bluuebunny/crossref_metadata_2025 huggingface dataset:
[Retracted] Innovate a Standard for the Future Model of Nursing Care at Medical‐Surgical Units in Najran University
Authors: Mahdy Shalby Abeer Y. , AlThubaity DaifAllah D.
Published: July 2022

Aim. Innovate a standard for the future model of nursing care at medical‐surgical units in Najran University through a training program for the standard of the future model evaluation on studied nurses’ knowledge, attitude about innovation standards, and innovative behavior among nurses. Methods. A quasi‐experimental research was used to achieve the study’s goal; the research was carried out at Najran University Hospital at Najran, in the medical and surgical units, as well as outpatient clinics. The sample is a convenience type; 100 nurses were used. Tool. A structured questionnaire sheet was used for data collection that includes nurses’ knowledge, attitude, and individual innovative scale. Results. This reveals the studied nurses related to their individual innovative scale pre‐ and postintervention. Concerning resistance to change, the mean of them preintervention is x ̅ SD 9.08 ± 2.60. Concerning opinion leadership, the mean of them postintervention is x ̅ SD 14.32 ± 3.16. There is a highly significant difference (p < 0.01∗∗) preintervention as regards all domains listed. Conclusion. The educational program significantly enhances nurses’ knowledge and attitude, according to our present study. Nurses’ innovative skills are also improved by enhancing their knowledge and attitude. Before and after the educational program was implemented, there was a highly positive linear association between the nurses’ knowledge, attitude, and innovative skills at p < 0.01.
Boundary Integral Technique of 2nd Order Partial Differential Equation by Using Radial Basis
Authors: Asghar A. , Ahmad M. O. , Bashir M. N. , Muhammad Taseer , Khan Sami Ullah , Ramzan M.
Published: July 2022

The solution of second order partial differential equation, with continuous change in coefficients by the formation of integral equation and then using radial basis function approximation (RBSA), has been developed in this paper. Use of boundary element method (BEM), which gives the solution of heat or mass diffusion in non-homogenous medium with function varying smoothly in space is also the part of this article. Discretization of boundary of integral domain instead of entire domain of the problem concerned is also the distinction of the recent work. The numerical solution of some problems with known value of the variable has also been included at the end.
Medical College Education Data Analysis Method Based on Improved Deep Learning Algorithm
Authors: Wei Lin , Yu Zhang , Qinge Zhang
Published: July 2022

Deep learning (DL) has become a popular study topic in the field of artificial intelligence (AI) in recent years, due to its significant role in various application areas. It leverages supercomputing capacity in the era of big data to uncover the high-level abstract ideas in the original dataset and serves as decision support in the application sector by increasing the number of channels and the scale of parameters. This study designs and implements a heterogeneous medical education data analysis system based on DL technology. The proposed system adopts DL technology to model, analyzes the heterogeneous medical education data, uses the decision-level fusion strategy for the data model, and designs and implements the voting method and the weighting method. The decision value is statistically calculated to realize the improved DL algorithm for the medical college education data analysis method. In addition, this study also uses the Alzheimer’s disease public dataset with various structures and modalities of medical education data to compare and evaluate the systematic data preprocessing model performance and the effect of fusion methods. The experimental result validates the proposed model’s performance, demonstrating that the way of evaluating complete heterogeneous multimodal data is not only closer to the genuine diagnostic process but also aids clinicians in grasping the patient’s entire state and obtaining outcomes. Further, the essential ideas and implementation techniques of convolutional neural network (CNN) and stacked autoencoder as well as its application cases in medical college education data analysis are thoroughly explained.
A Systematic Analysis of Machine Learning and Deep Learning Based Approaches for Plant Leaf Disease Classification: A Review
Authors: Kumar Raj , Chug Anuradha , Singh Amit Prakash , Singh Dinesh
Published: July 2022

Crops’ production and quality of yields are heavily affected by crop diseases which cause adverse impacts on food security as well as economic losses. In India, agriculture is a prime source of income in most rural areas. Hence, there is an intense need to employ novel and accurate computer vision-based techniques for automatic crop disease detection and their classification so that prophylactic actions can be recommended in a timely manner. In literature, numerous computer vision-based techniques by utilizing divergent combinations of machine learning, deep learning, CNN, and various image-processing techniques along with their associated merits and demerits have already been discussed. In this study, we systematically reviewed recent research studies undertaken by a variety of scholars and researchers of fungal and bacterial plant disease detection and classification and summarized them based on vital parameters like type of crop utilized, deep learning/machine learning architecture used, dataset utilized for experiments, performance matrices, types of disease detected and classified, and highest accuracy achieved by the model. As per the analysis carried out, in the category of machine learning-based approaches, 70% of studies utilized real-field plant leaf images and 30% utilized laboratory condition plant leaf images for disease classification while in the case of deep learning-based approaches, 55% studied employed laboratory-conditioned images from the PlantVillage dataset, 25% utilized real-field images, and 20% utilized open image datasets. The average accuracy attained with deep learning-based approaches is quite higher at 98.8% as compared to machine learning-based approaches at 92.2%. In the case of deep learning-based methods, we also analyzed the performances of pretrained and training from scratch models that have been utilized in various studies for plant leaf disease classification. Pretrained models perform better with 99.64% classification accuracy compared to training from scratch models which achieved 98.64% average accuracy. We also highlighted some major issues encountered in the computer vision-based disease detection and classification approach used in literature and provided recommendations that will help and guide researchers to explore new dimensions in crop disease recognition.
A Strangulated Congenital Diaphragmatic Bochdalek Hernia Diagnosed in an Adult
Authors: Warsinggih Warsinggih , Uwuratuw Julianus Aboyaman , Arsyad Arham , Faruk Muhammad
Published: July 2022

