bluuebunny/crossref_metadata_2025 huggingface dataset:
Kinetic energy of left ventricular blood flow across heart failure phenotypes and in subclinical diastolic dysfunction
Authors: Arvidsson Per M. , Nelsson Anders , Edlund Jonathan , Smith J. Gustav , Magnusson Martin , Jin Ning , Heiberg Einar , Carlsson Marcus , Steding-Ehrenborg Katarina , Arheden Håkan
Published: August 2022

Here we present the first study of left ventricular kinetic energy in individuals with subclinical diastolic dysfunction and in heart failure patients with preserved or impaired systolic function. Kinetic energy differs between groups in diastole, and reflects altered filling and emptying processes. Kinetic energy analysis should be considered in studies seeking to characterize myocardial energetics comprehensively.
Can abnormal chromatin folding cause high-penetrance cancer predisposition?
Authors: Schwartz Mathias
Published: August 2022

Sequencing cancer predisposing genes (CPGs) in evocative patients (i.e., patients with personal and family history of multiple/early-onset/unusual cancers) allows follow-up in their relatives to be adapted when a causative pathogenic variant is identified. Unfortunately, many evocative families remain unexplained. Part of this “missing heritability” could be due to CPG dysregulations caused by remote noncoding genomic alterations. Transcription levels are regulated through the ability of promoters to physically interact with their distant cis-regulatory elements. Three-dimensional chromatin contacts, mediated by a dynamic loop extrusion process, are uncovered by chromosome conformation capture (3C) and 3C-derived techniques, which have enabled the discovery of new pathological mechanisms in developmental diseases and cancers. High-penetrance cancer predisposition is caused by germline hereditary alterations otherwise found at the somatic level in sporadic cancers. Thus, data from both developmental diseases and cancers provide information about possible unknown cancer predisposition mechanisms. This mini-review aims to deduce from these data whether abnormal chromatin folding can cause high-penetrance cancer predisposition.
Calibration Approach for Variance Estimation of Small Domain
Authors: Ashutosh Ashutosh , Shahzad Usman , Ahmad Ishfaq , Ahmad Raza Muhammad , Benedict Troon J.
Published: August 2022

The population parameters are estimated using sample surveys. However, the current investigation’s goal is to estimate subpopulations parameters such as total through a calibration approach. The proposed estimator’s properties have been given under simple random sampling. In addition, the class of estimators for subpopulation total has been discussed. The proposed estimator has been evaluated theoretically and empirically in a comparative study. The results demonstrated that a high-level estimate outperforms a low-level estimate for subpopulation total using a calibration approach.
Ridge Regression Method and Bayesian Estimators under Composite LINEX Loss Function to Estimate the Shape Parameter in Lomax Distribution
Authors: Yassen Mansour F. , Al-Duais Fuad S. , Almazah Mohammed M. A.
Published: August 2022

In this paper, the Ridge Regression method is employed to estimate the shape parameter of the Lomax distribution (LD). In addition to that, the approaches of both classical and Bayesian are considered with several loss functions as a squared error (SELF), Linear Exponential (LLF), and Composite Linear Exponential (CLLF). As far as Bayesian estimators are concerned, informative and noninformative priors are used to estimate the shape parameter. To examine the performance of the Ridge Regression method, we compared it with classical estimators which included Maximum Likelihood, Ordinary Least Squares, Uniformly Minimum Variance Unbiased Estimator, and Median Method as well as Bayesian estimators. Monte Carlo simulation compares these estimators with respect to the Mean Square Error criteria (MSE’s). The result of the simulation mentioned that the Ridge Regression method is promising and can be used in a real environment. where it revealed better performance the than Ordinary Least Squares method for estimating shape parameter.
Feature Selection Based on Adaptive Particle Swarm Optimization with Leadership Learning
Authors: Ye Zhiwei , Xu Yi , He Qiyi , Wang Mingwei , Bai Wanfang , Xiao Hongwei
Published: August 2022

With the rapid development of the Internet of Things (IoT), the curse of dimensionality becomes increasingly common. Feature selection (FS) is to eliminate irrelevant and redundant features in the datasets. Particle swarm optimization (PSO) is an efficient metaheuristic algorithm that has been successfully applied to obtain the optimal feature subset with essential information in an acceptable time. However, it is easy to fall into the local optima when dealing with high-dimensional datasets due to constant parameter values and insufficient population diversity. In the paper, an FS method is proposed by utilizing adaptive PSO with leadership learning (APSOLL). An adaptive updating strategy for parameters is used to replace the constant parameters, and the leadership learning strategy is utilized to provide valid population diversity. Experimental results on 10 UCI datasets show that APSOLL has better exploration and exploitation capabilities through comparison with PSO, grey wolf optimizer (GWO), Harris hawks optimization (HHO), flower pollination algorithm (FPA), salp swarm algorithm (SSA), linear PSO (LPSO), and hybrid PSO and differential evolution (HPSO-DE). Moreover, less than 8% of features in the original datasets are selected on average, and the feature subsets are more effective in most cases compared to those generated by 6 traditional FS methods (analysis of variance (ANOVA), Chi-Squared (CHI2), Pearson, Spearman, Kendall, and Mutual Information (MI)).
Neural Network Model Design for Landscape Ecological Planning Assessment Based on Hierarchical Analysis
Authors: Liu Jing , Zhou Xudan
Published: August 2022

