bluuebunny/crossref_metadata_2025 huggingface dataset:
Biological and clinical correlates of the patient health questionnaire-9: exploratory cross-sectional analyses of the baseline health study
Authors: Califf Robert M , Wong Celeste , Doraiswamy P Murali , Hong David S , Miller David P , Mega Jessica L
Published: January 2022

Objectives

We assessed the relationship between the Patient Health Questionnaire-9 (PHQ-9) at intake and other measurements intended to assess biological factors, markers of disease and health status.

Design, setting and participants

We performed a cross-sectional analysis of 2365 participants from the Baseline Health Study, a prospective cohort of adults selected to represent major demographic groups in the USA. Participants underwent deep phenotyping on demographic, clinical, laboratory, functional and imaging findings.

Importance

Despite extensive research on the clinical implications of the PHQ-9, data are limited on the relationship between PHQ-9 scores and other measures of health and disease; we sought to better understand this relationship.

Interventions

None.

Main outcomes and measures

Cross-sectional measures of medical illnesses, gait, balance strength, activities of daily living, imaging and laboratory tests.

Results

Compared with lower PHQ-9 scores, higher scores were associated with female sex (46.9%–66.7%), younger participants (53.6–42.4 years) and compromised physical status (higher resting heart rates (65 vs 75 bpm), larger body mass index (26.5–30 kg/m2), greater waist circumference (91–96.5 cm)) and chronic conditions, including gastro-oesophageal reflux disease (13.2%–24.7%) and asthma (9.5%–20.4%) (p<0.0001). Increasing PHQ-9 score was associated with a higher frequency of comorbidities (migraines (6%–20.4%)) and active symptoms (leg cramps (6.4%–24.7%), mood change (1.2%–47.3%), lack of energy (1.2%–57%)) (p<0.0001). After adjustment for relevant demographic, socioeconomic, behavioural and medical characteristics, we found that memory change, tension, shortness of breath and indicators of musculoskeletal symptoms (backache and neck pain) are related to higher PHQ-9 scores (p<0.0001).

Conclusions

Our study highlights how: (1) even subthreshold depressive symptoms (measured by PHQ-9) may be indicative of several individual- and population-level concerns that demand more attention; and (2) depression should be considered a comorbidity in common disease.

Trial registration number

NCT03154346.
Effect of antenatal dietary myo-inositol supplementation on the incidence of gestational diabetes mellitus and fetal outcome: protocol for a double-blind randomised controlled trial
Authors: Ibrahim Ibrahim , Abdullahi Hala , Fagier Yassin , Ortashi Osman , Terranegra Annalisa , Okunoye Gbemisola
Published: January 2022

Introduction

Gestational diabetes mellitus (GDM) affects 23.6% of Qatari women and is associated with maternal and perinatal morbidity and long-term risk of developing type 2 diabetes. A number of challenges exist with current interventions, including non-compliance with dietary advice, the reluctance of mothers to ingest metformin tablets or use insulin injections. These challenges highlight the importance of pursuing evidence-based prevention strategies. Myo-inositol is readily available as an US Food and Drug Administration-approved food supplement with emerging but limited evidence suggesting it may be beneficial in reducing the incidence of GDM. Further studies, such as this one, from different ethnic contexts and with differing risk factors, are urgently needed to assess myo-inositol effects on maternal and neonatal outcomes.

Methods and analysis

This study is a prospective, randomised, double-blinded, placebo controlled clinical trial to either myo-inositol supplementation or placebo.

We plan to enrol 640 pregnant women attending antenatal care at Sidra Medicine, Doha, Qatar, 320 in each arm. All participants will complete at least 12 weeks of supplementation prior to undertaking the Oral Glucose Tolerance Test at 24–28 weeks. The daily use of the trial supplementation will continue until the end of pregnancy. All outcome measures will be collected from the electronic medical records.

Ethics and dissemination

Ethical approval for the study was obtained on 12 April 2021 from Sidra Medicine (IRB number 1538656). Results of the primary trial outcome and secondary endpoints will be submitted for publication in a peer-reviewed journal.

