bluuebunny/crossref_metadata_2025 huggingface dataset:
Application of Internet of Things and Data Optimization in the Design of Smart Medical Park
Authors: Liao Jiacheng , Zhong Yingxin
Published: July 2022

The ecological development of industrial parks has become a concern in current urban planning. The traditional development model and development ideas of pharmaceutical industrial parks need to be changed urgently, not only to improve their own functions but also to use land more effectively and save resource costs. Aiming at the problems existing in the construction of the park, this paper studies the use of the Internet of Things technology to build a smart park platform to realize the access of intelligent systems and equipment in the park. First of all, starting from the background of the combination of smart parks and the Internet of Things, by analyzing the architecture of the Internet of Things, it studies the requirements for the combination of smart parks and the Internet of Things technology. Second, according to the results of the demand analysis, we conducted a research on the construction plan of the smart park in the Internet of Things era, including the construction of the smart park platform using the Internet of Things technology, the ideas and access methods of the intelligent system access platforms in the smart park, and the research on the construction of the intelligent park platform architecture based on the Internet of Things and decision tree technology. Finally, the specific implementation process of its access to the smart campus platform is studied through simulation tests, and the feasibility of the access method is verified.
Component Composition and Biological Activity of Various Extracts of Onosma gmelinii (Boraginaceae)
Authors: Shilov Sergey V. , Ustenova Gulbaram O. , Kiyekbayeva Lashyn N. , Korotetskiy Ilya S. , Kudashkina Natalia V. , Zubenko Natalya V. , Parenova Raikhan A. , Jumagaziyeva Ardak B. , Iskakbayeva Zhanar A. , Kenesheva Sabina T.
Published: July 2022

Onosma roots are widely used in traditional medicine to treat various diseases throughout the world. In this study, for the first time, we investigated the component composition and biological activity of various extracts from the roots of Onosma gmelinii collected in the highlands of the Kakpakty Mountains of the Almaty region (Republic of Kazakhstan). Extracts were obtained by three different methods: percolation extraction, ultrasound-assisted extraction, and supercritical carbon dioxide extraction. The component composition of the extracts was determined by gas chromatography/mass spectrometry (GC/MS), naphthoquinones by thin-layer chromatography (TLC), and spectrophotometric method. In this study, the presence of shikonin and its derivatives in the extracts was confirmed. The concentration of naphthoquinones during CO2 extraction was about 40%, during ultrasonic extraction about 3%, and during percolation extraction about 1.3%. The GC-MS method identified 69 chemical compounds in the ultrasonic extract, 46 compounds in the CO2 extract, and 51 compounds in the percolation extract. The extracts were tested on a panel of bacteria and viruses: two Gram-negative bacteria (Escherichia coli ATCC 8739, Pseudomonas aeruginosa ATCC 9027); nine Gram-positive bacteria (Staphylococcus aureus ATCC 6538-P, Staphylococcus aureus ATCC BAA-39, Staphylococcus epidermidis ATCC 51625, Staphylococcus epidermidis ATCC 12228, Streptococcus pyogenes ATCC 19615, Streptococcus pneumoniae ATCC BAA-660, Enterococcus hirae ATCC 10541, Enterococcus faecalis ATCC 51575, Enterococcus faecium ATCC 700221); and two fungal species (Candida albicans ATCC 10231, Candida albicans ATCC 2091); five subtypes of influenza virus A (A/FPV/Weybridge/78 (H7N7), A/Swine/Iowa/15/30 (H1N1), A/black-headed gull/Atyrau/743/04 (H13N6), A/FPV/Rostock/1934 (H7N1), A/Almaty/8/98 (H3N2)). The root extracts of Onosma gmelinii showed antibacterial activity in different degrees against all tested Gram-positive bacterial strains, while no inhibitory effect on Gram-negative bacteria was observed. The results indicated that the ultrasonic extract effectively inhibits the growth of the majority of tested Gram-positive bacteria (MBC from 18.3 to 293.0 µg/mL). CO2 extract had the greatest bactericidal activity (MBC from 0.1 to 24.4 µg/mL). Percolation extract insignificantly inhibited bacterial growth (MBC from 2343.8 to 4687.5 µg/mL). CO2 extract and ultrasonic extract significantly reduced the activity of C. albicans. The results of the antiviral action showed that the ultrasonic extract has the greatest effectiveness against different subtypes of the influenza virus A, while other extracts did not show significant activity.
Seventy-Day Toxicity Study in Juvenile Sprague-Dawley Rats with Semicarbazide (SEM) from Weaning to Sexual Maturity
Authors: Malashetty Vijaykumar , Deshpande Raghunandan , Patil Somnathreddy
Published: July 2022

