bluuebunny/crossref_metadata_2025 huggingface dataset:
Enhancing Security-Problem-Based Deep Learning in Mobile Edge Computing
Authors: Zheng Xiao , Li Mingchu , Shah Syed Bilal Hussain , Do Dinh-Thuan , Chen Yuanfang , Mavromoustakis Constandinos X. , Mastorakis George , Pallis Evangelos
Published: May 2022

The implementation of a variety of complex and energy-intensive mobile applications by resource-limited mobile devices (MDs) is a huge challenge. Fortunately, mobile edge computing (MEC) as a new computing paragon can offer rich resources to perform all or part of the MD’s task, which greatly reduces the energy consumption of the MD and improves the quality of service (QoS) for applications. However, offloading tasks to the edge server is vulnerable to attacks such as tampering and snooping, resulting in a deep learning (DL) security feature developed by major cloud service providers. An effective security strategy method to minimize ongoing attacks in the MEC setting is proposed. The algorithm is based on the synthetic principle of a special set of strategies, and it can quickly construct suboptimal solutions even if the number of targets achieves hundreds of millions. In addition, for a given structure and a given number of patrollers, the upper bound of the protection level can be obtained, and the lower bound required for a given protection level can also be inferred. These bounds apply to universal strategies. By comparing with the previous three basic experiments, it can be proved that our algorithm is better than the previous ones in terms of security and running time.
Secure and Efficient Hybrid Data Deduplication in Edge Computing
Authors: Shin Hyungjune , Koo Dongyoung , Hur Junbeom
Published: May 2022

As an extension of cloud computing, edge computing introduces additional intermediate devices, called edge nodes near clients, providing computing services on behalf of the central cloud more efficiently. Although edge computing brings several benefits such as low latency and bandwidth savings on the edge side, rapid increase in the amount of data transmitted to the central cloud hinders efficient utilization of the storage system on the central cloud side especially when the data from edge devices are encrypted. To mitigate this issue in a privacy-preserving manner, data deduplication techniques for encrypted data have been extensively studied to enhance both the security and efficiency in the conventional cloud system with two different approaches. A server-side secure deduplication approach protects data privacy but impairs network efficiency by allowing duplicate uploads, while a client-side one improves network efficiency but suffers from potential information leakage due to its vulnerability to the side-channel attack. In this article, we propose a hybrid secure deduplication scheme for edge computing, which guarantees both advantages of the aforementioned two approaches. Specifically, our scheme guarantees data privacy by applying the server-side deduplication technique between the client and the edge nodes and maximizes network efficiency through the client-side deduplication technique between the edge nodes and the cloud. In addition, we devise a novel additively homomorphic encryption for efficient deduplication operations in the resource-limited edge nodes. Based on our experimental results, the proposed scheme reduces the communication costs by approximately 2.5 times for a storage server when the duplicate ratio is 50%, and the response time is reduced by about 2 times when the data size is 16 MB.
Bad Mouths: Taboo and Transgressive Language
Authors: Miller Laura
Published: May 2022

The academic literature on taboo language is flourishing not only in fields such as linguistic anthropology or sociolinguistics, but also in disciplines that usually target language itself as the object of study. Although there is more than a century of scholarly writing on taboo language, new and neglected areas and directions continue to provide valuable insights on a universal linguistic behavior. This review tracks four sometimes overlapping clusters: naming and linguistic avoidance behaviors, taboo language and transgression, taboo language in language contact situations, and taboo language in educational settings and other contexts. The discussion in this review includes examples of how taboo language is inextricably meshed with the relationships found among kinship circles, subcultural group members, generational cohorts, and other social groupings. New areas of research that are proving to be attractive to scholars include taboo language in global media translation, subtitling or scalation, language contact situations, and the teaching of taboo terms in second language instruction.
Best Practices on Big Data Analytics to Address Sex-Specific Biases in Our Understanding of the Etiology, Diagnosis, and Prognosis of Diseases
Authors: Golder Su , O'Connor Karen , Wang Yunwen , Stevens Robin , Gonzalez-Hernandez Graciela
Published: May 2022

A bias in health research to favor understanding diseases as they present in men can have a grave impact on the health of women. This paper reports on a conceptual review of the literature on machine learning or natural language processing (NLP) techniques to interrogate big data for identifying sex-specific health disparities. We searched Ovid MEDLINE, Embase, and PsycINFO in October 2021 using synonyms and indexing terms for ( a) “women,” “men,” or “sex”; ( b) “big data,” “artificial intelligence,” or “NLP”; and ( c) “disparities” or “differences.” From 902 records, 22 studies met the inclusion criteria and were analyzed. Results demonstrate that the inclusion by sex is inconsistent and often unreported, although the inclusion of men in these studies is disproportionately less than women. Even though artificial intelligence and NLP techniques are widely applied in healthresearch, few studies use them to take advantage of unstructured text to investigate sex-related differences or disparities. Researchers are increasingly aware of sex-based data bias, but the process toward correction is slow. We reflect on best practices on using big data analytics to address sex-specific biases in understanding the etiology, diagnosis, and prognosis of diseases.
The Use of Scanner Data for Economics Research
Authors: Dubois Pierre , Griffith Rachel , O'Connell Martin
Published: May 2022

