bluuebunny/crossref_metadata_2025_split huggingface dataset:
Developing a Theoretically Informed Implementation Model for Telemedicine-Delivered Medication for Opioid Use Disorder: Qualitative Study With Key Informants
Authors: Tay Wee Teck Joseph , Gittins Rosalind , Zlatkute Giedre , Oteo Pérez Alberto , Galea-Singer Susanna , Baldacchino Alexander 
Published: September 2023

Background
Telemedicine-delivered medication for opioid use disorder (TMOUD) has become more prevalent during the COVID-19 pandemic, particularly in North America. This is considered a positive development as TMOUD has the potential to increase access to evidence-based treatment for a population heavily affected by the opioid crisis and consequent rising mortality and morbidity rates in relation to opioid use disorder. Despite the increase in the use of TMOUD, there are no established service- and process-focused models to guide the implementation of this intervention.

Objective
This study aims to develop a process- and service-focused implementation model in collaboration with key stakeholders and bring together peer-reviewed literature, practice-based knowledge, and expert opinions.

Methods
The simple rules for evidence translation in complex systems framework was applied to guide the development of a 6-step qualitative study. The steps were definition of the scope and objectives of the model, identification of evidence, stakeholder engagement, draft model development, key informant consultation, and final model specification.

Results
The final specification for the TMOUD implementation model incorporated key strategic priorities, service delivery prerequisites, service design elements, stakeholder identification and engagement, key process domains, and iterative cycles of evaluation and improvement.

Conclusions
Through stakeholder engagement and key informant consultation, we produced a process- and service-focused TMOUD implementation model. The model is modifiable to different contexts and settings while also in keeping with the current evidence base and national and international standards of high-quality opioid use disorder care.
Creating a LabVIEW Sub VI for the INA219 sensor for detecting extremely low-level electrical quantities
Authors: B. Khudhair Abdulrahman , Hussein Furat I. , Obeidi Muhannad Ahmed 
Published: September 2023

يتطلب نظام الحماية الكاثودية للتيار القسري (ICCP) قياسات كميات منخفضة للغاية من الخصائص الكهربائية. استخدم العمل التجريبي الحالي وحدة مستشعر Adafruit INA219 للحصول على قيم الجهد والتيار وقدرة الحمل الافتراضي الذي يستهلك طاقة منخفضة جدًا تحاكي نظام ICCP. تكمن المشكلة الرئيسية في تكييف مستشعر INA219 مع بيئة LabVIEW بسبب عدم وجود مكتبة المستشعر هذا. تم تخصيص هذا العمل لتكييف وحدة استشعار Adafruit INA219 في بيئة LabVIEW من خلال إنشاء Sub VI وتطويره واختباره بنجاح ليكون جاهزًا للعمل في نظام ICCP. تمت مراقبة إخراج المستشعر باستخدام متحكم Arduino Uno ومجموعة أدوات البرامج الثابتة LabVIEW Linx. تم تطبيق تقنية تعديل عرض النبض (Pulse Width Modulation (PWM) ، والتي تتراوح من 0٪ إلى 100٪ ، بواسطة Arduino لتزويد متحكم الجهد l298N من أجل تنظيم إدخال الجهد للحمل. تم استخدام مرشح متوسط متحرك لقياس متوسط جهد التموج ، وتم استخدام مرشح متوسط لتثبيت القراءات. تقوم دائرة المرشح بتنعيم جهد PWM قبل تزويده الى الحمل. أظهرت النتائج من بيئة MATLAB-Simulink أن تردد القطع عند 2.33 هرتز ، و جهد التموج من اعلى قيمة الى اقل قيمة كان 41.1 مللي فولت وزمن استقرار قدره 0.157 ثانية. أظهرت النتائج التي تمت معايرتها لمستشعر وحدة INA219 عدم دقة الجهد المطلق بحوالي 2.3٪ على النطاق الكامل. بالإضافة إلى ذلك ، كانت قيمة الخطأ المطلق في التيار بنسبة 2.2٪ عند 25 مللي أمبير ويزداد تدريجيا بازدياد قيمة التيار حيث قيمة الخطأ المطلق التيار إلى 7٪ عند 43 مللي أمبير ، بينما كانت أعلى قيمة خطأ مطلق لمقياس القدرة على النطاق الكامل عند 5.8٪.
Fatores associados ao início precoce do aleitamento materno em crianças menores de 2 anos
Authors: Velho Caroline Farias , Saldan Paula Chuproski 
Published: September 2023