In this paper, an in-depth study and analysis of landscape ecological planning and evaluation are carried out using the analytic hierarchy process (AHP) algorithm that integrates neural networks. The application of AHP in the field of tree species planning and the introduction of quantitative analysis methods can effectively change the subjectivity of previous qualitative analysis in tree species selection and make it objective, scientific, and reasonable. The research can provide a reference for other urban tree species planning. From the connotation of landscape ecological service process and ecological space structure, the analysis of landscape ecological service process involves service supply area and service association area, which correspond to different key components of ecological space structure. With the help of the platform, based on the identification and identification methods and theories of ecological spatial structure, the key components of ecological spatial structure in different environments are identified and extracted by using the representation model, binary suitability model, weighted suitability model, and process model. The type of service is based on the different service processes supported by the key components of the ecological spatial structure, forming the ecological spatial structure under different service types. Spatial structure; on this basis, the basic characteristics of the key components of the ecological spatial structure are analyzed, and the correlation characteristics of the ecological spatial structure are analyzed based on the correlation classification system of ecological spatial structure. A backpropagation (BP) neural network-based state assessment method of the grid structure is established. The method takes the parameters of the autoregressive model constructed by the acceleration signals of different working conditions as the feature quantity and the results of the fuzzy hierarchical analysis method as the labels, divides the data set into a training set and a test set, and uses the BP neural network learning method and the training set to supervised train the BP neural network learning assessment model. The test set is used to test the effectiveness and accuracy of the BP neural network-based learning method. The study shows that the evaluation system established by the BP neural network structure is fast and accurate and can substantially reduce the cost of manual testing.
Application of Internet of Things Technology in Optimization of Electronic Assembly Process Parameters
Authors: Song Xianghui
Published: August 2022

In order to meet the demand of the Internet of things in the intelligent power monitoring system, this paper proposes a method to build an intelligent power monitoring system by combining 4G technology, the Android operating system, and other technologies closely related to the Internet of things. This method is evaluated by building an intelligent monitoring system and a transit node system and observing the test speed in the coco data set and the Pascal VOC data set. The experimental results show that the accuracy of animals measured by this method can reach up to 81%; the accuracy of humans can reach up to 76%; and the accuracy of vehicles can reach up to 87%. Conclusion. The application of Internet of things technology in the optimization of electronic assembly process parameters can quickly and effectively reflect the information in practical applications, so as to achieve the goal of seamless link and information exchange between things and people, and accurately manage and control the physical world in real time on the basis of scientific decisions.
Nonlinear Stochastic Multiobjective Optimization Problem in Multivariate Stratified Sampling Design
Authors: Alshqaq Shokrya Saleh A. , Ahmadini Abdullah Ali H. , Ali Irfan
Published: August 2022

Decision-making in survey sampling planning is a tricky situation; sometimes it involves multiple objectives, with various decision variables emanating from heterogeneous and homogeneous populations. Dealing with the entire population under study and its uncertain nature becomes a challenging issue for researchers and policymakers. Hence, an appropriate sampling design and optimization methodology are imperative. The study presents a useful discussion on stochastic multiobjective multivariate stratified sampling (MSS) models theoretically, and the concepts are illustrated with numerical examples. Also, it has been found that the linearization of sampling variance in survey sampling does not help determine the optimal sampling allocation problem with minimum variability. Optimal allocation problems under the weighted goal programming, stochastic goal programming, and Chebyshev goal programming methods are also discussed with numerical examples. Finally, the study discussed the linear approximation of the MSS problem with examples. The study is a conceptual and theoretical framework for MSS under a stochastic environment. The numerical data is simulated using the stratifyR package.
Maize Market Chain Analysis and the Determinants of Market Participation in the Gamo and Gofa Zones of Southern Ethiopia
Authors: Galtsa Duge , Tarekegn Kassa , Kamaylo Kusse , Oyka Endrias
Published: August 2022

The majority of farmers are producing maize in the Gamo and Gofa zones and they are not benefiting from it due to the marketing problem. Thus, this study was intended to analyze the maize market chain and determinants of market participation in the selected maize-producing districts of the Gamo and Gofa zones. To achieve this objective, multistage sampling techniques were followed to randomly select 151 sample respondents. The data were analyzed by using descriptive statistics, marketing margins, and the double hurdle model. The survey results revealed that approximately 35.88% of the maize from the total maize produced by the sampled farmers was marketed in the study area. The result indicates that among the five identified maize marketing channels, the largest volume of maize passed through channel V (producers, urban collectors, and consumers). In the marketing of maize, traders set the price due to poor market linkage and the low bargaining power of producers. The model regression result indicates that among the hypothesized factors, family size, allocated land size for maize, and market information have a significant effect on the quantity of maize market supply. Based on this finding, strengthening extension services through training and accessing inputs are recommended. Furthermore, market linkage through the cooperative establishment and the availability of market information by respective bodies is suggested.
Nonlinear Control of Induction Motor Based on Network Control System
Authors: Jin Changjiang
Published: August 2022

