bluuebunny/crossref_metadata_2025 huggingface dataset:
Flavonoids as Promising Neuroprotectants and Their Therapeutic Potential against Alzheimer’s Disease
Authors: Minocha Tarun , Birla Hareram , Obaid Ahmad A. , Rai Vipin , Sushma P. , Shivamallu Chandan , Moustafa Mahmoud , Al-Shehri Mohammed , Al-Emam Ahmed , Tikhonova Maria A. , Yadav Sanjeev Kumar , Poeggeler Burkhard , Singh Divakar , Singh Sandeep Kumar
Published: August 2022

Alzheimer’s disease (AD) is one of the serious and progressive neurodegenerative disorders in the elderly worldwide. Various genetic, environmental, and lifestyle factors are associated with its pathogenesis that affect neuronal cells to degenerate over the period of time. AD is characterized by cognitive dysfunctions, behavioural disability, and psychological impairments due to the accumulation of amyloid beta (Aβ) peptides and neurofibrillary tangles (NFT). Several research reports have shown that flavonoids are the polyphenolic compounds that significantly improve cognitive functions and inhibit or delay the amyloid beta aggregation or NFT formation in AD. Current research has uncovered that dietary use of flavonoid-rich food sources essentially increases intellectual abilities and postpones or hinders the senescence cycle and related neurodegenerative problems including AD. During AD pathogenesis, multiple signalling pathways are involved and to target a single pathway may relieve the symptoms but not provides the permanent cure. Flavonoids communicate with different signalling pathways and adjust their activities, accordingly prompting valuable neuroprotective impacts. Flavonoids likewise hamper the movement of obsessive indications of neurodegenerative disorders by hindering neuronal apoptosis incited by neurotoxic substances. In this short review, we briefly discussed about the classification of flavonoids and their neuroprotective properties that could be used as a potential source for the treatment of AD. In this review, we also highlight the structural features of flavonoids, their beneficial roles in human health, and significance in plants as well as their microbial production.
Synthesis, Structure, and Antifungal Activities of 3-(Difluoromethyl)-Pyrazole-4-Carboxylic Oxime Ester Derivatives
Authors: Wang Bin , Chen Wei-Ting , Min Li-Jing , Han Liang , Sun Na-Bo , Liu Xing-Hai
Published: August 2022

Fifteen new pyrazole-4-carboxylic oxime ester derivatives were conveniently synthesized, and their structures were confirmed by 1H NMR, 13C NMR, HRMS, and X-ray diffraction. Antifungal assays indicated that some of these compounds possessed good activity against S. sclerotiorum, B. cinerea, R. solani, P. oryae, and P. piricola at 50 ppm. Structure-activity relationships (SAR) were studied by molecular docking simulation.
Prediction Model of Music Popular Trend Based on NNS and DM Technology
Authors: Xu Yichen , Wang Mingxun , Chen Hao , Hu Fan
Published: August 2022

The popular trend of today’s music can be obtained by deep excavation, analysis, and prediction of the audience’s preferences. Using huge music library resources and user behavior to form music big data and truly realizing the aggregation of audience preferences determine the popular development trend of music. Therefore, this paper will apply data mining (DM) technology, introduce neural network (NNS) theory, establish a prediction model of music fashion trend, predict and evaluate the music fashion trend according to the selected evaluation index, find the change of music fashion trend in time, and provide decision-making basis for music fashion trend. In this paper, the prediction of music popularity trend based on NNS and DM technology is studied. In the prediction of the number of songs played by 10 artists, the NNS algorithm proposed in this paper reduces the prediction effect from the original 0.074 and 0.045 to 0.044 and 0.032, respectively, and the error rates are reduced by 35.7% and 29.4%, respectively, compared with the learning algorithm and the decision tree algorithm. Among the three methods, the NNS algorithm in this paper has the highest accuracy. Therefore, it can be proved that the model proposed in this paper is more suitable for predicting the trend of music popularity. In the end, it can accurately control the trend of pop music and also realize the aggregation of user preferences to determine the trend of pop music.
Clinical Effects of Outpatient Health Education on Fall Prevention and Self-health Management of Elderly Patients with Chronic Diseases
Authors: Wu Yongping , Gu Yueying , Rao Xiuhua , Cheng Minling , Chen Ping , He Lina
Published: August 2022