The adoption of barcode scanning technology in the 1970s gave rise to a new form of data: scanner data. Soon afterwards, researchers began using this new resource, and since then a large number of papers have exploited scanner data. The data provide detailed price, quantity, and product characteristic information for completely disaggregate products at high frequency, and they typically track a panel of stores and/or consumers. Their availability has led to advances, inter alia, in the study of consumer demand, the measurement of market power, firms’ strategic interactions and decision making, the evaluation of policy reforms, and the measurement of price dispersion and inflation. In this article we highlight some of the pros and cons of this data source, and we discuss some of the ways its availability to researchers has transformed the economics literature.
Mapping Human Reproduction with Single-Cell Genomics
Authors: Marečková Magda , Massalha Hassan , Lorenzi Valentina , Vento-Tormo Roser
Published: May 2022

The trillions of cells in the human body develop as a result of the fusion of two extremely specialized cells: an oocyte and a sperm. This process is essential for the continuation of our species, as it ensures that parental genetic information is mixed and passed on from generation to generation. In addition to producing oocytes, the female reproductive system must provide the environment for the appropriate development of the fetus until birth. New genomic and computational tools offer unique opportunities to study the tight spatiotemporal regulatory mechanisms that are required for the cycle of human reproduction. This review explores how single-cell technologies have been used to build cellular atlases of the human reproductive system across the life span and how these maps have proven useful to better understand reproductive pathologies and dissect the heterogeneity of in vitro model systems.
Architectural Glass
Authors: Wiederhorn Sheldon M. , Clarke David R.
Published: May 2022

Recent decades have seen growing and widespread adoption of glass as an architectural material that can be used not only as window panes but also as facades, walls, and roofs. This is despite glass traditionally being considered a brittle material, not readily capable of handling the high loads required of architectural materials. Architectural glass has enabled the vaulted, transparent structures of many modern airport terminals and eye-catching buildings, such as the ubiquitous all-glass Apple Stores found around the world. Glass has enabled architects to expand their visions of buildings, using light and space to create wonderful new designs. As described in this review, these dramatic new possibilities for how glass is used in architecture have been the result of a convergence of many developments, including a better understanding of the fracture of glass, new processes for strengthening glass, confidence in large-scale finite element modeling of gravitational and wind loads, advances in the lamination of glass sheets, and the availability of ever larger individual sheets of float glass. The concurrent evolution of standards for the use of glass in buildings has also played a role in advancing the use of architectural glass. Advances in the architectural use of glass have their roots in the traditional uses and physical understanding of the properties of glass that have developed over hundreds of years.
Women's Health: Population Patterns and Social Determinants
Authors: Short Susan E. , Zacher Meghan
Published: May 2022

Women's health, and what we know about it, is influenced by social factors. From the exclusion of women's bodies in medical research, to the silence and stigma of menstruation and menopause, to the racism reflected in maternal mortality, the relevance of social factors is paramount. After a brief history of research on women's health, we review selected patterns, trends, and inequalities in US women's health. These patterns reveal US women's poor and declining longevity relative to those in other high-income countries, gaps in knowledge about painful and debilitating conditions that affect millions of women, and deep inequalities that underscore the need to redress political and structural features of US society that enhance health for some and diminish it for others. We close by describing the challenges and opportunities for future research, and the promise of a social determinants of health approach for advancing a multilevel, intersectional, and biosocial understanding of women's health.
Cyclic Nucleotide Signaling in Phage Defense and Counter-Defense
Authors: Athukoralage Januka S. , White Malcolm F.
Published: May 2022

Advances in our understanding of prokaryotic antiphage defense mechanisms in the past few years have revealed a multitude of new cyclic nucleotide signaling molecules that play a crucial role in switching infected cells into an antiviral state. Defense pathways including type III CRISPR (clustered regularly interspaced palindromic repeats), CBASS (cyclic nucleotide-based antiphage signaling system), PYCSAR (pyrimidine cyclase system for antiphage resistance), and Thoeris all use cyclic nucleotides as second messengers to activate a diverse range of effector proteins. These effectors typically degrade or disrupt key cellular components such as nucleic acids, membranes, or metabolites, slowing down viral replication kinetics at great cost to the infected cell. Mechanisms to manipulate the levels of cyclic nucleotides are employed by cells to regulate defense pathways and by viruses to subvert them. Here we review the discovery and mechanism of the key pathways, signaling molecules and effectors, parallels and differences between the systems, open questions, and prospects for future research in this area.
Analysis of Pore Structure and Thaw Settlement Characteristics of Frozen Silty Sand Based on Computer-Assisted Pulse Nuclear Magnetic Resonance
Authors: Ma Maoyan , Zhang Biao , Peng Shuguang
Published: May 2022

