bluuebunny/crossref_metadata_2025 huggingface dataset:
Big Data Analysis and Prediction System Based on Improved Convolutional Neural Network
Authors: Du Xuegong , Cao Xiaojun , Zhang Rui
Published: March 2022

This paper presents a big data analysis and prediction system based on convolutional neural networks. Continuous template matching technology is used to analyze the distributed data structure of big data, and the information fusion processing of cloud service combination big data is combined with matching related detection methods, frequent item detection, and association rule feature extraction of high-dimensional fusion data. A clustering method is adopted to realize the classification and mining of cloud service portfolio big data. The hardware equipment of the car to detect the surrounding environment is complicated, and the combination of the convolutional neural network and the camera to detect the surrounding environment has become a research hotspot. However, simply using the convolutional neural network to process the camera data to control the turning angle of the car has the problems of long training time and low accuracy. An improved convolutional neural network is proposed. The experimental results show that the accuracy of data mining by this method is 12.43% and 21.76% higher than that of traditional methods, and the number of iteration steps is shorter, indicating that the timeliness of mining is higher. This network structure can effectively improve the training speed of the network and improve the accuracy of the network. It is proven that the convolutional neural network has faster training speed and higher accuracy.
The Novel Nrf2 Activator Omaveloxolone Regulates Microglia Phenotype and Ameliorates Secondary Brain Injury after Intracerebral Hemorrhage in Mice
Authors: Hu Libin , Cao Yang , Chen Huaijun , Xu Lei , Yang Qiguo , Zhou Hang , Li Jianru , Yu Qian , Dou Zhangqi , Li Yin , Yan Feng , Liu Fuyi , Chen Gao
Published: March 2022

The polarization of microglia is recognized as a crucial factor in reducing neuroinflammation and promoting hematoma clearance after intracerebral hemorrhage (ICH). Previous studies have revealed that redox components participate in the regulation of microglial polarization. Recently, the novel Nrf2 activator omaveloxolone (Omav) has been validated to improve neurological function in patients with neurodegenerative disorders by regulating antioxidant responses. In this study, we examined the efficacy of Omav in ICH. Omav significantly promoted Nrf2 nuclear accumulation and the expression of HO-1 and NQO1 in BV2 cells. In addition, both in vitro and in vivo experiments showed that Omav treatment inhibited M1-like activation and promoted the activation of the M2-like microglial phenotype. Omav inhibited OxyHb-induced ROS generation and preserved the function of mitochondria in BV2 cells. Intraperitoneal administration of Omav improved sensorimotor function in the ICH mouse model. Importantly, these effects were blocked by pretreatment with ML385, a selective inhibitor of Nrf2. Collectively, Omav modulated microglial polarization by activating Nrf2 and inhibiting ROS generation in ICH models, suggesting that it might be a promising drug candidate for the treatment of ICH.
Design of Distributed Human Resource Management System of Spark Framework Based on Fuzzy Clustering
Authors: Sun Qing , Wu Tao , Hua Jia
Published: March 2022

The construction of human resource management system is a key part of enterprise management and control. A perfect human resource management system is conducive to the long-term development of enterprises. Aiming at improving the current situation of enterprise human resource management, a distributed human resource management system is proposed in this paper based on Spark framework. Aiming at the disadvantages of traditional

k

-means algorithm in processing massive data, such as low computational efficiency and high time complexity, an improved

k

-means algorithm based on Spark computing framework is proposed. Through the spatial location relationship with the cluster center, redundant calculation is reduced and the ability of processing massive data is improved for the system. Combined with the actual situation of the enterprise, the human resource management system architecture is designed by using Java EE human-computer interaction. The proposed system can achieve user management, employee information, attendance, evaluation, performance, salary, personnel change, and other business management. The experimental results demonstrate that the system can effectively reduce the time complexity of calculation and improve the system efficiency.
Analysis of the Epidemic Biological Model of Tuberculosis (TB) via Numerical Schemes
Authors: Kanwal S. , Siddiqui M.K. , Bonyah E. , Sarwar K. , Shaikh T.S. , Ahmed N.
Published: March 2022

Tuberculosis (TB) is caused by bacillus Mycobacterium tuberculosis (MTB). In this study, a mathematical model of tuberculosis (TB) is analyzed. The numerical behaviour of the considered model is analyzed including basic reproduction number and stability. We applied three numerical techniques to this model, i.e., nonstandard finite difference (NSFD) scheme, Runge–Kutta method of order 4(RK‐4), and forward Euler (FD) scheme. NSFD scheme preserves all the essential properties of the model. Acquired results corroborate that NSFD scheme converges for each step size. While the other two schemes failed to preserve some properties of the model such as positivity and convergence. A graphical comparison presented in this study confirms the numerical stability of the NSFD technique shown here is maintained over a large area.
Analysis on the Types and Characteristics of Collusion Behavior of Government Investment Project Tenderees
Authors: Nie Sirui , Chen Yun , Li Jingjing , Zhu Wenxi , Ma Chongsen
Published: March 2022