Although Bochdalek hernias are uncommon in adults and difficult to diagnose, such congenital diaphragmatic hernias (CDHs) are some of the most serious malformations among newborns. In particular, CDHs are accompanied by high mortality and marked disability later in life due to concomitant morbidity (i.e., caused by pulmonary lung hypoplasia and persisting pulmonary hypertension of neonates) and require long-lasting neonatal treatment in an intensive care unit. Late-diagnosed CDHs are extremely rare and always show small defects that justify a better prognosis than CDHs with large defects. In most cases, such CDHs go undiagnosed due to their mild, delayed symptoms. In the case described here, an 18-year-old Asian male presented with abdominal pain and a bowel contour in the epigastric region and left upper quadrant. A chest X-ray and thoracoabdominal computerized tomography scan confirmed the diagnosis of bowel obstruction due to a left diaphragmatic hernia. Moreover, a defect was revealed in the posterolateral left diaphragm, and the transverse colon, spleen, and half of the stomach had herniated through it. A segmentectomy was performed on the transverse colon, followed by an end-to-end anastomosis, a diaphragmatic plasty, and the placement of an intrapleural catheter. In conclusion, diagnosing a diaphragmatic hernia before surgery can be difficult due to its rarity and wide range of symptoms. Although prenatal diagnosis using ultrasonography is possible in up to 80% of fetuses, that method may not be available in all regions in Indonesia or in all countries, where doctors thus continue to face a diagnostic challenge when dealing with CDHs.
Salmonella enterica Serovar Typhimurium and Enteritidis Isolated from Raw Shrimp in Bangladesh: An Investigation Based on Molecular Characteristics, Survival, Virulence, Antibiotic Resistance, and Biofilm Formation Attributes
Authors: Das Prosanto Kumar , Mandal Ananta , Rahman Md. Mizanur , Sarkar Shovon Lal , Jahid Iqbal Kabir , Hossain Md. Anwar , Alam A. S. M. Rubayet Ul , Roy Pravas Chandra
Published: July 2022

Shrimp is the white gold of Bangladesh, with the second-highest income source from exporting to foreign countries. Contamination with Salmonella spp. is now one of the significant issues for Bangladesh to export. Proper characterization of the salmonella pathogen is thus necessary to avoid undesirable losses due to the rejection of exported shrimp. In Bangladesh, the present condition of raw shrimp contamination with pathogenic Salmonella serovars and their survival/virulence properties was not adequately characterized. In this study, we collected 43 raw shrimps as samples from different farms in Jashore, Khulna, and Sathkhira regions. We then maintained standard cultural and biochemical protocols for isolating Salmonella strains, followed by the molecular identification of particular Salmonella serovars. The standard method for checking its credibility to form biofilm in 0–10% NaCl, tolerate acid/bile stress likewise in the gastrointestinal tract, and resist antimicrobial pressure was performed individually with the particular pathogenic strains. Our results successfully identified eleven Salmonella strains with three typhimurium serovars and three enteritidis serovars, which have biofilm-forming capability up to 4–8% NaCl, acid/bile habituation alike stomach/small intestine of humans, and resistance against necessary antibiotics generally used in treating human and poultry infection signifying the impending danger in the shrimp industry. While previous studies of Bangladesh successfully isolated Salmonella only presumptively, our research focused mainly on molecular characterization of the human Salmonella pathogen along with important survival and virulent attributes, such as biofilm formation, acid/bile tolerance, and antibiotic resistance of selected S. typhimurium and S. enteritidis strains. Further study with more sampling will be necessary to confer the transmission route of the pathogen from the natural reservoir to the shrimp industry.
[Retracted] Risk Factor Analysis of Hepatic Encephalopathy and the Establishment of Diagnostic Model
Authors: Chen Fangfang , Li Jing , Zhang Wenjie , Mao Caixia , Wang Yanxia , Qu Yan , Tian Shuju , Li Fanhong
Published: July 2022

