bluuebunny/crossref_metadata_2025 huggingface dataset:
Wireless Sensor Modeling Optimization Algorithm Based on Artificial Intelligence Neural Network
Authors: Ma Yanying , Liu Qiang , Sun Bohua , Li Xiuzhen , Liu Ying
Published: July 2022

With the development and progress of society, science and technology have entered the field of view of scholars at home and abroad. As the science and technology with the biggest potential in recent years, wireless sensor network has been involved in many scientific fields. This paper aims to study the wireless sensor modeling optimization algorithm of artificial intelligence neural network. In this paper, a WSN data fusion algorithm (DFRMP) based on regression model prediction is proposed, and the four algorithms of SLR, PAQ, TINA, and DFRMP are compared. The experimental results of this paper show that when the mean square error and mean absolute error are not much different, the data transmission rate of DFRMP algorithm is the smallest. When the absolute error threshold is 1, the data transfer rates of these four algorithms are 0.033, 0.0327, 0.035, and 0.017, respectively. This shows that the DFRMP algorithm proposed in this paper has superior performance.
Bilateral Harnack Inequalities for Stochastic Differential Equation with Multiplicative Noise
Authors: An Zihao , Zong Gaofeng
Published: July 2022

By constructing a coupling with unbounded time-dependent drift, a lower bound estimate of dimension-free Harnack inequality with power is obtained for a large class of stochastic differential equation with multiplicative noise. The key is an application of the inverse Hölder inequality. Combining this with the well-known upper bound, bilateral dimension-free Harnack inequality with power is established. As a dual inequality, the bilateral shift-Harnack inequalities with power are also investigated for stochastic differential equation with additive noise. Applications to the study of heat kernel inequalities are provided to illustrate the obtained inequalities.
[Retracted] The Balance Reaction Ability of Teenagers Based on the Evaluation Model of Unbalanced Sports Quotient
Authors: Yang Xiwen , He Ruihua
Published: July 2022

Dynamic balance is particularly important for the maintenance, transformation, and restabilization of various postures of the human body. Combined with the characteristics of unbalanced sports events, although there is no physical contact in sports events, it has intense antagonism due to the constant change of body movement. Athletes need to have the ability of fast movement and continuous high‐intensity multibeat confrontation. They need to adjust their body posture any time according to the situation, constantly move their body from one side to the other side in fast movement, and constantly change between being imbalanced and being stable to keep the center of gravity stable and adjust their body posture. Combining with the characteristics of unbalanced sports, this paper is aimed at the problem that young athletes have poor dynamic balance ability and cannot maintain the stability of their body’s center of gravity in the process of fast multidirectional movement and braking. The supporting leg needs ankle dorsiflexion, knee flexion, and hip flexion during SEBT testing. Therefore, the lower limb needs sufficient range of motion, strength, proprioception, and neuromuscular control ability to achieve the optimal test results. A randomized controlled experiment was used to test whether there were significant differences in the test indicators between the experimental group and the control group before and after the experiment by using a paired test. The test indicators between the experimental group and the control group before and after the intervention were tested by independent sample test to explore the influence of core balance training on the dynamic balance ability of teenagers in unbalanced sports. Through analysis, it is proved that strengthening balance exercise can significantly improve the functional movements and physical fitness of adolescents, which is of great significance to the development of basic flexibility and stability of joints and the strengthening of weak chain muscles.
Research on Mining Balanced Competition Strategy in Financial Market Based on Computer Data Mining Method
Authors: Sun Lishan
Published: July 2022

The mining process of traditional market equilibrium competition strategy is difficult to deal with massive data, resulting in the inability to accurately classify customer data in the process of competition strategy customization. Therefore, this paper proposes a strategy formulation method of balanced competition in the financial market based on computer data mining. Firstly, the process of the k-means clustering algorithm was optimized, and Murkowski distance and Markov distance were used as classification basis to find some potential information hidden in the data. Based on the optimized K-means clustering algorithm for data processing, in order to achieve effective data analysis, design customer behavior data mining process and analyze customer value matrix and customer pyramid. Finally, the layout framework of a balanced competition strategy in the financial market is established. The results show that the classification accuracy of the design method is higher than that of the traditional method in different states.
Novel PSO Optimized Voting Classifier Approach for Predicting Water Quality
Authors: Agrawal Shweta , Jain Sanjiv Kumar , Khatri Ajay , Agarwal Mohit , Tripathi Anshul , Hu Yu-Chen
Published: July 2022