Background. Elderly patients with chronic diseases (CDs) have a higher predilection for falls, with more severe consequences once they fall. Therefore, it is necessary to explore an effective way to prevent falls in elderly patients with CDs. Objective. To clarify the clinical effects of outpatient health education on fall prevention and self-health management in elderly patients with CDs. Methods. This retrospective study enrolled 102 elderly patients with CDs who received treatment in the School of Medicine, Sir Run Run Shaw Hospital of Zhejiang University, between January 2019 and December 2020. Patients intervened by routine nursing were assigned to the regular group (n = 48), and those additionally treated with outpatient health education were included in the research group (n = 54). Assessment of patients’ negative emotions (NEs) adopted the Self-Rating Anxiety/Depression Scale (SAS/SDS), determination of their sense of self-efficacy employed the Falls Efficacy Scale International (FES-I), and their self-care capacity evaluation used the Exercise of Self-Care Agency (ESCA). Patients’ falls, hospitalization time, fall prevention knowledge, fall prevention-related health behavior, and nursing satisfaction were recorded. Results. After the nursing intervention, lower SAS, SDS, and FES-I scores were determined in the research group versus the regular group; the total ESCA score assessed from various dimensions was higher in the research group; the research group also exhibited a markedly lower incidence of falls, and shorter hospitalization time than the regular group, with better mastery of fall prevention knowledge, fall prevention-related health behavior and nursing satisfaction. Conclusions. Outpatient health education intervention can prevent senile patients with CDs from falling, promote their rehabilitation, and enhance their mastery of fall prevention knowledge; moreover, it can improve patients’ healthy behaviors to prevent falls, mitigate their NEs, and improve their sense of self-efficacy and self-care ability, which has high clinical application value.
Estimation of Parameters and Pooling in Nonlinear Flooding Event Scenarios with Bayesian Model
Authors: Alduais Fuad S. , Jawa Taghreed M.
Published: August 2022

Water-related tragedies are the highest common of all proven natural calamities and pose severe attacks on people and on socioeconomic status development. Due to the obvious controversy surrounding, their volume, location and time of incidence, geological swaths, and geophysical interrelations, flood events are difficult to completely control. Hence, complete flood prevention is always considered to be a viable choice. The specialized flood occurrences are investigated by developing a structural measure. In this paper, nonlinear flood event circumstance is determined by using a statistical Bayesian parametric approach for parameter estimation. A popular tool for estimating a flood design is model of nonlinear flood event. Nonlinear flood event models are subjected to a Bayesian technique for estimating parameter. The approach is based on the minimization function of square for models with nonlinear calculated peak discharges in terms of parameters. The observed and calculated peak discharges for numerous storms in the watershed, data on the pattern of error observed, and previous information on values of parameter all influence this objective function. The subsequent matrix for covariance is a measure of the calculated parameters’ accuracy. Rainfall and runoff data from a Harvey River sample are used in this study to show the process.
Effects of Positive Psychological Nursing Combined with Free Posture on the Prognosis of Primipara with Singleton Spontaneous Delivery
Authors: Zhao Xuefei , He Jianjun , Liu Jue
Published: August 2022

Objective. To explore the effects of positive psychological nursing combined with free posture on the prognosis of primipara with singleton spontaneous delivery. Methods. 106 cases of primipara with singleton spontaneous delivery who were admitted to the obstetrics department of our hospital from January 2017 to December 2019 were selected as the research subjects and they were divided into the observation group and control group according to the random number table method and maternal willingness, with 53 cases in each group. The control group received routine nursing, and the observation group was given positive psychological nursing combined with free posture on the basis of the control group. The stress degree during delivery (Hamilton anxiety scale (HAMA) and Hamilton depression scale (HAMD)), the time of first stage of labor, the time of second stage of labor, the time of third stage of labor, pain level during the active period of the first stage of labor, and delivery outcomes were observed and compared between the two groups. Results. The degree of anxiety and depression during childbirth in the observation group was significantly lower than that in the control group (

P
<
0.05

). The time of first stage of labor and the time of second stage of labor in the observation group were shorter than those in the control group (

P
<
0.05

), and there was no significant difference in the time of the third stage of labor (

P
>
0.05

). The pain degree in the active stage of the first stage of labor in the observation group was lower than that in the control group (

P
<
0.05

). The pain degree in the active stage of the first stage of labor in the observation group was lower than that in the control group (

P
<
0.05

). Conclusion. Positive psychological nursing combined with free posture for primipara with singleton spontaneous delivery can shorten the stages of labor, reduce the pain, relieve psychological stress, and improve the delivery outcomes.
An Auxiliary Teaching System for Spoken English Based on Speech Recognition Technology
Authors: Bao Lei , Lv Jing
Published: August 2022

Because the English language has always been inaccurate and seemed difficult to correct errors, this development has created a reputation based on improvements to the DWJ algorithm and HMM speech scores and correction mistake. In this paper, different signal characteristics are used using the DWJ algorithm: the Mel frequency cepstrum coefficient compares the standard speech library and the distance between the speech sample and the sample message received. The conversation deciphered the Viterbi code according to the HMM model, which was recognized and evaluated by posteriori probabilities. Finally, the professional data were used to fix the wrong phone to determine, score, and make repair mistakes. The results of the experiments show that the tests used in this article are reliable. The results of the experiment show that the standard English language proficiency in this article is reliable, which can provide students with timely, accurate, and objective assessment and teaching feedback, improving English language proficiency.
Characterization of the Tumor Microenvironment in Osteosarcoma Identifies Prognostic- and Immunotherapy-Relevant Gene Signatures
Authors: Tan Jianye , Feng Xuhui , Wu Hangxing , Yang Bingsheng , Shi Meiling , Xie Chao , Su Zexin , Li Lin , Luo Mengliang , Zuo Zhijie , Zhu Shuang , Yang Jiancheng , Lin Lijun
Published: August 2022