Trial registration number

Prospectively registered on 26 May 2021. Registration number ISRCTN16448440 (ISRCTN registry).
Exploring hepatitis C virus testing and treatment engagement over time in Melbourne, Australia: a study protocol for a longitudinal cohort study (EC-Experience Cohort study)
Authors: O’Keefe Daniel , Gunn J , Ryan Kathleen , Djordjevic Filip , Kerr Phoebe , Gold Judy , Elsum Imogen , Layton Chloe , Chan Kico , Dietze Paul , Higgs Peter , Doyle Joseph , Stoové Mark A , Hellard Margaret , Pedrana A E
Published: January 2022

Introduction

The advent of direct acting antiviral therapy for hepatitis C virus (HCV) means the elimination of HCV is possible but requires sustained effort to achieve. Between 2016 and 2019, 44% of those living with HCV were treated in Australia. However, treatment uptake has declined significantly. In Australia, people who inject drugs (PWID) are the population most at risk of HCV acquisition. Eliminating HCV in Australia will require nuanced understanding of the barriers to HCV treatment experienced by PWID and tailored interventions to address these barriers. The EC-Experience Cohort study aims to explore the barriers and enablers reported by PWID to engagement in HCV care.

Methods and analysis

The EC-Experience Cohort study is a prospective cohort of PWID, established in Melbourne, Australia in 2018. Participants are assigned into three study groups: (1) those not currently engaged in HCV testing; (2) those diagnosed with HCV but not currently engaged in treatment and (3) those completed treatment. Participants complete a total of four interviews every 6 months across an 18-month study period. Predictors of experience of key outcome events along the HCV care cascade will be explored over time.

Ethics and dissemination

Ethical approval for the EC-Experience Cohort study was obtained by the Alfred Hospital Ethics Committee in Melbourne, Australia (Project Number: HREC/16/Alfred/164). All eligible participants are assessed for capacity to consent and partake in a thorough informed consent process. Results from the EC-Experience Cohort study will be disseminated via national and international scientific and public health conferences and peer-reviewed journal publications. Data from the EC-Experience Cohort study will improve the current understanding of the barriers to HCV care for PWID and guide the tailoring of service provision for specific subgroups. Understanding the barriers and how to increase engagement in care of PWID is critical to achieve HCV elimination goals.
Summer stream habitat preferences of Nunavik anadromous Arctic char (Salvelinus alpinus) fry and parr
Authors: Dubos Véronique , St-Hilaire André , Bergeron Normand E.
Published: January 2022

Arctic char (Salvelinus alpinus) is a fish species known to occupy diverse habitats within the Arctic region. However, summer habitat use during the juvenile stage of the anadromous form is largely unknown. The present study aims to characterize fry and parr summer habitat preferences. Surveys were conducted by electrofishing, associated with physical habitat characterization on several rivers of the Ungava Bay, Nunavik, Canada. At the microhabitat and station scales (group of microhabitats), fry showed significant habitat preferences for shallow water and slow velocity. At the mesohabitat scale, fry showed a significant habitat selectivity for riffles. This habitat selectivity implies that habitat models can be built to evaluate the potential of habitat suitability for Arctic char fry. However, no significant habitat selectivity was found for parr. Parr size was nonetheless positively correlated with velocity, which was found to be a limitative factor for juvenile habitat use. This first attempt at modeling juvenile anadromous Arctic char habitat in rivers emphasizes the importance of selecting an appropriate spatial scale and reiterates the fact that parr showed relatively high plasticity in stream habitat selection.
DETRENDED FLUCTUATION ANALYSIS OF THREE-DIMENSIONAL DATA: APPLICATION TO SOIL X-RAY CT SCANS
Authors: AGUIAR DOMINGOS , SANTOS CARLOS RENATO DOS , MENEZES RÔMULO SIMÕES CEZAR , ANTONINO ANTONIO CELSO DANTAS , STOSIC BORKO
Published: January 2022

