bluuebunny/crossref_metadata_2025 huggingface dataset:
Using Healthcare Resources Wisely: A Predictive Support System Regarding the Severity of Patient Falls
Authors: Wang Hsi-Hao , Huang Chun-Che , Talley Paul C. , Kuo Kuang-Ming
Published: August 2022

Background. An injurious fall is one of the main indicators of care quality in healthcare facilities. Despite several fall screen tools being widely used to evaluate a patient’s fall risk, they are frequently unable to reveal the severity level of patient falls. The purpose of this study is to build a practical system useful to predict the severity level of in-hospital falls. This practice is done in order to better allocate limited healthcare resources and to improve overall patient safety. Methods. Four hundred and forty-six patients who experienced fall events at a large Taiwanese hospital were referenced. Eight predictors were used to ascertain the severity of patient falls solely based on the above study population. Multinomial logistic regression, Naïve Bayes, random forest, support vector machine, eXtreme gradient boosting, deep learning, and ensemble learning were adopted to establish predictive models. Accuracy, F1 score, precision, and recall were utilized to assess the models’ performance. Results. Compared to other learners, random forest exhibited satisfying predictive performance in terms of all metrics (accuracy: 0.844, F1 score: 0.850, precision: 0.839, and recall: 0.875 for the test dataset), and it was adopted as the base learner for a severity-level predictive system which is web-based. Furthermore, age, ability of independent activity, patient sources, use of assistive devices, and fall history within the past 12 months were deemed the top five important risk factors for evaluating fall severity. Conclusions. The application of machine learning techniques for predicting the severity level of patient falls may result in some benefits to monitor fall severity and to better allocate limited healthcare resources.
Toll‐Like Receptor 4 Exacerbates Mycoplasma pneumoniaevia Promoting Transcription Factor EB‐Mediated Autophagy
Authors: Liu Yan , Li Jing , Lu Xianfeng , Zhen Shuangping , Huo Jing
Published: August 2022

Mycoplasma pneumoniae (M. pneumoniae) is the most common cause of community‐acquired pneumonia. Toll‐like receptors (TLRs) play an essential role in pneumonia. The purpose of this study was to investigate the roles of TLR4 in M. pneumoniae. Mice were administrated with 100 μl (1 × 107 ccu/ml) of M. pneumoniae. HE staining was applied for histological analysis. The protein expression was determined by western blot. The cytokine level was detected by ELISA. The results showed that TLR4‐deficient mice were protected from M. pneumoniae. However, downregulation of TLR4 inhibited inflammatory response and autophagy. Moreover, transcription factor EB (TFEB) participated in M. pneumoniae‐induced inflammatory response and autophagy, while knockdown of TLR4 downregulated TFEB and its nuclear translocation.
Physical Therapy for at Least 6 Months Improves Motor Symptoms in Parkinson’s Patients: A Meta-Analysis
Authors: Ji Xiaotian , Lu Danian , Yang Qinglan , Xiao Linting , Wang Jing , Wang Gaiqing
Published: August 2022

Objective. Long-term physical therapy helps to improve the motor symptoms of patients with Parkinson’s disease, but the effectiveness is not clear. The purpose of this study was to evaluate the effect of long-term physical therapy on improving motor symptoms or daily activities in Parkinson’s patients with drug use or discontinuation, as well as its impact on drug treatment dose. A subgroup analysis was conducted on different treatment methods to determine the most effective treatment method. Methods. The researchers independently searched databases, including PubMed, Medline, Embase, Ovid, Cochrane Library, and ISI Web of science. The search deadline was June 2022. A randomized controlled trial was conducted on Parkinson’s disease patients with HY stages 1-3 who received continuous physical therapy for 6 months or more. Systematic evaluation and meta-analysis were carried out by using common clinical evaluation indicators, namely, MDS-UPDRS exercise score, daily activity (ADL) score, or LED dose. The quality of the literature was assessed using the modified Jadad scale of Cochrane’s bias risk tool. Results. A total of 523 Parkinson’s disease patients with HY stages of 1-3 were included in the study. The results showed that long-term physical therapy could improve patients’ motor symptoms with combined antiparkinsonian drugs (

Z
=
2.61

and

P
=
0.009

) and had a significant positive effect on the motor symptoms of patients with discontinued antiparkinsonian drugs (

Z
=
2.73

and

P
=
0.006

). Meanwhile, it could reduce the LED dose of patients with Parkinson’s disease. The difference was statistically significant (

Z
=
2.58

and

P
=
0.010

). Conclusion. The results of this study indicated that physical therapy for at least 6 months or longer for patients with mild to moderate Parkinson’s HY could effectively improve the motor symptoms of Parkinson’s patients, whether or not combined with antiparkinson drugs. Meanwhile, long-term physical therapy reduced the LED dose of patients treated with drugs compared with patients in the control group who received short-term physical therapy, other types of intervention group, or no treatment.
A Decision Support Framework for Curriculum Planning in Undergraduate Supply Chain Management Program: An Integrated Approach
Authors: Tao Min , Jiang Jinde , Wang Xiong , Zhou Jiao , Xie Jichen
Published: August 2022

