bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparison of Bacterial and Fungal Community Structure and Potential Function Analysis of Yak Feces before and after Weaning
Authors: Li Yuanyuan , Li Xin , Liu Yanfeng , Nie Cunxi , Chen Cheng , Niu Junli , Zhang Wenju
Published: August 2022

Weaning is one of the most stressful periods in yak growth. However, the impact of weaning on microbial diversity, structure, and potential function of yak feces is not clear. In this study, 12 Xinjiang yaks aged 3, 4, 5, and 6 months old were selected to collect fresh feces before and after weaning. Through 16S rRNA and ITS high‐throughput sequencing, the dynamic distribution and potential function of yak fecal, bacterial, and fungal communities in each month were revealed. The study found that the richness of fungi had a significant impact on weaning. At the phylum level, Firmicutes, Bacteroidetes, Ascomycota, and Basidiomycota, and at the genus level, 5-7N15, Oscillospira, Roseburia, Dorea, Preussia, Neoascochyta, Naganishia, and Sporormiella were enriched in yak feces of different months old. The abundance and proportion of bacteria Firmicutes, Bacteroidetes, 5-7N15, and fungi Mucoromyceta changed significantly before and after weaning. With the increase of months, Verrucomicrobia and Akkermansia have shown a downward trend. Through the prediction and analysis of fecal microbial function, it was found that at the level of primary pathways, weaning has a significant impact on cellular processes, environmental information processing, genetic information processing, metabolism, and organismal systems. At the level of secondary metabolic pathways, weaning has a significant impact on cell motility, signal transduction, folding, sorting and degradation, translation, amino acid metabolism, glycan biosynthesis and metabolism, metabolism of terpenoids and polyketides, and xenobiotics biodegradation and metabolism. In addition, by analyzing the differences in functional pathways and microbial composition between sample groups of different months, it was found that the differences in functional pathways were related to the abundance differences of some microorganisms. In general, the changes in the composition and structure of yak fecal microflora may reflect the adaptability of the intestinal microbiota.
Acupuncture for the Treatment of Chronic Rhinosinusitis: A PRISMA-Compliant Systematic Review and Meta-Analysis
Authors: Lee Boram , Kwon Chan-Young , Park Man Young
Published: August 2022

Background. Chronic rhinosinusitis (CRS) is a highly prevalent disease associated with poor quality of life. In this paper, we appraised the role of acupuncture in the treatment of CRS. Methods. Electronic databases were searched for randomized controlled clinical trials (RCTs) that examined the role of acupuncture in CRS. The primary outcome measures included posttreatment CRS severity, as measured by the Visual Analogue Scale (VAS) and Total Effective Rate (TER). The risk of bias and quality of evidence were evaluated according to the Cochrane Collaboration’s risk-of-bias tool and GRADE tool, respectively. Results. Evidence from the RCTs (n = 10) suggested that acupuncture as a monotherapy or adjunctive therapy to conventional treatment was associated with significant improvements in VAS, TER, and quality of life when compared with conventional treatments for CRS. However, there was a similar incidence of adverse events. The risk of bias was unclear and the quality of evidence for each finding was generally moderate to low. Conclusions. Acupuncture as a stand-alone or adjunctive treatment for CRS was associated with clinical symptom improvement and better quality of life, without any risk for serious adverse events. However, the high clinical heterogeneity of the included RCTs and overall moderate-to-low quality of evidence necessitates rigorous, well-designed trials to confirm these findings. Trial Registrations. This trial is registered with PROSPERO (no. CRD42021292135).
Intelligent Detection Method of Gearbox Based on Adaptive Hierarchical Clustering and Subset
Authors: Yuan Huimiao , Tang Yongwei , Hao Huijuan , Zhao Yuanyuan , Zhang Yu , Chen Yu
Published: August 2022

Deep learning uses mechanical time-frequency signals to train deep neural networks, which realizes automatic feature extraction and intelligent diagnosis of fault features and gets rid of the dependence on a large number of signal processing technology and experience. Aiming at the problem of misclassification of similar samples, a fault diagnosis algorithm based on adaptive hierarchical clustering and subset (AHC-SFD) is proposed to extract features and applied to gearbox fault diagnosis. Firstly, the adaptive hierarchical clustering algorithm is used to analyze the characteristics of different data, and then the data set is clustered into multiple feature groups; finally, according to the feature group, the SubCNN model is established for multiscale feature extraction, so as to carry out fault diagnosis. The test results show that the fault recognition rate achieved by the proposed method is more than 99.7% on the gearbox dataset, and the method has better generalization ability.
Machine Learning and Novel Biomarkers Associated with Immune Infiltration for the Diagnosis of Esophageal Squamous Cell Carcinoma
Authors: Zhang Jipeng , Zhang Nian , Yang Xin , Xin Xiangbin , Jia Cheng-hui , Li Sen , Lu Qiang , Jiang Tao , Wang Tao
Published: August 2022

