bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of Rehabilitation Occupational Therapy Techniques Based on Instrumental Music Chinese Tonal Language Spectrogram Analysis
Authors: Liao Ying
Published: October 2022

This paper provides an in-depth analysis of timbre-speech spectrograms in instrumental music, designs a model analysis of rehabilitation occupational therapy techniques based on the analysis of timbre-speech spectrograms in instrumental music, and tests the models for comparison. Starting from the mechanism of human articulation, this paper models the process of human expression as a time-varying linear system consisting of excitation, vocal tract, and radiation models. The system’s overall architecture is designed according to the characteristics of Chinese speech and everyday speech rehabilitation theory (HSL theory). The dual judgment of temporal threshold and short-time average energy realized the phonetic length training. Tone and clear tone training were achieved by linear predictive coding technique (LPC) and autocorrelation function. Using the DTW technique, isolated word speech recognition was achieved by extracting Mel-scale Frequency Cepstral Coefficients (MFCC) parameters of speech signals. The system designs corresponding training scenes for each training module according to the extracted speech parameters, combines the multimedia speech spectrogram motion situation with the speech parameters, and finally presents the training content as a speech spectrogram, and evaluates the training results through human-machine interaction to stimulate the interest of rehabilitation therapy and realize the speech rehabilitation training of patients. After analyzing the pre- and post-test data, it was found that the

p

-values of all three groups were <0.05, which was judged to be significantly different. Also, all subjects changed their behavioral data during the treatment. Therefore, it was concluded that the music therapy technique could improve the patients’ active gaze communication ability, verbal command ability, and active question-answering ability after summarizing the data, i.e., the hypothesis of this experiment is valid. Therefore, it is believed that the technique of timbre-speech spectrogram analysis in instrumental music can achieve the effect of rehabilitation therapy to a certain extent.
On the Relationship between Speech Intelligibility and Fluency Indicators among English-Speaking Individuals with Parkinson’s Diseases
Authors: Liu Chin-Ting , Chu Shiao-Wei , Chen Yuan-Shan
Published: October 2022

The purpose of the study is to investigate how much of variance in Parkinson’s Disease (PD) individuals’ speech intelligibility could be predicted by seven speech fluency indicators (i.e., repetition, omission, distortion, correction, unfilled pauses, filled pauses, and speaking rate). Speech data were retrieved from a database containing a reading task produced by a group of 16 English-speaking individuals with PD (Jaeger, Trivedi & Stadtchnitzer, 2019). The results from a multiple regression indicated that an addition of 54% of variance in the speech intelligibility scores among individuals with PD could be accounted for after the speakers’ PD severity level measured based on Hoehn and Yahr’s (1967) disease stage was included as a covariate. In addition, omission and correction were the two fluency indicators that contributed to the general intelligibility score in a statistically significant way. Specifically, for every one-unit gain in the number of correction and omission, speech intelligibility scores would decline by 0.687 and 0.131 point (out of a 7-point scale), respectively. The current study hence supported Magee, Copland, and Vogel’s (2019) view that the language production abilities and quantified dysarthria measures among individuals with PD should be explored together. Additionally, the clinical implications based on the current findings were discussed.
Biofungicides for Improvement of Potato (Solanum tuberosum L) Production
Authors: Ehiobu John , Idamokoro Emrobowansan , Afolayan Anthony
Published: October 2022

Potato (Solanum tuberosum L) cultivation originated from Peru in Latin America. The cultivation has spread fast across the globe due to its ability to cope in the warm tropical and temperate climate. It is spotted by the United Nations as the only tuberous crop that can compete with the cereals in productivity. Fungal disease infestation has been identified as a major challenge confronting the farmers during the cultivation and marketing processes. Farmers’ reliance on Chemical fungicides has lost its credibility to the adoption of the use of biofungicides due to its toxic, high cost, and environmental hazard effects. The trend of the adoption of biofungicides by potato farmers is gaining ground at a fast rate. Various national governments are devising means of collaborating with the United Nations stakeholders through encouraging research funding and by organizing conferences that will enhance potato production. This could be achieved by minimizing losses through farmer’s complete adoption of biofungicides. This review, therefore, examines the various botanicals with antimicrobial properties as potential biofungicide against fungi diseases of potato.
Endogenous Vasoactive Peptides and Vascular Aging-Related Diseases
Authors: Chen Yao , Qi Yongfen , Lu Weiwei
Published: October 2022

Vascular aging is a specific type of organic aging that plays a central role in the morbidity and mortality of cardiovascular and cerebrovascular diseases among the elderly. It is essential to develop novel interventions to prevent/delay age-related vascular pathologies by targeting fundamental cellular and molecular aging processes. Endogenous vasoactive peptides are compounds formed by a group of amino acids connected by peptide chains that exert regulatory roles in intercellular interactions involved in a variety of biological and pathological processes. Emerging evidence suggests that a variety of vasoactive peptides play important roles in the occurrence and development of vascular aging and related diseases such as atherosclerosis, hypertension, vascular calcification, abdominal aortic aneurysms, and stroke. This review will summarize the cumulative roles and mechanisms of several important endogenous vasoactive peptides in vascular aging and vascular aging-related diseases. In addition, we also aim to explore the promising diagnostic function as biomarkers and the potential therapeutic application of endogenous vasoactive peptides in vascular aging-related diseases.
Breast Ultrasound Image Segmentation Algorithm Using Adaptive Region Growing and Variation Level Sets
Authors: Wang Yanwei , Ye Junbo , Wang Tianxiang , Liu Jingyu , Dong Hao , Qiao Xin
Published: October 2022