The classification of collusion behaviors of government‐invested project tenderers is one of the important methods to describe the characteristics and laws of collusion behaviors and strengthen the governance of collusion. Firstly, the variables that affect the type of collusion behavior are selected and cluster analysis is carried out on the cases of collusion in government investment project bidding. Then use the social network to mine the types and characteristics of the collusion behavior of the tenderee. Finally, a BP neural network automatic identification model is established to quickly discriminate the types of collusion, which can effectively overcome the subjectivity of traditional methods. As a result, three typical types of collusion of tenderees can be obtained: intervention type, opportunity type, and cooperation type. The study found that the three types of collusion behavior have their own characteristics and laws, and the relationship between the variables that affect the type of collusion behavior is complex and affects each other.
Research and Evaluation on Dynamic Response Characteristics of Various Pavement Structures
Authors: Guo Meng , Hou Fujin , Zhang Shuaixiang , Li Xu , Li Yunliang , Bi Yufeng
Published: March 2022

In order to comprehensively analyze the dynamic response of full-depth asphalt pavement under moving load, a three-dimensional model of pavement structure and dynamic load moving zone are established based on ABAQUS finite element software. Based on the time history curves of different structures, the stress-strain states at the bottom of each structural layer in different structures under moving load are analyzed. The results show that the stress, strain, and shear stress of the middle layer of full-depth pavement are smaller than those of semirigid base pavement, and rutting is closely related to the deformation of this layer. The dynamic response results of the same structure at different speeds are similar, but the increase of the maximum speed will increase the shear stress at the bottom of the layer, and the road is more prone to longitudinal crack.
Migration of Tenckhoff Catheter to Sigmoid Colon: A Rare Delayed Complication
Authors: Topal Uğur , Ülkü Abdullah , Sarıtaş Ahmet Gökhan , Akçam Atilgan Tolga , Ünal Ayşe Gizem , Eray İsmail Cem
Published: March 2022

Bowel perforation associated with inserted peritoneal dialysis (PD) catheter mainly occurs during the perioperative period. Delayed bowel perforation is difficult to diagnose because of its different clinical signs and rarity. A 53-year-old woman developed acute abdomen after her PD catheter was changed. It was found that the changed catheter perforated the sigmoid colon. Primary repair of the perforated area of the sigmoid colon was performed, and the last inserted PD catheter was removed. The postoperative period and recovery were uneventful. Perforations due to the PD catheter may remain silent until the catheter is replaced. In patients with frequent episodes of peritonitis, a perforation area due to PD catheter which limited itself should be considered as the etiology.
Roughness in Hypervector Spaces
Authors: Abughazalah Nabilah , Yaqoob Naveed , Usman Muhammad
Published: March 2022

This paper examines rough sets in hypervector spaces and provides a few examples and results in this regard. We also investigate the congruence relations-based unification of rough set theory in hypervector spaces. We introduce the concepts of lower and upper approximations in hypervector spaces.
Empirical Analysis of the Relationship between Renewable Energy Consumption and Economic Growth Based on the Grey Markov Model
Authors: Liu Chao
Published: March 2022

According to the global renewable energy attraction index, countries (regions) are selected as the analysis samples, and then the function model is improved. Considered as independent input factors into the function, the sample countries and the data are analyzed for stationarity and cointegration relationship test. With the excessive use of nonrenewable energy and the frequent occurrence of nuclear safety problems, it is imperative to develop renewable energy under the background that governments all over the world advocate energy conservation and emission reduction. By formulating active renewable energy industrial policies, governments and enterprises can not only enable the government to achieve the goal of energy conservation and emission reduction but also promote economic development to a certain extent. 34 countries (regions) were selected as analysis samples, and then the production function model was improved. Renewable energy and nonrenewable energy were considered as independent input factors into the Cobb‐Douglas function, and the panel data model was established by using the economic data of sample countries from 1994 to 2014.
Natural Products for Cancer Therapy: A Review of Their Mechanism of Actions and Toxicity in the Past Decade
Authors: Ali Abdalla Yasir Osman , Subramaniam Bavani , Nyamathulla Shaik , Shamsuddin Noorasyikin , Arshad Norhafiza M. , Mun Kein Seong , Awang Khalijah , Nagoor Noor Hasima
Published: March 2022

The ethnopharmacological information gathered over many centuries and the presence of diverse metabolites have made the medicinal plants as the prime source of drugs. Despite the positive attributes of natural products, there are many questions pertaining to their mechanism of actions and molecular targets that impede their development as therapeutic agents. One of the major challenges in cancer research is the toxicity exerted by investigational agents towards the host. An understanding of their molecular targets, underlying mechanisms can reveal their anticancer efficacy, help in optimal therapeutic dose selection, to mitigate their side effects and toxicity towards the host. The purpose of this review is to collate details on natural products that are recently been investigated extensively in the past decade for their anticancer potential. Besides, critical analysis of their molecular targets and underlying mechanisms on multiple cancer cell lines, an in-depth probe of their toxicological screening on rodent models is outlined as well to observe the prevalence of their toxicity towards host. This review can provide valuable insights for researchers in developing methods, strategies during preclinical and clinical evaluation of anticancer candidates.
The Index Data System of Agricultural Modernization Development Based on Internet Big Data
Authors: Cao Changyan
Published: March 2022