Esophageal squamous cell carcinoma (ESCC) accounts for the main esophageal cancer type, which is related to advanced stage and poor survivals. Therefore, novel diagnostic biomarkers are critically needed. In the current research, we aimed to screen novel diagnostic biomarkers based on machine learning. The expression profiles were obtained from GEO datasets (GSE20347, GSE38129, and GSE75241) and TCGA datasets. Differentially expressed genes (DEGs) were screened between 47 ESCC and 47 nontumor samples. The LASSO regression model and SVM-RFE analysis were carried out for the identification of potential markers. ROC analysis was carried out to assess discriminatory abilities. The expressions and diagnostic values of the candidates in ESCC were demonstrated in the GSE75241 datasets and TCGA datasets. We also explore the correlations between the critical genes and cancer immune infiltrates using CIBERSORT. In this study, we identified 27 DEGs in ESCC: 5 genes were significantly elevated, and 22 genes were significantly decreased. Based on the results of the SVM-RFE and LASSO regression model, we identified five potential diagnostic biomarkers for ESCC, including GPX3, COL11A1, EREG, MMP1, and MMP12. However, the diagnostic values of only GPX3, MMP1, and MMP12 were confirmed in GSE75241 datasets. Moreover, in TCGA datasets, we further confirmed that GPX3 expression was distinctly decreased in ESCC specimens, while the expression of MMP1 and MMP12 was noticeably increased in ESCC specimens. Immune cell infiltration analysis revealed that the expression of GPX3, MMP1, and MMP12 was associated with several immune, such as T cells CD8, macrophages M2, macrophages M0, and dendritic cells activated. Overall, our findings suggested GPX3, MMP1, and MMP12 as novel diagnostic marker and correlated with immune infiltrates in ESCC patients.
Systematic Evaluation of the Efficacy of Acupuncture Associated with Physical and Mental Intervention when Treating Idiopathic Tinnitus and the Improvement of Tinnitus Symptoms
Authors: Li Yan , Sang Di , Wu Zeting , Cao Xuemei
Published: August 2022

Objective. To systematically evaluate the efficacy of acupuncture associated with physical and mental intervention when treating idiopathic tinnitus and the improvement of tinnitus symptoms, so as to supply evidence-based medicine for its popularization and adoption. Methods. PubMed, EMBASE, ScienceDirect, Cochrane Library, China knowledge Network Database (CNKI), China VIP Database, Wanfang Database, and China Biomedical Literature Database (CBM) online database were searched for the controlled trial of acupuncture associated with physical and mental intervention when treating idiopathic tinnitus. The retrieval time limit is from January 2010 to March 2022. Separately, two researchers extracted the data, and according to the Cochrane Handbook 5.3, the bias risk of each piece of literature was assessed. The collected data were measured using RevMan5.3 statistical software. Results. Finally, 5 CT articles were included in this study, with a total sample size of 282. Meta-analysis showed that the effective rate of the study group was significantly higher than that of the control group (

P
<
0.05

). The scores of tinnitus disorder scale (THI) after treatment were analyzed by Meta. The THI scores of the study group after treatment were significantly lower than those before treatment. Meta-analysis of the severity of tinnitus after treatment showed that the severity of tinnitus in the observation group after treatment was significantly lower than that before treatment. There is a certain publication deviation in the literature, which may be related to the heterogeneity of the research and the small number of literatures. Conclusion. On the basis of acupuncture treatment, associated with physical and mental intervention is helpful to the recovery of patients with idiopathic tinnitus, can effectively improve their clinical symptoms, and is suitable for clinical application. A popularization of this concept in clinical practice is worth considering, but further research and follow-up with a higher methodological quality and longer intervention time are needed to confirm its efficacy.
Analysis of Uniaxial Compression Mechanical Properties of Rubber Powder Recycled Coarse Aggregate Concrete Based on Strain Energy Theory
Authors: Wang Lei , Wang Hailong
Published: August 2022

In order to develop and make full use of waste construction concrete and waste tyre rubber powder, the experiment entirely used recycled coarse aggregate to replace natural crushed stone aggregate and investigated the effect of different mesh sizes of rubber powder (20 mesh, 60 mesh, and 100 mesh) on the uniaxial compressive mechanical properties, strain energy density, and pore structure of recycled coarse aggregate concrete at three curing ages (14 d, 28 d, and 90 d). Based on the strain energy theory, fractal theory, and grey correlation theory, the effects of the fractal dimension of the pore size of the rubber powder recycled concrete on the correlation of the strain energy parameters were investigated at different curing ages. The research results show that as the age period increases, the ability of the rubber powder recycled coarse aggregate concrete to absorb strain energy increases. Before the peak stress, the rubber powder recycled coarse aggregate concrete mainly carries out the storage of elastic strain energy. The incorporation of rubber powder can refine the pore structure of the rubber powder recycled coarse aggregate concrete so that the large pore size pores evolve towards the medium (50–200 μm) or small pores (<50 μm). The fractal dimension analysis revealed that the incorporation of 20 mesh and 60 mesh rubber powder enhances the inhomogeneity of the small pore (<50 μm) and the medium pore (40 μm–140 μm) in the recycled concrete. The grey correlation analysis revealed that the pore size factor with the greatest influence on the elastic energy density was the large pore size (>200 μm).
The Association between Immune Subgroups and Gene Modules for the Clinical, Cellular, and Molecular Characteristic of Hepatocellular Carcinoma
Authors: Chen Wenbiao , Zhu Peng , Xu Huixuan , Hou Xianliang , Guo Changchun
Published: August 2022

