bluuebunny/crossref_metadata_2025 huggingface dataset:
MicroRNA-4735-3p Facilitates Ferroptosis in Clear Cell Renal Cell Carcinoma by Targeting SLC40A1
Authors: Zhu Cairong , Song Zhiquan , Chen Zhen , Lin Tianqi , Lin Haili , Xu Zhenqiang , Ai Fen , Zheng Shijiao
Published: May 2022

Objective. Clear cell renal cell carcinoma (ccRCC) is the major histopathological subtype of renal cancer, and ferroptosis is implicated in the pathogenesis of ccRCC. The present study was aimed at investigating the role and underlying mechanisms of microRNA-4735-3p (miR-4735-3p) in ccRCC. Methods. Human ccRCC cell lines were transfected with the miR-4735-3p mimic or inhibitor to manipulate the expression of miR-4735-3p. Cell proliferation, colony formation, cell migration, cell invasion, cell death, oxidative stress, lipid peroxidation, and iron metabolism were determined. To validate the necessity of solute carrier family 40 member 1 (SLC40A1), human ccRCC cell lines were overexpressed with SLC40A1 using adenoviral vectors. Results. miR-4735-3p expression was reduced in human ccRCC tissues and cell lines but elevated upon ferroptotic stimulation. The miR-4735-3p mimic increased, while the miR-4735-3p inhibitor decreased oxidative stress, lipid peroxidation, iron overload, and ferroptosis of human ccRCC cell lines. Mechanistic studies identified SLC40A1 as a direct target of miR-4735-3p, and SLC40A1 overexpression significantly attenuated iron overload and ferroptosis in the miR-4735-3p mimic-treated human ccRCC cell lines. Conclusion. miR-4735-3p facilitates ferroptosis and tumor suppression in ccRCC by targeting SLC40A1.
Comparative Study of Different Controllers for Levitating Ferromagnetic Material
Authors: Deepa T. , Subbulekshmi D. , Lakshmi P. , Maheedhar Marabathina , Kishore E. , Vinodharanai M. , Chockalingam T.
Published: May 2022

The purpose of the analysis is to levitate and stabilize a spherical ball of magnetic levitation system at the desired position using various controllers and determine the one which gives better performance. The ball which is used to levitate is a ferromagnetic material such as stainless steel. This study talks about the proportional derivative controller, proportional integral derivative (PID) controller, and linear quadratic regulator (LQR) controller in place of a physical system. The transient response of the magnetic levitation system can be modified for desirable results due to the implementation of the controller. Simulation and experimental methods are used to verify the results. Both the techniques have been made to stabilize the ball position in the desired position. PID and LQR are designed to achieve the ball position to the desired level, and it is observed that the LQR controller gives the best result.
Jinlida Granules Reduce Obesity in db/db Mice by Activating Beige Adipocytes
Authors: Zhou Hong-ru , Wang Tong-xing , Hao Yuan-yuan , Hou Yun-long , Wei Cong , Yao Bing , Wu Xuan , Huang Dan , Zhang Hui , Wu Yi-ling
Published: May 2022

Recent studies indicate existence of beige adipocytes in adults. Upon activation, beige adipocytes burn energy for thermogenesis and contribute to regulation of energy balance. In this study, we have analyzed whether Jinlida granules (JLD) could activate beige adipocytes. JLD suspended in 0.5% carboxymethyl cellulose (CMC) was gavage fed to db/db mice at a daily dose of 3.8 g/kg. After 10 weeks, body weight, biochemical, and histological analyses were performed. In situ hybridization, immunofluorescence, and western blotting were conducted to test beige adipocyte activation in mice. X9 cells were induced with induction medium and maintenance medium containing 400 μg/mL of JLD. After completion of induction, cells were analyzed by Nile red staining, time polymerase chain reaction (PCR), western blotting, and immunofluorescence to understand the effect of JLD on the activation of beige adipocytes. A molecular docking method was used to preliminarily identify compounds in JLD, which hold the potential activation effect on uncoupling protein 1 (UCP1). JLD treatment significantly improved obesity in db/db mice. Biochemical results showed that JLD reduced blood glucose (GLU), triglyceride (TG), and low‐density lipoprotein cholesterol (LDL) levels as well as liver aspartate aminotransferase (AST) and alanine aminotransferase (ALT) levels in mice. Hematoxylin and eosin staining (H&E) showed that JLD reduced hepatocyte ballooning changes in the liver. Immunofluorescence showed that JLD increased the expression of the thermogenic protein, UCP1, in the beige adipose tissue of mice. JLD also increased the expression of UCP1 and inhibited the expression of miR‐27a in X9 cells. Molecular docking results showed that epmedin B, epmedin C, icariin, puerarin, and salvianolic acid B had potential activation effects on UCP1. The results suggest that JLD may activate beige adipocytes by inhibiting miR‐27a expression, thereby promoting thermogenesis in beige adipocytes. This study provides a new pharmacological basis for the clinical use of JLD.
Modelling of Modulus of Elasticity of Low-Calcium-Based Geopolymer Concrete Using Regression Analysis
Authors: Khalaf Ali A. , Kopecskó Katalin
Published: May 2022