Over the last few years, different contaminants have posed a danger to the quality of the water. Hence modelling and forecasting water quality are very important in the management of water contamination. The paper proposes an ensemble machine learning-based model for assessing water quality. The results of the proposed model are compared with several machine learning models, including k-nearest neighbour, Naïve Bayes, support vector machine, and decision tree. The considered dataset contains seven statistically important parameters: pH, conductivity, dissolved oxygen, Biochemical Oxygen Demand, nitrate, total coliform, and fecal coliform. The water quality index is calculated for assessing water quality. To utilize an ensemble approach, a voting classifier has been designed with hard voting. The highest prediction accuracy of 99.5% of the water quality index is presented by the voting classifier as compared to the prediction accuracy of 99.2%, 90%, 79%, and 99% presented through k-nearest neighbour, Naïve Bayes, support vector machine, and decision tree, respectively. This was further enhanced to 99.74% using particle swarm based optimization.
Clinical Variation in the Treatment Practices for Medication Nonadherence, Drug–Drug Interactions, and Recognition of Disease Progression in Patients with Chronic Cardiometabolic Diseases: A Cross-Sectional Patient Simulation Study among Primary Care Physicians
Authors: Valdenor Czarlota , Ganesan Divya , Paculdo David , Schrecker Joshua , Heltsley Rebecca , Westerfield Christopher , Peabody John W.
Published: July 2022

Background. Medication nonadherence in patients with chronic diseases is common, costly, and often underdiagnosed. In the United States, approximately 40–50% of patients with cardiometabolic conditions are not adherent to long-term medications. Drug–drug interactions (DDI) are also underrecognized and may lead to medication nonadherence in this patient population. Treatment complexity associated with cardiometabolic conditions contributes to increased risk for adverse drug events and DDIs. Methods. We recruited a nationally representative sample of 246 board-certified family and internal medicine physicians to evaluate how they assessed, identified, and treated medication nonadherence, DDIs, and worsening disease. Participating physicians were asked to care for three online simulated patients, each with at least one chronic cardiometabolic disease, including atrial fibrillation, heart failure, diabetes mellitus, or hypertension, and who were taking prescription medications for their disease. Physicians’ scores were based on evidence-based care recommendation criteria, including overall care quality and treatment for medication nonadherence and DDIs. Results. Overall, quality-of-care scores across all cases ranged from 13% to 87% with an average of 50.8% ± 12.1%. The average overall diagnostic plus treatment score was 21.9% ± 13.6%. Participants identified nonadherence in just 3.6% of cases, DDIs in 8.9% of cases, and disease progression in 30.3% of cases. Conclusions. Based on these study results, primary care physicians were unable to adequately diagnose and treat patients with chronic cardiometabolic diseases who either suffered from medication nonadherence, DDIs, or progression of the disease. Improved standardization and technique in identifying these diagnoses is needed in primary care. Trial Registration. This trial is registered with clinicaltrials.gov, NCT05192590.
A Multivariate Evaluation Model of Physical Education Teaching Quality with Random Matrix Optimization Neural Network
Authors: Zhang Wang , Wen Yu
Published: July 2022

The status of physical education courses in education is increasing, there are many problems in teaching traditional physical education courses, and information technology and information-based education are developing continuously, providing enough space for the research of the topic. The online teaching of public physical education courses in colleges and universities is very complex, and its quality evaluation faces many difficulties. Considering the problem that most traditional PE teaching quality evaluation methods are affected by the accuracy of the established model in the process of positioning, a PE teaching quality evaluation model based on random matrix theory is established by using the advantage that random matrix theory does not rely on the simplification and assumptions of the system model and can extract effective information from a large amount of data. Firstly, the influencing factor data and physical education state data are constructed as a state augmentation matrix. Then, the average spectral radius of the characteristic statistic is used to construct indicators to analyze the size of the correlation between each influencing factor and physical education state to achieve the fundamental positioning of physical education quality. The main influencing factors of online teaching of public physical education classes in colleges and universities mainly include teacher quality, teaching process, course resources, and course effect, and the construction of an evaluation index system should be implemented based on adhering to the scientificity, accessibility, independence, and generality from these four aspects to construct the evaluation index system and evaluation criteria of online teaching quality of public physical education class in colleges and universities, which provides the final realization of the goal of physical education class in colleges and universities.
Synthesis of Nickel Sulfide Thin Films and Nanocrystals from the Nickel Ethyl Xanthate Complex
Authors: Kotei Patience Adei , Boadi Nathaniel Owusu , Saah Selina Ama , Mensah Michael Baah
Published: July 2022

Nickel sulfides have unique and diverse structural features, making them ideal for energy conversion and storage. This research focuses on the synthesis and characterization of nickel sulfide thin films and nanocrystals from nickel ethyl xanthate complex using spin-coating and solventless methods. The nickel ethyl xanthate complex (C6H10S4NiO2) was characterized using Fourier-transformed infrared (FT-IR), ultraviolet-visible (UV-Vis), and nuclear magnetic resonance (NMR) spectroscopies as well as thermogravimetric analysis (TGA). The NiS thin films and nanoparticles were analyzed with energy dispersive X-ray (EDX) spectroscopy and X-ray diffraction (XRD). Nickel ethyl xanthate was synthesized in an 81.2% yield. The bandgaps of the nickel sulfide obtained from the spin-coating method ranged from 4.35–4.88 eV. For the solventless method, the bandgap of the nickel sulfide ranged from 3.93–3.96 eV. The crystal phase observed from the spin-coating and solventless methods was α-NiS (hexagonal). A direct correlation was observed between annealing temperature, bandgap, and particle size.
Succinimide Derivatives as Antioxidant Anticholinesterases, Anti-α-Amylase, and Anti-α-Glucosidase: In Vitro and In Silico Approaches
Authors: Alshehri Osama M. , Mahnashi Mater H. , Sadiq Abdul , Zafar Rehman , Jan Muhammad Saeed , Ullah Farhat , Alshehri Mohammed Ali , Alshamrani Saleh , Hassan Elhashimi E.
Published: July 2022