The heterogeneity of hepatocellular carcinoma (HCC) is related to immune cell infiltration and genetic aberrations in the tumor microenvironment. This study aimed to identify the novel molecular typing of HCC according to the genetic and immune characteristics, to obtain accurate clinical management of this disease. We performed consensus clustering to divide 424 patients into different immune subgroups and assessed the reproducibility and efficiency in two independent cohorts with 921 patients. The associations between molecular typing and molecular, cellular, and clinical characteristics were investigated by a multidimensional bioinformatics approach. Furthermore, we conducted graph structure learning-based dimensionality reduction to depict the immune landscape to reveal the interrelation between the immune and gene systems in molecular typing. We revealed and validated that HCC patients could be segregated into 5 immune subgroups (IS1-5) and 7 gene modules with significantly different molecular, cellular, and clinical characteristics. IS5 had the worst prognosis and lowest enrichment of immune characteristics and was considered the immune cold type. IS4 had the longest overall survival, high immune activity, and antitumorigenesis, which were defined as the immune hot and antitumorigenesis types. In addition, immune landscape analysis further revealed significant intraclass heterogeneity within each IS, and each IS represented distinct clinical, cellular, and molecular characteristics. Our study provided 5 immune subgroups with distinct clinical, cellular, and molecular characteristics of HCC and may have clinical implications for precise therapeutic strategies and facilitate the investigation of immune mechanisms in HCC.
Large (Ti, V) Carbonitride in Nonquenched and Tempered Steel 38MnVS6
Authors: Xie You , Meng Xiaoling , Deng Xiangyang , Li Shichao
Published: August 2022

Large (Ti, V) carbonitrides with size even up to tens of microns in autoparts steel 38MnVS6 are studied in this work. A great number of micron-sized (Ti, V) carbonitrides are found in continuous casting billet, and the atomic ratios of V/Ti are mainly distributed in range 0.130–0.200 with an average value of 0.171. The large (Ti, V) carbonitrides have irregular morphologies, and some even have an obviously extending shape along the dendrite boundary. 3D morphologies of the large (Ti, V) carbonitride after being etched by AA solution present obvious long and flake shapes. The large (Ti, V) carbonitride has high thermal stability even at 1200°C, even though the atomic ratio of V/Ti has a decreasing tendency. There are still many large (Ti, V) carbonitrides in the rolled bar and partially broken in some which are clearly visible. According to the Thermo-Calc calculation result, the large (Ti, V) carbonitride precipitates in liquid steel during solidification. The chemical compositional characteristic is the result of subsequent mutual diffusion of elements Ti, V, C, and N. Simply reducing the content of Ti, even 13 ppm cannot eliminate the large (Ti, V) carbonitride for the nitrogen-containing, nonquenched, and tempered steel, but the quantity and size of large carbonitride are significantly reduced.
Evaluation Model of Football Players’ Training and Teaching Actions Based on Artificial Intelligence
Authors: Feng Yun , Wang Yongan
Published: August 2022

Football is a sport that needs to combine the physical stamina and physical characteristics of athletes. It needs to pay attention to the differences in different individuals and then conduct targeted training. In this regard, this article introduces artificial intelligence technology into the teaching actions of football player training and analyzes the teaching elements according to the characteristics of the football player’s body. Through the analysis of fog computing under artificial intelligence, this article aimed to study the related effects of combining intelligent technology on the basis of athletes’ original training. This article proposes the establishment of a system model and quantitative analysis of different frames of football players’ movements. According to the combination of two-phase analysis, it can be concluded that after the introduction of artificial intelligence technology, the ability of football players in various indexes has increased by 20%.
Index Construction and Application of School-Enterprise Collaborative Education Platform Based on AHP Fuzzy Method in Double Creation Education Practice
Authors: He Zhenzhen , Sun Xiuhong
Published: August 2022

At present, China’s education reform is developing rapidly, and many schools begin to study and implement school-enterprise cooperative education. There are also some conceptual deviations. In addition, the government’s weak implementation of the guarantee policy for the implementation of combination of school and enterprise education, coupled with the lack of relevant laws and regulations, rarely leads to the success and enthusiasm of combination of school and enterprise education. With the development of collaborative training companies, the participation rate needs to be improved, and the influence of school-enterprise colearning is not significant enough. Therefore, we should do more theoretical research on combination of school and enterprise education, so as to further improve the present situation of combination of school and enterprise education in China and promote the in-depth development of combination of school and enterprise education. At the same time, we should constantly improve relevant practices and systems, improve relevant laws and regulations, learn from the successful experience of cooperation between schools and enterprises training at home and abroad, and design a unique path of cooperation between schools and enterprises in combination with China’s reality. First of all, this paper deeply analyzes the synergy degree of combination of school and enterprise education. By defining the concepts of the combination of industry and teaching and the combination of colleges and enterprises, synergy degree, and cooperative development level, this paper makes an in-depth interpretation of the education and teaching of schools and enterprises. From the perspective of synergetic theory and interactive mechanism, school-enterprise cooperation needs to be strengthened. Secondly, the model is created through the analytic hierarchy process, in which the hierarchical model uses the 10/10-18/2 scaling method to form the classification matrix. Finally, this paper analyzes on the factors affecting the combination of school and enterprise education and puts forward some perfect countermeasures from three angles of government, school, and enterprise.
Esculentoside A Alleviates Intestinal Dysmotility in Ulcerative Colitis by Regulating H2S/CSE and NO/nNOS Systems
Authors: Liu Ying , Wei Wenhua , Liang Shiwei , Fang Haicheng , Cao Jie
Published: August 2022