To identify laboratory diagnostic indicators of hepatic encephalopathy (HE), the present study established a HE diagnostic model to explore the diagnostic value of serum homocysteine, lactic acid, procalcitonin, and bile acid levels in HE identification. 371 patients with liver cirrhosis were selected as research objects, who were admitted to the Department of Hepatic Diseases, Affiliated Hospital of Northwest Minzu University from August 2019 to August 2020. The Spearman correlation results indicated that between lactic acid, procalcitonin, bile acid, serum homocysteine, and HE, the coefficients were ‐0.15, 0.41, 0.29, and ‐0.19, respectively. Univariate and multivariate analysis methods were adopted for inpatient analysis to identify the influencing factors of HE occurrence, and the diagnosis of the HE identification model was subsequently constructed. The univariate logistic regression showed that risk of developing HE increased as bile acid level (P = 0.00434) and serum homocysteine (P = 0.058) increased. Multivariate logistic regression diagnostic model of bile acid level and serum homocysteine revealed that the AUC value of the area under the ROC curve was 0.7201, indicating that the diagnostic model produced a satisfactory evaluation effect. The model formula referred logistic (P) = −2.4544 + 0.0117 bile acid levels + 0.0198 serum homocysteine. In this study, the HE diagnostic model was established using logistic regression analysis, which could benefit patients in early HE differential diagnosis. Particularly, combined detection of serum homocysteine and bile acid levels was considered to be more significant.
Research on Network Security Situational Awareness Based on Crawler Algorithm
Authors: Wu Xu , Wei Dezhi , Vasgi Bharati P. , Oleiwi Ahmed Kareem , Bangare Sunil L. , Asenso Evans
Published: July 2022

Network security situation awareness is a critical basis for security solutions because it displays the target system’s security state by assessing actual or possible cyber-attacks in the target system. Aiming at the security and stability of global information flow, this paper studies the perception and measurement of the overall situation of network security. Through the Scrappy web crawler framework, data were collected from several Zhiming network security event websites, and based on the vulnerability database of China Computer Network Intrusion Prevention Center, the network security event database was designed and established, which enriched the data of situational awareness research. This study investigates the analysis and processing of network security events, a crucial parameter in the stage of security insight and perception, and builds and implements a text-based network security event analysis tool. By designing a network security event analysis tool based on text processing, the data cleaning of network security time text information is completed, and a set of network security event processing solutions with high applicability and comprehensiveness are formed. Statistical experimental results show that the network security event database built based on the crawler algorithm contains 43,848 pieces of data, which increases the capacity by 12.79% and 29.33% compared with the traditional algorithm, and reduces the reading time by 63.5% and 87.2%.
Double-UV Photoionizaion Detector with Graphene Oxide-Coated Electrodes
Authors: Zhou Qi , Zhang Xu , Ma Xu , Zhang Sixiang
Published: July 2022

The structure of a photoionization detector was optioned and researched. In order to solve the problem of the photoionization detector’ lamp surface residue interference, a new structure of the self-cleaning double-UV detector was adopted. At the same time, the air flow field of the detector was simulated by the finite element method. Through analyzing the results of the simulation experiment, further optimization of the gas channel for the microdetector was carried out, and the ionization chamber with axial flow structure was finally chosen. The new nanomaterial, graphene oxide was used to modify the surface of the collector plate of detector to improve the gas sensitivity and sensitivity of the photoionization detector. Through the experimental analysis, the performance indexes of detector were described in detail. The minimum detection limit of the detector is

2.5
×

10

−
7

. The linearity response of the detector was analyzed, and the linear correlation coefficient reaches 0.993. The experimental results show that the double-UV detector can improve the overall gas sensing characteristics and provide an ideal detection unit for volatile organic compound (VOC) gas detection.
Direct Position Determination for Noncooperative Source with Fast Moving Receivers
Authors: Ye Yun-Xia , Lu An-Nan , Huang Kai , You Ming-Yi , Yang Xin , Lou Cai-Yi
Published: July 2022

The problem of position estimation for a noncooperative source has always been widely discussed in the field of wireless communication. Direct position determination (DPD) for a noncooperative source with fast moving receivers is discussed in this paper. The sinc function is used to reconstruct the signals, which is an important step in DPD for wideband signals. A DPD method based on the baseband signal is proposed which is more practical in communication signal with high carrier frequency. And based on the proposed DPD method, a DPD method for multiple noncooperative stationary sources by single-channel receivers is presented. In order to evaluate the performance of the proposed DPD method, the Cramér-Rao lower bound (CRLB) for DPD based on baseband signal is derived. Several numerical investigations are carried out to evaluate the performance of the proposed method.
Fuzzy PI Control of Trapezoidal Back EMF Brushless DC Motor Drive Based on the Position Control Optimization Technique
Authors: Mary D. Magdalin , Kumar C. , Xavier Felix Joseph , Rashad Sara A. , Fayek Hady H. , Ravichandran Naganthini , Barua Sourav
Published: July 2022

