bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation Method of Performance of Cross-Border e-Commerce System Based on Fuzzy DEA Model
Authors: Zhu Zhihui , Zhu Meifang
Published: September 2022

Cross-border e-commerce trade is an important form of trade that is different from traditional international trade. Nowadays, cross-border e-commerce is more and more widely used in foreign trade activities. Cross-border e-commerce system has its own development constraints, such as the imperfection of cross-border e-commerce platforms, the security loopholes of cross-border payment, the slow development of supporting logistics, and the lag of policies, which will affect its development to varying degrees, thus affecting the performance of e-commerce enterprises in using cross-border e-commerce for foreign trade activities. Therefore, it is necessary to explore the factors of cross-border e-commerce system performance and compare the strength of various factors, which has certain theoretical and practical significance. Therefore, based on the analysis of performance data, this paper will establish a performance evaluation model for an e-commerce system, aiming at providing standards and a basis for performance evaluation of system performance. In order to continuously improve the accuracy of cross-border e-commerce performance evaluation and to achieve the accuracy of cross-border e-commerce evaluation and decision-making, a cross-border e-commerce system performance evaluation model based on the fuzzy DEA model is innovatively proposed. By combining the average analysis results of descriptive statistical data, the regression test is conducted on the performance evaluation samples of cross-border e-commerce systems. The fuzzy feature clustering method is used to classify and identify the performance of big data in the cross-border e-commerce system. According to the fusion results of cross-border e-commerce performance information, the principal component analysis and adaptive game decision are carried out, and the game decision model is established. Combined with the fuzzy DEA evaluation method, the performance of the cross-border e-commerce system can be quantified and evaluated. The F statistical analysis method is used to test the effectiveness of the performance evaluation of the cross-border e-commerce system. From the test results, it can be seen that the performance evaluation accuracy of the cross-border e-commerce system using this model is relatively high, and the confidence level is also relatively good. Finally, according to the conclusion of the study, the author puts forward the counter-measures for future research.
Pioglitazone Mediates Cardiac Progenitor Formation through Increasing ROS Levels
Authors: Baharlooie Maryam , Peymani Maryam , Nasr-Esfahani Mohammad Hossein , Ghaedi Kamran
Published: September 2022

In order to achieve a sufficient population of cardiac‐committed progenitor cells, it is crucial to know the mechanisms of cardiac progenitor formation. Previous studies suggested ROS effect on cardiac commitment events to play a key role in the cell signaling and activate cardiac differentiation of pluripotent stem cells. We previously reported that PPARγ activity is essential for cardiac progenitor cell commitment. Although several studies have conducted the involvement of PPARγ‐related signaling pathways in cardiac differentiation, so far, the regulatory mechanisms of these signaling pathways have not been discussed and cleared. In this study, we focus on the role of PPARγ agonist in ROS generation and its further effects on the differentiation of cardiac cells from mESCs. The results of this study show that the presence of ROS is necessary for heart differentiation in the precursor stage of cardiac cells, and the coenzyme Q10 antioxidant precludes proper cardiac differentiation. In addition, this antioxidant prevents the action of pioglitazone in increasing oxygen radicals as well as beating cardiomyocyte differentiation properties. In this case, it can be concluded that PPARγ is required to modulate ROS levels during cardiac differentiation.
A Wideband Feed Network for Vivaldi Antenna Arrays
Authors: Hall Natasha Antoinette , Odendaal Johann Wilhelm , Joubert Johan
Published: September 2022

A wideband feed network for a Vivaldi antenna array is presented. A limitation of current wideband antenna arrays is the bandwidth of either the feed network or the antenna element. The proposed antenna array consists of four wideband Vivaldi antennas fed with an improved wideband feed network to extend the useable bandwidth of the array. The proposed feed network consists of coplanar waveguide-to-slotline-to-microstrip line transitions. The feed network has a single coplanar waveguide input and four microstrip line output ports. The feed network achieved uniform amplitude and phase balance and an impedance bandwidth of 160% from 1 GHz to 9 GHz. The feed network was used in a uniform linear antenna array to feed four Vivaldi antenna elements. The Vivaldi antenna array achieved stable radiation patterns from 1.3 GHz to 8 GHz, resulting in a useable bandwidth of 144%. The antenna array has a minimum gain of 8 dBi and a maximum of 13.8 dBi within the frequency band. Results for a prototype Vivaldi antenna array, measured in a compact antenna test range, are presented and compared to simulated results from CST Studio Suite.
Hybrid Encryption Algorithm for Sensitive Information of College Physical Fitness in Cloud Storage Environment
Authors: Deng Miaolei
Published: September 2022