To address the features of strong noise, blurred boundaries, and poor imaging quality in breast ultrasound images, we propose a method for segmenting breast ultrasound images using adaptive region growing and variation level sets. First, this method builds a template layer from the difference between the marked image and the original image. Second, the Otsu algorithm is used to measure the target and background using the maximum class variance method to set the threshold. Finally, through the level set of the pixel neighborhood, the boundary points of the adaptive region growth are specified by the level set of the pixel neighborhood, and it is therefore possible to accurately determine the contour perimeter and area of the lesion region. The results demonstrate that the value of Jaccard and Dice for benign tumors is greater than 0.99. Therefore, the segmentation effect of breast images can be achieved by utilizing a breast ultrasound image segmentation approach that uses adaptive region growth and variation level sets.
[Retracted] Research on the Impact of Livelihood Capital by the Honghu Fishermen’s Willingness to Quit Fishing
Authors: Zhou Yu , Zhaohua Li  , Zhao Liya
Published: October 2022

Aiming at the livelihood of fishermen under the fishing prohibition policy, quantitative research methods were used to explore the relationship between the willingness to quit fishing and livelihood capital. With reference to 609 survey data from 20 fishing grounds in 2 counties and cities of Hubei Province, this paper explores the necessity of convincing fishermen in the Yangtze River to quit fishing and evaluates the impact of livelihood mode on Honghu fishermen’s willingness to quit fishing by means of structural equation model based on the sustainable livelihood framework developed by the UK Department for International Development. The results showed the following conclusions: (1) The proportion of fishermen who are willing to participate in quitting fishing is 66.7%, indicating that fishery production is still the main source of livelihood for many fishermen. The overall willingness of fishermen to quit fishing is strong, and fishermen have realized the importance of protecting fishery resources. (2) There is a strong correlation between the indicators of livelihood capital and the willingness of fishermen to quit fishing. Among them, the human capital has the most significant impact on fishermen’s willingness to quit fishing for some compensation from public power. The research conclusion is helpful for the government to improve the fishing prohibition policy in a targeted manner and mobilize the enthusiasm of fishermen to protect fishery resources.
Psychological Motivation of Athletes’ Physical Training Based on Deep Learning Model
Authors: Yang Yining
Published: October 2022

In the field of sports training, two methods of physical and psychological monitoring are usually used to monitor the training process. Physiological index monitoring can objectively reflect the physical function of athletes, and there are many monitoring constraints. Psychological indicators can subjectively reflect the athlete’s own state, and the monitoring is simple and easy. This paper mainly used the subjective perception of effort (RPE) and the profile of mood state (POMS) scales to track and monitor 20 nonprofessional athletes in a university track and field team. Based on the change of the same training volume, the change law and relationship between RPE and POMS, and the change law and relationship between RPE, POMS, heart rate, and blood pressure were analyzed. Finally, it was concluded that the athletes are feeling more and more about the amount of training, and the minimum valueP<0.01showed a very significant difference, reflecting that the increase of training volume has a significant impact on the t-test value. The training volume has an impact on both the positive and negative dimensions of POMS, but the negative dimension reflects the training volume more clearly. There was a linear relationship between RPE and POMS subscales. RPE was not significantly correlated with positive emotions but positively correlated with negative emotions and TMD. The change trend was the same and the RPE grade increases; the blood pressure and systolic blood pressure also increased accordingly, and vice versa. The POMS negative dimension and TMD were the same as changes in blood pressure increase or decrease, and TMD was not related to heart rate. Scientific training has a large impact on the training of nonprofessional athletes, and whether the training volume is reasonable or not directly affects the qualitative change of athletes’ physical functions. Therefore, it is particularly important to monitor the physiological and psychological indicators of nonprofessional athletes. The improvement of sports performance is the goal, and the improvement of physical function is the guarantee.
Correlation and Prediction of Students’ Level of Reading Comprehension through Their Perception of the Application of Transition Words
Authors: Anwar Md. Nurul , Ahad Md. Nurul , Anwar Choiril , Asaad Hani Qasem Mohammed , Hasan Md. Kamrul , Omanee Boonyarit
Published: October 2022

The role of reading comprehension and its correlation and prediction to other skills in terms of enhancing the proficiency level of students in English language has been widely recognized by researchers. However, research conducted on reading comprehension in roughly the last fifteen to twenty years shows no concrete evidence of identifying the knowledge of the transition words with the understanding of reading comprehension. This study was particularly designed to fill that gap and to measure students’ ability to differentiate among various categories of expressions in English language, such as descriptive, narrative, sequence, comparison and contrast, and cause and effect, and to identity the functions of their derivative transitions in the reading comprehension task. The current study adapted a quantitative method and collected data from 100 male and female EFL students at the tertiary level in a Bangladeshi university to conduct this study. To be specific, this research used transition words as the predictor variable/independent variable and reading comprehension as the dependent variable. The findings of the research suggested that there were positive and significant correlations between students’ knowledge of the transition words and their level of understanding the reading comprehension. In addition, the transitional word was found to be a strong predictor of reading comprehension. This study strongly suggests that students with a better understanding of transition words can perform equally better in their reading comprehension tasks. For tertiary level students, the knowledge of transitional words would be useful, and it would also have significance for lexical scholars and curriculum designers.
A Rare Case of BCL2-Positive Multiple Myeloma Complicated with Follicular Lymphoma
Authors: Tsutsumi Yutaka , Ito Shinich , Kobayashi Mirei , Teshima Takanori
Published: October 2022

