bluuebunny/crossref_metadata_2025 huggingface dataset:
An overlooked poultry trade network of the smallholder farms in the border provinces of Thailand, 2021: implications for avian influenza surveillance
Authors: Hinjoy Soawapak , Thumrin Pornchai , Sridet Jitphanu , Chaiyaso Chat , Suddee Weerachai , Thukngamdee Yupawat , Yasopa Oiythip , Prasarnphanich Ong-orn , Na Nan Somruethai , Smithsuwan Punnarai , Rodchangphuen Janjao , Sulpizio Carlie L. , Wiratsudakul Anuwat
Published: February 2024

Introduction

In Thailand, community-level poultry trade is conducted on a small-scale involving farmers and traders with many trade networks. Understanding the poultry movements may help identify different activities that farmers and traders might contribute to the spread of avian influenza.

Methods

This study aimed to describe the characteristics of players involved in the poultry trade network at the northeastern border of Thailand using network analysis approaches. Mukdahan and Nakhon Phanom provinces, which border Laos, and Ubon Ratchathani province, which borders both Laos and Cambodia, were selected as survey sites.

Results

Local veterinary officers identified and interviewed 338 poultry farmers and eight poultry traders in 2021. A weighted directed network identified incoming and outgoing movements of where the subdistricts traded chickens. Ninety-nine subdistricts and 181 trade links were captured. A self-looping (trader and consumer in the same subdistrict) feedback was found in 56 of 99 subdistricts. The median distance of the movements was 14.02 km (interquartile range (IQR): 6.04–102.74 km), with a maximum of 823.08 km. Most subdistricts in the network had few poultry trade connections, with a median of 1. They typically connected to 1–5 other subdistricts, most often receiving poultry from 1 to 2.5 subdistricts, and sending to 1–2 subdistricts. The subdistricts with the highest overall and in-degree centrality were located in Mukdahan province, whereas one with the highest out-degree centrality was found in Nakhon Phanom province.

Discussion

The poultry movement pattern observed in this network helps explain how avian influenza could spread over the networks once introduced.
Fecal PCR survey and genome analysis of Lawsonia intracellularis in China
Authors: Wang Lei , Wu Wenqing , Zhao Lifeng , Zhu Zhanwei , Yao Xinzhi , Fan Jie , Chen Hongjian , Song Wenbo , Huang Xi , Hua Lin , Qian Ping , Chen Huanchun , Peng Zhong , Wu Bin
Published: February 2024

Proliferative enteropathy caused by Lawsonia intracellularis is an important economic associated disease to pig industry, but the knowledge about the prevalence of L. intracellularis in pig farms in China is limited. In addition, there is no complete genome sequence available for L. intracellularis isolates from China. In this study, we developed a TaqMan qPCR for the screening of L. intracellularis by targeting the bacterial 16S rDNA gene. Laboratory evaluations revealed a good sensitivity and specificity on detecting L. intracellularis nucleic acid. Using this method, we investigated 891 fecal samples from apparently healthy pigs in 47 farms. The results demonstrated a screening positive rate of 37.3% (95% CI, 34.1–40.5%) for the samples, and a farm screening positive rate of 93.6% (95% CI, 65.3–94.4%). The screening positive rate at herd level ranged from 6.67% (95% CI, 0.2–31.9%) to 40% (95% CI, 38–79.6%), while at animal level, the highest screening positive rate was found in 12-week-old pigs [85.7% (95% CI, 67.3–96.0%)]. Investigation of 705 diarrheal or bloody feces from symptomatic pigs revealed that the highest positive rate was found in replacement gilts which was 37.18% (95% CI, 45.1–89.5%). Secondly, we conducted the complete genome sequence of a L. intracellularis PPE-GX01-2022 from China through PacBio sequencing. The genome of PPE-GX01-2022 consisted of a chromosome of 1,439,110 bp in length and three plasmids of 193,063, 39,799, and 27,067 bp, respectively. This genome encoded 1,428 predicted proteins, 44 tRNAs, and 6 rRNAs. Sequence comparisons demonstrated that the genome sequence of PPE-GX01-2022 was highly homologous to those of two isolates from US, and these three isolates shared 1,378 core genes. The screening results suggest a high prevalence rate of L. intracellularis in Chinese pig farms. In addition, the genome sequence of the Chinese isolate was highly homologous to those of the field isolates from the US.
Owner expectations and surprises of dog ownership experiences in the United Kingdom
Authors: Anderson Katharine L. , Holland Katrina E. , Casey Rachel A. , Cooper Ben , Christley Robert M.
Published: February 2024

Introduction

Although many owners are satisfied by dog ownership, large numbers of dogs are relinquished annually, with an estimated 130,000 dogs cared for each year by rescue organisations in the UK. Unrealistic ownership expectations are a potential factor in the decision to relinquish and therefore understanding what surprises owners about the realities of ownership and how this meets their expectations is vital.

Methods

Using a retrospective cross-sectional cohort study design, as part of Dogs Trust’s National Dog Survey 2021, owners were asked ‘what has surprised you most about owning a dog?’ and to classify how their experiences had compared with their expectations on a list of aspects of ownership as either more than, less than or as expected. Free text responses (n= 2,000) were analysed using reflexive thematic analysis in NVivo Pro (v.12 QSR) and a quantitative summary of classified expectations (n=354,224) was conducted in R.

