bluuebunny/crossref_metadata_2025 huggingface dataset:
Detection of Li Deposition on Si/Graphite Anodes from Commercial Li-Ion Cells: A Post-Mortem GD-OES Depth Profiling Study
Authors: Flügel Marius , Richter Karsten , Wohlfahrt-Mehrens Margret , Waldmann Thomas
Published: May 2022

A new semi-quantitative method was developed to detect Li deposition on Si/graphite anodes. This method is based on Post-Mortem glow discharge optical emission spectroscopy (GD-OES) depth profiling. Based on the contents of Si, Li, and O in the GD-OES depth profiles, we define a corridor, in which the minimum amount of metallic Li on the anode is located. This method was applied to three types of commercial 18650 cells with Si/graphite anodes in the fresh state and with Li plating intentionally produced by cycling at low temperatures. Additional cells were cycling aged at 45 °C to 80% SOH. The main aging mechanisms at 45 °C were determined using differential voltage analysis (DVA), SEM, and half cell experiments. Subsequently, the cells aged at 45 °C were further cycled under the conditions that had led to Li deposition for the fresh cells. Furthermore, the anode coating thickness for 18 types of commercial Li-ion cells are correlated with the specific energy, while distinguishing between graphite anodes and Si/graphite anodes. Our extensive Post-Mortem study gives deep insights into the aging behavior of state-of-the-art Li-ion cells with Si/graphite anodes.
Review—Recent Advancements in Dye-Sensitized Solar Cells; From Photoelectrode to Counter Electrode
Authors: Dhonde Mahesh , Sahu Kirti , Das Malyaj , Yadav Anand , Ghosh Pintu , Murty Vemparala Venkata Satyanarayana
Published: May 2022

Dye-sensitized solar cells (DSSCs) are promising photovoltaic technology with diverse indoor and outdoor applications. DSSCs can be integrated with curtains and glasses to power various devices, including wireless sensors, computer network peripherals, internet-of-things (IoT) devices, and wearable electronics. DSSCs have the potential to become the future source of energy. However, their efficiency, stability, and industrial production still need to be scaled up. The present review encompasses these elements and the various changes that have occurred inside the DSSC over the last few years, including device structure, TiO2 photoelectrode, novel electrolytes, new organic photosensitizers, efficient catalyst materials, and encapsulation strategies for sealing DSSC devices. We further discuss how the performance of each functional component of a DSSC has been enhanced as a result of the introduction of novel materials and manufacturing processes. In addition, we also briefly cover p-DSSCs and tandem DSSCs. Finally, the prospect of highly efficient and stable DSSCs is highlighted.
Investigation of the Reverse Leakage Behavior and Substrate Defects in Vertical GaN Schottky and PIN Diodes
Authors: Wang Yekan , Liao Michael E , Huynh Kenny , Olsen William , Gallagher James C , Anderson Travis J , Huang Xianrong , Wojcik Michael J , Goorsky Mark S
Published: May 2022

In this work, the effects of the substrate defect density and distribution on the reverse leakage behavior of GaN vertical Schottky diodes and p–i–n diodes are investigated. A direct connection between the reverse leakage behavior of GaN based vertical devices and the dislocation density of the underlying material was determined. The difference in the leakage current for devices on different locations of the wafer can be as high as 6 orders of magnitude (for p–i–n diodes) at −200V, for HVPE substrate with inhomogeneous but predictable defect distributions (GaN substrates with dot-core inversion domain features). For comparison, using HVPE substrates with uniform defect distribution (but with no cores), the p–i–n diodes show much more uniform leakage behavior, varying within only an order of magnitude, and that range fell within the much greater range of that for the inhomogeneous substrates. The substrates with inhomogeneous defect distribution proved to be useful to show the direct correlation. The topography measurements confirmed that the wafers with inhomogeneous defect distribution possess periodically patterned core-centers with higher defect density and larger lattice distortions surrounded by other regions, which have very low defect concentrations. Devices located away from the defective core-centers result in a reduction of the reverse bias leakage by over two orders of magnitude at −10 V for Schottky diodes. Similar trends are also observed in the p–i–n diodes; the devices close to the core centers show the highest reverse leakage (>0.01 A cm−2 at −200V). Devices further away from the core-centers (lower dislocation density) show lower reverse leakage current. Moreover, the p–i–n diodes on regions more than 300 μm away from the core-centers show the best leakage behavior (<10−7 A cm−2 at −200V) of all the devices, outperforming the devices on the substrates with uniform defect distribution (∼10−6 A cm−2 at −200V). The results from this study show that the substrate defect density and distribution play important roles in the device leakage current. X-ray topography is extremely effective for studying defect characteristics underneath individual devices. The use of the wafers with inhomogeneous, but predictable defect density clearly demonstrated the importance of low defect densities for high device performance.
Study on Negative Bias Temperature Instability Induced Degradation of P-Type FinFETs by Distinguishing Fin Top and Fin Sidewalls
Authors: Yeh Wen-Kuan , Yang Li-Quan , Shen Cheng-Hao , Kong Jhih-Hao , Tseng Po-Yang , Yang Yi-Lin
Published: May 2022