In order to improve the security of college sports fitness sensitive information, this paper proposes a hybrid encryption algorithm for college sports fitness sensitive information in cloud storage environment. Build an analysis model of influencing factors of cloud storage environment to identify the risk value of sensitive information; Using Bloom filter data structure to eliminate redundant data of sensitive information; The transmission channel model of sensitive information and the security coding model of sensitive information are constructed. Combined with the fuzzy differential information fusion method, the complete key of sensitive information under the symmetric encryption protocol is obtained to realize the key optimization design. Through AES encryption and decryption algorithm, the anti encryption control and structural reorganization of college sports fitness sensitive information, and the iterative convergence control of hybrid encryption, so as to realize the hybrid encryption of college sports fitness sensitive information. The encryption time of the design algorithm under different attribute numbers is always kept below 0.2S, the maximum encryption time under different number of software packages is only 0.5 s, and the encryption accuracy can reach 1, which proves that the design algorithm has certain application value.
Prognostic Role of Neutrophil to Lymphocyte Ratio in Nonalcoholic Fatty Liver Disease: A Systematic Review and Meta-Analysis
Authors: Shavakhi Mitra , Nourigheimasi Shima , Dioso Emma , Goutnik Michael , Lucke-Wold Brandon , Khanzadeh Shokoufeh , Heidari Fariba
Published: September 2022

Introduction. Nonalcoholic steatohepatitis (NASH) and liver fibrosis are the most common complications of nonalcoholic fatty liver disease (NAFLD). In this systematic review and meta-analysis, we aim to analyze the current literature to evaluate the association of neutrophil to lymphocyte ratio (NLR) with NASH and fibrosis in patients with NAFLD. Methods. PubMed, Web of Science, and Scopus were used to conduct a systematic search for relevant publications published before May 24, 2022. The Newcastle–Ottawa scale was used for quality assessment. Results. Thirteen studies were included in our study. The pooled results showed that NAFLD patients with significant NASH had elevated levels of NLR compared to those with nonsignificant or without NASH (SMD = 0.97, 95% CI = 0.59–1.39,

p
<
0.001

). The pooled sensitivity and specificity of NLR were 78.16% (95% CI = 73.70%–82.04%), and 76.93% (95% CI = 70.22%–82.50%), respectively. In addition, NAFLD patients with significant liver fibrosis had elevated levels of NLR compared to those with nonsignificant or without fibrosis (SMD = 1.59, 95% CI = 0.76–2.43,

p
<
0.001

). The pooled sensitivity and specificity of NLR were 82.62% (95% CI = 70.235%–90.55%) and 81.22% (95% CI = 75.62%–85.78%), respectively. Conclusion. Our findings support NLR to be a promising biomarker that can be readily integrated into clinical settings to aid in the prediction and prevention of NASH and fibrosis among patients with NAFLD.
Impact Assessment of the Effects of Strong Earthquake-Induced Hazards on the Socioeconomic Development Level of Earthquake-Stricken Areas after the 2008 Wenchuan Earthquake
Authors: Han Suyue , Liu Bin , Yang Jingjing , Feng Tingting , Luo Jie , Zhou Zhongli , Gong Hao
Published: September 2022

A strong earthquake-induced hazard has obvious long-term and spatial heterogeneity, which will result in continuous social and economic losses. Measuring the socioeconomic development level of the disaster area is of great significance for long-term development reconstruction after an earthquake. First, the kernel density estimation (KDE) is used to analyze the spatial effects of 10 extremely earthquake-stricken areas of the Wenchuan earthquake in this paper. Second, the economic gravity centers from 2006 to 2016 are calculated, and the temporal and spatial variation characteristics of the socioeconomic development level of the study area are analyzed. Finally, the relationship between the effects of strong earthquake-induced hazards and the level of socioeconomic development in earthquake-stricken areas is discussed. The results indicate that the effect of landslide hazards show an oscillatory attenuation trend with time from 2008 to 2016 and has significant spatial differentiation characteristics. The economic gravity centers move in the direction of “moving northeast first and moving southwest later” with time, and the movement trend is closely related to the effect of hazard and the industrial structure of the earthquake-stricken areas.
Effects of Task-Based LSVT-BIG Intervention on Hand Function, Activity of Daily Living, Psychological Function, and Quality of Life in Parkinson’s Disease: A Randomized Control Trial
Authors: Choi YoungSeok , Kim DeokJu
Published: September 2022

Previous studies have demonstrated that the Lee Silverman Voice Treatment-BIG (LSVT-BIG) program can improve motor functions such as balance and gait in Parkinson’s disease (PD) patients. However, no study has investigated the effects of a task-based LSVT-BIG intervention on hand function, psychological function, and quality of life in PD patients. Herein, we investigate the effects of a task-based LSVT-BIG intervention, which reflects the needs of PD patients, on hand function, activity of daily living (ADL), psychological function, and quality of life. A total of 14 PD patients were enrolled and randomly assigned to the experimental or control group. The experimental group performed 30 minutes of conventional occupational therapy and 40 minutes of the task-based LSVT-BIG program. The control group performed 30 minutes of conventional occupational therapy and 40 minutes of relaxation and stretching. Both groups underwent the respective interventions once a day 5 times a week for 4 weeks. As a result of the study, the experimental group showed improvement in hand function in both the dominant and nondominant hand, and the control group showed improvement only in the nondominant hand (

p
<
.05

). ADL was significantly improved in both groups, but the experimental group showed a more statistically significant difference than the control group (