Computer-assisted pulse nuclear magnetic resonance (NMR) can be used to get important parameters for pore structure characteristics of porous materials. In order to fully understand the effect of frozen soil thaw settlement, the mechanism of artificially frozen soil thaw settlement was examined from a microscopic perspective in conjunction with the frozen soil thaw settlement test. Additionally, to have a better understanding of how pore features change during the thaw settling process, the evolution of the pore size distribution in silty sand was studied. The findings demonstrate the porosity is obviously larger than the initial porosity after freeze-thaw, and the evolution of thaw settlement displacement is related to the change in porosity as thawing progresses, which grows exponentially with porosity. The fraction of medium and large pores (>0.1 μm) in the soil increases significantly during the thawing process. Accordingly, there is a slight increase in the proportion of pores (<0.1 μm) during the thawing progress. The variation in the pore size distribution of silty sand is compatible with that in settlement displacement during the thawing process. Additionally, the thaw settling rate’s development law is consistent with that of the proportion of pores. The number of medium and large pores is critical in determining the rate of thaw settlement. In other words, the development law of thaw settlement rate is consistent with the development law of medium and large pore size distribution.
Experimental Study on the Anisotropy and Non-coaxiality of Frozen Standard Sand under Different Principal Stress Directions
Authors: Chen Dun , Li Guoyu , Zhao Xiaodong , Ma Wei , Zhou Zhiwei , Mu Yanhu , Lai Zejin , Chen Tuo
Published: May 2022

Owing to the limitations of the apparatus, the influence of its principal stress direction on the anisotropic behavior and non-coaxiality of frozen soil has not been fully considered in previous studies. At a temperature of -10°C, a series of hollow cylinder tests for frozen standard sand (FSS) was conducted under different directional angles of major principal stress and mean principal stresses in this study. The experimental results indicate that the stress-strain-strength anisotropy and non-coaxiality of the FSS are highly dependent on the principal stress direction. The stress components of the FSS vary linearly with increasing shear stress at different directional angles of the major principal stress and mean principal stresses. With a linear increase in shear stress, the strain components of the FSS exhibited a nonlinear increasing trend. The FSS strength gradually decreased as the directional angle of the major principal stress and the mean principal stresses in the test range increased. Under the different principal stress directions, the non-coaxiality of the FSS, non-coincidence of the direction of the principal strain increment and the principal stress direction, were observed. The directions of the principal strain increment and principal stress gradually tended to be coaxial as shear stress increased. Although the non-coaxial angle of the FSS increased gradually with an increase in the directional angles of the major principal stress, it did not change with the change in the mean principal stress. The non-coaxial angle of the FSS was observed to be as large as 35° in the early stage of shearing under different mean principal stresses.
Fault Diagnosis Method for UHVDC Transmission Based on Deep Learning under Cloud-Edge Architecture
Authors: Zhou Shihao , Pan Benren , Lu Dongbin , Zhong Yiming , Wang Guannan
Published: May 2022

Aiming at the problem of fault diagnosis after the UHVDC system fails, a deep learning-based UHVDC fault diagnosis method under the cloud-edge architecture is proposed. First, based on the edge computing framework of the “cloud” + “edge terminal,” a four-layer fault diagnosis structure including the data integration layer, edge prediction layer, cloud diagnosis layer, and human-computer interaction layer is constructed. Then, a fault data set is constructed by finding effective information that can fully reflect the DC fault in the huge power grid environmental information, and the data set is screened, processed by classification feature fields, and linearly normalized. Finally, a deep convolutional generative adversarial network (DCGAN) is constructed by introducing a deep convolutional neural network (DCNN) into the traditional generative adversarial network (GAN) for data training and DC fault diagnosis. In addition, the corresponding process is given. The proposed method and the other three methods are compared and analyzed by simulation experiments. The results show that the method proposed has the highest accuracy and smallest error loss value of 95.6% and 0.18, respectively. It has the highest diagnosis accuracy under different fault types, and its performance is better than the other three comparison methods.
The Correlation between Stress Levels among Undergraduate Medical Students and Their Motivation for Studying Medicine
Authors: Alotiby Amna A.
Published: May 2022

Objective. This study aimed to investigate the relationship between undergraduate medical students’ motivations to study medicine and their stress levels in Saudi Arabia. This relationship has not previously been investigated in depth but is urgently required to help improve the academic performance of such students and protect them from academic burnout. Method. A questionnaire was created and shared on the official social media platforms of the Faculty of Medicine, Umm Alqura University, Makkah City, Saudi Arabia. A total of 572 students currently studying for a bachelor’s degree in medicine were recruited. Cross tabulation to determine the distribution of students’ stress levels in relation to their personal data and motivation to study medicine was conducted, using a Pearson chi-square test to assess significance. Results. A significant (

P
=
0.049

) relationship between two types of motivation among undergraduate medical students and their levels of stress was found. Students driven by intrinsic motivation had lower levels of stress than their colleagues and counterparts, whereas extrinsic motivation resulted in increased levels of stress. Furthermore, older female students and those in the advanced stages of their studies (years 4 and 5) were more likely to be stressed. Conclusion. Stress levels among undergraduate medical students were found to correlate with their motivation to study medicine. Intrinsic motivation needs to be promoted, which would help students view their accomplishments more positively and help protect them from burnout.
A Novel Numerical Treatment of Nonlinear and Nonequilibrium Model of Gradient Elution Chromatography considering Core-Shell Particles in the Column
Authors: Ahmad Abdulaziz Garba , Kaabar Mohammed K. A. , Rashid Saima , Abid Muhammad
Published: May 2022

