bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on static error identification of three-axis machine tool based on multi-flexible system theory
Authors: Jiang Xiaogeng , Wang Yan , Wang Hao 
Published: December 2024

Abstract

In order to comprehensively consider the influence of geometric error caused by manufacturing defects and elastic error caused by the gravity of structural components on the static accuracy of machine tools, as well as the coupling relationship between them, this paper proposes an identification method of static error of three-axis machine tools. Taking the three-axis machine tool as the research object, the static error model of the machine tool is established according to the multi-flexible system theory and the homogeneous transformation matrix (HTM), and the geometric error component and the elastic error component in the static error are qualitatively analyzed. The Chebyshev polynomials are used to establish the parametric model of static error. Based on the three-axis linkage experiment of the Double ball bar (DBB), all the static errors are decoupled. Then, the finite element method is used to discretize the machine tool into three subsystems. Based on the spatial beam element, the stiffness model of each subsystem is established, and the elastic error component in the static error is quantitatively analyzed. The results show that the elastic error affected by gravity is mainly reflected in seven straightness errors and angle errors, and is generally greater than the corresponding static error. It shows that the machine tool offsets the influence of geometric errors from the perspective of elastomer compensation in the design stage, and proposes a simplified static error model of the machine tool.
The Influence of Regulatory Framework and Environmental Factors on Accounting Practices by Companies in Ghana
Authors: AMPEDU Raphael , AGYEI Bright ANTWI , Frank Peter Mang'ati , BOAKYE-BOATENG Gifty , MENSAH NII CORNELIUS ODOI , MENSAH RICHMOND , OFEIBEA Linda Nunoo , BOADI Joana ANKOBEA 
Published: December 2024

Abstract

This paper explores the influence of regulatory frameworks and environmental factors on the accounting practices of companies in Ghana. It emphasizes the critical role of a robust regulatory environment, maintained by bodies such as the Institute of Chartered Accountants, Ghana (ICAG), and the Securities and Exchange Commission (SEC), in ensuring transparency and consistency in financial reporting. The adoption of International Financial Reporting Standards (IFRS) has been pivotal in aligning Ghanaian accounting practices with global standards, although challenges remain in terms of implementation and compliance. Additionally, environmental factors such as economic conditions, technological advancements, sociocultural influences, and political stability significantly impact accounting practices. Economic stability encourages rigorous accounting standards, while technological advancements enhance the accuracy and efficiency of financial reporting. Sociocultural factors, including the education and professional development of accountants, and ethical standards, shape the quality of accounting practices. Political stability and effective legal systems are essential for enforcing accounting standards. This study provides valuable insights for regulators, policymakers, and practitioners, highlighting the need for continuous improvement in the regulatory framework and addressing environmental challenges to enhance the quality and reliability of financial reporting in Ghana.
Investigation of the Likelihood of Accessing Mental Health Treatment Between Immigrant and Nonimmigrant Adult Residents of the United States
Authors: Ejubovic Nihad , Alexander Jeffrey 
Published: December 2024

Abstract

Background
In the United States, immigrants are at higher risk of experiencing mental health problems and are less likely to seek professional treatment than nonimmigrants.
Objective
To investigate the likelihood of immigrant and nonimmigrant adult residents of the United States to access professional mental health treatment.
Methods
We used a quantitative, survey study design to evaluate the attitudes, perceptions, and likelihood of US adults seeking mental health treatment. Participants were recruited through social media platforms and completed an anonymous 15-question online survey (11 multiple-choice and 4 open-ended questions).
Results
Overall, 1053 adults completed the survey: 742 (70%) immigrants and 308 (29%) nonimmigrants. Most immigrants (689, 93%) and over half (188, 61%) of nonimmigrants reported experiencing mental health problems in the past 12 months. More immigrants (612/738, 82%) than nonimmigrants (219/298, 74%) were very likely or somewhat likely to seek professional mental health treatment (χ2 = 42.9, P < .001). There was also a small association between immigrant status and likelihood of seeking professional mental health treatment (φ = 0.20, P < .001).
Conclusions
Our findings suggested immigrants had more mental health problems than nonimmigrants and were more likely to seek mental health treatment. Future studies should investigate the impact immigration has on mental health perceptions, such as an individual’s age at immigration, and the likelihood of seeking mental health treatment.
Sperm DNA damage and disturbed chromatin condensation indexes (DFI and CMA3) in normozoospermic men with unexplained infertility problem
Authors: Abedinzadeh Mehdi , Abedinzadeh Sara , Sadeghi-Nodoushan Fatemeh , pourrajab Fatemeh 
Published: December 2024

