bluuebunny/crossref_metadata_2025 huggingface dataset:
Application of Intelligent Sensor Algorithm in Student Management Information Fusion
Authors: Li Yanan
Published: December 2021

In order to improve the effectiveness of college student management and promote the integration of college student management information, this paper applies intelligent sensor algorithms to student management. Moreover, this paper combines uncertainty theory with multisensor data fusion technology to establish a complete set of multisensor data processing tools for student information and provides a complete mathematical theoretical framework for the principles of student management information fusion. In addition, in view of the problem of comparing a large number of mixed data of information sources, it is necessary to transfer the information fragments obtained by each sensor to a common set so that the information fragments expressed in different sets can be integrated. Finally, this paper constructs an intelligent student management model and conducts research in combination with simulation experiments. Through simulation research, it can be known that the method proposed in this paper can effectively improve the effect of student management.
Local Asymptotic Normality Complexity Arising in a Parametric Statistical Lévy Model
Authors: Jedidi Wissem
Published: December 2021

We consider statistical experiments associated with a Lévy process observed along a deterministic scheme (iun,  1 ≤ i ≤ n). We assume that under a probability ℙθ, the r.v. Xt,  t > 0, has a probability density function >o, which is regular enough relative to a parameter θ ∈ (0, ∞). We prove that the sequence of the associated statistical models has the LAN property at each θ, and we investigate the case when X is the product of an unknown parameter θ by another Lévy process Y with known characteristics. We illustrate the last results by the case where Y is attracted by a stable process.
Multi-Party Verifiable Privacy-Preserving Federated k-Means Clustering in Outsourced Environment
Authors: Hou Ruiqi , Tang Fei , Liang Shikai , Ling Guowei
Published: December 2021

As a commonly used algorithm in data mining, clustering has been widely applied in many fields, such as machine learning, information retrieval, and pattern recognition. In reality, data to be analyzed are often distributed to multiple parties. Moreover, the rapidly increasing data volume puts heavy computing pressure on data owners. Thus, data owners tend to outsource their own data to cloud servers and obtain data analysis results for the federated data. However, the existing privacy-preserving outsourced

k

-means schemes cannot verify whether participants share consistent data. Considering the scenarios with multiple data owners and sensitive information security in an outsourced environment, we propose a verifiable privacy-preserving federated

k

-means clustering scheme. In this article, cloud servers and participants perform

k

-means clustering algorithm over encrypted data without exposing private data and intermediate results in each iteration. In particular, our scheme can verify the shares from participants when updating the cluster centers based on secret sharing, hash function and blockchain, so that our scheme can resist inconsistent share attacks by malicious participants. Finally, the security and experimental analysis are carried out to show that our scheme can protect private data and get high-accuracy clustering results.
Methanolic Extract of Myrsine africana Leaf Ameliorates Hyperglycemia and Dyslipidemia in Alloxan-Induced Diabetic Albino Mice
Authors: Amare Yosef Eshetie
Published: December 2021

Background. Diabetes mellitus is one of the leading public health problems globally, and its prevalence is increasing in Ethiopia. The current drugs for people with diabetes are costly, less effective, and less safe with a challenging administration method. Thus, globally, the need for alternative herbal antidiabetic medicines is increasing. In the previous studies, antioxidant activities have been seen in crude extracts of M. africana leaves, which is an auspicious sign of antidiabetic property. Accordingly, this study has evaluated the antidiabetic and antidyslipidemic activities of methanolic extract of M. africana leaves. Methods. Hypoglycemic and antihyperglycemic activities of the three doses (250 mg/kg, 500 mg/kg, and 1000 mg/kg) of crude methanolic extract of M. africana leaf were studied on normoglycemic, oral glucose-loaded, and alloxan-induced diabetic mice models. The effect of the extract on diabetic dyslipidemia, insulin and glycated hemoglobin levels, carbohydrate-metabolizing enzymes, and body weight was also studied in alloxan-induced diabetic mice. Glibenclamide (5 mg/kg) was used as a standard drug in all cases. Data analysis was carried out using mixed-design ANOVA. A

P

value of ≤0.05 was considered a statistically significant difference. Results. The methanolic extract of M. africana leaf did not show acute toxicity up to the dose of 5000 mg/kg and showed better glucose utilization in the oral glucose tolerance test. After 14 days of treatment, M. africana leaf extract decreased the blood glucose level, glycated hemoglobin, glucose-6-phosphatase, and fructose-1-6-bisphosphatase in diabetic mice. In contrast, it increased hexokinase and insulin levels in diabetic mice. Moreover, weight loss and dyslipidemia profiles have been corrected significantly in diabetic mice. Conclusion. M. africana leaves showed antihyperglycemic and antidyslipidemic effects in alloxan-induced diabetic mice. That suggests M. africana may be a potential treatment option for diabetes in the future. However, further molecular studies are required to analyze the mechanisms.
[Retracted] A Study of Athlete Pose Estimation Techniques in Sports Game Videos Combining Multiresidual Module Convolutional Neural Networks
Authors: Liu Rui
Published: December 2021