With the integration and development of the Internet, the Internet of Things, cloud data, and communication technology, data has grown rapidly. Although science and technology have promoted the upgrade and modernization of the modern agricultural system, it has also brought about the problem of a sharp increase in data, making it difficult to grasp the direction of agricultural development. At the same time, in order to better grasp the development of agricultural modernization, this article has carried out research on the agricultural modernization development index data system based on network big data and raised the problem that agricultural modernization based on network big data can accurately grasp the development direction of agricultural modernization. Experiments show that the index data system studied in this article has a good grasp of the state of agricultural modernization development and is the basis for judging and formulating correct agricultural policies. Among them, the indicator data on the rate of change of the national agricultural policy needs to be maintained between 1.84 and 2.01. The research in this article is of great significance to the development of agricultural modernization.
Evaluating Rainy Weather Effects on Driving Behaviour Dimensions of Driving Behaviour Questionnaire
Authors: Bakhshi Vahid , Aghabayk Kayvan , Parishad Nasser , Shiwakoti Nirajan
Published: March 2022

This study aims to develop a modified version of the existing driving behaviour questionnaire (DBQ) by including items related to driving behaviour under rainy conditions to evaluate driving behaviour changes and their implications. A survey of 680 drivers in Iran was conducted with the modified DBQ considering rainy conditions. Exploratory and confirmatory factor analysis concluded a four-factor solution (high velocity with a law violation, slips, positive and cautious behaviours, and aggressive driving behaviours) with a 52% explanation of variance. One of the most affected driving behaviours during rainfall is the tendency of high velocity with law violation behaviours. Compared to male drivers, female drivers showed lower high-velocity behaviours with law violation when driving in dry weather and in rainy weather. Married drivers have not only less tendency to drive fast or violate the law compared to single drivers but are also less susceptible to these actions during rain. It was observed that young drivers under 25 did not change their aggressive driving behaviours in rainy conditions. The results from this study are valuable resources to help transportation agencies to understand drivers’ likely behaviour in rainy conditions and develop appropriate countermeasures to minimize the risky behaviours. Also, since aggressive driving, high acceleration, and speed variance have been reported to result in high fuel consumption and emissions, the findings from this study are valuable resources to understand the relationship between weather, driver behaviour, and emissions in future studies.
Motion Blur Fuzzy Blind Removal Algorithm for Character Images in Gradient Domain and Deep Learning
Authors: Ren Guoheng , Wang Wei , Wei Hanyu , Li Xiaofeng
Published: March 2022

The imaging device is susceptible to factors such as the subject or the shooting environment when imaging, and complex variable blurring occurs in the final imaging. In most cases, we not only do not have the conditions to re-shoot a clear image but also do not know the specific parameters of the variable blur in advance. Therefore, the purpose of this study is to propose a motion blur fuzzy blind removal algorithm for character images based on gradient domain and depth learning. Deep learning is to learn the inherent laws and representation levels of sample data, and the information obtained during these learning processes is of great help to the interpretation of data such as text, images, and sounds. The algorithm used in this study is to preprocess the image by using guided filtering and L0 filtering and send the preprocessed gradient domain image block to the designed convolutional neural network for training. Extract the trained model parameters and realize the fuzzy kernel estimation and image. Image deblurring is performed using the TV regular term during image restoration. The experiment proves that the algorithm can effectively suppress the ringing effect and reduce the noise, and the motion blur effect is better. In this study, the MLP method, the edge detection method, and the proposed method are discussed, respectively. The PSNR values of the three motion blur removal methods are 26.49, 27.51, and 29.18, respectively. It can be seen that the motion blur removal method proposed in this study can effectively remove image motion blur.
Conformance Control for Tight Oil Cyclic Gas Injection Using Foam
Authors: Wei Falin , Zhang Song , Xi Yilin , Zhu Zhouyuan , Xiong Chunming , Zang Chuanzhen , Li Junjian
Published: March 2022

Cyclic gas injection has been proven to be an effective enhanced oil recovery (EOR) technique for tight oil reservoirs. During such processes, we expect recovery mechanisms such as oil swelling, oil viscosity reduction, vaporization, and pressure support, which highly relies on the successful conformance control of the injected gas. In this work, we present the numerical simulation study of using foam for improving the conformance control of cyclic gas injection in tight oil reservoir. We focus on improving two categories of conformance control problems using foam, making the injection profile for single well more evenly distributed and mitigating the gas breakthrough to adjacent wells through the connected hydraulic fractures in a multiwell setting. The simulation results show that foam has shown major impact in improving the gas conformance control in both cases. Typical recovery factor improvements are estimated to be up to 1% for lean gas injection in this tight oil reservoir. In conclusion, we have demonstrated the great potential of using foam to improve the conformance in tight oil cyclic gas injection process.
Nomograms for Predicting the Risk of SIRS and Urosepsis after Uroscopic Minimally Invasive Lithotripsy
Authors: Wang Can , Xu Rufu , Zhang Yuanning , Wu Yingbing , Zhang Teng , Dong Xingyou , Zhang Rong , Hu Xuelian
Published: March 2022