p
<
.05

). Depression and anxiety were significantly decreased in both the experimental group and the control group, and in particular, in the case of anxiety, there was a more statistically significant difference in the experimental group (

p
<
.05

). In the case of the experimental group, there was a significant improvement in quality of life in all items, and in the control group, except for the social function item (

p
>
.05

), there was a significant improvement in other items (

p
<
.05

). The results of this study suggest that the task-based LSVT-BIG program, which consists of activities desired by the participants, may be an effective intervention to improve hand function, ADL, psychological function, and quality of life in PD patients.
Current-Sensorless Control Strategy for the MPPT of a PV Cell: An Energy-Based Approach
Authors: Phillips-Brenes Hayden , Pereira-Arroyo Roberto , Rímolo-Donadío Renato , Muñoz-Arias Mauricio
Published: September 2022

A novel energy-based modelling and control strategy is developed and implemented to solve the maximum power point tracking problem when a photovoltaic cell array is connected to consumption loads. A mathematical model that contains key characteristic parameters of an energy converter stage connected to a photovoltaic cell array is proposed and recast using the port-Hamiltonian framework. The system consists of input-output power port pairs and storage and dissipating elements. Then, a current-sensorless control loop for a maximum power point tracking is designed, acting over the energy converter stage and following an interconnection and damping assignment passivity-based strategy. The performance of the proposed strategy is compared to a (classical) sliding mode control law. Our energy-based strategy is implemented in a hardware platform with a sampling rate of 122 Hz, resulting in lower dynamic power consumption compared to other maximum power point tracking control strategies. Numerical simulations and experimental results validate the performance of the proposed energy-based modelling and the novel control law approach.
[Retracted] Psychological Shaping Function of Music Education to Cultivate the Subjective Initiative of University Students’ Physical Training
Authors: Zhou Lin , Yu Feng
Published: September 2022

The purpose of university students’ physical training (PT) is to make university students have a good exercise habit and improve their willpower while enhancing their immunity. However, because many university students are not active in physical exercise, who worry about sweating during exercise, with low requirements for physical exercise, the subjective motivation of university students in PT is poor. Music education (MUE) is a new educational model. Through the correct guidance of university students’ psychology, the inner health of university students can be enhanced, so that university students can carry out PT with a positive attitude. MUE is applied to university students’ PT to cultivate the subjective initiative of university students’ PT by shaping the psychology of university students. This paper evaluates the influence of the psychological shaping of MUE on the subjective initiative of university students’ PT through the analytic hierarchy process (AHP). The experimental results showed that the top three weights of the evaluation indicators were the effect of MUE, the effect of university students’ music learning, and the psychological state of university students. Comparing and analyzing the three indicators of MUE and traditional education, the average values of the two education methods in the subjective initiative of university students’ PT were 61.3% and 34.2%. Compared with traditional education, MUE can effectively improve the effect of PT. Therefore, MUE can improve the subjective initiative of university students’ PT through the psychological guidance of university students, so that university students can exercise actively, improving the effect of PT.
Minimally Invasive Abdominal Repair of a Giant Paraesophageal Hiatal Hernia with Occupation of the Right Thorax in a 53-Year-Old Man
Authors: Navarro Francisco , Pizarro Eduardo , Ceroni Marco
Published: September 2022

Paraesophageal giant hiatal hernia is a rare condition associated with serious complications if not treated surgically. There are no reports of the minimally invasive abdominal repair of a giant hiatal hernia of the stomach almost entirely occupying the right thoracic cavity. The most common clinical presentation includes pathological gastroesophageal reflux, dysphagia, chest pain, or respiratory symptoms such as chronic cough or dyspnoea. Chest computed tomography, upper gastrointestinal endoscopy, and high-resolution oesophageal manometry are used to indicate the best treatment. This article reports the minimally invasive abdominal repair of a case of paraesophageal giant hiatal hernia occupying the right thoracic cavity.
Research on the Application of 3D Animation Special Effects in Animated Films: Taking the Film Avatar as an Example
Authors: Sun Lin
Published: September 2022

Nowadays, 3D animation special effects are used more and more frequently in film and television works. The integration of its animation special effects enhances the visual impact of the film and makes it easier to resonate with the audience. Movies that use three-dimensional animation special effects have a more prominent performance in both visual effects and artistic expression. Taking the film Avatar as an example, this study is committed to providing a reference for the research of three-dimensional animation effects in Chinese film and television works through the analysis of the practical application effects of three-dimensional animation effects. Three dimensional technology provides technical support for film and television special effects, which has achieved unprecedented development. It combines reality with virtualization, brings virtualization to the screen, and then presents it to the audience, contributing to the progress of Chinese film and television art.
Building a Smart Education Ecosystem from a Metaverse Perspective
Authors: Zhou Binbin
Published: September 2022