The osteosarcoma (OS) microenvironment is composed of tumor cells, immune cells, and stromal tissue and is emerging as a pivotal player in OS development and progression. Thus, microenvironment-targeted strategies are urgently needed to improve OS treatment outcomes. Using principal component analysis (PCA), we systematically examined the tumor microenvironment (TME) and immune cell infiltration of 88 OS cases and constructed a TME scoring system based on the TMEscore high and TMEscore low phenotypes. Our analysis revealed that TMEscore high correlates with longer survival in OS patients, elevated immune cell infiltration, increased immune checkpoints, and increased sensitivity to chemotherapy. TMEscore low strongly correlated with immune exclusion. These observations were externally validated using a GEO dataset (GSE21257) from 53 OS patients. Our laboratory data also proved our findings. This finding enhances our understanding of the immunological landscape in OS and may uncover novel targeted therapeutic strategies.
The Distal Free Achilles Tendon Is Longer in People with Tendinopathy than in Controls: A Retrospective Case-Control Study
Authors: Callow Joanne H. , Cresswell Mark , Damji Faraz , Seto Joshua , Hodgson Antony J. , Scott Alex
Published: August 2022

Objectives. The free Achilles tendon is defined as the region of tendon distal to the soleus which is “unbuttressed,” i.e., unsupported by muscular tissue. We reasoned that a relative lack of distal buttressing could place the tendon at a greater risk for developing Achilles tendinopathy. Therefore, our primary goal was to compare the free Achilles tendon length between those with midportion or insertional Achilles tendinopathy and healthy controls. Design. This is a retrospective case-control study. Setting. Hospital in Vancouver, Canada. Participants. 66 cases with Achilles tendinopathy (25 insertional, 41 midportion) consecutively drawn from a hospital database within a 5-year period and matched to 66 controls (without tendinopathy) based on sex, age, and weight. Main outcome measures. Odds ratio of the risk of developing Achilles tendinopathy given the length of free tendon, defined anatomically on MRI, after adjustment for confounders. Results. MRI-defined free Achilles tendon length is a statistically significant predictor of having midportion Achilles tendinopathy (odds ratio = 0.53, 95% confidence interval 1.13 to 2.07). Midportion Achilles tendinopathy cases had significantly longer free tendons (Mdn = 51.2 mm, IQR = 26.9 mm) compared to controls (Mdn = 40.8 mm, IQR = 20.0 mm),

p
=
0.007

. However, there was no significant difference between the free Achilles tendon lengths in insertional AT cases (Mdn = 47.9 mm, IQR = 15.1 mm) and controls (Mdn = 39.2 mm, IQR = 17.9 mm),

p
=
0.158

. Free Achilles tendon length was also correlated with the tendon thickness among those with Achilles tendinopathy, rτ = 0.25, and

p
=
0
.003

. Conclusions. The MRI-defined length of the free Achilles tendon is positively associated with the risk of midportion Achilles tendinopathy. A relative lack of distal muscular buttressing of the Achilles tendon may therefore influence the development of tendinopathy.
An Outbreak of Coxsackievirus A6 Infection in Adults of a Collective Unit, China, 2019
Authors: Gao Yumeng , Ma Guangyuan , Xiao Yong , Cai Qun , Chen Yujun , Shi Ping , Wang Kewei , Shen Yuan , Shi Chao
Published: August 2022

Outbreaks/epidemics caused by coxsackievirus A6 (CVA6) have been reported continuously since 2008. However, outbreaks of ocular conjunctival hemorrhage caused by CVA6 in adults in a collective unit have not been reported. Methods. The epidemiological investigations were carried out according to the monitoring program, and the clinical data were collected from the treated hospitals. The nasopharyngeal swab specimens were collected to extract the total nucleic acid (DNA/RNA). The pathogen was determined using nucleic acid detection kits for 22 respiratory pathogens. The VP1 gene of this pathogen was amplified and sequenced. Sequence alignment and analysis were performed using BioEdit 7.0. The gene phylogenetic tree was constructed with MEGA4.0. Results. The factory emerged patients in succession from February 14 and reached the peak on the 18th. A total of 19 workers had symptoms in this factory up to March 31, 2019, giving an attack rate of 8.26%. The main symptoms were rash, ocular conjunctival hemorrhage, fever, and sore throat. The laboratory results showed that coxsackievirus A6 was the main pathogen causing this outbreak. The risk of taking a bath in the bathroom was 7.37 times higher than that of not taking a bath (95% confidence interval (CI): 1.67–32.79). Conclusion. This manuscript further enriched the infection-related information of CVA6, which was helpful to better identify and deal with the epidemic in the future.
Self-Consciousness, Self-Objectification, and Social Anxiety as Predictors of Photo Editing Behavior among Emerging Adults
Authors: Mustafa Sarah , Akram Mariyam
Published: August 2022