In this paper, we propose a multiresidual module convolutional neural network‐based method for athlete pose estimation in sports game videos. The network firstly designs an improved residual module based on the traditional residual module. Firstly, a large perceptual field residual module is designed to learn the correlation between the athlete components in the sports game video within a large perceptual field. A multiscale residual module is designed in the paper to better solve the inaccuracy of the pose estimation due to the problem of scale change of the athlete components in the sports game video. Secondly, these three residual modules are used as the building blocks of the convolutional neural network. When the resolution is high, the large perceptual field residual module and the multiscale residual module are used to capture information in a larger range as well as at each scale, and when the resolution is low, only the improved residual module is used. Finally, four multiresidual module convolutional neural networks are used to form the final multiresidual module stacked convolutional neural network. The neural network model proposed in this paper achieves high accuracy of 89.5% and 88.2% on the upper arm and lower arm, respectively, so the method in this paper reduces the influence of occlusion on the athlete’s posture estimation to a certain extent. Through the experiments, it can be seen that the proposed multiresidual module stacked convolutional neural network‐based method for athlete pose estimation in sports game videos further improves the accuracy of athlete pose estimation in sports game videos.
Relationship between Body Roundness Index and Risk of Type 2 Diabetes in Japanese Men and Women: A Reanalysis of a Cohort Study
Authors: Zhao Wei , Tong Jingjing , Li Jinghua , Cao Yongtong
Published: December 2021

Purpose. The purpose of this study was to investigate the association between body roundness index (BRI) and type 2 diabetes (T2DM) in each sex, explore the dose-response relationship between them, and evaluate the predictive value of BRI for T2DM. Materials and Methods. A retrospective cohort study was performed on 15,464 Japanese patients at the Murakami Memorial Hospital. Data on anthropometric indices and biochemical parameters were obtained. Multivariate Cox regression models were used to estimate the hazard ratios (HRs) of incident T2DM associated with BRI. Dose-response relationships were evaluated using a smoothing function analysis and the threshold effect. Receiver operating characteristic curves were used to evaluate and compare the predictive values of BRI, body mass index (BMI), and waist circumference (WC) for T2DM. Results. During a median 5.4-year follow-up period, 373 subjects were diagnosed with T2DM. After adjusting for age, alcohol intake, smoking status, fatty liver, systolic blood pressure, fasting plasma glucose, glycated hemoglobin, high-density lipoprotein cholesterol, triglycerides, and total cholesterol, the relationship between BRI and T2DM was linear in women (HR (95% CI) for BRI Z score = 1.48 (1.26,1.74)) and curvilinear in men (HR (95% CI) on the left and right of the inflection point = 0.70 (0.44, 1.10) and 1.46 (1.27, 1.67), respectively). Compared with BMI (area under the curve (AUC) = 0.684;

p
<
0.001

) and WC (AUC = 0.700;

p
=
0.007

), BRI was the strongest predictor of T2DM in men (AUC = 0.715). Similarly, the AUC of BRI was larger than that of BMI (AUC = 0.757;

p
=
0.966

) and WC (AUC = 0.733;

p
=
0.015

) in women. Conclusions. BRI was positively linearly associated with an elevated risk of incident T2DM in women. In men, the relationship between BRI and T2DM was J-shaped. BRI is an effective indicator of predicting T2DM. Its discriminatory power was higher than that of BMI and WC in both sexes.
Mobile Interface CMS Method for Vibration Characteristics Prediction of Mistuned Bladed Disk with Different Coupling Degrees
Authors: Zhang Liang , Wang Qidi , Li Xin
Published: December 2021

The prediction of vibration characteristics was studied in the mistuned bladed disk by the mobile interface prestressed component mode synthesis (CMS) superelement method. When the strongly, generally, and weakly coupling in the mistuned bladed disk, according to the results of the direct FEM method, the prediction accuracy of this method was verified and compared with the fixed-interface CMS method by using the relative error of dynamic frequency, vibration mode matching function, and dimensionless root mean square error of vibration amplitudes. It is pointed that for mistuned bladed disk in the strong coupling, the prediction accuracy of dynamic frequency and vibration amplitudes are higher by the mobile interface CMS method and the vibration modes are matched with the direct method. In weak coupling, the results of dynamic frequency and vibration modes predicted by the mobile interface CMS method and the fixed-interface CMS method are consistent with the direct method, but the vibration amplitudes’ prediction error of the mobile interface CMS method is lower than that of the fixed-interface CMS method. In general coupling, the mobile interface CMS method has higher dynamic frequency prediction accuracy at low order, and the two methods have comparable dynamic frequency prediction accuracy at high order. The vibration modes predicted by the two methods are matched with the direct FEM method, and the prediction accuracy of vibration amplitude by the mobile interface CMS method is better than that of the fixed-interface CMS method. The results indicate that the mobile interface CMS method could more accurately predict vibration characteristics of the mistuned bladed disk with different coupling degrees and could be an effective measurement for studying the vibration characteristics of the mistuned bladed disk system.
GPA Peptide Attenuates Sepsis‐Induced Acute Lung Injury in Mice via Inhibiting Oxidative Stress and Pyroptosis of Alveolar Macrophage
Authors: Liu Yukun , Zhang Yongsheng , Feng Quanrui , Liu Qinxin , Xie Jie , Li Hui , Yang Fan , Liu Xinghua , Gao Wei , Bai Xiangjun , Li Zhanfei , Wang Yuchang
Published: December 2021