Metaverse is the future of the Internet and integrates a variety of information technologies. It leads future education trends and brings profound changes to education. On the basis of analysis of the development trend of smart education and the connotation and action mechanism of edu-metaverse in the view of metaverse, this paper structures the smart education ecosystem, builds the scenario and modular smart learning space of three education scenarios of resource collaborative interaction, virtuality-reality integration experience, and ubiquitous spatial inquiry by using the six core technologies, and forms the new education mode of virtuality-reality symbiosis, trans-spatial fusion, and collaborative inquiry. Then, it verifies the application effect by AHP. Finally, it creates the smart education ecosystem of “four ecology integration”—resource ecology, interaction ecology, space ecology, and collaboration ecology, which accelerates the organic integration of metaverse and smart education and provides theoretical basis and reference for the new application of future education.
Hardware Realization of Kinematic Mechanism and Control System of Multifunctional Industrial Robot
Authors: Zhang Kai , Gao Jihao , Wang YunFei , Liang MingLiang
Published: September 2022

In order to improve the position control accuracy of industrial robots and solve the problems of poor real-time and reconfigurability of traditional motion controllers, a hardware implementation method for the motion mechanism and control system of multi-functional industrial robots is proposed. The video acquisition system is suitable for infrared detectors containing 4 channels or readout circuits in 4 channels. The video display system is compatible with the old AV/S-Video interface, and is also suitable for computer system video graphics array (VGA) analog video interface and high-definition video interface. Multimedia Interface (HDMI) digital high-definition video interface display terminal equipment. The hardware circuit of video acquisition and corresponding video interface image output is designed, including signal amplification circuit, analog-to-digital conversion circuit, video information buffer circuit, video display digital-to-analog conversion circuit, and interface hardware circuit, to realize the digitization of image information acquisition and image information. Display simulation, construct VGA, AV/S-Video, and HDMI timing sequence with hardware description language through Field programmable gate array (FPGA) to complete the display of corresponding terminal equipment. The experimental results show that the experimental data was substituted into the formula and the variance

σ

 = 0.09 mm was found, indicating that the detection error of the system is less than 0.27 mm, which meets the detection requirements. Through the 3D contour reconstruction experiment of the workpiece, the expected function realization of each module is proved, and the feasibility of the system software and hardware system is verified. This design has good scalability and stability, reducing labor costs.
The Dynamic Displacement Monitoring Method Using Unmanned Aerial Vehicles Based on Digital Close-Range Photogrammetry
Authors: Yu Xianzhi , Ge Yongquan , Zhao Tonglong , Zhang Guojian , Liu Yingchun , Yu Chengxin
Published: September 2022

How to carry out fast and reliable dynamic deformation monitoring of building structures is an important issue for engineers and technicians. Digital close-range photogrammetry technology has the advantages of noncontact, multipoint, and rapid monitoring, and the application of UAVs makes the monitoring task no longer limited by the size of the field, but the current technology can not guarantee the rapid deployment of UAVs in dynamic deformation monitoring, and these methods commonly have higher requirements for image quality, and cannot ensure the stability of accuracy. To this end, we propose a dynamic displacement monitoring method for UAVs based on digital close-range photogrammetry technology and optimize the data processing process for the problem that there is still moving when the UAV hovers. A building with an overhead corridor structure with a large flow of people was selected for the experiment. The experiment used ground digital cameras and drones to monitor separately to compare the monitoring results. The results show that the proposed method is simple and easy to use. The monitoring method can be deployed quickly, which is expected to be applied to emergency monitoring scenarios.
[Retracted] Perception Research of Artificial Intelligence in Environmental Public Health Physiotherapy Nursing for the Elderly
Authors: Shi Min , Peng Huadong , Lin Yuanxing , Ma Yiming , Qi Yanxin
Published: September 2022

This perceptual study focuses on developing artificial intelligence for elderly care design. It analyses and discusses the role of artificial intelligence in elderly care and its application to physiotherapy care. Artificial intelligence, as an emerging disruptive technology, is releasing the enormous energy accumulated in the technological and industrial revolutions, profoundly transforming how humans produce, live, and think about the world. Economic development and social progress are significantly impacted by it, and it has a great deal of practicality and broad application scope. Although there is a basic consensus in the 18 public understanding of AI, there is still some ambiguity and misunderstanding, knowing what is happening without understanding why. As a result, it is necessary to systematize and gain a comprehensive understanding of this concept and its associated practices.
System Design of Integrated Intelligent Platform of National Fitness Based on K-Means Clustering
Authors: Song Pingping , Ma Cheng
Published: September 2022

Voice communication is the most common, direct, and effective method of information exchange between humans. Dependent speech signal processing will inevitably become an important carrier for the interaction between people and the interaction between people and computers. With the development of science and technology, data mining has become a means for users to extract effective information from a large amount of data, and many branches have been derived. Among them, K-means clustering algorithm is used as a classic clustering analysis algorithm. It is fast and simple, and it is also affected by the randomness of the initial center selection and the interference of outliers, which may cause poor clustering, but even if the above problems exist, it does not affect its wide application in various industries. This paper applies HBase storage technology and microservice framework to the fitness system and implements a national fitness system based on HBase and microservices. The system uses HBase to store fitness information, venue opening, and usage information for national fitness people; simulation results show that the accuracy rate on the data set has an obvious improvement. A fitness system that combines massive data storage and microservice architecture can improve the utilization of fitness resources, solve the problem of fitness resources, improve professional fitness levels, and provide support for the masses who regularly exercise scientifically.
Critical Demand Response Opportunities in Heavy Industries as a Solution for Large Active Power Imbalance in Smart Grid: Study in Three Industrial Subgroups
Authors: Siahchehre Kholerdi Somayeh , Ghasemi-Marzbali Ali
Published: September 2022

