bluuebunny/crossref_metadata_2025 huggingface dataset:
ℒ1 Adaptive Output Feedback Control of Small Unmanned Aerial Vehicles
Authors: Souanef Toufik
Published: June 2022

An approach for output feedback [Formula: see text] adaptive control of small Unmanned Aerial Vehicles (UAVs) is presented in this paper. The design is based on a state observer instead of the state predictor. The main advantage is that a full state measurement can be avoided, and the design and implementation of the controller are simplified. Furthermore, since the state space description is maintained, the system dynamics including uncertainties can be specified with physical insight, which simplifies practical applications. The adaptation law borrows insights from the sliding mode control to estimate the unknown bounds of external disturbances. Flight test results for the control of a small UAV show the robustness of the [Formula: see text] adaptive controller to large uncertainties and disturbances.
Core-shell NiO Sphere Prepared by a Facile Method with Enhanced VOC Gas Sensing
Authors: Li Qingting , Zeng Wen , Li Yanqiong
Published: June 2022

In this work, we reported a novel core–shell NiO spheres with a three-layer structure for gas sensor. The obtained gas sensors exhibited a higher response, rapid response/recovery rate and nice reproducibility. The gas sensitivity test results showed that NiO-12 h with a three-layer structure obtained a gas response of 35.4, a response/recovery time of 13/9.8 s, to 200 ppm ethanol at 350 °C. The enhancement of gas sensing performance gave credit to the special core–shell structure and the more OV and OC. Furthermore, the formation mechanism of the core–shell structure was analyzed and we found that the formation of the core–shell structure was closely related to the reaction time. This work not only gave a solution for improving the gas sensing performance of the gas sensors based on NiO, but provided an analysis of the growth mechanism of the core–shell structure.
A Neuron-specific Enolase Electrochemical Immunosensor Based on rGO/Cu8Ni2 Nanocomposite with Enhanced Catalytic Activity
Authors: Yi Runze , Li Yueyuan , Wang Shujun , Liu Qing , Dong Hui , Liu Shanghua , Li Yueyun
Published: June 2022

Neuron-specific enolase (NSE) is a reliable biomarker for the diagnosis of small cell lung cancer (SCLC). Effective detection of NSE plays an important role in the clinical diagnosis, treatment, and prediction of disease recurrence of SCLC. Herein, a simple label-free electrochemical immunosensor based on reduced graphene oxide/Cu8Ni2 (rGO/Cu8Ni2) nanocomposite was reported to detect the neuron-specific enolase (NSE). The rGO/Cu8Ni2 nanocomposite was prepared by loading optimized CuNi (8:2) alloy on the reduced graphene oxide through electrostatic-adsorption interactions and in situ simultaneous reductions. As a noble-metal-free alloy, Cu8Ni2 exhibits favorable catalytic activity. Combining the CuNi alloys with graphene can effectively keep off the aggregation of the alloy and further maintain its high catalytic activity. Simultaneously with the huge surface area and conductivity of rGO, rGO/Cu8Ni2 showed increased bound antibodies and enhanced catalytic activity, which makes the fabricated immunosensor exhibit enhanced performance. Under the optimal conditions, the designed electrochemical immunosensor for detecting NSE showed a wide linear range from 500 fg ml−1 to 50 ng ml−1 and the low detection limit was 137 fg ml−1. The proposed immunosensor in this study provides an effective method for the detection of NSE and may be expected to be applied in clinical diagnosis and treatment.
Potentiodynamic Polarization of Pure Metals and Alloys in Molten LiF-NaF-KF (FLiNaK) Using the K/K+ Dynamic Reference Electrode
Authors: Doniger William H. , Couet Adrien , Sridharan Kumar
Published: June 2022

The potentiodynamic polarization method using the K/K+ dynamic reference electrode was used to understand the corrosion behavior of Ni, Fe, Cr, the Ni-20Cr binary alloy, and 316L stainless steel in molten 46.5LiF-11.5NaF-42KF (FLiNaK, composition in mol %) salt at 700 °C. Exposure of the materials without an applied potential revealed that Ni and Fe were stable in FLiNaK, but Cr was dissolved rapidly. The apparent redox potentials of each material with respect to the K/K+ redox couple are compared to gain insight into how the applied potential relates to the dominant corrosion mechanism for each alloy. The polarized pure metals experienced uniform surface recession while corrosion in the alloys resulted in preferential elemental dissolution depending on the applied potential with respect to the K/K+ reference reaction.
Novel roles of mTORC2 in regulation of insulin secretion by actin filament remodeling
Authors: Blandino-Rosano Manuel , Scheys Joshua O. , Werneck-de-Castro Joao Pedro , Louzada Ruy A. , Almaça Joana , Leibowitz Gil , Rüegg Markus A. , Hall Michael N. , Bernal-Mizrachi Ernesto
Published: June 2022

The current studies uncover a novel mechanism linking mTORC2 signaling to glucose-stimulated insulin secretion by modulation of the actin filaments. This work also underscores the important role of GLP-1 in rescuing defects in insulin secretion by modulating actin polymerization and suggests that this effect is independent of mTORC2 signaling.
Local and systemic transcriptomic responses from acute exercise induced muscle damage of the human knee extensors
Authors: Kirk Eric A. , Castellani Christina A. , Doherty Timothy J. , Rice Charles L. , Singh Shiva M.
Published: June 2022

