bluuebunny/crossref_metadata_2025 huggingface dataset:
The Need for Interpretable Features
Authors: Zytek Alexandra , Arnaldo Ignacio , Liu Dongyu , Berti-Equille Laure , Veeramachaneni Kalyan
Published: June 2022

Through extensive experience developing and explaining machine learning (ML) applications for real-world domains, we have learned that ML models are only as interpretable as their features. Even simple, highly interpretable model types such as regression models can be difficult or impossible to understand if they use uninterpretable features. Different users, especially those using ML models for decision-making in their domains, may require different levels and types of feature interpretability. Furthermore, based on our experiences, we claim that the term "interpretable feature" is not specific nor detailed enough to capture the full extent to which features impact the usefulness of ML explanations. In this paper, we motivate and discuss three key lessons: 1) more attention should be given to what we refer to as the interpretable feature space, or the state of features that are useful to domain experts taking real-world actions, 2) a formal taxonomy is needed of the feature properties that may be required by these domain experts (we propose a partial taxonomy in this paper), and 3) transforms that take data from the model-ready state to an interpretable form are just as essential as traditional ML transforms that prepare features for the model.
Liquid-Phase Transmission Electron Microscopy for Reliable In Situ Imaging of Nanomaterials
Authors: Sung Jongbaek , Bae Yuna , Park Hayoung , Kang Sungsu , Choi Back Kyu , Kim Joodeok , Park Jungwon
Published: June 2022

Liquid-phase transmission electron microscopy (LPTEM) is a powerful in situ visualization technique for directly characterizing nanomaterials in the liquid state. Despite its successful application in many fields, several challenges remain in achieving more accurate and reliable observations. We present LPTEM in chemical and biological applications, including studies for the morphological transformation and dynamics of nanoparticles, battery systems, catalysis, biomolecules, and organic systems. We describe the possible interactions and effects of the electron beam on specimens during observation and present sample-specific approaches to mitigate and control these electron-beam effects. We provide recent advances in achieving atomic-level resolution for liquid-phase investigation of structures anddynamics. Moreover, we discuss the development of liquid cell platforms and the introduction of machine-learning data processing for quantitative and objective LPTEM analysis.
Zn2SnO4 Thin Film for Ozone Gas Sensor Developed on MEMS Device and Synthesized by HiPIMS Co-sputtering
Authors: Chou Cheng-Hsueh , Hsiao Yu-Jen , Wang Sheng-Chang
Published: June 2022

The sensing film of Zn2SnO4 is developed and synthesized by High Power Impulse Magnetron Sputtering (HiPIMS) co-sputtering system which is integrated on the Microelectromechanical Systems (MEMS) gas sensor. The experimental results revealed that the optimal annealing temperature is at 600 °C and optimal operating temperature is at 100 °C which has the best sensing performance for Ozone sensing. It is found that 0.3 ppm of O3 gas concentration gas the response value (Ra/Rg) 39.03 and at 0.05 ppm of low concentration, the sensing response recorded to be 8.03. In the selectivity test, with 5 other gases like CO, NO2, C3H4O3, C2H5OH and H2S, sensor exhibited high selectivity for O3 gas. The Zn2SnO4 sensing film have quickly responded to O3 gas with 6 s response time and the 18 s recovery time. In the current study, the Zn2SnO4 film in MEMS gas sensor shown good detection performance at low gas concentrations and has potential applications in environmental sensing.
Uncertainty Estimation of Luminous Flux for LED Lamps Due to the Control of Electric Power
Authors: El-Moghazy E. M. , Gaballah A. E. H.
Published: June 2022

Electrical power efficiency has been of interest to both energy providers and consumers as it plays a pivotal role in our daily life. The voltage fluctuation is a significant issue with power quality since it has a substantial influence on electronic devices in addition to its economic impact. Several contributions have been dedicated to estimating the uncertainty in luminous flux including various parameters; however, most of them have been focused on traditional light sources such as incandescent lamps. One of the main parameters that have not been considered is the uncertainty in electric power due to voltage instabilities. In this study, the effect of regulating the electric power on the luminous flux and its combined uncertainty for different brands of LED lamps were explored. The LED lamps currently available in the Egyptian market have been tested according to their photometric and electric parameters. Three different brands labeled E, T, and V have been chosen with nominal power of 9 and 15 Watt. The experimental testing of such lamps showed that the power factors have a considerable effect on the combined uncertainty of the overall luminous flux.
Review—Electrochemistry and Other Emerging Technologies for Continuous Glucose Monitoring Devices
Authors: Kumar Das Saroj , Nayak Kavya K. , Krishnaswamy P. R. , Kumar Vinay , Bhat Navakanta
Published: June 2022