Despite the unremitting efforts to model the modulus of elasticity of low-calcium-based geopolymer concrete, the state-of-the-art models need much improvement to reduce the error signals and increase the reliability. This study represents a comprehensive regression analysis to model the modulus of elasticity of low-calcium-based geopolymer concrete in terms of its compressive strength. The proposed model’s assumptions are based on taking into account the chemical composition and compressive strength class and considering the normal density of concrete. The modelling is based on 67 different mix-design samples collected from peer-reviewed literature, which are divided into two groups. The first group consists of 59 samples that are used to construct the proposed model, while the second group consists of 8 samples that are used to test the validity of the proposed model. The analysis showed that the proposed model gives the root mean squared error value (RMSE) of 3.122 GPa and the mean absolute percentage error value (MAPE) of 15.0%. Therefore, the proposed model gives 41% and 52.2% reductions in RMSE and MAPE, respectively, from the state-of-the-art model in the literature. Furthermore, other statistical parameters to evaluate the goodness of fitness of the proposed model have been considered, such as the relative root mean squared error (RRMSE) (15.5%), the coefficient of determination (R-squared) (0.773), and the coefficient of correlation (R) (0.88); all of which indicated that the goodness of fitness is good and the proposed model has a high correlation to the actual values. Applying the proposed model in future applications will help reduce the time and cost of geopolymer production, as the proposed model has significantly reduced the error signals.
Design and Implementation of a Data Sharing Model for Improving Blockchain Technology
Authors: Wang Xiaowei
Published: May 2022

With the continuous development of technology, the advancement of various data sharing technologies has gradually penetrated into various fields. Thus, data sharing and security are vital to realizing the value of the data. Nevertheless, the original data sharing model is not easily monitored for traces of electronic data use. In addition, the reluctance of data providers to share their data is also a problem. In order to address the issues of traditional centralized data sharing and management in terms of security and control, this research proposes the data sharing model based on blockchain technology, thereby enabling secure access to data. Furthermore, this study evaluates the model in terms of functionality and security. The results show that the blockchain-based data sharing model designed in this paper has great feasibility, security, controllability, and efficiency.
Is Femoral Nerve Block Superior to Fascia Iliac Block in Hip Surgery? Meta‐Analysis of Randomized Controlled Trials
Authors: Li Xiao-dan , Han Chao , Yu Wen-li
Published: May 2022

Background. Femoral nerve block (FNB) and fascia iliac compartment block (FICB) are alternative methods of pain relief during hip surgery. Nevertheless, the effectiveness and safety of FNB compared with FICB are yet to be fully determined. Methods. Electronic databases were systematically searched. Only randomized controlled trials (RCTs) on hip surgery were included. Postoperatively, the pain scores at different time points, narcotic requirements in 24 h, mean arterial pressure, spinal anesthesia (SA) time, patient satisfaction, and adverse effect rates between the two groups were extracted throughout the study. Results. Fourteen RCTs including 1179 patients were included. Compared to the FICB, FNB decreased the VAS scores postoperatively at 24 h at rest (P < 0.05) and the incidence rate of some side effects (nausea, vomiting, and sedation) (P < 0.05). However, compared to the FICB, no significant difference was found in the FNB regarding the VAS scores postoperatively at any of the other time points (2 min, 20 min, 2 h, 24 h at movement, 48 h at rest, and 48 h at movement). Patients in both groups had similar narcotic needs after 24 h, mean arterial pressure, SA time, and patient satisfaction (P > 0.05). Conclusions. FNB has more advantages in reducing VAS scores postoperatively at 24 h at rest and the odds of some adverse effects. A better quality RCT is needed to properly compare FNB with FICB.
Therapeutic Potential of Polyscias fruticosa (L.) Harms Leaf Extract for Parkinson’s Disease Treatment by Drosophila melanogaster Model
Authors: Ly Hai Trieu , Nguyen Thi Thu Huong , Le Van Minh , Lam Bich Thao , Mai Thi Thu Trinh , Dang Thi Phuong Thao
Published: May 2022

Parkinson’s disease (PD) is characterized by progressive locomotive defects and loss of dopaminergic neurons. Polyscias fruticosa leaves are used by Vietnamese as herbal medicines to support the treatment of some diseases related to neurodegeneration such as Parkinson’s and Alzheimer’s diseases. However, recent scientific data have not provided sufficient evidence for the use of P. fruticosa leaves to treat PD or decelerate PD progression. In the present study, the capacity of P. fruticosa leaf extract for PD treatment on the dietary supplementation was investigated using dUCH-knockdown Drosophila model. The results indicated that P. fruticosa leaf extract decelerated dopaminergic neuron degeneration induced by dUCH knockdown in not only the larval stage but also the adult stage, which might result in the amelioration in locomotor ability of dUCH-knockdown larvae and flies. Furthermore, antioxidant activities and some key phytochemicals such as saponins, polyphenols, and flavonoids that might contribute to the effects of the P. fruticosa leaf extract were identified.
Modelling and Simulation of Fluid Flow through a Circular Cylinder with High Reynolds Number: A COMSOL Multiphysics Study
Authors: Memon Abid. A. , Memon M. Asif , Bhatti Kaleemullah , Jacob Kavikumar , Sitthiwirattham Thanin , Promsakon Chanon , khan Ilyas
Published: May 2022