Abstract

Purpose The quantitatively measured sperm DNA damage and disturbed chromatin condensation indexes (% DNA fragmentation index [DFI] and % high DNA staining index [HDS]) and their relationships with sperm quality in normospermic men with unexplained infertility were investigated. Methods In this retrospective study, conventional semen tests, including sperm motility and morphological evaluations and DNA fragmentation and disturbed chromatin condensation indexes (DFI, CMA3) were performed according to the World Health Organization 2021 criteria. DFI and CMA3 were evaluated using sperm chromatin dispersion (SCD) and chromomycin A3 (CMA3) staining assays and then correlation and regression analysis were done. Results By analyzing SCD and CMA3 results, notable differences were found in sperm parameters among different DFI and CMA3 groups (all P < 0.05). It was found that in the male fertility quality: sperm concentration, progressive/non-progressive motility, immobility, and morphology were significantly associated with sperm DFI and CMA3, but not with age (P < 0.05). Conclusions Sperm molecular index DFI and CMA3 negatively affect male fertility quality through semen parameters (sperm concentration, motility, and morphology).
Properties and Stability of Persistence Matching Diagrams
Authors: Gonzalez-Diaz Rocio , Torras-Casas Álvaro 
Published: December 2024

Abstract

We introduce persistence matching diagrams induced by set mappings of metric spaces, based on 0-persistent homology of Vietoris-Rips filtrations. Also, we present a geometric definition of the persistence matching diagram that is more intuitive than the algebraic one.In addition, we show that such matching diagrams encapsulate the information of persistence morphism images, kernels and cokernels induced by embeddings.The main result is a stability theorem for persistence matching diagrams induced by embeddings.At the end, we adapt our stability result for set injections (not embeddings) of finite metric spaces.
MSC Classification: 55N31
Modality-Aware Adaptive-Integration Guided Single-Stream Network for RGB-T Saliency Detection
Authors: Pang Yu , Zhang Longkun , Huang Yang , Yu Xiaosheng 
Published: December 2024

Abstract

RGB-T saliency detection becomes gradually a hot topic in saliency detection field recently. However, existing works (especially CNN based methods) usually use the two-stream structure to separately extract saliency cues from RGB and thermal infrared images, and then integrate them into the final detection result, this strategy greatly increases parameters scale while multi-modal fusion results are also very sensitive to two modalities’ quality. Based on above observation, we develop a novel Modality-Aware Adaptive-Integration Guided Single-Stream Network(MAANet), to detect salient objects from RGB-T image pairs. The feature pyramid network(FPN) is adopted as the basic structure of our MAANet. In order to tactfully fuse two supplementary modalities: (1)In the encoder: RGB and thermal infrared images are concatenated into 4-channel input of encoder structure in the proposed MAANet. (2)In the decoder: We propose a novel Modality-Aware Adaptive-Integration based Attention mechanism (MAAM) to enable the decoder to optimally perform the fusion of two modalities, and produce more accurate saliency predictions. (3)Finally: A novel coarse-and-refined bidirectional optimization(CRBO) method is proposed to suppress irrelevant background regions of saliency map generated by decoder structure. The proposed MAANet could better take both advantages of two modalities and is not sensitive to any one modality compared to previous RGB-T methods, meanwhile, MAANet is also more lightweight than previous works.Extensive experiments demonstrate that the proposed model performs favorably against most state-of-the-art RGB-T methods under different evaluation metrics, even outperforms than most RGB and RGB-D methods.
Optimizing Performance, Combustion and Emission characteristics of Mahua Biodiesel included GO and ZnO Nanoparticles: An ANN-RSM Approach
Authors: pala srinivasa reddy , Mohan Mangu Venkata Krishna , Vanthala Varaha siva Prasad 
Published: December 2024