Curriculum planning is an important but complex and challenging decision-making problem at universities. There is a growing interest in curriculum planning problem. However, the body of research on curriculum planning process using analytical methods is still small. Additionally, prior research focused on planning of an individual curriculum or making study plan for students. Curriculum planning at the program level is an under-researched topic. A robust model has not been constructed to address curriculum selection and credit allocation problems simultaneously. To help educational leaders make the most appropriate curriculum plan corresponding to their goals with the highest level of utility achieved, this study presents a new decision support framework with integrated approach. In the proposed framework, based on the competency weights derived from the analytical hierarchy process method, the importance of each potential curriculum is evaluated using the fuzzy comprehensive evaluation method. An exploratory estimation is made to calculate the contribution values of competency development by each curriculum taught at different levels. Finally, multichoice goal programming with utility function determines the curriculum to be provided and corresponding credits to minimize the aggregate deviations from predefined goals with multiple aspirations. An application to curriculum planning of an undergraduate supply chain management program is presented to validate the flexibility and practicality of the proposed approach. The implications of the study are not restricted to curriculum planning of supply chain management program.
A Waste Recycling Method Based on the Life Cycle Analysis of Products
Authors: Yu Longfei , Zhu Shifan
Published: August 2022

Life Cycle Assessment (LCA) is a method for quantifying the effects of different actions to make evaluations and decisions easier. There are various product waste management solutions, but determining which one is best in terms of environmental effects can be difficult. In this regard, recycling is frequently regarded as environmentally beneficial, as it involves the gathering and processing of waste into new products. Inspired by the necessity of recycling, this study proposes a waste recycling system based on product life cycle evaluation to increase the use rate of waste products. The suggested system built the product life cycle workflow using Electronic Product Cycle (EPC) to make the product’s complete life cycle scalable and unified. In addition, the proposed system uses a big data normalization approach to preprocess product life cycle data and extract the total weight of product life cycle assessment indicators. Furthermore, the suggested method seeks to demonstrate the usefulness of LCA as a waste recycling tool during the construction of a waste management framework and to identify a gap in research by designing a better framework. The simulation results show that compared with the designed PLA-based waste recycling system, the system has higher reliability, lower LCA complexity, less impact on throughput, and lower cost, meeting the economics of waste disposal requirements.
Microstructure Effects of the Electrical Discharge Machining Drill on Aerospace Super Alloys
Authors: Copher Garner , Harimkar Sandip , Rouser Kurt , McCain Connor , Velasco Daniel , Price Tanner , Schinzler Trey
Published: August 2022

This paper presents an analysis of the parent material damage and electrode wear of a handheld electrical discharge machining (EDM) drill. The motivation of this study is to investigate the material effects of EDM drilling on aerospace alloys at a microstructure level. The specific effects that are being investigated are heat affected zones (HAZ), grain structure changes, material composition changes, and fracturing. A secondary goal of this study is to determine if there is potential for electrode wear prediction models for supply chain management. The study consisted of making cuts into both Inconel and titanium test specimens while varying cut depths and electrode diameters. The results of the study found that the electrode wear while cutting Inconel showed some amount of predictable behavior. On the contrary, the titanium specimens did not indicate a predictable behavior and did not appear to follow an intuitive trend. Interestingly, when drilling into titanium, the active electrode increased in length, indicating that the titanium is being deposited onto the electrode. The EDM drill caused notable damage to the parent material, including a substantial recast layer of up to approximately 150 μm in thickness, incorporation of electrode material into the parent material through the recast layer, and formation of microcracks that can cross the recast layer/parent material interface. These noted characteristics can have an impact on material performance and longevity due to the nonuniform nature of the damage and the introduction of microcracks crossing from the recast layer into the parent material.
Analysis of Mobile Learning Model and Design of Mobile English Platform Based on Service-Oriented Architecture
Authors: Luo Yana
Published: August 2022

On the basis of extensive reading of domestic and foreign literature and full investigation, this paper studies the theories related to mobile learning. Based on these theories, the resource service model of cloud education resources and the mode of mobile English learning are designed, which forms the problem of identification and confirmation with practitioners. Design models and solutions produce new theories of mobile learning. On the system architecture, the system is divided into four layers to improve the flexibility and scalability of system services. Considering the security of system services, a set of session caching system is designed and proposes a service interface encryption scheme based on Sessionid, Timestamp, and public Key. Finally, this paper realizes the mobile English client and background management platform. English mobile platform is used widely for teachers and students on campus, so the pressure-bearing capacity of the system service is tested and verified. The results show that the running stability of this system can reach about 96.03%. Its bearing capacity is strong, reaching the expected goal, which can provide some reference for related research.
Buffett’s Value Investment Theory Based on Improved DCF Model
Authors: Gai Junyue
Published: August 2022