The study was conducted to evaluate the toxicological effects, functional observation battery tests, and sexual maturity of semicarbazide oral gavage administration to juvenile Sprague-Dawley rats for 70 days at 0, 15, 30, and 60 mg/kg/day weaning to sexual maturity. At 60 mg/kg/day, there was a delay in mean age at acquisition of balano-preputial and vaginal patency and a decrease in body weight and food consumption in males. Treatment increased reticulocyte count, aspartate aminotransferase, and alanine aminotransferase levels in both sexes and decreased hematocrit and protein in males. Increased absolute and relative liver and spleen weight in both sexes were observed. Male rats had lower thymus and testes weights, whereas female rats had lower uterine weights. Semicarbazide caused significant changes in sperm motility, sperm count, and sperm abnormality. Histopathologically, semicarbazide caused cortical hypertrophy in adrenals and increased extramedullary hematopoiesis in the spleen; hepatocellular hypertrophy, follicular epithelial hypertrophy in the thyroid, and degeneration of seminiferous tubules in the testis were observed at 60 mg/kg/day when compared to control. Results suggest that 60 mg/kg/day of semicarbazide can exert systemic toxicity in juvenile rats. The no observed adverse effect level (NOAEL) of semicarbazide for juvenile Sprague-Dawley rats was estimated to be 30 mg/kg/day.
Decentralized Power Control for an ALOHA-Type Random Multiple Access System with Short Packet Transmission
Authors: Tian Ni , Li Changle , Cheng Jun , Yue Wenwei , Luo Maofeng
Published: July 2022

Machine to machine communication is an important scenario in a 6G communication network. Random multiple access has recently been revisited and considered a key technology for machine to machine communication scenarios due to many advantages such as without coordination setup time. It is a regret that packet collision probability will be extremely higher for random multiple access when massive devices randomly accessing base station. Decentralized power control is an efficient scheme in random multiple access systems which can support intraslot successive interference cancellation to recover multiple collided packets at receivers. However, existing studies of decentralized power control for random multiple access are with the assumption that blocklength of transmitted packets is infinite, which neglects that machine to machine communication is characterized by finite blocklength transmission (i.e., short packet) in 6G. This paper focuses decentralized power control with short packet transmission in random multiple access systems. First, the closed-form expression of signal to interference plus noise ratio (SINR) threshold for short packets is derived. Then, decentralized transmission power profile is defined based on derived SINR threshold of short packets, which can support intraslot successive interference cancellation deciding at receivers for an ALOHA-type random multiple access system. Further, we propose derivation method to maximize system throughput, which can reduce optimization cost. Theoretical findings in this paper can provide valuable benchmark for short packet transmission with decentralized power control in random multiple access systems.
Construction of Rural Tourism Brand Value Management Model from the Perspective of Big Data
Authors: Wang Wenlong , Wu Daihanyu
Published: July 2022

Rural tourism has become an important branch of tourism management. Big data technology provides tools for rural tourism brand value management. This study aims to build a brand value management model for rural tourism from the perspective of big data. The rural tourism brand value management model under the big data perspective takes the rural tourism brand competitiveness as the starting point to analyze the relationship between brand value and brand competitiveness, so that the brand competitiveness under the perspective of rural tourism brand value has a more specific and quantifiable index system. From the two aspects of enterprise value advantage and customer value advantage, this article looks for the factors that comprehensively reflect the brand competitiveness of rural tourism. After the establishment of the index system, the BP neural network model is used to make the multiple factor evaluation more objective and feasible. Finally, it is proposed to enhance the competitiveness of rural tourism brands from the perspective of the reconstruction of competitive advantage based on enterprise value and the reconstruction of competitive advantage based on customers.
Application of SDN Network Traffic Prediction Based on Speech Recognition in Educational Information Optimization Platform
Authors: Zheng Susheng , Yang Shengxue
Published: July 2022

This paper constructs a SDN network traffic prediction model based on speech recognition and applies it to the educational information optimization platform. By analyzing the influencing factors of SDN network equipment, communication links, and network traffic, this paper constructs the initial index set of SDN network traffic situation. In the data plane of SDN, the queue management algorithm is used to control the flow. On this basis, an IRS mechanism is proposed based on the advantages of SDN centralized control and the difference of transmission performance requirements between large and small streams. For the transmission of large traffic, IRS adopts greedy routing and multipath routing based on the remaining bandwidth to make the traffic evenly distributed in the network, and IRS adds the scheduling strategy based on IP addressing to avoid packet disorder. Simulation results show that the effectiveness of this algorithm can reach 95.67% at the highest, and the MSE convergence is 0.0021 at the lowest. At the same time, this method completes the quantitative evaluation of SDN network traffic situation, effectively solves the problem that SDN traffic situation labels cannot be determined, and opens a new vision of global state observation for SDN network management. This research can provide some technical support for the educational information optimization platform.
Femoral Head Coverage Assessment in Healthy Children Younger than 6 Years
Authors: Vasyl Suvorov , Viktor Filipchuk , Evhen Zyablovskyi
Published: July 2022

Introduction. Developmental dysplasia of the hip (DDH) is one of the commonest hip joint pathologies in children; to treat it properly, hip surgeons should know the normal femoral head (FH) coverage by the acetabulum. This paper aims to assess the femoral head coverage in healthy children younger than 6 years. Methods. 270 hip joint CT scans were selected, and digital pelvic models were created according to these scans. FH coverage by the five acetabular regions was assessed according to patient’s age and sex. Results. Normal reference values of FH coverage by different acetabular regions were obtained. It was found that the growth process of different acetabular regions occurs nonlinearly with the periods of acceleration. Anterior and superior-anterior acetabular regions grow more intensively in boys up to 3 years old and between 4 and 5 years old both in boys and girls; superior-posterior, posterior-superior, and posterior-inferior acetabular regions grow more intensively in boys and girls up to 3 years old and between 4 and 5 years old (

p
≤
0.005

). The following sex differences in FH coverage by the acetabulum were found: more superior-anterior FH coverage was found in boys and posterior FH coverage in girls (

p
≤
0.005

).
Novel Mutations in the MKKS, BBS7, and ALMS1 Genes in Iranian Children with Clinically Suspected Bardet–Biedl Syndrome
Authors: Dehghan Roghayeh , Behnam Mahdiyeh , Salehi Mansoor , Kelishadi Roya
Published: July 2022