In this article, a novel methodology has been created based on optimized fuzzy PI controller using position control optimization (PCO). This proposed PCO algorithm ensures better control of brushless direct current motor (BLDCM) in order to reduce steady-state error and oscillation as well as improve the system response by optimizing the speed and position of rotor. The suitability of this technique has been simulated in different stages, so as to infer the optimization in results. The main motivation of this paper is to get better efficiency and optimum response from BLDCM, by comparing its performance characteristics with existing methods. The detailed investigation research through simulation is carried out using MATLAB/Simulink. However, in order to obtain well-defined results, the PCO technique was applied and the performance obtained was highly optimized than previously applied techniques. Through the simulations, the proposed approach can outperform the existing approaches such as PSO and moth-flame algorithm (MFA).
Wind Effects on Rectangular and Triaxial Symmetrical Tall Building Having Equal Area and Height
Authors: Verma Astha , Meena Rahul Kumar , Dubey Hrishikesh , Raj Ritu , Anbukumar S.
Published: July 2022

The study aims to investigate wind effects on the equal area and the same height building model having the plan cross‐sectional shape in the form of regular and irregular shape bulidings. The ratio of modification in the cross‐sectional shape is kept same for regular and irregular shaped models because limited studies are available for such type of comparison. The responses of the structure to resist the wind load is increased by applying these modifications in the corner configuration such as corner cut, chamfer, and fillet in the plan shape of the structure. The numerical study is performed using ANSYS CFX and wind incidence angle varies in the range of 0° to 180° at the interval of 15°. The results of velocity and pressure distribution are presented in the form of pressure contours and wind force coefficients for all four‐building models which are presented in the form of a graph. The comparison of numerical simulation results on two models are compared with the different international standards and with the experimental results. The regular shape with a corner cut and a “Y”‐shaped structure with a fillet corner model performed the best among all models for resisting overall wind force. The results of pressure distribution of all four models are presented in the form of pressure contours for 0° and 90° wind angles.
Study on the Performance Optimization Algorithm Strategy of Resource and Environment Audit Based on Computer Network Technology
Authors: Dai Yongjuan
Published: July 2022

In order to better control and repair resource and environmental problems, the state has invested a lot of manpower, material resources, and funds and issued corresponding ecological and environmental protection measures. As the national environmental supervision mechanism, the resource and environmental audit department is responsible for the supervision of national environmental governance. With the continuous development of computer technology, it brings convenience to resource and environment audit and improves the extraction of data processing, storage, and processing capacity. Because there are many departments involved in resource and environment audit, the cooperation between different departments will inevitably have errors. Using computer technology to mine the relevance of relevant data is conducive to the cooperation between departments. This study builds relevant algorithms and uses new technologies to collect data so as to improve the efficiency of audit work and better promote the construction of ecological civilization.
Recommending Crowdfunding Project: A Graph Kernel-Based Link Prediction Method for Extremely Sparse Implicit Feedback
Authors: Yin Pei , Chen Ya , Wang Huan , Gan Hongcheng , Zhou Ye
Published: July 2022

It is a critical task to provide recommendation on implicit feedback, and one of the biggest challenges is extreme data sparsity. To tackle the problem, a graph kernel-based link prediction method is proposed in this paper for recommending crowdfunding projects combining graph computing with collaborative filtering. First of all, an investor-project bipartite graph is established based on transaction histories. Then, a random walk graph kernel is constructed and computed, and a one-class SVM classifier is built for link prediction based on implicit feedback. At last, top N recommendations are made according to the ranking of investor-project pairs. Comparative experiments are conducted and the results show that the proposed method achieves the best performance on extremely sparse implicit feedback and outperforms baselines. This paper is of help to improve the success rate of crowdfunding by personalized recommendation and is of significance to enrich the research in recommendation systems.
Hybrid Graph Neural Network Model Design and Modeling Reasoning for Text Feature Extraction and Recognition
Authors: Huang Xuxiang , Qiu Dong , Xiang Chen , Chen Hewei
Published: July 2022

Natural language processing is an important branch of deep learning. In particular, the classification of short texts is one of the main tasks of computer linguistics, because it ensures the security of information. Therefore, this paper reviews the text classification methods for the first time, aiming at comparing the modern methods to solve the text classification problems, determine the trend in this direction, and select the best algorithm to be applied to research and business tasks. In this paper, with the help of the emerging algorithm in the field of deep learning, a web domain knowledge text classification method based on feature words is developed with the support vector machine (SVM) as the basic classification algorithm. Two datasets representing basic research disciplines and emerging research fields are selected to verify the proposed research framework. Experiments show that the performance of this method is improved by 3% compared with the benchmark method.
Application of Ultrahigh Voltage Transformer Oil Purification Software Technology
Authors: Song Chunran , Hu Xuechao , Xue Shouhong , Wu Lixia
Published: July 2022

In order to discuss the purification software technology of ultrahigh voltage transformer oil, the index variation trend of antioxidation stability test after each oil adsorption was investigated, and the relationship between the adsorption times and antioxidation stability parameters was obtained. It was proved that the antioxidation stability of the oil was getting better and better with the increase of adsorption times. The composition of hydrocarbon of new oil and recycled oil is analyzed by infrared spectroscopy. The composition of hydrocarbon of new oil and recycled oil is very similar to that of new oil, and their molecular composition structure has not changed much. The experimental results show that: according to dLT929-2005, the absorbance of samples at 1610∼720 cm−1 was measured, and the values of