With the development of global economy, the investment theory of capital market needs to be further developed in order to provide investors with various references in the process of value investment. Value theory is very important for international investors. Since Graham put forward the theory of value investment, he has always emphasized the importance of discounted cash flow model (DCF model) in investment evaluation. Therefore, the DCF model has great influence on investment. In order to provide some domestic investors with value-added analysis methods when investing, we will investigate the practical theory of improving the DCF model in extreme environment. Based on the theory of value investment, time series analysis is introduced to improve the DCF model. The improved DCF model can estimate the original value of an enterprise by combining the factors that affect the change of enterprise value. In the research of securities investment, considering that the existing DCF model based on the American capital market has some shortcomings in domestic capital market, it needs to be improved. To forecast the future cash flow, the time series analysis method should be used instead of the sales ratio method. American investor Warren Buffett’s philosophy and practice of value investment have been paid attention to and studied by the world. Value theory is a series of famous theories put forward by Graham and applied and developed by Buffett. By combining the improved DCF model with Buffett’s personal business experience, this paper analyzes and summarizes the relevant contents of Buffett’s value investment theory based on the improved DCF model and puts forward some suggestions worthy of reference for Chinese investors.
Prediction and Screening Model for Products Based on Fusion Regression and XGBoost Classification
Authors: Wu Jiaju , Kong Linggang , Yi Ming , Chen Qiuxian , Cheng Zheng , Zuo Hongfu , Yang Yonghui
Published: August 2022

Performance prediction based on candidates and screening based on predicted performance value are the core of product development. For example, the performance prediction and screening of equipment components and parts are an important guarantee for the reliability of equipment products. The prediction and screening of drug bioactivity value and performance are the keys to pharmaceutical product development. The main reasons for the failure of pharmaceutical discovery are the low bioactivity of the candidate compounds and the deficiencies in their efficacy and safety, which are related to the absorption, distribution, metabolism, excretion, and toxicity (ADMET) of the compounds. Therefore, it is very necessary to quickly and effectively perform systematic bioactivity value prediction and ADMET property evaluation for candidate compounds in the early stage of drug discovery. In this paper, a data-driven pharmaceutical products screening prediction model is proposed to screen drug candidates with higher bioactivity value and better ADMET properties. First, a quantitative prediction method for bioactivity value is proposed using the fusion regression of LGBM and neural network based on backpropagation (BP-NN). Then, the ADMET properties prediction method is proposed using XGBoost. According to the predicted bioactivity value and ADMET properties, the BVAP method is defined to screen the drug candidates. And the screening model is validated on the dataset of antagonized Erα active compounds, in which the mean square error (MSE) of fusion regression is 1.1496, the XGBoost prediction accuracy of ADMET properties are 94.0% for Caco-2, 95.7% for CYP3A4, 89.4% for HERG, 88.6% for hob, and 96.2% for Mn. Compared with the commonly used methods for ADMET properties such as SVM, RF, KNN, LDA, and NB, the XGBoost in this paper has the highest prediction accuracy and AUC value, which has better guiding significance and can help screen pharmaceutical product candidates with good bioactivity, pharmacokinetic properties, and safety.
[Retracted] The Relationship between Traditional Music in Xinjiang and the Geographical Environment of the Gobi Desert
Authors: Ma Shuhao
Published: August 2022

The natural environment and geographical environment provide the possibility for human survival and development and are also the premise of the formation of music culture. When studying the style characteristics and cultural types of music, more comprehensive and correct conclusions can be drawn only when considering various regional factors such as geography and topographic environment. If we want to explore the music of Xinjiang, we must understand the regional culture. The special geographical location of the Silk Road gives Xinjiang a foreign style compatible with Chinese and Western cultures. At the same time, because of the geographical environment of the Gobi Desert, the music style of Xinjiang is unique. This paper explores the relationship between the traditional music of Xinjiang and the Gobi desert, through the investigation and study of Xinjiang and various musical styles, which have certain reference significance for the study of the Chinese traditional culture.
Adolescent Identity Search Algorithm Based on Fast Search and Balance Optimization for Numerical and Engineering Design Problems
Authors: Wang Wentao , Liu Hao , He Quanqin
Published: August 2022

This paper proposed a fast convergence and balanced adolescent identity search algorithm (FCBAISA) for numerical and engineering design problems. The main contributions are as follows. Firstly, a hierarchical optimization strategy is proposed to balance the exploration and exploitation better. Secondly, a fast search strategy is proposed to avoid the local optimization and improve the accuracy of the algorithm; that is, the current optimal solution combines with the random disturbance of Brownian motion to guide other adolescents. Thirdly, the Chebyshev functional-link network (CFLN) is improved by recursive least squares estimation (RSLE), so as to find the optimal solution more effectively. Fourthly, the terminal bounce strategy is designed to avoid the algorithm falling into local optimization in the later stage of iteration. Fifthly, FCBAISA and comparison algorithms are tested by CEC2017 and CEC2022 benchmark functions, and the practical engineering problems are solved by algorithms above. The results show that FCBAISA is superior to other algorithms in all aspects and has high precision, fast convergence speed, and excellent performance.
“Fed-DRL”: A Timeliness Optimization Method for Dynamic Data Acquisition System Based on Mobile Edge Computing
Authors: Zheng Huiji , Yu Sicong , Qiu Xinyuan , Cui Xiaolong , Zhu Li
Published: August 2022