O aleitamento materno logo após o parto está associado à redução da mortalidade neonatal e infantil e à maior duração do aleitamento materno exclusivo. O objetivo deste estudo foi analisar os fatores associados ao início precoce do aleitamento materno em crianças menores de 2 anos de idade. Este estudo transversal foi conduzido durante a Campanha Nacional de Vacinação contra Poliomielite de 2012, em Guarapuava (PR), por meio de aplicação de questionário estruturado. Para identificação dos fatores, foram construídos modelos de regressão de Poisson, obtendo-se razões de prevalências em modelos bivariados e múltiplo. Mantiveram-se no modelo final as variáveis que apresentaram p < 0,05. A prevalência do aleitamento materno precoce foi de 78,54%, e os fatores associados ao não início do aleitamento materno precoce foram: criança do sexo masculino, baixo peso ao nascer, não nascer em hospital/maternidade e parto cesáreo. Idade materna entre 20 e 34 anos foi fator de proteção para o início precoce do aleitamento materno. É importante analisar os fatores de cada município para que, assim, sejam propostas ações efetivas direcionadas a serviços e profissionais de saúde e às mães.
Advance oxidation processes of Rhodamine B under O3/UV using spent bleaching earth-ZnO composite: Performance in kinetics
Authors: Yulikasari Andriyan , Nurhayati Ervin , Xaverius Fernando Cornelio Fransiscus , Susanti Diah 
Published: September 2023

Spent bleaching earth and ZnO composite (SBE/ZnO) was prepared as the catalyst for the advanced oxidation processes (AOPs) of rhodamine B (RB) under O3/UV. The photocatalytic ozonation process of RB was conducted at an ozone flow rate of 1 L/min by adjusting the variation of initial RB concentration, catalyst dosage, and reaction time. The RB removal efficiency of 96.7% was reached within 36 min at optimal operational conditions (initial concentration of 100 mg/L and catalyst dosage of 1.5 g). The kinetical analysis at this condition showed that the photocatalytic ozonation process of RB followed a pseudo-first-order reaction with a rate constant of 0.0975 min-1. Meanwhile, the effect of operational variables was evaluated using response surface methodology (RSM) and resulted in an optimized model for RB Removal following equation: RB Removal = 84.95 - 6.24A + 5.81B + 22.45C + 3.07AB + 13.14AC - 6.72BC + 0.1174A2 + 7.86B2 - 8.90C2, where A is the initial concentration of RB, B is catalyst dose and C is reaction time, with a high coefficient of determination R2 = 0.9432.
INDONESIAN EFL POSTGRADUATE STUDENTS' PERCEPTION TOWARD ACCENT IN LISTENING COMPREHENSION
Authors: Maharani Reynita Adlina 
Published: September 2023

Listening comprehension has been one of the most challenging proficiency for EFL learners in Indonesia, including for postgraduate students. In this research, the researcher aims to investigate postgraduate students’ perception of accents within listening comprehension. Furthermore, this research employed a mixed method and an online open-ended questionnaire as the instrument. 33 Indonesian participants who attended Indonesian and Indian universities were willing to join the research. Moreover, the Questionnaire consisted of 11 questions that needed to be answered by the participants. In addition, the researcher analyzed the data by chart and percentage to show the difference between the participants’ responses. The result revealed that 93.9% of postgraduate students were primarily familiar with the American accent rather than the British accent throughout their education. It is because most of the schools in Indonesia adopt an American accent for their English course.Furthermore, 87.9% of the participants used an American accent when speaking in English, and 63.6% sometimes had difficulty understanding Americans. Additionally, 66.7% of the participants stated that the speaker's speed was the significant problem they had in listening comprehension. However, all of the participants found that accent also had the utmost role in listening comprehension because the accent they listened to correlated to their understanding of vocabulary being spoken by the speaker in the listening comprehension audio. Thus, based on the research, Indonesian postgraduate students perceived accent as pivotal in listening comprehension. The speaker's accent on the listening comprehension audio determined how well they could do the listening comprehension test.
Deep Learning Based Sports Video Classification Research
Authors: Li Wenming 
Published: September 2023