Demand response (DR) is one of the most cost-effective and logical smart grid terms for power systems that can be used during peak load hours, whereas load shedding (LS) is the last and most expensive solution in emergency grid situations. The aim of them is to satisfy equilibrium constraints between consumption and generation and restore the power system frequency to normal bounds at the least possible time. The rapid increase in power grid costs and limitations on electricity generation resources have resulted in the increasing need for industrial customers’ participation as an alternative solution to peak load spikes. Therefore, this paper considers the estimation of imbalance active power in a smart strategy to introduce a critical DR (CDR) in heavy industries (pulp and paper, cement, and medium density fibreboard (MDF)) based on direct load control (DLC) technique in order to reduce the need for LS in frequency restore. To evaluate the proposed model, a real case study including the typical pulp and paper, cement, and MDF industries processes with actual power consumption data is considered. The numerical and graphical results confirm that the proposed CDR can be used as an inexpensive solution to replace the costly spinning reserves and avoid load shedding.
Coupling and Coordinated Development of Higher Vocational Education and Economic Development in the Yangtze River Economic Belt from 2008 to 2020
Authors: Ren Xiao , Zhou Yingling
Published: September 2022

According to the panel data from 2008 to 2020, empirical research is conducted on the coupling and coordination relationship between the higher vocational education and the regional economic development in the Yangtze River economic belt by constructing a comprehensive evaluation indicator system and using a coupling and coordination degree model. The research results show that, the development levels of the higher vocational education system and the regional economic development system in the Yangtze River economic belt have been on the rise over the past 13 years. There existed a sound coupling interaction between the two systems. However, their coupling and coordination degree were not high. By the end of 2020, 73% of the provinces (cities) were in transition and imbalance, and the coupling coordination degree showed a gradient phenomenon of “high in the East and low in the west.” To improve the coupling and coordination level between the two systems, the Yangtze River Economic Belt shall deepen the supply-side reform of the higher vocational talent training in accordance with the needs of industrial development, optimize the layout of higher vocational specialties to boost the adaptability of education to economy, and strengthen regional overall coordination to accelerate the cluster development of regional higher vocational education.
A New Approach Based on the Learning Effect for Sequence‐Dependent Parallel Machine Scheduling Problem under Uncertainty
Authors: Ebrahimi Maryam , Dinari Parviz , Samaei Mohamad , Sohrabi Rouhollah , Sherafatianfini Soheil
Published: September 2022

Production system design has lots of restrictions and complex assumptions that cause difficulty in decision making. One of the most important of them is the complexity of the relationship between man and machine. In this regard, operator learning is recognized as an effective element in completing tasks in the production system. In this research, a mathematical model for scheduling the parallel machines in terms of job degradation and operator learning is presented. As one of the most important assumptions, the sequence‐dependent setup time is of concern. In other words, jobs are processed sequentially, and there is a sequence‐dependent setup time. Moreover, the processing time and delivery due date are considered uncertain, and a fuzzy conversion method is used to deal with this uncertainty. The proposed mathematical model is a multiobjective one and tries to minimize speed and completion time. In order to optimize this mathematical model, the genetic algorithm (GA) and variable neighborhood search (VNS) algorithms have been used. A new hybrid algorithm has also been developed for this problem. The results show that the hybrid algorithm can provide more substantial results than classical algorithms. Moreover, it is revealed that a large percentage of Pareto solutions in the proposed algorithm have a generation time of more than 80% of the algorithm’s execution time.
Anti-Plane Wave Propagation in the Functionally Graded Hybrid Structure under an External Impulsive Force: A Green’s Function Approach
Authors: Bharti Uma , Vaishnav Pramod Kumar
Published: September 2022

To propagate the anti-plane wave, a hybrid layered-half-space schematic of fiber-reinforced and orthotropic materials is taken into account. Due to its importance in engineering applications, anti-plane wave propagation through functionally graded orthotropic materials has attracted a lot of attention. The functionally graded orthotropic materials in the half-space and the reinforced materials under high initial stress are utilized in the superficial layer of finite depth. To examine the effect of heterogeneity on wave phase velocity, the elastic characteristics of orthotropic materials are defined in terms of hyperbolic functions. Moreover, a rectangular plate is installed at the interface of the materials to expose the effect of irregularity in the materials. An external force (impulsive force) is applied to the wave at the point source of the disturbance to understand the influence of such a force on the phase velocity of the wave. The nonhomogeneous equations of motion are deduced by Fourier transformation and are solved analytically by Green’s function technique along with possible applications of Dirac delta function. The dispersion relation of the anti-plane wave propagation is obtained analytically. This study presents a graphic explanation of the proposed schematic and discusses the stability of the model.
Deep Learning Model for Predicting Rhythm Outcomes after Radiofrequency Catheter Ablation in Patients with Atrial Fibrillation
Authors: Lee Dae-In , Park Mi-Jung , Choi Jee-Woo , Park Seung
Published: September 2022