Objective. To analyze the potential risk factors that affect the development of urosepsis following uroscopic minimally invasive lithotripsy and to develop a nomogram that predicts the probability of postoperative urosepsis. Methods. We retrospectively analyzed the clinical data from patients that underwent percutaneous nephrolithotripsy (PCNL) or ureteroscopic lithotripsy (URL) between January 2018 and December 2019. The enrolled patients were grouped twice according to systemic inflammatory response syndrome (SIRS) and quick sequential organ failure assessment (qSOFA). After univariate and multivariate logistic regression analyses, we identified the independent predictive factors affecting the development of postoperative SIRS and urosepsis, and built the nomograms. Results. From January 2018 to December 2019, 1959 patients underwent PCNL or URL, of whom 236 patients were accorded with the inclusion criteria. Of all 236 patients, 64 (27.12%) patients developed postoperative SIRS, and 17 (7.20%) patients developed postoperative urosepsis. Multivariate logistic regression analysis showed that positive preoperative urine culture (PUC+) (OR = 2.331, P = 0.044), procalcitonin (PCT) (OR = 1.093, P = 0.037), C‐reactive protein (CRP) (OR = 1.017, P < 0.001), and neutrophil ratio (NEUT%) (OR = 1.091, P = 0.004) of postoperative were independent predictors of SIRS, and PCT (OR = 1.017, P = 0.003) and CRP (OR = 1.080, P < 0.001) were independent predictors of urosepsis. Additionally, the nomograms demonstrated good accuracy in predicting SIRS and urosepsis with a C‐index of 0.884 (95% CI: 0.835‐0.934) and 0.941 (95% CI: 0.885‐0.996), respectively. Conclusions. The nomograms achieved the prediction of SIRS and urosepsis after uroscopic minimally invasive lithotripsy. Using this model, the risk of SIRS or urosepsis for an individual patient can be determined, which facilitates early diagnosis and rational treatment.
Change in Antithyroglobulin Antibody Levels is a Good Predictor of Responses to Therapy in Antithyroglobulin Antibody-Positive Pediatric Papillary Thyroid Carcinoma Patients
Authors: Xi Chuang , Zhang Guo-Qiang , Song Hong-Jun , Shen Chen-Tian , Hou Li-Ying , Qiu Zhong-Ling , Luo Quan-Yong
Published: March 2022

Objective. Antithyroglobulin antibodies (TgAbs) could be used as a surrogate tumor marker of TgAb-positive-differentiated thyroid carcinoma. This study aims to determine whether the change in TgAb levels over time could be used as a predictor of responses to therapy in pediatric papillary thyroid carcinoma (PTC) patients. Methods. We retrospectively analyzed the records of 48 pediatric PTC patients with TgAb levels ≥50 IU/ml 6 months after initial 131I treatment. Suppressed thyroglobulin (Tg) levels 6 months after initial 131I treatment were used to divide the patients into positive Tg (P-Tg, Tg ≥ 0.2 ng/ml) and negative Tg (N-Tg, Tg < 0.2 ng/ml) groups. Responses to therapy were classified as the acceptable response (AR) group and the not acceptable response (NAR) group. Results. Of 48 enrolled patients with 58 months (range, 24–143 months) of follow-up, 28 patients had NAR and 20 patients had AR. TgAb levels were decreasing ≥50% in 28 patients, decreasing <50% in 8 patients, and increasing in 12 patients. Multivariate analysis showed that high initial risk stratification and TgAb levels decreasing <50% or increasing were significantly associated with NAR (

p
<
0.05

). Changes in Tg levels were also associated with NAR in the P-Tg group (

p
<
0.05

). Conclusion. Changes in TgAb levels over time could be used as a predictor of responses to therapy in TgAb-positive pediatric PTC patients. Changes in Tg levels over time are also associated with NAR to therapy in both TgAb-positive and Tg-positive pediatric PTC patients.
Evaluation of Intraocular Lens Tilt and Decentration in Congenital Ectopia Lentis by the Pentacam Scheimpflug System
Authors: Ye Huiwen , Liu Zhenzhen , Cao Qianzhong , Lian Zhangkai , Zhang Xinyu , Zheng Danying , Jin Guangming
Published: March 2022

Purpose. The purpose of this study was to quantify the characteristics of the tilt and decentration of the IOL after trans-scleral suture fixation surgery in congenital ectopia lentis (CEL) patients. Methods. The clinical characteristics of 70 CEL patients at Zhongshan Ophthalmic Center in China were retrospectively analyzed. The tilt and decentration of intraocular lens (IOL) were measured by using a Pentacam and compared between different axial length (AL) subgroups. The correlation between IOL tilt, decentration, and ocular characteristics was investigated using Spearman’s correlation analysis. Results. The postoperative IOL position of CEL patients was mainly located nasally inferiorly. The average tilt of the IOL in CEL patients was less than 7° (for temporal: 2.21 ± 1.53°, for nasal: −1.84 ± 2.04°, for superior: 2.22 ± 2.18°, and for inferior: −1.70 ± 1.62°), and the average decentration of the IOL in CEL patients was larger than 0.4 mm (for temporal: 0.49 ± 0.38 mm, for nasal: −0.69 ± 0.46 mm, for superior: 0.72 ± 0.58 mm, and for inferior: −0.68 ± 0.54 mm). The decentration of CEL patients in the AL ≥ 26 subgroup was greater than those with AL < 24 mm and AL 24 to 26 mm subgroups (for superior: 0.72 ± 0.28 mm vs. 0.46 ± 0.25 mm and 0.48 ± 0.22 mm, all

P
<
0.05

; for inferior: -0.94 ± 0.56 mm vs. −0.44 ± 0.26 mm and -0.44 ± 0.46 mm, all

P
<
0.05

). IOL decentration was positively correlated with AL (for superior: r = 0.44,

P
=
0.019

; for inferior: r = 0.54,

P
=
0.006

). IOL tilt was positively correlated with AL on the superior side (r = 0.38,

P
=
0.041

). Conclusions. The extent of IOL decentration after trans-scleral suture fixation was great in CEL patients, and the IOL decentration in CEL patients was significantly associated with AL.
Anaphylactic Rare Saponins Separated from Panax notoginseng Saponin and a Proteomic Approach to Their Anaphylactic Mechanism
Authors: Hao Feiran , Pang Xu , Xu Kaikun , Wang Meixi , Ma Zengchun , Tan Hongling , Han Lifeng , Chang Cheng , Chen Ming , Huang Zhanwen , Gao Yue
Published: March 2022