A 68-year-old woman presented with follicular lymphoma complicated by IgG kappa-positive multiple myeloma. In this case, both follicular lymphoma and plasma cells were positive for BCL2 by immunostaining. T-cell association in the FL and MM was also analyzed in this case. Some CD3-positive T-cells were found around the plasma cells. These cells were mainly CD8-positive T-cells and not CD4-positive T-cells. These results suggest that CD4-positive T-cells were not associated with the proliferation of the plasma cells in this case. Although the FL that developed was initially positive for BCL2 protein, this does not indicate that plasma cells were derived from FL cells because of the eventual complication that occurred in this case. Furthermore, in this case, rituximab and bendamustine were effective for FL. They were not effective for MM, however, demonstrating that additional treatment options are necessary for the simultaneous treatment of BCL2-positive MM with FL.
The Impact of Different Oxygen Delivery Methods on Corneal Epithelial Repair after Injury
Authors: Li Shanshan , Tian Qingfen , Ding Gang , Sun Yuqin , Hao Zhongkai , Wang Xu , Zhang Chenming , Tao Yuan
Published: October 2022

The hyperbaric oxygen therapy is often used in the management of acid and base burns of the eyes. However, oxygen is rarely supplied locally through goggles or face mask in ophthalmology. Therefore, in this study, we aim to investigate how oxygen delivery affects eye recovery after injury. We used a rabbit model with corneal epithelial injury to examine the effects of local oxygen supply via goggles or face mask on the recovery of cornea. A total of 75 healthy New Zealand white rabbits were randomly divided into three groups, A, B, and C, with 25 rabbits in each group. Then, on each rabbit eye (150 eyes in total), a circle of corneal epithelium with 5 mm in diameter was scraped off from the center of the cornea with a corneal epithelial scraper. Group A was given oxygen goggles every day (the oxygen flow rate was 3 L/min, once a day, 2 hours each time); group B was given nasal inhalation of oxygen every day (the oxygen flow rate was 3 L/min, once a day, 2 hours each time); and group C did not receive any treatment and was healed naturally. We found that the group A, which received oxygen supply via goggles, showed the best eye recovery. Transmission electron microscopy showed that the cornea with local oxygen supply via goggles or face mask exhibited intact capillary structure and obvious desmosome/hemidesmosome connections between cells. Moreover, the protein and RNA levels of hypoxia-related genes were lower in group A and B, suggesting that the hypoxia factor is a sensitive and early regulator in the low oxygen environment.
Mining of Potential Biomarkers and Pathway in Valvular Atrial Fibrillation (VAF) via Systematic Screening of Gene Coexpression Network
Authors: Zou Fan , Chen Tiantian , Xiang Xiuying , Peng Chengjiang , Huang Shuai , Ma Shaohong
Published: October 2022

Purpose. We apply the bioinformatics method to excavate the potential genes and therapeutic targets associated with valvular atrial fibrillation (VAF). Methods. The downloaded gene expression files from the gene expression omnibus (GEO) included patients with primary severe mitral regurgitation complicated with sinus or atrial fibrillation rhythm. Subsequently, the differential gene expression in left and right atrium was analyzed by R software. Additionally, weighted correlation network analysis (WGCNA), principal component analysis (PCA), and linear model for microarray data (LIMMA) algorithm were used to determine hub genes. Then, Metascape database, DAVID database, and STRING database were used to annotate and visualize the gene ontology (GO) analysis, KEGG pathway enrichment analysis, and PPI network analysis of differentially expressed genes (DEGs). Finally, the TFs and miRNAs were predicted by using online tools, such as PASTAA and miRDB. Results. 20,484 differentially expressed genes related to atrial fibrillation were obtained through the analysis of left and right atrial tissue samples of GSE115574 gene chip, and 1,009 were with statistical significance, including 45 upregulated genes and 964 downregulated genes. And the hub genes implicated in AF of NPC2, ODC1, SNAP29, LAPTM5, ST8SIA5, and FCGR3B were screened. Finally, the main regulators of targeted candidate biomarkers and microRNAs, EIF5A2, HIF1A, ZIC2, ELF1, and STAT2, were found in this study. Conclusion. These hub genes, NPC2, ODC1, SNAP29, LAPTM5, ST8SIA5, and FCGR3B, are important for the development of VAF, and their enrichment pathways and TFs elucidate the involved molecular mechanisms and assist in the validation of drug targets.
Establishment and Validation of a Tumor Microenvironment Prognostic Model for Predicting Bladder Cancer Survival Status Based on Integrated Bioinformatics Analyses
Authors: Chen Qiu , Yin Guicao , He Xingjun , Jiang Tianlin , Zhou Haisen , Wu Yunjiang , Li Yifan
Published: October 2022