Diabetes leads to chronic microvascular complications for the heart, kidney, and eyes due to uncontrolled glycemic fluctuations. Self-monitoring blood glucose meters can only provide a snapshot of glucose level and are incapable of capturing the granular glucose fluctuations over the 24 h in day. The clinical research has indicated that random blood glucose fluctuations can lead to organ damage. In pursuit of better glucose management, Continuous Glucose Monitoring (CGM) is emerging as a popular alternative owing to its ability to detect instantaneous changes in glucose levels and to alert the users of impending hypo- or hyper-glycemic events. In the last decade, several CGM devices have been launched in the market based on different glucose sensing chemistries and techniques. More research is still needed to come up with novel bio sensing concepts to make CGM low cost and highly accurate. Here, we elaborate the CGM techniques such as electrochemical, optical, reverse iontophoresis, microdialysis, and impedance spectroscopy. We emphasize on the widely used electrochemical CGMs with a focus on sensor design and bio-compatibility. We also provide an outlook for the future technologies, highlighting the need for innovative materials, possibility of integrating with the Internet of Things (IoT) for real-time e-health monitoring.
Comparison of Blood Pressure Variability between 24 h Ambulatory Monitoring and Office Blood Pressure in Diabetics and Nondiabetic Patients: A Cross-Sectional Study
Authors: Rouxinol-Dias Ana Lídia , Gonçalves Marta Lisandra , Ramalho Diogo , Silva Jose , Barbosa Loide , Polónia Jorge
Published: June 2022

Background. Evidence regarding blood pressure (BP) variability (BPV) and its independent association with adverse outcomes has grown. Diabetic patients might have increased BPV, but there is still an evidence gap regarding relation between BPV and type 2 diabetes beyond mean values of BP. Objective. To examine the relationship between 24 h ambulatory BP monitoring (ABPM, short-term variability) and visit-to-visit in-office BPV (OBP, long-term variability), in diabetics (D) and nondiabetics (ND), and to explore BPV relation with estimated glomerular filtration rate (eGFR), and pulse wave velocity (PWV) as indicators of target organ lesion. Materials and Methods. We conducted a single-center cross-sectional study in an outpatient BP unit, including adult patients consecutively admitted from 1999 to 2019. Multivariate was performed to compare BPV between D and ND adjusted for clinical variables. Pearson’s correlation was performed to evaluate relation of BPV with eGFR and PWV. Results. A total of 1123 patients with ABPM and OBP measurements were included. Values of eGFR and PWV were worse in D than in ND. Measurements of OBPV did not differ between groups. Of ABPM BPV, the coefficient of variation and standard deviation for daytime systolic BP were higher in D compared to ND, but only in ND did BPV correlated with both eGFR and PWV. Conclusion. We found that diabetes is associated with higher variability of daytime BP than nondiabetics along with worse damage of vascular and renal function. However, in contrast to nondiabetics, in diabetics eGFR and PWV may not be dependent on BP variability, suggesting that other mechanisms might explain more rigorously the greater damage of target organ lesion markers.
Characterization of lncRNA-Based ceRNA Network and Potential Prognostic Hub Genes for Sepsis
Authors: Tong Yiqing , Yang Yanping , Feng Qiming
Published: June 2022

Objective. Sepsis is one of the most common reasons for hospitalization and in-hospital mortality each year. Noncoding RNAs have been reported not only as diagnostic and prognostic indicators but also as therapeutic targets of sepsis. Herein, we used an integrative computational approach to identify miRNA-mediated ceRNA crosstalk between lncRNAs and genes in sepsis based on the “ceRNA hypothesis” and investigated prognostic roles of hub genes in sepsis. Methods. Two good-quality gene expression datasets with more than 10 patient samples, GSE89376 and GSE95233, were employed to obtain differentially expressed lncRNAs (DElncRNAs) and genes (DEGs) in sepsis. The DElncRNA-miRNA-DEG regulatory network was constructed using a combination of DElncRNA-miRNA pairs and miRNA-DEmRNA pairs. The protein-protein interaction (PPI) network was constructed by mapping DEGs into the STRING database to identify hub genes in sepsis. The clinical and prognostic significance of hub genes was validated in 89 patients with post-traumatic sepsis. Results. The integrative computational approach identified 311 DEGs and 19 DElncRNAs between septic patients and healthy volunteers. Results yielded 122 downDElncRNA-miRNA-downDEG networks based on two lncRNAs, HCP5, and HOTAIRM1, and 36 upDElncRNA-miRNA-upDEG network based on BASP1-AS1. The PPI network identified serum/glucocorticoid regulated kinase 1 (SGK1), arrestin beta 1 (ARRB1), and G protein-coupled receptor 183 (GPR183) as located at the core of the network, and three of them were downregulated in sepsis. SGK1, ARRB1, and GPR183 were all involved in lncRNA HCP5-based ceRNA network. The quantitative real-time PCR revealed that the patients with post-traumatic sepsis exhibited reduced relative mRNA levels of SGK1, ARRB1, and GPR183 compared to the patients without sepsis. The nonsurvivor group, according to the 28-day mortality, showed lower relative mRNA levels of SGK1, ARRB1, and GPR183 than the survivor group. We also demonstrated reduced mRNA levels of SGK1, ARRB1, and GPR183 were associated with sepsis-related death after trauma. Conclusion. Our integrative analysis and clinical validation suggest lncRNA HCP5-based ceRNA networks with SGK1, ARRB1, and GPR183 involved were associated with the occurrence and progression of sepsis.
Clinical Efficacy and Safety of Tenofovir in the Treatment of Patients with Chronic Hepatitis B
Authors: He Feng , Xia Zhongjiang , Wang Hui , Zhu Jinjun , Hu Laiwen
Published: June 2022