Bardet–Biedl syndrome is a rare autosomal recessive form of syndromic obesity which is characterized by retinal degeneration, obesity, polydactyly, cognitive impairment, and renal and urogenital anomalies. In this study, we used whole-exome sequencing (WES) to investigate the underlying mutations in four Iranian children from consanguineous families with a clinical diagnosis of Bardet–Biedl syndrome (BBS). In three out of four children, we identified one previously reported frameshifting variant in the BBS12 gene (c.265-266delTT, p.L89fs) and two novel nonsense variants in MKKS (c.1196T>G, p.L399X) and BBS7 genes (c.1636C>T, p.Q546X). In the other child, no mutations were detected in known genes for BBS. However, we identified a novel variant in the ALMS1 gene (c.10996delC, p.Q3666fs) indicative of Alström syndrome. All variants were interpreted as pathogenic according to American College of Medical Genetics and Genomics (ACMG) guidelines and confirmed through Sanger sequencing. In conclusion, our results not only expand the spectrum of mutations in BBS and ALMS1 genes but also accentuate the importance of genetic testing for differentiating BBS from Alström syndrome.
Evaluation Algorithm of Volleyball Players’ Competitive Ability Based on the Random Matrix Model
Authors: Wang Tailin , Zheng Hua , Li Fangshu , Jia Nian , Cai Zengliang
Published: July 2022

It is the trend of the development of modern competitive sports to put scientific and technological analysis methods and means into the study of volleyball, and it is also one of the powerful guarantee ways to promote the competitive level of all countries. The random matrix model algorithm has unique advantages to construct the team’s collective technical and tactical ability structure model. The quantitative relationship of the model describes the relationship between the technical and tactical ability structure and the result of victory and defeat and makes the advantages and disadvantages of the team clear, which is conducive to the subsequent targeted training and improvement. The technical and tactical abilities of the teams in different seasons were input to verify the prediction accuracy of the model for the teams in different seasons. In the face of the rapidly changing game situation, the coach team timely transmits the adjusted technical and tactical strategies to the players on the field and deals with the changes accurately and effectively. After the game, the opponent’s strengths and weaknesses should be clarified, and the team’s daily training details should be summarized to provide reference for the cultivation of collective technical and tactical consciousness. The random sample covariance matrix of the random monitoring matrix is constructed and the maximum and minimum eigenvalues of the sample covariance matrix are solved. The ratio of characteristic values is used to construct the detection index of characteristic values, and the detection threshold algorithm of characteristic values is determined to judge the competitive ability of volleyball players. In the case of false alarm rate and matrix size, based on Tracy-Widom distribution characteristics, the maximum eigenvalue and minimum eigenvalue approximations of sample covariance matrix are used to improve the eigenvalue index detection threshold algorithm, and the influence of false alarm rate, matrix size, and other parameters on the improved eigenvalue index detection threshold is further studied. Then, Iris data set was used to verify the effectiveness of the algorithm in terms of accuracy, recall rate, and comprehensive effective value, and the validation results proved that the accuracy of the algorithm reached more than 90%.
In-Plane Interactive Buckling of High Strength Steel Welded Wide Web I-Section Beam-Columns
Authors: Liang Pei Xin , Huang Bin
Published: July 2022

A numerical investigation on the overall-local interactive buckling performance of high strength steel (HSS) wide web I-section members was conducted using finite element (FE) models verified against experimental data. The effect of overall slenderness, the height-thickness ratio of the web

h

w

/

t

w

, and the width-thickness ratio of the flanges (bf/tf) on ultimate load was parametrically analyzed. The result demonstrated that (i) for the beam-columns with higher steel grade, the Pz-Uz curve presents a relatively obvious deformation plateau, meaning a certain degree of ductility. (ii) The ultimate load decreased essentially linearly resulting from higher

h

w

/

t

w

, and the trend was graphically consistent under various steel grades. (iii) bf/tf lower than 0.6 led to the failure mode of shearing buckling, and the corresponding ultimate load increased with an increase of bf/tf. In the case of bf/tf greater than 0.6, the ultimate load decreased as a result of the higher bf/tf. Based on the concept of the direct strength method, the local postbuckling strength prediction formula was fitted with stub beam-column FE results and examined with experiment data. The correlation formula of compression and bending moment was proposed to evaluate the resistance of the interactive buckling of the HSS wide web I-section underpinned by the FE results of beam-columns with intermediate length and experiment data.
Baicalin Inhibits Inflammation in Rats with Chronic Obstructive Pulmonary Disease by the TLR2/MYD88/NF-κBp65 Signaling Pathway
Authors: Ju Jiangang , Li Zheming , Shi Qiang
Published: July 2022