Results

Many aspects of ownership were reported to be as expected, however a discrepancy between expectation and reality regarding some aspects was revealed. The cost of vet visits was greater than expected for the majority of respondents (52%), whilst other factors that often exceeded expectations included buying/rehoming cost (33%) and amount of patience needed (25%). Damage to furniture was less than expected for many (50%) as was damage to garden (33%). From the thematic analysis, four themes were generated that reflected what surprised owners most about ownership: emotional connectedness of human–dog relationships; dog’s impact on human health/wellbeing; understanding what dogs are like; and meeting the demands of ownership.

Conclusion

Overall these results aid our understanding of dog-human interactions, highlighting the complexity of the dog-owner relationship which may come with unanticipated costs. Whilst this study’s results are reassuring given many aspects of ownership were as expected, and surprises were often positive, some areas had greater impacts than expected, raising opportunities for intervention, resources or support. The aim would be to manage owners’ expectations prior to acquisition or ensure these are more realistically met, reducing the likelihood of negative welfare implications for both dog and owner.
Rapid detection of high consequence and emerging viral pathogens in pigs
Authors: Neujahr Alison C. , Loy Duan S. , Loy John Dustin , Brodersen Bruce W. , Fernando Samodha C.
Published: February 2024

Introduction

An increasing emergence of novel animal pathogens has been observed over the last decade. Viruses are a major contributor to the increased emergence and therefore, veterinary surveillance and testing procedures are greatly needed to rapidly and accurately detect high-consequence animal diseases such as Foot and Mouth Disease, Highly Pathogenic Avian Influenza, Classical Swine Fever, and African Swine Fever. The major detection methods for such diseases include real-time PCR assays and pathogen-specific antibodies among others. However, due to genetic drift or -shift in virus genomes, failure to detect such pathogens is a risk with devastating consequences. Additionally, the emergence of novel pathogens with no prior knowledge requires non-biased detection methods for discovery.

Methods

Utilizing enrichment techniques coupled with Oxford Nanopore Technologies MinION™ sequencing platform, we developed a sample processing and analysis pipeline to identify DNA and RNA viruses and bacterial pathogens from clinical samples.

Results and discussion

The sample processing and analysis pipeline developed allows the identification of both DNA and RNA viruses and bacterial pathogens simultaneously from a single tissue sample and provides results in less than 12 h. Preliminary evaluation of this method using surrogate viruses in different matrices and using clinical samples from animals with unknown disease causality, we demonstrate that this method can be used to simultaneously detect pathogens from multiple domains of life simultaneously with high confidence.
Screening and selection of essential oils for an intranasal spray against bovine respiratory pathogens based on antimicrobial, antiviral, immunomodulatory, and antibiofilm activities
Authors: Amat Samat , Magossi Gabriela , Rakibuzzaman AGM , Holman Devin B. , Schmidt Kaycie N. , Kosel Luke , Ramamoorthy Sheela
Published: February 2024

Introduction

The rise in antibiotic resistant pathogens associated with bovine respiratory disease (BRD) poses a serious challenge, particularly to the beef feedlot industry, as they currently depend on antibiotics to prevent BRD to mitigate the financial burden (approx. $1 billion annual loss) inflicted by BRD-associated high mortality and morbidity in feedlot cattle. Thus, there is an impetus need for the development of antimicrobial alternative strategies against BRD. This study aimed to screen and select candidate essential oils (EOs) for the development of an intranasal EO spray that can inhibit BRD pathogens and promote microbiota-mediated respiratory health.

Methods

The effects of selected EOs (ajowan, cinnamon leaf, citronella, grapefruit, fennel, and thyme) on a bovine nasopharyngeal microbiota culture were evaluated using 16S rRNA gene sequencing. The microbiota culture was enriched by incubating nasopharyngeal swabs obtained from finishing beef heifers in brain heart infusion broth with and without EOs (0.025%, v/v). These EOs were then also evaluated for their immunomodulatory effects on bovine turbinate (BT) cells by analyzing the concentrations of 15 cytokines and chemokines in cell culture after 24 h incubation. The crystal violet assay was done to assess the antibiofilm activity of EOs against Escherichia coli UMN026 strain. Finally, 15 EOs were screened for their antiviral activity against the bovine viral diarrhea virus 1 (BVDV-1) using BT cells and a fluorescence-based method.

Results

Ajowan, fennel, and thyme resulted in a moderate reduction of overall nasopharyngeal microbiota growth with significant alterations of both alpha and beta diversity, and the relative abundance of predominant bacterial families (e.g., increasing Enterobacteriaceae and decreasing Moraxellaceae) compared to the control (p < 0.05). Co-incubation of BT cells with selected EOs resulted in minimal alterations in cytokine and chemokine levels (p > 0.05). Ajowan, thyme, fennel, and cinnamon leaf exhibited antibiofilm activity at concentrations of 0.025 and 0.05%. Reduction of BVDV-1 replication in BT cells was observed with thyme (strong), and ajowan and citronella (moderate) at 0.0125% concentration.