In recent years, many traditional Chinese medicine injections based on Panax notoginseng saponin (PNS) have been reported to cause anaphylaxis. Previous studies on the anaphylactic saponins of PNS and their mechanism are inadequate. In this study, potential anaphylactic saponins were obtained by the separation of PNS and preparation of each individual component through comprehensive techniques, such as liquid chromatography, preparative chromatography, HPLC, NMR, and MS. The anaphylactic abilities of these saponins were tested using RBL-2H3 cells via a β-hexosaminidase release rate test. The results for the mechanism of anaphylaxis were obtained by a proteomic analysis using RBL-2H3 cells. The results indicate that, among all the saponins prepared, gypenoside LXXV and notoginsenoside T5 showed strong anaphylactic abilities and notoginsenoside ST-4 and ginsenoside Rk3 showed weak anaphylactic abilities. These 4 saponins can induce anaphylaxis via direct stimulation of effector cells. The gene oncology enrichment analysis results showed that, among these saponins, only gypenoside LXXV was related to organelles of the endoplasmic reticulum and Golgi apparatus and biological processes in response to organic cyclic compounds. Four proteins in RBL-2H3 cells with the accession numbers A0A0G2JWQ0, D3ZL85, D4A5G8, and Q8K3F0 were identified as crucial proteins in the anaphylactic process. This research will help traditional Chinese medicine injection manufacturers strengthen their quality control and ensure the safety of anaphylactic saponins.
COVID-19 Shocks, Monetary Policy, and Real Estate Price Volatility: Analysis Based on a Dynamic Stochastic General Equilibrium Perspective
Authors: Hou Zhe , Song Yu , Xin Wen
Published: March 2022

The COVID-19 pneumonia epidemic in early 2020 severely affected all sectors of the Chinese economy, with economic growth plummeting but the property market continuing to heat up after a brief contraction. How to formulate an effective monetary policy in the face of the COVID-19 shock to achieve stable economic growth while curbing excessive real estate price inflation has become a pressing issue for Chinese policymakers today. To this end, this paper focuses on the impact of two types of monetary policy, price-based and quantity-based, on macro-economic variables such as real estate prices and aggregate output by developing a multi-sectoral DSGE model incorporating the COVID-19 shock and comparing them. The analysis finds that both monetary policy rules can achieve the objective of dampening real estate prices. Nevertheless, while causing the same magnitude of real estate price contraction, quantity-based monetary policy leads to greater volatility in variables such as aggregate output, while other economic variables are less volatile under the price-based monetary policy.
Overexpression of CISD1 Predicts Worse Survival in Hepatocarcinoma Patients
Authors: Lu Tailiang , Li Chenglong , Xiang Cailing , Gong Yongqiang , Peng Wei , Chen Chaowu
Published: March 2022

Background. Ferroptosis plays a vital role in hepatocellular carcinoma (HCC). CISD1 is known to regulate ferroptosis negatively. However, the correlations of CISD1 to prognosis in HCC and its potential mechanism remain unclear. Aim. To investigate the expression level and prognostic value of CISD1 in HCC. Methods. Gene expression and clinical data for 33 cancer types in TCGA were downloaded from the UCSC Xena platform. Pan‐cancer analysis was performed to determine the expression profile and prognostic value of CISD1 in human cancers. GEO datasets and Human Protein Atlas (HPA) were used to verify the mRNA and protein expression levels. The influence of CISD1 on clinical prognosis in HCC was evaluated using a Kaplan‐Meier plotter. The PPI network was constructed using the STRING database and Cytoscape. GO and KEGG pathways were constructed using the “clusterProfiler” R package with the FDR cutoff of 0.05. The methylation at the CISD1 promoter was detected using UALCAN and GEO datasets. The correlations between CISD1 and HCC immune infiltrates were investigated via TIMER. Results. Pan‐cancer analysis of TCGA data showed that CISD1 is differentially expressed in multiple tumors. Data of gene expression microarrays reveal that the mRNA expression of CISD1 is higher in HCC than that in normal tissue. The protein level of CISD1, validated by the Human Protein Atlas (HPA) database, was upregulated consistently with mRNA levels in HCC samples. High CISD1 expression was associated with better overall survival (OS), disease‐free survival (DFS), disease‐specific survival (DSS), and progression‐free survival (PFS) in LGG, but with poorer OS, DFS, DSS, and PFS in LIHC. Protein‐protein interaction (PPI) analysis and GO/KEGG analysis showed that the PPI network and GO term of CISD1 were mainly associated with energy and iron metabolism. Promoter hypomethylation correlated with overexpression of CISD1. CISD1 expression was positively correlated with infiltrating levels of CD8+ T cells, macrophages, neutrophils, and dendritic cells (DCs) in HCC. Conclusions. These findings suggest that hypomethylation of the CISD1 promoter increases its expression in HCC. CISD1 is associated with prognosis and immune infiltrating levels of CD8+ T cells, macrophages, neutrophils, and DCs in HCC patients. These findings suggest that CISD1 can be used as a prognostic biomarker for determining prognosis in HCC.
Farmers’ Willingness to Pay a High Premium for Different Types of Agricultural Insurance: Evidence from Inner Mongolia, China
Authors: Guo Xinya , Zhao Yuanfeng , Arshad Muhammad Umer , Gong Yufei
Published: March 2022