Acute lung injury (ALI) has been known to be a devastating form of respiratory infection and an important contributor to mortality in intensive care, due to its lacking of effective treatment. Inflammation, oxidative stress, and pyroptosis are associated with multiple kinds of inflammatory diseases such as ALI. It is commonly accepted that Gly‐Pro‐Ala (GPA) peptide regulates oxidative stress and pyroptosis in different kinds of inflammatory diseases. Our study is aimed at exploring the regulatory function and protective effects of GPA peptides on ALI. In the current study, the cecal ligation and puncture (CLP) technique was used to evoke sepsis in mice, and GPA peptide was administered intraperitoneally with different concentrations (50, 100, and 150 mg/kg) after CLP. Histopathological changes and the ratio of wet‐to‐dry in lung were recorded and analyzed. We also investigated the level of oxidative stress, inflammation, and pyroptosis. Results showed that GPA peptide significantly ameliorated CLP‐stimulated lung tissue injury, impeded proinflammatory cytokine release, and reduced inflammatory cell infiltration. Additionally, GPA peptide suppressed oxidative stress and caspase‐1‐dependent pyroptosis in alveolar macrophages. Furthermore, our study showed that the GPA peptide prevents alveolar macrophage from undergoing pyroptosis by attenuating ROS. In conclusion, results demonstrated that GPA peptide has protective effects in CLP‐stimulated ALI by inhibiting oxidative stress as well as pyroptosis of alveolar macrophage.
Badminton Backcourt Stroke Route Planning Method Based on Deep Learning
Authors: Ma Yanping
Published: December 2021

In order to improve the planning ability of the badminton backcourt stroke line, this study designs a badminton backcourt stroke line planning method based on deep learning. Firstly, the trajectory adaptive learning method of motion primitives is used to design the hitting line nodes and path space, so as to construct the shortest distributed grid structure model of the hitting line. Then, the constraint parameters of hitting route planning are analyzed, and then the hitting position and player posture are controlled according to node positioning and shortest path optimization deployment. Finally, the adaptive optimization of the route planning process is realized by combining the deep learning method. The simulation results show that this method has good learning control ability and good convergence performance and improves the reliability of badminton backcourt hitting line planning.
Spatial Patterns of the Urban Agglomeration of the Yellow River Ji‐Shaped Bend Based on Space of Multiple Flows
Authors: Guo Mengyao , Wang Fang , Zhao Ruixi , Guo Xi
Published: December 2021

Previous studies on the space of flows have mainly focused on a single flow element and have given less consideration to the joint effect of complex correlations among multiple flows. To fill this gap, in the context of the coordinated development of the urban agglomeration of the Yellow River Ji‐shaped bend (UAYB), in this study, three flows, namely population flow, logistics flow, and information flow, are selected to research the spatial patterns of the UAYB. The results show the following: (1) The information flow among cities in the UAYB is the strongest, followed by logistics flow and population flow. (2) Hohhot, Ordos, Yinchuan, and Taiyuan are the core cities and have attracted more flows to converge there; different flows have formed different central features. (3) Regarding the correlation of the three flows, information flow has a strong correlation with the other two flows. (4) From the perspective of the joint effects of the three flows considered, the hierarchy of UAYB is dominated by Hohhot and Taiyuan and sub‐dominated by Yinchuan and Ordos; four prominent city groups have been formed with these four cities as the center. On the basis of our results, we put forward some recommendations on the integrated development of cities at various levels within the UAYB to provide a reference for its spatial optimization strategy.
Disbursal of Text Steganography in the Space of Double-Secure Algorithm
Authors: Khan Yahya , Algarni Ali , Fayomi Aisha , Almarashi Abdullah M.
Published: December 2021

Hackers reveal sensitive information from encrypted conversations as the globe has become one community. As a result, steganography and cryptography are used together to safeguard sensitive data more effectively than previous approaches and newly developed algorithms. A double-secure algorithm for text steganography (DSTS) is the safest approach compared to the paragraph hiding method (PHM) and capital alphabet shape encoding (CASE) method. In this context, the paragraph hiding method uses ASCII coding, which is not a standard method, and the CASE method has a security issue that if someone understands its applicability, it can be easily attacked. DSTS algorithm overcomes its limitations by using UTF-16 coding and enhances the security of CASE with a one-time pad (OTP). The one-time pad is a theoretically unbreakable cryptographic method. Still, it is not feasible for long messages, however, it is usable for short messages such as a password or intelligence agency’s more secure messages. DSTS degrades the average hiding capacity in a PHM from 2.06% to 1% due to UTF-16 coding. Using the UTF-8 method, the authors have improved MDSTS and the CMPHM by 6.49% and 7.76% hiding capacity, which outperforms in existing procedures; in the CMPHM, there is one reason for the improvement in hiding capacity is using the LZW compression method. CMHPM algorithm optimization standard deviation is less than that of the HPM, DSTS, and MDSTS, ultimately increasing speed.
Development and Validation of a Novel ELISA for the Specific Detection of Antibodies against Mycobacterium avium Subspecies paratuberculosis Based on a Chimeric Polyprotein
Authors: Moyano Roberto Damián , Romero Magali Andrea , Colombatti Olivieri María Alejandra , Alvarado Pinedo María Fiorella , Traveria Gabriel Eduardo , Romano María Isabel , Alonso María Natalia
Published: December 2021