Abstract

The present study focuses on the use of artificial neural networks (ANNs) and response surface methodology (RSM) with GO and ZnO nanoparticles placed in Mahua oil biodiesel blend (B20) are utilized to fuel direct injection diesel engines. These approaches are used to forecast the engine's operating characteristics. At a concentration of 75 ppm, GO and ZnO nanoparticles were taken into consideration. Additionally, a dispersant (TWEEN 80) and surfactant (CTAB) were mixed respectively at a ratio of 1:1. Using a spectrophotometer, stability analysis was carried out on a variety of nanofuel samples, and a study based on experiments was done on a diesel engine. The output factors that were examined at were BSFC, BTE, NHRR, CP, UHC, CO, NOx, and smoke visibility. These metrics were based on combustion, emissions and performance. Input parameters such as gasoline samples, injection pressure, and engine load were considered. The injection pressures were 200, 225, and 250 bars, whereas the loads were considered to be 5%, 50%, 75%, and 100%, respectively. When compared to other samples, the dispersion ZnO and GO nanoparticles in B20 shown amazing performance. The B20 + GO 75 ppm + TWEEN 80 75 ppm combination has shown a 5.293% decrease in BSFC and a 5.067% improvement in BTE at 250 bars. Furthermore, 3.13% and 43.50% improvements were made to combustion parameters including CP and NHRR, respectively. Smoke opacity, CO, UHC, and NOx were all reduced by around 38.55%, 11.07%, 37.63%, and 27.77%, respectively. Finally, the correlation coefficient (R2) for all parameters ranged from 0.93 to 0.99 using ANNs and RSM predictions.
Genetic variability correlation by biochemical seed compounds of a natural population ofAcrocomia aculeata (Jacq.) Lodd. ex Mart. (Arecaceae)
Authors: Alcantara Marcelo Augusto Mendes , Silvestre Marcela Aparecida Moraes , Rossini Bruno César , Friia Ana Carolina Souza , Batista Alef Carvalho , Moraes Mario Luiz Teixeira , Freitas Miguel Luiz Menezes 
Published: December 2024

Abstract

Acrocomia aculeata is a species widely found in the Brazilian Cerrado, with significant economic and environmental potential. It is used for biofuels, construction, human and animal nutrition, and recovery of degraded areas. Evaluating the genetic variability of natural populations is crucial for characterizing A. aculeata seeds through the selection and correlation of their chemical compounds, such as starch, carbohydrates, lipids, micronutrients (N, P, K, Ca, Mg, and S), and reserve proteins. Seeds were collected from 30 open-pollinated matrix trees in a degraded area of the former “Engenheiro Sergio Motta” Hydroelectric Power Plant construction site in Rosana, São Paulo, Brazil. Statistical analyses, based on a randomized block design with 30 progenies and four replications, examined 13 characteristics by mean, variance, and standard deviation. Genetic correlations, divergence by the Generalized Mahalanobis Distance (D²), grouping by the Tocher Optimization Method, and the Mulamba & Mock index were estimated, revealing five distinct groups of individuals (84% in the first group, 7% in the second, and 3% in each of the three subsequent groups). The Mulamba & Mock index indicated satisfactory results for selection aimed at increasing biochemical compounds, highlighting the genetic variability of the population and potential sources for future breeding and conservation programs.
Incidence, Predictors, and Outcomes of Sepsis in Revision Total Hip Arthroplasty (rTHA)
Authors: Bulut Halil , Tomey Daniel 
Published: December 2024