This study aims to assess the impact of self-consciousness, self-objectification, and social anxiety on photo editing behavior among emerging adults. Correlational research strategy was used for the present quantitative research, and convenient sampling strategy was used to collect data of 444 university students (135 males and 309 females) with the age range of 18-25 years. The self-consciousness scale, objectified body consciousness scale, photo manipulation scale, and social anxiety scale were used as assessment tools for this study. For data analysis,

t

-test for independent samples, correlation, and regression analysis were implied. The results revealed that women had higher self-consciousness and social anxiety in contrast to men. Moreover, self-objectification and evaluation anxiety were positively correlated with photo editing behavior. Lastly, overall self-objectification and body shame, one of the three aspects of self-objectification resulted as significant predictors of photo manipulation behavior among emerging adults. This study contributes to the indigenous literature of clinical and social psychology.
A Systematic Study on the Extraction and Image Reproduction of Ceramic Sculpture Artworks
Authors: Wang Yuhong
Published: August 2022

In order to solve the research on the extraction of ceramic sculpture artwork patterns, and, in the process of image reproduction, the problem of too few feature points in the object image, the author proposes an image stitching algorithm that combines SIFT and MSER algorithms. After comprehensively analyzing the principles, advantages, and disadvantages of the current main image stitching methods, in terms of feature matching, based on the K-D tree search algorithm, the improved BBF algorithm is used to improve the search efficiency of feature points. In order to remove the possible cracks in the stitching process, an improved multiband fusion algorithm is used to seamlessly stitch the registered images. The results show that the feature points detected by the one-dimensional normal distribution algorithm are on average 0.1%, 0.5%, 1.7%, 4.4%, and 9.2%. The algorithm combining SIFT and MSER to extract feature points can reach 3.6%, 4.6%, 8.4%, 15%, and 19.1%. The experimental results show that the algorithm proposed by the author can extract more image feature points to facilitate later image registration. The image blur phenomenon in the original image fusion algorithm is solved, and a complete and clear two-dimensional plane pattern is finally obtained.
Systematic Analysis of Risk Associated with Supply Chain Operations Using Blockchain Technology
Authors: Khan Habib Ullah , Malik Muhammad Zain , Khan Sulaiman
Published: August 2022

Advancements in information and communication technologies (ICT), big data analytics, and artificial intelligence- (AI-) based techniques brought a dramatic revolution in diverse research domains, including healthcare, IoT, and networking. Blockchain technologies are gaining traction from both private and government organizations at an incredible rate. Emerging technologies have different levels of technological complexities and commercial ramifications. This technology is playing an essential role in the financial revolution of banking and regulatory sectors. Blockchain has piqued the interest of many academics, organizations, and businesses, particularly in using bitcoin. To grasp the significance of this revolution, a comprehensive assessment is performed to bridge the gaps in the targeted blockchain-driven domain with different perspectives. For this systematic review process, a set of four distinct research questions were formulated to accumulate the most relevant research trends. In private and public organizations, it is a securing technology to deliver trustworthy and protected services to users because of its decentralized, controlled aspect. Financial services, real estate, supply chain management, healthcare, academics, and other industries benefit significantly from this evolutionary technology. These application cases are diverse and far-reaching, ranging from smart contracts to blockchain-encrypted educational certificates. This systematic analysis has investigated a total of 113 relevant articles and concluded with the features and functions in an economic setting and briefed how these variables can balance players’ incentives, define core blockchain-related features, and present new research ideas to solve the proposed risk.
Intelligent Tourism Marketing and Publicity Methods for Revenue Enhancement
Authors: Lu Ying , Cui Bo
Published: August 2022

For online e-commerce platforms, big data intelligent marketing is an essential tool for promoting companies, creating pictures, participating in competitions, and engaging customers. This also gives traditional marketing a new sense of precision and a new approach to increasing revenue. Marketing and public relations based on big data analytics and intelligence should be considered important and profitable for the travel and tourism business. Tourism enterprises need to learn to use intelligent technology to guide marketing activities and formulate comprehensive and accurate marketing strategies. Infiltrate the advantages of intelligence into all aspects of tourism marketing, so as to form an intelligent, precise, and modern tourism marketing and publicity model, and help enterprises to improve their income. This work focuses on the research on intelligent tourism marketing and publicity. The main research contents include the following aspects. First, this work proposes a revenue-enhancing tourism marketing and publicity method, which is mainly divided into the use of intelligence to enrich the form of publicity and marketing and the use of intelligence to refine the content of publicity and marketing. Second, this work proposes an IWOA-BP network for evaluating a revenue-enhancing intelligent tourism marketing promotion method. It improves the WOA algorithm by introducing a nonlinear convergence factor and adaptive crossover mutation to construct the IWOA algorithm. Then IWOA is applied to initial weights and thresholds for optimization, which can solve the drawbacks of the traditional BP network and improve the performance and reduce the training time. Third, this work conducts a comprehensive evaluation of the proposed revenue enhancement-oriented tourism marketing and publicity methods and IWOA-BP, and the experimental results verify the feasibility of these methods.
Design and Fabrication of Patient-Specific Implant for Maxillofacial Surgery Using Additive Manufacturing
Authors: Koppunur Rakesh , Dama Kiran Kumar , Rokkala Uzwalkiran , Thirupathi Balaji , Sagar N. V. S. S. , Gugulothu Bhiksha
Published: August 2022