C

A

,

C

N

and

C

P

were obtained. A 1 mmNaCl liquid pool is used. Sample ① is the new oil; ② is the last simulated oil regeneration; ③ is the D111 overhaul recycled oil; ④ is again the living oil. It is proved that the composition of the oil is more reasonable and can be reused for adsorption and regeneration. In addition, the aromatic carbon value

C

A

of oil after adsorption treatment decreases due to natural consumption, and new oil can be added appropriately to increase the carbon value

C

A

.
Predictive Model and Analysis of Psychological Depression Based on College Students’ Behavior Data Mining
Authors: Qu Dongchen , Guan Qinghua
Published: July 2022

Contemporary college students face all kinds of pressure and are easy to cause psychological problems. In order to make students and schools do a good job in preventing psychological depression, this paper proposes a student depression prediction model based on college students’ behavior data mining. Due to the shortcomings of large error and low reliability of prediction results in the traditional psychological depression prediction model, it is impossible to carry out large-scale psychological depression data analysis. In order to solve the defects of traditional psychological depression prediction model and improve the reliability of psychological depression prediction results, a psychological depression prediction model based on data mining technology is proposed. Firstly, the sensor is used to collect the signals related to psychological depression, and the signals are denoised to obtain high-quality psychological depression signals; then, the features are extracted from the psychological depression signals, and the support vector machine in data mining technology is used to train and learn the relationship between the features and the types of psychological depression, so as to construct the prediction model of psychological depression; finally, the simulation experiment of psychological depression prediction is carried out on MATLAB platform. The results show that the prediction accuracy of psychological depression of the traditional model is less than 85%, the prediction accuracy of psychological depression of the proposed model is more than 90%, and the time of psychological depression prediction modelling is reduced, which can meet the development trend of modern psychological depression prediction and analysis.
The Transition and Spread of a Chaparral Crown Fire: Insights from Laboratory Scale Wind Tunnel Experiments
Authors: Cobian-Iñiguez Jeanette , Aminfar Amir Hessam , Saha Shusmita , Awayan Kyle , Weise David R. , Princevac Marko
Published: July 2022

Fire occurring in the chaparral behaves as a crown fire, a dual-layer fire that typically ignites in a dead surface fuel layer and transitions to an elevated live crown layer where it continues to spread. In chaparral fuels including chamise, a dominant species in southern California, flame transition to live crown fuels is associated with higher spread rates and greater fire intensity. Despite the relative importance of surface-to-crown transition and crown fire spread, most fire models represent chaparral fire as surface fire, therefore omitting key behavior processes driving this fire system. The purpose of this study was to characterize transition and spread behavior in chaparral fires modeled experimentally as crown fires. We examined heat release rate in the surface and crown fuel layers, time to transition, flame height, and rate of spread in wind-driven and nonwind-driven fires at two crown base heights. Our results showed that wind increased heat release rate, rate of spread, and flame height. A marked increase in heat release rate was observed in wind-driven fires, where adding wind produced an increase from 328 kW to 526 for a crown base height of 0.6 m and from 243 kW to 503 kW for a crown base height of 0.7 m. Further, crown base height served to decrease heat release rate and rate of spread for wind-driven and nonwind-driven fires.
Prediction of the Active Components and Mechanism of Forsythia suspensa Leaf against Respiratory Syncytial Virus Based on Network Pharmacology
Authors: Wang Xiaoxue , Wang Ping , Du Haitao , Li Na , Jing Tianyuan , Zhang Ru , Qi Wanying , Hu Yanan , Liu Tianyu , Zhang Lanxin , Xu Nan , Wang Yi , Zhang Huimin , Ding Xiaoyan
Published: July 2022

Objective. Forsythia suspensa leaf (FSL) has been used as a health tea in China for centuries. Previous experiments have proved that FSL extract has a good effect on the antirespiratory syncytial virus (RSV) in vitro, but its exact mechanism is not clear. Therefore, this study aims to determine the active components and targets of FSL and further explore its anti-RSV mechanism. Methods. UPLC-Q-Exactive-MS was used to analyze the main chemical components of FSL. The compound disease target network, PPI, GO, and KEGG were used to obtain key targets and potential ways. Then, the molecular docking was verified by Schrödinger Maestro software. Next, the cell model of RSV infection was established, and the inhibitory effect of each drug on RSV was detected. Finally, western blotting was used to detect the effect of the active components of FSL on the expression of PI3K/AKT signaling pathway-related protein. Results. UPLC-Q-Exactive-MS analysis showed that there were 67 main chemical constituents in FSL, while network pharmacological analysis showed that there were 169 anti-RSV targets of the active components in FSL, involving 177 signal pathways, among which PI3K/AKT signal pathway played an important role in the anti-RSV process of FSL. The results of molecular docking showed that cryptochlorogenic acid, phillyrin, phillygenin, rutin, and rosmarinic acid had higher binding activities to TP53, STAT3, MAPK1, AKT1, and MAPK3, respectively. In vitro experiments showed that phillyrin and rosmarinic acid could effectively improve the survival rate of RSV-infected cells, increase the expression level of PI3K, and decrease the expression level of AKT. Conclusion. The active ingredients of FSL, phillyrin, and rosmarinic acid can play an anti-RSV role by inhibiting PI3K/AKT signaling pathway. This study provides reliable theoretical and experimental support for the anti-RSV treatment of FSL.
Information Construction of Sports Tourism in Haikou City under the Background of Internet
Authors: Zhang Yu
Published: July 2022