Age of Information (AoI) is a metric to describe the timeliness of a system proposed in recent years. It measures the freshness of the latest received data from the perspective of the target node in the system. This work studies a kind of dynamic data acquisition system for urban security that can update and control the situation of urban environmental security by collecting environmental data. The collected data packets need to be uploaded to the cloud center in time for data update, which has high requirements on the timeliness of the system and freshness of data. However, due to the limited computing capacity of mobile terminals and the pressure of bandwidth for data transmission, problems such as high data execution delay and transmission interruption are caused. Emerging mobile edge computing (MEC), a new model of computing that extends cloud computing capabilities to the edge network, promises to solve these problems. This work focuses on the timeliness of the system, as measured by the average AoI across all mobile terminals. First, a timeliness optimization model is defined, and a multi-agent deep reinforcement learning (DRL) algorithm combined with an attention mechanism is proposed to carry out computing offloading and resource allocation through the continuous interaction between agent and environment; then, in order to improve algorithm performance and data security, the federated learning mode is proposed to train agents; finally, the proposed algorithm is compared with other main baseline algorithms based on deep reinforcement learning. The simulation results show that the proposed algorithm not only outperforms other algorithms in optimizing system timeliness, but also improves the stability of training.
[Retracted] Analysis on the Development and Influence of National Fitness Environment on Youth Basketball Coordination and Mental Health
Authors: Lu Pengfei , Su Yajuan
Published: August 2022

In order to improve the basketball theory and provide theoretical and intellectual support for the scientific, mental health, and sustainable development of basketball, we propose to take the development dynamic mechanism of juvenile basketball as the research object and make a systematic and in‐depth study on the dynamic mechanism, the cultivation of Chinese and foreign juvenile basketball reserve talents, and the dynamic dilemma and influencing factors of juvenile campus basketball development by using the methods of literature, questionnaire, and expert interview. A method of cultivating the ring tone of juvenile basketball is proposed. This method is based on Chan algorithm. When the target is close to each base station, the first estimation also needs an initial value to solve the initial solution estimation matrix. The method is also based on multivariate Taylor algorithm, taking into account the measured distance between the targets to be measured, so it will get some useful information, which will improve the positioning accuracy. The experimental results show that the accuracy of the algorithm used in this paper is more than 85%. However, the accuracy of rebounding and passing recognition and prediction is low. The recognition accuracy and prediction accuracy of the test set are slightly lower than that of the effective set, which shows that the performance of the target detection system model in this paper can be further improved through more significant training examples. It is proved that the algorithm based on Taylor ring can meet the needs of teenagers in the basketball coordination and mental health.
Ticagrelor versus Clopidogrel in Patients with Severe Renal Insufficiency Undergoing PCI for Acute Coronary Syndrome
Authors: Chen Yunxian , Tu Shaowen , Chen Zhixin , Xia Jue , Chen Baofeng , Chen Jinfeng , Liang Jiarong , Liu Xiangyang , Tang Liangqiu
Published: August 2022

Background. Current guidelines recommend the use of potent antiplatelet agents in patients undergoing percutaneous coronary intervention (PCI) following an acute coronary syndrome (ACS). However, data about optimal platelet inhibition in severe renal insufficiency patients are scarce. The purpose of this study is to determine if ticagrelor is more effective than clopidogrel in patients with ACS and severe renal insufficiency treated with PCI. Methods. We retrospectively enrolled patients with ACS and severe renal insufficiency (eGFR ≤ 30 ml/min·1.73 m2 or dialysis) who underwent PCI at our hospital between January 2015 and March 2020. We used the adjusted Cox proportional hazards models to analyze the 1-year outcome endpoints, including the primary endpoint (the composite of cardiovascular death, recurrence of MI, or nonfatal ischemic stroke), death from any cause, and bleeding events (Bleeding Academic Research Consortium, BARC criteria). Results. A total of 276 patients with ACS and severe renal insufficiency who were treated with PCI with ticagrelor (n = 108) or clopidogrel (n = 168) were included in the study. After adjustment, there was no statistical difference in risk of the primary endpoint (HR, 0.78; 95% CI, 0.46–1.33;

P
=
0.367

) and death from any cause (HR, 0.86; 95% CI, 0.38–1.89;

P
=
0.708

) in the ticagrelor group against the clopidogrel group. However, the risk of total bleeding was significantly higher in the ticagrelor group (HR, 3.01; 95% CI, 1.81–5.62;

