin Emerson C. , Dalosto Marcelo M. , Santos Sandro 
Published: July 2024

AbstractAegla is a genus of freshwater anomuran crabs encompassing 94 described species occurring in meridional South America. Brazil harbours the greatest diversity of species, mainly in its southern region, which becomes a priority area for Aegla conservation due to high species richness and phylogenetic diversity, elevated endemism and threats to the Atlantic Forest. Here, we assessed Aegla richness and distribution in this priority area and tested the hypothesis of crypticism in the region's species. Sampling sites were distributed inside and in the surroundings of five protected areas, covering the major distribution range of several species described for southern Brazil. We applied three species delimitation methods to COI mitochondrial gene data, coupled with phylogenetic and morphological analyses. By integrating species delimitation based on the COI data and traditional taxonomy, we uncovered a high proportion of hidden diversity among Aegla in our study area and identified ten known species besides impressive 17 new putative species. Of these, eight are possible new taxonomic units that do not conform to any known species, and nine are divided into three cryptic groups: Aegla jarai complex, Aegla franciscana complex and Aegla camargoi complex. Most of these species have a narrow spatial distribution, making them highly vulnerable to habitat degradation. Despite the real richness of the genus still being largely unknown, the high diversity revealed here makes our study area the richest known region regarding the number of Aegla species within its distribution, making this area even more worthy for conservation efforts.
On torsion‐freeness of Kähler differential sheaves
Authors: Das Nilkantha , Roy Sumit 
Published: July 2024

AbstractLet be a normal algebraic variety over an algebraically closed field . We prove that the Kähler differential sheaf of is torsion‐free if and only if any regular section of the ideal sheaf of the first order deformation of inside , defined outside the singular locus of , extends regularly to the singular locus.
Bayesian Model Updating of Multiscale Simulations Informing Corrosion Prognostics Using Conditional Invertible Neural Networks
Authors: Qian Guofeng , Zeng Jice , Hu Zhen , Todd Michael D. 
Published: July 2024

Abstract
Physics-based multiscale corrosion simulation plays a vital role in predicting the evolution of pitting corrosion on large civil infrastructure, contributing to a model-informed structural health monitoring strategy for risk-based asset health management. The physics-based analysis, however, may not accurately reflect the underlying true physics due to various uncertainty sources and needs to be updated using Bayesian inference methods based on observations to make the prediction closer to field observations. However, traditional Bayesian inference requires the evaluation of a likelihood function, which is often unavailable due to the complex model architecture and various surrogate models used in the analysis. Therefore, likelihood-free inference approaches are required for the updating of the multiscale corrosion simulation models. This paper meets this need by proposing a conditional invertible neural network (cINN)-based Bayesian model updating method for an existing corrosion simulation model. We first train a cINN model based on simulated observations generated from a high-fidelity forward corrosion analysis model. A convolutional neural network-based feature extraction algorithm is then employed to extract key features from corrosion images. After that, the extracted corrosion features are used as inputs of the cINN model to directly obtain posterior distributions of uncertain corrosion model parameters without evaluating the likelihood function. A case study of a miter gate structure is used to demonstrate the proposed approach. The results show that the proposed cINN-based model updating approach can provide more accurate inference results with a reduced computational cost in comparison to the classical approximate Bayesian computation (ABC) approach.
Exploring the Impact of HFO-1234YF Refrigerant on the Tribological Properties of Advanced Polymeric Coatings
Authors: Raut Ajinkya , Amiri Ahmad , Polycarpou Andreas A. 
Published: July 2024

Abstract
The global focus has shifted toward mitigating the impact of global warming, particularly in the air-conditioning and refrigeration sectors, where there is a strong emphasis on the use of environmentally friendly refrigerants. One such refrigerant that has gained increased usage is HFO-1234yf. The increasing use of HFO-1234yf as a refrigerant in automobile air-conditioning compressors presents new challenges in terms of material compatibility. In this research, we investigate the impact of HFO-1234yf in automobile compressor applications by comparing the tribological results of the same materials in air. We conducted tribological experiments under starved lubrication conditions using polyetheretherketone (PEEK)/polytetrafluoroethylene (PTFE) and aromatic thermosetting co-polyesters (ATSP)/PTFE-coated aluminum alloy samples. We found that the ATSP/PTFE coatings perform exceptionally well irrespective of the atmosphere, while the presence of HFO-1234yf refrigerant adversely affects the tribological performance of the PEEK/PTFE coatings, citing the lack of a stable tribofilm formation. These findings offer valuable insights for the development of materials and lubricants that are compatible with HFO-1234yf refrigerant applications.
Robust Visual SLAM in Dynamic Environment Based on Motion Detection and Segmentation
Authors: Yu Xin , Shen Rulin , Wu Kang , Lin Zhi 
Published: July 2024