The negative rate of serum HBV DNA, HBeAg, and ALT in the tenofovir group was significantly higher than that in the entecavir group (86.67%, 3.33%, and 80.00%) (all

P
<
0.05

). In the tenofovir group, 2cases were considered. Objective. The aim of this study is to analyze the clinical effect and safety of tenofovir in the treatment of chronic hepatitis B (CHB) patients. Methods. A total of 60 patients with CHB who were admitted and treated in Anqing First People’s Hospital Affiliated to Anhui Medical University from January 2019 to July 2020 were randomly assigned at a ratio of 1 : 1 into the tenofovir group (treated with tenofovir) and the entecavir group (treated with entecavir) via the random number table method. The clinical therapeutic effect and safety of the two groups were compared. Results. The serum hepatitis B virus (HBV) DNA levels in the two groups decreased after treatment, but there was no significant difference. Ths (2.50%) had nausea, 1 (1.25%) had headache, and 0 had an elevated creatine kinase. In the tenofovir group,1(3.33%) had nausea, 0 had headache, and 0 had an elevated creatine kinase. In the entecavir group, there were 3 (10.00%) cases of nausea, 2 (6.67%) cases of headache, and 1 (3.33%) case of elevated creatine kinase. The overall incidence of adverse reactions in the tenofovir group (3.33%) was significantly lower than that in the entecavir group (20.00%) (all

P
<
0.05

). Conclusion. Tenofovir is more effective than entecavir in the treatment of patients with CHB due to low incidence of adverse events and a good safety profile.
[Retracted] Identification of Hub Genes for Early Diagnosis and Predicting Prognosis in Colon Adenocarcinoma
Authors: Xu Shuo , Liu Dingsheng , Cui Mingming , Zhang Yao , Zhang Yu , Guo Shiqi , Zhang Hong
Published: June 2022

Colon adenocarcinoma (COAD) is among the most common digestive system malignancies worldwide, and its pathogenesis and gene signatures remain unclear. This study explored the genetic characteristics and molecular mechanisms underlying colon cancer development. Three gene expression data sets were obtained from the Gene Expression Omnibus (GEO) database. GEO2R was used to determine differentially expressed genes (DEGs) between COAD and normal tissues. Then, the intersection of the data sets was obtained. Metascape was used to perform the functional enrichment analyses. Next, STRING was used to build protein‐protein interaction (PPI) networks. Hub genes were identified and analysed using Cytoscape. Next, survival analysis and expression analysis of the hub genes were performed. ROC curve analysis was performed for further test of the diagnostic efficacy. Finally, alterations in the hub genes were predicted and analysed by cBioPortal. Altogether, 436 DEGs were detected. The DEGs were mainly enriched in cell cycle phase transition, nuclear division, meiotic nuclear division, and cytokinesis. Based on PPI networks, 20 hub genes were selected. Among them, 6 hub genes (CCNB1, CCNA2, AURKA, NCAPG, DLGAP5, and CENPE) showed significant prognostic value in colon cancer (P < 0.05), while 5 hub genes (CDK1, CCNB1, CCNA2, MAD2L1, and DLGAP5) were associated with early colon cancer diagnosis and ROC curve analysis showed good diagnostic accuracy. In conclusion, integrated bioinformatics analysis was used to identify hub genes that reveal the potential mechanism of carcinogenesis and progression of colon cancer. The hub genes might be novel biomarkers for early diagnosis, treatment, and prognosis of colon cancer.
Intraspecific Genetic Variation of Anisakis typica in Indian Mackerel Caught from the Gulf of Thailand, Samut Songkhram Province
Authors: Chaiphongpachara Tanawat , Adisakwattana Poom , Suwandittakul Nantana
Published: June 2022

Anisakis nematodes infecting Indian mackerel (Rastrelliger kanagurta) were initially discovered in Thailand in our preliminary investigation. Nevertheless, the species of Anisakis collected has not been determined nor has its genetic variation been researched. Thus, this study aimed to molecularly identify the species of Anisakis specimens using the internal transcribed spacer (ITS) region of ribosomal DNA sequences. In addition, the intraspecific genetic variation was also determined using mitochondrial cytochrome oxidase subunit II (COII) gene sequences. The phylogenetic relationships of the ITS region classified all samples into Anisakis typica; however, the genetic variation between them could not be distinguished. By contrast, the phylogenetic tree analysis of the COII region identified all samples as A. typica, with 17 different haplotypes by 66 polymorphic sites and five of the substitutions resulted in amino acid change. Additionally, the distribution pattern of the COII region can be separated into two groups between South America and Asian countries. All our haplotypes belong to Asian countries. Compared with the two genetic markers used in this investigation, COII appears to be a better candidate for studying genetic variation sensitive to environmental changes and intermediate or definitive host behavioral changes.
Molecular Characterization of Antibiotic Resistance and Genetic Diversity of Klebsiella pneumoniae Strains
Authors: Arabzadeh Bahareh , Ahmadi Zeynab , Ranjbar Reza
Published: June 2022