In this work, the components of fin top and fin sidewalls of tri-gate fin field-effect transistor (FinFET) were distinguished and extracted by a proposed method to find out the characteristic and reliability. Poor fresh characteristic could be found on fin sidewall area due to the existed surface defects after the fabrication the Si etching process. After NBTI stress, larger VTH shift and severe SS degradation reveals worse reliability on fin top area. The result indicates that the poor initial characteristics of the fin sidewalls will reduce the performance of tri-gate FinFETs, but the poor reliability of the fin top determines the overall degradation of the device.
Construction of Physical Education Quality Evaluation Index and Analysis with Wearable Device
Authors: Fang Lei
Published: May 2022

As an important part of the education system, college physical education directly affects the comprehensive development of college students’ physical and mental quality. It is necessary to build a scientific and efficient evaluation index of college physical education teaching quality. Physical fitness monitoring is an important indicator for the quality evaluation of physical education. However, how to achieve lightweight, portable, and high-accuracy quantitative physical fitness monitoring is currently a major challenge. In order to solve the above challenges, this paper proposes a method of constructing a physical education quality evaluation index based on wearable devices. The wearable device collects human ECG signals, calculates the exercise intensity of participating students, and realizes quantitative evaluation of the quality of physical education teaching. Aiming at the problems of complex equipment and low accuracy of the existing exercise intensity detection methods, this paper proposes an ECG signal wave group detection algorithm based on a one-dimensional convolutional neural network (1D-CNN) to obtain the heart rate variability signal more accurately. After obtaining the ECG feature vector, the SVM classifier is used to predict the exercise intensity. In order to verify the effectiveness of the method in this paper, the real data collected from students of one university and a public available dataset are selected for experiments. The experimental results show that the method proposed in this paper achieves a good performance.
Topological Descriptors and Polynomials for Analysing the Structure of Antimony Telluride
Authors: Imran Shahid , Muzammil Isra , Nigar Niat , Siddiqui M. K. , Bashier E.
Published: May 2022

In a molecular network, molecules are correlated with numerical values, which are referred to as topological indices. The chemical and physical properties of chemical substances can be determined using topological indices. Mathematicians frequently use topological indices to calculate the strain energy, melting point, boiling temperature, distortion, and stability of chemical compounds. Topological indices also serve as a connection between a compound’s biological activity and its physical properties. In this research paper, we have computed degree‐based topological descriptors and polynomials to analyze the structure of antimony telluride.
Porous Silicon Formation by Electrochemical Etching
Authors: Kuntyi Оrest , Zozulya Galyna , Shepida Mariana
Published: May 2022

Porous silicon (PSi) is used as an effective material in biomedicine, sensors, solar cells, electrochemical energy, microelectronics, and nanotechnology. Considering the dependence of PSi functional properties on pore geometry and porous layer architecture, it is important to develop methods for controlled pore formation. After all, in the “procession” the method of obtaining PSi ⟶ pore geometry and architecture of PSi ⟶ functional properties of PSi, the decisive role belongs to the first participant. Among the most used methods, electrochemical etching is the most suitable for the controllability of the processes of nucleation and growth of pores since it can be controlled using the value of the current density, and the results are easily reproduced. This work analyses the literature on two types of electrochemical formation of PSi by anodic etching of (1) silicon surface and (2) silicon surface, modified with metal nanostructures. A modern explanation of the process of anodic dissolution of silicon with forming a porous surface in solutions containing HF is presented. The influence of such main factors on the process of anodic formation of PSi and its morphology is analyzed: the composition of the electrolyte and the role of each component in it; anode current density and methods of its supply (stationary, pulsed); duration; exposure to lighting; and temperature. Considerable attention is paid to the illustration of the role of alcohols and organic aprotic solvents on the formation of pore geometry. The influence of MNPs and metallic nanostructures on the process of localized metal-activated anodic etching of a semiconductor is analyzed.
Cell-free DNA as a Promising Diagnostic Biomarker in Prostate Cancer: A Systematic Review and Meta-Analysis
Authors: Zhang Cong , Chao Fan , Wang Shiyu , Han Dunsheng , Chen Gang
Published: May 2022

Objective. The detection of cell-free DNA (cfDNA) as a part of “liquid biopsy” of prostate cancer (PCa) has been widely explored. However, its diagnostic value for PCa remains controversial. Based on the data from the latest literature published in the past decade, the present review was conducted to clarify the diagnostic value of cfDNA in PCa. Methods. The related studies were systematically searched in the databases of PubMed, Embase, Web of Science, and Cochrane Library from January 1, 2010 to December 1, 2020. Sensitivity (SEN), specificity (SPE), and other relative parameters were pooled using a random model. Results. 14 eligible studies with 1049 PCa patients and 973 controls were selected based on the inclusion and exclusion criteria. Results demonstrated that cfDNA showed favorable SPE (0.89, 95% CI: 0.79, 0.94) but unsatisfied SEN (0.56, 95% CI: 0.43, 0.68) in the PCa diagnosis. The positive likelihood ratios (PLR), negative likelihood ratios (NLR), and diagnostic odds ratios (DOR) were 5.1 (95% CI: 3.1, 8.5), 0.49 (95% CI: 0.39, 0.63), and 10 (95% CI: 6, 17), respectively. The summary receiver operating characteristic graph (SROC) with an area under the curve (AUC) of 0.80 (95% CI: 0.76, 0.83) was constructed which indicated favorable diagnostic accuracy for PCa. Results of the subgroup analysis and metaregression analysis reminded “ethnicity” and “methylation” might be sources of heterogeneity. The potential publication bias was not found using Deek’s funnel plot asymmetry test (