With the rapid development of network communication technology and computer technology, network control system has been applied in many different fields. Networked AC induction motor is controlled by a communication network to realize data transmission. This paper mainly studies the nonlinear control of induction motor based on network control system. In order to solve the nonlinear problem of AC induction motor, this paper adopts the method of the linear resolve coupling, and combined with the characteristics of the Internet, establishes the mathematical model of the AC induction motor, and considers the use of the system parameter perturbation to construct the mathematical model of the AC induction motor. Aiming at the problems of system parameter perturbation and network-induced delay in networked AC induction motor control system, the robust control of networked AC induction motor control system is studied. The experimental results show that the proposed control strategy can achieve asymptotic stability of the system with parameter perturbation under the action of the controller and can achieve asymptotic stability even with external disturbance. Compared with control strategies 1 and 2, the adjustment time of the speed waveform oversetting phenomenon is about 0.18 s and 0.26 s, and the adjustment time of the control strategy proposed in this paper is only 0.06 s. It is shown that the nonlinear control method of induction motor based on network control system can significantly improve the validity and stability of the system model.
Remote Human-Computer Interaction and STEM Teacher Online Training Based on Embedded Internet of Things
Authors: Wu Xinning , Zhang Qian
Published: August 2022

In order to expand the concept and form of teacher training, a remote human-computer interaction and STEM teacher online training platform based on the embedded Internet of Things is proposed. Based on the content analysis method, this article sorts out the development status of the current online teacher training platform and points out the shortcomings of the platform in information aggregation, resource construction, content setting, presentation, learning support services, and other aspects. Based on the combination of new concepts and new technologies, an online training platform for STEM teachers is proposed for the construction of the platform from four perspectives: innovative design concepts, enriching platform promotion ideas, developing educational makers, and improving support services, and the results of the use are investigated. The results show that the subjects believe that the STEM teacher online training system has clarified the STEM curriculum design steps, standardized STEM design methods, improved their cooperative learning ability, and cultivated design thinking. Among them, 13 people think that the training system has made STEM design steps clearer, “the design process is clearer,” “it makes me clearer about the whole design process,” and “the course design and development process is clearer.” Conclusion. This platform can provide a reference for online training and professional development of Chinese teachers.
The Analysis of the Effect of Blood Transfusion on Changes of Blood Platelet Parameters in Patients with Leukemia Treated with Chemotherapy
Authors: He Yangxin , Liang Shanshan , Xu Yali , Wan Chunjing , Ma Feng , Wang Baoyan
Published: August 2022

Objective. To study and analyze the effect of blood transfusion on the change of blood platelet parameters in patients with leukemia treated with chemotherapy. Methods. Ninety-eight patients with leukemia treated with chemotherapy in the First Affiliated Hospital of Xi’an Jiaotong University from January 2021 to January 2022 were selected to observe the changes of platelet parameters before and after blood transfusion. Results. There was significant difference between pre-transfusion and post-transfusion indexes (platelet count, mean platelet volume, and hematocrit) (

P
<
0.05

). After binary logistic regression analysis, the use of antibiotics (OR = 2.235), blood transfusion history (OR = 3.086), abnormal white blood cell count (OR = 1.134), and frozen plasma transfusion (OR = 3.121) were the main factors of blood platelet parameters after transfusion in leukemia patients (

P
<
0.05

). Conclusion. Blood transfusion is beneficial to improve blood platelet parameters and prevent bleeding in patients with leukemia treated with chemotherapy. Attention should be paid to patients with risk factors for poor response to blood platelet transfusion and early intervention.
An Evaluation Approach for English Teaching Quality Using DEA Fusion Algorithm
Authors: Tan Shuwen
Published: August 2022

The Data Envelope Analysis (DEA) is a technique that has been implemented in order to assess the effectiveness of various entities, including programs, organizations, and so on. They are accountable for making use of the available resources in order to obtain outputs that are of interest. It has been applied to the task of analyzing a variety of activities. The DEA is a fractional programming model that can contain multiple outputs and inputs without having to resort to prior weights or explicitly stating the functional relationship between inputs and outputs. This is because DEA is a model that is based on dynamic programming. It computes a scalar measure of efficiency and establishes the level of efficiency at both the organization’s inputs and outputs that are being evaluated. The assessment of the excellence of English instruction in universities and colleges is primarily plagued by two issues: first, the evaluation index system is lacking in its coverage, and second, the evaluation model struggles when confronted with highly nuanced signs. In order to find solutions to these issues, in this work, we delve deeply into the topic of assessing the quality of English instruction in colleges and universities and develop a model for doing so that is based on the DEA fusion algorithm. To assess the quality of English instruction provided by colleges and universities, a model, that takes into account both quantitative and qualitative research findings, has been developed. The findings of the implementation suggest that the DEA fusion algorithm that was proposed is capable of successfully assessing the quality of English instructions and teaching provided in colleges and universities. The proposed algorithm outperformed the traditional Multilayer Perceptron (MLP) algorithm and the Decision Tree (DT) algorithm. The findings of this research have been very helpful in encouraging the enhancement of the quality of English instruction in colleges.
Model and Simulation of Engineering Safety Risk Control Based on Artificial Intelligence Algorithm
Authors: Liu Zifeng , Zhao Xuliang , Tan Jianping , Tian Haotian
Published: August 2022