The aims of this study were the molecular characterization of antibiotic resistance and genotyping of Klebsiella pneumoniae strains isolated from clinical cases in Tehran, Iran. A total of 100 different types of clinical human samples were collected from a major teaching hospital in Tehran, Iran. Bacterial isolates were identified using standard microbiological tests. Antimicrobial susceptibility testing was done according to the latest CLSI guidelines. PCR was used to amplify the gyrA gene in quinolone-resistant isolates and sequencing was performed for the detection of probable mutations between the isolates. The occurrence of plasmid-mediated quinolone resistance genes (qnrA, qnrB, and qnrS) was also investigated by PCR. Finally, genotyping of the strains was performed by PFGE in a standard condition. The susceptibility pattern revealed a high and low level of resistance against meropenem (20%) and trimethoprim (37%), respectively. PCR and sequencing detected mutation in the gyrA gene in 51% of quinolone-resistant K. pneumoniae. According to the susceptibility report, among nalidixic acid-resistant strains, 60.5%, 50%, and 42.9% of isolates contained qnrA, qnrB, and qnrS, respectively. Among ciprofloxacin-resistant strains, qnrA was the most frequent PMQR gene. The PFGE differentiated the strains into 31 different genetic clusters so that the highest number (7/66) was in category A. Our results indicated that the frequency of resistance to various antibiotics particularly trimethoprim, nalidixic acid, and cefoxitin are increasing. The presence of qnr (S and A) genes and point mutation of the gyrA gene were likely to be responsible for the resistance toward nalidixic acid and ciprofloxacin in our strains. Also, the results obtained from genotyping indicated that the K. pneumoniae strains isolated in this study belonged to the diverse clones.
Usefulness of Noncontrast MRI-Based Radiomics Combined Clinic Biomarkers in Stratification of Liver Fibrosis
Authors: Zhao Ru , Zhao Hong , Ge Ya-Qiong , Zhou Fang-Fang , Wang Long-Sheng , Yu Hong-Zhen , Gong Xi-Jun
Published: June 2022

Purpose. To develop and validate a radiomic nomogram based on texture features from out-of-phase T1W images and clinical biomarkers in prediction of liver fibrosis. Materials and Methods. Patients clinically diagnosed with chronic liver fibrosis who underwent liver biopsy and noncontrast MRI were enrolled. All patients were assigned to the nonsignificant fibrosis group with fibrosis stage <2 and the significant fibrosis group with stage ≥2. Texture parameters were extracted from out-of-phase T1-weighted (T1W) images and calculated using the Artificial Intelligent Kit (AK). Boruta and LASSO regressions were used for feature selection and a multivariable logistic regression was used for construction of a combinational model integrating radiomics and clinical biomarkers. The performance of the models was assessed by using the receiver operator curve (ROC) and decision curve. Results. ROC analysis of the radiomics model that included the most discriminative features showed AUCs of the training and test groups were 0.80 and 0.78. A combinational model integrating RADscore and fibrosis 4 index was established. ROC analysis of the training and test groups showed good to excellent performance with AUC of 0.93 and 0.86. Decision curves showed the combinational model added more net benefit than radiomic and clinical models alone. Conclusions. The study presents a combinational model that incorporates RADscore and clinical biomarkers, which is promising in classification of liver fibrosis.
Feature Extraction of Athlete’s Post-Match Psychological and Emotional Changes Based on Deep Learning
Authors: Zhang Shuchang , Shan Fengjun
Published: June 2022

Athletes have had to deal with significant shifts in the way they think about psychology and emotion before and after attending a match in their respective fields. It has become increasingly difficult for players of any sport to overcome these differences due to massive technological advancements that aid in analyzing the difficulties of an athlete. The trainer can use the results of the analysis to help motivate and prepare the athletes for the upcoming competitions. The analysis in this study is based on information about the athletes who competed in the Tokyo Olympics. Deep learning models were used to evaluate the study. Image feature detection can be accomplished through the application of a machine learning technique known as deep learning. It employs a neural network, a computer system that mimics the human brain’s multiple layers. One or more unique features can be extracted from each layer. A deep learning model called the behavior recognition algorithm is used for the research. The questionnaire from the dataset was used to generate the results of the analysis.
Pattern and In-Hospital Mortality of Thoracoabdominal Injuries Associated with Motor Vehicle Accident-Related Head Injury: a Single-Center Retrospective Study
Authors: Abd El Maksoud Walid M. , Algahtany Mubarak Ali
Published: June 2022

Aim. To determine the pattern and in-hospital mortality of thoracoabdominal injuries associated with head injuries (HI) due to motor vehicle accidents. Settings and Design. A single-center retrospective study in a tertiary care hospital, level 1 trauma center in the southern region of Saudi Arabia. Methods and Materials. Descriptive analysis was conducted to evaluate sex, age, types of head injury, associated thoracoabdominal injuries, particular admission day, duration of hospital stay, and discharge category, and associations between different variables and outcomes were analyzed. Results. The cohort had a mean age of26.9±15.8 years, with a predominance of men (86.9%). Thoracoabdominal injuries were present in 6.8% of MVA-related HI, and 14.3% of victims expired during their hospital stay, mostly within the first 10 days. All expired patients had posttraumatic brain lesions. Moreover, there was a significant association between intensive care unit (ICU) admission and poor prognosis. Conclusions. Existence of posttraumatic brain lesions and requirement of ICU admission are significant variables affecting outcomes in patients with motor vehicle-associated HI with concomitant thoracoabdominal trauma in this study. Patients who survived the first 10 days after trauma seemed to have a better prognosis. More efforts are needed to reduce the health burden of this lethal injury.
Effect of Bodybuilding and Fitness Exercise on Physical Fitness Based on Deep Learning
Authors: Sun Manman , Wang Lijun
Published: June 2022