In this work, we compare three distinct schemes for detrended fluctuation analysis (DFA) of three-dimensional (3D) [Formula: see text] data sets: (i) an [Formula: see text] set of one-dimensional (1D) DFA runs for each vertical line of length [Formula: see text], (ii) a set of [Formula: see text] two-dimensional (2D) DFA runs for each of the [Formula: see text] planes along the vertical direction, and (iii) a single 3D DFA run. The objective of this work is two-fold: (i) to compare the performance of 1D, 2D, and 3D DFA methods in terms of compatibility as well as the richness of obtained results, and (ii) to demonstrate how these three complementary approaches shed new light on the complexity of the structure of the two real soil samples, through the analysis of grayscale high-resolution X-ray computed tomography scan images.
LEADER–FOLLOWER COHERENCE OF THE WEIGHTED RECURSIVE TREE NETWORKS
Authors: GUO YUANYUAN , DAI MEIFENG , LIU YAN
Published: January 2022

Recently, the consensus problem has attracted extensive attention of researchers from different scientific communities. In this paper, we study the leader–follower network coherence (i.e. the mean steady-state variance of the deviation from the static value of the leader nodes) in the weighted recursive tree networks with assigning the leaders orderly in the initial state. For the weighted recursive tree networks model, we study the characteristic polynomial of the Laplacian submatrix and obtain the relationship for the eigenvalues in two successive generations. The analytical formula of the leader–follower network coherence related by the sum of the reciprocal of all eigenvalues of this submatrix is obtained. The result shows that more number of leaders and the greater weight factor lead to better consensus.
SOLITARY WAVES OF THE VARIANT BOUSSINESQ–BURGERS EQUATION IN A FRACTAL-DIMENSIONAL SPACE
Authors: WU PIN-XIA , YANG QIAN , HE JI-HUAN
Published: January 2022

In this work, we mainly focus on the fractal variant Boussinesq–Burgers equation which can well describe the motion of shallow water traveling along an unsmooth boundary. First, we construct its fractal variational principle and prove its strong minimum condition by the fractal Weierstrass theorem. Then two types of soliton solutions are acquired according to the constructed fractal variational principle. We find that the order of the fractal derivative hardly affects the whole shape of the solitary waves, but it remarkably affects its propagation process.
Chaperonin Mechanisms: Multiple and (Mis)Understood?
Authors: Horovitz Amnon , Reingewertz Tali Haviv , Cuéllar Jorge , Valpuesta José María
Published: January 2022

The chaperonins are ubiquitous and essential nanomachines that assist in protein folding in an ATP-driven manner. They consist of two back-to-back stacked oligomeric rings with cavities in which protein (un)folding can take place in a shielding environment. This review focuses on GroEL from Escherichia coli and the eukaryotic chaperonin-containing t-complex polypeptide 1, which differ considerably in their reaction mechanisms despite sharing a similar overall architecture. Although chaperonins feature in many current biochemistry textbooks after being studied intensively for more than three decades, key aspects of their reaction mechanisms remain under debate and are discussed in this review. In particular, it is unclear whether a universal reaction mechanism operates for all substrates and whether it is passive, i.e., aggregation is prevented but the folding pathway is unaltered, or active. It is also unclear how chaperonin clients are distinguished from nonclients and what are the precise roles of the cofactors with which chaperonins interact.
Optimization, Modelling and Analysis of Air-Cooled Battery Thermal Management System for Electric Vehicles
Authors: Muddasar Muhammad
Published: January 2022

Electric Vehicles (EVs) are the need of the hour due to growing climate change problems linked with the transportation sector. Battery Thermal Management System (BTMS), which is accountable for certifying safety and performance of lithium-ion batteries (LiB), is the most vital part of an EV. LiB has auspicious gravimetric energy density but the heat generation due to chemical reactions inside a LiB during charging and discharging causes temperature rise which has a direct effect on LiB performance and safety. This study specifically focuses on aircooled BTMS, defines different types of air-cooled BTMS (active and Passive), discusses limitations associated with air-cooled BTMS, and investigates different optimization techniques and parameters to improve performance of air-cooled BTMS. Maintaining temperature within optimum range and uniform temperature distribution between cells of a battery pack are the major design parameters for improving the performance and efficiency of air-cooled BTMS. Various optimization techniques including cell arrangement with a battery pack, air-flow channel optimization, and air inlet/outlet position variations are discussed and each technique is thoroughly reviewed. Finally, it’s noted that passive air-cooled BTMS is not that effective for long-distance vehicles so most researchers shifted their focus toward active air-cooled BTMS. Active air-cooled BTMS requires a lot of power for effective performance. Lastly, the most recent field of air-cooled BTMS technology which is Air-Hybrid BTMS is discussed and declared a very promising solution for overcoming major limitations associated with air-cooled BTMS.
Some Algebraic Properties of the Wilson Loop
Authors: Li Han , Nadeem M. , Ali M. A. , Mutee ur Rehman H.
Published: January 2022