The implementation of engineering projects has a profound impact on the national economy and people’s livelihood. The current engineering projects are in full swing with the vigorous development of the economy. However, due to the high complexity of the engineering project environment, a large number of participants, the high technical standards, and the high labor intensity, it is easy to induce engineering safety risk accidents. Therefore, the demand for research on safety risks in engineering construction is becoming more and more urgent. However, the traditional construction safety risk management lacks systematicness and standardization, and it has limitations in engineering safety risk early warning and control. In order to solve this problem, this paper applies artificial intelligence algorithms to engineering construction safety risk management and establishes an engineering safety risk early warning control model. The Bayesian formula, information entropy theory, and other algorithms provide the theoretical basis and feasibility analysis for the model. Four engineering safety risk factors, including human factors, physical factors, management factors, and environmental factors, are analyzed through simulation experiments. The results show that the probability of injury to construction personnel has been reduced by 51.3%, the qualified rate of production materials in construction projects has increased by 6.5%, the risk factors of management have been reduced by 7%, and the environmental risk factors have been reduced by 7.7%; the final risk early warning control effect has increased by 7.45%.
Clinical Efficacy and Safety of Pulsed Dye Laser Combined with Pingyangmycin on Hyperplastic Scar after Acne
Authors: Guo Rong , Xuan Wenxia , He Xiao , Xu Kai
Published: August 2022

Background. Acne is the most common chronic inflammatory disease of hair follicles and sebaceous glands in dermatology. Hyperplastic scar (HS), a very common sequelae of acne, is also the most common scar type in clinical practice. Objective. This research analyzed the clinical effectiveness and safety of pulsed dye laser (PDL) combined with pingyangmycin (PI) in the treatment of post-acne HS. Methods. One hundred and nine patients with post-acne HS admitted in June 2020 were selected and divided into a research group (

n
=
52

) and a control group (

n
=
57

) according to the difference in treatment methods. The efficacy, incidence of adverse reactions, skin repair, treatment comfort, and satisfaction were compared between groups. Results. The total effective rate was higher in the research group compared with the control group. No statistical difference was observed between groups in the incidence of adverse reactions. The research group showed better scar repair, skin improvement, and granulation tissue maturity than the control group. And compared with the control group, the growth factor of the research group was lower, while the treatment comfort and satisfaction, psychological state, and prognosis quality of life were higher. The two groups showed no notable difference in the recurrence rate. Conclusions. PDL combined with PI can effectively improve the clinical efficacy, scar repair effect, overall skin status, and treatment experience of patients and boost the psychological state and prognostic quality of life of patients, which has great clinical application prospect for the treatment of HS.
[Retracted] Urban Management in the Dynamic Relationship between the Occurrence of Environmental Pollution Accidents and Economic Development in China
Authors: Cong Xuwen , Wang Huaixing , Huang Jingmei
Published: August 2022

After the reform and opening up, China has developed into a world factory due to the bias of Chinese policies, the need for urban development, and the limitations of science and technology. As a world factory, on the one hand, it expanded the scale of China’s economy, raised the level of science and technology, and improved the standard of people’s daily life. On the other hand, China’s technology level was backward at the beginning of the reform and opening‐up period, and the world countries in a competitive relationship could not give China a high‐end technology level. Most of the developed countries only transferred their rough industries to China, which led to the “three highs and one low” pattern of China’s economic development. The efficiency of resource utilization is very low, which not only wastes resources but also causes great deterioration of the environment. Based on China’s environmental development problems, this article summarizes and analyses the relationship between economic development and environmental pollution through the perspective of EKC curve research. Then, using the data of economic growth target published by government work report of 230 prefecture‐level cities from 2004 to 2014 collected by hand, the constraint of economic growth target is described from three dimensions. In particular, the study of economic growth target constraints is extended in terms of the portrayal of the characteristics of soft and hard constraints of economic growth targets. Finally, combining with the normative research method, feasible countermeasures are proposed for developed cities as well as less developed cities, providing new insights for the coordinated development of the urban environment and economy in China.
Antioxidative and Anti-Inflammatory Protective Effects of β-Caryophyllene against Amikacin-Induced Nephrotoxicity in Rat by Regulating the Nrf2/AMPK/AKT and NF-κB/TGF-β/KIM-1 Molecular Pathways
Authors: Rajab Bodour S. , Albukhari Talat A. , Khan Anmar A. , Refaat Bassem , Almehmadi Samah J. , Nasreldin Nani , Elshopakey Gehad E. , El-Boshy Mohamed
Published: August 2022