Skeletal muscle is adaptable to a direct stimulus of exercise-induced muscle damage (EIMD). Local muscle gene networks and systemic circulatory factors respond to EIMD within days, mediating anti-inflammation and cellular proliferation. Here we show in humans that local EIMD of one muscle group is associated with a systemic response of gene networks that regulate muscle structure and cellular development in nonlocal homologous muscle not directly altered by EIMD. In the nondominant knee extensors of seven males, EIMD was induced through voluntary contractions against an electric motor that lengthened muscles. Neuromuscular assessments, vastus lateralis muscle biopsies, and blood draws occurred 2 days prior and 1 and 2 days after the EIMD intervention. From the muscle and blood plasma samples, RNA-Seq measured transcriptome changes of differential expression using bioinformatic analyses. Relative to the time of the EIMD intervention, local muscle that was mechanically damaged had 475 genes differentially expressed, as compared with 33 genes in the nonlocal homologous muscle. Gene and network analysis showed that activity of the local muscle was related to structural maintenance, repair, and energetic processes, whereas gene and network activities of the nonlocal muscle (that was not directly modified by the EIMD) were related to muscle cell development, stress response, and structural maintenance. Altered expression of two novel miRNAs related to the EIMD response supported that systemic factors were active. Together, these results indicate that the expression of genes and gene networks that control muscle contractile structure can be modified in response to nonlocal EIMD in humans.
Effects of Dietary Lipid Levels on Growth, Digestive Enzyme Activities, Antioxidant Capacity, and Lipid Metabolism in Turbot (Scophthalmus maximus L.) at Three Different Stages
Authors: Zhang Wencong , Dan Zhijie , Zhuang Yanwen , Zheng Jichang , Gong Ye , Liu Yongtao , Mai Kangsen , Ai Qinghui
Published: June 2022

Three 56-day feeding trials were conducted to evaluate dietary lipid requirements and effects of dietary lipid levels on growth, digestive enzyme activities, antioxidant capacity, and lipid metabolism in turbot (Scophthalmus maximus L.) at three growth stages. The initial mean body weight of turbot was

9.13
±
0.17

 g,

50.10
±
0.38

 g, and

80.05
±
0.76

 g (small, medium, and large turbot), respectively. Five practical diets were formulated to contain 68.4, 93.9, 120.7, 147.8, and 171.2 g/kg lipid (L68.4, L93.9, L120.7, L147.8, and L171.2), respectively. Results of three trials showed that the weight gain rate and specific growth rate of turbot fed with L120.7, L147.8, and L171.2 diets were all significantly higher compared with turbot fed with L68.4 and L93.9 diets except for large turbot fed with the L147.8 diet. Activities of intestinal trypsin, lipase and hepatic catalase, superoxide dismutase, and total antioxidant capacity firstly increased and then decreased as dietary lipids increased. Meanwhile, malondialdehyde content decreased firstly but then increased with the elevation of dietary lipids in small and medium turbot, and it was significantly higher in the L171.2 group than the rest in large turbot. With increasing levels of dietary lipid, contents of whole-body lipid, liver lipid, serum total cholesterol, triglyceride, and low-density lipoprotein cholesterol were markedly increased at three stages. In addition, serum high-density lipoprotein cholesterol contents increased firstly and then decreased over the L120.7 group. Transcriptional levels of lipolysis-related genes lipin1 and lpl were significantly upregulated firstly and subsequently downregulated with increasing dietary lipid levels except lipin1 in medium fish. Meanwhile, a significant increase in lipogenesis-related genes lxr and pparγ expressions was detected in all fish. Based on the specific growth rate, the dietary lipid level of 130.1, 120.1, and 107.7 g/kg was optimal for the growth performance of turbot cultured at three phases, respectively. Additionally, the results indicated that high lipid diets may lead to abnormal lipid deposition and affect the physiological health of turbot.
Aberrant ROS Served as an Acquired Vulnerability of Cisplatin-Resistant Lung Cancer
Authors: Xin Qian , Ji Qinghong , Zhang Ying , Ma Weihong , Tian Baoqing , Liu Yanli , Chen Yunsong , Wang Fei , Zhang Ran , Wang Xingwu , Yuan Jupeng
Published: June 2022

Lung cancer has become a global health issue in recent decades. Approximately 80-85% of cases are non-small-cell lung cancer (NSCLC). Despite the high rate of resistance, cisplatin-base chemotherapy is still the main treatment for NSCLC patients. Thus, overcoming cisplatin resistance is urgently needed in NSCLC therapy. In this study, we identify NADPH metabolism and reactive oxygen species (ROS) levels as the main causes accounting for cisplatin resistance. Based on a small panel consisting of common chemotherapy drugs or compounds, APR-246 is proved to be an effective compound targeting cisplatin-resistant NSCLC cells. APR-246 specially inhibits proliferation and colony formation of cisplatin-resistant cells. In details, APR-246 can significantly cause G0/G1 accumulation and S phase arrest of cisplatin resistant cells and gives rise to severe mitochondria dysfunction as well as elevated apoptosis. Further study proves that it is the aberrant ROS levels as well as NRF2/SLC7A11/GSH axis dysfunction accounting for the specific antitumor effects of APR-246. Scavenging ROS with N-acetylcysteine (NAC) disrupts the inhibitory effect of APR-246 on cisplatin-resistant cells. Mechanistically, NRF2 is specifically degraded by the proteasome following its own ubiquitylation in APR-246-treated cisplatin-resistant cells, which in turn decreases NRF2/SLC7A11/GSH axis activity. Our study provides new insights into the biology driving cisplatin resistance of lung cancer and highlights APR-246 as a potential therapeutic reagent for overcoming cisplatin resistance.
[Retracted] Dense Convolutional Neural Network for Detection of Cancer from CT Images
Authors: Sreenivasu S. V. N. , Gomathi S. , Kumar M. Jogendra , Prathap Lavanya , Madduri Abhishek , Almutairi Khalid M. A. , Alonazi Wadi B. , Kali D. , Jayadhas S. Arockia
Published: June 2022