The productivity of the agricultural sector depends on natural resources, and farmers are vulnerable to substantial weather risks globally. For many years, different insurance products have been promoted in China to manage the negative impact and risk associated with unpredictable natural events. Generally, different insurance products correspond to the various premium levels, and farmers are unaware of the insurance policies and premium calculations. This study focuses on farmers’ preferences toward the insurance of corn crop, one of China’s largest grain crop productions. This study uses Heckman’s two‐stage model to focus on the farmers’ willingness to pay for multiple weather‐based insurances, who suffered severe disasters. The contingent valuation method was used to collect the data about farmers’ willingness to pay and preferences from 252 households across three cities of Inner Mongolia, China. The result of empirical estimation indicates that farmers with less experience and high income tend to choose “60% of full‐cost insurance product.” Farmers with a lack of specialization and lower diversified planting tend to choose “full‐cost insurance product.” In contrast, farmers with higher education prefer “output value insurance product.” The empirical result indicates that the promotion of various agricultural insurance could be a valuable strategy to improve protection levels and manage the risk adjustment input in the agricultural sector. Therefore, this study provides insights into risk reduction design that suggests adopting and encouraging different agricultural insurance products.
Research on Transfer Learning-Based English-Chinese Machine Translation
Authors: Jiaxin Li , Peiting Wang
Published: March 2022

In order to solve the problems of time-consuming and frequent mistranslations in traditional translation methods, this study designed an English-Chinese machine translation method based on transfer learning. On the basis of analyzing the basic principles and specific strategies of English-Chinese machine translation, the traditional neural machine translation methods are analyzed, and then the translation process is optimized by transfer learning. On the basis of preprocessing English-Chinese translation text data, features of English-Chinese translation text are extracted, features of English-Chinese translation text are rapidly classified by feature transfer learning, and machine models of English-Chinese translation are constructed based on the classification results. The objective of feature transfer learning is to reuse the past knowledge obtained in the form of dataset to be utilized for another target data. The findings of the experiment show the effectiveness of the proposed method in achieving the design expectation. The benefit of the proposed method includes a short translation time and fewer mistranslations.
Automatic Extraction of Web Page Text Information Based on Network Topology Coincidence Degree
Authors: Shu Zhinian , Li Xiaorong
Published: March 2022

In order to effectively solve the above problems, an automatic extraction method of web text information based on network topology coincidence degree is proposed. Search engine, web crawler, and hypertext tag are used to classify web text information, and then, dimensionality reduction is carried out. After processing, the similarity of different features of web page text information is calculated, the similarity is sorted, and the similar text information is extracted according to the correlation based on segment estimation. The experimental results show that the designed method can simplify the complexity of the associated information of the data set and improve the amount of data collection and the success rate of information collection.
Sevoflurane Improves Hemorrhagic Shock and Resuscitation-Induced Cognitive Impairments and Mitochondrial Dysfunctions through SIRT1-Mediated Autophagy
Authors: Shu Jianwei , Huang Xiaotong , Liao Qizhi , Wang Jianan , Zhou Yuqi , Chen Yihuan , Chen Ming , Qian Cheng , Zhang Ye , Hu Xianwen , Huang Chunxia
Published: March 2022

Cerebral ischemia reperfusion injury (IRI) induced by hemorrhagic shock and reperfusion (HSR) is the main cause of death following trauma. Previous studies indicated the neuroprotective effect of sevoflurane postconditioning (SP) in cerebral IRI. However, the mechanisms still remain elusive. Cerebral IRI models with SP were established by using HSR with C57BL/6 mice (male, 3-month-old) in vivo and by using oxygen glucose deprivation and reoxygenation (OGD/R) with HT22 cells in vitro. Postoperative cognition was evaluated by the Morris water maze, novel object recognition, and elevated plus maze tests. The role of SIRT1 was determined by using siRNA, a sensitive inhibitor (EX527), or an overexpression shRNA-GFP lentivirus. IRI caused significant disabilities of spatial learning and memory associated with enhanced cerebral infarct and neuronal apoptosis, which were effectively attenuated by SP. IRI also made a significant decrease of SIRT1 accompanied by oxidative stress, mitochondria dysfunction, and inactivated autophagy. SP or genetically overexpressing SIRT1 significantly suppressed defective autophagy, mitochondrial oxidative injury, and neuronal death caused by HSR or OGD/R. However, genetic suppression or pharmacological inhibition of SIRT1 significantly reversed the impact of SP treatment on mitochondrial DNA transcription ability and autophagy. Our results demonstrate that the loss of SIRT1 causes a sequential chain of mitochondrial dysfunction, defective autophagy, and neuronal apoptosis after IRI in the preclinical stroke models. Sevoflurane postconditioning treatment could effectively attenuate pathophysiological signatures induced by noxious stimuli, which maybe mediated by SIRT1.
Gear Fault Detection in a Planetary Gearbox Using Deep Belief Network
Authors: Hao Hu , Fuzhou Feng , Feng Jiang , Xun Zhou , Junzhen Zhu , Jun Xue , Pengcheng Jiang , Yazhi Li , Yongchan Qian , Guanghui Sun , Caishen Chen
Published: March 2022