p
>
0.05

). Conclusions. Our meta-analysis illustrated that the cfDNA could undertake a promising role in the PCa diagnosis.
Antibiotic Susceptibility Patterns of ESβL Producers Isolated from the Mobile Phones
Authors: NG Manjula , Borehalli Mayegowda Shilpa , Priyanka L. , Priyanka D. , Alghamdi Saad , Choudary Shalini , Sanchita V. , Chishmitha G. , Atwah Banan , Alhindi Zain , Islam Fahadul
Published: May 2022

Mobile phones have become an indispensable part of human lives for communication, education, and entertainment activities. This study aims to evaluate the diversity pattern of bacterial contaminants on mobiles and to check antibiotic resistance profiles in 105 samples. The study revealed a contamination of 51% in men and 49% in women, the highest in the 21- to 30-year age group, evidencing the extreme use of mobiles by teenagers. The study observed Gram-negative bacteria (63%) versus Gram-positive bacteria (37%). Overall, Gram-negative bacterial isolates showed the highest sensitivity to antibiotic nitrofurantoin (90%) and the lowest in ampicillin (35%). Gram positive has highest incidence of sensitivity towards tigecycline (100%) and lowest in cefoxitin (20%). ESβL producers were found to be 21.0% and highest being in Klebsiella oxytoca (35%) followed by Klebsiella pneumonia (31%). Staphylococcus pseudintermedius and Staphylococcus capitis have been identified on the mobile phones for the very first time. Interestingly, some soil microbes were also isolated and unfortunately found to have some antibiotic resistance like Raoultella ornithinolytica and Sphingomonas paucimobilis. The results revealed that mobiles were contaminated with multidrug-resistant (MDR) pathogens, and this study also showed that few of the saprophytic soil strains have antibiotic resistance, which can be an alarming situation that needs to be addressed.
Machine Learning: Supervised Algorithms to Determine the Defect in High‐Precision Foundry Operation
Authors: BramahHazela  , Hymavathi J. , Kumar T. Rajasanthosh , Kavitha S. , Deepa D. , Lalar Sachin , Karunakaran Prabakaran
Published: May 2022

In this paper, we represent a method for machine learning to predict the defect in foundry operation. Foundry has become a driving tool to produce the part to another industry like automobile, marine, and weapon. These foundry processes mainly have two critical problems to decrease the quality assurance. Now, we have to predict the defect to increase the quality of foundry operation. The foundry process’s failure is associated with micro shrinkage and ultimate tensile strength. We process by utilizing a machine learning classifier to predict the micro shrinkage and maximum tensile strength and describe the process, learning process, and evaluate the predataset from the foundry process to compare the accuracy and stability.
Computational Technologies for Pakistani Consumers’ Understanding of the Country-of-Origin Label for Fruit and Vegetable Products in Social Networks
Authors: Wang Bin , Li Hong , Zhou Chang-ming , Wu Ting
Published: May 2022

Whether or not consumers consider information about origin in their routine food purchase decisions is a contentious issue. Usage of social networks has redefined lifestyle and culture, and firms are finding it difficult to understand their customers. This study aims to investigate the effect of social networks (digital marketing) on Pakistani consumers’ understanding of the CoO (country-of-origin) label for F&V (fruit and vegetable) products and its relative importance in daily purchase decisions of fruit and vegetable products. In a random survey of 797 consumers in two Pakistani cities, we found that the relationship between the CoO information and the daily F&V product choices of Pakistani consumers was less important than other factors. Consumers are mistaken about the CoO label, with only one-third of respondents correctly understanding the difference between labels of “made in...” and “product of....” Therefore, mandatory CoO label policies may increase costs and reinforce consumers’ misinterpretation of the meaning of these labels; obtaining a “user-friendly” CoO label serves only those consumers who properly understand the information. This study contributes to understanding of the extent to which consumers are competent in their knowledge and understanding of these informational labels.
Numerical Simulation of CAARC Standard High-Rise Building Model Based on MRT-LBM Large Eddy Simulation
Authors: Zhao Rui , Feng Zehua , Dan Danhui , Wu Yuhang , Li Xianduo
Published: May 2022