In this paper, we develop a detection module with strong training testing to develop a dense convolutional neural network model. The model is designed in such a way that it is trained with necessary features for optimal modelling of the cancer detection. The method involves preprocessing of computerized tomography (CT) images for optimal classification at the testing stages. A 10‐fold cross‐validation is conducted to test the reliability of the model for cancer detection. The experimental validation is conducted in python to validate the effectiveness of the model. The result shows that the model offers robust detection of cancer instances that novel approaches on large image datasets. The simulation result shows that the proposed method provides analyzes with 94% accuracy than other methods. Also, it helps to reduce the detection errors while classifying the cancer instances than other methods the several existing methods.
Sustainable Smart Industry: A Secure and Energy Efficient Consensus Mechanism for Artificial Intelligence Enabled Industrial Internet of Things
Authors: Sasikumar A. , Ravi Logesh , Kotecha Ketan , Saini Jatinderkumar R. , Varadarajan Vijayakumar , Subramaniyaswamy V.
Published: June 2022

In recent years, the Internet of Things (IoT) has been industrializing in various real-world applications, including smart industry and smart grids, to make human existence more reliable. An overwhelming volume of sensing data is produced from numerous sensor devices as the Industrial IoT (IIoT) becomes more industrialized. Artificial Intelligence (AI) plays a vital part in big data analyses as a powerful analytic tool that provides flexible and reliable information insights in real-time. However, there are some difficulties in designing and developing a useful big data analysis tool using machine learning, such as a centralized approach, security, privacy, resource limitations, and a lack of sufficient training data. On the other hand, Blockchain promotes a decentralized architecture for IIoT applications. It encourages the secure data exchange and resources among the various nodes of the IoT network, removing centralized control and overcoming the industry’s current challenges. Our proposed approach goal is to design and implement a consensus mechanism that incorporates Blockchain and AI to allow successful big data analysis. This work presents an improved Delegated Proof of Stake (DPoS) algorithm-based IIoT network that combines Blockchain and AI for real-time data transmission. To accelerate IIoT block generation, nodes use an improved DPoS to reach a consensus for selecting delegates and store block information in the trading node. The proposed approach is evaluated regarding energy consumption and transaction efficiency compared with the exciting consensus mechanism. The evaluation results reveal that the proposed consensus algorithm reduces energy consumption and addresses current security issues.
Computational Technique to Study Analytical Solutions to the Fractional Modified KDV-Zakharov-Kuznetsov Equation
Authors: Abdoon Mohamed A. , Hasan Faeza Lafta , Taha Nidal E.
Published: June 2022

In this article, we study and investigate the analytical solutions of the space-time nonlinear fractional modified KDV-Zakharov-Kuznetsov (mKDV-ZK) equation. We have got new exact solutions of the fractional mKDV-ZK equation by using first integral method; we found new types of hyperbolic solutions and trigonometric solutions by symbolic computation.
An Accurate Prediction Algorithm of RUL for Bearings: Time-Frequency Analysis Based on MRCNN
Authors: Huang Dezhi , Yu Gang , Zhang Jian , Tang Jian , Su Jian
Published: June 2022

Remaining useful life (RUL) prediction of mechanical components is of high research value in the field of prognostics and health management (PHM). However, RUL prediction problems are completely challenging due to the complicacy of bearings’ operating environment. In this paper, we transform the vibration acceleration signal collected by sensors into a time-frequency domain matrix through continuous wavelet transform (CWT) and then extract the features of the time-frequency domain matrix through the proposed multiscale residual convolutional neural network (MRCNN), which enables the model to extract more local and global features while constructing more accurate health indicators (HI). In order to highlight the degradation trend of mechanical components, the obtained health indicators are smoothed by exponential moving average (EMA). Finally, linear regression is exploited to predict the RUL of the bearing. Performance evaluations based on the public dataset PRONOSTIA demonstrate the effectiveness of our proposed algorithm, which is superior to existing data-driven algorithms in terms of prediction accuracy.
Patients Perceived Knowledge, Attitude, and Practice of Dental Abscess Management in Periurban District, Ghana
Authors: Damilare Kingsley Adeoye , Abass David , Antwi-Agyei David , Osei-Owusu Frederick , Ahenkan Ebenezer , Boadu Kwame Adu Okyere , Boadu Richard Okyere
Published: June 2022