P
=
0.01

). Subgroup analysis according to the confounders did not identify any significant subgroup heterogeneity. Conclusion. Ticagrelor did not improve the major adverse cardiovascular events and all-cause mortality when compared to clopidogrel, but significantly increased the risk of bleeding in Chinese patients with ACS and severe renal insufficiency undergoing PCI.
Economic Transformation and Security Analysis of RMB Integration Based on CNN
Authors: Gong Liming
Published: August 2022

Due to the productivity shocks, there exist inherently systemic biases when using purchasing power parity as the equilibrium real exchange rate measure standard. In this paper, based on the characteristic of Chinese economic transformation, considering demographic and weakened Balassa–Samuelson effect, we reestimate the equilibrium level of the real exchange rate of RMB with the quarterly frequency data since 1994 and measure the misalignment of the RMB real exchange rate. The empirical results show that the improved convolutional neural network (CNN) model is a reasonable analytical framework for the RMB equilibrium real exchange rate, and in the sample period, the real exchange rate of RMB is robust, and demographic is an important variable affecting the RMB equilibrium exchange rate. The real exchange rate of RMB is closely related to China’s economic development strategy.
Multipath Stability Routing in Cognitive UAV Swarm for Emergency Communications: A Hypergraph Matching Approach
Authors: Ma Xiaozheng , Wang Yao , Zhang Long
Published: August 2022

With the rapid development of unmanned aerial vehicles (UAVs), it has been considered as an effective solution for emergency communications. In order to solve the contradiction between the rapid growth of user equipments and the shortage of spectrum resources as well as the problem that a single UAV cannot meet the multimission requirements, we integrate the cognitive radio spectrum access and UAVs to form a cognitive UAV swarm. Since most of the base stations cannot work properly in disaster scenarios, cognitive UAV swarm transmits the collected information through multihop routing in the form of a decentralized distributed ad hoc network. In order to solve the problems of low robustness of single paths and unstable links, we explore a multipath stability optimization problem and then propose a multipath stable routing algorithm based on the multidimensional hypergraph matching method. The results show that compared with the greedy algorithm, the proposed algorithm can obtain higher path stability while obtaining multiple node disjoint paths. Finally, this paper provides a reference value for establishing multipath routing of UAV ad hoc networks in emergency communication scenarios.
Research on Edge Detection Algorithm of Indoor Soft Decoration Pattern
Authors: Zheng Hao , Wang Lixia
Published: August 2022

Purpose of edge detection is to identify the points with obvious brightness change in digital image. The image edge detection effect under normal light is good, but the image display effect under dark vision is poor, and most of the edge information is lost. In order to quickly and accurately obtain the image edge part containing a large amount of feature information, many classical algorithms have appeared in the field of edge detection. This paper discusses the development of soft edge detection and intelligent edge detection technology for readers. Aiming at the image difference caused by proportion, rotation, and folding in the process of automatic recognition of indoor soft decoration patterns, this paper focuses on the collection of proportion, rotation, blur, and illumination of indoor soft decoration pattern images under five folding changes. The edge detection algorithm (EDA) is used to quickly and accurately obtain images containing a large amount of feature information at a low cost of edge parts, extract the local features of the pattern, calculate the feature matching with Euclidean distance, and eliminate the false matching with random sampling consistency algorithm. Finally, the experimental results show that EDA algorithm usually combines a variety of features to realize edge detection, and its output edge detection result is better than the traditional edge detection algorithm which only considers the gradient change. The algorithm has the highest accurate matching rate, and the average accurate matching rate is 87.10%; the robustness of this algorithm is better than other algorithms, and the speed is the fastest. Therefore, EDA algorithm has good applicability in indoor soft decoration pattern feature matching.
Research on Video Target Detection and Tracking in Football Matches
Authors: Zou Xiaoju , Huang Yuanling , Zhou Nairun , Fang Zuoming
Published: August 2022

Computer vision is an interesting branch of artificial intelligence which is dedicated to how electronic devices can achieve the level of capabilities to perceive things just like ordinary human beings do. In order to solve the poor effect of video for the detection of target in football matches and the low accuracy of target tracking, this paper aims to make a deep exploration of the methods of video for the detection of target and tracking in football matches. The video moving for the detection of target method based on background model is used to extract the image in the background of the matching video which improves the light flow field. Secondly, the video differential image is acquired according to the difference of colors, the ghost target of the image in the video background model is scientifically determined, the ghost degree of the pixel points of the image is scientifically determined, and the flicker matrix of the target image is constructed. The number of pixels of the moving target is derived. A meanshift-based video target tracking algorithm is used in conjunction for the detection of target result to determine whether to track the target image until the overall video target tracking task is completed, move the central position of the target frame and background frame to the target position, select the best one to adapt to the target change, and determine whether to track the target image until the overall video target tracking task is completed. The simulation results suggest that the approach described in this study is capable of detecting and tracking moving objects, as well as improving target recognition and tracking accuracy.
A V2P Collision Risk Warning Method based on LSTM in IOV
Authors: Pan Ruoyu , Jie Lihua , Zhang Xinyue , Pang Shengli , Wang Honggang , Wei Zhaoying
Published: August 2022