Background. Ulcerative colitis (UC) is a type of inflammatory bowel disease (IBD) that commonly affects the health of many individuals. Esculentoside A (EsA), a saponin extracted from the roots of Phytolacca esculenta, has antioxidative and anti-inflammatory effects against various diseases. Nonetheless, its role in UC is undetermined. Hence, in this study, we examined the therapeutic effects of EsA in UC. Methods. Primary intestinal neuronal cells (in vitro) were treated with lipopolysaccharide (LPS) to induce inflammatory injury. An in vivo UC rat model was created by the administration of dextran sulfate sodium (DSS) to rats, which were subsequently treated with different doses of EsA. The effects of EsA on intestinal motility, histological score, inflammatory response, hydrogen sulfide (H2S)/cystathionine γ-lyase (CSE) system, NO/neuronal nitric oxide synthase (nNOS) system, and LPS-induced primary intestinal neuronal cell viability loss, proliferation inhibition, and apoptosis were detected. Results. In vitro, EsA treatment increased the number of DSS-inhibited bowel movements and body weight, improved the histological score of colitis, and inhibited the inflammatory response by reducing IL-6 and TNF-α levels in rats. More importantly, EsA reduced the NO and H2S levels in serum and CSE, CBS, and nNOS expressions in the colon tissue. In vivo, EsA treatment eased the viability loss, proliferation inhibition, and apoptosis of LPS-stimulated primary intestinal neuronal cells, as well as inhibited the expressions of IL-6, TNF-α, CSE, CBS, and nNOS in cells. Conclusion. EsA improved intestinal motility and suppressed inflammatory response in DSS-induced UC, which may be mediated by H2S/CSE and NO/nNOS systems.
Enhanced Memetic Algorithm-Based Extreme Learning Machine Model for Smart Grid Stability Prediction
Authors: Mishra Manohar , Nayak Janmenjoy , Naik Bignaraj , Patnaik Bhaskar
Published: August 2022

The smart grid is considered a conventional application domain of cyber-physical system (CPS) tools in the electrical utility industry. The physical system dynamics of SG with the assistance of CPS are generally controlled by connected sensors and controllers via a communication link. These CPSs, which rely heavily on an expansive communication network and intelligent computing algorithms, are susceptible to cyber-physical attacks and are also sensitive to various technical, economical, and social factors compromising their stability. Assessment and prediction of the stability of CPSs are very vital in this context. In this work, a novel optimized (memetic algorithm-based) extreme learning machine model for smart grid-CPS stability prediction has been proposed. Here, the teaching-learning-based optimization and simulated annealing techniques are used to design the memetic algorithm. The experimental result regarding the proposed model is then compared with other contemporary machine learning and deep learning models.
Utilization of Skilled Birth Attendance among Mothers Who Gave Birth in the Last 12 Months in Kembata Tembaro Zone
Authors: Mathewos Oridanigo Eyassu , Kassa Belete
Published: August 2022

Background. Skilled delivery is considered the single most important strategy in preventing maternal and neonatal morbidity and mortality. It ensures safe birth, reduces actual and potential complications, and increases the survival of most mothers and newborns. Objective. To identify determinants of the utilization of skilled birth attendance among women who gave birth in the last 12 months in the Kembata Tembaro zone, Southern Ethiopia, 2020. Methods. A community-based cross-sectional study was employed from 1 April 2020 to 30 April 2020 among women who gave birth in the last 12 months in the Kembata Tembaro zone. Six hundred twenty-four mothers were recruited for the study as eligible participants. Multistage stratified sampling was used to select three districts and one town administrative unit of the study area. The data were collected and verified for their completeness, followed by editing and coding. Multivariate analysis was performed using the backward LR method to identify factors independently associated with the dependent variable. Statistical significance was declared at a

p

value of less than 0.05, and the strength of statistical association was measured by adjusted odds ratio and 95% confidence interval. Result. Of 624 study subjects sampled, 607 provided information with a response rate of 97.3%. In this study, 309 (50.9%) women had their last birth at health facilities attended by skilled birth attendants. Place of residence (AOR (95% CI) = 0.33 (0.22,0.58)); age at interview (AOR (95% CI = 3.41 (1.57,5.45)); maternal education (AOR (95% CI) = 1.50 (1.34, 4.19)); history of still birth (AOR (95% CI) = 3.85 (2.14,6.91)); maternal occupation (AOR (95% CI) = 3.35 (1.79,6.27)); husband occupation (AOR (95% CI) = 2.69 (1.70,7.09)); ANC visit (AOR (95% CI) = 4.62 (3.12,7.32)); knowledge of obstetric complications (AOR (95% CI) = 3.10 (1.37,5.21)); and final decision-making about place of delivery (AOR (95% CI) = 3.64 (1.70,7.99)) were significantly associated with the use of skilled birth attendance. Conclusion. In this study, nearly half of the mothers used skilled birth attendance. Place of residence, age at interview, maternal education, history of still birth, maternal occupation, husband occupation, antenatal visit, knowledge about obstetric complications, and final decision-maker about place of delivery were determinants of the use of skilled attendance delivery.
Nr2f2 Overexpression Aggravates Ferroptosis and Mitochondrial Dysfunction by Regulating the PGC-1α Signaling in Diabetes-Induced Heart Failure Mice
Authors: Miao Weilun , Chen Mengli , Chen Minglong , Cui Chang , Zhu Yue , Luo Xinping , Wu Bangwei
Published: August 2022