Based on the diverse pharmacological potency and the structural features of succinimide, this research considered to synthesize succinimide derivatives. Moreover, these compounds were estimated for their biological potential in terms of anti-diabetic, anti-cholinesterase, and anti-oxidant capacities. The compounds were synthesized through Michael addition of various ketones to N-aryl maleimides. Similarly, the MOE software was used for the molecular docking study to explore the binding mode of the potent compounds against different enzymes. In the anti-cholinesterase activity, the compounds MSJ2 and MSJ10 exhibited outstanding activity against acetylcholinesterase (AChE), i.e., 91.90, 93.20%, and against butyrylcholinesterase (BChE), i.e., 97.30, 91.36% inhibitory potentials, respectively. The compounds MSJ9 and MSJ10 exhibited prominent α-glucosidase inhibitory potentials, i.e., 87.63 and 89.37 with IC50 value of 32 and 28.04 μM, respectively. Moreover, the compounds MSJ2 and MSJ10 revealed significant scavenging activity against DPPH free radicals with IC50 values of 2.59 and 2.52, while against ABTS displayed excellent scavenging potential with IC50 values 7.32 and 3.29 μM, respectively. The tentative results are added with molecular docking studies in the active sites of enzymes to predict the theoretical protein-ligand binding modes. Further detailed mechanism-based studies in animal models are essential for the in vivo evaluation of the potent compound.
Comparative Study on the Effect of Various Aerobic Exercises on College Students’ Weight Loss Based on Deep Learning Analysis
Authors: Li Fanghui , Huang Yongtian , Luo Yijun , He Jing
Published: July 2022

In order to solve the problem of higher obesity rate of college students and meet the needs of college students to lose weight effectively, a comparative study on the effect of various aerobic exercises on college students’ weight loss based on in-depth learning analysis is proposed. The experiment shows that 30 subjects who voluntarily participated in the weight loss experiment and research were selected from a university, including 16 men and 14 women. It shows that aerobic exercise plays an important role in improving people’s energy metabolism. Based on the deep unsupervised learning algorithm, this paper studies the effect of a variety of aerobic exercises on college students’ weight loss. It is found that visceral fat obese people are easier to lose weight than outer skin fat obese people. With the help of aerobic exercise to lose weight, we should choose the aerobic exercise items significantly increased in EPOC during exercise recovery according to the obesity characteristics and types of different college students so that the effect of exercise weight loss is more effective.
Design of Health Detection System for Elderly Smart Watch Based on Biosignal Acquisition
Authors: Zhu Zhu , Wang Peixian , Wang Fuguang
Published: July 2022

The health monitoring of the elderly has attracted increasing attention of researchers. Based on the biosignal acquisition method, this paper proposes a design structure of the health detection system for smart watches for the elderly and realizes the effective detection of health signals by analyzing the Lipschitz exponent of the maximum value column of the transform. The multiphysiological parameter acquisition and monitoring system of the wearable smart watch designed in this paper can continuously monitor the physiological parameters of the elderly such as body temperature, pulse, and respiration for a long time and solve the problem of the accuracy of the health detection of the elderly. In the simulation process, based on the performance of the synchronization source and the difference of the network path, the model applies the multivariate and multiscale biological signals to collect the human gait acceleration. The experimental results show that, compared with the international recognition rate obtained for this data set, the highest recognition rate obtained by the method in this paper reaches 96.5%, which can provide a calibration accuracy of 1 ~ 50 ms, and the synchronized system time and the national time service center network are given. The error obtained by comparing the published time is within 50 ms, which meets the accuracy requirements of the time protocol. The results fully prove that the algorithm in this paper can effectively extract the biosignal features of the elderly’s health detection and has good statistical features and classification accuracy.
Serum Biomarkers for Chronic Renal Failure Screening and Mechanistic Understanding: A Global LC-MS-Based Metabolomics Research
Authors: Su Xiaojuan , Ren Ruru , Yang Lingling , Su Chao , Wang Yingli , Lu Jun , Liu Jing , Zong Rong , Lu Fangfang , Wilson Gidion , Ding Shuqin , Ma Xueqin
Published: July 2022