Discussion

Accordingly, ajowan, thyme, fennel, cinnamon leaf, and citronella EOs were selected for further development as an intranasal EO spray to prevent and control of BRD pathogens in feedlot cattle.
Crop Guidance Photography Algorithm for Mobile Terminals
Authors: Jia Yunsong , Zhao Qingxin , Xiong Yi , Chen Xin , Li Xiang
Published: February 2024

The issues of inadequate digital proficiency among agricultural practitioners and the suboptimal image quality captured using mobile smart devices have been addressed by providing appropriate guidance to photographers to properly position their mobile devices during image capture. An application for crop guidance photography was developed, which involved classifying and identifying crops from various orientations and providing guidance prompts. Three steps were executed, including increasing sample randomness, model pruning, and knowledge distillation, to improve the MobileNet model for constructing a smartphone-based orientation detection model with high accuracy and low computational requirements. Subsequently, the application was realized by utilizing the classification results for guidance prompts. The test demonstrated that this method effectively and seamlessly guided agricultural practitioners in capturing high-quality crop images, providing effective photographic guidance for farmers.
A Lightweight Algorithm for Recognizing Pear Leaf Diseases in Natural Scenes Based on an Improved YOLOv5 Deep Learning Model
Authors: Li Jianian , Liu Zhengquan , Wang Dejin
Published: February 2024

The precise detection of diseases is crucial for the effective treatment of pear trees and to improve their fruit yield and quality. Currently, recognizing plant diseases in complex backgrounds remains a significant challenge. Therefore, a lightweight CCG-YOLOv5n model was designed to efficiently recognize pear leaf diseases in complex backgrounds. The CCG-YOLOv5n model integrates a CA attention mechanism, CARAFE up-sampling operator, and GSConv into YOLOv5n. It was trained and validated using a self-constructed dataset of pear leaf diseases. The model size and FLOPs are only 3.49 M and 3.8 G, respectively. The mAP@0.5 is 92.4%, and the FPS is up to 129. Compared to other lightweight indicates that the models, the experimental results demonstrate that the CCG-YOLOv5n achieves higher average detection accuracy and faster detection speed with a smaller computation and model size. In addition, the robustness comparison test CCG-YOLOv5n model has strong robustness under various lighting and weather conditions, including frontlight, backlight, sidelight, tree shade, and rain. This study proposed a CCG-YOLOv5n model for accurately detecting pear leaf diseases in complex backgrounds. The model is suitable for use on mobile terminals or devices.
Hyperspectral Response of the Soybean Crop as a Function of Target Spot (Corynespora cassiicola) Using Machine Learning to Classify Severity Levels
Authors: de Queiroz Otone José Donizete , Theodoro Gustavo de Faria , Santana Dthenifer Cordeiro , Teodoro Larissa Pereira Ribeiro , de Oliveira Job Teixeira , de Oliveira Izabela Cristina , da Silva Junior Carlos Antonio , Teodoro Paulo Eduardo , Baio Fabio Henrique Rojo
Published: February 2024

Plants respond to biotic and abiotic pressures by changing their biophysical and biochemical aspects, such as reducing their biomass and developing chlorosis, which can be readily identified using remote-sensing techniques applied to the VIS/NIR/SWIR spectrum range. In the current scenario of agriculture, production efficiency is fundamental for farmers, but diseases such as target spot continue to harm soybean yield. Remote sensing, especially hyperspectral sensing, can detect these diseases, but has disadvantages such as cost and complexity, thus favoring the use of UAVs in these activities, as they are more economical. The objectives of this study were: (i) to identify the most appropriate input variable (bands, vegetation indices and all reflectance ranges) for the metrics assessed in machine learning models; (ii) to verify whether there is a statistical difference in the response of NDVI (normalized difference vegetation index), grain weight and yield when subjected to different levels of severity; and (iii) to identify whether there is a relationship between the spectral bands and vegetation indices with the levels of target spot severity, grain weight and yield. The field experiment was carried out in the 2022/23 crop season and involved different fungicide treatments to obtain different levels of disease severity. A spectroradiometer and UAV (unmanned aerial vehicle) imagery were used to collect spectral data from the leaves. Data were subjected to machine learning analysis using different algorithms. LR (logistic regression) and SVM (support vector machine) algorithms performed better in classifying target spot severity levels when spectral data were used. Multivariate canonical analysis showed that healthy leaves stood out at specific wavelengths, while diseased leaves showed different spectral patterns. Disease detection using hyperspectral sensors enabled detailed information acquisition. Our findings reveal that remote sensing, especially using hyperspectral sensors and machine learning techniques, can be effective in the early detection and monitoring of target spot in the soybean crop, enabling fast decision-making for the control and prevention of yield losses.
Automated Classification of User Needs for Beginner User Experience Designers: A Kano Model and Text Analysis Approach Using Deep Learning
Authors: Zhang Zhejun , Chen Huiying , Huang Ruonan , Zhu Lihong , Ma Shengling , Leifer Larry , Liu Wei
Published: February 2024