Herein, the molecular pathogenic pathways implicated in renal injury triggered by amikacin (AK), together with the alleviating actions of β-caryophyllene (BCP), were investigated. Adult male Wistar rats (

n
=
32

) were disseminated to the four following groups (

n
=
8

/group): normal group, positive control animals (PC) that received AK intraperitoneal injections for 14 days (500 mg/kg/day), and rats that received AK simultaneously with small (200 mg/kg/day) and high doses (400 mg/kg/day) of BCP. The PC renal tissues revealed abnormal histology alongside increased apoptosis and significantly elevated serum creatinine and urea with marked proteinuria and oliguria relative to the normal rats. Moreover, renal tissues from the PC animals also showed substantial upregulations in NF-κB/TGF-β/KIM-1, whilst Nrf2/AMPK/AKT/PCNA declined, at the gene and protein levels in comparison to the normal rats. Additionally, the levels of markers of oxidative stress (MDA/H2O2/protein adducts) and inflammation (TNF-α/IL-1β/IL-6/IL-18/TLR/HSP25) were substantially higher in the PC renal specimens, whereas the antioxidants (GSH/GPx/SOD1/CAT) and interleukin-10 decreased, relative to the NC group. Both BCP protocols improved the biochemical markers of renal functions, alleviated renal histopathology and apoptosis, and decreased NF-κB/TGF-β/KIM-1 alongside the concentrations of oxidative stress and proinflammatory markers, whilst promoting Nrf2/AMPK/AKT/IL-10/PCNA and the targeted antioxidants. However, the improving effects in the high-dose regimen were markedly stronger than those observed in animals treated with low dose of BCP. In conclusion, the present report is the first to connect NF-κB/TGF-β/KIM-1 proinflammatory and Nrf2/AMPK/AKT antioxidative stress pathways with the pathogenesis of AK-induced nephrotoxicity. Additionally, the current report is the first to disclose alleviating activities for BCP against AK-triggered nephrotoxicity by modulating multiple antioxidative stress with anti-inflammatory molecular pathways.
Pain Sensitization and Neuropathic Pain-like Symptoms Associated with Effectiveness of Exercise Therapy in Patients with Hip and Knee Osteoarthritis
Authors: Hattori Takafumi , Shimo Kazuhiro , Niwa Yuto , Katsura Yuichi , Tokiwa Yuji , Ohga Satoshi , Matsubara Takako
Published: August 2022

Pain sensitization and neuropathic pain-like symptoms are some of the common pain symptoms in patients with lower limbs, including hip and knee, osteoarthritis (HOA/KOA). Exercise therapy has been the first-line treatment; however, the effects differ for each patient. This prospective cohort study investigated the relationship between the effectiveness of exercise therapy and pretreatment characteristics (radiologic severity, pain sensitization, and neuropathic pain-like symptoms) of patients with HOA/KOA. We assessed the pain intensity using a numerical rating scale (NRS) before and after 12 weeks of exercise therapy in patients with HOA/KOA (n = 101). Before treatment, the Kellgren–Lawrence (K-L) grade; minimum joint space width (mJSW); pressure pain threshold (PPT) and temporal summation of pain (TSP) at the affected joint, tibia, and forearm; Central Sensitization Inventory-9; and painDETECT questionnaire (PDQ) were assessed. Cluster analysis was based on the pretreatment NRS and change in NRS with exercise therapy to identify the subgroups of pain reduction. The pretreatment characteristics of each cluster were compared. According to the results of the cluster analyses, patients in cluster 1 had severe pain that did not improve after exercise therapy, patients in cluster 2 had severe pain that improved, and those in cluster 3 had mild pain that improved. The patients in cluster 1 exhibited lower PPT at all measurement sites, higher TSP at the affected joint, and higher PDQ scores than those in other clusters. There was no difference in the K-L grade and mJSW among the clusters. The subgroup with severe pain and pain sensitization or neuropathic pain-like symptoms at pretreatment, even with mild joint deformity, may have difficulty in achieving improvement in pain after 12 weeks of exercise therapy. These findings could be useful for prognosis prediction and for planning exercise therapy and combining with other treatment.
Numerical Study of Natural Circulation Flow in Reactor Coolant System during a Severe Accident
Authors: Choi Dae Kyung , Park Won Man , Son Sung Man , Lim Kukhee , Cho Yong Jin , Choi Choengryul
Published: August 2022