The calculation of wind load of high-rise buildings depends on the wind pressure distribution data and wind pressure coefficient on the outer surface of the building, but the actual wind pressure measurement of high-rise buildings is difficult to carry out. In order to obtain the effective wind pressure coefficient of the building and the application of the extended lattice Boltzmann method (LBM) in the wind resistance of high-rise buildings, in this paper, the wall-adapting local eddy (WALE) model, dynamic Smagorinsky model (DSM), and Smagorinsky model (SM) are embedded into LBM with multiple-relaxation-time (MRT) format. Three LBM large eddy simulation models, MRT-LBM-WALE, MRT-LBM-DSM, and MRT-LBM-SM, which can simulate the flow around a bluff body with high Rayleigh number, are constructed by using the subgrid eddy viscosity to modify the kinematic viscosity of LBM. Finally, the three turbulence models are used to simulate and analyze the three-dimensional steady wind flow field of a single high-rise building of the standard CAARC high-rise building model in the atmospheric boundary layer, and the numerical results are analyzed and compared with the wind tunnel test results. The results show that the numerical simulation better reflects the flow characteristics and surface wind pressure of the wind environment around the high-rise building. On the windward side, it fits well with the test results. On the crosswind side and leeward side, the numerical simulation results are between the NPL and TJ-2 test results. The windward side is subject to positive pressure, which is the highest at 2/3 of the height of the windward side and low on both sides and below. The leeward and crosswind surfaces of the building are all under negative pressure. The simulation results of the three turbulence models have little difference, which provides a basis for the study of the flow around the bluff body of high-rise buildings. It is proved that the numerical solutions of the three models are in good agreement with the experimental solutions, and the real subgrid eddy viscosity near the wall can be obtained, which can accurately predict the development of turbulent flow.
Circ-GTF2I/miR-590-5p Axis Aggravates Myocardial Ischemia-Reperfusion Injury by Regulating Kelch Repeat and BTB Domain-Containing Protein 7
Authors: Yuan Chunju , Lu Jing , Chen Zhongpu , Zhou Qianxing
Published: May 2022

Purpose. We investigated the effect of the circular RNA (circRNA) general transcription factor IIi (GTF2I) on myocardial ischemia (MI) deterioration and neonatal rat cardiomyocyte damage. Methods. The cell experiment was performed by using neonatal rat cardiomyocytes. Moreover, a hypoxia/reoxygenation treatment model was established. Cell Counting Kit-8 assay was conducted, and EdU cell proliferation was detected. Cell apoptosis was detected via flow cytometry and quantitative RT-PCR (RT-qPCR). Binding detection was performed through a double-luciferase reporter assay. Interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), and lactate dehydrogenase (LDH) were detected via enzyme-linked immunosorbent assay (ELISA). Results. Compared with that in the sham and control groups, circ-GTF2I expression in MIRI and the hypoxia/reoxygenation treatment model was significantly upregulated in vivo and in vitro. The knockdown of circ-GTF2I relieved neonatal rat cardiomyocyte damage and MI. Further detection through the double-luciferase reporter assay confirmed that the binding site of circ-GTF2I to miR-590-5p and miR-590-5p was Kelch repeat and BTB domain-containing protein 7 (KBTBD7). ELISA and RT-qPCR results showed that circ-GTF2I induced the abnormal expressions of IL-6 TNF-α, LDH, Bax, Bcl-2, and Cyt-c in MIRI and the hypoxia/reoxygenation treatment models by regulating miR-590-5p and the heart development transcription factor KBTBD7. Conclusions. CircRNA circ-GTF2I aggravated MIRI and neonatal rat cardiomyocyte damage in vivo and in vitro by regulating miR-590-5p and the heart development transcription factor KBTBD7.
Association of RDW, NLR, and PLR with Atrial Fibrillation in Critical Care Patients: A Retrospective Study Based on Propensity Score Matching
Authors: Guan Yao-Zong , Yin Rui-Xing , Zheng Peng-Fei , Liu Chun-Xiao , Wei Bi-Liu , Deng Guo-Xiong
Published: May 2022

Objective. Previous studies have shown inconsistent results in relation to the red cell distribution width (RDW), neutrophil to lymphocyte ratio (NLR), and platelet to lymphocyte ratio (PLR) of atrial fibrillation (AF). This retrospective study is aimed at detecting the association of RDW, NLR, and PLR with AF. Methods. A total of 4717 critical care patients were screened from the Medical Information Mart for Intensive Care- (MIMIC-) III database. The patients were separated into the non-AF and AF groups. The imbalances between the groups were reduced using propensity score matching (PSM). ROC curves were generated to detect the diagnostic value of RDW, NLR, and PLR. Logistic regression analysis was used to detect the risk factors for AF. Results. A total of 991 non-AF patients paired with 991 AF patients were included after PSM in this study. The RDW level in the AF group was significantly higher than that in the non-AF group (

15.09
±
1.93

vs.

14.89
±
1.91

,

P
=
0.017

). Neither NLR nor PLR showed any significant difference between the two groups (

P
>
0.05

for each). According to ROC curve, RDW showed a very low diagnostic value of AF (

AUC
=
0.5341

), and the best cutoff of RDW was 14.1 (

ACU
=
0.5257

,

sensitivity
=
0.658

,

specificity
=
0.395

). Logistic regression analysis showed that an elevated RDW level increased 1.308-fold (

95
%
CI
=
1.077

-1.588,

P
=
0.007

) risk of AF. Neither elevated NLR nor elevated PLR was a significant risk factor for AF (

OR
=
0.993

,

95
%
CI
=
0.802

-1.228,

P
=
0.945

for NLR;

OR
=
0.945

,

95
%
CI
=
0.763

-1.170,

P
=
0.603

for PLR). Conclusions. Elevated RDW level but not NLR or PLR levels is associated with AF.