With the rapid development of society and economy, people’s living standards are improving day by day, and increasingly attention is paid to physical health, which has set off a fitness upsurge. The purpose of this paper was to analyze the impact of bodybuilding exercise on physical fitness based on deep learning. It provides a reference for fitness enthusiasts to choose scientific and targeted exercise methods, and provides a theoretical basis for the promotion of bodybuilding and fitness. This paper first gives a general introduction to deep learning and adds image segmentation technology to design experiments for bodybuilding and fitness. The experiment was divided into groups A and B, and control group C. In this paper, recurrent neural network and gated recurrent neural network are introduced to compare and analyze the data, and the stability of data processing with different activation functions is compared. The data results show that under the scientific and reasonable arrangement of exercise conditions, bodybuilding and fitness exercises have a corresponding positive effect on the body shape and posture of the subjects. It is more practical to choose a combination of aerobic and anaerobic exercise. In this paper, based on the deep learning algorithm, compared with the recurrent neural network, the gated recurrent neural network is more suitable for processing sequence problems. In the experimental analysis part, this paper compares and analyzes the experimental results of the data under different activation functions, sigmoid function, and tanh function. It is found that the tanh activation function and the gated recurrent neural network are more stable for data processing. The highest AUC value of the traditional recurrent neural network differs by 0.78 from the highest AUC value of the gated recurrent neural network. The data analysis results are in line with the actual situation.
Study on Energy Dissipation and Fuel Consumption in Lattice Hydrodynamic Model under Traffic Control
Authors: Wen Qi-Yun , Xue Yu , Cen Bing-Ling , Tang Yuan , Huang Mu-Yang , Pan Wei
Published: June 2022

A lattice hydrodynamic traffic model considering the average optimal flow of multiple grids downstream as a feedback control is proposed. The energy dissipation and fuel consumption are investigated under the feedback control based on the lattice hydrodynamic traffic model. Through linear stability analysis, the stability condition of the model is obtained. The mKdV equation and its kink-antikink density wave solution are derived by using the reduced perturbation method of nonlinear analysis. The variation trends of density wave, energy dissipation, and fuel consumption under traffic control are studied by numerical simulations. The research shows that exerting the feedback control can effectively suppress traffic congestion and improve the stability of traffic system. Meanwhile, it can also reduce the energy dissipation and fuel consumption of traffic system.
Thermal Conductivity of Thermally Insulated Concretes in a Nuclear Safety Vessel of Reactor Vault: Experimental Interpretation
Authors: Anish M. , Arunkumar T. , Jayaprabakar J. , Al Obaid Sami , Alfarraj Saleh , Raj M. M. , Belay Assefa
Published: June 2022

Thermally insulated concretes are a type of alternative building material that helps improve thermal efficiency in nuclear reactor vault safety vessel applications. The experimental results of thermal conductivity values of lightweight concrete materials at various temperatures are presented in this paper. To minimize heat conduction in concrete, different lightweight aggregates and vermiculite are employed as coarse aggregate alternatives.Both linear and plane heat source approaches are used to calculate the thermal conductivity values of the specimens. The findings emphasize that increasing the proportion of lightweight particles in concrete may dramatically lower the thermal conductivity, with the kind of lightweight aggregates having a vital role in thermal insulation. The inclusion of micron-sized vermiculite decreases heat conductivity even further; however, the effect is less obvious than that of lightweight particles.
Research on the Design of a Training Room Management System for Automotive Professionals in a 5G Wireless Network Environment
Authors: Luo Cheng , Yuan Xiang , He Tao , Yao Xing
Published: June 2022

Education informatization is getting more popular, smart learning spaces are gaining popularity, and students' demands for personalized, convenient, and diverse learning content are becoming more apparent. This study focuses on exploring the design of automotive professional training room management system with 5G technology. On the basis of sorting out the main features of education informatization, it analyzes the technical challenges faced by the design of automotive professional training room management system, starts from three aspects of teaching, teaching and research, and education management, argues and proposes the corresponding 5G automotive professional training room management application scenarios, and forms a general view of 5G education informatization. It will continue to enhance the connotation of educational scenarios, stimulate educational scenario change, and become the primary driving force of innovation in automotive professional education informatization.
Smart Attendance Monitoring Technology for Industry 4.0
Authors: Nadhan Archana S. , Tukkoji Chetana , Shyamala Boosi , Dayanand Lal N. , Sanjeev Kumar A. N. , Mohan Gowda V. , Adhoni Zameer Ahmed , Endaweke Melaku
Published: June 2022

Keeping track of employee attendance in academic settings can be a difficult task. It frequently wastes a significant percentage of the category’s productive time when done manually. In this study, the OpenCV open‐source image processing library presents an effective Raspberry Pi‐based methodology that reduces product cost and aids in connecting to heterogeneous devices for attendance. When teaching and testing and collecting employee photos and taking attendance, the system delivers a user‐friendly interface that maximizes the user experience. Face detection and recognition are done with LBP histograms, and the database is updated with SQLite (a lightweight version of SQL for the Raspberry Pi) rather than MySQL.
Practicability of Sports Goods in the Sports Field Based on Artificial Intelligence Technology
Authors: Zhang Huaibo , Zhu Jianghua
Published: June 2022