In this study, we intend to investigate the steady‐state and laminar flow of a viscous fluid through a circular cylinder fixed between two parallel plates keeping the aspect ratio of 1 : 5 from cylinder radius to height of the channel. The two‐dimensional, incompressible fluid flow problem has been simulated using COMSOL Multiphysics 5.4 which implements finite element’s procedure. The flow pattern will be investigated by using the Reynolds number from 100 to 1000. The reattachment length formed at the back of the cylinder and drag force when the fluid comes to strike with the front surface of the cylinder is expressed in terms of Reynolds numbers. We propose to calculate the velocity and the pressure before and after the cylinder. For this purpose, two‐line graphs before and after the cylinder will be drawn to check the impact of cylinder on both velocity and pressure. It was found that the percentage change in the velocity as well as pressure before to after the cylinder is changing their behaviours at Re = 700. The study is important because the empirical equations between the vortex’s lengths formed along the cylinder using the linear regression process obtained in this study may be used for future implementation.
Inhibitory Effects of Mongolian Medicine Yihe-Tang on Continuous Darkness Induced Liver Steatosis in Zebrafish
Authors: Sa Rigaiqiqige , Feng Chi , Bai Hongxia , Yin Xiaoyu , Song Lei , Hu Xiaodong , Xu Rui , Li Xinshan , Dong Wu , Yang Jingfeng
Published: May 2022

The constant dark induction (DD) causes lipid degeneration and nonalcoholic fatty liver disease (NAFLD) in zebrafish, which might be closely related to the imbalance of gut microbiota and require in-depth study. In this study, a total of 144 zebrafish were divided into four groups, including the control group, Yihe-Tang group, constant dark group, and constant dark + Yihe-Tang group, and were treated with constant darkness (except control and Yihe-Tang groups) for 21 days. The bodyweights of zebrafish were recorded after 8 d, 15 d, and 22 d. The sequencing analysis of gut microbiota, detection of liver histopathological changes, and comparison of lipid metabolism-related gene expression levels were performed on the 22nd day of the experiment. The results showed that the Yihe-Tang could inhibit the constant dark-induced increase in zebrafish weight and liver steatosis. As compared to the control group, the dark treatment could alter the composition of gut microbiota in zebrafish, increase the relative abundance of harmful bacteria, and decrease the Cetobacterium and Bacteroides to Firmicutes ratio in the intestines. The abundance of Proteobacteria in the constant dark + Yihe-Tang group was close to that in the control group and that of Fusobacteria and Cetobacterium increased, especially the Cetobacterium, which increased significantly. The constant dark treatment caused an abnormal expression of liver lipid-related genes, inhibited lipid metabolism, and promoted fat accumulation. However, the Yihe-Tang could restore these changes to the level of the control group. This study indicated that Yihe-Tang could restore the constant dark-induced liver lipid degeneration. We hypothesized that Cetobacterium could significantly inhibit steatosis.
Antihypertensive and Vasorelaxant Effects of Citrus aurantifolia Linn. Fruit: Proposed Mechanisms
Authors: Bukhari Syed Nasir Abbas , Alamgeer  , Saeed Sumera , Asim Mulazim Hussain , Irfan Hafiz Muhammad , Ejaz Hasan , Elsherif Mervat A. , Junaid Kashaf
Published: May 2022

Background. Citrus aurantifolia Linn. fruit, a natural dietary item, has long been used traditionally to treat hypertension in Pakistan. The current research work aims to explore the effect on blood pressure and its mechanisms. Methods. The aqueous methanol extract of plant fruit was used to evaluate hypotensive/antihypertensive, vasorelaxation, and safety profiles. Moreover, the in vitro inhibitory effect of AMECA on phosphodiesterase was also evaluated. Results. In hypotensive studies, extracts of Citrus aurantifolia fruit exhibited a concentration-dependent reduction in SBP, DBP, MAP, and heart rate. A similar effect has been observed on anesthetized rats, but the effects exerted by the extract were not altered significantly in the presence of L-NAME, atropine, captopril, and propranolol. Moreover, in coronary arteries, the extract significantly potentiated relaxations induced by cGMP- and cAMP-dependent relaxing agonists. When exposed to PDEs, the extract concentration dependently subdued cGMP-hydrolyzing activity of different PDEs with IC50 values of 40–130 μg/mL. Conclusion. It is conceivable that extracts obtained from Citrus aurantifolia fruit produced hypotensive and antihypertensive effects in rats. The extract elicited endothelium-independent vasorelaxation, possibly by acting directly on smooth muscles of the coronary artery and by increasing cGMP and cAMP via nonselective inhibition of vascular PDEs.
Synchronization Problems of Fuzzy Competitive Neural Networks
Authors: Zhang Lingping , Duan Feng , Du Bo
Published: May 2022