RDW
>
14.1

is a risk factor for AF, but its diagnostic capacity for AF is not of great value.
Gaussian Function Fusing Fully Convolutional Network and Region Proposal-Based Network for Ship Target Detection in SAR Images
Authors: Zhang Peipei , Xie Guokun , Zhang Jinsong
Published: May 2022

Recently, ship target detection in Synthetic aperture radar (SAR) images has become one of the current research hotspots and plays an important role in the real-time detection of sea regions. The traditional SAR ship detection methods usually consist of two modules, one module named land-sea segmentation for removing the complicated land regions, and one module named ship target detection for realizing fine ship detection. An algorithm combining the Unet-based land-sea segmentation method and improved Faster RCNN-based ship detection method is proposed in this paper. The residual convolution module is introduced into the Unet structure to deepen the network level and improve the feature representation ability. The K-means method is introduced in the Faster RCNN method to cluster the size and aspect ratio of ship targets, to improve the anchor frame design, and make it more suitable for our ship detection task. Meanwhile, a fine detection algorithm uses the Gaussian function to fuse the confidence value of sea-land segmentation results and the coarse detection results. The segmentation and detection results on the established segmentation dataset and detection dataset, respectively, demonstrate the effectiveness of our proposed segmentation methods and detection methods.
The Research of Multimedia Complex Intelligent System in Financial Reporting Mode
Authors: Li Yanqin , Li Xiaoping
Published: May 2022

With the development of science and technology, in order to provide better financial information for economic decision-making, people urgently need a new financial reporting model. For the existing financial reporting model, it is only published in PDF or HTML format. This paper introduces multimedia technology and XBRL to reform, and studies the financial reporting model under the multimedia complex intelligent system, which can effectively remedy the drawbacks of the existing financial reporting model. Firstly, this paper introduces the theory and technical basis of the financial reporting model; secondly, according to the specific needs, it designs the relevant functions; finally, combined with multimedia technology and network technology, the financial reporting system under multimedia complex intelligent system is constructed. In addition, through testing the system implemented in this paper, the performance and functional practicability of the system are analyzed, which shows that the financial reporting system designed in this paper is suitable for today’s economic environment and can provide financial information very well. When the number of process instances reaches 900 at the same time, the average flow cycle is only about 1.5 s.
Multisign Health Monitoring Technology of Athletes Based on Artificial Intelligence
Authors: Cai Long , Zheng Yuan
Published: May 2022

In order to improve the monitoring efficiency of physical fitness characteristics of athletes in training state, this paper proposes the research on athletes’ multisign health monitoring technology based on artificial intelligence sensor technology. Taking six excellent boxers as the experimental objects, four weeks of heavy load training and 10 training courses per week were arranged from six weeks before the competition to two weeks before the competition. The 4-week training is divided into two stages. From the first week to the fourth week, the training amount remains unchanged and the training intensity increases. The artificial intelligence sensor technology is used to design the athlete training state pulse test system. The athlete training state pulse sensor is responsible for collecting the athlete training state pulse data. The athlete pulse sensor in this system adopts zn17-kg200 pulse vibration sensor as the pulse sampling sensor. After 4 weeks of heavy load training, before and after adjusting for rest, venous blood was taken fasting on the next morning. White blood cells (WBC), red blood cells (RBC), hemoglobin (hemoglobin, Hb), testosterone (hemoglobin, H), cortisol (cortisol), and testosterone/cortisol ratio were measured. The experimental results showed that

T

and

T
/
C

of athletes were significantly lower than those before training (

P
<
0.01

), 37.99% and 52.69%, respectively.

C

and morning pulse were significantly higher than those before training (

P
<
0.05

), with an increase range of 32.39% and 20.39%. There was no statistical significance in the changes of WBC, RBC, and Hb. HRV indexes lnLF and LF/HF were significantly higher than those before training. Athletes carry the designed portable athlete training state pulse test for heavy load training and display the current training state pulse data of each athlete in real time. The experimental data show that the system designed in this paper can monitor the pulse information of athletes in the training state in real time. The monitoring has good real-time result and accuracy and can realize the abnormal pulse alarm, which has a certain practical value.
Study on the Effect of Apple Size Difference on Soluble Solids Content Model Based on Near-Infrared (NIR) Spectroscopy
Authors: Jiang Xiaogang , Zhu Mingwang , Yao Jinliang , Zhang Yuxiang , Liu Yande
Published: May 2022