In this article, some algebraic properties of the Wilson loop have been investigated in a broad manner. These properties include identities, autotopisms, and implications. We use some equivalent conditions to study the behavior of holomorphism of this loop. Under the shadow of this holomorphism, we are able to observe coincident loops.
Blended Oral English Teaching Based on Core Competence Training Model
Authors: Gu Jiahui
Published: January 2022

The traditional mixed oral English teaching model has many obvious shortcomings, such as the inability to correct the students’ oral pronunciation errors and feed them back in time, which leads to the slow improvement of students’ English learning level. For this reason, this paper proposes a guided teaching model based on core literacy. According to the structure of the oral English mixed teaching model, determine the application plan of the oral English mixed teaching model, design the development environment, obtain the corpus, design the oral training model, extract the oral features, identify the wrong pronunciation and correct it in time, clarify the evaluation purpose, obtain preliminary evaluation indicators, reduce evaluation indicators and determine indicator weights, obtain indicator feature information, generate fuzzy rules, obtain fuzzy matrices, achieve quantitative evaluation, and synthesize all evaluation scores to construct a result vector matrix to realize the study of mixed spoken language teaching mode. Research shows that the mixed teaching method is effective and feasible and can effectively improve the accuracy of the evaluation results of the mixed oral English teaching model.
Structure Optimization of Mixed‐Speed Train Traffic for Cyclic Timetable: Model and Algorithm Development
Authors: Zhang Jiamin , Zhang Jiarui
Published: January 2022

Trains can be optimally spread over the period of the cyclic timetable. By integrating sequencing issue with headway time together, this paper studies the structure optimization of mixed‐speed train traffic for a cyclic timetable. Firstly, by taking it as a job‐shop problem with sequence‐dependent setup times on one machine, in the type of infinite capacity resource with headway (ICR + H), the problem is transformed to alternative graph (AG) and then recast to the mixed‐speed train traffic planning (MSTTP) model. For the multiobjective in MSTTP, three indicators are optimized, i.e., heterogeneity, cycle time, and buffer time, which correspond to diversity of train service toward passenger, capacity consumption of rail network, and stability of train operation, respectively. Secondly, the random‐key genetic algorithm (RKGA) is proposed to tackle the sequence and headway simultaneously. Finally, RKGA is coded with visual studio C# and the proposed method is validated with a case study. The rail system considered is a line section encompassing a territory of 180 km with 15 mixed‐speed trains in each cycle of the timetable. Results indicate the comprehensively balanced train plan for all stakeholders from random variations of train sequence and headway time. Both the quantitative proportion of heterogeneity/homogeneity (e.g., 2.5) about the optimized distribution of the mixed train traffic and the link between train headway time and the sequence for each traffic scenario are found. All the findings can be used to arrange the mixed‐speed train traffic more scientifically.
A Novel Approach to Improving E‐Government Performance from Budget Challenges in Complex Financial Systems
Authors: Lulaj Enkeleda , Zarin Ismat , Rahman Shawkat
Published: January 2022