Diabetes is well recognized to increase the risk of heart failure, which is associated with higher mortality and morbidity. It is important for the development of novel therapeutic methods targeting heart failure in diabetic patients. Ferroptosis, an iron-dependent regulated cell death, has been implicated in the progression of diabetes-induced heart failure (DIHF). This study was designed to investigate the contribution of Nr2f2 to the activation of ferroptosis and mitochondrial dysfunction in DIHF. We established a diabetic model by a high-fat feeding diet combined with an intraperitoneal injection of streptozotocin. After 16 weeks, Nr2f2 expression was increased in heart tissue of DIHF mice. In vivo, DIHF mice overexpressing Nr2f2 (AAV9-cTNT-Nr2f2) exhibited severe heart failure and enhanced cardiac ferroptosis compared with DIHF control mice (AAV9-cTNT-ctrl), accompanied by mitochondrial dysfunction and aggravated oxidative stress reaction. In vitro, Nr2f2 knockdown ameliorated ferroptosis and mitochondrial dysfunction by negatively regulating PGC-1α, a crucial metabolic regulator. PGC-1α knockdown counteracted the protective effect of Nr2f2 knockdown. These data suggest that Nr2f2 promotes heart failure and ferroptosis in DIHF by modulating the PGC-1α signaling. Our study provides a new idea for the treatment of diabetes-induced heart failure.
Hospital Rurality and Gene Expression Profiling for Early-Stage Breast Cancer among Iowa Residents (2010–2018)
Authors: Riley Danielle , Charlton Mary , Chrischilles Elizabeth A. , Lizarraga Ingrid M. , Phadke Sneha , Smith Brian J. , Skibbe Adam , Lynch Charles F.
Published: August 2022

Objective. Given the challenges rural cancer patients face in accessing cancer care as well as the slower diffusion and adoption of new medical technologies among rural providers, the aim of our study was to examine trends in gene expression profiling (GEP) testing and evaluate the association between hospital rurality and receipt of GEP testing. Methods. Data from the Iowa Cancer Registry (ICR) were used to identify women with newly diagnosed, histologically confirmed breast cancer from 2010 through 2018 who met eligibility criteria for GEP testing. Patients were allocated to the hospitals where their most definitive surgical treatment was received, and Rural-Urban Commuting Area codes were used to categorize hospitals into urban (N = 43), large rural (N = 16), and small rural (N = 48). Adjusted odds ratios (aORs) and 95% confidence intervals (CIs) were estimated using multivariable logistic regression to evaluate the association between hospital rurality and GEP test use, adjusting for demographic and clinical characteristics. The association between test result and treatment received was assessed among patients who received Oncotype DX (ODX) testing. Results. Of 6,726 patients eligible for GEP test use, 46% (N = 3,069) underwent testing with 95% receiving ODX. While overall GEP testing rates increased over time from 42% between 2010 and 2012 to 51% between 2016 and 2018 (

P

trend

<
0.0001

), use continued to be the lowest among patients treated at hospitals in small rural areas. The odds of GEP testing remained significantly lower among patients treated at hospitals located in small rural areas (aOR 0.55; 95% CI 0.43–0.71), after adjusting for demographic and clinical characteristics. ODX recurrence scores were highly correlated with chemotherapy use across all strata of hospital rurality. Conclusions. GEP testing continues to be underutilized, especially among those treated at small rural hospitals. Targeted interventions aimed at increasing rates of GEP testing to ensure the appropriate use of adjuvant chemotherapy may improve health outcomes and lower treatment-related costs.
Application of Clustering Algorithm in Corporate Strategy and Risk
Authors: Wen Qiong
Published: August 2022

With the increasing rise of market mechanism and corporate strategic management theory, many companies, especially listed companies, take diversification as their basic strategy. As the main source of power to promote the rapid development of China’s economy, listed companies have also changed the way of China’s economic development. It increases the speed of economic development, improves the level of economic technology, and accelerates the process of economic internationalization. Any economic behavior of an enterprise involves risks. As the development plan to mobilize the overall interests of the enterprise, the strategy will definitely involve the long-term development direction of the enterprise. Enterprise strategic deployments to strategic managements are affected by risk control elements. Strategic risk, as an unavoidable practical problem for enterprises, must be managed. Managing strategic risk is the key to effectively evaluate the management and control system. In order to solve this problem, this paper introduces a clustering algorithm, classifies the strategic risk of diversification, and analyzes its causes. For an in-depth analysis of the risks that diversification will face, this paper selects the case of the enterprise’s diversification development to carry out the research. It conducts in-depth analysis and research on its basic situation, diversification strategy, dilemma, and behavior. The experimental results show that the financial leverage coefficients of the company in the four quarters are 24.64, 3.93, 104.71, and 6.59 respectively. From the numerical value, it can be concluded that the enterprise is in a high-risk state and the strategic risk status of the company can be accurately judged.
The Biomarker Like the Correlation between Vasculogenic Mimicry, Vascular Endothelial Cadherin, Sex-DeterminingRegion on Y-Box Transcription Factor 17, and Cyclin D1 in Oesophageal Squamous Cell Carcinoma
Authors: Qin Yanzi , Zhao Wenjun , Cai Zhaogeng , Wang Qi , Gao Jin , Ci Hongfei , Feng Zhenzhong , Ma Li
Published: August 2022