Chronic kidney disease, including renal failure (RF), is a global public health problem. The clinical diagnosis mainly depends on the change of estimated glomerular filtration rate, which usually lags behind disease progression and likely has limited clinical utility for the early detection of this health problem. Now, we employed Q-Exactive HFX Orbitrap LC-MS/MS based metabolomics to reveal the metabolic profile and potential biomarkers for RF screening. 27 RF patients and 27 healthy controls were included as the testing groups, and comparative analysis of results using different techniques, such as multivariate pattern recognition and univariate statistical analysis, was applied to screen and elucidate the differential metabolites. The dot plots and receiver operating characteristics curves of identified different metabolites were established to discover the potential biomarkers of RF. The results exhibited a clear separation between the two groups, and a total of 216 different metabolites corresponding to 13 metabolic pathways were discovered to be associated with RF; and 44 metabolites showed high levels of sensitivity and specificity under curve values of close to 1, thus might be used as serum biomarkers for RF. In summary, for the first time, our untargeted metabolomics study revealed the distinct metabolic profile of RF, and 44 metabolites with high sensitivity and specificity were discovered, 3 of which have been reported and were consistent with our observations. The other metabolites were first reported by us. Our findings might provide a feasible diagnostic tool for identifying populations at risk for RF through detection of serum metabolites.
Nano-SiO2 and PVA Fiber Synergistically Strengthened Concrete to Optimize the Antifreeze, Antipermeability, and Anticorrosion Performance of Roads
Authors: Tang Li
Published: July 2022

As a modified material, nano-SiO2 can be compounded with many high molecular polymer resins to improve the performance of the polymer and be used as a concrete filler. PVA is a kind of synthetic fiber made of high-quality polyvinyl alcohol with a high degree of polymerization and processed by specific advanced technology. This research mainly discusses the optimization of the antifreeze, antipermeability, and anticorrosion performance of the concrete reinforced by nano-SiO2 and PVA fiber synergistically. In this paper, nanosilica PVA fiber-modified concrete was synthesized. Through compressive strength test, split tensile strength test, rapid freeze-thaw test, and microstructure test (X-ray diffraction and scanning electron microscope), this paper also analyzed the modification effect of PVA fiber concrete in different blends and the corresponding mechanism of nanoparticles. The instrument model of the scanning electron microscope used is S-4700; the manufacturer is Hitachi, a Japanese company; and the test voltage is 20 kV. Before the test, the hydrogel was placed in a freeze-drying oven at −40°C for 48 hours to remove water. Then, we put the sample in liquid nitrogen and break. The morphology of the cross-section was observed by SEM, and the microscopic morphology changes brought by different amounts of MTMS to the hydrogel were analyzed. After the test piece is immersed in water to reach a saturated state, we check the appearance size of the test piece, wipe the surface of the test piece clean with a rag, weigh the unfreeze-thaw test piece, then measure the ultrasonic wave speed of the test piece with a nondestructive testing instrument, and do good record. After every 25 freeze-thaw cycles, we measure the mass and relative dynamic elastic modulus of each group of specimens, make corresponding records, then put them into the freeze-thaw box, and add clean water as the freeze-thaw medium to continue the test. The average initial crack load of the three specimens of

W

W3 is increased by 52% compared with that of the specimens of

W

W1, and the load of

W

W4 is increased by 77%. This research helps promote the application of concrete on roads.
Formative Assessment of College English Autonomous Learning Based on Fuzzy Comprehensive Evaluation Algorithm
Authors: Li Yalei
Published: July 2022

With the rapid development of computer networks and multimedia technology, independent e-learning has become an integral part of modern education. However, the allocation of time and space for teaching and learning, the lack of instruction and guidance necessary for self-directed learning for students, and the development of e-learning are becoming increasingly problematic. Because of this, this thesis uses guided evaluation to determine the impact of improving the quality of Student learning. Firstly, under the background of college English web-based autonomous learning, this paper constructs a formative assessment index system and then combines the formative assessment with fuzzy comprehensive evaluation algorithm to form a formative assessment of college English web-based autonomous learning. Fuzzy comprehensive evaluation is an important application of analyzing complex fuzzy systems using the principle of fuzzy transformation. The simulation uses the online learning English behavior of college students to carry out an example evaluation. The results show that students can find their own shortcomings in network autonomous learning, which can be improved in later learning.
Analysis and Recognition of Clinical Features of Diabetes Based on Convolutional Neural Network
Authors: Wang Rui , Li Ping , Yang Zhengfei
Published: July 2022

Diabetes mellitus is a common chronic noncommunicable disease, the main manifestation of which is the long-term high blood sugar level in patients due to metabolic disorders. However, due to excessive reliance on the clinical experience of ophthalmologists, our diagnosis takes a long time, and it is prone to missed diagnosis and misdiagnosis. In recent years, with the development of deep learning, its application in the auxiliary diagnosis of diabetic retinopathy has become possible. How to use the powerful feature extraction ability of deep learning algorithm to realize the mining of massive medical data is of great significance. Therefore, under the action of computer-aided technology, this paper processes and analyzes the retinal images of the fundus through traditional image processing and convolutional neural network-related methods, so as to achieve the role of assisting clinical treatment. Based on the admission records of diabetic patients after data analysis and feature processing, this paper uses an improved convolutional neural network algorithm to establish a model for predicting changes in diabetic conditions. The model can assist doctors to judge the patient’s treatment effect by using it based on the case records of inpatient diagnosis and treatment and to predict the risk of readmission of inpatients after discharge. It also can help to judge the effectiveness of the treatment plan. The results of the study show that the model proposed in this paper has a lower probability of misjudging patients with poor recovery as good recovery, and the prediction is more accurate.
Huangjia Ruangan Granule Inhibits Inflammation in a Rat Model with Liver Fibrosis by Regulating TNF/MAPK and NF-κB Signaling Pathways
Authors: Cai Qiang , Wang Zongquan , Zhang Rong , Zhang Lili , Cui Sainan , Lin Huiyuan , Tang Xinran , Yang Dongying , Lin Xianrong , Bai Shasha , Gao Jin , Yang Lei
Published: July 2022