With the evolution of communication networks, the Internet of Vehicles (IOV) continues to accelerate the safe and rapid development of autonomous vehicles. Vehicle-to-Pedestrian (V2P) communication is a key technology in autonomous vehicles and a potential solution to realize collaborative intelligence between vehicles and pedestrians. However, the existing V2P communication early warning system does not consider the uncertainty of pedestrian trajectory, and the determination of the collision area is limited to a single point, resulting in an inaccurate system judgment and limited improvement of traffic efficiency. This paper designs a new autonomous-oriented V2P communication network architecture and completes a V2P communication early warning system based on Long Range (LoRa). A V2P anticollision model is established, and a new V2P collision risk early warning method is proposed. In this method, danger index is introduced into the early warning of collision between pedestrian and vehicle. The long short-term memory (LSTM) artificial neural network is used to predict the pedestrian’s trajectory, so as to deduce the pedestrian-vehicle collision risk area when the pedestrian trajectory is uncertain. Meanwhile, the confidence probability is used to judge whether the pedestrian and vehicle are warned. The simulation shows that the V2P collision risk warning method proposed in this paper has good performance, which can accurately warn the pedestrian and vehicle under different vehicle speeds and Global Positioning System (GPS) positioning errors. At the same time, it reflects the characteristics of intelligence brought by using LSTM methods. Using the V2P communication early warning system based on LoRa to verify the experimental results show that when the GPS positioning accuracy is submeter level, the prediction accuracy is greater than 98%. The results of the proposed method show good performance and high detection rate.
Design of Mobile English Teaching Platform Based on Collaborative Filtering Algorithm
Authors: Xu Cong
Published: August 2022

With the rapid development of information technology, today’s talent training mode is no longer limited to traditional school education. At the same time, with the maturity of portable mobile devices, a new learning method—mobile learning has been born. In this paper, the narrative of data is taken into account in the way of user collaborative filtering recommendation. For prefilling the matrix, the project confidence level also needs to be considered during the whole process. The project confidence level is measured by information entropy model. In the process of correction, it combines with traditional cosine similarity, calculates the user similarity matrix, can budget equalization, and expands the original matrix. After filling the matrix, the user uses the method of similarity calculation, using Pearson similarity and combining with the Euclidean distance correction method. When comparing the particular result prediction with the actual prediction following the completion of the similarity matrix data, all results point to a considerable reduction in MAE and RMSE. The user does not assess the item score to forecast. This demonstrates how this technique may enhance the reliability and consistency of the mobile English system platform.
Research on Inversion of Suspended Sediment Concentration in Estuary Surface Based on Remote Sensing and GIS
Authors: Zeng Ming , Peng Jun , Liu Fucheng
Published: August 2022

The concentration of suspended sediments at the estuarine surface (SSC) is a crucial indicator for monitoring water bodies. Given the current situation in which SSC remote sensing inversion is primarily based on low-resolution satellites, this study first discusses remote sensing and GIS technologies before employing the Sentinel-2 satellite, whose resolution can exceed 10 m after resampling. Inversion and comparison of SSC content during wet and dry periods. In addition, based on the neural network’s ability to compensate for the inherent errors of traditional empirical techniques, this study designs and develops an artificial neural network-based neural network corrector to perform secondary correction on the empirical inversion results. In this study, the B2, B3, B4, and B8 inversion models are used to generate the sensitive bands, and the ratio of these bands is used to generate the inversion model. The results indicate that the model has a high level of precision, which can aid in reducing the model’s inherent error and ensuring inversion precision.
Having a Parent with Early-Onset Dementia: A Qualitative Study of Young Adult Children
Authors: Groennestad Hanne , Malmedal Wenche
Published: August 2022

Background. Children of a parent with early-onset dementia (EOD) are confronted with losing a parent to a progressive neurodegenerative illness, usually perceived as an older adult illness, which may have a great impact on their lives at a time that is usually preserved for self-development. Objective. The objective of this study is to explore the experiences and perceptions of young adult children of a parent with EOD, with specific focus on personal lives and family and social relationships in a Norwegian context. Methods. Semistructured interviews with 10 young adult children between the ages of 19 and 30 years of a parent with EOD were analysed using a thematic analysis. Results. The analysis identified six main themes. “Upon discovering dementia, Keeping the family together, Others do not understand, A sense of relief, A need for support” and Apprehension for the future. The participants expressed an overarching feeling of living parallel lives, summarised by the phrase “We are not in the same boat.” Furthermore, the themes demonstrated that the participants experienced difficulties with managing new responsibilities, at the same time, as preserving their own lives. They also shared concerns about the future and often experienced a lack of understanding and support from others. Finally, the need for targeted support throughout the illness was a central theme, whereby many felt more comfortable talking with someone with similar experiences or knowledge of their situation. Conclusion. The findings in this study strengthen the notion that the children of persons with EOD experience a challenging life situation, underlining the need for a person- and family-oriented approach.
The Default Risk of Bank Customers Based on Embedded Microprocessor Wireless Communication under the Internet Finance Background
Authors: Wangsong Xie
Published: August 2022