Patient-specific implants are well known for fixing the fracture for bone repairs. However, the exact fixation of the fabricated implant to the patients is a challenging task. To overcome this problem, in the present study two kinds of designs are developed and fabricated. Based on the exact fitting to the patient’s oral system, the best design is selected to fabricate. Computed tomography (CT) scan data of the patient oral anatomy is converted into a 3D model using the DICOM Software “Slicer 3D.” The patient-specific maxillofacial implant is fabricated using fused filament fabrication (FFF) and direct metal laser sintering (DMLS) techniques. Before fabricating real time product, a prototype is fabricated at the initial stage using FFF. Later, stress distribution and displacement of the implant was investigated using a FEM simulation. The conclusion of the present work results are potential for FFF of patient-specific implants out of Ti-6Al-4V.
Scene Classification Using Deep Networks Combined with Visual Attention
Authors: Shi Jing , Zhu Hong , Li Yuxing , Li YangHui , Du Sen
Published: August 2022

In view of the scene’s complexity and diversity in scene classification, this paper makes full use of the contextual semantic relationships between the objects to describe the visual attention regions of the scenes and combines with the deep convolution neural networks, so that a scene classification model using visual attention and deep networks is constructed. Firstly, the visual attention regions in the scene image are marked by using the context-based saliency detection algorithm. Then, the original image and the visual attention region detection image are superimposed to obtain a visual attention region enhancement image. Furthermore, the deep convolution features of the original image, the visual attention region detection image, and the visual attention region enhancement image are extracted by using the deep convolution neural networks pretrained on the large-scale scene image dataset Places. Finally, the deep visual attention features are constructed by using the multilayer deep convolution features of the deep convolution networks, and a classification model is constructed. In order to verify the effectiveness of the proposed model, the experiments are carried out on four standard scene datasets LabelMe, UIUC-Sports, Scene-15, and MIT67. The results show that the proposed model improves the performance of the classification well and has good adaptability.
Perceived Need to Counseling Service and Associated Factors among Higher Education Institutions: The Case of Dilla University, Southern Ethiopia
Authors: Awol Amado Asebe , Shiferew Biniam
Published: August 2022

In the university academic atmosphere, guidance and counseling practices are an efficient and effective way of supporting and helping students deal with problems and issues in educational, career, and personal/social areas. This study aimed to assess the magnitude, perceived need, and associated factors to counseling services of students in Dilla University, Southern Ethiopia. A mixed-study design was employed with both quantitative and qualitative research approaches. Both primary and secondary sources of data were employed. Data collection tools are questionnaires, focus group discussions, and in-depth interviews. The collected data were coded, entered, and analyzed using SPSS version 20 software. Quantitative data were presented as mean, percentage, frequency, and cross-tabulation. The qualitative data were analyzed and interpreted thematically, and the results are presented in narrative form. The finding of the study shows that there are a high number of students who need guidance and counseling at Dilla University from different colleges and departments. The student’s age level, sex, parental marital nature, the department they joined, family economy, occupation, and residence are the main factors that affect positively or negatively their counseling needs in higher education. The identified highest personal counseling needs and indicators in Dilla University students are for maintaining good physical and mental health, handling stress and anxiety in their life, solving personal problems, overcoming procrastination, dealing with stress due to their job, and coping with a broken relationship. The items that were indicated as having the lowest prevalence for concerns in terms of personal needs required by students were concerns about learning how to manage drug addiction, to become overcome insomnia, and reproductive health problems are the lowest need reported by participants of the study. This needs all stakeholders’ attention and support on the issues of guidance and counseling at Dilla University.
BP Neural Network-Based Evaluation Method for Enterprise Comprehensive Performance
Authors: Wenjing Chen
Published: August 2022

Comprehensive performance evaluation is an important basis for improving the training effect of enterprise employees and the effective allocation of enterprise resources. Based on AHP and BP neural network theory, this paper constructs a comprehensive performance evaluation method for enterprises, AHP is used to calculate the weight of the index, and then the importance index is screened. The model proposes a conceptual model of comprehensive performance of manufacturing enterprises from the support layer, core layer, and promotion layer and constructs a manufacturing system from horizontal and vertical. The influencing factors of comprehensive performance solve the quantification problem of enterprise comprehensive performance evaluation and have obvious guiding value for the research on the integration mode and path of industrialization and industrialization of regional manufacturing enterprises. In the simulation process, the weight of each index in the evaluation system is first determined by the analytic hierarchy process; then the evaluation index membership score table is established, and fuzzy mathematics is used to calculate the expert’s score, so as to solve the problem caused by the intermediate value. The uncertainty caused by the jump is finally established by the analytic hierarchy process, and the neural network is used to simulate the sample. The experimental results show that by using AHP to collect training samples for neural network evaluation, the comprehensive performance evaluation system has good fitness and achieves the best comprehensive consideration of accuracy and training time when there are 17 hidden layer neurons. The maximum relative error is 1.64%, which is much lower than the general accuracy requirement of 5%, which effectively improves the performance and calculation accuracy of the network.
Experimental Study on Deformation Law of Rectangular Roadway in Horizontal Layered Rock Mass
Authors: Hou Dinggui , Zhou Yunying , Wang Jingxiang
Published: August 2022

