bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ultrasonographic approach to visualize the medial shoulder compartment and diagnose medial glenohumeral ligament and subscapularis lesions in dogs
Authors: Porter Ian , Miller Allison , Jennings Carol , Frye Christopher 
Published: October 2024

Abstract

OBJECTIVE
To provide a video tutorial on the diagnostic ultrasound approach to the medial compartment of the canine shoulder and provide comparisons of normal and pathological images with corresponding MRI.

ANIMALS
Dogs undergoing diagnostic ultrasound of the medial shoulder.

METHODS
The medial shoulder was positioned in flexion with external rotation to allow transducer access, clipped, and scrubbed with dilute chlorhexidine. A 2- to 14-MHz linear array probe with a footprint of 50 mm (V8 ultrasound system; Samsung) was used to visualize the medial glenohumeral ligament (MGL), subscapularis, and coracobrachialis with coupling gel, confirmed by cadaveric ultrasound-guided dye injection and dissection. Ultrasound and corresponding MRI were then used to contrast normal anatomy to a live sedated dog with clinical subscapularis tendinopathy and MGL desmopathy. Proton density–weighted MRI sequences (1.5T Vantage Orian; Canon) using a flex coil were able to identify all 3 structures and corresponded to ultrasound findings for normal and pathological anatomy.

RESULTS
Diagnostic ultrasound identified normal and abnormal structures of the medial shoulder (coracobrachialis, subscapularis, and MGL). All imaging correlated well to MRI.

CLINICAL RELEVANCE
Medial compartment disease of the shoulder is a well-described cause of canine lameness, but diagnosis has traditionally relied on MRI or arthroscopy. Prior ultrasound approaches did not distinguish MGL components, failed to consistently identify normal or surgically transected ligaments, and have not been studied in vivo. Our approach is different and can play an important role in diagnosing medial compartment lesions, as it possesses greater anatomical visualization than arthroscopy and is noninvasive, accomplished with sedation, and relatively accessible and affordable.
New Prediction Of Cracks Propagation In Repaired Steel Plate With Bonded Composite Patch At Cyclic Loading
Authors: Maachou Sofiane , Mechab Belaïd , Bouiadjra Bel Abbes Bachir , Salem Mokadem 
Published: October 2024

Abstract
This study presents a numerical prediction of the fatigue life of steel panels repaired by a composite patch. The effect of length cracks, the stress ratio R and properties of the patch is presented. The obtained results show that the bonded composite repair significantly reduces the stress intensity factors at the tip of repaired cracks. The results are in a good agreement with those in the literature. The Monte Carlo method is used to predict the distribution function governing crack propagation in fatigue analysis. In computing the failure probability of the structure, we consider the statistical uncertainty associated with key variables, along with the previously discussed model uncertainty. The results obtained highlight the considerable impact of variations in crack length and stress ratio on the distribution function. Notably, uncertainty in these parameters significantly amplifies the probability of structural failure in plates, thereby diminishing overall structural durability.
Analytical Analysis for Space Fractional Helmholtz Equations by Using The Hybrid Efficient Approach
Authors: Khan Adnan , Liaqat Muhammad Imran , Mushtaq Asma 
Published: October 2024

Abstract
The Helmholtz equation is an important differential equation. It has a wide range of uses in physics, including acoustics, electro-statics, optics, and quantum mechanics. In this article, a hybrid approach called the Shehu transform decomposition method (STDM) is implemented to solve space-fractional-order Helmholtz equations with initial boundary conditions. The fractional-order derivative is regarded in the Caputo sense. The solutions are provided as series, and then we use the Mittag-Leffler function to identify the exact solutions to the Helmholtz equations. The accuracy of the considered problem is examined graphically and numerically by the absolute, relative, and recurrence errors of the three problems. For different values of fractional-order derivatives, graphs are also developed. The results show that our approach can be a suitable alternative to the approximate methods that exist in the literature to solve fractional differential equations.
Mechanical Properties of 3D Printed PLA Scaffolds for Bone Regeneration
Authors: Kundreckaitė Paula , Šešok Andžela , Stonkus Rimantas , Gaidulis Gediminas , Romańczuk-Ruszuk Eliza , Pauk Jolanta 
Published: October 2024