Internet finance refers to a new financial business model in which traditional financial institutions and Internet enterprises use Internet technology and information and communication technology to achieve capital financing, payment, investment, and information intermediary services. Embedded microprocessors have more than 32-bit processors with high performance. And it is small in size, light in weight, and low in cost. This article aims to explore the default risk of bank customers based on embedded microprocessor wireless communication under the background of Internet finance and how to control the credit risk of bank customers and help to clarify the development direction of Internet finance. Based on multimedia technology and orderly logistics model, this article designs a customer default credit risk management system. In order to test the performance of the bank customer credit risk management system, a small customer credit evaluation system was created. The experiment proves that the customer credit evaluation system can well realize risk evaluation and risk early warning and promote the sustainable development of the bank. At the same time, the system can be applied to most scenarios in the financial industry.
A Study of College Teachers’ English Teaching Quality Based on Fuzzy Neural Network
Authors: Chen Chunfang
Published: August 2022

In many universities and colleges, the government is now paying more attention to the quality of teaching assessment, and research on English teaching quality evaluation is becoming increasingly significant. The goal of this paper is to investigate how to use a fuzzy neural network to assess the quality of English education. The research of the model NN and the evaluation of the quality of English teaching is detailed first. A fuzzy NN is an algorithm that examines the quality of English instruction evaluation using fuzzy criteria. In the case results, the data show that the previous evaluation of quality teaching is between the intermediate and the intermediate level, while the research on the evaluation quality of English teaching based on fuzzy NN shows that the evaluation quality is between the intermediate and the advanced level. Therefore, the combination of Fuzzy Rules (FR) and NN methods can effectively improve the quality of college teachers’ English teaching evaluation. In college English teaching, FRs can simplify the analysis steps of evaluation of quality teaching, accurately judge the quality of college English teaching evaluation, and provide support for the improvement of evaluation of quality teaching.
Nanometer TiO2 Film-Based Solar Thin Film Manufacturing Technology and Performance Research
Authors: Wu Hongliang
Published: August 2022

TiO2 sols are usually prepared by sol-gel process using butyl titanate as a precursor, and TiO2 thin films are loaded on ceramic substrates by impregnation lifting method. In this work, the effects of precursor concentration and heat treatment on the properties of TiO2 thin films are investigated to achieve better performance. In addition, the crystal structure of TiO2 is examined by XRD characterization. Experimental results show that the TiO2 films calcined at 500°C are anatase-type structure; the hydrophilic property of the films changes less with the increase of precursor concentration. Moreover, the photodegradation property is improved gradually. The adhesion of the films improved after calcination for each layer of TiO2 films loaded on the ceramic sheet.
Mechanical Characteristics of Variable Cross‐Section Immersed Tunnels under Spatial Differential Settlement
Authors: Yang Chunshan , Wang Yatian , Wei Lixin , Chen Yizhen
Published: August 2022

This work establishes a fine model reflecting the characteristics of immersed tube structures to study the spatial mechanical characteristics of variable cross section immersed tunnels. Then, the mechanical behavior of the pipe segments under differential deformation is explored, based on which we propose a formula for estimating the shear key force and analyze the corresponding failure mechanism and failure mode. Thus, the critical points of the pipe segment design are specified. The results show that, first, the variable cross section segment bears more sectional internal force (over 47%) than the uniform cross section segment in actual cases, which should be fully considered in practical reinforcement design. Bearing deformation alternatively occurs at different shear keys, implying an apparent spatial stiffness matching problem. Second, the pipe segments show overall settlement under longitudinal bending, failing to satisfy the assumption of deformed plane sections. The force on the shear keys varies with the quadratic function of the longitudinal bending degree, and the dislocation magnitude has a positive near‐linear relationship with the bending degree. Third, when subjected to torsion, the shear keys of the weak sidewalls are sheared to resist torsion. Then, this force is laterally transferred to the top and bottom plates and jointly shared by the adjacent shear keys, explaining why shear is adjusted with structural deformation. Fourth, under the action of spatial differential deformation, the shear force is mainly undertaken by the vertical shear keys. When the structure is subjected to bending, compression and shear failure occur at the end angle of the middle wall shear key, and its root junction experiences tension and shear failure. When subjected to longitudinal torsion, the local tension and shear failure at the root of the shear key on the soft subgrade side cause a joint failure. Finally, based on the bearing characteristics, failure mechanism, and failure mode of variable cross section immersed tunnels, the idea of strengthening immersed tube structures is put forward, which can guide similar engineers.
Dexmedetomidine Attenuates LPS-Stimulated Alveolar Type II Cells’ Injury through Upregulation of miR-140-3p and Partial Suppression of PD-L1 Involving Inactivating JNK-Bnip3 Pathway
Authors: Chen Xianfeng , Hu Juntao , Lai Jie , Zhang Zhiyong , Tang Zhanhong
Published: August 2022

