bluuebunny/crossref_metadata_2025_split huggingface dataset:
Canine distemper outbreak and laryngeal paralysis in captive tigers (Panthera tigris)
Authors: Suwanpakdee Sarin , Wiratsudakul Anuwat , Chaisilp Nattarun , Prasittichai Luxsana , Skulpong Anurux , Maneeorn Patarapol , Bhusri Benjaporn , Mongkolpan Chalisa , Buddhirongawatr Ruangrat , Taowan Jarupa , Wongluechai Peerawat , Arya Nlin , Suwannaprapha Parin , Ngamwongsatit Natharin , Wiriyarat Witthawat , Sangkachai Nareerat 
Published: December 2023

Abstract

The canine distemper virus (CDV) could infect various wildlife species worldwide. The viral infection in large felids directly impacts wildlife conservation. This study aimed to understand better the burden of CDV outbreaks in captive tiger populations in Thailand and a novel discovery of their clinical signs with a history of CDV exposure. We followed up on their infection from June 2016 to October 2020 with laboratory testing and veterinary medical records. The cumulative morbidity and mortality rates were relatively high. Moreover, 50% of the tigers survived at 2 years after infection. Approximately 38% of CDV infections were detected with laryngeal inflammation, which developed into paralysis in almost 50% of cases. Altogether, 50% of tigers with chronic infection developed stridor at 314 days after virus infection [95% CI: 302–320]. Our data indicates that laryngeal paralysis resulted from the CDV infection, potentially affecting the peripheral and central nervous systems. This condition can pose a life-threatening risk to tigers. The virus can spread quickly by contact with bodily excretion among tigers and fomite contamination once it affects a specific population. Implementation of biosecurity measures and vaccination is essential to mitigate the risk of disease spread and infection rates in tiger populations.
A Systematic review and meta-analysis to compare the effectiveness of shorter 12-hour N-Acetylcysteine (NAC) regimen VS 20-21-hour NAC regimen in management of paracetamol poisoning
Authors: Oyedeji¹ Olawunmi Oluwakemi , Oisakede¹ Emmanuel Ojeabuo 
Published: December 2023

Abstract

Background: Paracetamol poisoning due to unrecommended doses is a leading cause of acute liver failure (ALF) globally, resulting in significant medical consequences. N-Acetylcysteine (NAC) is the standard antidote for paracetamol poisoning, administered through a 20-21 hour 3-bag infusion since 1980. However, this regimen has been associated with adverse reactions, prompting the investigation of shorter NAC regimens like the 12-hour version. A comparison of evidence on the effectiveness and safety between the two interventions is lacking, necessitating this research.
Aims and Objectives: A meta-analysis to compare the effectiveness of a 12-hour NAC regimen with the longer 20-21hour regimen in managing paracetamol poisoning.
Methods: A quantitative systematic review of Randomized Controlled Trials (RCTs) and observational studies was performed, using PICO criteria to search databases Medline, Web of Science, PubMed, Cochrane and Clinical trials.com from 2008 to 2023. The extracted data were analyzed separately for RCTs and observational studies.
Results: Eight studies, including three RCTs and five observational studies involving 10,924 patients, were analyzed. The primary outcome, hepatic injury, showed an insignificant reduction with the 20-21hour NAC regimen (odds ratio= 1.53, 95% CI 0.69-3.40, p=0.29) in RCTs and with the 12-hour NAC regimen (odds ratio= 0.88, 95% CI 0.70-1.11, p=0.29) in observational studies. The secondary outcome, adverse reactions (anaphylactoid reaction), showed a statistically significant reduction with the 12-hour NAC regimen (odds ratio= 0.37, 95% CI 0.20-0.68, p=0.001) in RCTs and (odds ratio= 0.16, 95% CI 0.12-0.22, p=0.00001) in the observational studies.
Conclusions: This study suggests that the 12-hour NAC regimen is as effective as the 20-21hour regimen in managing paracetamol poisoning, but with fewer adverse reactions. However, further research is needed to explore the impact of factors like late presentation and delayed infusion on adverse reactions.
Asymmetric scattering effect of solitary wave in a two-section composite granular chain
Authors: Liu Xingyi , Jiao Tengfei , Zhang Shutian , Sun Min , Huang Decai 
Published: December 2023