The Huangjia Ruangan granule (HJRG) is a clinically effective Kampo formula, which has a significant effect on liver fibrosis and early liver cirrhosis. However, the mechanism underlying HJRG in treating liver fibrosis remains unclear. In this study, carbon tetrachloride (CCl4) was used to induce liver fibrosis in rats to clarify the effect of HJRG on liver fibrosis and its mechanism. Using network pharmacology, the potential mechanism of HJRG was initially explored, and a variety of analyses were performed to verify this mechanism. In the liver fibrosis model, treatment with HJRG can maintain the liver morphology, lower the levels of AST and ALT in the serum, and ameliorate pathological damage. Histopathological examinations revealed that the liver structure was significantly improved and fibrotic changes were alleviated. It can effectively inhibit collagen deposition and the expression of α-SMA, reduce the levels of the rat serum (HA, LN, PC III, and Col IV), and inhibit the expression of desmin, vimentin, and HYP content in the liver. Analyzing the results of network pharmacology, the oxidative stress, inflammation, and the related pathways (primarily the TNF signaling pathway) were identified as the potential mechanism of HJRG against liver fibrosis. Experiments confirmed that HJRG can significantly increase the content of superoxide dismutase and glutathione and reduce the levels of malondialdehyde and myeloperoxidase in the rat liver; in addition, HJRG significantly inhibited the content of proinflammatory cytokines (TNF-α, IL-1β, and IL-6) and reduced the expression of inflammatory regulators (Cox2 and iNOS). Meanwhile, treatment with HJRG inhibited the phosphorylation of NF-κB P65, IκBα, ERK, JNK, and MAPK P38. Moreover, HJRG treatment reversed the increased expression of TNFR1. The Huangjia Ruangan granule can effectively inhibit liver fibrosis through antioxidation, suppressing liver inflammation by regulating the TNF/MAPK and NF-κB signaling pathways, thereby preventing the effect of liver fibrosis.
SARS-CoV-2 Spike Protein Vaccine-Induced Immune Imprinting Reduces Nucleocapsid Protein Antibody Response in SARS-CoV-2 Infection
Authors: Delgado Juan F. , Vidal-Pla Mónica , Moya M. Carmen , Espasa Mateu , Casabella Antonio , Seda Manel , Calvet Joan , Gratacós Jordi , Serrano Rosa M. , Peña Pilar
Published: July 2022

Immune imprinting or original antigenic sin (OAS) is the process by which the humoral memory response to an antigen can inhibit the response to new epitopes of that antigen originating from a second encounter with the pathogen. Given the situation of the COVID-19 pandemic, multiple vaccines have been developed against SARS-CoV-2 infection. These vaccines are directed to the spike protein (S protein) of the original variant of Wuhan D614G. Vaccine memory immune response against S protein in noninfected subjects could inhibit, through the OAS mechanism, the response to new epitopes of SARS-CoV-2 after infection. The present study analyzes whether the memory antibody B cell response generated by mRNA vaccines against S protein can inhibit the primary antibody immune response to other SARS-CoV-2 antigens, such as nucleocapsid protein (N protein). SARS-CoV-2 primary infection in vaccinated healthcare workers (HCWs) produced significantly lower titers of anti-N antibodies than that in nonvaccinated HCWs: 5.7 (IQR 2.3-15.2) versus 12.2 (IQR 4.2-32.0), respectively (

p
=
0.005

). Therefore, spike protein vaccine-induced immune imprinting (original antigenic sin) reduces N protein antibody response.
Single-Cell RNA Sequencing Reveals the Role of Epithelial Cell Marker Genes in Predicting the Prognosis of Colorectal Cancer Patients
Authors: Shen Kai-yu , Chen Bin-yu , Gao Wen-cang
Published: August 2022

Single-cell RNA sequencing (scRNA-seq) is increasingly used in studies on gastrointestinal cancers. This study investigated the prognostic value of epithelial cell-associated biomarkers in colorectal cancer (CRC) using scRNA-seq data. We downloaded and analysed scRNA-seq data from four CRC samples from the Gene Expression Omnibus (GEO), and we identified marker genes of malignant epithelial cells (MECs) using CRC transcriptome and clinical data downloaded from The Cancer Genome Atlas (TCGA) and GEO as training and validation cohorts, respectively. In the TCGA training cohort, weighted gene correlation network analysis, univariate Cox proportional hazard model (Cox) analysis, and least absolute shrinkage and selection operator regression analysis were performed on the marker genes of MEC subsets to identify a signature of nine prognostic MEC-related genes (MECRGs) and calculate a risk score based on the signature. CRC patients were divided into high- and low-risk groups according to the median risk score. We found that the MECRG risk score was significantly correlated with the clinical features and overall survival of CRC patients, and that CRC patients in the high-risk group showed a significantly shorter survival time. The univariate and multivariate Cox regression analyses showed that the MECRG risk score can serve as an independent prognostic factor for CRC patients. Gene set enrichment analysis revealed that the MECRG signature genes are involved in fatty acid metabolism, p53 signalling, and other pathways. To increase the clinical application value, we constructed a MECRG nomogram by combining the MECRG risk score with other independent prognostic factors. The validity of the nomogram is based on receiver operating characteristics and calibration curves. The MECRG signature and nomogram models were well validated in the GEO dataset. In conclusion, we established an epithelial cell marker gene-based risk assessment model based on scRNA-seq analysis of CRC samples for predicting the prognosis of CRC patients.
Art Financial Risk Prediction Algorithm Based on Random Matrix
Authors: Guo Shiqin , Xu Jilin
Published: July 2022