This study introduces a novel tool for classifying user needs in user experience (UX) design, specifically tailored for beginners, with potential applications in education. The tool employs the Kano model, text analysis, and deep learning to classify user needs efficiently into four categories. The data for the study were collected through interviews and web crawling, yielding 19 user needs from Generation Z users (born between 1995 and 2009) of LEGO toys (Billund, Denmark). These needs were then categorized into must-be, one-dimensional, attractive, and indifferent needs through a Kano-based questionnaire survey. A dataset of over 3000 online comments was created through preprocessing and annotating, which was used to train and evaluate seven deep learning models. The most effective model, the Recurrent Convolutional Neural Network (RCNN), was employed to develop a graphical text classification tool that accurately outputs the corresponding category and probability of user input text according to the Kano model. A usability test compared the tool’s performance to the traditional affinity diagram method. The tool outperformed the affinity diagram method in six dimensions and outperformed three qualities of the User Experience Questionnaire (UEQ), indicating a superior UX. The tool also demonstrated a lower perceived workload, as measured using the NASA Task Load Index (NASA-TLX), and received a positive Net Promoter Score (NPS) of 23 from the participants. These findings underscore the potential of this tool as a valuable educational resource in UX design courses. It offers students a more efficient and engaging and less burdensome learning experience while seamlessly integrating artificial intelligence into UX design education. This study provides UX design beginners with a practical and intuitive tool, facilitating a deeper understanding of user needs and innovative design strategies.
A Comprehensive Review of AI Techniques for Addressing Algorithmic Bias in Job Hiring
Authors: Albaroudi Elham , Mansouri Taha , Alameer Ali
Published: February 2024

The study comprehensively reviews artificial intelligence (AI) techniques for addressing algorithmic bias in job hiring. More businesses are using AI in curriculum vitae (CV) screening. While the move improves efficiency in the recruitment process, it is vulnerable to biases, which have adverse effects on organizations and the broader society. This research aims to analyze case studies on AI hiring to demonstrate both successful implementations and instances of bias. It also seeks to evaluate the impact of algorithmic bias and the strategies to mitigate it. The basic design of the study entails undertaking a systematic review of existing literature and research studies that focus on artificial intelligence techniques employed to mitigate bias in hiring. The results demonstrate that the correction of the vector space and data augmentation are effective natural language processing (NLP) and deep learning techniques for mitigating algorithmic bias in hiring. The findings underscore the potential of artificial intelligence techniques in promoting fairness and diversity in the hiring process with the application of artificial intelligence techniques. The study contributes to human resource practice by enhancing hiring algorithms’ fairness. It recommends the need for collaboration between machines and humans to enhance the fairness of the hiring process. The results can help AI developers make algorithmic changes needed to enhance fairness in AI-driven tools. This will enable the development of ethical hiring tools, contributing to fairness in society.
Insights into Analytical Precision: Understanding the Factors Influencing Accurate Vitamin A Determination in Various Samples
Authors: Shastak Yauheni , Pelletier Wolf , Kuntz Andrea
Published: February 2024

The accurate assessment of vitamin A in animal feed and tissues is vital for safeguarding animal well-being and ensuring high-quality nutritional feed. However, challenges in achieving precise results persist, necessitating a comprehensive understanding of the influencing factors. This review delves into the historical progression of analytical techniques, from colorimetric assays and spectrophotometry to advanced chromatographic methods and non-destructive spectroscopic approaches. Factors influencing analytical precision are scrutinized, encompassing sample preparation, storage conditions, interfering substances, and human errors. The crucial role of quality control and standardized protocols in ensuring the reproducibility and reliability of results is emphasized. Moreover, this review highlights the need for tailored analytical approaches to account for the complexities of sample matrices and the significance of cutting-edge technologies, including on-site analysis and data science integration, in enhancing analytical precision. By acknowledging the challenges and prospects in vitamin A analysis, this paper provides insights for optimizing analytical methodologies and promoting animal welfare and product safety.
Morbidity and Prognostic Factors Associated with Wild Hedgehogs Admitted to a Wildlife Rehabilitation Center in Catalonia (NE Spain) from 1995 to 2020
Authors: Molina-Lopez Rafael A. , Obón Elena , Darwich Laila
Published: February 2024

Wildlife rehabilitation centers (WRC) play a crucial role in the collection of data and the monitoring of hedgehog populations. The main objective of this study was to identify the morbidity and prognostic factors associated with the mortality of wild hedgehogs admitted at a WRC in Catalonia. A total number of 3397 hedgehogs admitted from 1995 to 2020 were studied. The principal cause of admission was orphaned/young category (41%) followed by misplacement (19%), natural disease (17%), and trauma (14%). The best outcomes for release were for misplacement (93.6%), orphaned/young (72.3%), and other causes (77.6%), and the lowest proportion of released animals were found for natural disease (41.4%) and trauma (44.7%) categories. The most common macroscopic findings were the respiratory and digestive lesions. Internal parasites were also prevalent in 61% of the animals but with no association with a higher mortality. In the multivariate analyses, the prognostic indicators related with the mortality outcome were the presence of systemic (OR = 3.6, CI 95%: 2.8–4.6) and neurological (OR = 4.3, CI 95%: 2.9–6.4) signs. Morbidity and prognostic factors in wildlife rehabilitation are essential for providing effective care, making informed decisions, optimizing resources, and improving rehabilitation success rates.
Mechanisms of Gills Response to Cadmium Exposure in Greenfin Horse-Faced Filefish (Thamnaconus septentrionalis): Oxidative Stress, Immune Response, and Energy Metabolism
Authors: Zhang Xuanxuan , Zhang Wenquan , Zhao Linlin , Zheng Li , Wang Bingshu , Song Chengbing , Liu Shenghao
Published: February 2024