Abstract
This study presents numerical simulations on the asymmetric scattering effect of solitary waves in a two$-$section composite granular chain. On the basis of Nesterenko's work on solitary waves in monodisperse granular chains and continuous acoustic wave theory in linear medium, we argue that the mismatches of acoustic velocity and acoustic impedance, because of the differences of mass density and elastic coefficient, dominate the asymmetric scattering effect at the mismatched interface. The simulation results confirm the occurrence of a multipusle structure for the transmitted solitary waves when the solitary wave passes through the mismatched interface with a small$-$large wave velocity. The overshooting effect occurs for the reflected solitary waves because of the mismatched interface with high$-$low acoustic impedance. The phase diagram in the space of the mass density and the elastic coefficient ratio of the right$-$section granular chain to the left$-$section granular chain further validates the predictions. The results are crucial for the fundamental understanding of the dynamic behavior of solitary waves in granular chains.
Fault Detection and Isolation in System of Multiple-Sources of Energy Using Hierarchical Bayesian Belief Networks
Authors: EDDINE Abbass ZEIN , GUERIN Francois , ZAAROUR Iyad , HIJZAI Abbas , LEFEBVRE Dimitri 
Published: December 2023

Abstract
Ensuring fault tolerance in Systems of Multiple-Sources of Energy (SMSE) is of paramount impor-tance for their reliable operation. Detecting, localizing, and characterizing faults are critical tasks toensure system integrity. One crucial element within SMSE, susceptible to faults, is the power convert-ers. This paper introduces an innovative approach leveraging Hierarchical Bayesian Belief Networks(HBBNs) for the identification and isolation of open circuit faults in DC-DC power converters com-monly employed in SMSE applications. Our proposed method addresses the challenge of fault detectionand localization, contributing to enhanced system reliability. The effectiveness of the approach isdemonstrated through extensive testing on simulated data generated via a developed state spacemodel. The results underscore the viability of our approach in bolstering the robustness of DC-DCpower converters against open circuit faults.
Nomogram in Predicting Hemorrhagic Shock in Pediatric Patients with Multiple Trauma: A Retrospective Analysis
Authors: Lin Nan , Jin Jingyi , Yang Sisi , Zhong Xiaohui , Zhang Hang , Ren Yichao , Tan Linhua , Xu Hongzhen , Ma Daqing , Tou Jinfa , Shu Qiang , Lai Dengming 
Published: December 2023

Abstract
Background: The timely detection and management of hemorrhagic shock hold paramount importance in clinical practice. This study was designed to establish a nomogram that may facilitate early identification of hemorrhagic shock in pediatric patients with multiple-trauma.
Methods: A retrospective study was conducted utilizing a cohort comprising 325 pediatric patients diagnosed with multiple-trauma, who received treatment at the Children's Hospital, Zhejiang University School of Medicine, Zhejiang, China. For external validation, an additional cohort of 144 patients from a children's hospital in Taizhouwas included. The model's predictor selection was optimized through the application of the Least Absolute Shrinkage and Selection Operator (LASSO) regression. Subsequently, a prediction nomogram was constructed using multivariable logistic regression analysis. The performance and clinical utility of the developed model were comprehensively assessed utilizing various statistical metrics, including Harrell's Concordance Index (C-index), receiver operating characteristic (ROC) curve analysis, calibration curve analysis, and decision curve analysis (DCA).
Findings: Multivariate logistic regression analysis identified systolic blood pressure (SBP), platelet count, activated partial thromboplastin time (APTT), and injury severity score (ISS) as independent predictors for hemorrhagic shock. The nomogram constructed using these predictors demonstrated robust predictive capabilities, as evidenced by an impressive area under the curve (AUC) value of 0.967 and a concordance index of 0.968. The model's goodness-of-fit was assessed using the Hosmer-Lemeshow test (Chi Square =10.065, P=0.260). Furthermore, decision curve analysis revealed significantly improved net benefits with the model. External validation further confirmed the reliability of the proposed predictive nomogram.
Conclusions: This study successfully developed a nomogram for predicting the occurrence of hemorrhagic shock in pediatric patients with multiple trauma. This nomogram may serve as an accurate and effective tool for timely and efficient management of children with multiple trauma.
An Artificial Intelligence-Assisted Digital Microfluidic System for Multistate Droplet Control
Authors: Gu Zhen , Guo Kunlun , Song Zerui , Zhou Jiale , Shen Bin , Yan Bingyong , Wang Huifeng 
Published: December 2023