Soluble solids content (SSC) is a vital evaluation index for the internal quality of apples, and NIR spectroscopy is the preferred technique for predicting the SSC of apples. Due to the differences in fruits’ sizes, their SSC prediction models have poor robustness and low prediction accuracy, so it is important to eliminate the effects brought by the differences in fruit sizes to improve the accuracy of fruit sorting models. The NIR spectra of apples with different fruit sizes were collected by applying NIR spectroscopy online detection device, and after various preprocessing of the spectra, the partial least squares (PLS) models of apple SSC were established, respectively, and then the modeling set in the apple fruit size group of 75 mm–85 mm was used to predict the prediction set samples in the apple fruit size group of 65 mm–75 mm and 85 mm–95 mm, respectively. To better address the effects of apple size differences, data fusion techniques were used to perform an intermediate fusion of apple fruit diameter and spectra, firstly, the competitive adaptive reweighting algorithm (CARS) and the continuous projection algorithm (SPA) were used to select spectral variables and build their prediction models for apple SSC, respectively, and the results showed that the models built with 61 spectral variables selected by CARS had better performance, greatly reduced the amount of data involved in modeling, effectively simplified the model, and improved the stability of the model. The apple size variables were added to the wavelength variables selected by CARS, and the data were normalized to establish a PLS model of apple SSC with the normalized spectral and apple fruit diameter data, and the results showed that the size compensation model based on intermediate fusion had the best prediction performance, with the prediction set Rp of 0.886 for fruit diameter of 65 mm–75 mm, RMSEP of 0.536%, and its prediction set Rp was 0.913 and RMSEP was 0.497% for the fruit diameter of 85 mm–95 mm. Therefore, adding the fruit diameter variable to establish the size-compensated model of apple SSC can improve the prediction performance of the model.
The Superficial Temporal Artery and Zygomatico‐Orbital Artery: Superficial Arterial Distribution of the Anterior Temple Area
Authors: Park Hyun Jin , Lee Ji-Hyun , Jung Wonsug
Published: May 2022

A hollow temple may give rise to a false impression of early facial aging. This is corrected with dermal fillers that are injected into the hollow temple area to produce a smoother facial contour. However, various complications of this procedure have been reported, with the most common being the inadvertent injection of the filler material into the superficial temporal artery (STA). The aim of this study was to investigate the topographic anatomy of the STA and zygomatico‐orbital artery (ZOA) to provide essential anatomical information to aid in various clinical procedures involving the temporal region. The superficial arterial distribution of the temple area was studied in 43 hemisectioned Korean cadavers. The courses of the STA and ZOA were identified and classified based on the line connecting the tragus and the superciliary arch (TR‐SA line). The ZOA was present in 85.2% of cases and bifurcated from the frontal branch of the STA, after which it ran along the TR‐SA line. In this study, the STA pattern was classified into a typical pattern where the ZOA coexists with the STA and a lower pattern where the ZOA was absent. The current findings suggested that the ZOA ran close to the TR‐SA line. Therefore, to minimize vascular complications during invasive procedures, injection into this area should be avoided. In addition, clinicians should verify the existence of ZOA and the course of STA before performing various clinical procedures.
Comparing the Transcriptomes of Two Different Tissues in Helicoverpa assulta (Guenée)
Authors: Zhang Hailing , Li Kuiyin , Zhang Yubo
Published: May 2022

Helicoverpa assulta (Guenée), a moth species belonging to the Noctuidae (Lepidoptera) family, is a destructive agricultural pest that infests multiple cash crops. To assess differences in the gene expression profiles of different tissues in H. assulta, we analyzed the transcriptomes of two tissue types (midgut and hemocytes) using the Illumina Hiseq 2000 platform, on the basis of which we obtained 52076750 and 53404200 high-quality clean reads, respectively. De novo assembly yielded 46146 and 33707 unigenes from the midgut and hemocytes, respectively. After screening, we identified 23726 unigenes differentially expressed between the midgut and hemocytes. Taking the midgut as the control, we detected 7448 and 16278 unigenes that were up- and downregulated in hemocytes, respectively. Gene Ontology functional annotation divided the differentially expressed unigenes (DEUs) into three categories (biological process, cellular component, and molecular function) and 51 branches, whereas the Kyoto Encyclopedia of Genes and Genomes metabolic pathway annotation assigned the DEUs to six categories, mapping these to 258 pathways. In addition, we detected 224918 single-nucleotide polymorphic sites. Our findings based on transcriptome sequencing, data assembly, and functional gene annotation of two different tissues in H. assulta will provide a valuable reference for further excavation and study of functional genes in H. assulta.
Merging Sequence Optimization Based on Reverse Auction Theory and Merging Strategy with Active Trajectory Adjustment of Heterogeneous Vehicles
Authors: Wang ShiHui , Zhao Min , Sun DiHua , Liu Xiaoyu
Published: May 2022

This paper investigates the optimized merging sequence (MS) and on-ramp merging strategy in mixed traffic with vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I). To this end, a cooperative merging sequence optimization method is first proposed based on the reverse auction. In the method, a hybrid optimized computing structure is proposed to provide the foundation for connected and human-driving vehicles (CHVs) and connected and automated vehicles (CAVs) to obtain the MS more efficiently. And a cooperative merging strategy based on all cooperative merging vehicles under mixed traffic conditions is proposed. In particular, the downstream vehicles in the strategy can change their original velocities to actively participate in the cooperative merging process according to the merging requirements of on-ramp vehicles. And the vehicles in this strategy are all subject to state constraints to avoid the adverse effects of cooperative merging behavior on the following traffic on the main road. Results of numerical experiments illustrate that the merging sequence optimization method can reduce the time to obtain the optimal MS, and the increased computational efficiency is affected by CAV penetration. In addition, in mixed traffic conditions, the cooperative merging strategy can reduce fuel consumption and the time required for merging.
A Graph-Related High-Order Neural Network Architecture via Feature Aggregation Enhancement for Identification Application of Diseases and Pests
Authors: Kong Jianlei , Yang Chengcai , Xiao Yang , Lin Sen , Ma Kai , Zhu Qingzhen
Published: May 2022