Abstract

Introduction:
Revision total hip arthroplasty (rTHA) is increasingly common, with sepsis being a serious but rare complication. Sepsis rates in rTHA vary widely, and understanding risk factors is crucial for improving outcomes. This study aims to evaluate the incidence of sepsis following rTHA and identify preoperative and intraoperative predictors.
Methods:
A retrospective observational study using the ACS NSQIP database analyzed 12,966 rTHA patients (2016–2021). Predictors of sepsis were identified through univariate and multivariate analysis, including demographic, comorbid, and surgical factors. The primary endpoint was identifying sepsis predictors; secondary endpoints included sepsis incidence across patient groups.
Results:
In a cohort of 12,966 patients undergoing revision total hip arthroplasty, the incidence of sepsis was 1.9% (251 patients). Preoperative factors associated with increased sepsis risk included diabetes (2.6%), smoking (2.9%), dyspnea (3.7%), severe COPD (3.5%), dialysis (5.3%), open wounds (9.5%), steroid use (3.1%), partial/total dependence (3.5%), and ASA III-IV status (2.7%). Multivariate analysis identified several predictors of sepsis, including age (OR + 0.02 per year), total operation time (OR -0.004 per minute), open wounds (OR 3.6), severe COPD (OR 1.9), transfusion within 72 hours (OR 3.3), dyspnea (OR 8.1), and emergent cases (OR 3.4). The sepsis group had higher adverse outcomes, including a 30-day mortality rate of 0.8% (vs. 0.22% in non-septic patients), higher rates of deep vein thrombosis (2.8% vs. 0.7%), pulmonary embolism (1.6% vs. 0.5%), stroke (0.8% vs. 0.2%), and acute renal failure (1.2% vs. 0.1%), all with significant p-values and higher odds ratios.
Conclusion:
Sepsis after rTHA is a significant complication. Predictors include age, open wounds, COPD, dyspnea, and transfusions. Identifying at-risk patients can improve prevention and management strategies to enhance patient outcomes.
Phenotypic Changes in Chamaecyparis hodginsii Seedlings Induced by New Environments and Mediated by Gene Expression
Authors: Zhu Peng-Kai , Xu Yan-Ping , Rong Jun-Dong , Liu Kai , He Tian-You , Chen Li-Guang , Zheng Yu-Shan , Chen Ling-Yan 
Published: December 2024

Abstract

In the context of climate change, assessing the adaptive potential of species and populations is crucial for developing effective conservation strategies. Changes in plant gene expression play a significant role in the adaptation process to climate change. This study aims to explore the adaptive responses of the near-threatened conifer species Chamaecyparis hodginsii to climate change and analyze the molecular-level reactions of these long-lived trees to climatic shifts. It seeks to understand their phenotypic responses to climate change, identify key environmental factors driving adaptive gene expression, and provide information for transplantation conservation strategies based on genetic adaptability. By conducting mixed-tissue RNA sequencing on seeds from multiple provenances and employing redundancy analysis (RDA), weighted gene co-expression network analysis (WGCNA), and partial least squares path modeling (PLS-PM), the study assesses the impact of climatic variables on gene expression and phenotype. It identifies key gene groups associated with environmental responses and elucidates the complex relationships between environmental factors, functional gene groups, and phenotypic traits. The findings reveal that C. hodginsii adapts to environmental stresses by regulating specific gene activities related to morphological trait adjustments. Moreover, environmental factors such as the impact on tree architecture emphasize the importance of Precipitation Seasonality, Isothermality, and Precipitation of Driest Quarter for adapting to climate stresses. This research not only unveils the complex adaptive responses of C. hodginsii to climate change but also provides critical insights for the management and conservation of long-lived tree species facing climate change threats.
Synergistic Response of Phycosphere Bacteria with Microalga Phaeodactylum tricornutum under the 2,6-Di-tert-butyl-p-cresol Stress
Authors: Lu Xiao , Liu Jie , Xiao Xinfeng , Xue Jianliang , Cheng Dongle , Zhang Linlin 
Published: December 2024