Current guidelines on atrial fibrillation (AF) emphasized that radiofrequency catheter ablation (RFCA) should be decided after fully considering its prognosis. However, a robust prediction model reflecting the complex interactions between the features affecting prognosis remains to be developed. In this paper, we propose a deep learning model for predicting the late recurrence after RFCA in patients with AF. Aiming to predict the late recurrence (LR) of AF within 1 year after pulmonary vein isolation, we designed a multimodal model based on the multilayer perceptron architecture. For quantitative evaluation, we conducted 4-fold cross-validation on data from 177 AF patients including 47 LR patients. The proposed model (area under the receiver operating characteristic curve-AUROC, 0.766) outperformed the acute patient physiologic and laboratory evaluation (APPLE) score (AUROC, 0.605), CHA2DS2-VASc score (AUROC, 0.595), linear regression (AUROC, 0.541), logistic regression (AUROC, 0.546), extreme gradient boosting (AUROC, 0.608), and support vector machine (AUROC, 0.638). The proposed model exhibited better performance than clinical indicators (APPLE and CHA2DS2-VASc score) and machine learning techniques (linear regression, logistic regression, extreme gradient boosting, and support vector machine). The model will support clinical decision-making for selecting good responders to the RFCA intervention.
A Deep Neural Network for Gastric Cancer Prognosis Prediction Based on Biological Information Pathways
Authors: Hu Jili , Yu Weiqiang , Dai Yuting , Liu Can , Wang Yongkang , Wu Qingfa
Published: September 2022

Background. Gastric cancer (GC) is one of the deadliest cancers in the world, with a 5-year overall survival rate of lower than 20% for patients with advanced GC. Genomic information is now frequently employed for precision cancer treatment due to the rapid advancements of high-throughput sequencing technologies. As a result, integrating multiomics data to construct predictive models for the GC patient prognosis is critical for tailored medical care. Results. In this study, we integrated multiomics data to design a biological pathway-based gastric cancer sparse deep neural network (GCS-Net) by modifying the P-NET model for long-term survival prediction of GC. The GCS-Net showed higher accuracy (accuracy = 0.844), area under the curve (AUC = 0.807), and F1 score (F1 = 0.913) than traditional machine learning models. Furthermore, the GCS-Net not only enables accurate patient survival prognosis but also provides model interpretability capabilities lacking in most traditional deep neural networks to describe the complex biological process of prognosis. The GCS-Net suggested the importance of genes (UBE2C, JAK2, RAD21, CEP250, NUP210, PTPN1, CDC27, NINL, NUP188, and PLK4) and biological pathways (Mitotic Anaphase, Resolution of Sister Chromatid Cohesion, and SUMO E3 ligases) to GC, which is consistent with the results revealed in biological- and medical-related studies of GC. Conclusion. The GCS-Net is an interpretable deep neural network built using biological pathway information whose structure represents a nonlinear hierarchical representation of genes and biological pathways. It can not only accurately predict the prognosis of GC patients but also suggest the importance of genes and biological pathways. The GCS-Net opens up new avenues for biological research and could be adapted for other cancer prediction and discovery activities as well.
A Face Recognition Method Based on Multifeature Fusion
Authors: Ye Shengxi
Published: September 2022

Face recognition is widely used in daily life and has an important supporting role for social management. Face recognition is mainly based on historical accumulation data to confirm people’s identities in unknown samples and obtain valuable intelligence information. For the problem of face recognition, this paper proposes a multifeature joint adaptive weighting algorithm framework. In this method, a number of different types of features are first used to describe the face characteristics. The selected features should be as complementary as possible, and the overlap redundant information should be reduced to the greatest extent, so as to ensure the performance and efficiency of multifeature fusion. In the classification stage, based on the joint sparse representation model, the multiple types of features are characterized, and their reconstruction error vectors for the corresponding features of the test sample are calculated. The joint sparse representation model can examine the correlation between different types of features, thereby improving the accuracy of representation and fully integrating the advantages of multiple types of features. At the same time, in view of the simple superposition of reconstruction errors in the traditional sparse representation model, this paper uses a random weight matrix to comprehensively consider the weighted reconstruction errors under different weight conditions, so as to obtain statistical decision quantities for the final decision. The framework proposed in this paper can adapt to different multifeature combinations and has good practicability. In the experiment, training and test sets are constructed based on public face image data sets to test the proposed method. The experimental results show that the method in this paper is more effective and robust compared with some present methods for face recognition.
[Retracted] Susceptibility Loci in SLC15A1, UGT1A3, and CWC27 Genes Associated with Bladder Cancer in the Northeast Chinese Population
Authors: Wu Peihong , Guo Yaoxing
Published: September 2022