Traditional prognostics and health management (PHM) methods for fault detection require complex signal processing and manual fault feature extraction, and the accuracy is low. To address these problems, a fault diagnosis method of planetary gearbox based on deep belief networks (DBNs) is proposed. Firstly, the vibration signals of the planetary gearbox are collected and analyzed in the time domain and the frequency domain. Then, the DBN model and optimal parameters are determined to meet the task requirements. Finally, the vibration data is divided into training set and test set and input into the DBN model, which can realize the automatic feature extraction and fault recognition of vibration signals. The results show that the identification accuracy reaches 97% under five working conditions of planetary gearbox.
A Data-Driven Functional Classification of Urban Roadways Based on Geometric Design, Traffic Characteristics, and Land Use Features
Authors: Mehdian Mostafa , Mirzahossein Hamid , Abdi Kordani Ali
Published: March 2022

The functional classification system (FCS) of roads means categorizing roads based on their service characteristics. The two primary considerations in classifying highway and street networks are accessibility and mobility, where by increasing the role of one, the other’s role is reduced. In this paper, besides the conventional variables such as geometric design characteristics, parking lots, land use features, and accessibility; the Sydney Coordinated Adaptive Traffic System (SCATS) data following the real-time traffic flow and average speed of vehicles collected by Location-Based Services (LBS) are considered as new variables for estimating the FCS. Linear regression is used to model the importance of the variables. The chi-square test compared the observational and predicted speeds in the five categories of roads in Tehran, the capital of Iran. Results show that on-street parking has the highest impact and the land use variable has the lowest impact on speed that changes the FCS. Moreover, the presented classification was one to two categories compared with the conventional FCS presented in manuals in the case of Tehran’s transportation network as a developing city.
Clinical Evaluation of Single-Use, Fiber-Optic, and Digital Ureterorenoscopes in the Treatment of Kidney Stones
Authors: Eismann Lennert , Kretschmer Alexander , Alghamdi Abdulmajeed , Eisel Maximilian , Sroka Ronald , Stief Christian G. , Strittmatter Frank
Published: March 2022

Introduction: Indication of ureteroscopy for the treatment of urolithiasis has expanded immensely over the last decade. Fiber-optic and digital reusable instruments present the standard in clinical practice, but various newly available single-use devices might offer an exciting alternative. To date, the evidence is limited to clinical evaluation and efficacy of single-use ureteroscopes (URS) compared to standard instruments. Therefore, we evaluate a single-use instrument’s clinical characteristics and efficacy in direct comparison with a fiber-optic and digital device. Methods: A prospective study was conducted for patients undergoing endoscopic therapy for urolithiasis at a tertiary care center. We evaluated the different instruments’ clinical performance in categories of visibility, the stability of visibility, irrigation flow, and surgeon’s satisfaction. Statistical analyses were performed by SPSS using the Chi-Quadrat and Kruskal-Wallis test. A p value of p ≤ 0.05 was defined as statistically significant. Results: A total number of 77 patients were included and distributed as follows: 35 (46.7%) single-use, 19 (25.3%) digital, and 23 (28%) fiber-optic URS. Patients’ characteristics were homogenous over the three cohorts in sex, stone amount, and localization. The stone-free rate was equal in all three cohorts (p = 0.31). We identify stability of visibility, irrigation flow, and satisfaction were equal in all cohorts (p = 0.73; p = 0.20; p = 0.20). We report a significant difference in visibility, with 100% rated excellent in the digital URS group (p = 0.028). Discussion/Conclusions: Single-use URS achieve comparable clinical outcomes with equal stone-free rates in direct comparison with fiber-optic and digital reusable instruments. Accordingly, single-use devices present an adequate alternative for endoscopic therapy of urolithiasis.
Identification of Centromere-Specific Repeats in the Zebra Finch Genome
Authors: Takki Olga , Komissarov Aleksey , Kulak Maria , Galkina Svetlana
Published: March 2022

Tandem repetitive sequences represent a significant part of many genomes but remain poorly characterized due to various methodological difficulties. Here, we describe the tandem repeat composition in the genome of zebra finch, Taeniopygia guttata, a species that has long served as an animal model, primarily in neurobiology and comparative genomics. Using available genome sequencing raw read datasets, we bioinformatically reconstructed consensus sequences of several tandem repeats and proved that the most abundant ones, Tgut191A and Tgut716A, are centromere-associated in chromosomes. Each centromeric region can have a different number of copies of each repeat, with Tgut716A enrichment in almost all microchromosomes and sex chromosomes. Sequences similar to Tgut191A and Tgut716A found in other Estrildidae and Viduidae species can be considered as candidate centromeric sequences, but this requires further cytogenetic verification.
Comparative Effectiveness between Expanded Hemodialysis (Hemodialysis Using a Medium Cut-Off Dialyzer) and Mixed-Dilution Online Hemodiafiltration Using a High-Flux Dialyzer in Removing Middle-Molecule Uremic Toxins
Authors: Eiamcharoenying Jirarat , Takkavatakarn Kullaya , Chariyavilaskul Pajaree , Susantitaphong Paweena , Eiam-Ong Somchai , Tiranathanagul Khajohn
Published: March 2022