Abstract
The growing interest in biodegradable scaffolds for bone regeneration created a need to investigate new materials suitable for scaffold formation. Poly(lactic acid) (PLA) is a polymer commonly used in biomedical engineering, e.g. in tissue engineering as a biodegradable material. However, the mechanical behavior of PLA along its degradation time is still not explored well. For this reason, the mechanical properties of PLA scaffolds affected by incubation in physiological medium needs to be investigated to show the potential of PLA to be used as a material for biodegradable scaffold formation. The purpose of this research is to determine the mechanical properties of PLA scaffolds before and after incubation, and to apply constitutive material models for further behavior prediction. Two sets of PLA scaffolds were printed by the 3D printer “Prusa i3 MK3S” and sterilized by ultraviolet light and ethanol solution. The first set of specimens was incubated in DMEM (Dulbecco’s Modified Eagle Medium) for 60, 120, and 180 days maintaining 36.5 °C temperature. The mechanical properties of the scaffolds were determined after performing the compression test in the “Mecmesin MultiTest 2.5-i” testing stand with a force applied at two different speed modes. The obtained data was curve fitted with the hyperelastic material models for a model suitability study. The second set of specimens was incubated in PBS (Phosphate Buffered Saline) for 20 weeks and used in a polymer degradation study. The obtained results show that the mechanical properties of PLA scaffolds do not decrease during incubation in physiological medium for a predicted new bone tissue formation period, though hydrolysis starts at the very beginning and increases with time. PLA as a material seems to be suitable for the use in bone tissue engineering as it allows to form biocompatible and biodegradable scaffolds with high mechanical strength, required for effective tissue formation.
Data analysis and modeling study of the relationship between physical activity and sleep disorder intervention for college students
Authors: Shen Delei , Ma Chao 
Published: October 2024

Abstract
Accompanied by the increasing prevalence of sleep disorders among students in colleges and universities, there is an urgent need for colleges and universities to provide a scientific basis and practical guidance for exercise intervention for sleep disorders among students. In this paper, in order to study the relationship between physical exercise and sleep disorder intervention, after analyzing the etiology and pathology of sleep disorders, we first surveyed students of a university in Guangzhou to analyze the differential characteristics of students’ sleep quality under different statistical variables. Then, a logistic linear regression model was established to analyze the influencing factors of college students’ sleep quality by taking the variables with statistically significant results in the one-way analysis as independent variables and college students’ sleep quality as dependent variables. Finally, college students with more serious sleep disorders in the university were subjected to a semester of walking, running, and soccer physical exercise to analyze the role of physical activity in influencing the intervention of sleep disorders in students. It was found that the PSQI scores of the walking group, running group, and soccer group before and after one semester of walking exercise decreased by 2.29, 3.16, and 3.18 points, respectively, and the scores of the rest of the items decreased to different degrees, which reflected the good effect of the physical exercise intervention on the intervention of sleep disorders. Explore the effects of physical exercise intervention on the quality of sleep among college students and provide practical suggestions for improving college students’ sleep quality through exercise.
Evaluating the Teaching Effectiveness of Business English Courses in Colleges and Universities Based on the DPSIR Model
Authors: Wang Ying 
Published: October 2024

Abstract
This paper takes the drive and pressure of teachers and students in the process of English teaching as the basis of evaluation, focuses on the state of the two in the process of teaching and the influence of teaching on teachers and students as well as the feedback of teachers and students on teaching, and constructs a framework for evaluating the effectiveness of business English teaching based on the model of “Drive, Pressure, State, Influence, Response”. After two rounds of expert consultation, the number of evaluation indicators was reduced from 34 to 21. Finally, the evaluation index system was constructed by combining the weight calculation of the hierarchical analysis method. The data show that A3 (state factors) > A1 (driving force factors) > A5 (response factors) > A2 (pressure factors) > A4 (influence factors), and the comprehensive evaluation score of the teaching effectiveness of business English courses in colleges and universities is 3.5944, which indicates that the evaluation grade of the teaching effectiveness of the university is located in the range between medium and good. This study aims to promote digital innovation and reform in the teaching of business English courses in colleges and universities by evaluating their teaching effects.
Semantic Accuracy and Cultural Adaptability in the English-Chinese Translation of Jane Eyre Based on Computational Linguistics and Natural Language Processing Techniques
Authors: Ye Chunbo 
Published: October 2024

Abstract
This paper takes Jane Eyre as an example to study the role of computational linguistics and natural language processing technology on the semantic accuracy and cultural adaptability of English-Chinese translation. We construct an interactive translation system of Jane Eyre, based on the interactive translation model design of computational linguistics and natural language processing technology, to support the application of these technologies in the English-Chinese translation of Jane Eyre. Context-association mapping, semantic retrieval, and semantic ontology structural feature construction methods are employed to evaluate semantic accuracy and cultural adaptability. We empirically analyze the semantic accuracy and cultural adaptability of the English-Chinese translation of Jane Eyre using text data from a Python web crawler. The results show that the semantic accuracy of the English-Chinese translation of Jane Eyre in this paper’s model is the highest compared to SAN (self-attention network) and RNN (recurrent neural network) translation models. Among the 200 students sampled, the translation result achieved a satisfaction rate of 71.5%. The work’s translation of literary sentences is more in line with the effect of Chinese expression, indicating excellent cultural adaptability.
Multi energy complementary optimization scheduling method for wind solar energy storage and charging integrated energy system
Authors: Miao Peng , Hongfei Zhao , Dezhi Dong , Hao Sun 
Published: October 2024