Objective. Chronic obstructive pulmonary disease (COPD) is a chronic inflammatory disease with a relatively high morbidity and death rate. This study aimed to investigate the inhibitory effect of baicalin (BA) on inflammation in COPD rats and its possible mechanism. Methods. The experimental COPD of SD rats were induced by LPS, smoking, and cold stimulation, and they were randomly divided into the control group, COPD group, COPD + LB group, COPD + MB group, and COPD + HB group. The test of pulmonary function and the HE staining were carried out in COPD rats. The levels of TNF-α, IL-1β, IL-6, IL-10, and IL-8, as well as GSH, SOD, and MDA in serum, were detected by ELISA. The levels of TLR2, MYD88, TNF-α, and IL-1β mRNA in BALF were detected by qPCR. The expression of TLR2/MYD88/NF-κBp65 pathway-related proteins was also detected by the Western blot and immunohistochemistry assays. Results. Compared to the COPD model group, BA treatment significantly improved the pulmonary function and pathologic changes, reduced the levels of TNF-α, IL-1β, IL-6, IL-10, IL-8, and MDA, and increased the levels of IL-10, SOD, and GSH in COPD rats. In addition, BA could also decrease the protein levels of MYD88, p–NF–κBp65/NF-κBp65, TLR2, and TLR4 but increase the protein level of p-IκBa/IκB in lung tissue of COPD rats. Conclusion. BA ameliorated inflammatory response and oxidative stress in COPD rats by regulating the TLR2/MYD88/NF-κBp65 signaling pathway.
Comparative Impact of Various Exercises on Circulating Irisin in Healthy Subjects: A Systematic Review and Network Meta-Analysis
Authors: Kazeminasab Fatemeh , Sadeghi Erfan , Afshari-Safavi Alireza
Published: July 2022

Irisin is a myokine that is secreted from skeletal muscle during exercise and increases lipid metabolism, converting white adipose tissue to brown adipose tissue. Recent studies have shown conflicting results in relation to chronic and acute exercise and irisin. The aim of this study was to evaluate the effects of chronic and acute exercise training on circulating (plasma/serum) irisin level in healthy subjects. We conducted a search of Cochrane Library, PubMed, ISI, Scopus, Embase, and Pedro up to September 2021. A random effects network meta-analysis was performed to calculate the pooled estimate of standardized mean difference (SMD) for acute and chronic exercise effects on irisin level, using Hedge’s

g

statistic. Of the 16 studies included, six were acute exercise studies (175 participants). The aerobic (Hedge’s

g
=
0.23

; 95% CI: -0.58, 1.03) and the anaerobic exercises (Hedge’s

g
=
0.12

; 95% CI: -0.45, 0.70) were associated with the increased level of irisin, compared to the control. In the ten chronic exercise studies (433 participants), the resistance training was superior to anaerobic and aerobic training (

P

score = 0.632). However, comparing acute and chronic exercise studies, acute training showed the most excellent potential as the best treatment to improve the irisin level (

P

score = 0.721). This network meta-analysis showed that acute aerobic exercise has a more effect on irisin levels than acute anaerobic exercise. Also, chronic resistance training has the greatest additive effect on irisin levels compared to chronic aerobic and anaerobic training.
Identifying a Novel Endoplasmic Reticulum-Related Prognostic Model for Hepatocellular Carcinomas
Authors: Ding Fei , Li Jinping , Zhang Yong , Wang Chengang , Yu Yonghua
Published: July 2022

From the standpoint of the ER (endoplasmic reticulum), we were interested in identifying hub genes that impact clinical prognosis for HCC (hepatocellular carcinoma) patients and developing an ER-related prognostic model. Using TCGA-LIHC (The Cancer Genome Atlas-Liver Hepatocellular Carcinoma) and GSE14520 datasets, we conducted a series of analyses, which included differential gene screening, clinical prognostic analysis, Lasso regression, nomogram prediction, tumour clustering, gene functional enrichment, and tumour infiltration of immune cells. Following our screening for ER-related genes (

n
=
1975

), we conducted a Lasso regression model to obtain five hub genes, KPNA2, FMO3, SPP1, KIF2C, and LPCAT1, using TCGA-LIHC as a training set. According to risk scores, HCC samples within either the TCGG-LIHC or GSE14520 cohort were categorized into high- and low-risk groups. Compared to the high-risk group of HCC patients, patients in the low-risk group had a better prognosis of OS (overall survival) or RFS (relapse-free survival). For TCGA-LIHC training set, with the factors of risk score, stage, age, and sex, we plotted a nomogram for 1-, 3-, and 5-year survival predictions. Our model demonstrated better clinical validity in both TCGA-LIHC and GSE14520 cohorts. Additionally, events related to biological enzyme activity, biological metabolic processes, or the cell cycle were associated with the prognostic risk of ER. Furthermore, two HCC prognosis-associated tumour clusters were identified by ER hub gene-based consensus clustering. Our findings indicated a link between ER prognostic signature-related high/low risk and tumour infiltration levels of several immune cells, such as “macrophages M2/M0” and “regulatory T cells (Tregs).” Overall, we developed a novel ER-related clinical prognostic model for HCC patients.
Determinants of COVID-19 Related Perception among University of Gondar Academic Staff, Gondar, Ethiopia, 2021: A Structural Equation Modeling Approach
Authors: Zewdie Amare , Nigusie Adane , Wolde Maereg , Mazengia Elyas Melaku , Belaineh Haimanot Aysheshim , Habtie Adane , Kassa Anteneh
Published: July 2022