Abstract
In this paper, we study sports video classification technology based on a deep learning algorithm, using a convolutional neural network and deep learning gradient descent algorithm as the main research method to classify and regress the image features of sports video output. A sports video classification model is built to clarify the full research idea, and the results of extracted data are verified one by one with OTB target tracking dataset and specifically analyzed the accuracy and check-all rate of various types of videos, and then conclusions are drawn. The data show that the accuracy of the sports video classification test set with deep learning algorithm reaches 98.3%, and the detection rate of tennis, badminton, and table tennis all reach 92%. Soccer and basketball have a lower accuracy rate but can reach 83%. The accuracy rate of capturing detailed actions is 97.6%. The sports video classification based on deep learning accurately and effectively captures faces and actions accurately, which is important for viewers to find interesting sports video categories quickly.
Design of a perceptron model-based physical fitness index monitoring system for sports training
Authors: Li Wenming 
Published: September 2023

Abstract
The purpose of designing a sports training fitness index monitoring system is to grasp better the physical performance data of athletes in the training process to ensure training safety. In this paper, the principle of multilayer perceptron is explained based on the perceptron model, the optimal loss function of multilayer perceptron is solved by using the activation function and forward propagation algorithm, the sensor data collection module is constructed, and the physical fitness index monitoring system for sports training is built by this method. To verify the feasibility of the detection system in this paper, experimental analysis was conducted from three aspects: the distribution of physical fitness index monitoring information density, physical fitness index data and monitoring data accuracy. The index monitoring density distribution was between 0.11 and 2.09 from the monitoring information density. Regarding physical performance indicators, the average values of maximum oxygen uptake, heart rate, relative energy metabolism level, and exercise intensity were 41.02, 121.58, and 11.84, respectively. From the accuracy of indicator monitoring data, the accuracy of the system in this paper was 93.63%, which was 21.57 and 11.03 percentage points higher than that of GAN and MCNN algorithms, respectively. The physical fitness index monitoring system constructed based on the perceptron model can effectively realize the monitoring of physical fitness indexes, help trainers master the training rhythm, and improve the safety of sports training.
The evolution from information-based HRM to big data HRM
Authors: Zhu Rong 
Published: September 2023

Abstract
The current research on big data human resource management is increasing, and this paper uses big data technology to analyze the research on the evolution from information-based human resource management to big data human resource management. Firstly, the idea of the evolution of enterprise human resource management is proposed by analyzing the current situation of human resource management and data decision making, combined with the requirements of the development of the big data era. Then the HR data model system is constructed by drawing on the world’s successful cases, and there are six modules in the system, and each module has the corresponding index analysis that needs to be solved. Finally, the empirical analysis of the company’s employee turnover using the gray correlation model, based on the data of the characteristics of the company’s leavers, set 12 evaluation indicators to facilitate the research analysis. The scores of environmental variables are in third place, with an average score of 0.4381, which indicates that personal environmental factors do not greatly influence employee turnover. The score of the individual variable is in second place with an average score of 0.4532, which indicates that the company has formed a better learning culture and employees are willing to put more effort into their work, and individual factors are not the most important reason for employees to leave. In this study, the mastery, understanding and, use of data have turned into a core driving force for companies to keep moving forward, and the guiding document also places new demands on the top management within the companies involved.
Analysis of the Expression of Buddhist Monks’ Literary Activities in the Early Sui and Tang Periods Based on Fuzzy Mathematical Models
Authors: Yang Jianxiao , Wang Chuan 
Published: September 2023