In order to analyze the characteristics and mechanism of roadway deformation caused by high stress in horizontal strata, a physical model with rectangular roadway was designed. The model was constructed by the so-called “Physically Finite Elemental Slab Assemblage (PFESA)” to bring about the structural effect of the deep strata. In the experiment, the vertical and horizontal pressures were increased step-by-step to simulate high stress. The deformation characteristics of surrounding rock in layered rock roadway were observed by video image and digital image correlation method (DIC). The strain and stress characteristics of surrounding rock of roadway in layered rock mass were obtained by using the strain gauge test method, and compared with the deformation characteristics. For the sake of analyzing the deformation and failure mechanism of layers, the mechanical model of layered rock structure was established, and the experimental phenomenon and mechanism were verified. Through systematic study, this paper enriches the research methods of model experiment and provides an experimental basis for practical engineering of similar conditions.
Construction of Online English Corpus Based on Web Crawler Technology
Authors: Qi Yanfei
Published: August 2022

Using 100 random questionnaires, 89 people said they were increasingly dependent on the Internet for information, while the remaining 11 said they were not dependent much. Nowadays, the development of Internet technology is more and more mature, and the scale of the Internet is more and more large. At the same time, with the gradual deepening of global economic integration, English has become one of the indispensable language methods for international communication and cooperation. The development of network technology has been applied more and more widely in the process of English teaching; especially, the construction, research, and practical application of corpus have ushered in a broad development prospect. Based on web crawler technology, this paper focuses on the construction of web English corpus, which lays a foundation for English learning. Experiments show that crawler technology can effectively solve the collection and recognition of big data in English corpus.
Diagnosis, Prevention, and Treatment of Radiotherapy-Induced Xerostomia: A Review
Authors: Li Yanli , Li Xuehan , Pang Runxuan , Yang Guang , Tian Mingxu , Zhao Tengyu , Sun Yunhan , Lee Eui-Seok , Jiang Heng Bo , Han Jianmin
Published: August 2022

In patients with head and neck cancer, irradiation (IR)-sensitive salivary gland (SG) tissue is highly prone to damage during radiotherapy (RT). This leads to SG hypofunction and xerostomia. Xerostomia is defined as the subjective complaint of dry mouth, which can cause other symptoms and adversely affect the quality of life. In recent years, diagnostic techniques have constantly improved with the emergence of more reliable and valid questionnaires as well as more accurate equipment for saliva flow rate measurement and imaging methods. Preventive measures such as the antioxidant MitoTEMPO, botulinum toxin (BoNT), and growth factors have been successfully applied in animal experiments, resulting in positive outcomes. Interventions, such as the new delivery methods of pilocarpine, edible saliva substitutes, acupuncture and electrical stimulation, gene transfer, and stem cell transplantation, have shown potential to alleviate or restore xerostomia in patients. The review summarizes the existing and new diagnostic methods for xerostomia, along with current and potential strategies for reducing IR-induced damage to SG function. We also aim to provide guidance on the advantages and disadvantages of the diagnostic methods. Additionally, most prevention and treatment methods remain in the stage of animal experiments, suggesting a need for further clinical research, among which we believe that antioxidants, gene transfer, and stem cell transplantation have broad prospects.
Solving User Priority in Cloud Computing Using Enhanced Optimization Algorithm in Workflow Scheduling
Authors: Aggarwal Ambika , Kumar Sunil , Bhatt Ashutosh , Shah Mohd Asif
Published: August 2022

Cloud computing is a procedure of stockpiling as well as retrieval of data or computer services over the Internet that allows all its users to remotely access the data centers. Cloud computing provides all required services to the users, but every platform has its share of pros and cons, and another major problem in the cloud is task scheduling or workflow scheduling. Multiple factors are becoming a challenge for scheduling in cloud computing namely the heterogeneity of resources, tasks, and user priority. User priority has been encountered as the most challenging problem during the last decade as the number of users is increasing worldwide. This issue has been resolved by an advanced encryption standard (AES) algorithm, which decreases the response time and execution delay of the user-request. There are multifarious tasks, for instance, deploying the data on the cloud, that will be executed according to first come first serve (FCFS) and not on the payment basis, which provides an ease to the users. These investigated techniques are 30.21%, 25.20%, 25.30%, 30.25%, 24.26%, and 36.9 8% improved in comparison with the traditional FFOA, DE, ABC, PSO, GA, and ETC, respectively. Moreover, during iteration number 5, this approach is 15.20%, 20.22%, 30.56%, 26.30%, and 36.23% improved than that of the traditional techniques FFOA, DE, ABC, PSO, GA, and ETC, respectively. This investigated method is more efficient and applicable in certain arenas where user priority is the primary concern and can offer all the required services to the users without any interruption.
Gastric Cancer Subtypes in Tumour and Nontumour Tissues by Immunologic and Hallmark Gene Sets
Authors: Zheng Xia , Wang Yanzhong , Chen Yirui
Published: August 2022