Background. Seeking conventional oral health care for various dental conditions is still a challenge for many worldwide and poses a global public health challenge. It is not until the individual starts experiencing pain and disfigurement of the facial profile that they seek dental care after many self‐care interventions have failed. This study sought to determine perceived knowledge, attitude, practice, and satisfaction of dental abscess management among dental abscess patients (DAPs). Methods. The research used a cross‐sectional design to collect data from patients who visited the Dental Department of Effiduase Government Hospital with dental abscess from 6 May 2020–27 August 2020. A total sample size of 82 was selected from a population of 377. About 76 DAPs who met the inclusion criteria and consented to participate were interviewed. Results. About 57% of respondents believed that dental caries caused their abscess. However, 46% sought medical treatment between 0 and 2 weeks after the onset of their dental abscess, while the rest did that after 3 weeks. Close to 64.5% have ever had episode of abscess before current one which they managed with alternative treatment. About 95% of respondents saw the hospital as a good place for dental care. A significant association was established between patient’s level of education and influence to seek orthodox treatment (p = 0.015, Fisher’s exact test (FET)). Another significant association was established between patient’s level of education and the kind of alternative treatment they used (p = 0.016, Fisher’s exact test (FET)). Conclusions. Most DAPs believe that dental caries was the main cause of dental abscess. DAPs sought late medical care, after they have tried a failed alternative treatment. DAPs expressed satisfaction with reception, equipment and materials, and medicines used. Majority of the patients rated the cost of dental care in the facility as affordable.
A Multivariate Statistical Model of Water Leakage in Urban Water Supply Networks Based on Random Matrix Theory
Authors: Chen Yumo , Yang Ying
Published: June 2022

In this paper, model construction of random matrix theory is carried out to analyze water leakage of urban water supply pipeline network, and a multivariate statistical model of water leakage of urban water supply pipeline network based on random matrix theory is proposed. This paper presents a three-level DMA, short-term water demand prediction method based on water use patterns, aiming to solve the problem of inaccurate water demand prediction caused by climate and social factors. Correlation analysis and factor analysis analyze the main factors affecting daily water demand changes. The extracted information of the main influencing factors and historical monitoring data are used to establish the Elman water demand prediction model. At the same time, the daily water consumption pattern was extracted by correlation analysis, matched with the water consumption pattern of the predicted day, and combined with the expected value of water demand for momentary water demand allocation, which improved the prediction accuracy of short-term water demand. This paper is based on the precise leakage location based on the real-time hydraulic model. The real-time hydraulic model under leakage conditions is established, GA and NSGA2 are designed, and the nondominated ranking algorithm with elite strategy is used to achieve accurate leakage location using hydraulic model calibration search. This paper uses a random matrix algorithm to establish the leakage estimation model. A laboratory case pipe network is built to simulate the water supply conditions in residential areas, and the operating data of the laboratory case pipe network are used to confirm that the random matrix leakage estimation model can estimate the leakage. The applicability of the random matrix leakage estimation model and the wavelet transform algorithm for leakage calculation are compared in an engineering example. The example confirms that the leakage amount calculated by the random matrix model has a less relative error and more similar trend than the wavelet transform algorithm.
Analysis of the Style Characteristics of National Dance Based on 3D Reconstruction
Authors: Zhang Dongqi
Published: June 2022

National dance is an important symbol of national spiritual culture, as it embodies each nation’s unique history, living habits, ideology, and culture. Many Chinese ethnic groups have developed their own dance forms and styles, each with their own set of charms. Strengthening our understanding of its style and characteristics is critical to our understanding of the national dance. To begin with, this paper proposes a patch-based multiview stereo reconstruction scheme that can accurately reconstruct 3D character models. The movement capture system then collects national dance movement data and uses them to drive a three-dimensional character model that generates dance visual animation. In the human skeleton model, a spatial-temporal HMM (hidden Markov model) is proposed that not only studies the temporal information of human movements but also the spatial information of adjacent connection points. The recognition rate of this algorithm increases to 95.68 percent when the number of setting points is increased to ten and to 98.28 percent when the number of setting points is increased to twenty, according to the research. The experimental results show that the 3D reconstruction model of ethnic dance developed in this paper is capable of meeting the goal of ethnic dance digitalization while being simple to use, being low in cost, and with a good display effect.
Factors Shaping Occupational Injustice among Resettled Syrian Refugees in the United States
Authors: Darawsheh Wesam B. , Bewernitz Megan , Tabbaa Sawsan , Justiss Michael
Published: June 2022

Background. There have been a limited number of studies that have focused on factors which shape the experiences of resettlement and occupational injustice among refugee populations. Purpose. To explore the factors that shape the living difficulties of Syrian refugees who were lawfully admitted into the United States and ways whereby they might interfere with shaping occupational injustice. Method. Mixed methodologies were incorporated. The living difficulty scale for refugees (LDSR) was disseminated. Semistructured interviews were conducted, and fieldnotes were collected as sources of qualitative data. Results. 254 participants (mean age

36.2
±
9.6

 yrs; 159 females and 95 males) completed the survey, and nine of them participated in the semistructured interviews. Age (

p
<
0.01

), region (

p
<
0.001

), and time in the United States (

p
<
0.05

) had significant effects on the experiences of the participants, but not gender (

p
=
0.308

). Occupational injustice is an outcome of an interaction between interpersonal and contextual factors. Practice Implications. Occupational therapists need to assume a vital role in maximizing opportunities of engagement in meaningful occupations for Syrian refugees to counteract occupational injustice and difficulties associated with resettlement.
Jiawei Yanghe Decoction Regulates Bone-Lipid Balance through the BMP-SMAD Signaling Pathway to Promote Osteogenic Differentiation of Bone Mesenchymal Stem Cells
Authors: Luo Yunfeng , Xia Hanting , Wang Jiacai , Hu Qian , Luo Yinghua , Liu Jiangyuan , Yang Zhijun , Li Wei , Wang Hongyu , Li Fuwei , Mao Zhaochong , Yang Wenlong , Yang Fengyun
Published: June 2022