Introduction. Public perceptions of pandemic risk and prevention measures influence adherence to COVID-19 prevention efforts. Even though several factors influence public perceptions, there has been no research on the predictors of COVID-19-related perception in Ethiopia and there are few articles among academic staff worldwide. Thus, this study aims to assess predictors of COVID-19-related perception among Gondar University academic staff. Method. Institutional based cross-sectional study was conducted from April 10 to May 10, 2021. Daniel Soper’s calculator was used to determine the sample size. A simple random sampling technique was employed. Data were collected through a self-administered questionnaire and analyzed using Stata V14. Structural equation modeling was performed to identify determinants of COVID-19 related perception. A

p

value less than 0.05 and a 95% confidence interval of β were used to declare the statistical significance of the variables. Result. A total of 602 academic staff participated. Mean age of participants was 32.38 (±5.83) years. Family size (β = 0.12), chronic illness (β = −0.19), knowledge (β = 0.11), and cues to action (β = 0.43) were significantly associated with perceived susceptibility. Similarly, educational status (β = −0.11), perceived susceptibility (β = 0.61), and cues to action (β = 0.13) were significantly associated with perceived severity. Likewise, knowledge (β = 0.11) and cues to action (β = 0.62) were significant predictors of self-efficacy. Correspondingly, knowledge (β = 0.23), chronic illness (β = 0.09), profession (β = −0.09), perceived susceptibility (β = 0.19), perceived severity (β = 0.23), and self-efficacy (β = 0.29) were significant predictors of perceived benefit. Similarly, age (β = −0.18), profession (β = 0.10), and perceived susceptibility (β = −0.39) were significantly associated with perceived barriers. Conclusion. Several sociodemographic and other factors affect COVID-19 related perceptions. Intervention should consider those factors to improve COVID-19 prevention practice.
Trends in Glycemia between 2002 and 2016 among Incident Youth Cohorts Early in the Course of Type 1 Diabetes: The SEARCH for Diabetes in Youth Study
Authors: Igudesman Daria , Reboussin Beth A. , Souris Katherine J. , Pihoker Catherine , Dolan Lawrence , Lawrence Jean M. , Saydah Sharon , Dabelea Dana , Marcovina Santica , Clouet-Foraison Noémie , Malik Faisal S. , Mayer-Davis Elizabeth J.
Published: July 2022

Objective. Hyperglycemia early in the course of type 1 diabetes (T1D) may increase the risk of cardiometabolic complications later in life. We tested the hypothesis that there were temporal trends in population-level glycemia and insulin pump use near T1D diagnosis among incident youth cohorts diagnosed between 2002 and 2016. Methods. Weighted and adjusted regression models were applied to data from the SEARCH for Diabetes in Youth study to analyze trends in hemoglobin A1c (HbA1c), suboptimal glycemia (

HbA
1
c
>
9
%

or not), and insulin pump use among youth with T1D within 30 months of diagnosis. We tested the interaction of year with race and ethnicity, sex, and insulin regimen to assess potential disparities. Results. Among the 3,956 youth with T1D, there was a small, clinically insignificant reduction in HbA1c between 2002 (

7.9
%
±
1.5

) and 2016 (

7.8
%
±
2.4

) (fully adjusted change by year (-0.013% [95% CI -0.026, -0.0008],

p
=
0.04

). The proportion of youth with suboptimal glycemia increased with each year, but the adjusted odds did not change. Insulin pump use increased more than fivefold. Although interaction effects of time with race and ethnicity, sex, and insulin regimen were not detected, in 2016, suboptimal glycemia was 4.3 and 1.8 times more prevalent among Black and Hispanic than among non-Hispanic White youth, respectively. Conclusions. There was not a clinically significant population-level improvement in glycemia across incident youth cohorts early in the course of T1D, despite severalfold increases in insulin pump use. Comprehensive clinical interventions to improve glycemia early in the T1D course and address disparities are urgently needed.
A Video Key Frame Extraction Method Based on Multiview Fusion
Authors: Chen Ken , Wang Jun , Yang Yang , Tang Yong , Zhou Yong , Zhu Jin
Published: July 2022

A massive amount of video data is stored in the real-time road monitoring system, especially in high-speed scenes. Traditional methods of video key frame extraction have the problems of large computation and long-time consumption. Thus, it is imperative to decrease the massive video data generated by monitoring and help researchers to study key frames. Aiming at the above problems, we propose an efficient key frame extraction method based on multiview fusion, where the autoencoder is used to compress the video data. Specifically, all the video frames of the video data are subjected to feature dimensionality reduction, and the features after dimensionality reduction are subjected to multiview fusion. Finally, dynamic programming and clustering are used to extract key frames. The experimental results show that the proposed method has lower computational complexity in extracting key frames, while the mutual information in the extracted key frames is large. It illustrates the reliability and efficiency of the proposed method, which provides technical support for subsequent video research.
Image Composition and Semantic Expression of Traditional Folk Art Based on Evolutionary Computing Technology
Authors: Ma Suili
Published: July 2022