The rupturing of steam generator tubes leads to serious accidents in nuclear power plants. It causes radioactive materials to leak into the secondary system and release outside the reactor containment region. Therefore, it is important to model a technique to determine whether the natural circulation within a reactor coolant system (RCS) can cause rupture. In this study, a computational fluid dynamics (CFD) analysis methodology was incorporated as a first step to establish an RCS natural circulation evaluation technique to generate RCS natural circulation input parameters for the MELCOR analysis of thermally induced steam generator tube rupture (TI-SGTR) in nuclear power plants. Benchmarking tests were conducted against existing experimental studies; the results demonstrated a difference of 9.4% or less between the experimental and CFD analysis results with respect to the main evaluation factors. Subsequently, a steam generator tube simplification modeling technique was established for application to nuclear power plants, and CFD analysis was conducted to determine its applicability. The CFD analysis results revealed that when numerous tubes are simplified into one equivalent tube, the thermal flow characteristics generated in the RCS could be distorted. The findings of this research are expected to be helpful in understanding the thermal flow characteristics of natural circulation in the RCS. Further, the findings may potentially serve as a foundation for future CFD analysis research related to the natural circulation in the RCS of nuclear power plants.
Compression Domain Reversible Robust Watermarking Based on Multilayer Embedding
Authors: Li Qianwen , Wang Xiang , Pei Qingqi
Published: August 2022

The integration of data sensing, communication, and computing (SCC) is a requirement for the IoT to provide a high quality of service. However, there are still data security issues in SCC integration, where data are vulnerable to leakage during sensing, communication, and computing, and the leaked data are difficult to be copyrighted and traced to the source of leakage. In this study, we consider the copyright protection problem in multimedia data transmission and propose a robust reversible watermarking algorithm based on multilayer embedding in the compression domain. In the first stage, the robust watermark is embedded into the mid-frequency coefficients, and then, the auxiliary information to revert the robust embedding is embedded into the high-frequency coefficients. To improve robustness and reduce embedding distortion, we propose a coefficient selection method, by which the watermark and the recovery information are embedded in different DCT-quantized coefficients according to the texture complexity. Experiment results indicate that the proposed method performs better than some state-of-the-art RRW methods.
Effect of Gradient Doping on Charge Collection Efficiency of EBCMOS Devices
Authors: Qin Xulei , Shi Qidong , Shi Feng , Li Ye , Song De
Published: August 2022

We investigated the effect of different gradient doping methods on the charge collection efficiency of the electron multiplication layer of EBCMOS devices. Exponential doping of the electron multiplication layer can form a built-in electric field in the electron multiplication layer that is favorable for photoelectron transport, so exponential doping instead of uniform doping in the electron multiplication layer of EBCMOS can effectively improve the charge collection efficiency. It is shown that exponential heavy doping on the side of the electron multiplication layer near the dead layer and exponential light doping on the side near the depletion region can improve the built-in electric field structure and increase the lifetime of the multiplied electrons, thereby improving the charge collection efficiency of EBCMOS. The optimized device achieves a charge collection efficiency of 94.48% at an incident electron energy of 4 keV, an electron beam diameter of 20 nm, a dead layer thickness of 60 nm, and a P-type silicon epitaxial layer thickness of 10 μm.
Effects of Propofol Intravenous Anesthesia on Serum NGF, S100B Protein, and Immune Function in Patients with Bladder Cancer after Resection
Authors: Guan Xiaohong , Peng Qingxiong , Liu Yongping , Wang Jiansong
Published: August 2022

Objective. To explore the efficacy of intravenous propofol anesthesia on patients with bladder cancer after resection, as well as its effect on cognitive and immune function. Methods. Patients with bladder cancer and received resection of bladder cancer at our hospital from May 1, 2019, to November 30, 2021, were retrospectively retrieved and included in this study. The included patients were summarized into group A (isoflurane) and group B (intravenous propofol). The anesthesia intervention effect, serum NGF level, serum S100B protein level, and immune function before surgery, 6 h after surgery, 1 d after surgery, and 3 d after surgery were compared between the two groups. Results. Eighty-six patients were retrieved. The anesthesia intervention effective rate of patients in group B was significantly higher than that of patients in group A (

P
<
0.01

). The serum NGF and S100B of patients in both groups were significantly lower on postsurgical day 1, but in the trend to returning to those before intervention level on day 3. There were also fluctuations in immune function represented by changes in CD3+, CD4+, CD8+, and CD4+/CD8+ T cells, which showed return of function by postsurgical day 3. Conclusion. The anesthetic effect of intravenous propofol in patients with bladder cancer resection is significantly more satisfactory than isoflurane, with a transient effect on serum NGF and S100B protein levels and patients’ immune function, which suggests that intravenous propofol can be widely used for general anesthesia in clinical practice.
Application of 3D Virtual Scanning Technology in Landscape Planning of Complex Landscape Gardens
Authors: Huang Chunmei , Zheng Yushan
Published: August 2022

In order to solve the problem of technical precision in landscape planning of complex landscape garden topography, the authors propose a research using 3D virtual scanning technology. The main content of this research is based on the overall architecture of the 3D virtual landscape planning system, the construction of the system architecture, and the optimization of VR design scenarios; finally, through experiments, the feasibility of 3D virtual scanning technology is obtained. Experimental results show that the number of landscape connection points measured by the author is more than 1500, and the accuracy is between 0.2 and 0.6 pixels, indicating that for the mutual connection and orientation between models, the system has a good application prospect in the landscape planning of complex landscape garden topography. The research on 3D virtual scanning technology is proven, and it can meet the application in the landscape planning of complex landscape garden topography.
Key Point Detection Method of 3D Network Model Based on Virtual Reality Technology
Authors: Sun Ji
Published: August 2022