Today, the risk management of budget challenges throughout the budget process is greater than ever. The process of change has been driven by new information and communication technologies, resulting in e‐government. The purpose of this scientific paper is to see whether budgetary challenges have an effect on the performance of e‐government in complex financial systems based on factors F1, F2, F3, F4, and F5: lack of information, lack of cooperation, lack of resources and reduction of focus, lack of budget experts and financial stability, and shortcomings and inconsistencies during the budget process. Therefore, this study aims to advance the understanding of how to manage risks from budgetary challenges by focusing on a novel approach to improve e‐government performance in complex financial systems. Empirical research was based on three key issues: an approach to e‐government, analyzing which variables need more attention to risk, and learning how to meet budgetary challenges to improve performance during governance. For this study, the data were conducted by Kosovo’s public institutions, more specifically at the central level (Ministry of Finance) and at the local level (38 municipalities of Kosovo). A total of 38 questionnaires were analyzed and divided into three sessions, which were analyzed through three analyses, such as factor analysis, data reliability analysis, and multiple regression analysis, using SPSS version 23.0 for Windows. The research was conducted over the years 2017, 2018, 2019, and 2020, while the analysis involved several processes, where some of the factors were removed in order to make the model acceptable. In this case, 21 variables were tested and divided into 5 factors. The results showed that special attention should be paid to these factors to reduce budgetary challenges and increase the performance of e‐government in complex financial systems, such as (a) lack of resources (staff, funds, infrastructure, tools, etc.), (b) increasing the focus on risk management even after the transfer of funds from the ministry to the municipality, (c) the selection of programs based on priorities and not on the basis of wishes and policies, (d) having political stability, rule of law, and more control, and (e) having regulations and guidelines from the practices of developed countries as well as taking into account the opinions of budget experts. The implications of this paper have to do with only a considerable number of variables, which were taken in the study as well as only in the municipalities of Kosovo. In this case, for other analyses by other researchers, other variables can be analyzed in other countries by making comparisons.
Artificial Intelligence Algorithm-Based CTA Imaging for Diagnosing Ischemic Type Biliary Lesions after Orthotopic Liver Transplantation
Authors: Yu Zhenxing , Ou Guixue , Wang Ruihua , Zhang Qinghua
Published: January 2022

The study focused on the clinical application value of artificial intelligence-based computed tomography angiography (CTA) in the diagnosis of orthotopic liver transplantation (OLT) after ischemic type biliary lesions (ITBL). A total of 66 patients receiving OLT in hospital were selected. Convolutional neural network (CNN) algorithm was used to denoise and detect the edges of CTA images of patients. At the same time, the quality of the processed image was subjectively evaluated and quantified by Hmax, Ur, Cr, and other indicators. Then, the digital subtraction angiography (DSA) diagnosis and CTA diagnosis based on CNN were compared for the sensitivity, specificity, positive predictive value, negative predictive value, and patient classification results. It was found that CTA can clearly reflect the information of hepatic aorta lesions and thrombosis in patients with ischemic single-duct injury after liver transplantation. After neural network algorithm processing, the image quality is obviously improved, the lesions are more prominent, and the details of lesion parts are also well displayed. ITBL occurred in 40 (71%) of 56 patients with abnormal CTA at early stage. ITBL occurred in only 8 (12.3%) of 65 patients with normal CTA at early stage. Early CTA manifestations had high sensitivity (72.22%), specificity (87.44%), positive predictive value (60.94%), and negative predictive value (92.06%) for the diagnosis of ITBL. It was concluded that artificial intelligence-based CTA had high clinical application value in the diagnosis of ITBL after OLT.
[Retracted] Design of Sports Image Contour Feature Acquisition System Based on the Background Subtraction Method
Authors: Xiong Zhichao
Published: January 2022

Moving target detection (MTD) is one of the emphases and difficulties in the field of computer vision and image processing. It is the basis of moving target tracking and behavior recognition. We propose two methods are improved and fused, respectively, and the fusion algorithm is applied to the complex scene for MTD, so as to improve the accuracy of MTD in complex and hybrid scenes. Using the main idea of the three‐frame difference image method, the background difference method and the interframe difference method are combined to make their advantages complementary to overcome each other’s weaknesses. The experimental results show that the method can be well adapted to the situation of periodic motion interference in the background, and it can adapt to the situation of sudden background changes.
A New Multiface Target Detection Algorithm for Students in Class Based on Bayesian Optimized YOLOv3 Model
Authors: Shi Dongmei , Tang Hongyu
Published: January 2022