So far, there are few reports on the evaluation and analysis of sports tourism resources in Haikou by the combination of qualitative evaluation and quantitative evaluation. This paper comprehensively uses Delphi method, questionnaire survey method, analytic hierarchy process, mathematical statistics, and other research methods to take Haikou sports tourism resources as the research object. Through the field investigation of Haikou sports tourism resources, this paper comprehensively evaluates Haikou sports tourism resources by combining qualitative and quantitative evaluation methods, in order to improve and innovate the theoretical level of Haikou sports tourism resource evaluation and provide data support and practical basis for the development and utilization of sports tourism resources in Haikou, so as to promote the sustainable and efficient development of sports tourism industry in Haikou. The evaluation results of sports tourism resources in Haikou are divided into four parts: advantages, disadvantages, opportunities, and challenges. It is considered that the advantage of sports tourism resources in Haikou is the scarcity of resources, unique charm, exciting events, and strong appreciation. The disadvantage is that the popularity of sports tourism resources in Haikou is low, and the suitable travel period is short. The opportunity is that the natural environmental conditions and the traditional sports characteristics of ethnic minorities are prominent, the cooperation with surrounding cities in sports tourism is deepened, and the tourist market potential is huge. The threat is that the market competition of homogeneous sports tourism products is fierce, the conditions of sports tourism human resources are poor, the publicity methods are old, and the development of local air transportation is backward.
Characterization of Butyrate‐Resistant Colorectal Cancer Cell Lines and the Cytotoxicity of Anticancer Drugs against These Cells
Authors: Nittayaboon Kesara , Leetanaporn Kittinun , Sangkhathat Surasak , Roytrakul Sittiruk , Navakanitworakul Raphatphorn
Published: July 2022

Colorectal cancer (CRC) is the third most common cancer worldwide. The gut microbiota plays a critical role in homeostasis and carcinogenesis. Butyrate, a short‐chain fatty acid produced by the gut microbiota, plays a role in intestinal homeostasis and acts as an anticancer agent by inhibiting growth and inducing apoptosis. However, microbiota studies have revealed an abnormally high abundance of butyrate‐producing bacteria in patients with CRC and indicated that it leads to chemoresistance. We characterized butyrate resistance in HCT‐116 and PMF‐K014 CRC cells after treatment with a maximum butyrate concentration of 3.2 mM. The 50% inhibitory concentration of butyrate was increased in butyrate‐resistant (BR) cells compared with that in parental (PT) cells. The mechanism of butyrate resistance was initially investigated by determining the expression of butyrate influx‐ and drug efflux‐related genes. We found the increased expression of influx‐ and efflux‐related genes in BR cells compared with that in PT cells. Proteomic data showed both identical and different proteins in PT and BR cells. Further analysis revealed the crossresistance of HCT‐116 cells to metformin and oxaliplatin and that of PMF‐K014 cells to 5‐fluorouracil. Our findings suggest that the acquisition of butyrate resistance induces the development of chemoresistance in CRC cells, which may play an important role in CRC development, treatment, and metastasis.
Identification of Critical miRNAs as Novel Diagnostic Markers for Laryngeal Squamous Cell Carcinoma
Authors: Luo Kuo , Zhao Yanguang , Liu Hong , Mo Jinhua
Published: July 2022

The prognosis of laryngeal squamous cell carcinoma (LSCC) patients remains poor, and early diagnosis can distinctly improve the long-term survival of LSCC patients. MicroRNAs (miRs) are a group of endogenous, noncoding, 18-24 nucleotide length single-strand RNAs and have been demonstrated to regulate the expression of many genes, thus modulating various cellular biological processes. In this study, we aimed to identify critical diagnostic miRNAs based on two machine learning algorithms. The GSE133632 dataset was acquired from the Gene Expression Omnibus (GEO) datasets, comprising LSCC tissular samples (57 specimens) and matched neighboring healthy mucosa tissular samples (57 specimens). Differentially expressed miRNAs (DEMs) were screened between 57 LSCC specimens and 57 normal specimens. The LASSO regression model and SVM-RFE analysis were carried out for the identification of critical miRNAs. ROC assays were applied to evaluate discriminatory ability. We identified 32 DEMs between LSCC specimens and normal specimens. Two machine learning algorithms confirmed that hsa-miR-615-3p, hsa-miR-4652-5p, hsa-miR-450a-5p, hsa-miR-196a-5p, hsa-miR-21-3p, hsa-miR-139-5p, and hsa-miR-424-5p were critical diagnostic factors. According to the ROC assays, seven miRNAs had an AUC value of >0.85 for LSCC. Taken together, our findings identified seven critical miRNAs in LSCC patients which can be used to diagnose LSCC patients with high sensitivity and specificity. These results must be verified by large-scale prospective studies.
[Retracted] Relationship between Economic Growth and Energy Consumption from the Perspective of Sustainable Development
Authors: Dai Liuyi , Jia Rui , Wang Xinran
Published: July 2022