People are in the intellectual age. The use of technologies such as smart search engines, machine translation, fingerprint analysis, facial scanning, and self-driving makes people’s social and work lives happier. The intersection of artificial intelligence and other projects has also become the focus of research in the new era. This article uses comparative experimental methods and sampling methods, puts forward the evaluation method of association rules in the recommendation of sports goods, and compares the selection of sensors used by the five types of sports companies in the sports experiments. In the experiment part, according to the minimum confidence level, the two rules are met. Minimum confidence is a threshold defined by users or experts to measure confidence, which represents the lowest reliability of association rules. The conclusion is that 30% of users have bought running shoes and hiking shoes at the same time and 66.6% of users have also purchased sports suits; there are also sports suits purchased at the same time. All mountain bike users have bought sports gloves. The weight of Freescale is 0.2530, the weight of Bosch is 0.4457, the weight of ST is 0.0946, the weight of VTI is 0.0953, and the weight of Konix is 0.1114. The experimental results show that the selection result of the three-axis acceleration sensor is the SMB380 model of Bosch.
Research on the Design of English Comprehensive Learning Activities Based on Deep Learning
Authors: Wang Tao , Gu Yufang
Published: June 2022

To explore the application ways and effects of in-depth learning in English Teaching for Non-English Majors in Colleges and universities, 419 students are selected for the experiment, 205 students from grade 2018 were used as the reference group and 214 students from grade 2019 were used as the observation group to observe the effect of examination-oriented education and the impact of quality through in-depth learning. The performance of students of grade 2019 in examination-oriented education performance data and quality education performance data was significantly better than that of students of grade 2018, T < 10.000,

P
<
0.01

, which was statistically significant, Finally, it is found that the intelligent deep learning algorithm is applied to the analysis of the knowledge structure of non-English students’ English papers, and the application scenarios of the analysis results are widely developed, which is helpful to improve the English teaching effect of non-English students, improve students’ learning efficiency and reduce students’ pressure.
A New Iterative Method for the Approximate Solution of Klein-Gordon and Sine-Gordon Equations
Authors: Fang Jiahua , Nadeem Muhammad , Habib Mustafa , Karim Shazia , Wahash Hanan A.
Published: June 2022

This article presents a new iterative method (NIM) for the investigation of the approximate solution of the Klein-Gordon and sine-Gordon equations. This approach is formulated on the combination of the Mohand transform and the homotopy perturbation method. Mohand transform (MT) is capable to handle the linear terms only, thus we introduce homotopy perturbation method (HPM) to tackle the nonlinear terms. This NIM derives the results in the form of a series solution. The proposed method emphasizes the stability of the derived solutions without any linearization, discretization, or hypothesis. Graphical representation and absolute error demonstrate the efficiency and authenticity of this scheme. Some numerical models are illustrated to show the compactness and reliability of this strategy.
Research on Application of High-Frequency Pulse Vibration in Ship Electric Propulsion System
Authors: Langtao Yan , Guangyin Liu , Jianfeng Zhang
Published: June 2022

Aiming at the problems existing in the method of using sensors to detect the rotor position of marine main propulsion motor at low speed, a sensorless rotor position identification method based on high-frequency pulse vibration signal is proposed. In this method, the low-pass filter is used to separate the high-frequency signal component, and the current component of d-axis to q-axis is demodulated. The control mode of PI action law is used to phase-locked processing of the demodulated signal, in which purpose is to obtain the rotor position signal. The design method is simulated and verified by MATLAB/Simulink software. The error between the estimated position and the actual position of the rotor in the simulation waveform is small, and the accuracy is high. The simulation results show that this method can achieve good results when applied to the ship electric propulsion system without position sensor, which provides a theoretical reference for the design of marine main propulsion motor control system.
Production and Characterization of Polymer Blends and Assessment of Biodegradation
Authors: Sakthiselvan Punniavan , Madhumathi Ramasamy , Karthick V. , Mukhopadhyay Gangotry , Dass Prakash M. V. , Srinivasan T. , John Shani T.
Published: June 2022

Polyhydroxybutyrate (PHB), a microbial polyester well known for its high glass transition and melting temperatures, is found in the intracellular granule within microbes. Herein, we have attempted to synthesize PHB along with xyloglucan (XG) as a copolymer to lower glass transition and melting temperature. Fourier transform infrared spectroscopic (FTIR) and Scanning Electron Microscopic (SEM) analyses were used to investigate the characteristics of blend films. We found that the addition of XG resulted in increased moisture absorption of the blend films. XG‐PHB blend of ratio 80 : 20 showed the highest tensile strength and was subjected to thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC) analysis. The results revealed that the XG‐PHB blend has a lower melting point (121.3°C) and lesser crystalline degree (17.26%) than PHB. TGA results showed that blend film was more thermally stable than PHB. An effort to understand and analyze microorganisms that can produce and biodegrade copolymers such as PHB‐XG is the main effort of this study which unfolds “new hope” in the field of biodegradable alternatives to plastics.
Analytical Approaches on the Attractivity of Solutions for Multiterm Fractional Functional Evolution Equations
Authors: Li Xiangling , Niazi Azmat Ullah Khan , Hafeez Farva , George Reny , Hussain Azhar
Published: June 2022