Deep learning theory is widely used in face recognition. Combined with the needs of classroom attendance and students’ learning status monitoring, this article analyzes the YOLO (You Only Look Once) face recognition algorithms based on regression method. Aiming at the problem of small target missing detection in the YOLOv3 network structure, an improved YOLOv3 algorithm based on Bayesian optimization is proposed. The algorithm uses deep separable convolution instead of conventional convolution to improve the Darknet-53 basic network, and it reduces the amount of calculation and parameters of the network. A multiscale feature pyramid is built, and an attention guidance module is designed to strengthen multiscale fusion, detecting different sizes of targets. The loss function is improved to solve the imbalance of positive and negative sample distribution and the imbalance between simple samples and difficult samples. The Bayesian function is adopted to optimize the classifier and improve the classification efficiency and accuracy, ensuring the accuracy of small target detection. Five groups of comparative experiments are carried out on public COCO and VOC2012 datasets and self-built datasets. The experimental results show that the proposed improved YOLOv3 model can effectively improve the detection accuracy of multiple faces and small targets. Compared with the traditional YOLOv3 model, the mean mAP of the target is improved by more than 1.2%.
hsa-MicroRNA-28-5p Inhibits Diffuse Large B-Cell Lymphoma Cell Proliferation by Downregulating 14-3-3ζ Expression
Authors: Yan Shufang , Chen Yang , Yang Meihong , Zhang Qian , Ma Jiajia , Liu Bo , Yang Liuqing , Li Xinxia
Published: January 2022

MicroRNAs (miRNAs) participate in the comprehensive biological process of several cancer types. In our former study, we found that hsa-microRNA- (miR-)28-5p was downregulated, but tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activating protein zeta (14-3-3ζ or YWHAZ) was upregulated in diffuse large B-cell lymphoma (DLBCL) tissues. We predicted that YWHAZ was a target gene for hsa-miR- 28-5p using bioinformatics analysis. Our goal was to reveal the role of hsa-miR-28-5p in DLBCL. YWHAZ was tested by immunohistochemistry (IHC) in formalin-fixed paraffin-embedded (FFPE) tissues of 137 DLBCL tissues, and the expression of hsa-miR-28-5p and YWHAZ was examined by quantitative real-time polymerase chain reaction (qRT-PCR) in 15 fresh and frozen DLBCL tissues. To study the functional roles of the downregulated hsa-miR-28-5p in DLBCL, a Cell Counting Kit-8 assay was conducted to estimate cell proliferation. Transient transfection of miRNA mimics was performed to overexpress hsa-miR-28-5p, and flow cytometry was performed to examine cell apoptosis and cell cycle progression. A dual-luciferase reporter assay was employed to explore the relationship between hsa-miR-28-5p and YWHAZ. Western blotting and qRT-PCR were used to investigate the function of hsa-miR-28-5p in YWHAZ expression. hsa-miR-28-5p was found to be significantly downregulated in DLBCL tissues and cell lines. Functional studies showed that hsa-miR-28-5p overexpression inhibited cell viability and proliferation, and YWHAZ was predicted to be a target of hsa-miR-28-5p. Dual-luciferase reporter assay, Western blotting, and qRT-PCR verified that hsa-miR-28-5p negatively regulated YWHAZ expression by directly targeting its 3′ untranslated regions in DLBCL cells. hsa-miR-28-5p may suppress the growth of DLBCL cells by inhibiting YWHAZ expression. These findings could provide novel targets for DLBCL diagnosis and therapy.
Application of the Data-Driven Educational Decision-Making System to Curriculum Optimization of Higher Education
Authors: Du Yufan
Published: January 2022

Advancement in information technology has given a tremendous change in the education system. The traditional classroom education system is slowly getting transferred to the modernized system. In this conversion, the students choose to select the courses to learn in their higher education. The selection will aid the student in learning advanced technologies through theoretical and practical methods. In this research work, a data-driven educational decision-making system with the support of a course curriculum is analyzed with student’s response after the course. The educational decision-making is implemented with the help of the mobile learning technology designed and maintained by the colleges and universities. For performing the analysis, the student response dataset is given as input to the fuzzy logic system to perform the analysis. The research shows that mobile learning technology with the fuzzy logic system has provided better decision-making analysis to curriculum optimization for the student and teachers.
The Predictive Efficacy of Serum Exosomal microRNA-122 and microRNA-148a for Hepatocellular Carcinoma Based on Smart Healthcare
Authors: Deng Peng , Li Mi , Wu Yuni
Published: January 2022