Image media are used by people to perceive the world’s material reality and spiritual symbols. Traditional folk art images, unlike natural scene images, are characterized by “form to write God.” Their semantic data are more abstract and detailed. As a result, folk art images limit the use of low-level visual feature descriptors in natural images. By simulating the evolution of natural species, evolutionary computation solves optimization problems. Black box optimization, combinatorial optimization, nonconvex optimization, and multiobjective optimization are all examples of optimization techniques. The semantic model is built using the semantic dictionary, and the semantic expression between images is then determined using semantic measurement. As a result, this paper focuses on the “semantic gap” of evolutionary computing-based image search technology, as well as related feedback and image semantic analysis technology. The results show that this method uses the deep database’s triple cross validation method to achieve average comfort and wakefulness, with accuracy of 63.62 percent and 72.38 percent, respectively, which is better than the methods in the comparative literature and can verify the algorithm’s efficiency and feasibility. To summarize, using evolutionary computing technology to improve the performance of object classification and retrieval, traditional folk art image composition and semantic expression can effectively reduce quantization error and improve the resolution of image semantic expression.
Study on Intelligent Online Piano Teaching System Based on Deep Learning Recurrent Neural Network Model
Authors: Li Yuhan
Published: July 2022

This study has been conducted to solve the problem of repetitive piano lessons and to bring a personalized experience for each piano learner. The application of deep learning (DL) technology for children’s piano teaching has a positive effect on their interest in the subject and improves the teaching quality. Music instruments were identified in the system using an instrument recognition model that was developed using deep learning techniques. It was also utilized to help children learn to play the piano by giving them direction and boosting their excitement for it. The proposed model’s ability to recognize and acquire features has been improved. The recurrent neural network (RNN) demonstrated instrument recognition accuracy of 96.4%, and the model’s recognition error rate decreased and stabilized as the number of iterations increased. The proposed RNN for musical instruments recognizes instruments by using DL to accurately identify musical properties.
Unified Approach to Fractional Calculus Images Involving the Pathway Transform of Extendedk-Gamma Function and Applications
Authors: Tassaddiq Asifa , Nantomah Kwara
Published: July 2022

A path way model is concerned with the rules of swapping among different classes of functions. Such model is significant to fit a parametric class of distributions for new data. Based on a such model, the path way orPδtransform is of binomial type and contains a family of different transforms. Taking inspiration from these facts, present research is concerned with the computation of new fractional calculus images involving the extendedk-gamma function. The non-integer kinetic equations containing the extendedk-gamma function is solved by using pathway transform as well as validated with the earlier obtained results.Pδtransform of Dirac delta function is obtained which proved useful to achieve the purpose. As customary, the results for the frequently used Laplace transform can be recovered by takingδ⟶1in the definition ofPδtransform. Important new identities involving the Fox-Wright function are obtained and used to simplify the results. It is remarkable that the several new and novel results involving the classical gamma function became possible by using this approach.
Central Nervous System Xanthoma Disseminatum: Response to 2CdA in an Adolescent
Authors: DeMoss Patrick , Tang Nancy , Yeom Kristen , Chiang Audris , Marqueling Ann L. , Jeng Michael R.
Published: July 2022

Xanthoma disseminatum is a normolipemic non-Langerhans cell histiocytosis characterized by red-brown rubbery papules of the skin which coalesce into plaque-like lesions with symmetric involvement of face, flexor, and intertriginous areas. Less commonly, xanthoma disseminatum may affect mucosal linings, abdominal organs, and the central nervous system, leading to endocrinopathies. We report a 12-year-old adolescent with mucosal, central nervous system, and painful cutaneous lesions, further complicated by diabetes insipidus and amenorrhea. Treatment with 2-chlorodeoxyadenosine led to relief of pain and significant improvement of mucosal, central nervous system, and cutaneous lesions, with subsequent restoration of menstrual cycles.
Frailty Prevalence, Incidence, and Association with Incident Disability in the Italian Longitudinal Study on Aging
Authors: Galluzzo Lucia , Noale Marianna , Maggi Stefania , Feraldi Alessandro , Baldereschi Marzia , Di Carlo Antonio , Onder Graziano ,   the ILSA Working Group
Published: July 2022

Introduction: Data on frailty frequency are heterogeneous and mostly based on cross-sectional studies. Little is known about frailty development and progression over time. Our aim was to conduct a systematic analysis of frailty prevalence and incidence in a large cohort of older adults and to evaluate the association with incident disability, in order to tackle the current paucity and fragmentation of longitudinal data on frailty. Methods: As secondary analysis of the Italian Longitudinal Study on Aging (ILSA) population-based cohort (n = 5,632, 65–84), frailty status was operationalized according to Fried criteria (n = 2,457). Weighted prevalence and incidence rates were calculated at each ILSA wave (T0 1992–1993, T1 1995–1996, T2 2000–2001). The association with incident disability in Activities of Daily Living (ADL) or Instrumental Activities of Daily Living (IADL) was investigated through Cox proportional hazard models, controlling for possible confounders. Results: Prevalence of frailty and pre-frailty at baseline (mean age 71.6 years; women 58.9%) were 4.0% (95% confidence interval [CI]: 3.4–4.6) and 44.6% (95% CI: 43.1–46.1), respectively. Incidence rates per 1,000 person-years for the T0–T1 interval were 7.3 (95% CI: 5.2–9.3) for frailty and 83.7 (95% CI: 73.6–93.8) for pre-frailty. Prevalence and incidence of frailty, and to a lesser degree of pre-frailty, were overall higher for women and increased with age, yet no increasing trend with advancing age was detected for pre-frailty incidence. Frailty incidence rates were significantly higher among pre-frail than non-frail individuals at follow-up entry. After full adjustment, being frail markedly increased the risk of incident disability in ADL (hazard ratio [HR] 3.58, 95% CI: 1.97–6.52) and IADL (HR 2.56, 95% CI: 1.58–4.16) over a 4-year period. Discussion/Conclusion: According to our findings, frailty is common among older people and is a strong and independent predictor of disability. Further research on factors and characteristics related to frailty progression, and especially remission, over time is crucial to calibrate effective public health preventive measures.
Tuberculosis: Retos en el diagnóstico del derrame pleural
Authors: Rodríguez-Llamazares Sebastián
Published: July 2022