This paper is devoted to investigating the fixed-time and finite-time synchronization for fuzzy competitive neural networks with discontinuous activation functions. We introduce Filippov solution for overcoming the nonexistence of classical solutions of discontinuous system. Using the fixed-time synchronization theory, inequality technique, we obtain simple robust fixed-time synchronization conditions. Designing proper feedback controllers is a key step for the implementation of synchronization. Furthermore, based on the fixed-time robust synchronization, we design a switching adaptive controller and obtain the finite-time synchronization. It is noted that the settling time is independent on the initial value in the fixed-time robust synchronization. Hence, under the conditions of this paper, the considered system has better stability and feasibility. Finally, the theoretical results of this paper are attested to be indeed feasible in terms of a numerical example.
Energy-Efficient Resource Allocation for Backscatter-Assisted Wireless Powered Communication Networks in Twin Workshop
Authors: Li Yujian , Zhang Xinxing
Published: May 2022

The problem of energy shortage in sensor nodes caused by frequent data interactions is one of the major constraints on the development of twin workshops. A backscatter-assisted wireless powered communication network (BAWPCN) has been deemed a potential solution for addressing the problem of energy shortage in twin workshops. How to effectively ensure the link energy efficiency (EE) while satisfying the quality of servers for each user has been of high interest, while it has not been well studied in previous works. Inspired by this, in this paper, we propose a resource allocation scheme based on the max–min criterion, considering the user quality of service and energy-causality constraints. The optimization problem is formulated as a mixed-integer nonconvex fractional planning problem which is aimed at maximizing the minimum EE of each link. The generalized fractional theory is used to transform the nonconvex fractional planning problem into an equivalent mixed-integer nonconvex subtraction optimization problem, and then, the mixed-integer nonconvex subtractive optimization problem is transformed into an equivalent nonconvex optimization problem by introducing relaxation variables to eliminate the integer programming problem arising from the maximum-minimum function. Based on this, the block coordinate descent method is used to decompose the transformation problem into two convex subproblems, and an iterative algorithm is proposed to solve the transformation problem. Simulation results verify the fast convergence of the proposed iterative algorithm and show that the proposed resource allocation method can effectively guarantee the fairness of the energy efficiency of the system in twin workshops.
Identification and Evaluation of Urban Rail Transit Operation Risk Factors Based on Entropy-AHP Hybrid Constrained DEA Method
Authors: He Jingshi , Fan Xiangjun , Wu Li-Chun
Published: May 2022

The whole society is increasingly aware of the importance of urban rail transit (URT) safety and risk management. In order to correctly identify and evaluate the risk factors of URT operation and then classify and take differential measures to deal with the risk factors, the risk sources of URT accidents were analyzed by fault tree analysis and the URT operation risk evaluation index system concerning 8 categories and 40 risk sources were constructed. The DEA (data envelopment analysis) method with entropy-AHP hybrid constraint was established, and the probability and consequences of URT operation risk were taken as decision variables to evaluate and rank various risk factors. The results show that decision-making units (DMU) 1and 2， namely, vehicle system failure and signal communication system failure, are at the largest Pareto risk units, the probability of risk can be reduced by 50.08% and 41.7%, and the risk consequences can be reduced by 35.57% and 46.83%, respectively. Staff factors and environment and management factors are the other two units closest to the maximum risk surface. A risk factor distribution matrix was established, and 40 risk factors are divided into risk factors, leverage risk factors, conventional risk factors, and influential risk factors, which provide a basis for the classification and policy of rail transit risk management.
Research on the Contribution of Electronic Commerce to Economic Development: An Empirical Analysis Based on Artificial Neural Network
Authors: Feng Zhitan
Published: May 2022

Data collinearity, nonlinearity, and even the data itself helped us solve regression of blind areas throughout this study. When it comes to China’s economic change in the new normal era, high-quality development will be an inescapable trend. By capitalizing on the industrial advantages of speed, flexibility, and convenience, e-commerce has given new momentum to the change of industrial structure and created prospects for the times’ high-quality economic growth. Based on a comparison of the changes in provincial panel data from 2013 to 2020, the following conclusion may be drawn: following per capita education and per capita online sales weight in ANN analysis of economic growth is e-contribution commerce’s to economic growth followed by e-commerce volume, express volume, and domain name; other factors are less important.
Monocyte-to-Lymphocyte Ratio Was an Independent Factor of the Severity of Spinal Tuberculosis
Authors: Chen Liyi , Liu Chong , Liang Tuo , Ye Zhen , Huang Shengsheng , Chen Jiarui , Sun Xuhua , Yi Ming , Jiang Jie , Chen Tianyou , Li Hao , Chen Wuhua , Guo Hao , Yao Yuanlin , Liao Shian , Yu Chaojie , Wu Shaofeng , Fan Binguang , Gan Zhaoping , Zhan Xinli
Published: May 2022