An extended method of semidiscrete high-resolution finite volume is used in this paper to obtain numerical solutions for a formulated nonlinear lumped kinetic model of liquid chromatographic process to examine the effect of chromatographic column overloading gradient elution considering core-shell particles. The model constitutes linear solvent strength (LSS), Henry’s constant, coefficient of nonlinearity, and coefficient of axial dispersion. The effects of modulator concentration changes for the elution of single and two components are analyzed. The advantages of introducing gradient elution against isocratic elution in terms of core radius fraction are investigated intensively. Numerical temporal moments are generated from the solutions obtained for a more in-depth examination of the considered model. Moreover, multiple forms of a single- and two-component mixture are generated to analyze the influences of core radius fractions on gradient elution. For example, the obtained results are utilized to investigate the effects of the slope of gradient, concentration of modulator, solvent strength parameter, coefficient of nonlinearity, coefficient of mass transfer, and coefficient of axial dispersion on the profiles of concentration in order to improve the process performance using optimal core radius fraction parameter values.
An Improved Particle Swarm Optimization Algorithm and Its Application to the Extreme Value Optimization Problem of Multivariable Function
Authors: Cai Min
Published: May 2022

It is proposed to improve the study of particle optimization and its application in order to solve the problem of inefficiency and lack of local optimization skills in the use of particle herd optimization. Firstly, the basic principle, mathematical description, algorithm parameters, and flow of the original (Particle Swarm Optimization, PSO) algorithm are introduced, and then the standard PSO algorithm is introduced; thirdly, over the last 10 years, four types of improvements have been proposed through the study of improved particle algorithms. The improved algorithm is applied to the extreme value optimization problem of multivariable function. The simulation results show that the basic (Cloud Particle Swarm Optimization, CPSO) algorithm within 500 generations has not reached convergence for 8 times, 6 times, 4 times, and 5 times, respectively. In the case of convergence, the average number of steps is much higher than ICPSO, and the improved algorithm converges completely. In terms of time performance, the convergence time of ICPSO is much better than that of CPSO algorithm. Therefore, the improved particle optimization algorithm ensures the effectiveness of the improvement measures, such as small optimization algebra, fast merging speed, high efficiency, and good population diversity.
Learning Chinese Classical Music with the Aid of Soundscape by Using Intelligent Network
Authors: Zhang LiLan
Published: May 2022

A soundscape is a sound environment of the awareness of auditory perception and social or cultural understanding. To improve the subjective initiative of the Chinese classical music students, this study explores new learning modes and methods using soundscape and investigates its learning effect using intelligent music software. To examine the emotional experience of players in playing before and after learning, 50 students from music majors and 50 from non-music majors were selected. Results show that in the positive and negative emotional classical music experiment, most music majors and non-music majors have weak emotional experience at the beginning, and only a few have a strong emotional experience, which could reach 6 points. In the second scoring, most majors have a score of about 7 points, indicating strong emotional experience and a few have a score of about 4 points and 9 points, representing that there were relatively few majors with weak emotional experience and strong emotional experience. The overall emotional experience score is low in the comparison between non-music majors and music majors, and the second score in the entire experiment is significantly higher than the first score, signifying that the learning effect of players is obvious, and intelligent music software and soundscape play a role in the exploration of Chinese classical music.
Multiple Consecutive Cervicovaginal Cytology Specimens Confirm Persistent Colonization by Cokeromyces recurvatus: Case Report and Literature Review
Authors: Lor Keng , Hartley Christopher P. , Pritt Bobbi S. , Kemp Anna M. , Swanson Amy A. , Sturgis Charles D.
Published: May 2022

The published literature on cervicovaginal cytology includes fewer than ten reported cases of Cokeromyces recurvatus identified in Pap test samples. We report a unique case of an asymptomatic 27-year-old female with persistent gynecologic tract colonization by C. recurvatus in which distinctive fungal microorganisms were identified in three samples collected over three consecutive years.
Application of Fluorescence Dye in Combination with Methylene Blue for Axillary Reverse Mapping in Patients with Modified Radical Mastectomy for Breast Cancer
Authors: Wang Haiyi , Wu Baochao , Wang Zheng
Published: May 2022

Background. Axillary reverse mapping (ARM) is a novel intraoperative technique developed in recent years. This study was aimed at determining the effect of combined use of fluorescence dye and methylene blue, as well as its feasibility of ARM in patients with breast cancers who undergo modified radical mastectomy. Method. From January 2016 to June 2017, 46 patients with primary breast cancer at stage I-IV (Tis-T3, N0-N3, and M0) who received modified radical mastectomy were enrolled in this study. The exclusion criteria included preoperative radiotherapy/chemotherapy or bilateral disease. Patients were divided into 2 groups: methylene blue group (22 patients, 47.8%) and methylene blue+indocyanine green (ICG) group (24 patients, 52.2%). ARM was performed before surgery. Results. The overall visualization rate of ARM nodes was 80.4% (37/46). The visualization rate was significantly increased in methylene blue+ICG group (91.67%, 22/24) than that in methylene blue group (63.64%, 14/22) (