Bovine paratuberculosis (PTB) is caused by Mycobacterium avium subsp. paratuberculosis (MAP). The optimization of detection tests specific for MAP is crucial to improve PTB control. In this work, we aimed to develop and validate a diagnostic tool based on an ELISA to specifically detect anti-MAP antibodies from bovine serum samples. For that purpose, we designed a recombinant polyprotein containing four specific antigens from MAP and optimized the ELISA. The validation consisted of the assessment of 10 sera from PTB-infected and healthy bovines with different OD values. The diagnostic performance of the polyprotein-ELISA was evaluated by testing 130 bovine serum samples (47 healthy, 48 MAP-infected, and 35 M. bovis-infected bovines). The ELISA using the polyprotein yielded an area under the ROC curve (AUC) of 0.9912 (95% CI, 0.9758–1.007;

P

 < 0.0001). Moreover, for this ELISA, the cut-off selected from the ROC curve based on the point with a sensitivity of 95.56% (95% CI, 0.8485–0.9946) and specificity of 97.92 (95% CI, 0.8893–0.9995) was 0.3328. Similar results were obtained with an ELISA using the commercial Paratuberculosis Protoplasmatic Antigen (PPA). However, the ELISA with the polyprotein antigen showed a better performance against sera from animals infected with Mycobacterium bovis compared to the ELISA with PPA: lower cross-reactivity (2.85% versus 25.71%). These results demonstrate a very low cross-reactivity of the polyprotein with antibodies present in serum samples from animals infected with M. bovis. The designed polyprotein and the validated ELISA could be very useful for the specific identification of MAP-infected animals in herds.
[Retracted] Automatic Detection of High‐Frequency Oscillations Based on an End‐to‐End Bi‐Branch Neural Network and Clinical Cross‐Validation
Authors: Liu Zimo , Wei Penghu , Wang Yiping , Yang Yanfeng , Dai Yang , Cao Gongpeng , Kang Guixia , Shan Yongzhi , Liu Da , Xie Yongzhao
Published: December 2021

Accurate identification of high‐frequency oscillation (HFO) is an important prerequisite for precise localization of epileptic foci and good prognosis of drug‐refractory epilepsy. Exploring a high‐performance automatic detection method for HFOs can effectively help clinicians reduce the error rate and reduce manpower. Due to the limited analysis perspective and simple model design, it is difficult to meet the requirements of clinical application by the existing methods. Therefore, an end‐to‐end bi‐branch fusion model is proposed to automatically detect HFOs. With the filtered band‐pass signal (signal branch) and time‐frequency image (TFpic branch) as the input of the model, two backbone networks for deep feature extraction are established, respectively. Specifically, a hybrid model based on ResNet1d and long short‐term memory (LSTM) is designed for signal branch, which can focus on both the features in time and space dimension, while a ResNet2d with a Convolutional Block Attention Module (CBAM) is constructed for TFpic branch, by which more attention is paid to useful information of TF images. Then the outputs of two branches are fused to realize end‐to‐end automatic identification of HFOs. Our method is verified on 5 patients with intractable epilepsy. In intravalidation, the proposed method obtained high sensitivity of 94.62%, specificity of 92.7%, and F1‐score of 93.33%, and in cross‐validation, our method achieved high sensitivity of 92.00%, specificity of 88.26%, and F1‐score of 89.11% on average. The results show that the proposed method outperforms the existing detection paradigms of either single signal or single time‐frequency diagram strategy. In addition, the average kappa coefficient of visual analysis and automatic detection results is 0.795. The method shows strong generalization ability and high degree of consistency with the gold standard meanwhile. Therefore, it has great potential to be a clinical assistant tool.
Estimation and Analysis of Sports Energy Consumption Based on Gait Tactile Parameters
Authors: Yan Wang , Jian-Cheng Zang , Bi-Tao Li
Published: December 2021

The morbidity of obesity and related metabolic syndrome is on the rise, which may be related to the decrease of physical activity. Therefore, keeping energy balance is the basic premise to prevent multiple metabolic syndromes, and the research on the composition and application of energy consumption has become a hot spot. The combination of expectation-maximization algorithm and MapReduce computing model realizes the migration of traditional algorithm to “cloud computing” platform. The physical fitness evaluation algorithm based on collaborative filtering is constructed, and a gait tactile recognition algorithm is proposed by feature selection based on the MEMS sensor. Finally, the algorithm is tested, and a conclusion is drawn. This algorithm is effective in monitoring and recognizing human gait. With the increase of weightlessness characteristics, the sensitivity of detection remains unchanged, and the specificity will increase. In a word, it is scientific and effective. Thus, the reference for establishing the index system of tactile biomechanical parameters of adolescent gait and studying the low-cost and portable energy measurement method of multiparameter indexes is provided.
Banks Credit Risk Prediction with Optimized ANN Based on Improved Owl Search Algorithm
Authors: Sharifi Pegah , Jain Vipin , Arab Poshtkohi Mehdi , seyyedi Erfan , Aghapour Vahid
Published: December 2021