Purpose. The purpose was to explore the relationship between monocyte-to-lymphocyte ratio (MLR) and the severity of spinal tuberculosis. Methods. A total of 1,000 clinical cases were collected, including 496 cases of spinal tuberculosis and 504 cases of nonspinal tuberculosis. Laboratory blood results were collected, including C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), white blood cells (WBC), hemoglobin (HGB), platelets (PLT), neutrophil count, percentage of neutrophils, lymphocyte count, percentage of lymphocytes, monocyte count, percentage of monocytes, MLR, platelets -to- monocyte ratio (PMR), platelets -to- lymphocyte ratio (PLR), neutrophil -to- lymphocyte ratio (NLR), and platelets -to- neutrophil ratio (PNR). The statistical parameters analyzed by the Least Absolute Shrinkage and Selection Operator (LASSO) and receiver-operating characteristic (ROC) curves were used to construct the nomogram. The nomogram was assessed by C-index, calibration curve, ROC curve, and decision curve analysis (DCA) curve. Results. The C-index of the nomogram in the training set and external validation set was 0.801 and 0.861, respectively. Similarly, AUC was 0.801 in the former and 0.861 in the latter. The net benefit of the former nomogram ranged from 0.1 to 0.95 and 0.02 to 0.99 in the latter nomogram. Furthermore, there was a correlation between MLR and the severity of spinal tuberculosis. Conclusion. MLR was an independent factor in the diagnosis of spinal tuberculosis and was associated with the severity of spinal tuberculosis. Additionally, MLR may be a predictor of active spinal tuberculosis.
Understanding Physical Activity and Exercise Behavior in China University Students: An Application of Theories of the Flow and Planned Behavior
Authors: Feng Haitao , Hwang Jin , Hou Li
Published: May 2022

Objectives. The purpose of this study was to examine a extended model of the theory of planned behavior (TPB) model by adding the variables of the flow theory and to investigate Chinese university students’ exercise behavior and its influence factors. Methods. The hypothesized model was validated through testing three competing models using a sample collected from 248 Chinese university students involving 165 males and 83 females. Results. The three competitive models fitted well and predicted exercise behavior significantly. Among them, the enjoyment + TPB model is the optimal model. Conclusions. Enjoyment and concentration can all predicting exercise behavior directly or indirectly. Enjoyment is stronger than concentration in predicting TPB constructs and exercise behavior, and it is a more important predictor than concentration in the field of exercise behavior research. Values. Research provides insights to better understand the exercise behavior of Chinese university students as well as useful information for designing exercise interventions and developing university students’ education and training.
Interference Mitigation Based on Low Complexity Subspace Tracking Method for Vehicle Positioning
Authors: Zhang Ping , Wu Qiang , Jing Binbin
Published: May 2022

Advanced driver assistance systems and automatic driving have drawn lots of attentions due to user’s multiapplication needs. Among different technologies, the integration of Inertial Navigation System (INS) and Global Navigation Satellite System (GNSS) is a key technique with the decreasing costs of Inertial Measurement Unit (IMU) and the increasing deployment of GNSS for navigation applications. Although the integration may have immune ability to interference in a certain extent, interference suppression strategy applied on the integration system can greatly improve the performance. A complete framework including interference monitor, detection, and mitigation is provided jointly using subspace tracking method and Kalman filter measurements innovation of INS and GNSS. The proposed monitor is simple, efficient, and can decide when to start the interference mitigation procedure, which can reduce the computation complexity significantly; Subspace‐based method is introduced to track the interference basis matrix that can be feed to RootMUSIC to detect the frequency of interference, followed by the interference mitigation with a notch filter. The proposed framework has superior performance than the well‐known time‐frequency algorithm, such as short‐time Fourier transform (STFT) and smoothed pseudo Wigner‐Ville distribution (SPWVD), and can improve the performance of INS/GNSS system in the presence of interference with simulation verification.
A GNN-Based Variable Partition Framework for DCOPs
Authors: Chen Chun , Ning Li , Zhou Rong , Zhang Yong , Zhou Chan , Feng Shengzhong
Published: May 2022

Many problems of the Internet of Things (IoT), such as radio frequency allocation and sensor network, can be regarded as constraint optimal problems (COPs), which can be formulated as graphical representations. The scale of graph is large, which is hard to implement, and the information shared by all the variables is unsafe for all the variables running in an agent. On the other hand, supercomputers are playing a significant and growing role in various fields of large-scale processing tasks. When countering this scene, the supercomputers can accelerate to complete the task according to the distributed solution, where they divide the task into sub-tasks and each sub-task is running on an agent, such as a process or a computation node. However, finding an optimal distributed solution is difficult to minimize the completion time with the optimal computing resources. Putting the task on too many agents not only wastes resources but also increases the risk of attacks. Conversely, fewer agents may take too much time, which is unacceptable for users. Determining the number of agents needs to strike a balance between communication and computation. In this paper, we propose a new framework GVPNN for predicting the optimal numbers of agents for COPs and further provide the allocation from variable to agent. Experimental result shows the framework can learn the structure of the corresponding graphical representation well, and the 1-distant accuracy rate and the top 3 accuracy rate of GVPNN reach 74% and 70%, respectively.
Biomimetic Design and Biocompatibility of Biomimetic Calcium Carbonate Nanocomposites for Skeletal Muscle Injury Repair
Authors: Han Yan
Published: May 2022