While promoting the economic growth, energy has also brought pollution problems to the world environment, which has gradually become a bottleneck impeding sustainable economic development. In view of the rapid evolution of urbanization and industrialization, economic growth is increasingly dependent on the energy consumption, the development of the two is difficult to coordinate, and the internal contradictions are becoming increasingly serious, which hinders the sustainable development of economic growth. This study establishes the relationship between energy consumption and economic growth according to the energy Kuznets curve and studies the future trend of China’s sustainable development through the comparative analysis of the energy Kuznets curve of the United States and Germany. The results show that, at the turning point of energy consumption, China’s energy economic rate is higher than that of Germany and the United States. In addition, in terms of urbanization rate and industrial structure, although China’s tertiary industry has made a breakthrough, it is still lower than that of the United States and Germany, but the level of urbanization rate has made significant progress. In short, China has obvious advantages in future economic development and has a late developing advantage compared with the United States and Germany. This paper makes an empirical analysis of the relationship between energy consumption and economic growth in OECD countries and finds out the turning point of energy consumption, so as to provide a theoretical basis for coordinating China’s energy consumption and economic growth.
Innovative Design of Artificial Intelligence in Intangible Cultural Heritage
Authors: Xie Jing
Published: July 2022

Driven by artificial intelligence technology, the research of intangible cultural heritage innovative design is carried out. Firstly, the appearance modeling characteristics, decorative element characteristics, and composition form characteristics of typical intangible cultural heritage products are analyzed. According to the collected relevant data of intangible cultural heritage products and existing products, combined with the regional cultural characteristics of intangible cultural heritage products and other factors, the analysis Atlas of intangible cultural heritage product innovation design is constructed. Based on perceptual engineering, the elements of intangible cultural heritage product innovation design for user participation are determined according to the needs and perceptual images of users. The shape grammar is used to extract the elements of intangible cultural heritage products, deduce and deform them, and finally generate the preliminary design scheme.
Facial Expression Recognition from a Single Face Image Based on Deep Learning and Broad Learning
Authors: Bie Mei , Xu Huan , Gao Yan , Che Xiangjiu
Published: July 2022

With advances in computer vision and artificial intelligence technology, facial expression recognition research has become a prominent topic. Current research is grappling with how to enable computers to fully understand expression features and improve recognition rates. Most single face image datasets are based on the psychological classification of the six basic human expressions used for network training. By outlining the problem of facial recognition by comparing traditional methods, deep learning, and broad learning techniques, this review highlights the remaining challenges and future directions of deep learning and broad learning research. The deep learning method has made it easier and more effective to extract expression features and improve facial expression recognition accuracy by end-to-end feature learning, but there are still many difficulties in robustness and real-time performance. The broad learning system (BLS) is a broad network structure that is expanded by increasing the number of feature nodes and enhancement nodes appropriately to reinforce the structure and is also effective in facial expression recognition. However, outliers and noises in unbalanced datasets need BLS to solve in the future. Finally, we present several problems that still need to be addressed in facial expression recognition.
Mechanistic Research into the Effects of the Jianpi Xiaozhi Formula on Liver Injury in Diabetic Rats
Authors: Yuanyuan Zhang , Huaizhen Liu
Published: July 2022

Objective. The purpose of this study was to explore the mechanism of Jianpi Xiaozhi Formula (JPXZF) action in attenuating liver injury in a rat model of type 2 diabetes mellitus (T2DM). Methods. A rat model of T2DM was established. Forty-eight male Sprague–Dawley (SD) rats were randomly allocated to six groups: healthy untreated rats (normal control (NC)), rats with diabetes mellitus (DM), diabetic rats treated with low-dosage JPXZF (DM + JL), diabetic rats treated with an intermediate JPXZF dosage (DM + JM), diabetic rats treated with high-dosage JPXZF (DM + JH), and diabetic rats treated with 4-phenylbutyric acid (PBA) (DM + PBA). The rats in each group were given the indicated drugs for 8 weeks, and pathological changes in the liver tissues of each rat group were observed by haematoxylin-eosin (HE) staining. Reverse-transcription polymerase chain reaction (RT-PCR) and Western blotting (WB) were performed to determine the expression of glucose-regulated protein 78 (GRP78), activating transcription factor 6 (ATF6), family with sequence similarity 134, member B (FAM134B), P62, Beclin-1, and light chain 3II/I (LC3II/I) genes and proteins in the liver tissues of the rats in each group. Immunofluorescence was used to observe changes in FAM134B expression. Results. After successfully establishing the rat model, RT-PCR assays revealed that, compared with those in the NC group rats, the expression levels of GRP78, ATF6, and P62 mRNA in the livers of the DM group rats were significantly increased, and the relative expression levels of FAM134B and Beclin-1 mRNA were significantly decreased. Compared with that in the DM group, the relative expression of GRP78, ATF6, and P62 mRNA in the liver of the rats in each JPXZF intervention group was decreased in a dosage-dependent manner, and the relative expression of FAM134B and Beclin-1 mRNA was increased significantly (