Abstract

Digital microfluidics (DMF) is a versatile technique for parallel and field-programmable control of individual droplets. Given the high freedom in droplet manipulation, it is essential to establish self-adaptive and intelligent control methods for DMF systems with informed of the transient state of droplets and their interactions. However, most related studies focus on the localization and shape recognition of droplets. Here, we develop an AI-assisted DMF framework named "µDropAI" for multistate droplet control based on droplet morphology. Semantic segmentation model is integrated into our custom-designed DMF system to recognize the droplet states and their interactions for feedback control with a state machine. The proposed model has a strong flexibility and can recognize droplets of different colors and shapes with an error rate of less than 0.63%. It enables control of droplets without user intervention. The coefficient variation (CV) of the volumes of split droplets can be limited to below 2.8%, which is lower than the CV of traditional dispense, contributing to an improvement in the precision of droplet split. The proposed system will inspire the development of semantic-driven DMF systems which can interface with multimodal large language models (MLLM) for fully automatic control.
Change in Sexual and Reproductive Health Knowledge among Young Women Using the Conversational Agent “Nthabi” in Lesotho: A Clinical Trial
Authors: Nkabane-Nkholongo Elizabeth , Mokgatle Mathildah , Bickmore Timothy , Julce Clevanne , Thompson David , JAck Brian 
Published: December 2023

Abstract
Background. Young women worldwide face problems like unwanted pregnancy and sexually transmitted infections. Providing sexual and reproductive health education to this population remains a priority. It is unknown if using digital health interventions to deliver health education in human resource-constrained settings is effective.Methods. We conducted a clinical trial of the Nthabi intervention to determine participant’s knowledge before and after discussion of family planning, folic acid and healthy eating among young women aged 18–28 years in two rural districts of Lesotho who used the Nthabi conversational agent system on either smartphones or tablets for up to six weeks. The number of correct pre- and post-test responses were compared using generalized linear models that directly estimated the proportions and percentages of correct responses.Results. Of the 172 participants enrolled, the mean age was 22.5 years, 91% were unmarried, 69% completed high school, 23% were unemployed and 66% were students. The mean number of interactions with Nthabi was 8.6. Family planning was chosen to be discussed by 82 (52.2%), of the 172 participants and of those, 49 (59.8%) completed the content on this topic, and 26 (53.1%) completed the post-test. For the 11 questions about family planning, there were 717 (76.6%) correct responses on the pre-test and 320 (89.9%) on the post-test (p = 0.0233). Folic acid was chosen to be discussed by 74 (47.1%) of 172 participants, and of those, 27 (36.5%) completed the content on this topic, and all 27 (100%) completed the post-test. For the 5 questions about folic acid use, there were 181 (45.3%) correct responses on the pre-test and 111 (71.6%) on the post-test (p < 0.0001). The number of correct responses on the post-test was positively associated with the number of sessions that the participant engaged with Nthabi.Conclusion. The Nthabi conversational agent system increased knowledge of family planning methods and folic acid use among young women in Lesotho. Digital health interventions like Nthabi offer new opportunities to deliver reproductive health information in countries that have limited human resources for health.Trial Registration: ClinicalTrials.gov ID: NCT04354168
Development of Variable Wheels for Wheelchairs and Evaluation of Their Step-climbing Performance Using a Wheel Traction Device
Authors: Kuge Mayuu , Inoue Jun 
Published: December 2023