As an important part of the human body, skeletal muscle is easily damaged in the process of exercise. The purpose of this study is to investigate the controllable construction and biocompatibility of biomimetic calcium carbonate nanocomposites in exercise skeletal muscle repair. In this study, adult healthy mice were selected as the research objects. First, the mice were anesthetized with 2.5% pentobarbital sodium. Then, the mice were fixed and hit with steel balls on the middle part of the gastrocnemius muscle abdomen to establish a skeletal muscle contusion model. The mice were killed by cervical dislocation under anesthesia. The injured gastrocnemius muscles were quickly removed to prepare the cell suspension. 0.8600 g chitosan was weighed and dissolved in 200 ml deionized water. Then, 0.0660 g of calcium chloride dihydrate was added and stirred to dissolve to prepare chitosan calcium carbonate composite. The calcium carbonate composite material with a length of 8.0 cm is cut into a square sheet of stainless steel. The stainless steel plate was sterilized and then placed in a 12 culture plate to dilute the full cells in the culture bottle. The cells were seeded in 12 well culture plates, and 100 μL cells and 600 μL medium were added to each well. The samples were cultured in the incubator (there were three control holes in each group for SEM test, three control holes for fluorescence measurement, and six control holes for MTT measurement). The plates were taken out and placed in a new 24 plate. 1000 μL medium was added. Then. 100 μL MTT solution was added into each well. The biocompatibility test was conducted for 4 h. The GSH PX level in the chitosan calcium carbonate composite group was lower than that in the natural recovery group (P < 0.01). The results showed that chitosan calcium carbonate composite could promote the growth of skeletal muscle cells.
Deformation Monitoring and Spatiotemporal Evolution of Mining Area with Unmanned Aerial Vehicle and D-InSAR Technology
Authors: Tan Hao , Yu Xuexiang , Zhu Mingfei , Guo Zhongchen , Chen Hengzhi
Published: May 2022

The extraction of underground mineral sources has a significant negative impact on the local environment, results in land surface subsidence. As far as subsidence monitoring technology is concerned, leveling is the most accurate. However, leveling can only obtain discrete point data but not the whole area information of the subsidence basin. In this study, Differential Interferometric Synthetic Aperture Radar (D-InSAR) combined with Unmanned Aerial Vehicle (UAV) technology is used to study the subsidence characteristics of the whole working panel. In this analysis, the Huainan mining area is tested as a research area; measured data are compared to the elevation accuracy of the Digital Surface Model (DSM) data, which can be considered for the subsequent works of the mining area. Based on the subsidence affected area, the ground object-type information is recorded to provide basic information for the ecological restoration work after mining so that the data before and after mining can be obtained synchronously. Finally, the differential interference results and Digital Orthophoto Map (DOM) data are combined to assess the spatiotemporal evolution of working panel subsidence and its influence on surface features. The main novelty of the proposed work is combining UAV and D-InSAR to get more accurate analysis of mining subsidence. It can be done using the proposed method.
Block Cipher’s Substitution Box Generation Based on Natural Randomness in Underwater Acoustics and Knight’s Tour Chain
Authors: Khan Muhammad Fahad , Saleem Khalid , Shah Tariq , Hazzazi Mohammad Mazyad , Bahkali Ismail , Shukla Piyush Kumar
Published: May 2022

The protection of confidential information is a global issue, and block encryption algorithms are the most reliable option for securing data. The famous information theorist, Claude Shannon, has given two desirable characteristics that should exist in a strong cipher which are substitution and permutation in their fundamental research on “Communication Theory of Secrecy Systems.” block ciphers strictly follow the substitution and permutation principle in an iterative manner to generate a ciphertext. The actual strength of the block ciphers against several attacks is entirely based on its substitution characteristic, which is gained by using the substitution box (S-box). In the current literature, algebraic structure-based and chaos-based techniques are highly used for the construction of S-boxes because both these techniques have favourable features for S-box construction but also various attacks of these techniques have been identified including SAT solver, linear and differential attacks, Gröbner-based attacks, XSL attacks, interpolation attacks, XL-based attacks, finite precision effect, chaotic systems degradation, predictability, weak randomness, chaotic discontinuity, and limited control parameters. The main objective of this research is to design a novel technique for the dynamic generation of S-boxes that are safe against the cryptanalysis techniques of algebraic structure-based and chaos-based approaches. True randomness has been universally recognized as the ideal method for cipher primitives design because true random numbers are unpredictable, irreversible, and unreproducible. The biggest challenge we faced during this research was how can we generate the true random numbers and how can true random numbers utilized for strengthening the S-box construction technique. The basic concept of the proposed technique is the extraction of true random bits from underwater acoustic waves and to design a novel technique for the dynamic generation of S-boxes using the chain of knight’s tour. Rather than algebraic structure- and chaos-based techniques, our proposed technique depends on inevitable high-quality randomness which exists in underwater acoustics waves. The proposed method satisfies all standard evaluation tests of S-boxes construction and true random numbers generation. Two million bits have been analyzed using the NIST randomness test suite, and the results show that underwater sound waves are an impeccable entropy source for true randomness. Additionally, our dynamically generated S-boxes have better or equal strength, over the latest published S-boxes (2020 to 2021). According to our knowledge first time, this type of research has been conducted, in which natural randomness of underwater acoustic waves has been used for the construction of block cipher’s substitution box.
Characterization and Evaluation of Bambara Groundnut (Vigna subterranea (L.) Verdc.) for Yield and Related Traits in Asosa Zone, Northwestern Ethiopia
Authors: Paulos Mesay , Loha Gobeze , Kassa Mesfin
Published: May 2022