Diseases and pests are essential threat factors that affect agricultural production, food security supply, and ecological plant diversity. However, the accurate recognition of various diseases and pests is still challenging for existing advanced information and intelligence technologies. Disease and pest recognition is typically a fine-grained visual classification problem, which is easy to confuse the traditional coarse-grained methods due to the external similarity between different categories and the significant differences among each subsample of the same category. Toward this end, this paper proposes an effective graph-related high-order network with feature aggregation enhancement (GHA-Net) to handle the fine-grained image recognition of plant pests and diseases. In our approach, an improved CSP-stage backbone network is first formed to offer massive channel-shuffled features in multiple granularities. Secondly, relying on the multilevel attention mechanism, the feature aggregation enhancement module is designed to exploit distinguishable fine-grained features representing different discriminating parts. Meanwhile, the graphic convolution module is constructed to analyse the graph-correlated representation of part-specific interrelationships by regularizing semantic features into the high-order tensor space. With the collaborative learning of three modules, our approach can grasp the robust contextual details of diseases and pests for better fine-grained identification. Extensive experiments on several public fine-grained disease and pest datasets demonstrate that the proposed GHA-Net achieves better performances in accuracy and efficiency surpassing several other existing models and is more suitable for fine-grained identification applications in complex scenes.
Investigation of Tribological Behaviour on DLC Coatings for AA5051 using DC Sputtering
Authors: Natrayan L. , Gaur Piyush , Merneedi Anjibabu , Kaliappan S. , Patil Pravin P. , Sivaprakash V. , Chewaka Muse Degefe
Published: May 2022

DLC coatings are deposited on aluminium substrates to improve the wear resistance property of the substrates using sputtering deposition in this study. DLC coatings are deposited using the graphite target onto the Al5051 substrates using DC sputtering. The deposited coatings are then analyzed for their adhesion strength, hardness, coefficient of friction, and chemical compositions. The pin-on-disk method is conducted in vacuumed conditions, dry air conditions (0% RH), and ambient air conditions (40% RH). The different testing conditions have shown different results for the same testing sample. This indicates the nature of DLC film adsorption in ambient air conditions. The chemical composition study has further revealed the adsorbing compounds and the ability of hydrogen and water molecules to get adsorbed on the thin-film surface. This study gives insight into the effect of molecules present in the ambient air on the performance of DLC coatings. It investigates the effect of three DLC coatings deposited using the graphite target onto the Al5051 substrates using DC sputtering.
Tension Strength and Fiber Morphology of Agave Cantala Roxb Leaves due to Liquid Smoke Immersion Treatment
Authors: Palungan Musa Bondaris , Muslimin Mukhlis
Published: May 2022

In this work, we investigate the fiber tensile strength of the Agave cantala roxb leaves based on the treatment of immersion in liquid smoke which was obtained from mature coconut shells. Four different time variations of treatments, namely, one hour, two hours, three hours, and four hours, have been carried out. After the immersion, we investigated the chemical contents of the Agave cantala using scanning electron microscope (SEM) which is equipped by energy dispersive spectroscopy (EDS). Furthermore, the tension strength is tested using tensile strength plus 50 N. The test is applied for a single Agave cantala fiber. The results of the tensile test of single fiber showed an increase in tensile strength when compared with fiber tensile strength without immersion. The tensile strength of a single fiber of Agave cantala leaves increased with increasing duration of immersion time. After reaching a certain strength, however, the strength of the fiber decreases. The tensile strength of a single fiber without immersion is 192.85 MPa and the highest is 670.82 MPa for Agave cantala after immersion for three hours, with an elongation of 0.68 mm. By increasing the tensile strength of Agave cantala through liquid smoke immersion treatment, it can potentially improve its performance as a material composite reinforcement.
Troponin I Cutoff for Non-ST-Segment Elevation Myocardial Infarction in Sepsis
Authors: Tsai Meng-Ko , Lai Chao-Hung , Hung Chia-Lien , Wu Keng-Yi
Published: May 2022

The diagnostic value and optimal cutoff level of cardiac troponin I in patients with sepsis have not been studied. In this single hospital retrospective study, we assessed the optimal cutoff value of troponin I for diagnosing non-ST-segment elevation myocardial infarction (NSTEMI) with type 1 myocardial infarction (MI) in patients with sepsis who had undergone a percutaneous coronary intervention from 2009 to 2019. In total, 5,341 patients (excluding patients with chronic kidney disease) were included, of whom 277 had sepsis or septic shock. Of the 123 patients with non-ST-segment elevation acute coronary syndrome (NSTE-ACS) and sepsis, 77 (62.6%) were diagnosed with NSTEMI with type 1 MI. The receiver-operating characteristic curve showed an area under the curve (AUC) of 0.705 for diagnosis of NSTEMI with type 1 MI with a troponin I cutoff of >300 ng/L (sensitivity: 68.4%, specificity: 70.2%, Youden index: 0.386). Multiple linear regression showed no significant predictors of NSTEMI with type 1 MI. Troponin level and the Global Registry of Acute Coronary Events (GRACE) scores were correlated (