In order to meet the higher requirements of today’s society for the details and fidelity of 3D models, a key point detection method for 3D network models based on virtual reality technology is proposed. The key technical steps include model normalization preprocessing, feature extraction, and similarity calculation. The 3D model retrieval test of cars, trucks, and buses is carried out using the VTFT algorithm. The results showed that in different databases, the highest success rate was 86.4% and the lowest was 77.10%. Practice has proved that this method can effectively improve the efficiency and accuracy of current 3D model processing and can better meet social needs such as games and entertainment.
Neuropsychiatric Lupus and Lupus Nephritis Successfully Treated with Combined IVIG and Rituximab: An Alternative to Standard of Care
Authors: Cheikh Mohamed M. , Bahakim Abdullah K. , Aljabri Moayad K. , Alharthi Saad M. , Alharthi Sanad M. , Alsaeedi Abdullah K. , Alqahtani Saad F.
Published: August 2022

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease with unpredictable course and flares. The clinical manifestation can vary from mild to severe and life-threatening disease. Infection is the primary cause of mortality in hospitalized SLE patients. There is a paucity of evidence to support the co-management of SLE with major organ involvement and sepsis. We describe the clinical response of a 35-year-old male diagnosed with SLE; then, he developed severe sepsis and a flare of SLE with major organ involvement including lupus nephritis (LN), myocarditis, and neuropsychiatric systemic lupus erythematosus (NPSLE). Based on the patient’s condition, a treatment dilemma was encountered, and after a multidisciplinary meeting, the decision was made to use a combination of rituximab (RTX), intravenous immunoglobulin (IVIG), and pulse steroid. Shortly, the patient’s condition started to improve, and his symptoms were resolved. In conclusion, our clinical case suggests that combined RTX, IVIG, and pulse steroid seem to be effective and safe in achieving clinical response, thus representing a good choice for managing severe SLE flares in sepsis.
Stock Portfolio Optimization Using a Combined Approach of Multi Objective Grey Wolf Optimizer and Machine Learning Preselection Methods
Authors: Mazraeh Nasrin Bagheri , Daneshvar Amir , Madanchi zaj Mahdi , Roodposhti Fereydon Rahnamay
Published: August 2022

The present paper deals with optimizing the stock portfolio of active companies listed on the Tehran Stock Exchange based on the forecast price. This paper is based on a combination of different filtering methods such as optimization of trading rules based on technical analysis (ROC, SMA, EMA, WMA, and MACD at six levels—Very Very Weak (VVW), Very Weak (VW), Weak (W), Strong (S), Very Strong (VS), and Very Very Strong (VVS)), Markov Chains, and Machine Learning (Random Forest and Support Vector Machine) Filter stock exchanges and provide buy signals between 2011 and 2020. In proportion to each combination of filtering methods, a buy signal is issued and based on the mean-variance (M-V) model, the stock portfolio is optimized based on increasing the portfolio return and minimizing the stock portfolio risk. Based on this, out of 480 companies listed on the Tehran Stock Exchange, 85 active companies have been selected and stock portfolio optimization is based on two algorithms, MOGWO and NSGA II. The analysis results show that the use of SVM learning machine leads to minor correlation error than the random forest method. Therefore, this method was used to predict stock prices. Based on the results, it was observed that if the shares of companies are filtered, the risk of transactions decreases, and the return on the stock portfolio increases. Also, if two filtering methods are applied simultaneously, the stock portfolio returns slightly and the risk increases. In the analysis, MOGWO algorithm has obtained 133.13% stock return rate with a risk of 3.346%, while the stock portfolio returns in NSGA II algorithm 107.73, with a risk of 1.459%. Comparison of solution methods shows that the MOGWO algorithm has high efficiency in stock portfolio optimization.
Optimization on Material Removal Rate and Surface Roughness of Stainless Steel 304 Wire Cut EDM by Response Surface Methodology
Authors: Seshaiah Sathishkumar , Sampathkumar Deepak , Mariappan Mathanbabu , Mohankumar Ashokkumar , Balachandran Guruprasad , Kaliyamoorthy Murugan , Rajendran Barathiraja , Gopal Rajendiran
Published: August 2022

In this work, wire cut electrical discharge machining (WEDM) is used for the material removing processes; it is utilized for machining conductive parts where it is required to produce complicated shapes, new profiles, new geometry, new product development, and high-accuracy components. This machining process is best suitable for high-end applications such as aerospace, automations, automobile, and medical devices. At present, most of the industrial sectors choose the WEDM process because it is used to develop products in a very short development cycle and at a better economic rate. In this paper, the selected complex geometry of the metal sample was eroded away from the wire during the WEDM process, which eliminates mechanical tensions during machining. The effect of different WEDM operation variables set as wire speed, wire tension, discharge current, dielectric flow rate, and pulse on and off time on the parameter, stainless steel 304 material removing rate (MRR) using RSM, has been studied. The MRR will be maximized if the optimum sets of operational variations are used and also achieve a superior surface finish.
circFOXO3 Induced by KLF16 Modulates Clear Cell Renal Cell Carcinoma Growth and Natural Killer Cell Cytotoxic Activity through Sponging miR-29a-3p and miR-122-5p
Authors: Yang Fafen , Chen Yuke , Luo Linxue , Nong Shengbin , Li Tong
Published: August 2022