This study was designed to analyze the characteristics of bladder cancer-related genes and establish a prognostic model of bladder cancer. The model passed an independent external validation set test. Differentially expressed genes (DEGs) related to bladder cancer were obtained from the Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA), and Genotype-Tissue Expression (GTEx) databases. WGCNA was used to fit the GSE188715, TCGA, and GTEx RNA-Seq data. Fusing the module genes with the high significance in tumor development extracted from WGCNA and DEGs screened from multiple databases. 709 common prognostic-related genes were obtained. The 709 genes were enriched in the Gene Ontology database. Univariate Cox and LASSO regression analyses were used to screen out 21 prognostic-related genes and further multivariate Cox regression established a bladder cancer prognostic model consisting of 8 genes. After the eight-gene prognostic model was established, the Human Protein Atlas (HPA) database, GEPIA 2, and quantitative real-time PCR (qRT-PCR) verified the differential expression of these genes. Gene Set Enrichment Analysis and immune infiltration analysis found biologically enrichment pathways and cellular immune infiltration related to this bladder cancer prognostic model. Then, we selected bladder cancer patients in the TCGA database to evaluate the predictive ability of the model on the training set and validation set. The overall survival status of the two TCGA patient groups in the training and the test sets was obtained by Kaplan–Meier survival analysis. Three-year survival rates in the training and test sets were 37.163% and 25.009% for the low-risk groups and 70.000% and 62.235% for the high-risk groups, respectively. Receiver operating characteristic curve (ROC) analysis showed that the areas under the curve (AUCs) for the training and test sets were above 0.7. In an external independent validation database GSE13507, Kaplan–Meier survival analysis showed that the three-year survival rates of the high-risk and the low-risk groups in this database were 56.719% and 76.734%, respectively. The AUCs of the ROC drawn in the external validation set were both above 0.65. Here, we constructed a prognostic model of bladder cancer based on data from the GEO, TCGA, and GTEx databases. This model has potential prognostic and clinical auxiliary diagnostic value.
Enhance Software-Defined Network Security with IoT for Strengthen the Encryption of Information Access Control
Authors: Vimal Vrince , Muruganantham R. , Prabha R. , Arularasan A. N. , Nandal P. , Chanthirasekaran K. , Reddy Ranabothu Gopi
Published: October 2022

The Internet of Things (IoT) is legitimately growing quicker. The operators have already started setting up a diligent infrastructure for these gadgets. Various technologies need to be developed for this type of sensor, including enterprise safety initiatives. This paper covers the stability routing protocol, which assumes an assessment of credibility in gadgets and packet flow. To build reliable Software-Defined Network (SDN) routes, build on the trust between network element flows and Quality of Service (QoS) or energy conditions. The SDN architecture is used for the Cognitive Protocol Network (CPN) technical platform to increase the energy level. Stochastic Neural Networks (SNNs) are accredited with information extracted from perceptual packets and make decentralized decisions. The proposed network infrastructure is designed and integrated into the SerIoT techniques to strengthen IoT encryption for information access control. The versatility of the technology is to circumvent the unpredictable connectivity of the system and the node decreases in terms of potential cryptographic capacity, limited interval, a target node, and deterministic energy. Based on factual statistical data, appropriate marketing generates an end-to-end antitheft solution that meets a set of predetermined circuit restrictions. A study must collaborate by demonstrating numerous flaws due to the obvious instability of clusters, which is essential for the efficiency of the platform.
Identification of Concomitant Inhibitors against Glutamine Synthetase and Isocitrate Lyase in Mycobacterium tuberculosis from Natural Sources
Authors: Chanda Anesha , Kalita Sanjib , Mishra Awdhesh Kumar , Changkakoti Liza , Sarma Janayita Biswa , Biswas Kunal , Kakati Debashree , Mohanta Yugal Kishore , Tanti Bhaben , Mahanta Saurov , Saravanan Muthupandian
Published: October 2022

Tuberculosis (T.B.) is a disease that occurs due to infection by the bacterium, Mycobacterium tuberculosis (Mtb), which is responsible for millions of deaths every year. Due to the emergence of multidrug and extensive drug‐resistant Mtb strains, there is an urgent need to develop more powerful drugs for inclusion in the current tuberculosis treatment regime. In this study, 1778 molecules from four medicinal plants, Azadirachta indica, Camellia sinensis, Adhatoda vasica, and Ginkgo biloba, were selected and docked against two chosen drug targets, namely, Glutamine Synthetase (G.S.) and Isocitrate Lyase (I.C.L.). Molecular Docking was performed using the Glide module of the Schrӧdinger suite to identify the best‐performing ligands; the complexes formed by the best‐performing ligands were further investigated for their binding stability via Molecular Dynamics Simulation of 100 ns. The present study suggests that Azadiradione from Azadirachta indica possesses the potential to inhibit Glutamine Synthetase and Isocitrate Lyase of M. tuberculosis concomitantly. The excellent docking score of the ligand and the stability of receptor‐ligand complexes, coupled with the complete pharmacokinetic profile of Azadiradione, support the proposal of the small molecule, Azadiradione as a novel antitubercular agent. Further, wet lab analysis of Azadiradione may lead to the possible discovery of a novel antitubercular drug.
Hydroxychloroquine Therapy Led to the Diagnosis of Glucose-6-Phosphate Dehydrogenase (G6PD) Deficiency in an Elderly Patient with COVID-19 Involvement: A Case Report and Review of the Literature
Authors: Taghizadeh-Sarvestani Razieh , Reihani Hamid , Ghanei-Shahmirzadi Ali , Keshtkar Alireza , Yazdanpanahi Parsa
Published: October 2022