Credit is one of the most significant elements in banks and financial institutions. It can also be described as unpredicted events, which mainly occur in the form of either assets or liabilities. The risk occurrence is that the facility recipients have no willingness and ability to repay their debt to the bank, which is a default that is synonymous with credit risk. Credit ratings are a way to decrease and measure credit risk and, therefore, manage it appropriately. Credit rating is an approach for estimating the features and recipients of facilities’ performance based on quantitative criteria, including the company’s financial information. The anticipated future performance allows the applicants to obtain facilities with the exact specifications. In this study, due to the need and significance of calculating the credit risk concept, a novel method based on the hybrid method of artificial neural networks and an improved version of Owl search algorithm (IOSA) and forecasting of C5 risk of decision tree credit is done. This algorithm has two major parts. The decision tree runs based on an IOSA to provide the best weighting of the neural network. The weights created along with the problem data are then given as the input to the main network, and the data are classified. The algorithm has the highest level of accuracy, 96% that is much higher than other algorithms. The results also show a precision of 0.885 and a recall of 0.83 for 618 true positive samples. The proposed method has the highest accuracy and reliability toward the other comparative methods. The study is based on actual data noticed in one of the branches of the Bank Melli, Iran.
Research on the Evolution Path of China’s Provincial Innovation Chain Model Based on Complex Network Model
Authors: Li Xiangqian , Chen Caiyun , Huang Li , Chen Huawei , Huang Cunquan
Published: December 2021

By constructing a complex network analysis model, this paper analyzes the data of 31 selected provinces in China from 2010 to 2019, summarizes China’s provincial innovation chain development model, and then combined with the time series analyzes the evolution path of the model. The research shows that there is certain group proximity in China’s provincial innovation chain in each year, and there are eleven models in ten years. The evolution path of the provincial innovation chain development model is mainly manifested in the development trend of low-level to medium-level and then high-level equilibrium model. Increasing investment and improving efficiency are the leading driving force for the development of China’s provincial innovation chain. The medium-level equilibrium model runs through almost all years. Taking this as the node, the innovation driving force gradually changes from high investment to high efficiency.
Degradation Analysis of Jute Fiber Reinforced Waste Tile Powder-Filled Polymer Composite on Wear Characteristics
Authors: Balan G. Sakthi , Sridharan M. , Balasundaram R. , Sasikaran A. , Sagar M. , Dinesh S. , Vijayan V. , Rajkumar S.
Published: December 2021

In this study, a polymer composite is made using chemically treated jute fiber and waste floor tile powder as an alternative source for roof tile application. The wear qualities were examined at various ages, and the outcomes were optimized. In order to improve the wetting properties of the jute fiber, it was chemically treated. MINITAB software was used to develop Taguchi method parameters such as jute fiber percentage, waste tile powder percentage, and NaOH chemical treatment using the MINITAB software. It was determined that hardness was the most important characteristic in terms of wear properties after the specimens were subjected to ageing and abrasion wear testing and hardness tests were carried out as per normal protocols. As a result of the waste tile powder addition, the surface and core pore formation rates were reduced and the wear index rates were low. Jute fiber with 15%, 9% tile powder, and 5% NaOH treatment were found to have the lowest wear index of the other specimen compositions tested, according to the wear index. Specimen made with 5% jute fiber addition, 9% tile powder inclusion, and 10% NaOH treatment, on the other hand, had more hardness. Degradation of the fibers and delamination are side effects of the ageing process. The wear resistance of the surface was increased by the use of waste tile powder.
Efficient Synthesis of Biodiesel Catalyzed by Chitosan-Based Catalysts
Authors: Wang Anping , Quan Wenxuan , Zhang Heng
Published: December 2021

Catalysts play an important role in the preparation of biodiesel. It is of great significance to study catalysts with high efficiency, low cost, and easy preparation. Compared with the homogeneous catalyst system, the heterogeneous catalyst is easy to separate and has a better catalytic effect. In heterogeneous catalysts, supports and preparation methods have important effects on the dispersion of active centers and the overall performance of catalysts. However, the supports of existing solid catalysts have defects in porosity, structural uniformity, stability, and specific surface area, and the preparation methods cannot stabilize covalent bonds or ionic bonds to bind catalytic sites. Considering the activity, preparation method, and cost of the catalyst, biomass-based catalyst is the best choice, but the specific surface area of the biomass-based catalyst is relatively low, the distribution of active centers is uneven, and it is easy to lose. Therefore, the hybrid carrier of biomass-based catalyst and other materials can not only improve the specific surface area but also make the distribution of active centers uniform and the catalytic activity better. Based on this, we summarized the application of chitosan hybrid material catalysts in biodiesel. The preparation, advantages and disadvantages, reaction conditions, and so on of chitosan-based catalysts were mainly concerned. At the same time, exploring the effects of different types of chitosan-based catalysts on the preparation of biodiesel and exploring the process technology with high efficiency and low consumption is the focus of this paper.
Application of English Vocabulary Presentation Based on Clustering in College English Teaching
Authors: Yang Qiujuan
Published: December 2021

As the most basic element in English learning, vocabulary has always been the focus of teaching in college English classes, but the teaching effect is often unsatisfactory. In this paper, the genetic algorithm fitness function design part is integrated with the K-medoids algorithm to form K-GA-medoids, and secondly, it is combined with KNN to form an algorithmic framework for English vocabulary classification. In the classification process, clustering and classification steps are taken to realize the reduction of the training set samples and thus reduce the computational overhead. The experiments show that K-GA-medoids have significantly improved the clustering effect compared with traditional K-medoids, and the combination of K-GA-medoids and KNNs has effectively improved the efficiency of English vocabulary classification compared with the traditional KNN algorithm, while ensuring the classification accuracy. We found that students in college English course consider word memorization as a difficult learning task, and the traditional vocabulary teaching methods are not very effective, and the knowledge of etymology is often little known and rarely covered in classroom lectures. Therefore, the article explores new ideas and strategies for teaching vocabulary in college English from the perspective of etymology.
Diagnosis and Analysis of Transabdominal and Intracavitary Ultrasound in Gynecological Acute Abdomen
Authors: Yang Huali , Wang Renying , Zhao Liangchao , Ye Jinhua , Li Nengping , Kong Lei
Published: December 2021