Background: Tuberculosis poses a severe threat to human health. At present, compared with the traditional diagnostic methods for tuberculosis pleural effusion, such as Löwenstein-Jensen culture, pleural biopsy, and Ziehl-Neelsen smear microscopy, Xpert MTB/RIF was regarded as an emerging technology for its efficiency. The Xpert MTB/RIF accuracy for tuberculous pleural effusion diagnosis was evaluated in this systematic study. Materials and methods: We searched the relevant literature published before January 2021 in PubMed, Cochrane, EMBASE, and Web of Science databases. Utilizing Review Manager 5.3 software, the quality of the included literature was evaluated based on the Quality Assessment of Diagnostic Accuracy Studies criteria. Sensitivity, specificity, and the summary receiver operating characteristic curves were plotted and analyzed with Metadisc 1.40 software. We used Stata 12.0 software to evaluate the publication bias of this study. Results: Eighteen articles were identified in total. The sensitivity of Xpert MTB/RIF in the pleural effusion was 0.24, and specificity was 1.00, respectively. The area under the summary receiver operating characteristic curve was 0.9737, which indicated that the overall accuracy of the Xpert MTB/RIF was high. In addition, based on the Deeks funnel plot, no publication bias of the study was found. Conclusion: Xpert MTB/RIF is a rapid method with high specificity but relatively low sensitivity for detecting Mycobacterium tuberculosis in pleural effusion. Its less sensitivity made it difficult to be used clinically, but the high specificity suggests that it can be used as a specific diagnostic method for tuberculous pleural effusion.
ThreatNet: advanced threat detection, region-based convolutional neural network framework
Authors: Singh Anurag , Kumar Naresh , Kadry Seifedine
Published: July 2022

It is critical for many countries to ensure public safety in detecting and identifying threats in a night, commercial places, border areas and public places. Majority of past research in this area has focused on the use of image-level categorization and object-level detection techniques. As an X-ray and thermal security image analysis strategy, object separation can considerably improve automatic threat detection when used in conjunction with other techniques. In order to detect possible threats, the effects of introducing segmentation deep learning models into the threat detection pipeline of a large imbalanced X-ray and thermal dataset were investigated. With the purpose of boosting the number of true positives discovered, a faster regional convolutional neural network (R-CNN) model was trained on a balanced dataset to identify probable hazard zones in X-ray and thermal security pictures. In order to get the final results, we combined the two models i.e faster R-CNN with Mask RCNN into a single detection pipeline using the transfer learning technique, which outperforms baseline and end-to-end instance segmentation methods using less number of the practical dataset, with mAPs ranging from 94.88 percent to 91.40 percent helps in detecting the person with guns, knives, pliers to avoid cross border threats.
Hybrid machine learning approach for anomaly detection
Authors: Lok Lai Kai , Abdul Hameed Vazeerudeen , Ehsan Rana Muhammad
Published: July 2022

This research aims to improve anomaly detection performance by developing two variants of hybrid models combining supervised and unsupervised machine learning techniques. Supervised models cannot detect new or unseen types of anomaly. Hence in variant 1, a supervised model that detects normal samples is followed by an unsupervised learning model to screen anomaly. The unsupervised model is weak in differentiating between noise and fraud. Hence in variant 2, the hybrid model incorporates an unsupervised model that detects anomaly is followed by a supervised model to validate an anomaly. Three different datasets are used for model evaluation. The experiment is begun with 5 supervised models and 3 unsupervised models. After performance evaluation, 2 supervised models with the highest F1-Score and one unsupervised model with the best recall value are selected for hybrid model development. The variant 1 hybrid model recorded the best recall value across all the experiments, indicating that it is the best at detecting actual fraud and less likely to miss it compared to other models. The variant 2 hybrid model can improve the precision score significantly compared to the original unsupervised model, indicating that it is better in separating noise from fraud,
Thermal-aware directional and adaptive routing algorithm for 3D network-on-chip
Authors: Kaleem Muhammad , Isnin Ismail Fauzi
Published: July 2022