Background. This study aimed to explore the relationships between the sex-determining region on Y (SRY) box transcription factor 17 (SOX17), Cyclin D1, vascular endothelial cadherin (VE-cadherin), and vasculogenic mimicry (VM) in the occurrence and development of esophageal squamous cell carcinoma (ESCC). Methods. The expressions of SOX17, Cyclin D1, and VE-cadherin, as well as VM, in tissues, were determined using immunohistochemistry. SOX17, Cyclin D1, and VE-cadherin mRNA in ESCC and their corresponding adjacent normal tissues were quantified using quantitative reverse transcription polymerase chain reaction analysis. Cell invasion, migration, and proliferation were determined after the silencing of VE-cadherin. SOX17, Cyclin D1, and VE-cadherin protein were quantified using Western blotting. Results. The expression levels of SOX17, Cyclin D1, and VE-cadherin significantly correlated with the clinical characteristics of ESCC. After the VE-cadherin silencing, cell invasion, migration, and proliferation decreased, along with the Cyclin D1 levels, while the SOX17 levels increased. Conclusion. SOX17, Cyclin D1, and VE-cadherin are involved in the development of ESCC.
Artificial Intelligence-Based Recommendation and Application of Public Services in Smart Cities
Authors: Zhou Jin
Published: August 2022

With the promotion and application of information technology, smart cities based on artificial intelligence have become the best choice for the government to solve urban problems, connect urban citizens, and provide quality public services. From the initial information city and digital city to the current smart city, the construction of smart cities has undergone profound changes with five major characteristics: big data, intelligence, innovation, interaction, and integration, and Internet giants have emerged in the field of public services in smart cities. Internet giants are emerging in the construction of public service platforms for smart cities, and traditional smart city construction enterprises are also expanding various forms of urban operation services through the form of “Internet+“. Nevertheless, there is still a gap between the quantity and quality of China’s smart cities compared with developed countries, and there is a need to build a number of pilot smart cities characterized by the linkage of artificial intelligence technology and public services, easy to promote, and sustainable development. The smart city construction model with public services as the core has research value and has the possibility of becoming the mainstream development in the future. Therefore, exploring the organic combination of AI technology and urban public services is the key to answer whether AI technology can promote the improvement of urban public services.
Synergistic Lethality Effects of Apatinib and Homoharringtonine in Acute Myeloid Leukemia
Authors: Shi Yuanfei , Xu Dandan , Xu Yi , Shen Huafei , Zhang Yan , Ye Xiujin , Jin Jie , Cui Dawei , Xie Wanzhuo
Published: August 2022

Purpose. The significance of vascular endothelial growth factor receptor (VEGFR)-2 in numerous solid tumors and acute myeloid leukemia (AML) has been demonstrated, but Apatinib remains largely unexplored. In this study, whether Apatinib combined with homoharringtonine (HHT) kills AML cell lines and its possible mechanisms have been explored. Methods. AML cell lines were treated with Apatinib and HHT in different concentrations with control, Apatinib alone, HHT alone, and Apatinib combined with HHT. The changes of IC50 were measured by CCK8 assay, and apoptosis rate, cell cycle, and the mitochondrial membrane potential in each group were measured by flow cytometry. Finally, the possible cytotoxicity mechanism was analyzed by Western blotting. Results. Our results noted that Apatinib combined with HHT remarkably inhibited cell proliferation, reduced the capacity of colony-forming, and induced apoptosis and cell cycle arrest in AML cells. Mechanistically, Apatinib and HHT play a role as a suppressor in the expression of VEGFR-2 and the downstream signaling cascades, such as the PI3K, MAPK, and STAT3 pathways. Conclusion. Our preclinical data demonstrate that Apatinib combined with HHT exerts a better antileukemia effect than Apatinib alone by inhibiting the VEGFR-2 signaling pathway, suggesting the potential role of Apatinib and HHT in the treatment of AML. This study provides clinicians with innovative combination therapies and new therapeutic targets for the treatment of AML.
Edge Node Aware Adaptive Data Processing Method for Ubiquitous NB-IoT
Authors: Sun Fanglei , Diao Zhifeng
Published: August 2022