Glucose-6-phosphate dehydrogenase (G6PD) deficiency is the most common RBC abnormality, affecting 400 million people globally. Neonatal jaundice, hemolytic anemia, icteric skin, dark urine, and fever are usually the primary signs of this condition, which is generally diagnosed between the ages of infancy and 16 years old. Therefore, its first manifestation in old age is an unexpected phenomenon. Here, we present the case of a 70-year-old man with no past medical history of G6PD deficiency that was admitted to our hospital due to COVID-19 infection and developed acute hemolytic anemia while receiving hydroxychloroquine (HCQ) medication for COVID-19-related pneumonia.
A Meta-Analysis of How Nonalcoholic Fatty Liver Disease Affect Antiviral Treatment of Patients with e Antigen-Positive Chronic Hepatitis B
Authors: Chen Yandong , Liu Qiang , Han Jing , Gao Siyu , Xiao Qian , Huang Xiaoli , Lu Lu , Zhou xiaolin
Published: October 2022

Background. Nonalcoholic fatty liver disease (NAFLD) and chronic hepatitis B (CHB) are both the most common underlying diseases leading to cirrhosis and hepatocellular carcinoma, and NAFLD and HBV infection are the first and second leading causes of chronic liver disease in China. However, there are still a lot of controversies about whether the combined presence of CHB and NAFLD will affect the course or outcome of liver disease together with HBV, and how the two affect each other. Objective. To investigate the effect of nonalcoholic fatty liver disease (NAFLD) on antiviral therapy in patients with chronic hepatitis B (CHB). Methods. Computer searches of databases such as PubMed, CNKI, VIP.com, and Wanfang Data Knowledge Service Platform were used. The time frame was from the creation of the database to June 2022. The search subject terms were hepatitis B, CHB, or NAFLD. The observation group consisted of patients with e antigen-positive CHB with NAFLD, and the control group consisted of patients with e-antigen + CHB. Extracts including title, name, date of publication, number of samples, antiviral drugs, and outcome indicators were used for Meta-analysis. Funnel plots were drawn to analyze literature bias. Results. Seven papers including 1348 patients with HBeAg + CHB (observation group: n = 547, control group: n = 801) were finally included. Results. Meta-analysis showed that CHB patients with NAFLD had lower efficacy than CHB patients after 48 weeks of antiviral treatment with nucleotide analogs, as measured by three outcome indicators HBV DNA conversion rate, ALT-normalization, and HBeAg conversion rate. Conclusion. NAFLD reduces the effect of antiviral therapy in CHB patients, and the clinicopathological features of patients with NAFLD combined with chronic hepatitis B are different from those of patients with chronic hepatitis B alone, so early diagnosis by liver histological examination should be actively performed and reasonable antiviral therapy should be administered.
Predicting Conserved Water Molecules in Binding Sites of Proteins Using Machine Learning Methods and Combining Features
Authors: Xiao Wei , Ren Juhui , Hao Jutao , Wang Haoyu , Li Yuhao , Lin Liangzhao
Published: October 2022

Water molecules play an important role in many biological processes in terms of stabilizing protein structures, assisting protein folding, and improving binding affinity. It is well known that, due to the impacts of various environmental factors, it is difficult to identify the conserved water molecules (CWMs) from free water molecules (FWMs) directly as CWMs are normally deeply embedded in proteins and form strong hydrogen bonds with surrounding polar groups. To circumvent this difficulty, in this work, the abundance of spatial structure information and physicochemical properties of water molecules in proteins inspires us to adopt machine learning methods for identifying the CWMs. Therefore, in this study, a machine learning framework to identify the CWMs in the binding sites of the proteins was presented. First, by analyzing water molecules’ physicochemical properties and spatial structure information, six features (i.e., atom density, hydrophilicity, hydrophobicity, solvent-accessible surface area, temperature B-factors, and mobility) were extracted. Those features were further analyzed and combined to reach a higher CWM identification rate. As a result, an optimal feature combination was determined. Based on this optimal combination, seven different machine learning models (including support vector machine (SVM),

K

-nearest neighbor (KNN), decision tree (DT), logistic regression (LR), discriminant analysis (DA), naïve Bayes (NB), and ensemble learning (EL)) were evaluated for their abilities in identifying two categories of water molecules, i.e., CWMs and FWMs. It showed that the EL model was the desired prediction model due to its comprehensive advantages. Furthermore, the presented methodology was validated through a case study of crystal 3skh and extensively compared with Dowser++. The prediction performance showed that the optimal feature combination and the desired EL model in our method could achieve satisfactory prediction accuracy in identifying CWMs from FWMs in the proteins’ binding sites.
[Retracted] The Protection for Personal Information Based on IoT Network Management and Data Sharing in Big Data Era
Authors: Zhang Yu , Yin Hexiao , Dong Haoyun
Published: October 2022