p
<
0.05

). WB indicated that, compared with that in the NC group rats, the LC3II/I protein expression ratio in the liver of the DM group rats was significantly reduced, and the LC3II/I protein expression ratio in the liver of the rats in each JPXZF intervention group was significantly increased. In addition, the expression of the other measured proteins was consistent with that of the corresponding mRNA measured by RT-PCR (

p
<
0.05

). The immunofluorescence assay results showed that FAM134B changes were consistent with the results obtained by RT-PCR and WB (

p
<
0.05

). Conclusion. Jianpi Xiaozhi Formula may be effective in treating liver injury in diabetic rats by regulating autophagy induced by endoplasmic reticulum stress (ERS).
Innovative College Students’ Educational Management Mode Based on BP Neural Network
Authors: Zhang Yuanyuan
Published: July 2022

With the advancement of society, the necessities for school graduates are getting increasingly elevated. In this unique situation, the conventional showing the board model in schools and colleges has not been able to adjust to the pattern of present day advancement and should be improved and developed likewise. By advancing the instructive administration model, this paper expects to work on the idea, conduct, and advancement capacity of undergrads to address the issues of social turn of events. In light of this, this paper principally concentrates on the issues existing in the instruction of the board of undergrads and the comparing imaginative models. This paper takes Wenzhou University students as the research object, combining qualitative analysis with quantitative analysis. This paper assembles a general travel industry proficient development and business venture schooling assessment framework based on BP brain organization. It lessens the impedance brought about by human elements in the assessment cycle and guarantees the precision of the assessment results. This paper improves the research and analysis framework of related fields, enriches the research results of innovation and entrepreneurship education evaluation in tourism, and has important theoretical value for improving the evaluation model in this field. The exploratory aftereffects of this paper show that the thorough organization yield esteem is 0.7261 as per the information gathered by Wenzhou University utilizing the poll review. It demonstrates that the advancement and business training of Wenzhou University is at a medium level, and there is still a lot of opportunity to get better.
Research on the MEG of Depression Patients Based on Multivariate Transfer Entropy
Authors: Zhang Xinyu , Xie Jicheng , Fan Changyu , Wang Jun
Published: July 2022

The pathogenesis of depression is complex, and the current means of medical diagnosis is single. Patients with severe depression may even have great physical pain and suicidal tendencies. Magnetoencephalography (MEG) has the characteristics of ultrahigh spatiotemporal resolution and safety. It is a good medical means for the diagnosis of depression. In this paper, multivariate transfer entropy algorithm is used to study MEG of depression. In this paper, the subjects are divided into the same brain region and the multichannel combination between different brain regions, and the multivariate transfer entropy of patients with depression and healthy controls under different EEG signal frequency bands is calculated. Finally, the significant difference between the two groups of experimental samples is verified by the results of independent sample t-test. The experimental results show that for the same combination of brain channels, the multivariate transfer entropy in the depression group is generally lower than that in the healthy control group, and the difference is the best in

γ

frequency band and the largest in the frontal region.
[Retracted] Study on Inflammatory Factors in Aneurysmal Perimembranous Ventricular Septal Defect in Congenital Heart Disease
Authors: Zhou Jin , Liu Ying , Wang Jing , Yan Wei , Liu Yongjian , Chen Litao , Du Zhixing , Xie Qilian
Published: July 2022

To detect the expression of inflammatory factors such as interleukin‐1β (IL‐1β), interleukin‐6 (IL‐6), transforming growth factor (TGF‐β), and tumor necrosis factor (TNF‐α) in the tumor tissue of ventricular septal defect (VSD) in congenital heart disease and to explore the role of inflammatory response in the formation of aneurysmal perimembranous VSD(APVSD). Children with APVSD of congenital heart disease treated by surgery were selected and divided into true aneurysmal perimembranous group (TAP group) and pseudoaneurysmal perimembranous group (PAP group) according to echocardiography and surgical findings. There were 15 children in the TAP group and 31 in the PAP group. The aneurysmal perimembranous tissue of the two groups of children was collected during the operation. IL‐1β, IL‐6, TGF‐β, and TNF‐α were positively expressed in the aneurysmal perimembranous tissue of the two groups, and the expression levels of all inflammatory factors in the PAP group were higher than those in the TAP group, and the difference was statistically significant (P < 0.05). The expression levels of IL‐1β, IL‐6, TGF‐β, and TNF‐α in the aneurysmal perimembranous tissue of the two groups were negatively correlated with the width of the APVSD breach. IL‐1β, IL‐6, TGF‐β, and TNF‐α may be involved in the occurrence and development of APVSD through inflammatory mechanism.