Abstract

In 2021, the percentage of the population aged 65 years and higher was 9.6% of the total population, and this ageing population is expected to increase globally. According to Sustainable Development Goal 11, barrier-free urban areas are expected to increase as braille blocks and roadside boundary blocks are widely used. However, this may cause discomfort to wheelchair users or become an obstacle to running wheelchairs. In this study, we focused on improving the wheel-type mechanism of climbing steps, which exhibits the highest performance when driving on flat terrain, to ensure the smooth and safe movement of wheelchairs. Although a step-climbing robot with a wheel-type mechanism can climb high steps, it has a large body and involves complicated control. The large size of the machine renders its attachment to wheelchairs difficult, reducing the mobility and safety of existing wheelchairs. Therefore, we developed a wheel to maintain the advantages of existing wheelchairs and improve their step-climbing performance. The developed wheel comprises a ‘normal mode’ for running on flat ground and an ‘expand mode’ for climbing steps. The diameter of the wheel in the expand mode is larger than that in the normal mode to improve the performance when climbing steps. Additionally, a spring was attached to the ‘foot’, which was installed to widen the diameter for enhanced driving stability. The step-climbing performance of the developed wheels was experimentally evaluated. A device was fabricated to pull the wheel using manual power and a motor. The motor-driven experimental apparatus maintained a constant traction force, facilitating a quantitative evaluation. The experiment further indicated that the contact position between the step and foot affected the step-climbing performance. Therefore, the study findings provide insights into the enhancement of the wheel-type mechanism for its efficient implementation in wheelchairs, which can contribute to their ease of use.
Dynamic PScore: A Dynamic Method to Prioritize User Reviews
Authors: Dehkordi Mehrdad Razavi , Rastegari Hamid , Najafabadi Akbar Nabiolahi , Gandomani Taghi Javdani 
Published: December 2023

Abstract
Since the emergence of mobile apps, user reviews have been of great importance for app developers as they contain users’ sentiment, bugs and new requests. Due to the large number of reviews, it is a difficult, time-consuming and error-prone task to prioritize them manually. Having a tool or method for automated prioritization of reviews could save the development team’s time, help application development and maintenance cycle and prevent the development team’s errors. Various methods have been presented for prioritizing reviews, most of which have focused on old features that are no longer valid or ignored new features provided by the store. This study provides a method, called Dynamic PScore, for dynamic prioritization of reviews into five categories of hot, serious, pay attention, getting traction and not serious in the Google Play store. In this method, the score is calculated using ThumbsUp features (popularity of each review), extracting sentiment and considering the number of words in the review and, then, prioritization is done through the obtained score. To experimentally evaluate the proposed method in PPrior database, the corresponding score is calculated for each review and prioritization is done. Finally, the results indicate the presented method has the Accuracy and PSP of 99.94% and 99.86%, respectively, in prioritizing and scoring reviews and its prioritization accuracy has improved by 13.34% compared to recent research.
Prediction of Bridge Damage Factors Using Decision Tree Technique (Case Study: Concrete Rad Bridges in ZANJAN Province-IRAN)
Authors: Medghalchi Ali , Rashvad Pooria , Delnavaz Ali 
Published: December 2023

Abstract
The current management system for concrete road bridges in Iran is primarily based on a descriptive model, which assesses the condition of bridge elements and assigns grades based on the level of deterioration. However, there have been concerns raised about the use of descriptive statistics when analyzing large amounts of data. In order to address these concerns, this research incorporates the data mining method known as decision tree analysis. The decision tree analysis involves in-depth examination of data, including objective observations by experts and calculations of damage indices. We have introduced this method to replace descriptive analysis in his research. To conduct this study, various data such as physical characteristics, atmospheric and climatic conditions, traffic conditions, and deterioration indices (derived from established formulas and tables) of concrete bridges with spans exceeding 6 meters on a main 5-axis road in Zanjan province were collected. The decision tree method, along with Rapid Miner software, was utilized to model and analyze this data. The research findings indicate that the decision tree method demonstrates a high level of accuracy in predicting and prioritizing factors that contribute to bridge damage, surpassing the capabilities of conventional models. Specifically, the study reveals that the percentage of heavy vehicles passing over a bridge is the most significant factor influencing its damage. Furthermore, it predicts that bridges with a percentage exceeding 19.5% would fall into the category of heavily damaged bridges.
YOLOv8-CML: A lightweight target detection method for Color-changing melon ripening in intelligent agriculture
Authors: Chen Guojun , Hou Yongjie , Cui Tao , Li Huihui , Shangguan Fengyang , Cao Lei 
Published: December 2023