Bladder cancer (BCa) is an increasingly severe clinical and public health issue. Therefore, we aim to investigate BCa susceptibility loci in the Chinese population. In this study, 487 BCa patients and 563 controls were recruited from the First Affiliated Hospital of China Medical University from July 2015 to September 2020. A total of ten single‐nucleotide polymorphisms (SNPs) in solute carrier family 15 member 1 (SLC15A1), CWC27 spliceosome associated cyclophilin (CWC27), or UDP glucuronosyltransferase family 1 member A3 (UGT1A3) genes were genotyped. The associations between the candidate SNPs and BCa were analyzed using genotype and haplotype analysis. The results demonstrated that Rs4646227 of SLC15A1 has a significant association with BCa. The patients with CG (OR =2.513, p < 0.05) and GG (OR =2.859, p < 0.05) genotypes had an increasing risk of BCa compared with the CC genotype. For the CWC27 gene, genotypic frequency analysis revealed that the GT or TT genotype of rs2042329 and the CT or TT genotype of rs1870437 were more frequent in BCa patients than those in the control group, indicating that these genotypes were associated with a higher risk of BCa (all p < 0.05). Haplotypes of SLC15A1, UGT1A3, and CWC27 genes found that the C‐C‐C haplotype of SLC15A1 was associated with a lower risk of BCa while the C‐G‐C haplotype was associated with a higher risk. For the UGT1A3 gene, a moderate protective effect was observed with the most frequent T‐T‐C haplotype, and for the CWC27 gene, most of the haplotypes showed no association with BCa, except the G‐G‐C‐T haplotype (order of SNPs: rs2042329‐rs7735338‐rs1870437‐rs2278351, OR =0.81, p =0.038). In sum, this study indicated that rs2042329 and rs1870437 in the CWC27 gene and rs4646227 in the SLC15A1 gene are independent indicators for BCa risk in Chinese people. Further large‐scale studies are required to validate these findings. Also, this study provided the theoretical basis for developing new therapeutic drug targeting of BCa.
Construction of a Random Matrix Model of Curriculum System Based on Digital Technology in the Context of Smart Education
Authors: Chen Jing
Published: September 2022

This paper adopts the method of digital technology fused with a random matrix to conduct in-depth research and analysis on the curriculum system under the context of smart education and designs a corresponding model for practical use. Firstly, we analyze the status of digital learning research, take the digital teaching model based on independent inquiry as to the basis of teaching design, and carry out digital-based teaching experiments under the premise of fully examining the actual teaching conditions. The digital learning platform is designed to meet the teaching model, platform design, platform application, and implementation of the school, and the digital learning platform is designed and developed through PHP technology. Then, the matrix filling algorithm is used to fill in some of the missing data in the observation matrix to obtain the complete data matrix, and the Hankel matrix inverse transformation is used to finally obtain the reconstructed original signal, thereby forming the ability of innovative works. It is an important aspect of cultivating students’ innovative spirit and practical ability in the development of educational informatization. Ultimately, students use the platform to try out and be able to learn the knowledge. The experimental class and the control class experimented with a quasi-experimental research method, the experimental class used a digital teaching mode, and the control class used a traditional IT teaching mode. The digital learning ability of students was measured by a digital learning ability measurement scale before and after the experiment, and then the data before and after the experiment were analyzed by horizontal and vertical comparison to verify whether the digital teaching model can effectively cultivate junior high school students compared with the traditional teaching model. The digital learning ability of junior high school students was verified.
Low Testosterone Level and Risk of Adverse Clinical Events among Male Patients with Chronic Kidney Disease: A Systematic Review and Meta-Analysis of Cohort Studies
Authors: Li Li , Ju Huixiang , Jin Hao , Chen Hongmei , Sun Mingzhong , Zhou Zhongwei
Published: September 2022

The phenomenon of low testosterone level is extremely common in male patients with chronic kidney diseases (CKDs). This meta-analysis aimed to evaluate whether the low circulating testosterone could independently predict adverse outcomes among male patients with chronic kidney diseases (CKDs). The data till May 2022 were systematically searched from Pubmed, Web of Science, and Embase from inception. Studies meeting the PICOS (population, intervention/exposure, control/comparison, outcomes, and study design) principles were included in this meta-analysis. Study-specific effect estimates were pooled using fixed-effects (I2 > 50%) or random-effects models (I2 < 50%). Ultimately, 9 cohort studies covering 5331 patients with CKDs were involved in this meta-analysis. The results suggested that per 1-standard deviation (SD) decrease in total testosterone independently increased the risk of all-cause mortality by 27% [hazard risk (HR) 1.27, 95% confidence interval (CI) 1.16–1.38], cardiovascular mortality by 100% (HR 2.00, 95% CI 1.39–2.86), cardiovascular events by 20% (HR 1.20, 95% CI 1.04–1.39), and infectious events by 41% (HR 1.41, 95% CI 1.08–1.84). Besides, with per 1-SD decrease in free testosterone, the risk of overall adverse events increased by 66% (HR 1.66, 95% CI 1.34–2.05). Stratified analyses indicated that the negative relationship of the total testosterone with all-cause death risk was independent of factors involving age, race, body mass index, diabetes, hypertension, C-reactive protein, creatinine, and sex hormone binding globulin. In conclusion, it was identified that low endogenous testosterone could serve as an independent predictor of adverse clinical events among male patients with CKDs.
Development and Validation of a Novel Nomogram to Predict the Risk of Intervertebral Disc Degeneration
Authors: Li Fudong , Sun Xiaofei , Wang Yuan , Gao Lu , Shi Jiangang , Sun Kaiqiang
Published: September 2022