A few decades ago, the protection of personal information was basically in the state of none, with more and more problems due to personal information, such as the use of information to achieve fraud and the use of false information to publish bad information, causing great property losses to people’s lives. People only began to have awareness of the protection of personal information. After this, the civil law protection of personal information in IoT management has been developed. In this paper, we present a comparative analysis of the application of data sharing and protection of personal information based on the Internet of Things (IoT) management, as well as the sharing mechanisms used in data information, the protection of information security, and the drawbacks, which explains the safety information analysis of personal information in the case of data sharing and the calculation method used by the IoT in data sharing. A comparative study found that on the basis of IoT management, the security and concealment of personal information have been improved by about 20%. In practical application, IoT also brings great convenience in information data sharing. It increases the efficiency of operation, reduces losses, and to a certain extent guarantees the security of people’s individual information.
Constraint on the Higgs-Dilaton Potential via Warm Inflation in Two-Time Physics
Authors: Phong Vo Quoc , Loc Ngo Phuc Duc
Published: October 2022

Within the

S
P

2
,
R

symmetry, the two-time model (2T model) has six dimensions with two dimensions of time and the dilaton field that can be identified as inflaton in a warm inflation scenario with potential of the form

~

ϕ

4

. From that consideration, we derive the range of parameters for the Higgs-Dilaton potential, the coupling constant between Higgs and Dilaton (

α

) is larger than 0.0053 and the mass of Dilaton is smaller than

1

0

−
7

 GeV. Therefore, the 2T model indirectly suggests that extra dimension can also be a source of inflation.
Macrophage-Derived Exosomes in TLR9-/- Mice Ameliorate Sepsis-Induced Mitochondrial Oxidative Stress and Apoptosis in Cardiomyocytes
Authors: Li Xiang , Luo Junyu , Li Yanmei , Jia Lu , Li Yuejin , Ye Shili , Liu Lanlan , Yu Yanxuan , Lu Yonggang , Luan Yunpeng
Published: October 2022

Objective. To explore the mechanisms of TLR9 from macrophages on mitochondrial apoptosis in cardiomyocytes at early stage of sepsis. Methods. The in vivo and in vitro sepsis mice were bone marrow transplantation (BMT) with wild type (WT) or (toll-like receptor 9) TLR9 knockout (-/- or KO) myeloid cells and then constructed by cecum ligation and puncture (CLP) as vivo experiment and cardiomyocytes cocultured with WT or TLR9-deficient macrophages treated with LPS as vitro experiment, respectively. Sepsis model were performed by CLP. The expression levels of exosome, PI3K/AKT, and ERK1/2, inflammatory factors, and apoptotic proteins were tested by western blot in vivo. Besides, associated apoptotic proteins and JC-1 fluorescence assay were tested in vitro. Results. The expressions of p-PI3K, p-AKT, exosome markers (CD9, CD63, and TSG101), p-ERK1/2, TNF-α, IFN-γ, IL-1β, and cleaved-caspase-3/-9 were significantly increased in septic mice vs. control mice, and these proteins were declined dramatically in TLR9-/- BMT mice vs. WT BMT mice in sepsis mice models. Meanwhile, the protein expression of cytochrome C, cleaved-caspase-3, and cleaved-caspase-9 increased significantly in primary mouse myocardial cells cocultured with TLR9-/- or WT macrophages stimulated with LPS, and these mitochondrial apoptotic proteins as well as the green 5,5',6,6'-tetrachloro-1,1',3,3'- tetraethylbenzimidazolcarbocyanine iodide (JC-1) fluorescence were dramatically lower in LPS-stimulated cardiomyocytes cocultured with TLR9-/- than with WT macrophages. Conclusion. TLR9-/- in macrophages suppressed the inflammatory reaction as well as the exosome secretion and resulted in the inhibition of apoptosis and oxidative stress in sepsis-induced cardiomyopathy.
Trend Prediction Model of Asian Stock Market Volatility Dynamic Relationship Based on Machine Learning
Authors: Lee Peiyuan , Huang Zhigang , Tang Yong
Published: October 2022