Background. The Jiawei Yanghe decoction (JWYHD) is a traditional Chinese medicine formula for the treatment of osteoporosis, but its therapeutic mechanism has not been fully elucidated, and the therapeutic target of the intervention disease needs to be further verified. The dysfunction of bone mesenchymal stem cells (BMSCs) is considered to be an important pathogenesis of postmenopausal osteoporosis (PMOP). The purpose of this study was to explore how JWYHD regulates BMSC differentiation through the BMP-SMAD signal pathway. Methods. In the in vivo study, we used an ovariectomized PMOP rat (n = 36, 2-month-old, 200 ± 20 g) model and femur micro-CT analysis to study the effect of JWYHD on bone loss in rats. By immunofluorescence, the translocation expression of BMP2, a key protein in the pathway, was detected. Serum bone metabolism was detected by an enzyme-linked immunosorbent assay (ELISA). Alkaline phosphatase (ALP) activity was detected by alkaline phosphatase staining (ALPS), osteogenesis and matrix mineralization were detected by alizarin red staining (ARS), the adipogenic ability of BMSCs was detected by oil red staining (ORS), and CFU is used to detect the ability of cells to form colonies. The expression of related proteins was detected by western blotting. Results. In vivo and in vitro, the OP phenotypes of SD rats induced by ovariectomy (OVX) included impaired bone mineral density and microstructure, abnormal bone metabolism, and impaired MSC differentiation potential. JWYHD treatment reversed this trend and restored the differentiation potential of MSCs. JWYHD medicated serum and direct intervention of drugs activated the BMP-SMAD signaling pathway, promoted the osteogenic differentiation of BMSCs, and inhibited their adipogenic differentiation. Conclusions. Our data identified that JWYHD is an effective alternative drug for the treatment of PMOP that functions to stimulate the differentiation of BMSCs into osteoblasts in the BMP-SMAD signaling-dependent mechanism.
[Retracted] Silencing of Long Noncoding RNA HLA Complex P5 (HCP5) Suppresses Glioma Progression through the HCP5‐miR‐205‐Vascular Endothelial Growth Factor A Feedback Loop
Authors: Cheng Rui , Ji Lei , Su Haiyang , Wang Lijun , Jia Ding , Yao Xiaohui , Ji Hongming
Published: June 2022

Long noncoding RNA (lncRNA) HLA complex P5 (HCP5) is correlated with multiple diseases, especially cancers. However, it remains to be further studied whether HCP5 is involved in the malignant behaviors of gliomas. This study is aimed at investigating the role and regulation mechanisms of HCP5 in gliomas. HCP5 expression in glioma tumor tissues and its association with glioma patients’ survival were analyzed based on RNA‐sequencing data. The expression of HCP5 was also examined in glioma cells. Then, HCP5 was downregulated in U251 cells and/or primary glioblastoma cells to explore its effects on cell proliferation and migration. The influence of HCP5 downregulation on tumor growth was confirmed in xenograft mice. About the mechanism, we investigated whether HCP5 functioned via interacting with microRNA‐ (miR‐) 205 and regulating vascular endothelial growth factor A (VEGF-A) expression in gliomas. Results showed that HCP5 upregulation was found in glioma tissues and cell lines. Patients with high HCP5 expression showed lower survival probability and shorter survival time. HCP5 downregulation inhibited cell proliferation and migration and mitigated tumor growth. miR‐205 was downregulated in glioma cells. Knockdown of HCP5 led to miR‐205 upregulation and VEGF-A downregulation. miR‐205 overexpression exhibited the similar effects as HCP5 downregulation on cell viability and proliferation. And VEGF-A overexpression could reverse the effects of HCP5 downregulation on cell viability and proliferation, as well as tumor growth. In conclusion, HCP5 silencing suppressed glioma progression through the HCP5‐miR‐205‐VEGF-A feedback loop.
Network Traffic Forecasting in Network Cybersecurity: Granular Computing Model
Authors: Alzahrani Ali , Aldhyani Theyazn H. H , Alsubari Saleh Nagi , Alghamdi Ans D.
Published: June 2022

Industry 4.0, also known as the Internet of Things, is a concept that encompasses the joint applicability of operation, the Internet, and information technologies to expand the efficiency expectation of automation to include green and flexible processes and innovative products and services. Industrial network infrastructures must be modified to accommodate extra traffic from a variety of technologies in order to achieve this integration. In order to successfully implement cutting-edge wireless technologies, high-quality service (QoS) must be provided to end users. It is thus important to keep an eye on the functioning of the whole network without impacting base station throughput. Improved network performance is constantly needed, even for already-deployed cellular networks, such as the 4th generation (4G) and 3rd generation (3G). For the purpose of forecasting network traffic, an integrated model based on the long short-term memory (LSTM) model was used to combine clustering rough k-means (RKM) and fuzzy c-means (FCM). Clustering granules derived from FCM and RKM were also utilized to examine the network data for each calendar year. The novelty of our proposed model is the integration of the prediction and forecasting results obtained using existing prediction models with centroids of clusters. The WIDE backbone network’s live network traffic statistics were used to evaluate the proposed solution. The integrated model’s outcomes were assessed using a variety of statistical markers, including mean square error (MSE), root mean square error (RMSE), and standard error. The suggested technique was able to provide findings that were very accurate. The prediction error of LSTM with FCM was less on the basis of the MSE of 0.00783 and RMSE of 0.0885 at the training phase, where the prediction values of LSTM with the RKM had an MSE of 0.00564 and RMSE of 0.7511. Finally, the suggested model may substantially increase the prediction accuracy attained using FCM and RKM clustering.
Study on Decarburization Mechanism and Law of GCr15 Bearing Steel during Heat Treatment
Authors: Wang Hui , Su Fuyong , Wen Zhi
Published: June 2022