Cadmium (Cd) pollution has become a global issue due to industrial and agricultural developments. However, the molecular mechanism of Cd-induced detrimental effects and relevant signal transduction/metabolic networks are largely unknown in marine fishes. Here, greenfin horse-faced filefish (Thamnaconus septentrionalis) were exposed to 5.0 mg/L Cd up to 7 days. We applied both biochemical methods and multi-omics techniques to investigate how the gills respond to Cd exposure. Our findings revealed that Cd exposure caused the formation of reactive oxygen species (ROS), which in turn activated the MAPK and apoptotic pathways to alleviate oxidative stress and cell damage. Glycolysis, protein degradation, as well as fatty acid metabolism might assist to meet the requirements of nutrition and energy under Cd stress. We also found that long-term (7 days, “long-term” means compared to 12 and 48 h) Cd exposure caused the accumulation of succinate, which would in turn trigger an inflammatory response and start an immunological process. Moreover, ferroptosis might induce inflammation. Overall, Cd exposure caused oxidative stress, energy metabolism disturbance, and immune response in greenfin horse-faced filefish. Our conclusions can be used as references for safety risk assessment of Cd to marine economic fishes.
In Vitro Antibacterial Activity of Ceftobiprole and Comparator Compounds against Nation-Wide Bloodstream Isolates and Different Sequence Types of MRSA
Authors: Li Lingqin , Zhou Wangxiao , Chen Yunbo , Shen Ping , Xiao Yonghong
Published: February 2024

Bloodstream infections by bacteria, especially multidrug-resistant bacteria, remain a worldwide public health concern. We evaluated the antibacterial activity of ceftobiprole and comparable drugs against different bloodstream isolates and different sequence types of methicillin-resistant Staphylococcus aureus (MRSA) in China. We found that MRSA, methicillin-susceptible Staphylococcus aureus (MSSA), and methicillin-susceptible coagulase-negative Staphylococcus (MSCNS) displayed ceftobiprole sensitivity rates of >95%, which are similar to the rates for linezolid, daptomycin, and vancomycin. Of the tested MRCNS strains, 90.4% were sensitive to ceftobiprole. The sensitivities of ST59, ST398, and ST22 MRSA to ceftobiprole were higher than that of ST239. Ceftobiprole’s MIC50/90 value against Enterococcus faecalis was 0.25/2 mg/L, whereas Enterococcus faecium was completely resistant to this drug. Ceftobiprole exhibited no activity against ESBL-positive Enterobacterales, with resistance rates between 78.6% and 100%. For ESBL-negative Enterobacterales, excluding Klebsiella oxytoca, the sensitivity to ceftobiprole was comparable to that of ceftazidime, ceftriaxone, and cefepime. The MIC50/90 value of ceftobiprole against Pseudomonas aeruginosa was 2/16 mg/L, and for Acinetobacter baumannii, it was 32/>32 mg/L. Thus, ceftobiprole shows excellent antimicrobial activity against ESBL-negative Enterobacterales and Pseudomonas aeruginosa (comparable to that of ceftazidime, ceftriaxone, and cefepime); however, it is not effective against ESBL-positive Enterobacterales and Acinetobacter baumannii. These results provide important information to clinicians.
Iron, Oxidative Stress, and Metabolic Dysfunction—Associated Steatotic Liver Disease
Authors: Gensluckner Sophie , Wernly Bernhard , Datz Christian , Aigner Elmar
Published: February 2024

Excess free iron is a substrate for the formation of reactive oxygen species (ROS), thereby augmenting oxidative stress. Oxidative stress is a well-established cause of organ damage in the liver, the main site of iron storage. Ferroptosis, an iron-dependent mechanism of regulated cell death, has recently been gaining attention in the development of organ damage and the progression of liver disease. We therefore summarize the main mechanisms of iron metabolism, its close connection to oxidative stress and ferroptosis, and its particular relevance to disease mechanisms in metabolic-dysfunction-associated fatty liver disease and potential targets for therapy from a clinical perspective.
Gender Influence on XOR Activities and Related Pathologies: A Narrative Review
Authors: Bolognesi Andrea , Bortolotti Massimo , Battelli Maria Giulia , Polito Letizia
Published: February 2024

Taking into account the patient’s gender is the first step towards more precise and egalitarian medicine. The gender-related divergences observed in purine catabolism and their pathological consequences are good examples of gender medicine differences. Uric acid is produced by the activity of xanthine oxidoreductase (XOR). The serum levels of both XOR activity and uric acid differ physiologically between the genders, being higher in men than in women. Their higher levels have been associated with gout and hypertension, as well as with vascular, cardiac, renal, and metabolic diseases. The present review analyzes the gender-related differences in these pathological conditions in relation to increases in the serum levels of XOR and/or uric acid and the opportunity for gender-driven pharmacological treatment.
Highway Construction Safety Analysis Using Large Language Models
Authors: Smetana Mason , Salles de Salles Lucio , Sukharev Igor , Khazanovich Lev
Published: February 2024