In order to explore the effective diagnosis method of gynecological acute abdomen, this paper takes hospital gynecological acute abdomen patients as samples and selects gynecological acute abdomen patients admitted to the hospital to be included in this study. They are divided into transabdominal ultrasound group, intracavitary ultrasound group, and combined group. Moreover, this paper uses mathematical statistics to carry out sample statistics. The statistical data mainly include ectopic pregnancy, torsion of ovarian tumor pedicle, acute suppurative salpingitis, torsion of fallopian tube, hemorrhagic salpingitis, acute pelvic inflammatory disease, rupture of corpus luteum cyst, and diagnosis accuracy rate. In addition, this paper compares the diagnostic accuracy of the abdominal ultrasound group, the intracavitary ultrasound group, and the combined group. The experimental research shows that the combined ultrasound diagnosis method can effectively improve the accuracy of the diagnosis of gynecological acute abdomen.
Analysis of the Influence of Transmission Housing Elasticity on the Vibration Characteristics of Gear Shafting under Coupling Effect
Authors: Huang Hanlin , Fu Shengping , Luo Shanming
Published: December 2021

The influences of transmission housing elastic deformations on the vibration gear shafting characteristics are studied. The vibration model of the vehicle transmission system in consideration of the dynamics coupling of the housing and the gear shafting is constructed. Aiming at a vehicle transmission, the mathematical model of the bending and torsional gear shafting vibrations is established based on the lumped mass method. Following the elastic treatment of the box, a comprehensive stiffness model at the bearing considering the housing deformation is proposed to achieve the dynamic coupling between the box and the gear shafting system. Furthermore, the gear shafting vibration characteristics considering housing deformations are obtained by integrating multisource dynamic excitation, which is solved using an iterative method. The results are verified through a bench test. And, it shows that the elastic deformation of the housing aggravates the gear shafting vibration (bending and torsional coupled vibration). The peak frequency mostly remains the same. The maximum speed changes amplitude and associated root mean square value (calculated at the gear position) increase by 55.5% and 59.6%, respectively. Next, the maximum bearing support force and its root mean square value are increased by 63.7% and 97.6%, respectively. Finally, the largest increase in maximum vibration acceleration at the measuring point and the simulated root mean square value are 90% and 63.1%, respectively. It is concluded that the research results provide a theoretical basis for the study of transmission dynamic reliability.
Correlation between Renal Artery Anatomy and Hypertension: A Retrospective Analysis of 3000 Patients
Authors: Shen Jiayi , Lyu Lingchun , Wu Xiaoyan , Ji Jiansong , Zeng Chunlai , Li Shan , Zhao Yanan , Xu Jian , Lin Li , Lu Chenyin , Mao Wei , Wei Tiemin
Published: December 2021

Objective. To assess the correlation between renal artery anatomy and blood pressure in Undiagnosed Hypertension and Diagnosed Hypertension. Methods. The renal artery CT scanning imaging data and laboratory data of 3000 inpatients and outpatients were collected retrospectively in 4 centers of China. Morphometric parameters were assessed using the quantitative vascular analysis (unit: mM). Results. 687 cases (23.2%) had accessory renal arteries unilaterally, and 216 cases (7.3%) had bilateral accessory renal arteries, including left kidney 825 (27.9%) and right kidney 798 (27.0%). The presence of accessory renal arteries and renal artery branches was higher in the diagnosed hypertension group as compared with the undiagnosed hypertension group (MARB,

p

p < 0.001; ARA,

p

 < 0.001; others,

p

 < 0.001). Consequently, multivariate regression analysis showed that age (OR = 2.519 (95% CI: 0.990–6.411,

p

 < 0.001)), dyslipidemia (OR = 1.187 (95% CI: 0.960–1.454,

p

 = 0.007)), renal hilum Outside the main renal artery branch (MRAB) (OR = 2.069 (95% CI: 1.614–2.524,

p

 = 0.002)), and accessory renal artery (ARA) (OR = 2.071 (95% CI: 1.614–2.634,

p

 = 0.001)) were risk factors of hypertension. In addition, higher renin activity was associated with ARA patients (2.19 ± 2.91 vs. 1.75 ± 2.85,

p

 < 0.001). Conclusions. When comparing renal arteries side by side, the anatomical length of the renal arteries is significantly different. In addition, the prevalence of accessory renal arteries and renal artery branches is higher in the hypertension group. The auxiliary renal artery and the main renal artery branch outside the renal portal are independent factors of hypertension. Renal sympathetic nerve activity is affected by renin activity and is related to the accessory renal artery.
Prevention of Postsurgical Abdominal Adhesion Using Electrospun TPU Nanofibers in Rat Model
Authors: Gholami Ahmad , Abdoluosefi Homeira Emad , Riazimontazer Elham , Azarpira Negar , Behnam Mohamadali , Emami Farzin , Omidifar Navid
Published: December 2021