A previous research study on differentiating gastric cancer (GC) into distinct subtypes or prognostic models was mostly based on GC tissues, which neglected the role of nontumour tissues in GC subtypes. The purpose of the research was to identify GC subtypes on the basis of tumour and adjacent nontumour tissues to assess the prognosis of GC patients. We characterized three GC subtypes on the basis of the immunologic and hallmark gene sets in GC and adjacent nontumour tissues: among them, the GC patients with subtype I had the longest survival time compared to patients with other subtypes. The classification was closely associated with T stage and pathological stage of GC patients. A prognostic model containing two gene sets was constructed by LASSO analysis. Kaplan–Meier analysis showed that patients in the high-risk group survived longer than those in the low-risk group and the two prognostic genes sets in the model were strongly correlated with survival status. Then, GO and KEGG analyses and PPI network show that nontumour and tumour tissues are influencing the prognosis of GC patients in separate manners. In summary, we emphasized the prognostic value of nontumour tissue in GC patients and proposed a novel insight that both changes in tumour and nontumour tissues should be taken into account when selecting a treatment strategy for GC.
Disseminated Histoplasmosis, Pulmonary Tuberculosis, and Cytomegalovirus Disease in a Renal Transplant Recipient after Infection with SARS-CoV-2
Authors: Mauricio Carvallo-Venegas , Angélica Fuentes-López Elsa , de Jesús Andrade-Ortega Antonio , Rodrigo Torres-Baranda José , Aldo Carrasco-Carrizosa , Ignacio Cerrillos-Gutierrez José , Jorge Andrade-Sierra
Published: August 2022

Introduction. Infection with SARS-CoV-2 increases the risk of acute graft dysfunction (AGD) in renal transplant recipients (RTR), and the risk of concurrently presenting with opportunistic infections is also increased. There is no current consensus on the management of immunosuppression during SARS-CoV-2 infection in RTR. Case Presentation. A 35-year-old male RTR from a living related donor presented with SARS-CoV-2 infection (January 2021). Two months later, despite alterations to his immunosuppression regimen (tacrolimus (TAC) was reduced by 50%, and the mycophenolic acid (MMF) was suspended with the remission of symptoms), the patient presented with pulmonary tuberculosis, pneumonia due to respiratory syncytial virus (RSV), cytomegalovirus (CMV) pneumonitis, and histoplasmosis (HP). Management was initiated with antituberculosis medications, ganciclovir, antibiotics, and liposomal amphotericin B, and the immunosuppressants were suspended, yet the patient’s evolution was catastrophic and the outcome fatal. Conclusion. We recommend that in RTR post-COVID-19, the immunosuppression regimen should be gradually reinstated along with strict vigilance in observing for highly prevalent coinfections (TB, HP, and CMV).
Application of Random Trees Model in Online Learning Perspective in Evaluating Learners’ Behavioral Engagement
Authors: Wu Meiping , Tang Tao
Published: August 2022

Under digital technology, the vigorous development of online education has also encountered challenges of different degrees, such as the high dropout rate of learners, the low completion rate of courses, and the loss of users. Learning engagement has not yet formed an effective assessment system. Based on an exploration of the core of learning activity engagement, this research evaluates the state of learning activity engagement utilizing learners’ adaptive adjustment processes of information exchange activities and a random trees model. A combined classifier is a random tree. Random trees are a combined classifier. Its main idea is to build multiple relatively independent decision tree classifiers based on two random processes, and then obtain the final prediction results by voting all decision trees. The traditional random trees model is improved by weighted calculation and aggregation calculation. After experimental analysis, it can be found that the highest can reach more than 80%, which proves that the improvement of the weighted value has a good reflection on the random trees model, and the accuracy rate is increased by 65.2% after the weighted improvement. Overall, the performance of the improved random trees model is improved by 67.3%.
Impact of Diabetic Nephropathy on Pulmonary Function and Clinical Outcomes
Authors: Niu Chunbo , Liu Lu , Li Yang , Li Xiaoqi
Published: August 2022

Objective. The main objective is to study the effect of diabetic nephropathy on pulmonary function and clinical outcomes. Methods. The method is to retrospectively analyze patients with diabetic nephropathy (DN) in our hospital from April 2018 to March 2022 as study subjects. The differences in baseline data, serum indicators, renal function indicators, and pulmonary function of patients at different clinical stages were analyzed and then explored. Finally, logistic regression was used to analyze the risk factors affecting patients’ clinical outcomes and to evaluate the diagnostic effects. Results. Baseline information (age, disease duration, BMI, and systolic and diastolic blood pressure), serum indicators (HbA1c, FBG, 2hPG, TG, TC, and LDLC), renal function indicators (CysC, BUN, and Scr), and pulmonary function (TLC, VC, FEV1, FEV1/FVC, MVV, MEF25, MEF50 MEF75, DLCO, and DLCO/VA) were significantly different