The highway construction industry carries substantial safety risks for workers, necessitating thorough accident analyses to implement effective preventive measures. Current research lacks comprehensive investigations into safety incidents, relying heavily on conventional statistical methods and overlooking valuable textual information in publicly available databases. This study leverages a state-of-the-art large language model (LLM), specifically OpenAI’s GPT-3.5 model. The primary focus is to enhance text-based incident analysis that is sourced from OSHA’s Severe Injury Reports (SIR) database. By incorporating novel natural language processing (NLP) techniques, dimensionality reduction, clustering algorithms, and LLM prompting of incident narratives, the study aims to develop an approach to the analysis of major accident causes in highway construction. The resulting cluster analysis, coupled with LLM summarization and cause identification, reveals the major accident types, such as heat-related and struck-by injuries, as well as commonalities between incidents. This research showcases the potential of artificial intelligence (AI) and LLM technology in data-driven analysis. By efficiently processing textual data and providing insightful analysis, the study fosters practical implications for safety professionals and the development of more effective accident prevention and intervention strategies within the industry.
The Effect of Different Ferrule Configurations and Preparation Designs on the Fatigue Performance of Endodontically Treated Maxillary Central Incisors: A 3D Finite Element Analysis
Authors: Demirel Mehmet Gökberkkaan , Mohammadi Reza
Published: February 2024

The presence of an adequate circumferential ferrule is of great importance for the prosthetic rehabilitation of endodontically treated teeth. However, there may not be an adequate circumferential ferrule effect. This study aimed to evaluate the fatigue performance of endocrown and post–core restorations applied to different configurations without an adequate ferrule effect using the finite element method and endeavors to offer a comprehensive perspective on the challenging rehabilitation of maxillary incisors with excessive coronal substance loss, addressing a notable gap in research and providing valuable insights for clinicians. The goal is to address this gap in research and contribute valuable insights that could be beneficial for practitioners. The maxillary central incisor was selected, and lithium disilicate (LS) and a polymer-infiltrated ceramic network (PICN) were used in post–core groups with no ferrule effect (PC0); a 2 mm ferrule effect on the buccal wall (PC1); a 2 mm ferrule effect on the buccal-mesial wall (PC2); a 2 mm ferrule effect on the buccal–mesial–palatal wall (PC3); and a 2 mm circumferential ferrule effect (PC4) In the endocrown groups, an external retention group with a circumferential ferrule (ECER) and an inner retention form group (ECIR) were prepared. Fatigue performance was examined by applying a 150 N oblique load. The evaluation of the fatigue performance of the restorative materials shows that LS always had more successful fatigue performance results, while the post–core groups were generally more successful in terms of dentin survival. In situations where there is insufficient circumferential ferrule, the application of endocrowns is likely to result in a less successful prognosis for survival.
Segmental Regularized Constrained Inversion of Transient Electromagnetism Based on the Improved Sparrow Search Algorithm
Authors: Tan Chao , Ou Xingzuo , Tan Jiwei , Min Xinyu , Sun Qihao
Published: February 2024

The initial inversion model is typically established in a transient electromagnetic nonlinear inversion, assuming the accurate capture of the number of layers in the geoelectric model; however, this assumption leads to significantly poorer inversion results for complex models when obtaining the exact number of layers from available a priori information, which is challenging. This study proposes a segmented regularized inversion method to enhance inversion accuracy and stability under varying conditions. The process involves two key steps: Firstly, a segmented initial model is established based on preliminary information. The layering criteria and layer thickness threshold for each segment are set during inversion to reduce dependence on the accuracy of the preliminary information. Secondly, a segmented regularization constraint is added to the objective function to improve the efficiency and stability of the inversion, as numerous parameters can exacerbate the problem of inversion ambiguity. Subsequently, an improved sparrow search algorithm (ISSA) is utilized to optimize the inversion objective function. This enhances the efficiency of searching for the objective function and the algorithm’s ability to escape local optimal solutions. The proposed method is evaluated using one-dimensional and two-dimensional models with different initial models and inversion algorithms and applied to the inversion of on-site exploration data in a coal mining area in Chongqing. Comparative results demonstrate that the proposed segmented regularization method, based on the improved sparrow search algorithm, exhibits superior practicality and a higher fitting accuracy.
Enhancing Freeway Traffic Capacity: The Impact of Autonomous Vehicle Platooning Intensity
Authors: Chang Qing , Chen Hong
Published: February 2024

This paper proposes a theoretical model to discuss the capacity of heterogeneous saturated flow. A crucial indicator, platooning intensity, which represents the willingness of connected and autonomous vehicles to form platoons, is taken into consideration. The relationship between platooning intensity and the penetration rate of connected and autonomous vehicles is also evaluated. Numerical analysis is conducted based on relevant parameters, which further improves the proposed theoretical model. Finally, a microscopic simulation is used to verify the accuracy of the proposed model. The results indicate that both the speed and the market penetration rate have a significant impact on capacity; however, the impact is not linear. The slope of the speed-affected curve gradually decreases, whereas the slope of the market penetration rate-affected curve gradually increases. The impact of market penetration rate on theoretical capacity intensifies with the increase in speed. As the number of vehicles within a fleet increase, the weighted average of platooning intensity gradually tends towards the market penetration rate. The formulation offers important insights into traffic performance with heterogeneous flow.
Multi-View Jujube Tree Trunks Stereo Reconstruction Based on UAV Remote Sensing Imaging Acquisition System
Authors: Ling Shunkang , Li Jingbin , Ding Longpeng , Wang Nianyi
Published: February 2024