With the rapid development of the global economy and stock market, stock investment has become a common investment method. People’s research on stock forecasting has never stopped. Accurately predicting the dynamic fluctuation of stocks can bring rich investment returns to investors while avoiding investment risks. Machine learning is a relatively important research field in artificial intelligence today, which is mainly used to study how to use machines to simulate human activities. In recent years, with the continuous development of the economy, machine learning under artificial intelligence has developed comprehensively in different fields, and it has been widely used in the field of the financial economy. Machine learning under artificial intelligence is currently widely used in stock market volatility dynamics and related research. This paper applied machine learning to the prediction of the dynamic relationship of Asian stock market volatility and established a model for predicting the dynamic relationship of stock market volatility under machine learning. By using statistical theory, linear support vector machines, generalizable bounds, and other algorithms, it provides the theoretical basis and feasibility analysis for the model. Through investigation and research, this paper found that compared with ordinary forecasting model methods, the stock volatility dynamic trend forecasting model based on machine learning has a relatively complete forecasting effect, and the accuracy of the machine learning forecasting model was up to 52%. The lowest was 39%, the average prediction accuracy was 46.5%, and the accuracy was improved by 16.8%. This showed that the introduction of machine learning prediction models in the dynamic prediction model of Asian stock volatility is relatively successful.
Paeoniflorin Ameliorates Colonic Fibrosis in Rats with Postinfectious Irritable Bowel Syndrome by Inhibiting the Leptin/LepRb Pathway
Authors: Tian Ya-Qing , Zhang Sheng-Peng , Zhang Kun-Li , Cao Di , Zheng Yi-Jun , Liu Ping , Zhou Hui-Hui , Wu Ya-Ning , Xu Qi-Xiang , Liu Xiao-Ping , Tang Xu-Dong , Zheng Yong-Qiu , Wang Feng-Yun
Published: October 2022

Postinfectious irritable bowel syndrome (PI-IBS) is a highly prevalent gastrointestinal disorder associated with immune dysregulation and depression- and anxiety-like behaviors. Through traditional medicine, the active ingredient of Paeoniae Radix called paeoniflorin (PF) was previously found to prevent the symptoms of PI-IBS. However, there is limited information on the effects of PF on intestinal function and depression- and anxiety-like symptoms in PI-IBS animal models. Here, we aimed to determine the effects of PF treatment on the symptoms of PI-IBS in a rat model. The PI-IBS rat model was established via early postnatal sibling deprivation (EPSD), trinitrobenzenesulfonic acid (TNBS), and chronic unpredictable mild stress (CUMS) stimulation and then treated with different dosages of PF (10, 20, and 40 mg/kg) and leptin (1 and 10 mg/kg). The fecal water content and body weight were measured to evaluate the intestinal function, while the two-bottle test for sucrose intake, open field test (OFT), and elevated plus maze test (EMT) were performed to assess behavioral changes. The serum leptin levels were also measured using an enzyme-linked immunosorbent assay. Furthermore, the expressions of leptin and its receptor, LepRb, were detected in colonic mucosal tissues through an immunohistochemical assay. The activation of the PI3K/AKT signaling pathway and the expression of brain-derived neurotrophic factor (BDNF) were also detected via western blotting. After the experimental period, the PI-IBS rats presented decreased body weight and increased fecal water content, which coincided with elevated leptin levels and heightened depression- and anxiety-like behaviors (e.g., low sucrose intake, less frequency in the center areas during OFT, and fewer activities in the open arms during EMT). However, the PF treatment ameliorated these observed symptoms. Furthermore, PF not only inhibited leptin/LepRb expression but also reduced the PI3K/AKT phosphorylation and BDNF expression in PI-IBS rats. Notably, cotreatment with leptin (10 mg/kg) reduced the effects of PF (20 mg/kg) on colonic fibrosis, leptin/LepRb expression, and PI3K/AKT activation. Therefore, our findings suggest that leptin is targeted by PF via the leptin/LepRb pathway, consequently ameliorating the symptoms of PI-IBS. Our study also contributes novel insights for elucidating the pharmacological action of PF on gastrointestinal disorders and may be used for the clinical treatment of PI-IBS in the future.
Mesenchymal Stem Cells May Alleviate the Intervertebral Disc Degeneration by Reducing the Oxidative Stress in Nucleus Pulposus Cells
Authors: Zhao Yongzhao , Xiang Qian , Cheng Yunzhong , Lin Jialiang , Jiang Shuai , Li Weishi
Published: October 2022

Background. Stem cell therapy is a promising therapeutic modality for intervertebral disc degeneration (IDD). Oxidative stress is a vital contributor to the IDD; however, the definite role of oxidative stress in stem cell therapy for IDD remains obscure. The aim of this study was to determine the vital role of oxidative stress-related differentially expressed genes (OSRDEGs) in degenerative NPCs cocultured with mesenchymal stem cells (MSCs). Methods. A series of bioinformatic methods were used to calculate the oxidative stress score and autophagy score, identify the OSRDEGs, conduct the function enrichment analysis and protein-protein interaction (PPI) analysis, build the relevant competing endogenous RNA (ceRNA) regulatory networks, and explore the potential association between oxidative stress and autophagy in degenerative NPCs cocultured with MSCs. Results. There was a significantly different oxidative stress score between NPC/MSC samples and NPC samples (

p
<
0.05

). Forty-one OSRDEGs were selected for the function enrichment and PPI analyses. Ten hub OSRDEGs were obtained according to the PPI score, including JUN, CAT, PTGS2, TLR4, FOS, APOE, EDN1, TXNRD1, LRRK2, and KLF2. The ceRNA regulatory network, which contained 17 DElncRNAs, 240 miRNAs, and 10 hub OSRDEGs, was constructed. Moreover, a significant relationship between the oxidative stress score and autophagy score was observed (

p
<
0.05

), and 125 significantly related gene pairs were obtained (

r

>
0.90

,

p
<
0.05

). Conclusion. Stem cell therapy might repair the degenerative IVD via reducing the oxidative stress through the ceRNA regulatory work and restoration of autophagy in degenerative NPCs. This research could provide new insights into the mechanism research of stem cell therapy for IDD and potential therapeutic targets in the IDD treatment.
Sishen Pill Ameliorates Dextran Sulfate Sodium (DSS)-Induced Colitis with Spleen-Kidney Yang Deficiency Syndromes: Role of Gut Microbiota, Fecal Metabolites, Inflammatory Dendritic Cells, and TLR4/NF-κB Pathway
Authors: Ge Wei , Zhou Bu-Gao , Zhong You-Bao , Liu Su-Qing , Huang Jia-Qi , Yuan Wang-Yuan , Xie Chang-Ying , Liu Duan-Yong , Wang Hai-Yan , Zuo Zheng-Yun
Published: October 2022