P
=
0.032

). There was a statistical difference of visualization rate between clinical groups of N0-N1 and N3-N4 (

t
=
2.431

,

P
=
0.19
<
0.05

). Although there was no significant difference found in the total drainage volume and arm perimeter of patients between the two groups (

P
>
0.05

), the harden diameter of the injection site in methylene blue+ICG group was significantly longer than that in methylene blue group (

P
<
0.05

). Among the 44 patients with different molecular profiling of breast cancer, there was no significant difference of visualization rate of ARM nodes in luminal A group (100%,5/5), luminal B group (75.0%, 18/24,

P
=
0.21

), HER2 group (75.0%, 6/8,

P
=
0.22

), and basal-like group (85.7%, 6/7,

P
=
0.37

). Conclusions. ARM using methylene blue+ICG presented greater identification rate than that with methylene blue alone, especially in patients with more invasive breast cancer. Our finding offers support for the improvement of ARM in future breast cancer management.
Hax-1 Regulates Radiation-Induced Mitochondrial-Dependent Apoptosis of Uveal Melanoma Cells through PI3K/AKT/eNOS Pathway
Authors: Wang Sha , Tan Jia , Chen Lu , Wang Jinwei
Published: May 2022

Uveal melanoma is an aggressive skin cancer that remains insurmountable and is accompanied by inferior prognostic results. The proliferative and survival mechanisms of uveal melanoma cells need to be further investigated to improve the treatment of uveal melanoma. According to reports, HAX-1 is an antiapoptotic protein vital for multiple malignancies. Nevertheless, the role and causal link of HAX-1 in uveal melanoma are still elusive. The survival diversity of uveal melanoma sufferers with diverse haX-1 expressing levels was studied by TCGA database. Patients in the riskhigh group exhibited greater levels of HAX-1 in contrast to the risklow group, and individuals with higher HAX-1 levels displayed inferior survival times. The outcomes of CCK-8 and clonogenesis revealed that the proliferative rate of haX-1 knockout cells was slower. The result of scratch experiment shows that the ability of scratch recovery after HAX-1 is reduced. Transwell migration and tumor cell pelletization experiments showed that siHAX-1 significantly reduced cell migration and tumor cell pelletization. After haX-1 was knocked out, the loss of MMP was decreased, the transfer of CyT C was elevated, and the protein expression of Bax, Caspase 3, and Bcl2 was elevated, suggesting that mitochondria-induced apoptosis was increased. Sihax-1 treatment remarkably decreased the phosphonation of phosphatidylinositol 3-kinase (PI3K)/AKT/mammalian target of rapamycin (mTOR)/endothelial NO synthase (eNOS) in mum-2B and C918. Pretreatment with LY294002 significantly restored iHAX-1-induced decline in PI3K/AKT/mTOR/eNOS phosphorylation. Therefore, our results suggest that haX-1 induces radiation-dependent apoptosis of UM cells via the PI3K/AKT/eNOS signal path.
Rational Primer and Probe Construction in PCR-Based Assays for the Efficient Diagnosis of Drifting Variants of SARS-CoV-2
Authors: Rana Divya RSJB , Pokhrel Nischal , Dulal Santosh
Published: May 2022

The genome sequence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been evolving via genomic drifts resulting in “emerging/drifting variants” circulating worldwide. The construction of polymerase chain reaction (PCR) assays for the reliable, efficient, and specific diagnosis of the drifting variants of SARS-CoV-2 is specifically governed by the selection and construction of primers and probes. The efficiency of molecular diagnosis is impacted by the identity/homology of the genome sequence of SARS-CoV-2 with other coronaviruses, drifting variants or variants of concern (VOCs) circulating in communities, inherent capacity of mutation(s) of various target genes of SARS-CoV-2, and concentration of genes of interest in host cells. The precise amplicon selection and construction of primers and probes for PCR-based assays can efficiently discriminate specific SARS-CoV-2 drifting variants. The construction of single nucleotide polymorphism (SNP)-specific primers and probes for PCR assays is pivotal to specifically distinguish SARS-CoV-2 variants present in the communities and contributes to better diagnosis and prevention of the ongoing COVID-19 pandemic. In this study, we have utilized in silico-based bioinformatic tools where the alignment for genes, the positions and types of SNPs/mutations of VOCs, and the relative number of SNPs per nucleotide in different genomic regions were investigated. Optimal and specific genome region (amplicon) selection with comparatively lower mutability in the SARS-CoV-2 genome should be prioritized to design/construct PCR assays for reliable and consistent diagnosis in various regions of the world for a longer duration of time. Further, the rational selection of target genes that is at an optimal detectable concentration in biological samples can bolster PCR assays of high analytical sensitivity. Hence, the construction of primers and probes with the rational selection of targeting specific E gene, genomic regions with highly conserved sequences, multiple target genes with relatively lower mutability and detectable level of concentration, SNP-specific binding regions of spike (S gene) protein, and shorter amplicon size (100–150 bp) are vital for the PCR assays to achieve optimal efficiency in the point-of-care laboratory diagnosis of circulating drifting variants of SARS-CoV-2 with optimal accuracy.
LETR: An End-to-End Detector of Reconstruction Area in Blades Adaptive Machining with Transformer
Authors: Yin Zikai , Liang Yongshou , Ren Junxue , An Jungang , He Famei
Published: May 2022