Intervertebral disc degeneration (IVDD) has been a complex disorder resulted from genetic and environmental risk factors. The aim of this study was to identify the risk factors associated with IVDD in orthopaedic patients and develop a prediction model for predicting the risk of IVDD. A total of 309 patients were retrospectively included in the study and randomly divided into the training group and the validation group. The least absolute shrinkage and selection operator regression (LASSO) and the univariate logistic regression analysis were used to optimize factors selection for the IVDD risk model. Multivariable logistic regression analysis was used to establish a predicting nomogram model incorporating the factors. In addition, discrimination, calibration, and clinical usefulness of the nomogram model were evaluated via the C-index, receiver operating characteristic (ROC) curve, calibration plot, and decision curve analysis (DCA). Then, based on the results above, the relationship between IVDD and angiotensin II (AngII) level in peripheral blood was examined prospectively. The predictors of the nomogram include age, sex, hypertension, diabetes, gout, working posture, and exercising hours per week. The

C

-index values of the training and validation groups were 0.916 (95% CI, 0.876-0.956) and 0.949 (95% CI, 0.909-0.989), respectively, which indicated that the model displayed good discrimination. In addition, the area under the curve (AUC) values of the ROC curve of the training and the validation group were 0.815 (95% CI, 0.759-0.870) and 0.805 (95% CI, 0.718-0.892), respectively, revealing the satisfactory discrimination performance of the model. The prospective investigation showed that the average AngII level in the degenerated group (

97.62
±
44.02

 pg/mL) was significantly higher than that in the nondegenerated group (

52.91
±
9.01

 pg/mL) (

p
<
0.001

). This present study explored the risk factors for IVDD and established a prediction model, which would effectively predict the risk of IVDD. In addition, based on the prediction model, AngII was revealed to be a potentially auxiliary clinical diagnostic marker for IVDD.
The Ameliorative Role of Eugenol against Silver Nanoparticles-Induced Hepatotoxicity in Male Wistar Rats
Authors: Yousef Hany N. , Ibraheim Somaya S. , Ramadan Ramadan A. , Aboelwafa Hanaa R.
Published: September 2022

Background. Silver nanoparticles (AgNPs) utilization is becoming increasingly popular. The existing investigation evaluates the ameliorative impact of eugenol (Eug) against the toxic influences of AgNPs on rats’ liver. Methods. Sixty adult male rats were enrolled equally into control, Eug (100 mg kg-1 orally), AgNPs-low dose (1 mg kg-1 i.p), AgNPs-high dose (2 mg kg-1 i.p), Eug + AgNPs-low dose (

100
 
mg
 
k

g

−
1

 
orally
+
1
 
mg
 
k

g

−
1

 
i
.
p

), and Eug + AgNPs high dose (

100
 
mg
 
k

g

−
1

 
orally
+
2
 
mg
 
k

g

−
1

 
i
.
p

). All the groups were treated daily for 30 days, subsequently serum aspartate transaminase (AST), alanine transaminase (ALT), alkaline phosphatase (ALP), total protein, total albumin, lactate dehydrogenase (LDH), total oxidative capacity (TOC), malondialdehyde (MDA), tumor necrosis factor-alpha (TNF-α), total antioxidant capacity (TAC), and interleukin 6 (IL-6) levels were measured; hepatic tissues superoxide dismutase (SOD), catalase (CAT), reduced glutathione (GSH), and glutathione peroxidase (GPx) levels were evaluated; histopathology and histomorphometry were documented in the liver of all groups; and Bcl-2, P53, Caspase-3, and TNF-α reactive proteins were also immunohistochemically detected. Results. AgNPs significantly triggered oxidative stress in hepatic tissues, characterized by elevated levels of AST, ALT, ALP, LDH, TOC, MDA, TNF-α, and IL-6 correlating with considerable decline in total protein, total albumin, TAC, SOD, CAT, GSH, and GPx. These changes were paralleled with histopathological alterations remarkable by devastation of the ordinary hepatic structure, with decrease in the numbers of normal hepatocytes, elevation in the numbers of necrotic hepatocytes, periportal and centrilobular inflammatory cells, deteriorated Kupffer cells, and dilated/congested central and portal veins. Alongside, a marked diminution in Bcl-2 immunoreactivity and a significant elevation in P53, Caspase-3, and TNF-α immunoreactivities were recorded. Supplementation of AgNPs-treated animals with Eug reversed most of the biochemical, histopathological, and immunohistochemical changes. Conclusion. This study proposed that Eug has an ameliorative effect against AgNPs-induced hepatotoxicity.