Abstract

To enhance the efficiency of robot automatic picking of Color-changing melons under intelligent agriculture environments, this study introduces a lightweight model for target detection, YOLOv8-CML, for effectively detecting the ripeness of Color-changing melons. The model structure is simplified to reduce the deployment cost of image recognition models on agricultural edge devices. First, we replace the Bottleneck structure of the C2f module with a Faster Block, which reduces superfluous computations and the frequency of memory accesses by the model. Then, we use a lightweight C2f module combined with EMA attention in Backbone, which can efficiently collect multi-scale spatial information and reduce the interference of background factors on Color-changing melon recognition. Next, we use the idea of shared parameters to redesign the detection head to perform the Conv operation uniformly before performing the classification and localization tasks separately, thus simplifying the structure of the model. Finally, we use the α-IoU approach to optimize the CIoU loss function, which can better measure the overlap between the predicted and actual frames to improve the accuracy of the recognition. The experimental results show that the parameters and FLOPs ratio of the improved YOLOv8-CML model decreased by 42.9% and 51.8%, respectively, compared to the YOLOv8n model. In addition, the model size is merely 3.7MB, and the inference speed is increased by 6.9%, along with mAP@0.5, Precision, and FPS. Our proposed model provides a vital reference for deploying Color-changing melon picking robots.
Screening Stability, Thermochemistry, and Chemical kinetics of 3-Hydroxy butanoic acid as a bi-functional biodiesel additive
Authors: Abdel-Rahman Mohamed A. 
Published: December 2023

Abstract
Thermo-kinetic aspects of 3-Hydroxybutanoic acid (3-HBA) pyrolysis in the gas phase have been studied computationally in the temperature range 600–1700 K and pressure of 1 bar using the ab initio CBS-QB3 method and M06-2X/cc-pvTZ level with the aid of the Gaussian 09 program and the Kinetic and Statistical Thermodynamical Package (KiSThelP). The degradation mechanism was divided into seventeen pathways: seven complex fissions and ten barrierless reactions. Chemical kinetics simulations of barrier reactions are calculated using transition state theory (TST) and unimolecular Rice-Ramsperger-Kassel-Marcus (RRKM) theories, while the kinetics of barrier reactions are estimated using the accurate classical method. Thermodynamics results indicate six stable conformers within 4 kcal mol− 1. To confirm the chemical stability of these conformers, the HOMO-LUMOs energy gaps were checked. The estimated chemical kinetics results indicated that TST and RRKM are comparable which gives confidence to our calculations. Branching ratio analysis shows the full dominance of the dehydration reaction R4 at T ≤ 650 K, with a minor contribution for the simple bond fission R9. At T ≥700 K, R9 became the main decomposition route, with a small contribution from R10 (~ 16% at 1700 K) and R8 (~ 9% at 1700 K) reactions.
Detection of deep and shallow defects in Concrete Filled Steel Tube Using Impact-Echo Method
Authors: Twite Franck Ngole , Fei Yao 
Published: December 2023

Abstract
Concrete Filled Steel Tube (CFST) is widely used in construction due to its good bearing performance, low cost and excellent structural seismic performance. Quality problems such as voids and debonding are often encounters in the process of pouring CFST. They significantly reduce the bearing capacity and ductility of specimens, and adversely affect the restraining effect of concrete. Such internal hidden defects cannot be visually identified. However, Non-destructive Testing Technique (NDT) is required. This paper employed the Impact Echo (IE) method to determine the location of defects in various types of concrete structures. Since the IE method was developed in the 1980s and used to test concrete structures, there have been little researches on defect detection in CFST. Therefore, this paper studies the square CFST specimens with defects located at different depths which are tested using the IE method. The Fast Fourier Transform (FFT) was employed to detect the location of defects by analyzing waveform and frequency spectrum. In addition, the CFST finite element model under more working conditions has been established, including internal defects of different depths and widths. The analysis of frequency distribution provides more details about the depth and location of the defects. A time-frequency analysis using Wavelet Transform was introduced in this study to assess the reliability of the IE method. According to the models carried out in this work it is demonstrated that IE method has been able to detect defects in Concrete Filled Steel Tube.