Abstract
Buddhist culture was widely spread in Chang’an during the Sui and Tang dynasties, and as the center of literary development in the country at that time, literary works in Chang’an were influenced by Buddhist literary activities from form to content. This paper first analyzes the current situation of Buddhist literary activities in the Sui and Tang dynasties, applies fuzzy mathematical theory to the analysis of literary activities based on the research of domestic and foreign experts and scholars on the manifestation of literary activities, and establishes an analysis model of literary activities based on fuzzy mathematical methods. Secondly, Buddhist thought is fitted through the closeness of a fuzzy mathematical model. The weights among the influencing factors of Buddhist literary expressions were determined through characteristic factors and affiliation degrees. The experimental results show that the deviation rate of the expression form analysis of Buddhist monks’ literary activities based on the fuzzy mathematical model in the early Sui and Tang dynasties ranges from 5% to 10%, but the deviation rate of the final overall estimation accuracy does not exceed 5%, which verifies that the model can be applied to the expression form analysis of literary activities. The fuzzy mathematical model proposed in this paper is more accurate than the traditional method of literary activity analysis and yields the highest degree of closeness, which is a guide to the study of traditional cultural transmission and integration and provides a new way of thinking for the transmission of traditional culture.
A study on the application of using big data information technology to implement physics laboratory courses in universities
Authors: Tao Guanqi , Wang Yinshu , Fan Yina 
Published: September 2023

Abstract
In today’s fast development of big data information technology, the traditional physics experiment method is difficult to adapt to the new curriculum reform physics experiment course objectives. The key topic of concern today is how to use big data information technology and physics experiment course integration for teaching. This study mainly uses the fuzzy comprehensive evaluation algorithm in big data information technology to study and analyze the physics laboratory courses in colleges and universities. Firstly, according to the principles and methods of the fuzzy comprehensive evaluation method, the model of a fuzzy comprehensive evaluation of university physics laboratory teaching is established, and the index system and evaluation level criteria of university physics laboratory teaching are established. Then the weights of each factor of the index system were determined using fuzzy comprehensive evaluation, and the evaluation results combining qualitative and quantitative were obtained by processing the data. Finally, the results were obtained regarding teaching attitude, teaching content, and teaching effect: the weights of good 55%, 64% and 38% performed better than other evaluation grades. Regarding teaching implementation: 54% weight of good evaluation is greater than other evaluation grades. From the evaluation grade, the average weight of a good grade is 48.25% greater than the other three categories, and the weight performance is better. This study is conducive to improving the experimental application ability of college students and thus has important historical significance for the development of physics in China.
Application of economic model optimization algorithm for international trade based on big data technology
Authors: Chen Yali , Xiang Zheng 
Published: September 2023

Abstract
The advent of the era of big data has posed greater challenges to the economic model of international trade and opportunities for international trade. In this paper, from the application of big data in international trade, we study the SVM-based big data clustering analysis method for international trade and propose to optimize the objective function in the iterative process by using the individual fitness function of the chicken flock optimization algorithm for the problem that SVM is easy to fall into the optimal local solution. Then, the steps of international trade big data analysis by constructing CSO-SVM are used to forecast international port throughput, international trade exports, and imports. The average absolute error rate of the trained CSO-SVM model for the prediction of international port throughput decreased to 6.19%, and the accuracy of the prediction of international trade export volume and export price reached 86.86% and 87.83%, respectively, and the accuracy of the prediction of international trade import demand and import price reached 86.71% and 87.07%, respectively. During the test, CSO-SVM has higher prediction performance than other models. The analysis based on big data can better quantify the challenges faced by international trade, optimize international logistics scheduling, and improve import and export planning.
Synergistic study of cellulose enzymatic factors and cellulase adsorption properties under bioinformatics
Authors: Yin Liwei , Yang Chuncheng , Zhou Duoqi , Huang Zhu , Zhu Yu , Wu Lin 
Published: September 2023