R

2

=
0.0625

,

p
=
0.032

) and showed comparable predictive value for 6-month mortality (AUC: 0.637 and 0.611, respectively,

p
=
0.7651

). The optimal troponin I cutoff to effectively diagnose NSTEMI with type 1 MI in patients with sepsis was 300 ng/L.
A Hybrid Model for the Impact of COVID-19 Prevention Measures on the Sustainable Development of the Aviation System
Authors: Zhu Hongli , Qin Yang , Zhao Qiao , Zhao Qirui
Published: May 2022

An airport is a complicated system that serves as a vital link in the aviation system. Airplanes are also a popular mode of transportation for daily travel and tourism. Now that COVID-19 is spreading over the world, many airlines are under severe financial strain. Therefore, long-term air traffic planning is critical, especially since the airport is a key region for COVID-19 to expand. To anticipate, simulate, and estimate the medical and health expenditures caused by the propagation of the epidemic under lax, mild, and strict social contact intervention, we utilize a hybrid model of the agent-based model and discrete event simulation. An agent-based model can capture individual behavior, and discrete event simulation can be used to explain the entire boarding process. Limiting the rate of wearing masks while traveling and upgrading airport facilities are the most effective strategies to manage the epidemic, given the convenience of travelers and the swift recovery of the national economy. Simulating passenger boarding will aid government agencies in improving airport equipment and facilities, facilitating passengers’ reasonable travel plans, avoiding large-scale contact, preventing the spread of epidemic diseases, and promoting the long-term sustainability of densely populated public transportation systems such as airports.
Network Information Security Platform Based on Artificial Intelligence for the Elderly’s Health “Integration of Physical, Medical, and Nursing Care”
Authors: Yang Zongyou , Xia Siyong , Feng Sheng
Published: May 2022

With the development of my country’s economy and society and the improvement of civilization, the silver wave has gradually come. The country has launched a multifaceted pension model, such as institutional pension, home-based pension, and pension real estate. With the increasing aging of the population, traditional elderly care services can no longer meet the growing needs of the elderly. This research mainly discusses the construction of a network information security platform based on artificial intelligence for the elderly’s health “integration of physical, medical, and nursing care.” The platform consists of five modules: health records, follow-up plans, remote training, health education, and remote consultation. Each module is equipped with a corresponding main interface and/or subinterface. Some modules also have submodules as needed. The structure is reasonable, and the interface is displayed. The combined medical care service model is divided into medical care, care care, and medical care. Among them, the medical care model mainly provides long-term comprehensive care services for the disabled, demented, semidisabled, and other elderly groups. The support-oriented model is mainly for self-care or semi-self-care elderly groups, providing rehabilitation monitoring and life care services. In terms of the overall effect of the platform, 13 users (81.25%) gave a high evaluation of the overall effect of the platform. This research will promote the development of the smart elderly care industry.
Parking Resource Allocation Optimization Framework Based on a Two-Level Grid Model
Authors: Guo Haonan , Wang Yun , Yan Xuedong , Guan Yunlin , Zhou Yu
Published: May 2022

With the rapid increase in vehicle population, solving difficult-to-park and inconvenient-to-park problems has become a necessity for sustainable transportation in major cities. This study investigated the parking resource allocation optimization problem based on a two-level grid model. To address this problem, first users’ travel data were matched to the map to obtain the distribution of both parking resources and demands. Second, key demand-supply imbalanced grids were identified. Subsequently, the parking resource allocation optimization problem was formulated as an integer linear programming (ILP) problem aiming to minimize the total cost, including the parking facility construction cost, users’ total walking distance, and the penalty for unserved users. Finally, a case study based on real-world data in Cangzhou was conducted to verify the feasibility and effectiveness of the proposed method. The results show that the imbalance between the supply and demand of parking resources can be effectively alleviated.
Electrochemical-Based Extraction, Separation, and Purification of Coumarin Compounds from Trifolium chinensis
Authors: Zhu Yujie , Wang Wenle , Ruan Renyu , Chen Jinquan
Published: May 2022

In order to deal with the problems of the unstable transformation process and volatile palatability of coumarin compounds in C. chinensis, a method for the extraction, separation, and purification of coumarins in Chinese medicinal materials based on electrochemistry was prepared. First, an electrochemical distance-independent localization mechanism is used to determine node locations and routing mechanisms, and an extraction method is designed to achieve automatic and accurate real-time collection, aggregation, and transmission of ever-growing data. Environmental information for C. chinensis is collected. On the basis of this method, according to the chemical properties of coumarin and the extraction rate of coumarin as an index, the two-phase solvent extraction method and macroporous adsorption resin method were used to separate and purify it, and the best separation was determined. The purification process achieves efficient purification of coumarin. The experimental results show that the retention rate of coumarin by ethyl acetate is 34.5–56.8% higher than that of the other three extractants. When the optimal process determined in this study is adopted, the coumarin adsorption rate is greater than 98% and the recovery rate is greater than 85%. The purity of samples with 50% coumarin content can be increased to more than 97%, which verifies the correctness and advancement of the separation and purification process in this study.