In the leading/trailing edge’s adaptive machining of the near-net-shaped blade, a small portion of the theoretical part, called the reconstruction area, is retained for securing aerodynamic performance by manual work. The next work is to recognize the reconstruction area of the reconstructed leading/trailing edge’s image. To accelerate this process, an anchor-free neural network model based on Transformer was proposed, named Leading/trailing Edge Transformer (LETR). LETR extracts image features from an aspect of mixed frequency and channel domain. We also integrated LETR with the newest meta-Acon activation function. We tested our model on the self-made dataset LDEG2021 on a single GPU and got an mAP of 91.9%, which surpassed our baseline model, Deformable DETR, by 1.1%. Furthermore, we modified LETR’s convolution layer and named the new model after Ghost Leading/trailing Edge Transformer (GLETR) as a lightweight model for real-time detection. It is proved that GLETR has fewer weight parameters and converges faster than LETR with an acceptable decrease in mAP (0.1%) by test results. The proposed models provide the basis for subsequent parameter extraction work in the reconstruction area.
Implementing the Vieta–Lucas Collocation Optimization Method for MHD Casson and Williamson Model under the Effects of Heat Generation and Viscous Dissipation
Authors: Khader M.M. , Eid A. , Adel M.
Published: May 2022

Theoretical investigation of magnetohydrodynamics (MHD) Casson and Williamson fluid flow and heat and mass transfer in laminar flow through a stretching sheet in the presence of heat generation is carried out in this study. The convective wall temperature and convective wall mass boundary condition are taken into account in this study. A study is also provided, which looks into the impact of viscous dissipation. Except for a temperature‐dependent thermal conductivity, all properties of the proposed model are assumed to be constants in the study. The spectral collocation method based on the shifted Vieta–Lucas polynomials is used to give an approximate formula for the n‐order derivative and solve numerically the coupled momentum, energy, and mass equations. This method is used to convert the problem’s system of ordinary differential equations (ODEs) into a nonlinear system of algebraic equations. This system is built as a restricted optimization problem and optimized to obtain the series solution’s unknown coefficients. Some theorems are provided to investigate the method’s convergence. The statistics, which are given visually, were compared to the results of other researchers’ theoretical analysis.
A Prediction Model for Top-Coal Drawing Capability in Steep Seams Based on PCA–GRNN
Authors: Zhu Zhijie , Hong Yin , Liang Zhuang
Published: May 2022

To improve prediction accuracy of top-coal drawing capability in steep seams, principal component analysis (PCA) and the general regression neural network (GRNN) are combined (PCA–GRNN model) to predict top-coal drawing capability in steep seams. Nine commonly used influencing factors are selected to establish a predictive index system for top-coal drawing capability in steep seams. The PCA is used to eliminate correlation and reduce dimensions of various indices, thus obtaining three linearly uncorrelated principal components (PCs)

y

1

,

y

2

, and

y

3

, which form the input vectors of the GRNN. In this way, the factors that most affect the top-coal drawing capability in steep seams are found to be floor flatness, dip angle of the coal seam, and the hardness of the coal seam. The results show that the PCA–GRNN model outperforms the GRNN and random forest models in prediction results, which indicates that the PCA improves prediction accuracy of the GRNN model. It is feasible to predict top-coal drawing capability in steep seams by combining or even integrating different analytical models into one. The proposed PCA–GRNN model can be used to predict top-coal drawing capability in steep seams.
A Study on Resource Security under Legal Protection of e-Commerce Data Sovereignty Based on Blockchain Network
Authors: Cheng Yishuang , Pan Juan
Published: May 2022

With the growing demand for cross-border electronic data forensics, national sovereignty and international network security have ushered in great challenges, and how to achieve dynamic balance in various fields under cross-border electronic data forensics, advance the process of global cyberspace governance, reach international consensus, and achieve win-win cooperation is a question that China needs to solve. Based on the above status quo, a blockchain-based secure e-commerce system is researched and implemented. Using the distributed architecture of the blockchain system and the automatic execution feature of smart contracts, a secure transaction application system is designed to realize decentralization and solve the problem of untrustworthy intermediate parties. Data storage is based on the mechanism of combining blockchain and offchain databases to ensure data security, and the characteristic of blockchain can only be appended and read to prevent the system from being tampered. The database index and the storage structure of smart contract commodity information and transaction information are established to improve the query efficiency. The functional and performance tests of the system show that the transaction processing efficiency is high in the multinode environment, and the response time of order and commodity status query can reach 80 ms. The design and development process of the system is introduced in detail, which is an important reference value for the application of blockchain technology in e-commerce.
Managing Peak-Hour Congestion in Urban Rail Transit with the Sub-Train Price Adjustment Strategy
Authors: Liang Hui , Tian Zhiqiang , Liu Renhua , Sun Guofeng , He Fujing
Published: May 2022