Abstract
Cellulose enzymatic saccharification is a key link in converting lignocellulose to fuel ethanol via a sugar platform. In this paper, the maximum information coefficient (MIC) algorithm is proposed to detect linear correlations and nonlinear correlations between bioinformatics variables from the application of bioinformatics. Meanwhile, to address the problems of excessive grid division and low statistical efficacy of MIC algorithm, BackMIC, an optimization algorithm using quiz control number of segments, is proposed to terminate the network search using the chi-square test. Then, cellulase hydrolysis and adsorption experiments were designed and performed, and the experimental data were analyzed based on the BackMIC algorithm. The optimum activity temperature of different cellulases was around 50°C, while the hydrolysis rate of cellulases of different treated raw materials increased and then decreased with the increase of temperature, and basically, the maximum was achieved in the temperature range of 50~55°C. In the pH test, the optimum temperature of cellulase hydrolysis was concentrated at 4.4~4.5. In the cellulase adsorption experiments, the enzymatic activity of steam-popped wheatgrass was adsorbed in the following order: FPA> C1> CMCase> β-Case. The study of cellulase hydrolysis based on bioinformatics reveals the synergistic relationship between cellulase hydrolysis and adsorbed properties, which provides a theoretical basis for reducing the ineffective adsorption of cellulose and the development of enzymatic strengthening technology. The theoretical basis for reducing the ineffective adsorption of cellulose and the development of enzymatic enhancement technology can help reduce the cost of lignocellulose enzymatic digestion.
Financial risk assessment management of state-owned enterprises based on cloud accounting in the era of big data
Authors: Zou Xiang 
Published: September 2023

Abstract
To solve the financial risk problem of enterprise financing difficulties and large financing amounts in the era of big data, this paper constructs a financial risk assessment model and evaluates the indexes of enterprise financial risk by combining it with cloud accounting products. Firstly, we assign and determine the weights, use the evidence theory to develop the enterprise financial risk evaluation, and determine the weights of each risk evaluation index. Secondly, we set up a fuzzy evaluation language set, calculate the maximum value of the fuzzy rubric affiliation function for the risk indicators of state-owned enterprises under cloud accounting, pre-process the obtained data, determine the specific indicator weights with the help of fuzzy hierarchical analysis, and carry out consistency tests on them. Finally, the relative importance of each indicator is calculated among the model factors to obtain the overall risk score of cloud accounting enterprise finance. The experimental results show that the risk level measured according to the steps of the cloud accounting risk assessment system, the data confidentiality risk score is 76.14, the cloud accounting product risk is 85.96, the service risk is 72.88, and only one item is higher risk. This shows that the use of cloud accounting financial risk control measures can improve the quality of financial risk management of enterprises.
Analysis of punitive damages in the context of economic law based on the singular value analysis method
Authors: Geng Qiaoying 
Published: September 2023

Abstract
Based on some problems in the punitive damages system that are not conducive to economic development, we take the perspective of economic law to play a positive role in promoting the further improvement of punitive damages. In this paper, the rank of punitive damages is first defined by the singular value analysis algorithm, and the function is set up as a diagonal matrix composed of different vectors, and the square root of the decomposition eigenvalue is the singular value of the matrix. Then the matrix nodes are calculated, and each node is divided into two column blocks and predicted, and the number of nodes is input for the eigenvalue decomposition. The matrix regression coefficients of the independent variables are examined after the decomposition is performed, and the fit of the singular value analysis algorithm in dealing with the compensation problem is derived from this coefficient. The experimental results from a region of the United States show that among 100 large punitive damages cases exceeding $100 million between January 2009 and December 2018, the number of cases of punitive damages in 2010, 2011, and 2013 was only one, and the highest number reached 12 in 2018 illustrating the accuracy of singular value analysis in locating punitive damages, which helps to promote the construction and development of the punitive compensation system and contribute to the stable development of the social economy.