Abstract
IES (The Integrated Energy System), consisting of distributed wind and solar power generation and multiple types of loads for cooling, heating, and electrical systems, is an important application scenario in the current energy configuration. It is not possible to balance multiple objectives like economy, carbon emissions, and wind and solar energy curtailment. Furthermore, there are numerous equipment that have multiple energy flows, complex conversion processes, and multiple scheduling requirements. Therefore, multi-objective optimization and minute-level scheduling strategies are key technologies to improve the utilization efficiency of comprehensive energy systems. This article proposes a comprehensive method for optimizing and scheduling energy systems that is based on multi-objective optimization and multi-time scale decomposition. Firstly, a comprehensive energy system architecture for wind solar storage and charging was constructed, and its operational characteristics were analyzed. Then, a multi-objective optimization scheduling model was established, which comprehensively considered multiple objectives such as system operating cost, minimum carbon emissions, and minimum wind and solar curtailment rate. Through time scale decomposition, the optimization scheduling problem was transformed into multiple subproblems and solved separately. Finally, it was verified through a case study. The simulation results show that the constructed model reduces the total operating cost by 5%, the wind abandonment rate by 7%, and the carbon emissions by 5.6% compared to the system without energy storage and charging piles. This verifies the effectiveness of the constructed model, reduces the system operating cost, and reduces the impact on the environment; compared with the DA-P (Day Ahead Programming), the proposed optimization method reduced the system’s electricity purchase cost by 7.51%, increased renewable energy utilization by 11%, and reduced carbon emissions by 6.1%. This verifies the feasibility of the proposed method in reducing system operating costs, improving system environmental protection, and stabilizing the system.
An improved AO algorithm optimized PID rectification model for wind speed and wind pressure regulation in video cabinet of tobacco sorting machine
Authors: Lu Zhimin , Jiang Lin , Jiang Zhishan , Dong Zixin , Li Huajie , Zhang Wei 
Published: October 2024

Abstract
Sorting and removing impurities is the use of raw materials and light impurities suspended speed differences through the wind to separate the hemp, paper, plastic, and other light materials to remove impurities. Article to tobacco sorting machine video cabinet wind pressure control system principle as a guide, combined with the structure of the sorting and impurity removal machine and the principle of wind speed balance designed to balance the wind speed and wind pressure of the tobacco sorting machine. The control model of wind speed and pressure in the video cabinet system of the tobacco sorting machine is established, and the improved AO algorithm is used for the design of the overall PID controller and optimization of the PID controller’s setting parameters. The IAO algorithm optimizes the parameters of the PID setting controller with a steady state error within 3%, and the introduction of the IAO-PID controller can make the wind speed of the sorting machine system control from 16.4m/s to 11.1m/s within 17ms. When the system detects that the negative pressure of wire feeding changes sharply to about 1.12MPa within 20ms and exceeds the differential pressure start value of 0.9MPa set by the sorter system, the tobacco wire feeding anti-clogging function is activated. The PID controller optimized by the IAO algorithm can achieve precise regulation and control of wind speed and pressure of tobacco sorting machines, improving the sorting efficiency of tobacco production.
Analysis of Film and Television + Professional Cluster Resource Integration Model and Industry Development Dynamics
Authors: Zhang Huixin , Liu Zexi 
Published: October 2024

Abstract
This paper proposes a resource integration model for film and television + professional clusters and builds a corresponding digital platform to realize the effective integration of film and television professional resources. Using XML technology of different modalities of film and television professional resources, the association of film and television professional resources is defined, and a multi-objective integration scheduling algorithm is incorporated to optimize the integration speed to ensure the operational efficiency of the integration model. The integrated film and television professional resources are stored in the digitization platform, the wavelet transform technology is used to decompose the image signals, and the classifiers trained by the learning algorithm and the information entropy are used to complete the classification of film and television professional resources. After applying the design model and platform of this paper in the practical course teaching Film and Television Production for the 2022 undergraduate students majoring in Film and Television Studies at University X, the quality of film and television works created by the students improved by 2.12 and 1.64 in the dimensions of artistry and innovativeness compared with the pre-practice dimension, which showed a significant difference (P<0.05). H Pictures, on the other hand, predicts that in 2024, the cash income security, structural rationality, profitability sustainability, and growth sustainability metrics will improve to 0.6432, 0.9558, 0.00005, 0.4868, and 0.3767.
Computational model design for road to waterway transportation conversion efficiency improvement based on deep learning algorithm
Authors: Fang Zengli , Liang Yali , Di Shuai , Han Mingqi 
Published: October 2024