Random matrix theory is applied in the financial field to study the correlation of the financial correlation coefficient matrix, which is a key factor in network construction. In this paper, the random matrix theory is combined with network construction to study the art financial risk prediction algorithm based on the random matrix. Based on the stochastic matrix theory and the key nodes of the network, the financial network and the “noise” network before and after the “denoising” are analyzed and compared. It is found that the key and important information of the original network is still retained after the “denoising” of the network, and the noise information corresponds to the information represented by the smaller nodes in the original network. Based on the stochastic matrix of artwork financial risk prediction, the topological properties of the financial network before and after denoising are analyzed and compared from the perspectives of minimum spanning tree, model, and community structure. Based on the random matrix theory, this paper discusses the financial correlation coefficient matrix and the statistical properties of the eigenvalues of the random matrix, and on this basis, the existing denoising methods are improved, the correlation coefficient matrix more suitable for constructing the financial network is established, and the art financial risk prediction algorithm is constructed. Then, based on the stochastic matrix theory and the key nodes of the network, the financial network and the noise network before and after denoising are analyzed and compared. It is found that the key and important information of the original network is still retained after denoising the network, and the noise information corresponds to the information represented by the relatively small nodes in the original network. Finally, based on the stochastic matrix of art financial risk prediction, analysis of the financial network topology, such as minimum spanning tree, model, and community structure, found that the improved financial network topology is more obvious and the structure is closer.
Treatment Alternative and High Safety Profile of Acupuncture Plus Chemotherapy for Advanced Gastric Cancer
Authors: Miao Xiaomei , Wu Hongying , Liu Yan , Zhang Shu , Li Chaohui , Hao Jie
Published: July 2022

Objective. The aim of this study is to evaluate the safety and tumor marker level changes of acupuncture plus chemotherapy (FOLFOX4) for advanced gastric cancer. Methods. One hundred and twenty patients with advanced gastric cancer who were treated at our hospital between May 2019 and April 2021 were recruited for prospective analysis, and all patients were allocated to the control and experimental groups in a 1 : 1 ratio using the random number table method, with 60 patients in each group. They received either chemotherapy using the FOLFOX4 regimen (control group) or the FOLFOX4 chemotherapy plus acupuncture (experimental group). Outcome measures included tumor marker levels, quality of life, and adverse events. Results. Before treatment, the two groups showed similar tumor markers levels and the MOS 36-item short-form health survey (SF-36) scores (

P
>
0.05

). FOLFOX4 chemotherapy plus acupuncture was associated with significantly lower levels of carcinoembryonic antigen (CEA), carbohydrate antigen (CA) 19-9, and CA72-4 versus FOLFOX4 chemotherapy alone (

P
<
0.05

). The patients who were given FOLFOX4 chemotherapy plus acupuncture showed significantly increased SF-36 scores versus monotherapy of the FOLFOX4 regimen (

P
<
0.05

). The joint therapy resulted in a significantly lower incidence of adverse events versus the monotherapy (

P
<
0.05

). Conclusion. Acupuncture plus chemotherapy using the FOLFOX4 regimen can effectively regulate the serum tumor marker levels of patients with advanced gastric cancer, with a high safety profile, which provides a viable treatment alternative.
Optimizing Language Teachers’ Competencies Based on Big Data Technology
Authors: Miao Xia , Wang Yanping
Published: July 2022

Using big data technology to promote the maturity and application of human analysis is the key to establish and maintain the competitive advantage of the school. Modern teachers must have the quality and ability to adapt to their work, that is, professional ability, in order to improve the teaching quality more pertinently. In order to effectively promote teachers’ professional growth, this paper proposes a Chinese teachers’ Ability Optimization Model Based on big data technology. Chinese teachers should take the initiative to meet the mission and challenges given by the times, strengthen Chinese teaching ability through the promotion of microability of information technology, explore the changes of learning and teaching style under the environment of information technology, and improve the ability of Chinese teachers. The research on the ability optimization of Chinese teachers based on big data technology in this paper can help schools optimize the training plan system by using the winning power model, that is, the training plan system can be improved from three aspects: determining the training objectives and contents and selecting the training methods. Teachers must improve their abilities through continuous learning, so as to promote education more actively and cultivate more talents for the country.
Challenges and Innovative Countermeasures Faced by Public Administration in the Context of Big Data and Internet of Things
Authors: Jin Wenfang
Published: July 2022