Intra‐abdominal adhesions following surgery are a challenging problem in surgical practice. This study fabricated different thermoplastic polyurethane (TPU) nanofibers with different average diameters using the electrospinning method. The conditions were evaluated by scanning electron microscopy (SEM), atomic force microscope (AFM), and Fourier transform infrared spectrometer (FTIR) analysis. A static tensile test was applied using a strength testing device to assess the mechanical properties of the electrospun scaffolds. By changing the effective electrospinning parameters, the best quality of nanofibers could be achieved with the lowest bead numbers. The electrospun nanofibers were evaluated in vivo using a rat cecal abrasion model. The macroscopic evaluation and the microscopic study, including the degree of adhesion and inflammation, were investigated after three and five weeks. The resultant electrospun TPU nanofibers had diameters ranging from about 200 to 1000 nm. The diameters and morphology of the nanofibers were significantly affected by the concentration of polymer. Uniform TPU nanofibers without beads could be prepared by electrospinning through reasonable control of the process concentration. These nanofibers’ biodegradability and antibacterial properties were investigated by weight loss measurement and microdilution methods, respectively. The purpose of this study was to provide electrospun nanofibers having biodegradability and antibacterial properties that prevent any adhesions or inflammation after pelvic and abdominal surgeries. The in vivo experiments revealed that electrospun TPU nanofibers reduced the degree of abdominal adhesions. The histopathological study confirmed only a small extent of inflammatory cell infiltration in the 8% and 10% TPU. Conclusively, nanofibers containing 8% TPU significantly decreased the incidence and severity of postsurgical adhesions, and it is expected to be used in clinical applications in the future.
Accelerative Effect of Cinnamon Nanoparticles as well as HAMLET on Healing of Wounds Infected with MRSA in Diabetic Rats
Authors: Ali Ramezani , Alireza Najafpour , Reza Farahpour Mohammad , Rahim Mohammadi
Published: December 2021

Objective. The aim of the present study was to investigate the effect of cinnamon nanoparticles (CNPs) on healing of wounds infected with methicillin‐resistant Staphylococcus aurous with human alpha‐lactalbumin made lethal to tumor cells sensitization in diabetic rats. Methods. We included fifty diabetic male rats and divided them into 5 groups. There were 10 rats in each group as follows: CONTROL group: we did not infect the CONTROL group. The wound was only covered with sterile saline 0.9% solution (0.1 mL). INFCTD group: in this group, the wounds were infected with MRSA and covered with sterile saline 0.9% solution (0.1 mL). INFCTD‐HMLT group: in this group, the wounds were infected with MRSA and HAMLET (100 μg). INFCTD‐CNM group: in this group, the wounds were infected with MRSA and 0.1 mL CNPs (1 mg/mL) were applied topically to wounds. INFCTD‐HMLT‐CNM group: in this group, the wounds were infected with MRSA, HAMLET (100 μg), and 0.1 mL CNPs (1 mg/mL). Results. Bacteriology, wound area reduction measurements, biochemistry, histomorphometrical studies, hydroxyproline levels, and reverse transcription polymerase chain reaction for caspase‐3, Bcl‐2, and p53 showed significant difference between rats in the INFCTD‐HMT‐CNM group in comparison with other groups (P < 0.05). Conclusions. Accelerated healing of diabetic wounds infected with MRSA showed that local application of cinnamon nanoparticles along with HAMLET sensitization on S. aureus‐infected wound could be taken into consideration.
EIF4A3-Induced circARHGAP29 Promotes Aerobic Glycolysis in Docetaxel-Resistant Prostate Cancer through IGF2BP2/c-Myc/LDHA Signaling
Authors: Jiang Xingkang , Guo Shanqi , Wang Shuo , Zhang Yangyi , Chen Haojie , Wang Yong , Liu Ranlu , Niu Yuanjie , Xu Yong
Published: December 2021

Docetaxel-based chemotherapy is a standard-of-care treatment for metastatic prostate cancer, and chemoresistance remains a major challenge in clinical practice. Recent studies have demonstrated that circular RNAs (circRNA) play critical roles in the development and progression of prostate cancer. However, the biological roles and potential functions of circRNAs in mediating docetaxel-resistant prostate cancer have yet to be well elucidated. In this study, we analyzed the expression profiles of circRNAs in docetaxel-resistant and -sensitive prostate cancer cells through RNA sequencing and found that expression of circARHGAP29 was significantly upregulated in docetaxel-resistant cell lines and clinical samples. Ectopic expression of circARHGAP29 triggered docetaxel resistance and aerobic glycolysis in prostate cancer cells, which was reduced by silencing circARHGAP29. Moreover, eukaryotic initiation factor 4A3, which bound the back-spliced junction site and the downstream flanking sequence of circARHGAP29, induced cyclization and cytoplasmic export of circARHGAP29. circARHGAP29 increased the stability of lactate dehydrogenase A (LDHA) mRNA by strengthening its interaction with insulin-like growth factor 2 mRNA-binding protein 2, leading to enhanced glycolytic metabolism. In addition, circARHGAP29 interacted with and stabilized c-Myc mRNA and protein, which further increased LDHA expression by facilitating its transcription. These findings reveal the crucial function of circARHGAP29 in prostate cancer glycolysis by increasing and stabilizing LDHA mRNA, providing a promising therapeutic target in docetaxel-resistant prostate cancer.