P
<
0.01

; multiple logistic regression analysis showed that SBP, HbA1c, FBG, 2hPG, BUN, Scr, TLC, VC, FEV1/FVC, MVV, DLCO, and DLCO/VA were all key factors in the development of clinical outcomes in DN

P
<
0.05

. ROC analysis showed that all of these important factors had an AUC greater than 0.75 for the diagnosis of DN with high sensitivity and specificity. Conclusion. Serum and renal function indices of DN patients gradually increased with stage, accompanied by a decrease in pulmonary ventilation, and diffusion function; SBP, HbA1c, FBG, 2hPG, BUN, Scr, TLC, VC, FEV1/FVC, MVV, DLCO, and DLCO/VA were all key factors affecting the clinical outcome of DN; controlling blood glucose, lipids, improving pulmonary ventilation, and diffusion function can better prevent the occurrence and worsening of DN.
Intelligent Financial Auditing Model Based on Deep Learning
Authors: Dai Xiaofeng , Zhu Weidong
Published: August 2022

The entire auditing process is complicated and tedious and requires a lot of human resources. Therefore, the intelligent development of auditing is the general trend. In order to improve the audit quality, this paper establishes an intelligent financial audit model that can predict the audit opinion of the consolidated financial statements. This paper proposes an audit opinion prediction model based on the fusion of deep belief neural network (DBN) and long-short term memory (LSTM). First, an indicator system is established for audit opinions, and multiple financial parameters are used to describe possible audit opinions. On this basis, a DBN network is designed to complete deep feature extraction and used for LSTM training. According to the prediction model obtained by training, the subsequent audit opinion can be scientifically predicted. In the experiment, the method in this paper is tested based on financial audit related data sets and compared with the prediction results of traditional multilayer perceptron (MLP), convolutional neural network (CNN), and LSTM models. The results verify the validity and reliability of the model in this paper.
Postoperative Nursing and Functional Rehabilitation of Ultrasound Diagnosis of Lower Rotator Cuff Injury
Authors: Hou Riying
Published: August 2022

In order to explore the postoperative nursing effect and functional rehabilitation of rotator cuff repair under ultrasound diagnosis, a method of nursing and rehabilitation functional training for athletes’ wrist injury under the assistance of microscopic B-ultrasound was proposed. This study retrospectively analyzed the therapeutic effect of tendon anastomosis in 237 patients with wrist tendon injury, adopted nursing measures such as health education and functional exercise, and observed its clinical effect. The results showed that after 3-6 months of follow-up, all patients had satisfactory recovery of tendon function. Of these, 132 patients recovered well. 84 patients recovered well. The excellent and good rate of patients was 91%. Ultrasound diagnosis of rotator cuff repair combined with functional exercise promotes good recovery of shoulder joint function in patients.
Identification and Validation of Two Heterogeneous Molecular Subtypes and a Prognosis Predictive Model for Hepatocellular Carcinoma Based on Pyroptosis
Authors: Lai Minshan , Liu Qiang , Chen Wenbo , Qi Xuxin , Yang Jianfeng , Jiang Li , Yuan Meng , Liu Zhichun , He Qiaojun , Cao Ji , Yang Bo
Published: August 2022

Hepatocellular carcinoma (HCC) is a worldwide malignant cancer with high incidence and mortality. Considering the high heterogeneity of HCC, clarifying molecular characteristics associated with HCC development could help improve patients’ outcomes. Pyroptosis is a novel form of cell death and is noted to be implicated in HCC pathogenesis whereas its molecular feature in HCC is unclear. Thus, we intended to clarify the molecular characteristic as well as the clinical significance of pyroptosis for HCC. A systematic bioinformatics analysis was conducted among 40 pyroptosis-related genes based on The Cancer Genome Atlas, the International Cancer Genome Consortium, and the Gene Expression Omnibus databases. A total of 12 HCC-associated pyroptosis-related genes (HPRGs) were identified to be overexpressed in HCC tissues and significantly connected to patients’ poor survival. Through consensus clustering based on the HPRGs’ expression, we found patients could be stratified into two distinctive pyroptosis subtypes, PyLow and PyHigh. The PyHigh group owned a notable lower survival rate and a higher high-grade proportion compared with the PyLow subtype. Besides, patients’ sensitivities to chemotherapeutic drugs also presented distinctive differences between the two subtypes. Indicated by pathway enrichment analysis and immune characteristic difference analysis, the distinctions between the pyroptosis subtypes may be related to tumor immunity. Further, a five-gene risk model composed of BAK1, CHMP4A, CHMP4B, DHX9, and GSDME was established. Subsequent analyses demonstrated that the model could credibly classify patients as low or high risk and was an independent prognostic indicator for HCC. Abnormal expressions of the five genes were validated by biological experiments and new bioinformatics analysis. In conclusion, this study recognized and verified two heterogeneous pyroptosis subtypes and a predictable prognosis model for HCC. Our work may help facilitate the clinical management and treatment of HCC and understand the functions of pyroptosis in oncology.