With the advent of nonrelational databases, data science has gradually become the focus of attention in academia and engineering. The data generated by human social networking is also gradually increasing, and big data technology appears in this context. Its main purpose is to obtain key information from complex data sets and realize the role of comprehensive analysis. In recent years, the concept of the Internet of Everything has gradually entered all walks of life. Similar to the design of smart cities, smart communities, and smart buildings, IoT technology has also been adopted. The development of the market economy and the deepening of the reform of the economic system require that the government’s public services must also be transformed as soon as possible. The responsibilities undertaken by the government are becoming more and more complex and important. The traditional government public management methods cannot meet the needs of all levels of society. The development of big data and the Internet of Things provides new opportunities for the government to innovate management methods, which is also one of the cores of future government work. The government needs to gradually transform the government’s public management method based on big data and the Internet of Things platform, relying on information technology, so as to improve people’s satisfaction and happiness index. Based on the problems existing in traditional public management, this paper focuses on the analysis of local government management methods and takes Shenyang City as the case analysis object to innovate local government public management methods and at the same time provides some reference for other regions to innovate public management methods.
The Effect of Amniotic Membrane Transplantation on Trabeculectomy in Patients with Pseudoexfoliation Glaucoma
Authors: Kim Huikyung , Moon Sangwoo , Kim Jinmi , Lee Jiwoong
Published: July 2022

Purpose. The aim is to evaluate the effect of amniotic membrane transplantation (AMT) on trabeculectomy with mitomycin C in patients with pseudoexfoliation glaucoma (PXG). Methods. This retrospective cohort study included 85 eyes of PXG who underwent trabeculectomy with or without AMT (52/33 eyes in the AMT/control group). Surgical success was defined by these criteria: (1) intraocular pressure (IOP) ≤18 mmHg and IOP reduction

≥

20% and (2) IOP ≤15 mmHg and IOP reduction

≥

25%. Criteria A and B defined complete success rates as patients who met these criteria without medication, respectively. Criteria C and D defined qualified success rates as patients who met these criteria with medication, respectively. Cumulative probabilities of success were compared using the Kaplan–Meier survival analysis. Cox proportional hazard models were used to evaluate the influence of AMT on surgical success accounting for confounding variables. Results. For the AMT group, compared with the control group, the complete success rates at 12 months for criterion A were 86.5% and 63.6%, respectively (

P
=
0.017

) and for criterion B, 86.4% and 63.6% (

P
=
0.005

). The qualified success rates at 12 months for criterion C were 92.1% and 75.1%, respectively (

P
=
0.047

) and for criterion D, 92.1% and 72.1% (

P
=
0.021

). On multivariable Cox regression analyses, AMT was associated with a lower failure rate on criteria A, B, and D (all

P
≤
0.047

). Incidence of avascular bleb was higher in the control group than in the AMT group (7 vs 0 eyes;

P
=
0.004

). Conclusions. In patients with PXG, trabeculectomy with AMT was associated with higher success rates and a lower incidence of avascular bleb compared with conventional trabeculectomy. Research Registration. This retrospective cohort study was registered at the Clinical Trial Registry of Korea (https://cris.nih.go.kr/cris/index/index.do, KCT0007228).
Study on the In Situ Test of the Treatment Effect for the Riverbank Soft Soil Subgrade in the Hetao Area
Authors: Zuo Shen , Li Tian-yu , Jiang Peng , Zuo Xiang-long , Li Jin
Published: July 2022

The Inner Mongolia Hetao area has a widely distributed riverbank fluvial soft soil with high groundwater levels and ground surface water. This situation may incur some potential engineering problems for the Linhe-Baigeda section of the Beijing-Xinjiang Expressway, such as subgrade settlement control and waterproofing. In situ experiments were conducted on the site using five subgrade base treatment schemes for subgrade construction. The long-term monitoring of various technical indicators like settlement, earth pressure, pore water pressure, and reinforcement material deformation was carried out. Study results show that the cumulative settlement generated when the double-layer geogrid reinforces the subgrade base is 6.9 cm, which is the smallest among the five subgrade base reinforcement methods, and the cumulative settlement of the subgrade base reinforced with a single-layer geocell is the largest, which is 15.4 mm. The size and distribution of subgrade earth pressure change significantly during farmland irrigation. When the single-layer geocell reinforces the base, the subgrade stress is smaller than that of the other four, and the average earth pressure is 8 kPa. The membrane-pulling effect of reinforcement material significantly disperses the upper load of subgrade backfill soil, and the subgrade settlement control with different base treatment schemes meets the technical requirements.
IL‐8 Is Upregulated in the Tissue‐Derived EVs of Odontogenic Keratocysts
Authors: Liu Jian-Feng , Zhang Chen-Xi , Li Rui-Fang , Man Qi-Wen
Published: July 2022