Dexmedetomidine (DEX), which is reported to be a newly discovered, novel α-2 adrenoceptor agonist, is known to exhibit anti-inflammatory properties in several diseases. DEX regulates inflammation-related signaling pathways and genes through interactions with several miRNAs. This study verified that expression levels of miR-140-3p were diminished when alveolar type II cells were exposed to LPS. However, the levels of miR-140-3p were confirmed as showing an increase with DEX treatment. These observations revealed that the expression of miR-140-3p was related to the beneficial effects that accompanied the DEX treatment of LPS-induced ALI. In addition, PD-1/PD-L1 expression increased extensively when RLE-6TN cells were induced by LPS. The increased expression was reduced after treatment with DEX. Thus, it appears that the PD-L1 expression was targeted directly by miR-140-3p, resulting in the partial repression of PD-L1 levels, which involved the inhibition of p-JNK and Bnip3 expression. Therefore, DEX was shown to inhibit the PD-L1 expression by promoting partially increased miR-140-3p levels in RLE-6TN cells. DEX also inactivated the JNK-Bnip3 pathway, resulting in the inhibition of inflammation and alleviating alveolar type II cell injury.
Mechanism and Mesoscopic Characteristics of Indirectly Reinforced Gravelly Soil by a Geogrid
Authors: Liu Jie , Wang Bin , Sun Yunlong
Published: August 2022

The geogrid is a type of spatial network structure with a certain thickness; through its interactions with the surrounding soil, the soil can be reinforced. In this study, the characteristics of the interface between the geogrid and gravelly soil were investigated with a pull-out test. To investigate the mesoscopic characteristics of the geogrid-soil interface, the Particle Flow Code 3D (PFC3D) program was employed to simulate the pull-out test, which can reproduce the evolution of the influencing zones of the geogrid during the pull-out test from macroscopic and mesoscopic perspectives. Both sides of the geogrid were characterised by a shear zone and an advanced influencing zone. The geogrid indirectly reinforced the soil within the influencing zones to a certain extent, and the thickness of this zone was rarely related to the normal pressure. Additionally, the widths of the influencing zones above and below the interface were different; the above one was wider.
Efficacy of Patellar Taping and Electromyographic Biofeedback Training at Various Knee Angles on Quadriceps Strength and Functional Performance in Young Adult Male Athletes with Patellofemoral Pain Syndrome: A Randomized Controlled Trial
Authors: Hasan Shahnaz , Alonazi Asma , Anwer Shahnawaz , Jamal Azfar , Parvez Suhel , Alfaiz Faiz Abdulaziz Saleh , Li Heng
Published: August 2022

Background. The severity of the articular lesion is the single most essential element in investigating the extent of flexion that is required for activities. However, a prior study found no differences in muscle strength gains of quadriceps muscles at different knee angles in people with patellofemoral pain syndrome (PFPS). Objective. The effects of patellar taping and electromyographic biofeedback (EMG-BF)-guided isometric quadriceps strengthening at different knee angles (e.g., 30°, 60°, and 90° of knee flexion) on quadriceps strength and functional performance in people with PFPS were compared in this single-blind randomized controlled parallel trial. Methods. Sixty adult male athletes with PFPS (age: 26.9 ± 1.4 years) were randomly divided into two groups. The experimental group (n = 30) received patellar taping and EMG-BF-guided isometric contraction exercise at 30°, 60°, and 90° angles, and the control group (n = 30) received sham patellar taping without EMG-BF-guided exercises for six weeks. Pain intensity, knee function, muscle strength, and the single-leg triple hop (SLTH) test were assessed. Results. The pain intensity and SLTH scores between the groups were significantly different at the end of the trial (

p
≤
0.001

). The EMG-BF and control groups had mean pain scores of 1.3 (0.8) and 4.5 (0.8), respectively. The EMG-BF and control groups had mean functional scores of 80.4 (5.1) and 69.1 (6.1), respectively. The mean SLTH score for the EMG-BF group was 540.7 (51.2) and for the control group it was 509.4 (49.8) after the trial. Quadriceps muscle strength was significantly higher in those who performed quadriceps strength training at 60° of knee flexion after six weeks than in those who performed strength training at 30° or 90° of knee flexion. Conclusion. The findings indicated that individuals who trained their quadriceps at a 60° knee angle had significantly stronger quadriceps muscles than individuals who trained at 30° or 90° of knee flexion. Trial Registration. This trial is registered at Clinical Trials.gov under the identifier NCT05055284.