High-quality agricultural multi-view stereo reconstruction technology is the key to precision and informatization in agriculture. Multi-view stereo reconstruction methods are an important part of 3D vision technology. In the multi-view stereo 3D reconstruction method based on deep learning, the effect of feature extraction directly affects the accuracy of reconstruction. Aiming at the actual problems in orchard fruit tree reconstruction, this paper designs an improved multi-view stereo structure based on the combination of remote sensing and artificial intelligence to realize the accurate reconstruction of jujube tree trunks. Firstly, an automatic key frame extraction method is proposed for the DSST target tracking algorithm to quickly recognize and extract high-quality data. Secondly, a composite U-Net feature extraction network is designed to enhance the reconstruction accuracy, while the DRE-Net feature extraction enhancement network improved by the parallel self-attention mechanism enhances the reconstruction completeness. Comparison tests show different levels of improvement on the Technical University of Denmark (DTU) dataset compared to other deep learning-based methods. Ablation test on the self-constructed dataset, the MVSNet + Co U-Net + DRE-Net_SA method proposed in this paper improves 20.4% in Accuracy, 12.8% in Completion, and 16.8% in Overall compared to the base model, which verifies the real effectiveness of the scheme.
An Overview of Recent Developments and Understandings of Unconventionals in the Vaca Muerta Formation, Argentina
Authors: Lu Xinqian , Li Siyuan , Han Ruijing , Jia Bao , Xian Chenggang , Ding Fei , Zhang Yu , Zhong Shibo , Xu Qi , Zuo Xuan
Published: February 2024

In this article, we comprehensively reviewed Argentina’s Vaca Muerta formation, which encompasses a geological overview, advances in extraction technologies, the potential environmental impact, and economic analysis. Detailed geological analysis is discussed, emphasizing the stratigraphy, lithology, and depositional environments of the formation, which is crucial for understanding the distribution and quality of hydrocarbon resources. The latest advancements in hydraulic fracturing and horizontal drilling are explored, which have significantly improved efficiency and increased recoverable resources. The environmental implications of these extraction methods are critically examined. This includes a discussion of the necessity of sustainable practices in hydrocarbon extraction, highlighting the balance between resource development and environmental stewardship. The economic viability of the Vaca Muerta formation is analyzed, with a focus on cost-effectiveness, market trends, and investment patterns. This section assesses the formation’s potential as a profitable venture and its impact on the global energy market. Finally, the review anticipates future technological and policy developments. The strategic importance of the Vaca Muerta formation in the global energy sector is underscored, and its potential role in shaping future hydrocarbon exploration and production strategies is examined. In short, this essay not only presents data and findings, but also contextualizes them within the broader scope of energy production, environmental sustainability, and economic viability. This comprehensive approach provides a multi-faceted understanding of the Vaca Muerta formation’s significance in the global energy landscape.
Unmanned Helicopter Airborne Fourier Transform Infrared Spectrometer Remote Sensing System for Hazardous Vapors Detection
Authors: Shi Zhengyang , Huang Min , Qian Lulu , Han Wei , Zhang Guifeng , Lu Xiangning
Published: February 2024

The rapid development of unmanned aerial vehicles (UAVs) provides a new application mode for gas remote sensing. Compared with fixed observation and vehicle-mounted platforms, a Fourier transform infrared spectrometer (FTIR) integrated in the UAV can monitor chemical gases across a large area, can collect data from multiple angles in three-dimensional space, and can operate in contaminated or hazardous environments. The unmanned helicopter has a larger payload and longer endurance than the rotary-wing drone, which relaxes the weight, size and power consumption limitations of the spectrometer. A FTIR remote sensing system integrated in an unmanned helicopter was developed. In order to solve the data acquisition and analysis problem caused by vibration and attitude instability of the unmanned helicopter, a dual-channel parallel oscillating mirror was designed to improve the stability of the interferometer module, and a robust principal component analysis algorithm based on kernel function was used to separate background spectrum and gas features. The flight experiment of sulfur hexafluoride gas detection was carried out. The results show that the system operates stably and can collect and identify the target spectrum in real time under the motion and hovering modes of an unmanned helicopter, which has broad application prospects.
A Realistic Hand Image Composition Method for Palmprint ROI Embedding Attack
Authors: Yan Licheng , Leng Lu , Teoh Andrew Beng Jin , Kim Cheonshik
Published: February 2024

Palmprint recognition (PPR) has recently garnered attention due to its robustness and accuracy. Many PPR methods rely on preprocessing the region of interest (ROI). However, the emergence of ROI attacks capable of generating synthetic ROI images poses a significant threat to PPR systems. Despite this, ROI attacks are less practical since PPR systems typically take hand images as input rather than just the ROI. Therefore, there is a pressing need for a method that specifically targets the system by composing hand images. The intuitive approach involves embedding an ROI into a hand image, a comparatively simpler process requiring less data than generating entirely synthetic images. However, embedding faces challenges, as the composited hand image must maintain a consistent color and texture. To overcome these challenges, we propose a training-free, end-to-end hand image composition method incorporating ROI harmonization and palm blending. The ROI harmonization process iteratively adjusts the ROI to seamlessly integrate with the hand using a modified style transfer method. Simultaneously, palm blending employs a pretrained inpainting model to composite a hand image with a continuous transition. Our results demonstrate that the proposed method achieves a high attack performance on the IITD and Tongji datasets, with the composited hand images exhibiting realistic visual quality.
Status Recognition of Marine Centrifugal Pumps Based on a Stacked Sparse Auto-Encoder
Authors: He Yi , Yao Yunan , Ou Hongsen
Published: February 2024