Introduction: Expanded hemodialysis (HD using a medium cut-off dialyzer [HD + MCO]) provides comparable or better removal of various uremic toxins, particularly large middle-molecule uremic toxins, than post-dilution online hemodiafiltration (olHDF). Uremic toxin-removing effectiveness between HD + MCO and mixed-dilution olHDF, one of the currently most efficient olHDF modalities, has not been assessed. Method: This randomized controlled trial was conducted in 14 prevalent thrice-a-week HD patients with blood flow rate above 400 mL/min. The patients were randomized into two sequences of 2-week treatment periods of HD + MCO and later mixed-dilution olHDF or vice versa. The reduction ratio (RR) values of small-molecule as well as middle-molecule uremic toxins and protein-bound uremic toxins were measured at baseline and at the end of the treatment. Results: When compared with mixed-dilution olHDF, HD + MCO provided slightly lower β2M RR, but the value was still higher than 75%; showed similar κFLC RR, IS RR, and URR; and yielded significantly higher RR values of α1M (p < 0.001) and λFLC (p < 0.001). Despite higher albumin loss in HD + MCO, the serum albumin levels at the end of the study were comparable between both groups. Conclusion: Expanded HD (HD + MCO) provided similar effectiveness in removing various uremic toxins and could exhibit greater removal of large middle-molecule uremic toxins, such as α1M and λFLC. Expanded HD can be used as an effective alternative option for mixed-dilution olHDF.
A novel autonomous remote system applied in agriculture using transmission control protocol
Authors: Deroussi Anass , Ait Madi Abdessalam , Alihamidi Imam , Charaf Lalla Amina , Saber Mohammed , Erraoui Anass , Addaim Adnane
Published: March 2022

An internet of things (IoT) irrigation system is challenged by several issues, such as cost, energy consumption, and data storage. This paper proposes a novel energy-efficient, cost-effective IoT system called "NewAgriCom" to monitor agricultural field water flow. NewAgriCom works with an embedded energy harvesting system, is an autonomous remote supervisory control and data acquisition (SCADA) based on a general packet radio service (GPRS) cellular network that effectively communicates irrigation field data to the Node.js server using SIM808 EVBV3.2 modem. In javascript object notation (JSON) format, data is transmitted over the hypertext transfer protocol (HTTP) protocol to the MySQL database. Then data are transferred to the proposed IoT platform, which gives us a hand to control actuators, visualise, store and download the data. NewAgriCom can significantly reduce water consumption. It can set a schedule to control water automatically at specific times in various modes, including normal, light, and deep sleep modes. It regularly provides the location, time, signal strength, and the state of actuators with the identifier of every device remotely on the IoT Platform.
 
COVID-19 paediatric cavity telecare system: a novel chain key generation and encryption scheme
Authors: Dey Joydeep
Published: March 2022

In this unprecedented coronavirus crisis, telehealth had emerged as a substitute way of treatment. More specifically, paediatric children are at high risk of outside exposure now. Non critical children must be treated remotely through the tableware system. A key based secured online transmission of an intraoral image of the paediatric cavity has been proposed in this manuscript. A cavity is a dental disease occurring in children. It is mainly caused due to prolonged bacterial infections. Secured online transmission with respect to medical transactions is immensely required in telecare information systems (TIS). Data confidentiality factor is preserved with preference in this proposed technique. A parity based novel chain key (NCK) has been generated and diffused inside the intraoral paediatric cavity image. NCK generation scheme is so highly robust that it gives different combinations after each bit altering. Initial seeds are kept at the dentist and patients, to resist myriad attacks inside the wireless channel, especially during this COVID-19 period. Histogram, floating frequency, and autocorrelation were obtained with accuracy using the proposed technique. Effects were observed by flipping simultaneous bits of the initial key and results were highly acceptable. The time for the proposed key generation has been found to be 514.61 ms. The total cryptographic time has been noted as 3.5983 ms in this technique.
Flexibilização legislativa para a certificação de hospitais sem fins lucrativos no Brasil
Authors: Zanatta Carolina Lopes , Scheffer Mário César
Published: March 2022

Para as entidades beneficentes de assistência social que prestam serviços ao Sistema Único de Saúde, a Constituição Federal de 1988 previu a concessão de imunidade tributária, desde que atendidos os requisitos previstos em lei. Ocorre que há uma primeira dificuldade em estabelecer os conceitos de entidade filantrópica e entidade beneficente de assistência social, bem como as diferenças entre eles. O objetivo deste trabalho foi realizar uma revisão e uma reflexão sobre a diferença doutrinária entre os conceitos de filantropia e beneficência social,  discutir o processo histórico de certificação dos hospitais sem fins lucrativos que prestam serviços ao Sistema Único de Saúde para obtenção de imunidade tributária e identificar as consequências disso para a seguridade social (previdência, saúde e assistência social) no Brasil. Esta reflexão se faz de suma importância, principalmente em momentos de escassez de recursos financeiros em que há tentativas de fragilizar o sistema de seguridade social do país. A Constituição Federal de 1988 adotou o termo “entidade beneficente de assistência social” para a concessão de imunidade tributária, conceito que se distingue do de filantropia por envolver três características essenciais da assistência social: serviços de natureza essencial, gratuidade e acesso generalizado a quem necessita. Essa ampliação de conceito e as flexibilizações legislativas ocorridas ao longo dos anos para permitir a concessão de certificado – e, consequentemente, a obtenção de imunidade tributária – prejudicam a arrecadação de recursos para a seguridade social e podem ocasionar desvantagens para o Sistema Único de Saúde.