Nowadays, we have entered the golden age of economic development, and the Internet of Things (IoT) has also ushered in the opportunity of development, and the rapid development of IoT is also beneficial to drive the economy forward continuously. Therefore, the research on IoT is very meaningful and meets the contemporary development needs and greatly facilitates people’s daily life through the interconnection of all things. In today’s era of massive data, all kinds of data are complicated and messy, and if the large amount of data obtained is not properly classified and processed, the major problem will be that a pile of disordered and messy data is generated, and it is impossible to find the corresponding useful, engineering value, and regular data among them, and then, such data can only be discarded. Such a simple and brutal way of data processing is not only a waste of data resources but also may inadvertently throw away important, confidential, and private data information. If such data is carelessly discarded, the consequences will be incalculable, because such data information is likely to be used, processed, and disseminated by unscrupulous elements, which will eventually result in the following consequences: for individuals, it is equivalent to making their privacy public, which will seriously affect all aspects of life; for enterprises, if confidential data information is disseminated, then it will bring unpredictable losses to the enterprise. The adaptive data processing method for edge node sensing in ubiquitous NB-IoT can make the data generated from NB-IoT modules in ubiquitous IoT have practical engineering application value after processing, so the data source of this paper is the IoT data generated from NB-IoT communication modules in ubiquitous network (called NB-IoT dataset in this paper). The experimental results show that the accuracy of the adaptive data classification achieved by these two algorithms reaches about 75%, which provides some help to improve the efficiency of data utilization.
The Finite Element Numerical Study of Transonic Flow of Moist Air with Nonequilibrium Condensation
Authors: Tian Weijun , Mei Liquan
Published: August 2022

The finite element numerical simulation of the transonic flow with condensation is studied in this paper. The transformed weak form is numerically discretized by using the classical Galerkin finite element spatial discretization scheme and the backward Euler difference time discretization scheme. Because the coupled Euler equations are convection equations, the results obtained by the classical Galerkin method often have nonphysical numerical oscillations, so the stabilization method is introduced. Another important feature of compressible Euler equation is the existence of shock wave. Because the thickness of shock wave is small and difficult to capture, the shock wave can be better captured by adding artificial viscosity term. Here, the streamline upwind/Petrov–Galerkin (SUPG) finite element method with good stability and the isotropic diffusion method with shock capture ability are used to solve the problem of transonic flow with condensation. In the simulation of steady problems, in order to improve the calculation accuracy of the existing area of the shock wave, the adaptive mesh refinement technology is added, which refines the mesh in the region of the shock wave to improve the resolution of the shock wave. Numerical experiments verify the feasibility and stabilization of the numerical method. Finally, the simulation of transonic flow around NACA-0012 and parallel-jet nozzle A1 has obtained the better numerical results.
An Efficient Deep Learning Mechanism for the Recognition of Olive Trees in Jouf Region
Authors: Alshammari Hamoud H. , Shahin Osama R.
Published: August 2022

Olive trees grow all over the world in reasonably moderate and dry climates, making them fortunate and medicinal. Pesticides are required to improve crop quality and productivity. Olive trees have had important cultural and economic significance since the early pre-Roman era. In 2019, Al-Jouf region in a Kingdom of Saudi Arabia’s north achieved global prominence by breaking a Guinness World Record for having more number of olive trees in a world. Unmanned aerial systems (UAS) were increasingly being used in aerial sensing activities. However, sensing data must be processed further before it can be used. This processing necessitates a huge amount of computational power as well as the time until transmission. Accurately measuring the biovolume of trees is an initial step in monitoring their effectiveness in olive output and health. To overcome these issues, we initially formed a large scale of olive database for deep learning technology and applications. The collection comprises 250 RGB photos captured throughout Al-Jouf, KSA. This paper employs among the greatest efficient deep learning occurrence segmentation techniques (Mask Regional-CNN) with photos from unmanned aerial vehicles (UAVs) to calculate the biovolume of single olive trees. Then, using satellite imagery, we present an actual deep learning method (SwinTU-net) for identifying and counting of olive trees. SwinTU-net is a U-net-like network that includes encoding, decoding, and skipping links. SwinTU-net’s essential unit for learning locally and globally semantic features is the Swin Transformer blocks. Then, we tested the method on photos with several wavelength channels (red, greenish, blues, and infrared region) and vegetation indexes (NDVI and GNDVI). The effectiveness of RGB images is evaluated at the two spatial rulings:

3
 
cm

/pixel and

13
 
cm

/pixel, whereas NDVI and GNDV images have only been evaluated at 13 cm/pixel. As a result of integrating all datasets of GNDVI and NDVI, all generated mask regional-CNN-based systems performed well in segmenting tree crowns (F1-measure from 95.0 to 98.0 percent). Based on ground truth readings in a group of trees, a calculated biovolume was 82 percent accurate. These findings support all usage of NDVI and GNDVI spectrum indices in UAV pictures to accurately estimate the biovolume of distributed trees including olive trees.
Downregulation of S100A9 Reverses Cisplatin-Resistance and Inhibits Proliferation and Migration in Hypopharyngeal Carcinoma
Authors: Zeng Shiyu , Tan Guolin , Wang Tiansheng , Wang Xianyao , Zhou Zheng , Xiao Jian , Li Tieqi , Zhang Gehou , Li Wei
Published: August 2022