Bambara groundnut, a future emerging legume, is usually known as a poor man’s crop or as “women’s crop” and newly noted as crop for new millennium. In this context, a field experiment was conducted during 2019/20 cropping season at Sonka testing site of Asosa zone in northwestern Ethiopia with objective to estimate the variability of Bambara groundnut genotypes with respect to important quantitative and qualitative traits. Treatments consisted in 20 accessions collected from five distracts of Benishangul Gumuz province in northwestern Ethiopia. The treatments were laid out in a randomized block design with three replications. All the qualitative characteristics recorded for genotypes showed different modalities and frequencies at vegetative stage with 70.12% of the fully expanded leaflet colour, 74.26% oval terminal leaflet shape, 76.24% petiole green colour, 78.22% stem green colour, 88.27% sparse hair on their stems, 70.41% spreading types, 81.33% rounded base with a point at the top, 90.11% yellowish brown pods at harvest, and 90.06% oval shaped seeds. With respect to quantitative traits, genotypes AMN/04/013, AMN/04/014, AMN/04/015, AMN/04/019, and AMN/04/020 gave relatively higher grain yield (>2000 kg/ha) with the highest grain yield recorded for genotype AMN/04/016. Thus, these genotypes showed relatively better adaptation at tested location. Higher correlation values were observed for days to maturity, plant height, number of stems per plant, pods per plant, seed per pod, and HSW, indicating that these traits are very important to be used in selection for the crop improvement. Agronomic and morphological evaluations have provided more accurate estimation of genetic diversity, the raw material of plant breeding. In general, this study enabled to determine how the influential traits direct to improve Bambara groundnut genotypes.
Enterprise Financing Risk Analysis and Internal Accounting Management Based on BP Neural Network Model
Authors: Liao Haojie , Yue Huabo , Lin Yibin , Li Dong , Zhang Lei
Published: May 2022

A BP neural network-based model is proposed to study corporate financial risk analysis and internal accounting management. Using MATLAB software and the BP neural network model, it is possible to obtain enterprise financing risk situations over a period by simulating and predicting enterprise financing risks by creating an early warning model for enterprise financing risks. Finally, from the point of view of the company's internal and external operations, the company's financial risk prevention measures and proposals are proposed to improve the financing efficiency of the companies and to prevent financial risks. This study predicts the financing risk of companies listed on the Mongolian Stock Exchange and analyzes the causes of the risk status. According to the test results, the learning speeds for successive substitutions are as follows: 0.005, 0.01, 0.02, 0.03, and 0.04. Finally, it was found that the error was minimal and the stability was best when the learning speed was exactly 0.01. The error is 0.0031011, and the step size is 157, which is only slightly lower than the target error value, which indicates that the learning speed is good. In addition, the novelty of this study is the use of the BP neural network model to conduct an early warning study of corporate financial risks. The BP neural network assessment model for corporate lending risk in this document is highly accurate. In addition to providing theoretical insights to researchers, it can be a good tool for banks to realistically assess the credit risk of SME supply chain financing.
A Modified ResNeXt for Android Malware Identification and Classification
Authors: Albahar Marwan Ali , ElSayed Mahmoud Said , Jurcut Anca
Published: May 2022

It is critical to successfully identify, mitigate, and fight against Android malware assaults, since Android malware has long been a significant threat to the security of Android applications. Identifying and categorizing dangerous applications into categories that are similar to one another are especially important in the development of a safe Android app ecosystem. The categorization of malware families may be used to improve the efficiency of the malware detection process as well as to systematically identify malicious trends. In this study, we proposed a modified ResNeXt model by embedding a new regularization technique to improve the classification task. In addition, we present a comprehensive evaluation of the Android malware classification and detection using our modified ResNeXt. The nonintuitive malware’s features are converted into fingerprint images in order to extract the rich information from the input data. In addition, we applied fine-tuned deep learning (DL) based on the convolutional neural network (CNN) on the visualized malware samples to automatically obtain the discriminatory features that separate normal from malicious data. Using DL techniques not only avoids the domain expert costs but also eliminates the frequent need for the feature engineering methods. Furthermore, we evaluated the effectiveness of the modified ResNeXt model in the classification process by testing a total of fifteen different combinations of the Android malware image sections on the Drebin dataset. In this study, we only use grayscale malware images from a modified ResNeXt to analyze the malware samples. The experimental results show that the modified ResNeXt successfully achieved an accuracy of 98.25% using Android certificates only. Furthermore, we undertook extensive trials on the dataset in order to confirm the efficacy of our methodology, and we compared our approach with several existing methods. Finally, this article reveals the evaluation of different models and a much more precise option for malware identification.
Film Effect Optimization by Deep Learning and Virtual Reality Technology in New Media Environment
Authors: Cui Linlin , Zhang Zhuoran , Wang Jiayi , Meng Zhu
Published: May 2022