Marine centrifugal pumps (MCPs) are widely used in ships, so it is important to identify their status accurately for their maintenance. Due to the influence of load, friction, and other non-linear factors, the vibration signal of an MCP shows non-linear and non-stationary characteristics, and it is difficult to extract the state characteristics contained in the vibration signal. To solve the difficulty of feature extraction of non-linear non-stationary vibration signals generated by MCPs, a novel MCP frequency domain signal feature extraction method based on a stacked sparse auto-encoder (SSAE) is proposed. The characteristic parameters of MCP frequency domain signals are extracted via the SSAE model for classification training, and different statuses of MCPs are identified. The vibration signals in different MCP statuses were collected for feature extraction and classification training, and the MCP status recognition accuracy based on the time domain feature and fuzzy entropy feature was compared. According to the test data, the accuracy of MCP status recognition based on the time domain feature is 71.2%, the accuracy of MCP status recognition based on the fuzzy entropy feature is 87.7%, and the accuracy of MCP status recognition based on the proposed method is 100%. These results show that the proposed method can accurately identify each status of an MCP under test conditions.
Bonding to Psychedelics: Synthesis of Molecularly Imprinted Polymers Targeting 4-Bromo-2,5-dimethoxyphenethylamine (2C-B)
Authors: Martins Daniel , Fernandes Carlos , Mendes Ricardo F. , Cagide Fernando , Silva António Fernando , Borges Fernanda , Garrido Jorge
Published: February 2024

The increasing interest in utilizing psychedelics for therapeutic purposes demands the development of tools capable of efficiently monitoring and accurately identifying these substances, thereby supporting medical interventions. 4-Bromo-2,5-dimethoxyphenethylamine (2C-B) has gained significant popularity as one of the most widely used psychedelic compounds in non-medical settings. In this study, we aimed to create a material with selective recognition of 2C-B by synthesizing a series of molecularly imprinted polymers (MIP) using 2C-B as the template and varying ratios of methacrylic acid (MAA) as the functional monomer (1:2, 1:3, and 1:4). Both thermal and microwave-assisted polymerization processes were employed. The molar ratio between the template molecule (2C-B) and functional monomer (MAA) was 1:4, utilizing a microwave-assisted polymerization process. Isotherm studies revealed a Langmuir’s maximum absorption capacity (Bmax) value of 115.6 μmol·mg−1 and Kd values of 26.7 μM for this material. An imprint factor of 4.2 was determined for this material, against the corresponding non-imprinted polymer. The good selectivity against 14 other new psychoactive substances highlighted the material’s potential for applications requiring selective recognition. These findings can contribute to the development of tailored materials for the detection and analysis of 2C-B, supporting advancements in non-medical use monitoring and potential therapeutic models involving psychedelics.
On Some Properties of a Complete Quadrangle
Authors: Volenec Vladimir , Šimić Horvath Marija , Jurkin Ema
Published: February 2024

In this paper, we study the properties of a complete quadrangle in the Euclidean plane. The proofs are based on using rectangular coordinates symmetrically on four vertices and four parameters a,b,c,d. Here, many properties of the complete quadrangle known from earlier research are proved using the same method, and some new results are given.
Reply to Theodorou et al. Comment on “Umemoto et al. Management of Migraine-Associated Vestibulocochlear Disorders. Audiol. Res. 2023, 13, 528–545”
Authors: Mazhari Najva , Tawk Karen , Umemoto Kayla K. , Abouzari Mehdi , Djalilian Hamid R.
Published: February 2024

We thank the authors for their insightful and thoughtful commentary on our recent publication [...]
Combined Effect of Maternal Separation and Early-Life Immune Activation on Brain and Behaviour of Rat Offspring
Authors: Biswas Bharti , Eapen Valsamma , Morris Margaret J. , Jones Nicole M.
Published: February 2024

Adversity during early life, a critical period for brain development, increases vulnerability and can have a lasting impact on the brain and behaviour of a child. However, the long-term effects of cumulative early-life stressors on brain and behaviour are not well known. We studied a 2-hit rat model of early-life adversity using maternal separation (MS) and immune activation (lipopolysaccharide (LPS)). Rat pups underwent MS for 15 (control) or 180 (MS) minutes per day from postnatal day (P)2–14 and were administered saline or LPS (intraperitoneal) on P3. Open-field (OFT) and object-place recognition tests were performed on rat offspring at P33–35 and P42–50, respectively. The pre-frontal cortex (PFC) and hippocampus were removed at the experimental endpoint (P52–55) for mRNA expression. MS induced anxiety-like behaviour in OFT in male and reduced locomotor activity in both male and female offspring. LPS induced a subtle decline in memory in the object-place recognition test in male offspring. MS increased glial fibrillary acidic protein (GFAP) and brain-derived neurotrophic factor expression in PFC and ionised calcium-binding adapter molecule-1 expression in male hippocampus. MS and LPS resulted in distinct behavioural phenotypes in a sex-specific manner. The combination of MS and LPS had a synergistic effect on the anxiety-like behaviour, locomotor activity, and GFAP mRNA expression outcomes.