Background. Interleukin 8 (IL‐8) is a chemotactic cytokine released by various cells including leukocytes, endothelial cells, and epithelial cells. IL‐8 has multiple functions in inflammation, tumour invasion, or angiogenesis. Human odontogenic cystic lesions are chronic and frequently inflamed. Tissue‐derived extracellular vesicles (Ti‐EVs) are widely present in various tissues and could more accurately reflect the characteristics of the primary tissue. However, the involvement of IL‐8 in Ti‐EVs of human odontogenic lesions is still unclear. This study aimed to explore the expression of IL‐8 in Ti‐EVs of human odontogenic lesions and the potential roles of Ti‐EVs that carried IL‐8. Methods. Fresh tissue samples of dentigerous cyst (DC, n = 5) and odontogenic keratocyst (OKC, n = 5) were collected for Ti‐EVs isolation. Ti‐EVs were characterised by transmission electron microscopy and nano‐flow cytometry analysis. The cytokine profile of Ti‐EVs was explored by cytokine antibody array. The IL‐8 expression was examined by immunochemical staining in tissue of odontogenic lesions (DC, n =12; OKC, n =28). Antioxidants (N‐acetyl‐L‐cysteine and diphenyleneiodonium) were employed to treat HaCaT cells, and the expression of IL‐8 was detected by enzyme‐linked immunosorbent assay. The gene expression of MMP9 was explored by quantitative real‐time polymerase chain reaction in co‐culture system of fibroblasts of OKC with Ti‐EVs. Results. Compared with DC, the expression of IL‐8 in Ti‐EVs and fixed tissue specimens of OKC was markedly upregulated. The antioxidants decreased the expression level of IL‐8 protein in the supernatant of HaCaT cells. The Ti‐EVs treatment (10 μg/ml) of fibroblasts significantly induced the MMP9 mRNA expressions in OKC fibroblasts. Conclusions. IL‐8 was upregulated in Ti‐EVs of OKC and might be involved in the tissue destruction of OKC.
Analysis on the Evolution of Ecological Transformation of Consumption Patterns to Help Realize the Evolution of Realize Low-Carbon City Construction Taking into Account Similarity Knowledge Recognition and Matching Algorithms
Authors: Li Xudong , Tao Lan , Zhou Xiaoqian
Published: July 2022

For the purpose of addressing or eliminating the influence of low-carbon city construction effectively, it is crucial to carry out qualitative analysis on the evolutionary process in the construction of the low-carbon city based on the similarity knowledge identification matching algorithm. The ecological transformation of consumption patterns is implemented to facilitate the distribution of resources in the evolution analysis of the low-carbon city construction. The regularity and innovation during the process of building low-carbon cities is effectively summarized. On the premises of fully grasping the principles of low-carbon city development and related policy protection, a suitable low-carbon city development model is found. In accordance with the features of separate transmission, the model is recovered by using the characteristics in the total deviation observed, and the constrained nonoptimizable case is replaced with the computation case of constrained separate line segment with the relaxation factor. Finally, the results of the practical case analysis suggest that the image processing method supported by the ecological transformation of consumption patterns applied in this paper uses the relatively advanced computer network technology and 3D visualization model construction based on the establishment of a low-carbon city construction model according to the effective analysis of geological surveys and data, which can provide theoretical support for the subsequent construction of low-carbon cities.
3D Image Based on Visual Sensor in Public Space Landscape Model
Authors: Liu Tengjiao
Published: July 2022

With the rapid development of the times, the computing of the internet of things and the industry go hand in hand, the application of visual sensors is becoming more and more extensive, and the image fusion technology and target recognition technology have been further improved. It can be said that it is a hot topic at home and abroad high-end technology. With the continuous improvement of people’s living standards, the specific requirements for the quality of life are gradually increasing. The landscape construction of public space has become a topic of discussion. People are becoming more and more stringent about the landscape environment around them. Landscape designers also feel distressed by this and pursue this higher level, which can not only improve the living environment, but also make people being able to live and work in peace, and contentment is an honor for the landscape architect. Therefore, this study builds an excellent public space landscape model based on the 3D image processing of the visual sensor, establishes the coverage relationship table through the genetic algorithm and the greedy algorithm, and then uses the infrared image segmentation method of the local entropy combined with the region growth method to segment the 3D image of the vision sensor. Then, we use the multi-image fusion method based on the dimensional closeness to merge and finally analyze the public space landscape model with extremely high integrity. Moreover, this study also discusses the analysis results of temperature and time on the integrity of the landscape model. Between 35.5°C and 36.7°C, from 12 o’clock to 14 o’clock, the integrity of the public space landscape model is as high as 97.2%.
[Retracted] Review on the Effect of Exercise Training on Immune Function
Authors: Du Feijiao , Wu Cuicui
Published: July 2022

Exercise training is not only a necessary means to improve the level of exercise, but also an important means to improve the body’s immunity. Different time, intensity, items, and forms of exercise training have different effects on the body’s immune function. As a double‐edged sword to improve the body’s immune function, exercise training is a different reaction mechanism of different immune cells after exercise training. This paper combined with foreign scholars’ studies on the immune function of the body of literature from different exercise intensity, different time, different sports, different movement forms, and different external environment such as angle of view for athletes body’s immune cells and humoral immunity summarized the various indexes such as combing, in order to help academia, medicine, and sports. It provides enlightenment to the contemporary public on how to participate in sports training more healthily.