The most important objective of the current research is to establish some theoretical existence and attractivity results of solutions for a novel nonlinear fractional functional evolution equations (FFEE) of Caputo type. In this respect, we use a familiar Schauder’s fixed-point theorem (SFPT) related to the method of measure of noncompactness (MNC). Furthermore, we consider the operator

E

and show that it is invariant and continuous. Moreover, we provide an application to show the capability of the achieved results.
Identifying the Geographical Origin of Tobacco Leaf by Strontium and Lead Isotopic with Mineral Elemental Fingerprint
Authors: Hong Liu , Wang Wenyuan , Su Yang , Zhang Guiping , Su Yong , Zhang Chenming , Chen Jianhua , Zhe Wei , Liu Zhihua , Cui Jianyong , Mao Deshou , Wang Jin
Published: June 2022

The primary aim of this paper was to identifying the geographical origin of tobacco leaves based on stable isotopic and mineral elemental fingerprint. We collected eighty-one tobacco leaf samples from Argentina, Brazil, Zimbabwe, the U.S., Zambia, and China. And nine mineral element contents and four strontium and lead isotope ratios of the tobacco leaves were determined by thermal ionization mass spectrometry (TIMS) and inductively coupled plasma mass spectrometry (ICP-MS). After variance and stepwise discriminant analysis, the discriminant functions of the tobacco leaf’s geographical origin were established. The results indicate that: (1) the contents of six mineral elements including Cu, Zn, Cr, Ni, Cd, and Pb, together with four strontium and lead isotope ratios containing 87Sr/86Sr, 208Pb/204Pb, 207Pb/204Pb, and 206Pb/204Pb, were significantly different among six countries. (2) Different countries presented some characteristic mineral elemental and isotopic fingerprint. The even contents of mineral elements from Zambian tobacco leaf were much lower than the other countries, among which four elements consisting of Zn, Cr, As, and Cd were not detected. The three average lead isotope ratios including 208Pb/204Pb, 207Pb/204Pb, and 206Pb/204Pb from Zimbabwe tobacco leaves were far higher than the other countries, and the range of which was unoverlapped. (3) The effective identification of the geographical origin of tobacco leaf was accomplished by Fisher stepwise discriminant analysis and the characteristic tracing elements consisted of Cu, Zn, Cr, Ni, Cd, Pb, 87Sr/86Sr, 207Pb/204Pb, and 206Pb/204Pb. Based on the established discriminant functions, the original and cross-validation accuracy towards different geographical origins of tobacco leaves were 98.8% and 95.1%, respectively. The study shows that the strontium and lead isotopic with mineral elemental fingerprints is a potential effective method to identify the geographical origin of tobacco leaves from different countries.
A New Highly Secure Optical Image Security Technique Using Gyrator Transform for Image Security-Related Applications
Authors: Anusree L. , Rahiman M. Abdul
Published: June 2022

New methods and apparatuses for information security have evolved as a result of the rapid expansion of optical information processing. Security is one of the major issues in digital image transmission because it can deliver very secret information to any corresponding agency such as the military, biomedical, and security agencies. Previously, various techniques are proposed to perform optical image encryption techniques using different transformation and pixel-level techniques. Each work has its advantages and disadvantages in terms of computational complexity, security level, flexibility, quality, and so on. To overcome the security issues present in the previous works, a novel optical image encryption standard is proposed in this paper. This work uses information hiding followed by image encryption using Gyrator Transform (GT) using mean gradient key-based block swapping techniques. The main advantage of this work is that the key generation is dynamic and it depends upon the pixel intensity of 8 × 8 blocks. Secret information hiding is performed in the Discrete Cosine Transform (DCT) domain to protect the data against noise attacks. To analyze the performance, various evaluation metrics are used to measure the quality of the decrypted image under various distortions such as cropping and rotation. The robustness of information hiding is analyzed using a noise attack on the received image. This work achieved 45.6 dB of Peak Signal-to-Noise Ratio (PSNR) and 0.965 of Structural Similarity Index (SSIM), which is the best when compared to the conventional image encryption standards.
High Expression of UPK3A Promotes the Progression of Gastric Cancer Cells by Inactivating p53 Pathway
Authors: Xu Deliang , Guo Jing , Xu Hongwei
Published: June 2022