Abstract

The emerging contaminant 2, 6-di-tert-butyl-p-cresol (BHT) is a kind of synthetic phenolic antioxidant and can pose negative effects on the microalgal cells. Enriching specific bacteria from the phycosphere environment was an important adaptive strategy for algae cells when they are under the adverse stress. However, the mechanism of phycosphere bacteria coordinating with microalgae in response to BHT stress remains poorly understood. Herein, the effect of BHT on the microalgae Phaeodactylum tricornutum was comprehensively analyzed. Results showed that the growth and photosynthetic pigment biosynthesis of P. tricornutum was inhibited with the increase of BHT concentration. BHT also led to an increase in the content of malondialdehyde, therefore microalgae responded to the oxidative stress by enhancing activities of antioxidant enzymes, including superoxide dismutase, catalase and peroxidase, to eliminate excess reactive oxygen species in the cells. Furthermore, transcriptome analysis revealed that up-regulation of genes related to photosynthesis, TCA cycle, oxidative phosphorylation and indole-3-acetic acid (IAA) in response to BHT stress. In addition, high-throughput Illumina MiSeq sequencing results demonstrated a significant increase in the relative abundance of bacteria affiliated with Halomonas, Marivita and Oceanicaulis. Microbiological assays demonstrated that Halomonas can thrive by using BHT as the sole energy source and exhibit a chemotactic response to IAA. Therefore, we conclude that the content increase of IAA secreted by microalgae in the phycosphere environment promoted the enrichment of BHT-tolerant bacterium Halomonas, thereby it is helpful for environmental pressures adaptability of P. tricornutum. Overall, this study provided a comprehensive understanding of the physiological and biochemical effects of BHT on microalgae, and we highlight the potential functional significance of IAA in establishing an interaction between microalgae and algae-associated bacteria in adverse environments.
SemiHMER: Semi-supervised HandwrittenMathematical Expression Recognition using pseudo-labels
Authors: Chen Kehua , Shen Haoyang 
Published: December 2024

Abstract

In recent years, deep learning with Convolutional Neural Networks (CNNs) has achieved remarkable results in Handwritten Mathematical Expression Recognition(HMER). However, improving the performance with limited labeled training data remains challenging. This paper presents, for the first time, a simple yet effective semi-supervised HMER framework by introducing dual-branch semi-supervised learning. Specifically, we simplify the conventional deep co-training from consistency regularization to cross-supervised learning, where the prediction of one branch is used as a pseudo-label to supervise the other branch directly end-to-end. Considering that the learning of the two branches tends to converge in the later stages of model optimization, we also incorporate a weak-to-strong strategy by applying different levels of augmentation to each branch, which expands the training data and improves the quality of network training. Meanwhile, We propose a novel module, called Global Dynamic Counting Module(GDCM), to enhance the performance of the HMER decoder, which alleviates recognition inaccuracies in long-distance formula recognition and the occurrence of repeated characters. We will release our code at https://github.com/chenkehua/SemiHMER.
Dynamical analysis of soliton wave solutions of $(2+1)$-Dimensional Kadomtsev-Petviashvili (KP) Equation through two efficient analytical techniques
Authors: Kumar Dharmendra , Saharan Ashwani , Kumar Praveen 
Published: December 2024

Abstract

In this paper, we consider generalized Kadomtsev-Petviashvili (KP) equation and presents new closed-form solutions through an analytical technique and Lie symmetry analysis. The KP equation, a key tool in modeling long waves and frequency dispersion, is relevant in various nonlinear physical systems. New soliton solutions—including single, multi, elastic, kink, bright, and dark types—are derived using the (2+1)-dimensional KP equation. The approach employs both a novel analytical method and Lie symmetry transformations to generate invariant solutions, reducing the governing equation to various ordinary differential equations (ODEs). These solutions are analyzed for dynamic behavior with detailed 2-D, 3-D, contour, and density plots created via Mathematica, providing insights into complex phenomena in fields like geophysics, optics, and atmospheric sciences.
Examining the Efficacy of a Virtual Group Program for Survivors of Complex Trauma: A Mixed-Methods Explanatory Study
Authors: Kinley Jackie , Reyno Sandra 
Published: December 2024

Abstract

This study examined the efficacy of a virtual, group-based treatment for individuals with histories of complex trauma and persistent mental illness. Participants reported significant positive changes in psychological symptoms, emotion regulation, beliefs about self and others, resilience, and dimensional Complex Post-Traumatic Stress Disorder symptoms at post-treatment. These gains were maintained at follow-up. Deductive, reflexive thematic analysis was employed to better understand the program’s impact on ‘disturbances in self-organization’, with positive changes attributed to enhanced 1) processing, managing, and resolving painful emotions, 2) self-acceptance, self-investment, and motivation for change and 3) empathy, assertiveness, and boundary setting. Our virtual program may present an effective treatment with significant implications for enhancing service capacity for individuals struggling with the chronic and pervasive residual impacts of complex trauma.