In order to understand the effects of heating temperature and holding time on decarburization of GCr15 bearing steel, an experimental device for heat treatment of bearing steel was designed and the sample was heated and held by a tubular heating furnace. The microstructure and depth of decarburized layer of bearing steel under various working conditions were observed and measured by a metallographic microscope. The results show that the total decarburization depth increases with the increase of temperature; almost no decarburization occurred below 700°C; ferrite decarburization occurred at 750°C; partial decarburization began to occur at 820°C; after 900°C, the decarburization layer is mainly partial decarburization. When the heating temperature is below 1000°C, the depth of total decarburization layer increases slowly and increases rapidly after 1000°C. The total depth of decarburization layer is directly proportional to the square root of holding time. The relationship between the depth of the total decarburization layer of bearing steel and the heating temperature and holding time in the annealing process was obtained.
CD96 Downregulation Promotes the Immune Response of CD4 T Cells and Associates with Ankylosing Spondylitis
Authors: Wu Fengqing , Yang Huan , Xu Xiao , Ren Conglin , Zheng Yang , Zhang Helou , Cai Bingbing , Qiu Rui , Ren Weifan , Quan Renfu
Published: June 2022

Inhibitory receptors (IRs) play an indispensable role in regulating T cell activation and expansion. This study is aimed at exploring the correlation between IRs and ankylosing spondylitis (AS). Bioinformatics analysis of two datasets (GSE25101 and GSE73754), including 68 AS cases and 36 healthy controls, demonstrated that “T cell receptor signaling pathway” was significantly enriched, and two IRs (CD112R and CD96) were downregulated in AS cases. Real‐time Quantitative PCR Detecting System (qPCR) analysis confirmed the decreased expression of CD112R and CD96 in the peripheral blood of AS patients. Flow cytometry demonstrated that the frequency of CD96‐positive cells among CD4 T cells in AS patients was significantly reduced and that expressed on the cells was also significantly lower than the healthy controls. In addition, the expression of CD96 was altered on human primary CD4 T cells extracted from 3 healthy volunteers and cocultured with allogeneic dendritic cells (DCs). Also, low expression of CD96 elevated the phosphorylation of ERK in CD4 T cells and increased the level of TNF‐α, IL‐23, IL‐17A, IL‐6, and IFN‐γ in the cell culture supernatant. These results suggested that CD96 is crucial for the pathogenesis of AS and may be a potential target in the treatment of the disease.
Prediction of Metro Train‐Induced Tunnel Vibrations Using Machine Learning Method
Authors: Xu Zhuosheng , Ma Meng , Zhou Zikai , Xie Xintong , Xie Haoxiang , Jiang Bolong , Zhang Zhongshuai
Published: June 2022

The tunnel vibration level is usually employed as a vibration source intensity of the empirical prediction method. Currently, the analogy test and data base are two main means to determine the vibration source intensity. To improve the accuracy efficiency, the machine learning (ML) method was introduced to predict the tunnel vibration responses. To acquire model training samples, the measurements were performed in 80 different running tunnel sections of Beijing metro lines. Two types of method, back propagation neural network (BPNN) and generalised regression neural network (GRNN) were employed, which can make full use of characteristics of measured samples and reduce the data noise. The results indicate that the prediction efficiency is high and the mean square errors of the two ML methods are acceptable. Accordingly, both of the ML methods can be used as the reference of vibration source intensity in metro train‐induced environmental impact evaluation. GRNN has relatively better predicting ability than BPNN.
Combination of the NRF2 Inhibitor and Autophagy Inhibitor Significantly Inhibited Tumorigenicity of Castration-Resistant Prostate Cancer
Authors: Zhang Yong , Xin Zhixiang , Dong Baijun , Xue Wei
Published: June 2022

Prostate cancer (PCa) is the most frequent cancer in men. Developing new treatment methods for CRPC will be a significant challenge in the clinical treatment of PCa. In conclusion, the results of this study show that NRF2 is downregulated in untreated PCa samples compared to normal PCa samples; however, it was upregulated in mCRPC samples compared to HSPC samples. These results demonstrated that NRF2 may serve as a tumor suppressor in tumorigenesis but promote PCa androgen-independent transferring after ADT treatment. Bioinformatics analysis showed that NRF2 was related to multiple signaling, such as the AGE-RAGE pathway, MAPK pathway, NF-kappa B signaling, PI3K-Akt signaling pathway, and VEGF signaling pathway. Moreover, we revealed that the NRF2 inhibitor significantly inhibited tumorigenicity of CRPC cells in vitro. Of note, combination of the NRF2 inhibitor and autophagy inhibitor had a more significantly suppressive role than either ML385 or CQ, indicating that combination of CQ (autophagy inhibitor) and ML385 (NRF2 inhibitor) is a potential treatment of CRPC. Finally, we conformed that high levels of autophagy regulators LC3B, ULK1, and beclin1 significantly correlated to longer PSA recurrence-free survival time. We think that this study could provide more evidence to confirm that NRF2 is a crucial regulator and targeting NRF2 and autophagy is a potential therapy option for CRPC.
Construction of the Evaluation Index System of Physical Education Teaching in Colleges and Universities Based on Scientific Knowledge Graph
Authors: Wang Chang , Xu Shuangshuang
Published: June 2022