Due to the tier architecture of 3D network-on-chip (3D-NoC), reducing the thermal hotspot within the chip is challenging as a cooling mechanism that lies merely on the single side of a chip. High power density in 3D NoC is responsible for reliability degradation and thermal difficulties. Thermal-aware routing becomes substantial to handle thermal difficulties and diffusion of heat to the cooler regions. Thermal-aware routing focuses on bypassing hotspot areas by selecting cooler areas. Existing thermal-aware routing algorithms adopt slightly cooler but longer and extended paths, due to lack of ability to know the proximity of the destination's location, which aggravate thermal issues. This work presents a novel thermal-aware directional and adaptive routing algorithm. Objective of the proposed algorithm is to strive to find the best possible neighbour to reach closer to the proximity of the destination. The proposed algorithm can adaptively choose any suitable neighbour that can lead packets closer to the destination at each intermediate node. The performance of the proposed algorithm is evaluated and compared with existing thermal-aware routing algorithm in a simulator environment. Simulation results demonstrate that the proposed method outperformed its counterpart in terms of average delay with 11-26% improvement, total hop counts with 8-24% reduction under various traffic conditions and improvement in overall thermal profiling of the chip.
Cluster-based fuzzy regression trees for software cost prediction
Authors: Najm Assia , Zakrani Abdelali , Marzak Abdelaziz
Published: July 2022

The current paper proposes a novel type of decision tree, which is never used for software development cost prediction (SDCP) purposes, the cluster-based fuzzy regression tree (CFRT). This model uses the fuzzy k-means (FKM), which deals with data uncertainty and imprecision. The tree expansion is based on the variability measure by choosing the node with the highest value of granulation diversity. This paper outlined an experimental study comparing CFRT with four SDCP methods, notably linear regression, multi-layer perceptron, K-nearest-neighbors, and classification and regression trees (CART), employing eight datasets and the leave-one-out cross-validation (LOOCV). The results show that CFRT is among the best, ranked first in 3 datasets according to four accuracy measures. Also, according to the Pred(25%) values, the proposed CFRT model outperformed all the twelve compared techniques in four datasets: Albrecht, constructive cost model (COCOMO), Desharnais, and The International Software Benchmarking Standards Group (ISBSG) using LOOCV and 30-fold cross-validation technique.
A novel approach for grounding resistance estimation
Authors: Bhosale Meghna , Karandikar Parashuram B. , Karkaria Vispi , Kulkarni Neelima R.
Published: July 2022

Grounding is crucial to achieving equipment and personnel protection. This paper presents input-output pair-based modeling using the response surface method and artificial neural network to predict earth resistance for novel factors associated with grounding. The effect of various types of cone-shaped earth electrodes, charcoal size, and industrial waste metal fibers on earth resistance is investigated for the first time. The experimental trials are carried out in a scaled down manner. Artificial neural network and response surface method are used as investigatory tool for parametric variation. Artificial neural network model predicts earth resistance with more accuracy as compared to response surface method. These methods are found to be very effective in prediction of earth resistance of grounding system which is complex in nature.
Effects of titanium dioxide quantum dots on the color deviation and luminous flux of white light-emitting diodes
Authors: Binh Ly Thanh , Ton That Phung , Xuan Le Phan
Published: July 2022

The application of quantum dots has been considered as a promising approach to the advancement of phosphor-converted light-emitting diodes (pc-LEDs) since they perform an excellent extinction coefficient. Yet, it is challenging to manage their influences on the optical properties of LEDs due to their different nanometers in size. Hence, the object of this research is to analyze the influences of quantum dot (QDs) to figure out the solution to control the enhancement of LED lighting performances. Particularly, the study worked on investigating the scattering and absorption features of titanium dioxide (TiO2) QDs. It demonstrated that the radiant efficiency and luminous stability of the TiO2 QDs-converted LEDs (QC-LEDs) was inferior due to the strong light absorption and reabsorption occurring inside the LED packages. Additionally, it also presented low uniformity of color distribution because the scattering ability of QDs is weak. Therefore, reducing the concentration of QDs when adding to the LED structure seems to be possible to enhance the luminous output of QC-LEDs. We propose 0.05% wt. TiO2 for white LED to reduce the illumination losing caused by re-absorbent and total internal backscattering, resulting in approximate 31% lumen improvement and high color rendering index (CRI) measured at about 85, at a high color temperature of 7500 K.
The application YAG:Ce3+@SiO2 phosphor for improving color deviation of phosphor-converted light-emitting diode
Authors: Binh Ly Thanh , Xuan Le Phan
Published: July 2022

The yellow phosphor Y3Al5O12:Ce3+ (YAG:Ce3+), which sees its most popular use in white light-emitting diode (wLEDs), possess an optical spectrum that lacks the red element. The following article will propose a fresh solution for this problem, which involves adjusting the properties of Ce3+ spectrum by using exterior dye particles of ATTO-Rho101, possessing dramatic, wide absorption within the zone of green-yellow spectrum of Ce3+ emission and significant release of the red element. The globular YAG:Ce3+, which is micrometer and nanometer in size with significant dispersion (micro/nano-YAG:Ce3+) was created by employing an altered solvothermal technique. The YAG:Ce3+ produced by said technique, along with the heated micro-YAG:Ce3+ and commercial phosphors, were exteriorly covered with SiO2 and immersed in dye at the same time. Effective radiant transmission/reabsorption from Ce3+ within the YAG’s internal bowel to the dye particles of the exterior hull of SiO2, regardless of the phosphors’ size, was displayed in the YAG: Ce3+@SiO2+ dye powder amassed over the stimulation of the light of blue, which boosted the red element of it. The fluorescent microscope was considered an effective device intended for detecting the reabsorption event in grinded substances.