In urban rail transit, adjusting fares to satisfy passenger flow requirements is a new method to relieve urban congestion. A bilevel model is proposed herein to solve the congestion problem for an urban rail line. The upper level of the model determines the discount factor to minimize the total number of passengers exceeding the full-load rate, and the lower level of the model determines the distribution of passengers on the line, in which the cost-minimizing behavior of each passenger is considered using the allocation method based on the probability of selection. To achieve a more realistic model, the range of acceptable train numbers for each passenger is considered. A simulated annealing algorithm is introduced to solve the bilevel model. Based on an example, we obtain the specific fare and passenger flow distribution of each train after fare adjustment. The results show that the objective function is reduced by 17.5%, the congested section is reduced by 9.1% when the full-load rate is 90% of the train loading capacity, and the passenger flow shifts to both ends of the peak period. Finally, relevant parameters are discussed.
Yaobishu Regulates Inflammatory, Metabolic, Autophagic, and Apoptosis Pathways to Attenuate Lumbar Disc Herniation
Authors: Li Xiaosheng , Li Shuoqi , Zang Zhengwu , He Yinhao
Published: May 2022

Objective. Here, we aimed to explore the main mechanism of Yaobishu (YBS) in lumbar disc herniation (LDH). Methods and Results. Eighteen compounds that might act on LDH were obtained through a combination of network pharmacology prediction and identification by high-performance liquid chromatography-mass spectrometry. The key compounds were palmitic acid and trans-4-hydroxy-3-methoxycinnamate (cinnamate). KEGG analysis demonstrated that palmitic acid target genes mainly regulate the PPAR signaling pathway, Ras signaling pathway, and fatty acid metabolism. Cinnamate target genes were primarily involved in chemical carcinogenesis-receptor activation, lipid and atherosclerosis, the HIF-1 signaling pathway, and nitrogen metabolism. The rat LDH model was constructed using autologous nucleus pulposus tissue implantation. Differential expression gene (DEGs) related to metabolism (CDKN1A and UHRF1), inflammation (S100A9 and SOCS3), autophagy (DCN and LEPR), and apoptosis (CTSW and BCL2A1) in dorsal root ganglion (DRG) tissues of the control and LDH groups was evaluated by RNA-Seq. TNF-α stimulated DRG neuronal cells were used to establish an in vitro LDH model. YBS, palmitic acid, and cinnamate reduced the expression of substance P, CGRP, S100A9, CTSW, and cleaved caspase-3, while enhancing the expression of CDKN1A, UHRF1, PCNA, Ki67, SOCS3, DCN, LEPR, and BCL2A1, as well as telomerase activity. Pearson’s correlation analysis confirmed that DCN was positively correlated with BCL2A1, indicating that autophagy might be negatively correlated with apoptosis in LDH. YBS, palmitic acid, and cinnamate reduced the Siegal neurological score and serum IL-1β and IL-18 levels, while increasing changes in the hind paw mechanical withdrawal threshold. The RNA-Seq results further showed that YBS downregulated S100A9 and CTSW expression, while upregulating SOCS3, CDKN1A, UHRF1, DCN, LEPR, and BCL2A1 expression. Conclusion. YBS and its compounds, palmitic acid, and cinnamate, attenuated LDH by regulating the inflammatory, metabolic, autophagic, and apoptotic pathways. Our results might improve the theoretical and experimental basis for clinical applications of LDH disease treatment.
Definition of Mucosal Breaks in the Era of Magnifying Endoscopy with Narrow-Band Imaging
Authors: Kikuchi Daisuke , Odagiri Hiroyuki , Hoshihara Yoshio , Ochiai Yorinari , Suzuki Yugo , Hayasaka Junnosuke , Tanaka Masami , Nomura Kosuke , Yamashita Satoshi , Matsui Akira , Iizuka Toshiro , Hoteya Shu
Published: May 2022