Purpose. Patients with hypopharyngeal carcinoma (HPC) often progress to an advanced clinical stage at diagnosis. Cisplatin has been widely used in first-line chemotherapy for advanced HPC. However, acquired chemotherapeutic resistance leads to recurrence, metastasis, and a poor survival rate. Therefore, identifying new drug targets to improve treatment effects is still in need. Methods. To screen the differential expression genes (DEGs) and proteins (DEPs), we conducted transcriptomic and proteomic analysis on cisplatin-sensitive cell lines (FaDu) and cisplatin-resistant cell lines (FaDu/DDP) of hypopharyngeal carcinoma. DEGs and DEPs, possibly the most associated with cisplatin-resistance, were verified by real-time polymerase chain reaction (RT-PCR) and western blot (WB), respectively, and the biological function of the screened S100A9 was further tested by CCK8, wound healing, and transwell assays. Results. We identified S100A9 as a target for resensitizing the response to cisplatin in an acquired resistance model. S100A9 overexpression was significantly related to cisplatin resistance. Functional studies in vitro models demonstrated that downregulation of S100A9 overcame cisplatin-resistance and inhibited proliferation and migration. Later, we verified that downregulation of S100A9 suppressed the interleukin-6 (IL6) expression and epithelial-mesenchymal transition (EMT) pathway. Conclusion. In all, S100A9 plays a crucial role in cisplatin-resistance, proliferation, and migration of HPC. Targeting S100A9 may become a novel strategy for the treatment of HPC.
Length of Stay Prediction Model of Indoor Patients Based on Light Gradient Boosting Machine
Authors: Zeng Xiangrui
Published: August 2022

The influx of hospital patients has become common in recent years. Hospital management departments need to redeploy healthcare resources to meet the massive medical needs of patients. In this process, the hospital length of stay (LOS) of different patients is a crucial reference to the management department. Therefore, building a model to predict LOS is of great significance. Five machine learning (ML) algorithms named Lasso regression (LR), ridge regression (RR), random forest regression (RFR), light gradient boosting machine (LightGBM), and extreme gradient boosting regression (XGBR) and six feature encoding methods named label encoding, count encoding, one-hot encoding, target encoding, leave-one-out encoding, and the proposed encoding method are used to construct the regression prediction model. The Scikit-Learn toolbox on the Python platform builds the prediction model. The input is the dataset named Hospital Inpatient Discharges (SPARCS De-Identified) 2017 with 2343569 instances provided by the New York State Department of Health verify the model after removing 2.2% of the missing data, and the model ultimately uses mean squared error (MSE) and coefficient of determination (R2) as the performance measurement. The results show that the model with the LightGBM algorithm and the proposed encoding method has the best R2 (96.0%) and MSE score (2.231).
Two for the Road: Measuring Regional Disparity and Agglomeration in Human Development Level and Transportation Infrastructure
Authors: Wang Zhiheng , Xing Tao , Wang Daikun , Fan Hongkui , Wang Dongchuan , Wu Yanwang , Guo Qiaozhen , Xiu Lina
Published: August 2022

As the core element of social-economic development in the Qinghai-Tibet Plateau, transportation dramatically shapes the scale, type, and intensity of human activities. First, this study utilizes night light data and kilometer-grid population data to construct night light development index (NLDI) and to evaluate the human development level at the county scale. Then, based on the complex transportation infrastructure data, the weight assignment method is adopted to create transportation infrastructure influence degree (TIID), which is used to evaluate the location conditions of the counties. Finally, bivariate spatial autocorrelation is utilized to analyze the effect of regional conditions on the county-level human development variation. The results show that (1) NLDI is verified to assess differences in the level of human development among counties in Qinghai-Tibet Plateau and to overcome the difficulties of systematically and integrally obtaining socio-economic statistical data. The pattern of human development level in Qinghai-Tibet Plateau presents a “core-periphery” spatial structure with the transportation network as the axis. (2) On the whole, with the improvement of location conditions influenced by transportation infrastructure, the spatial aggregation of human development level is constantly improving, and the spatial disparity continues to decrease. (3) Locally, four spatial interaction patterns of high/low clustering are recognized and analyzed. It reflects the complexity and spatial heterogeneity between transport infrastructure construction and human development level in the Qinghai-Tibet Plateau.
Injury Prevention Effect of MRI Imaging Technology in Physical Education and Sports Training
Authors: Liu Jianxin
Published: August 2022

In order to solve the problem of observing and analyzing the clinical value of MRI diagnosis in patients with knee sports injury and guiding clinical targeted treatment, the author proposed a sports injury prevention method in sports training teaching based on MRI image observation. This method retrospectively analyzed the imaging data of 101 patients with knee joint MRI examination due to osteoarthritis, sports injury and synovitis in joint surgery, and arthroscopic exclusion of true meniscus tear, MR multisequence and multiplane scans were performed to observe the anatomical features of TGL and MFL images and the occurrence rate of the lateral meniscus “false tear sign,” and the

χ

2

test was used to compare the occurrence rate of “pseudo-tear sign” between genders and sides. Experimental results show that the incidence of TGL on MRI was about 67.3% (68/101), and the incidence of “pseudo-tear sign” in the anterior horn of the lateral meniscus caused by TGL was 2.9% (2/68). The overall appearance rate of MFL on MRI was 91.1% (92/101), the appearance rate of plate anterior ligament (HL) was 13.9% (14/101), and the occurrence rate of “pseudo-tear sign” in the posterior horn of the lateral meniscus caused by HL was 7.1% (1/14). The occurrence rate of the posterior ligament (WL) was 77.2% (78/101), and the incidence of “pseudo-tear sign” in the posterior horn was 20.5% (16/78). According to the shape and course of TGL and MFL on MRI, and the direction and position of the lateral meniscus pseudotear, combined with MRI sagittal plane and coronal plane observation, it can effectively identify the true and false attributes of lateral meniscus anterior and posterior horn tears, thereby reducing unnecessary surgical treatment.