Abstract
Path planning for combined transportation can improve the irrationality in the carrier task so as to achieve the purpose of cost reduction and efficiency. This study takes economic efficiency as the starting point, takes the transportation time window as a constraint, and constructs the total cost objective function in the transportation process. The objective function of carbon emission in the transportation process is designed to address the green and low-carbon problem. The Ant colony algorithm is used to solve the multi-objective joint transportation model, aiming to obtain a green and efficient transportation path that meets the actual demand. The ACO algorithm shows good convergence performance in the transportation task from starting point O to ending point D. The ACO algorithm is capable of solving the transportation task from starting point O to ending point D after 130 iterations. After 130 iterations of the algorithm, the cost objective function value converged to 3427.8 RMB, and the carbon emission objective function value converged to 5534 kg after 90 iterations of the algorithm. Furthermore, the ACO algorithm’s Pareto solution set exhibits a uniform spatial distribution and excellent ductility and approximation effects. Assigning the same weights to cost, carbon emissions, and transportation time, the optimal solution 4 is obtained. The scheme from the starting point O via nodes 1, 2, and 6 to the end point D, through the joint transportation of road and waterway for 162 hours, a total of 5549 kg CO2, and the cost of transporting each ton of goods is 4093.9 yuan.
A Study of Artificial Intelligence-Driven Educational Intervention Strategies for Students with Special Educational Needs
Authors: Mo Dongxia , Mo Bohai 
Published: October 2024

Abstract
This paper first introduces the intervention path of artificial intelligence in special education. It then takes the deaf and hard-of-hearing people as the research object, adopts artificial intelligence technology, digitizes the speech signal, performs sound-rhyme syncopation, and constructs an interactive speech evaluation system using the HMM model as the evaluation basis. Finally, this paper discusses the effect of an interactive speech recognition model on special education interventions and describes the future development trend of combining artificial intelligence and special education. The results show that the subjects’ passive response to basic interactive speech in the baseline period showed a stable state, the interactive speech ability in the intervention period showed stable progress, and the subjects’ ability in the maintenance period remained at a high level. In the three periods, the posttest error rates of the experimental group testers on semantic recognition were 40%, 30%, and 10%, respectively, whereas the control group was 80%, 70%, and 65%, respectively, which shows that the semantic network training affected the improvement of the speech recognition ability of the 10 subjects. The mean values of the average error rate of the three stages of the experimental group were 7.53%, 2.44%, and 2.07%, and their average recognition times were 1566.73 seconds, 1051.30 seconds, and 463.55 seconds, respectively. The three-stage semantic recognition training significantly improves the subjects’ semantic recognition ability and reduces the recognition time. The integration of artificial intelligence and special education is critical for special education groups’ education and healing.
Research on deep learning-based action recognition and quantitative assessment method for sports skills
Authors: Wang Tao 
Published: October 2024

Abstract
The current sports training lacks data-based scientific training tools, and the use of action recognition technology to collect and mine sports data can effectively identify and evaluate sports skill actions. In this paper, a Transformer-based convolutional neural human action recognition network is proposed, which integrates the C3D convolutional network with the visual Transformer structure, using the 3D convolutional kernel for the extraction of time-domain features and using the Transformer network to accurately classify the feature sequences. The OpenPose algorithm is used to extract the essential points of the skeletal joints to estimate the human action posture. Through the dynamic time regularization algorithm, athletes’ sports movements are matched with standard movements to achieve a quantitative assessment of sports skill movements. The experimental results show that the method in this paper has better performance than similar neural network models in the task of sports action recognition and evaluation, and its class average accuracy mAP value and GFLOPs/V value are 0.9291 and 25.01, respectively, which substantially improves the recognition efficiency of sports skill actions.
Exploring strategies to improve the effectiveness of neurology ideology teaching team building using machine learning techniques
Authors: Wang Ying , Zhang Huakai , Li Tongtong , Yin Dongyan , Li Xiaoting 
Published: October 2024

Abstract
This paper takes the students of neurology specialty in a medical school as the research object and analyzes the current situation of its educational team construction. A machine learning algorithm based on weighted plain Bayes is used to construct an evaluation model, through which different weights are given to each index to explore the effectiveness enhancement strategy of neurology ideology and politics teaching team construction. Finally, the teaching performance and comprehensive ability of Civics and Politics were compared between the two groups of students to explore the effect of infiltrating the course Civics and Politics in neurology teaching. The results showed that 54.65% believed that teaching neuroscience ideology and politics in team construction should be improved as soon as possible. The mean value of “exerting the guiding role of professional teachers of Civics and Politics” was 23.76 points, which was also the furthest away from a perfect score, and was the focus of the subsequent team-building concern. The teaching performance and comprehensive ability of the students in the experimental group were better than that of the reference group (P<0.001), and the full penetration of the relevant elements of the course Civics in the teaching of clinical internships can transform the students’ ideological concepts and conscious behaviors.