The purpose of physical education (PE) teaching in general institutions of higher education is to enhance students’ fitness and mental quality, which in turn improves students’ physiological ability and sports skills and finally enables students to develop healthy lifestyle. The conventional assessment of students’ PE instruction only focuses on the evaluation of their body condition and sports skills, ignoring the cultivation of their mental and physical development and healthy living habits and evaluating students with a relatively single evaluation standard, lacking the cultivation of “teaching to suit the individual.” At present, the evaluation method of instructional quality of PE teachers in China’s institutions of higher education is relatively single and dominated by qualitative methods, which cannot be applied to instructional innovation. The evaluation of physical education teaching quality plays an important role in building a complete and effective teaching process, which plays an important role in judging whether the formulation of physical education teaching objectives and principles is reasonable, and the evaluation of students’ learning behavior and learning effect. This article takes the relevant theory of scientific knowledge graph as the guiding idea, based on the current situation of PE teaching assessment in institutions of higher education, and employs experimental research methods to conduct empirical studies on 10 universities in Jilin Province. The empirical findings suggest that students’ satisfaction with the new evaluation method is 83.68 points on average, and the accuracy rate is 84.54 points on average; teachers’ satisfaction with the new evaluation method is 86.12 points on average, and the accuracy rate is 88.4 points on average.
Research on SLAM Road Sign Observation Based on Particle Filter
Authors: Wang Yifan , Wang Xiaoyan
Published: June 2022

With the development of computer hardware technology, the real-time problem of visual target tracking algorithm increasingly depends on hardware solutions. The core problem of visual target tracking is how to enhance the robustness of tracking algorithm to various complex background environments and various interference factors. Aiming at overcoming the defect that the traditional SLAM (simultaneous localization and map building) algorithm based on EKF (extended Kalman filter) has a slow repair speed for environmental interference, a Monocular SLAM_WOCPF (Monocular vision SLAM based on weight optimization combined particle filter) algorithm is proposed. The weights of all particles are reoptimized in the particle set and they are combined with the tendency of particles to degenerate and deplete. In this way, the chance of self replication of low weight particles is increased, thus increasing the diversity of the whole sample. Furthermore, the improved PF (particle filter) algorithm is applied to solve the problem of road sign observation of mobile robots, so as to expand its application scope. The results show that the mean road sign errors of the Monocular SLAM_WOCPF algorithm in two noise environments are 0.332/m and 0.441/m. The conclusion shows that the Monocular SLAM_WOCPF road sign observation method proposed in this paper can effectively improve the matching success rate of visual road signs and improve the observation quality.
A New Self-Assessment “TQM Hybrid MCDM Fuzzy Model” For Enhancing the KPIs in Mega Universities
Authors: Ragab Abdul Hamid M. , Noaman Amin Y. , Gad-Elrab Ahmed A. A. , Abdul Fatah Ezz H.
Published: June 2022

The key performance indicators (KPIs) are an effective part of benchmarking for measuring the performance of universities aiming to raise the university quality services level. The problem is that there is no general standard analytical evaluation model for assessing KPIs criteria in higher education institutes for evaluating mega universities, and there are inadequacies in the treatment of specific current educational quality standards. In this paper, a hybrid fuzzy analytical model for TQM self-assessment to enhance KPIs in mega universities is proposed. The proposed model produces important weights for TQM-KPIs that are recommended for helping higher authorities at the university for enhancing the demanded total quality services and aid the university to achieve its strategic objectives and to be one of the highly ranked universities. In addition, the European Foundation for Quality Management (EFQM) excellence model enabler criteria were modified and used. Two additional enabler criteria for representing the mega university and the world ranking were proposed. The “TQM Hybrid Fuzzy Model” proposed integrates three fuzzy multiple criteria decision-making (MCDM) submodels including (1) the fuzzy analytic hierarchy process (FAHP), (2) the fuzzy decision-making trial and evaluation laboratory (FDEMATEL), and (3) the fuzzy multiple criteria decision analysis (FVIKOR). Each of these submodels is computed and evaluated analytically. A comparison between them is achieved. Finally, the whole “TQM Hybrid F-MCDM Model” proposed is proved and evaluated analytically and programmed using Excel. Hence, by comparison, it is found that the proposed hybrid fuzzy model is the most effective model for evaluating the TQM-KPIs for enhancing mega universities’ organizational assessment. Results show that the subcriteria that occupied the first three positions are the managed and improved distance learning sources and materials, policy, and strategies that are based on the present and future needs and expectations of stakeholders.
A Case of Cervical Intraneural Lipoma That Was Removed by Intercapsular Resection with No Resultant Postoperative Neurological Deficit
Authors: Sato Hitoshi , Saito Yoshiro , Kitajima Tatsuya , Egawa Shunya , Shimane Toshikazu
Published: June 2022