Significance:

Upregulation of a novel circRNA, circARHGAP29, promotes docetaxel resistance and glycolytic metabolism, suggesting it could be a prognostic biomarker and therapeutic target in chemoresistant prostate cancer.
From Basic Science to Clinical Translation in Kidney Cancer: A Report from the Second Kidney Cancer Research Summit
Authors: Choueiri Toni K. , Albiges Laurence , Atkins Michael B. , Bakouny Ziad , Bratslavsky Gennady , Braun David A. , Haas Naomi B. , Haanen John B.A.G. , Hakimi A. Ari , Jewett Michael A.S. , Jonasch Eric , Kaelin William G. , Kapur Payal , Labaki Chris , Lewis Bryan , McDermott David F. , Pal Sumanta K. , Pels Kevin , Poteat Susan , Powles Thomas , Rathmell W. Kimryn , Rini Brian I. , Signoretti Sabina , Tannir Nizar M. , Uzzo Robert G. , Hammers Hans J.
Published: December 2021

The second Kidney Cancer Research Summit was held virtually in October 2020. The meeting gathered worldwide experts in the field of kidney cancer, including basic, translational, and clinical scientists as well as patient advocates. Novel studies were presented, addressing areas of unmet need related to different topics. These include novel metabolic targets, promising immunotherapeutic regimens, predictive genomic and transcriptomic biomarkers, and variant histologies of renal cell carcinoma (RCC). With the development of pioneering technologies, and an unprecedented commitment to kidney cancer research, the field has tremendously evolved. This perspective aims to summarize the different sessions of the conference, outline major advances in the understanding of RCC and discuss current challenges faced by the field.
Preclinical Development of the Class-I–Selective Histone Deacetylase Inhibitor OKI-179 for the Treatment of Solid Tumors
Authors: Diamond Jennifer R. , Pitts Todd M. , Ungermannova Dana , Nasveschuk Christopher G. , Zhang Gan , Phillips Andrew J. , Bagby Stacey M. , Pafford Jessica , Yacob Betelehem W. , Newton Timothy P. , Tentler John J. , Gittleman Brian , Hartman Sarah J. , DeMattei John A. , Winkler James D. , Wendt Michael K. , Schiemann William P. , Eckhardt S. Gail , Liu Xuedong , Piscopio Anthony D.
Published: December 2021

Histone deacetylases (HDACs) play critical roles in epigenomic regulation, and histone acetylation is dysregulated in many human cancers. Although HDAC inhibitors are active in T-cell lymphomas, poor isoform selectivity, narrow therapeutic indices, and a deficiency of reliable biomarkers may contribute to the lack of efficacy in solid tumors. In this article, we report the discovery and preclinical development of the novel, orally bioavailable, class-I–selective HDAC inhibitor, OKI-179. OKI-179 and its cell active predecessor OKI-005 are thioester prodrugs of the active metabolite OKI-006, a unique congener of the natural product HDAC inhibitor largazole. OKI-006, OKI-005, and subsequently OKI-179, were developed through a lead candidate optimization program designed to enhance physiochemical properties without eroding potency and selectivity relative to largazole. OKI-005 displays antiproliferative activity in vitro with induction of apoptosis and increased histone acetylation, consistent with target engagement. OKI-179 showed antitumor activity in preclinical cancer models with a favorable pharmacokinetic profile and on-target pharmacodynamic effects. Based on its potency, desirable class I HDAC inhibition profile, oral bioavailability, and efficacy against a broad range of solid tumors, OKI-179 is currently being evaluated in a first-in-human phase I clinical trial with plans for continued clinical development in solid tumor and hematologic malignancies.
Targeting IKKε in Androgen-Independent Prostate Cancer Causes Phenotypic Senescence and Genomic Instability
Authors: Gilbert Sophie , Péant Benjamin , Malaquin Nicolas , Tu Véronique , Fleury Hubert , Leclerc-Desaulniers Kim , Rodier Francis , Mes-Masson Anne-Marie , Saad Fred
Published: December 2021

Advanced prostate cancer will often progress to a lethal, castration-resistant state. We previously demonstrated that IKKε expression correlated with the aggressiveness of prostate cancer disease. Here, we address the potential of IKKε as a therapeutic target in prostate cancer. We examined cell fate decisions (proliferation, cell death, and senescence) in IKKε-depleted PC-3 cells, which exhibited delayed cell proliferation and a senescent phenotype, but did not undergo cell death. Using IKKε/TBK1 inhibitors, BX795 and Amlexanox, we measured their effects on cell fate decisions in androgen-sensitive prostate cancer and androgen-independent prostate cancer cell lines. Cell-cycle analyses revealed a G2–M cell-cycle arrest and a higher proportion of cells with 8N DNA content in androgen-independent prostate cancer cells only. Androgen-independent prostate cancer cells also displayed increased senescence-associated (SA)-β-galactosidase activity; increased γH2AX foci; genomic instability; and altered p15, p16, and p21 expression. In our mouse model, IKKε inhibitors also decreased tumor growth of androgen-independent prostate cancer xenografts but not 22Rv1 androgen-sensitive prostate cancer xenografts. Our study suggests that targeting IKKε with BX795 or Amlexanox in androgen-independent prostate cancer cells induces a senescence phenotype and demonstrates in vivo antitumor activity. These results strengthen the potential of exploiting IKKε as a therapeutic target.