Abstract
In this study, we propose a robust and accurate simultaneous localization and mapping (SLAM) method for dynamic environments. Our approach combines sparse optical flow with epipolar geometric constraints to detect motion, determining whether a priori dynamic objects are moving. By integrating semantic segmentation with this motion detection, we can effectively remove dynamic keypoints, eliminating the influence of dynamic objects. This dynamic object removal technique is integrated into ORB-SLAM2, enhancing its robustness and accuracy for localization and mapping. Experimental results on the TUM dataset demonstrate that our proposed system significantly reduces pose estimation error compared to ORB-SLAM2. Specifically, the RMSE and standard deviation (S.D.) of ORB-SLAM2 are reduced by up to 97.78% and 97.91%, respectively, in highly dynamic sequences, markedly improving robustness in dynamic environments. Furthermore, compared to other similar SLAM methods, our method reduces RMSE and S.D. by up to 69.26% and 73.03%, respectively. Dense semantic maps generated by our method also closely align with the ground truth.
Epidemiology of
Clostridioides difficile
infection at one hospital 10 years after an outbreak of the epidemic
C. difficile
strain BI/027: changing strain prevalence, antimicrobial susceptibilities, and patient antibiotic exposures
Authors: Wieczorkiewicz Jeffrey T. , Skinner Andrew M. , Cheknis Adam , Petrella Laurica A. , Stevens Vanessa W. , Wright Lorinda M. , Gerding Dale N. , Johnson Stuart 
Published: July 2024

ABSTRACT

In contrast to the epidemiology 10 years earlier at our hospital when the epidemic restriction endonuclease analysis (REA) group strain BI accounted for 72% of
Clostridioides difficile
isolates recovered from first-episode
C. difficile
infection (CDI) cases, BI represented 19% of first-episode CDI isolates in 2013–2015. Two additional REA group strains accounted for 31% of isolates (Y, 16%; DH, 12%). High-level resistance to fluoroquinolones and azithromycin was more common among BI isolates than among DH, Y, and non-BI/DH/Y isolates. Multivariable analysis revealed that BI cases were 2.47 times more likely to be associated with fluoroquinolone exposure compared to non-BI cases (95% confidence interval [CI]: 1.12–5.46). In addition, the odds of developing a CDI after third- or fourth-generation cephalosporin exposure was 2.83 times for DH cases than for non-DH cases (95% CI: 1.06–7.54). Fluoroquinolone use in the hospital decreased from 2005 to 2015 from a peak of 113 to a low of 56 antimicrobial days/1,000 patient days. In contrast, cephalosporin use increased from 42 to 81 antimicrobial days/1,000 patient days. These changes correlated with a decrease in geometric mean MIC for ciprofloxacin (61.03 to 42.65 mg/L,
P
= 0.02) and an increase in geometric mean MIC for ceftriaxone (40.87 to 86.14 mg/L,
P
< 0.01) among BI isolates. The BI strain remained resistant to fluoroquinolones, but an overall decrease in fluoroquinolone use and increase in cephalosporin use were associated with a decrease in the prevalence of BI, an increased diversity of
C. difficile
strain types, and the emergence of strains DH and Y.
Six adenoviral vectored African swine fever virus genes protect against fatal disease caused by genotype I challenge
Authors: Portugal Raquel , Goldswain Hannah , Moore Rebecca , Tully Matthew , Harris Katie , Corla Amanda , Flannery John , Dixon Linda K. , Netherton Christopher L. 
Published: July 2024

ABSTRACT

African swine fever virus causes a lethal hemorrhagic disease in domestic swine and wild boar for which currently licensed commercial vaccines are only available in Vietnam. Development of subunit vaccines is complicated by the lack of information on protective antigens as well as suitable delivery systems. Our previous work showed that a pool of eight African swine fever virus genes vectored using an adenovirus prime and modified vaccinia virus boost could prevent fatal disease after challenge with a virulent genotype I isolate of the virus. Here, we identify antigens within this pool of eight that are essential for the observed protection and demonstrate that adenovirus-prime followed by adenovirus-boost can also induce protective immune responses against genotype I African swine fever virus. Immunization with a pool of adenoviruses expressing individual African swine fever virus genes partially tailored to genotype II virus did not protect against challenge with genotype II Georgia 2007/1 strain, suggesting that different antigens may be required to induce cross-protection for genetically distinct viruses.

IMPORTANCE
African swine fever virus causes a lethal hemorrhagic disease in domestic pigs and has killed millions of animals across Europe and Asia since 2007. Development of safe and effective subunit vaccines against African swine fever has been problematic due to the complexity of the virus and a poor understanding of protective immunity. In a previous study, we demonstrated that a complex combination of eight different virus genes delivered using two different viral vector vaccine platforms protected domestic pigs from fatal disease. In this study, we show that three of the eight genes are required for protection and that one viral vector is sufficient, significantly reducing the complexity of the vaccine. Unfortunately, this combination did not protect against the current outbreak strain of African swine fever virus, suggesting that more work to identify immunogenic and protective viral proteins is required to develop a truly effective African swine fever vaccine.