Intraneural lipomas in peripheral nerves of cervical lesions are extremely rare and have not been previously reported. We present a 48-year-old male with a gradually increasing right cervical mass since 5 years. He visited our department because of pain and difficulty in raising the right upper limb. A tumor about 80 mm in size was palpable in the right neck along the cervical nerve. The tumor was suspected to involve fatty degeneration in schwannoma of cervical nerve origin, for which intercapsular resection was performed under general anesthesia. Histopathologically, bifurcated growth of mature adipocytes with sparse fibrous septa and lack of tumor proliferation of Schwann cells was observed on H&E staining, suggesting a diagnosis of intraneural lipoma. The patient had no new motor or sensory deficits postoperatively and with improvement in his preoperative symptoms.
Mechanical and Durability Performance of High‐Strength Concrete with Waste Tyre Steel Fibres
Authors: Augustino Daudi Salezi , Onchiri Richard Ocharo , Kabubo Charles , Kanali Christopher
Published: June 2022

Concrete with various fibres has been in practice over the years now to improve the internal characteristics of concrete. In most of the developing countries, there is a high rate of waste tyres due to the importation of used cars. Waste tyres increase the environmental burden due to their resistance to decomposition in landfills. To have alternative disposal of waste tyres, their components of steel fibres were utilized in concrete to assess their effect on the mechanical and durability performance of high‐strength concrete with a target mean strength of 70 MPa. Fibres had a diameter of 1.3 mm and lengths of 30, 50, and 60 mm with fibre contents of 0.3, 0.5, 0.75, and 1.0% in each length. Slump tests were performed on fresh concrete with and without fibres. The mechanical performance variables assessed were compressive strength, splitting tensile strength, flexural strength, flexural toughness, residual strength, static modulus, and Poisson’s ratio. In addition, durability tests such as chloride ion penetration and absorption rate of water were investigated. The results showed that an increase in fibre length to 60 mm and a 1.0% fibre content resulted in the high bond strength in the concrete matrix resulting in a smaller crack width. Moreover, these fibre length and content resulted in improved tensile and flexural strength to 21.5% and 71.1% of control mix, respectively. The increase in fibre length and content affected both the durability properties and the flowability of the concrete, and as for length (60 mm) and 1% content, concrete had a slump of 77.8% lesser compared to the control mix. The compressive strength was improved to 15.2% for concrete with a fibre length of 50 mm and a fibre content of 0.5%. However, further increases in fibre content and length caused an increase in the number of weaker interfacial transition zones at the composite interface that reduces compressive stiffness, resulting in low compressive strength. Furthermore, the reduced fibre content and length (30 mm) improve the static modulus linearly up to 0.75% fibre content; however, concrete with a fibre length of 50 mm and content of 0.3% gives the best results.
Antiviral Therapy for a Postpartum Flare in Women with Chronic HBV Infection Shortens the ALT Recovery Time and Reduces Hepatitis Re-Flare Rates within 4 years
Authors: Quan Min , Liu Cong , Li Wei , Xing Hui-Chun
Published: June 2022

Background. Few studies explored whether anti-hepatitis B virus (HBV) therapy should be initiated during postpartum hepatitis flare. Aim. This study aimed to analyze the effect of anti-HBV therapy on postpartum hepatitis flare and evaluate the prognosis within 4 years postpartum. Methods. This retrospective study enrolled hepatitis B surface antigen (HBsAg)-positive and hepatitis B e antigen (HBeAg)-positive pregnant women with HBV DNA ≥ 106 IU/mL. A total of 152 pregnant women were included: 103 in the prophylactic anti-HBV therapy group (PT-G) and 49 in the non-prophylactic anti-HBV therapy group (NPT-G). The women with a postpartum flare were assigned to the anti-HBV therapy group (AT-G) and non-anti-HBV therapy group (NAT-G) to analyze the effect of postpartum anti-HBV therapy on hepatitis flare. Virological and biochemical parameters were assessed. Results. Taking postpartum 12 weeks as the cutoff point, the ALT recovered time for postpartum flare women is shorter in AT-G (n = 16, 42.1%) or PT-G (n = 23, 34.8%) than in NAT-G (n = 14, 23.0%; x2 = 4.067,P=0.044) or NPT-G (n = 4, 11.1%; x2 = 5.579,P=0.018). Taking postpartum 26 weeks as the cutoff point, the ALT recovered time is shorter in AT-G (n = 35, 57.3%) or PT-G (n = 44, 66.7%) than in NAT-G (n = 32, 84.2%; x2 = 7.707,P=0.006) or NPT-G (n = 16, 44.4%; x2 = 4.749,P=0.029). Postpartum flare recovery time was positively correlated with HBV DNA level at delivery [r = 0.223,P=0.025, 95%CI (0.022～0.41)]. The hepatitis re-flare rates within postpartum 4 years in AT-G (n = 3, 9.68%) is lower than that in NAT-G (n = 24, 45.4%; x2 = 14.003,P≤0.001). The HBeAg, HBsAg, HBV DNA, and ALT level at postpartum 4 years in AT-G were lower than that in NAT-G (P<0.001). Conclusion. Anti-HBV therapy for postpartum hepatitis flare of women with chronic HBV could shorten the ALT recovery time and reduce hepatitis re-flare rates within 4 years of postpartum.
On a Classification of Almost C(α)‐Manifolds
Authors: Mert Tuğba
Published: June 2022

In this paper, pseudosymmetric and Ricci pseudosymmetric almost C(α)‐manifold are studied. For an almost C(α)‐manifold, Riemann pseudosymmetric, Riemann Ricci pseudosymmetric, Ricci pseudosymmetric, projective pseudosymmetric, projective Ricci pseudosymmetric, concircular pseudosymmetric, and concircular Ricci pseudosymmetric cases are considered and new results are obtained.