Background. Gastroesophageal reflux disease is diagnosed endoscopically based on the presence of mucosal breaks. However, mucosal breaks can be judged differently depending on the endoscopist, even in the same image. We investigated how narrow-band imaging (NBI) and magnified endoscopy affect the judgment of mucosal breaks. Methods. A total of 43 consecutive patients were enrolled who had suspected mucosal breaks on white-light images (WLI) and underwent nonmagnified NBI (N-NBI) and magnified NBI (M-NBI) by a single endoscopist. From WLI, N-NBI, and M-NBI, 129 image files were created. Eight endoscopists reviewed the image files and judged the presence of mucosal breaks. Results. The 8 endoscopists determined mucosal breaks were present in 79.4 ± 9.5% (67.4%–93.0%) on WLI, and 76.7 ± 12.7% (53.5%–90.7%) on N-NBI. However, the percentage of mucosal breaks on M-NBI was significantly lower at 48.8 ± 17.0% (18.6%–65.1%) (

p
<
0.05

). Intraclass correlation between observers was 0.864 (95% CI 0.793–0.918) for WLI and 0.863 (95% CI 0.791–0.917) for N-NBI but was lower for M-NBI at 0.758 (95% CI 0.631–0.854). Conclusion. Rates of detection and agreement for mucosal breaks on WLI and N-NBI were high among endoscopists. However, these rates were lower on M-NBI.
[Retracted] Characterization of Tumor Mutation Burden‐Based Gene Signature and Molecular Subtypes to Assist Precision Treatment in Gastric Cancer
Authors: Wei Cheng , Li Minzhe , Lin Shaofeng , Xiao Jun
Published: May 2022

Objective. Tumor mutation burden (TMB) represents a useful biomarker for predicting survival outcomes and immunotherapy response. Here, we aimed to conduct TMB‐based gene signature and molecular subtypes in gastric cancer. Methods. Based on differentially expressed genes (DEGs) between high‐ and low‐TMB groups in TCGA, a LASSO model was developed for predicting overall survival (OS) and disease‐free survival (DFS). The predictive performance was externally verified in the GSE84437 dataset. Molecular subtypes were conducted via consensus clustering approach based on TMB‐related DEGs. The immune microenvironment was estimated by ESTIMATE and ssGSEA algorithms. Results. High‐TMB patients had prolonged survival duration. TMB‐related DEGs were distinctly enriched in cancer‐ (MAPK, P53, PI3K‐Akt, and Wnt pathways) and immune‐related pathways (T cell selection and differentiation). The TMB‐based gene model was developed (including MATN3, UPK1B, GPX3, and RGS2), and high‐risk score was predictive of poor prognosis and recurrence. ROC and multivariate analyses revealed the well predictive performance, which was confirmed in the external cohort. Furthermore, we established the nomogram containing the risk score, age, and stage for personalized prediction of OS and DFS. High‐risk score was characterized by high stromal score, increased immune checkpoints, immune cell infiltrations, and enhanced sensitivity to gefitinib, vinorelbine, and gemcitabine. Three TMB‐based molecular subtypes were conducted, characterized by distinct prognosis, immune microenvironment, and drug sensitivity. Conclusion. Collectively, we established a prognostic signature and three distinct molecular subtypes based on TMB features for gastric cancer, which might be beneficial for prognostic prediction and clinical decision‐making.
Application of Knowledge Map Based on BiLSTM-CRF Algorithm Model in Ideological and Political Education Question Answering System
Authors: Zhao Wei , Liu Juan
Published: May 2022

Ideological and political education plays an important role in university education and is an important way to realize the function of educating people. It is of great significance to establish a perfect automatic question answering system for ideological and political education. Traditional automatic question answering methods usually rely on predicates and other prior information to achieve knowledge base question answering, which requires a lot of manpower and poor generalization ability. In order to solve this problem, this paper designs a question answering system for ideological and political education based on BiLSTM-CRF algorithm model (BiLSTM: Bidirectional Long Short-Term Memory and CRF: Conditional Random Fields). For the knowledge base question answering method with weak-dependent information, this paper combines BERT (Bidirectional Encoder Representation from Transformers) and BiLSTM-CRF network to extract the named entity in the questions and locate the triplet information related to the entity in the knowledge base. Through the answer matching network, the similarity score is marked for the answers in the triplet set, and the threshold selection strategy is used to select the answers that meet the requirements. And according to the similarity score from high to paper, it is presented to the user. The experimental results show that the method weakens the dependence on prior information, reduces manual intervention and ensures the quality of question answering, and completes the validity verification of the question answering system of ideological and political education.
Modelling the Role of Human Behaviour in Ebola Virus Disease (EVD) Transmission Dynamics
Authors: Djiomba Njankou Sylvie Diane , Nyabadza Farai
Published: May 2022

The role of human behaviour in the dynamics of infectious diseases cannot be underestimated. A clear understanding of how human behaviour influences the spread of infectious diseases is critical in establishing and designing control measures. To study the role that human behaviour plays in Ebola disease dynamics, in this paper, we design an Ebola virus disease model with disease transmission dynamics based on a new exponential nonlinear incidence function. This new incidence function that captures the reduction in disease transmission due to human behaviour innovatively considers the efficacy and the speed of behaviour change. The model’s steady states are determined and suitable Lyapunov functions are built. The proofs of the global stability of equilibrium points are presented. To demonstrate the utility of the model, we fit the model to Ebola virus disease data from Liberia and Sierra Leone. The results which are comparable to existing findings from the outbreak of

2014
−
2016

show a better fit when the efficacy and the speed of behaviour change are higher. A rapid and efficacious behaviour change as a control measure to rapidly control an Ebola virus disease epidemic is advocated. Consequently, this model has implications for the management and control of future Ebola virus disease outbreaks.