Today, new media technology has widely penetrated art forms such as film and television, which has changed the way of visual expression in the new media environment. To better solve the problems of weak immersion, poor interaction, and low degree of simulation, the present work uses deep learning technology and virtual reality (VR) technology to optimize the film playing effect. Firstly, the optimized extremum median filter algorithm is used to optimize the “burr” phenomenon and a low compression ratio of the single video image. Secondly, the Generative Adversarial Network (GAN) in deep learning technology is used to enhance the data of the single video image. Finally, the decision tree algorithm and hierarchical clustering algorithm are used for the color enhancement of VR images. The experimental results show that the contrast of a single-frame image optimized by this system is 4.21, the entropy is 8.66, and the noise ratio is 145.1, which shows that this method can effectively adjust the contrast parameters to prevent the loss of details and reduce the dazzling intensity. The quality and diversity of the specific types of images generated by the proposed GAN are improved compared with the current mainstream GAN method with supervision, which is in line with the subjective evaluation results of human beings. The Frechet Inception Distance value is also significantly improved compared with Self-Attention Generative Adversarial Network. It shows that the sample generated by the proposed method has precise details and rich texture features. The proposed scheme provides a reference for optimizing the interactivity, immersion, and simulation of VR film.
Assistive Relief Tool for Early Childhood and Special Psychological Symptom Groups during the Pandemic: Clothing Design Based on the Virtual Contact Principle
Authors: Liu Yunjuan , Wang Yan , Liu Meiyan
Published: May 2022

During the COVID-19 pandemic, some special populations—groups of early childhood and people with autism, among others—faced more profound challenges than the common people. The lack of real physical contact such as embracing greatly affected the effectiveness of development, psychiatric treatment, and other processes for these populations. This study is aimed at developing clothing with appropriate contact pressure based on the contact comfort principle of psychology and providing a type of pressure clothing that can relieve the wearer’s tension by simulating hugging, alleviating the lack of physical contact for early childhood education and special education groups during the pandemic. First, the elementary requirements of clothing design are attained using a questionnaire survey and test method. The analysis revealed that clothing should fulfill the four requirements of pressure comfort, fabric softness, wearing and taking off comfort, and visual beauty. Second, we realized the performance requirements in the fabric and accessories, style design, structure design, and functional design. Finally, the product experience is proposed through a fitting, and the reasonable opinions were fed back to the product design to enhance the functionality of clothing. The research shows that clothing can simulate hugging and can ease the loneliness of the wearer. This study can be used as a good tool to assist during the pandemic for early childhood education and special psychological symptom groups, as well as a broader group of people living alone at home, to play an adjunctive treatment and loneliness relief functions.
Applicable Measuring Range of Two-Electrode Type Commercial Electrolytic Conductivity Meter for Accurate Determination of Electrolytic Conductivity
Authors: Hibino Yuya , Asakai Toshiaki , Suzuki Toshihiro , Ohata Masaki
Published: May 2022

Applicable measuring range of electrolytic conductivity (EC) for commercially available two-electrode type EC meter was examined. The measurement error caused by a gap in ECs between the measurement sample and the standard solution was also evaluated. Seven potassium chloride (KCl) solutions including certified reference materials (CRMs) manufactured by the National Metrology Institute of Japan (NMIJ) were measured, and the cell constants observed for commercial EC meters as well as the effect of electrode polarization were compared in detail under strict temperature control. The effect of electrode polarization can be sufficiently small if the frequency is properly selected. In the case of KCl standard solution with concentrations of 0.1 mol kg-1 (1 S m-1) or less, the obtained cell constants were almost identical to those of declared ones. However, in the case of KCl standard solution with concentrations of 0.5 mol kg-1 (5 S m-1) or more, the obtained cell constants showed 2-10% higher than those of declared ones. From these results, the calibration by standard solution with closer EC to the measurement solution is especially important if about 1% accuracy of measurement by commercial EC meter is required in higher EC range such as 5 S m-1 or more.
¡Precios, precios!
Authors: González Pablo
Published: May 2022

Desde hace un tiempo hasta la fecha, las encuestas de expectativas de consumidores, operadores financieros y empresas, los Informes de Política Monetaria emitidos por el Banco Central de Chile, los informes del Ministerio de Hacienda, los discursos de las autoridades de la República previas y de las que asumieron hace poco más de dos meses nos vienen repitiendo lamisma preocupación. La tasa de inflación en Chile está fuera de control y toda medida (ya sea fiscal, monetaria o que afecte a los mercados financieros locales) debe ser analizada profundamente antes de ver la luz para evitar este trauma que significa una economía con alta inflación.