Background. Gastric cancer is a common gastrointestinal tract cancer and is a considerable health burden worldwide. TCGA analysis found Uroplakin 3A (UPK3A) was upregulated in gastric cancer tissues. Our study was designed to investigate the underlying mechanism of Uroplakin 3A (UPK3A) in gastric cancer. Methods. Data from TCGA database were used to assess the expression, and Kaplan-Meier plotter analysis was used to assess the prognosis value of UPK3A. Furthermore, there are effects of UPK3A silencing on the activity, proliferation, migration, and invasion of human gastric cancer cells (SNU-216 and HGC-27) using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT), colony formation, wound healing, and Transwell assays. In addition, the expression of UPK3A, p53, KLF4, ZMAT3, MDM2, and SP1 was detected by qRT-PCR and Western blot assay. Results. UPK3A was markedly upregulated in gastric cancer tissues compared to that in normal tissues, and patients with high UPK3A level showed poor prognosis. UPK3A was highly expressed in human gastric cancer cell lines compared to that in a normal human gastric epithelial cell line. Silencing of UPK3A inhibited the proliferation, migration, and invasion of gastric cancer cells. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis revealed that UPK3A was involved in the p53 signaling pathway. UPK3A suppressed the activation of p53 signaling pathway, and treatment with Pifithrin-α (an inhibitor of the p53 signaling pathway) or silencing of p53 significantly reversed the effect of UPK3A silencing on the expression of p53, KLF4, ZMAT3, MDM2, and SP1. Conclusion. Our findings showed that UPK3A promotes the progression of gastric cancer by regulating the p53 signaling pathway and could be a potential therapeutic target for gastric cancer.
Design and Research of College English Reading, Writing, and Translation Teaching Classroom Based on 5G Technology
Authors: Wang Min
Published: June 2022

Traditional college English lectures, writing, and translation over wireless networks have several problems. As a consequence, research and development for fifth-generation (5G) technologies are already beginning. High data speeds, decreased latency, energy savings, low cost, increased system capability, and large-scale device connectivity are all characteristics of 5G, the fifth generation of mobile communication technology. The 5G network is a wireless network interaction approach for the digital cellular network that allows for massive volumes of data traffic and a large number of wireless connections. The newest 5G technologies must be incorporated into the curriculum to attain higher-order educational capacities. Educators must fully use network resources, especially 5G network interaction tools, to improve English lecture, writing, and translation, as the fast expansion of 5G network interaction methods provides a fresh viewpoint for English lecture, writing, and translation. In this paper, we design a 5G-enabled Genetic Algorithm- (GA-) based approach for college English lectures, writing, and translation. The proposed method can promote resource sharing, empower teacher-student connections, and improve students’ overall English writing performance by researching this novel kind of network. The proposed method is further improved by incorporating 5G network-dependent English writing and interaction tools. Experimental results reveal that the proposed method outperforms state-of-the-art methods.
Hydrogen Sulfide Suppresses Skin Fibroblast Proliferation via Oxidative Stress Alleviation and Necroptosis Inhibition
Authors: Li Ling , He Ziying , Zhu Yue , Shen Qiyan , Yang Shengju , Cao Shuanglin
Published: June 2022

Keloid is a common dermatofibrotic disease with excessive skin fibroblast proliferation. Hydrogen sulfide (H2S) as the third gasotransmitter improves fibrosis of various organs and tissues. Our study is aimed at investigating the effects and possible mechanisms of H2S on skin fibroblast proliferation. Scar tissues from six patients with keloid and discarded skin tissue from six normal control patients were collected after surgery, respectively. Plasma H2S content and skin H2S production in patients with keloid were measured. Keloid fibroblasts and transforming growth factor-β1- (TGF-β1, 10 ng/mL) stimulated normal skin fibroblasts were pretreated with H2S donor as NaHS (50 μM) for 4 h. Cell migration after scratch was assessed. The expressions of α-smooth muscle actin (α-SMA), proliferating cell nuclear antigen (PCNA), collagen I, and collagen III were detected by immunofluorescence, real-time PCR, and/or Western blot. Intracellular superoxide anion and mitochondrial superoxide were evaluated by dihydroethidium (DHE) and MitoSOX staining, respectively. Mitochondrial membrane potential was detected by JC-1 staining. Apoptotic cells were detected by TDT-mediated dUTP nick end labeling (TUNEL). The expressions of receptor interacting protein kinase 1 (RIPK1), RIPK3, and mixed lineage kinase domain-like protein (MLKL) were measured by Western blot. We found that H2S production was impaired in both the plasma and skin of patients with keloid. In keloid fibroblasts and TGF-β1-stimulated normal skin fibroblasts, exogenous H2S supplementation suppressed the expressions of α-SMA, PCNA, collagen I, and collagen III, reduced intracellular superoxide anion and mitochondrial superoxide, improved the mitochondrial membrane potential, decreased the positive rate of TUNEL staining, and inhibited RIPK1 and RIPK3 expression as well as MLKL phosphorylation. Overall, H2S suppressed skin fibroblast proliferation via oxidative stress alleviation and necroptosis inhibition.
Network Security Technology of Supply Chain Management Based on Internet of Things and Big Data
Authors: Lin Xiuchun
Published: June 2022

In order to improve the network security of supply chain management based on the Internet of Things and big data, this paper studies the Internet of Things and big data technology and analyzes the data processing process of the Internet of Things. On the premise that the terminal device meets the requirements of delay and energy consumption, a data offloading encryption model is established to offload data to multiple edge servers for encryption. In addition, this paper proposes an optimization problem including overall security, delay, and equipment energy consumption and establishes a mathematical model that maximizes overall security under the condition of satisfying the requirements of delay and equipment energy consumption. From the simulation data, it can be seen that the network security technology of supply chain management based on the Internet of Things and big data proposed in this paper can achieve effective management and control of supply chain nodes and improve their information security.