Sishen pill (SSP) is an old Chinese medicine used to treat colitis with spleen-kidney-yang deficiency (SKYD) syndromes. However, its exact mechanism of action has not yet been fully elucidated. The aim of this study was to evaluate the effects and potential mechanisms of SSP on colitis with SKYD syndromes in mice. Colitis with SKYD syndromes was induced by rhubarb, hydrocortisone, and dextran sulfate sodium (DSS), and treatment was provided with SSP. Flow cytometry was performed to examine the inflammatory dendritic cell (infDC) regulations of SSP. The changes in the gut microbiota (GM) and fecal metabolites post-SSP treatment were investigated using the combination of 16S rRNA sequencing and untargeted metabolomics. Additionally, we also examined whether SSPs could regulate the infDCs by modifying TLR4/NF-κB signaling pathways. Compared with the DSS group, the disease activity index, colonic weight, index of colonic weight, and colonic injury scores, as well as the levels of tumor necrosis factor (TNF)-α, interleukin (IL)-1β, IL-6, and IL-12p70 decreased significantly in the DSS + SSP group, while free triiodothyronine (FT3), free tetraiodothyronine (FT4), testosterone (TESTO), body weight change, colonic length, and the levels of IL-10 increased. Also, SSP decreased the amounts of CD103+CD11c+iNOS+, CD103+CD11c+TNF-α+, CD11c+CD103+CD324+, CD103+CD11c+MHC-II+, and CD103+CD11c+CD115+. Interestingly, 16S rRNA sequencing and untargeted metabolomics showed that SSP treatment restored the dysbiosis of GM and improved the dysfunction in fecal metabolism in colitis mice with SKYD syndromes. Correlation analysis indicated that the modulatory effects of SSP on FT3, FT4, IL-10, colonic weight index, CD103+CD11c+TNF-α+, CD103+CD11c+MHC-II+, and 13 common differential metabolites were related to alterations in the abundance of Parvibacter, Aerococcus, norank_f_Lachnospiraceae, Lachnospiraceae_UCG-006, Akkermansia, and Rhodococcus in the GM. In addition, SSP markedly inhibited the activation of the TLR4, MyD88, TRAF6, TAB2, and NF-κBp65 proteins and activated IκB. These results indicate that SSP can effectively alleviate colitis mice with SKYD syndrome by regulating infDCs, GM, fecal metabolites, and TLR4/NF-κB signaling pathways.
Fuzzy Application in the Design of QR Code Data Binding Based on the GD Packaging Machine
Authors: Taicheng Wei , Hao Chen , Haoran Zhu
Published: October 2022

The tracking of raw materials, production, and circulation links is carried out using QR codes in cigarette products. Each link’s current data collection and correlation analysis are still in the research and development stage. When used in conjunction with the GD packing machine’s production process feature, the QR code reader serves as an acquisition element for the process of data acquisition and the associated design for the tobacco packets and boxes, and the software is used to associate the received data and correct process exceptions. The system satisfies the design requirements, according to the results of the field verification.
The Construction of Smart Chinese Medicine Cloud Health Platform Based on Deep Neural Networks
Authors: Miao Yaofeng , Zhou Yuan
Published: October 2022

In order to improve the efficiency of doctors’ diagnosis and treatment, the state has built a Chinese medicine cloud health platform. However, most medical institutions currently use internal networks, and the technical standards and specifications are not uniform. Some information is not compatible and patient information cannot be shared. Therefore, the construction of a smart traditional Chinese medicine (TCM) cloud health platform based on deep neural networks has become a current research hotspot. The research results show that the deep neural network technology has a theoretical basis and feasibility in the smart Chinese medicine cloud health platform. Combining with deep neural network technology, a cloud-based Chinese medicine cloud health system has been developed through big data analysis technology. Through the investigation and research method, this paper found that the smart Chinese medicine cloud health platform based on deep neural networks was more popular with citizens, which could improve the quality and efficiency of management. The average management quality of a smart TCM health cloud platform based on deep neural networks was 81.1, and the average management quality of a common TCM cloud health platform was 75. The efficiency of the smart Chinese medicine cloud health platform based on deep neural networks was relatively stable, with an average of 84%. The efficiency of the general TCM cloud health platform fluctuated significantly and was relatively unstable, with an average of 73.5%. The efficiency of the smart Chinese medicine cloud health platform was 10.5% higher than that of the ordinary Chinese medicine cloud health platform. This shows that the construction of the intelligent Chinese medicine cloud health platform under the deep neural network is relatively successful.