Renal cell carcinoma (RCC) is one of the most common urological malignancies with high incidence and metastatic relapse. Clear cell RCC (ccRCC) comprises nearly 70% of all RCC cases and is responsible for the majority of morbidity and mortality of RCC. Due to the poor diagnosis strategy and unsatisfactory clinical intervention, ccRCC causes a huge economic burden and poor patient quality of life; therefore, novel diagnostic or therapeutic targets for ccRCC are urgently needed. This study investigated the biological role of circFOXO3 in ccRCC development, showing that circFOXO3 is highly expressed in RCC cells and tissues and inhibits the viability of ccRCC cells. circFOXO3 dysregulation regulates NK cell cytotoxicity towards RCC cells by directly sponging miR-29a-3p and miR-122-5p. Overexpression of miR-29a-3p or miR-122-5p attenuated NK cell toxicity towards RCC cells and the transcriptional factor Kruppel-Like Factor 16 (KLF16) regulates circFOXO3 expression in RCC cells. In conclusion, this study has partially elucidated the function of circFOXO3 in ccRCC development, providing potential novel therapeutic targets for ccRCC.
Research on Deflection of Partial Steel Fiber Reinforced Concrete Beams with BFRP Bars
Authors: Dong Hui , Chen Shengping , Li Hangyu , Zhang Jianbo
Published: August 2022

In this study, the flexural behavior tests of steel fiber reinforced concrete beams with BFRP bars under static load are carried out by means of statics experiment and theoretical analysis. A total of seven beams were designed for this experiment, and the effects of two factors on the mid-span deflection of the beams were investigated with the steel fiber incorporation rate (0%, 0.5%, 1%, 1%/0.5%, 1.5%) and the height of steel fibers in the concrete layer in the compression zone (180 mm, 210 mm, 300 mm) as the main variables. In this study, based on the existing research results and combined with the actual test results, the formulae for calculating the cracking section moment of inertia applicable to BFRP reinforced steel fiber (full section/pressure zone reinforced) concrete beams are derived. At the same time, the results obtained from the formula and the results of the ACI code in the United States are compared with the data of the results obtained from this test, and the calculated results of this formula are in good agreement with the actual values.
Skin Diseases Classification Using Hybrid AI Based Localization Approach
Authors: Sreekala Keshetti , Rajkumar N. , Sugumar R. , Sagar K. V. Daya , Shobarani R. , Krishnamoorthy K. Parthiban , Saini A. K. , Palivela H. , Yeshitla A.
Published: August 2022

One of the most prevalent diseases that can be initially identified by visual inspection and further identified with the use of dermoscopic examination and other testing is skin cancer. Since eye observation provides the earliest opportunity for artificial intelligence to intercept various skin images, some skin lesion classification algorithms based on deep learning and annotated skin photos display improved outcomes. The researcher used a variety of strategies and methods to identify and stop diseases earlier. All of them yield positive results for identifying and categorizing diseases, but proper disease categorization is still lacking. Computer-aided diagnosis is one of the most crucial methods for more accurate disease detection, although it is rarely used in dermatology. For Feature Extraction, we introduced Spectral Centroid Magnitude (SCM). The given dataset is classified using an enhanced convolutional neural network; the first stage of preprocessing uses a median filter, and the final stage compares the accuracy results to the current method.
Safety-Based Optimization Model for Highway Horizontal Alignment Design
Authors: You Kesi , Yu Qifeng , Huang Weiguo , Hu Yong
Published: August 2022

The construction cost and crash cost of the highway are contradictory, but there is an optimal balance between them. This study focused on the best balance point by microadjusting the highway alignment design using the optimization theory. A multiobjective optimization method was proposed to optimize the highway horizontal alignment design considering the economy and safety. The optimization model includes three main objective functions which are the economic objective function, safety objective function, and position constraint objective function. Constraints were established for the optimization model following the corresponding specifications, such as constraints for the three elements in the design unit, continuous constraints for adjacent alignments, constraints for the location of horizontal alignment, and constraints for speed coordination. Two scenarios were considered to verify the effect of the optimization model. One scenario considered the constraints of the intermediate control points, and the other does not. In addition, two cases were analyzed. One is optimization for a horizontal alignment design unit. Another one is for a highway segment including four design units. The parallel genetic algorithm was used to solve the optimization model. Case study results indicate that the optimization model could help to improve the safety and economics of highways. In addition, the proposed optimization model could reduce much more redundant debugging work for the designer and reduce the influence of the designer’s subjectivity.