Objective. Hepatocellular carcinoma (HCC) remains a devastating tumor globally. Serum exosomes are reliable biomarkers for tumors, including HCC. Hence, this study explored the efficacy and mechanism of serum exosomes in HCC. Methods. microRNA (miR)-122 and miR-148a expressions in serum exosomes from HCC patients and healthy subjects and their predictive efficacy for HCC were detected. Correlation between serum exosomal miR-122/148a expressions with survival rate, clinical stage, lymph node metastasis, and tumor differentiation level and levels of HCC-related serum markers (CA199, FucAFP, ALD-A, and AFu) were detected. PAX2 staining intensity and expression in HCC were measured. PAX2 predictive efficacy for HCC and its correlation with clinical stage, lymph node metastasis, tumor differentiation level, and HCC-related serum marker levels were analyzed. The targeted binding relationship between miR-122 and miR-148a and PAX2 was predicted and verified. Results. Serum exosomal miR-122 and miR-148a expressions were downregulated in HCC, showing potent predictive efficacy for HCC, which was negatively related to clinical stage and lymph node metastasis and positively related to tumor differentiation level, patient survival rate, and HCC-related serum marker levels. PAX2 showed increased staining intensity and expression in HCC, together with high predictive efficacy for HCC. PAX2 expression showed a positive correlation with clinical stage and lymph node metastasis and a negative correlation with tumor differentiation level and HCC-related serum marker levels. miR-122 and miR-148a conjointly targeted PAX2 in HCC. Conclusion. We demonstrated that serum exosomal miR-122 and miR-148a played a predictive role and were linked to prognosis in HCC via interactions with PAX2.
Recognition of Gurmukhi Handwritten City Names Using Deep Learning and Cloud Computing
Authors: Sharma Sandhya , Gupta Sheifali , Gupta Deepali , Juneja Sapna , Singal Gaurav , Dhiman Gaurav , Kautish Sandeep
Published: January 2022

The challenges involved in the traditional cloud computing paradigms have prompted the development of architectures for the next generation cloud computing. The new cloud computing architectures can generate and handle huge amount of data, which was not possible to handle with the help of traditional architectures. Deep learning algorithms have the ability to process this huge amount of data and, thus, can now solve the problem of the next generation computing algorithms. Therefore, these days, deep learning has become the state-of-the-art approach for solving various tasks and most importantly in the field of recognition. In this work, recognition of city names is proposed. Recognition of handwritten city names is one of the potential research application areas in the field of postal automation For recognition using a segmentation-free approach (Holistic approach). This proposed work demystifies the role of convolutional neural network (CNN), which is one of the methods of deep learning technique. Proposed CNN model is trained, validated, and analyzed using Adam and stochastic gradient descent (SGD) optimizer with a batch size of 2, 4, and 8 and learning rate (LR) of 0.001, 0.01, and 0.1. The model is trained and validated on 10 different classes of the handwritten city names written in Gurmukhi script, where each class has 400 samples. Our analysis shows that the CNN model, using an Adam optimizer, batch size of 4, and a LR of 0.001, has achieved the best average validation accuracy of 99.13.
Network Design Algorithm Implementation for Resilient Transportation System under Continuous Risk Perturbation with Big Data Analysis
Authors: Wang Hongxiao , Li Qiang , Tsai Sang-Bing
Published: January 2022

With the rapid economic development and urbanization process accelerating, motor vehicle ownership in large cities is increasing year by year; urban traffic congestion, parking difficulties, and other problems are becoming increasingly serious; in ordinary daily life, continuous risk of disturbance, having a flexible transportation system network is more able to alleviate daily congestion in the city, and the main thing about flexible transportation network is its algorithm. It is worth noting that congestion in many cities is generally reflected in the main roads, while many secondary roads and branch roads are underutilized, and the limited road resources in cities are not fully utilized. As an economic and effective road traffic management measure, one-way traffic can balance the spatial and temporal distribution of traffic pressure within the road network, make full use of the existing urban road network capacity, and solve the traffic congestion problem. Therefore, it is of great theoretical and practical significance to develop a reasonable and scientific one-way traffic scheme according to the characteristics of traffic operation in different regions. Based on the fixed demand model, the influence of traffic demand changes is further considered, the lower-level model is designed as an elastic demand traffic distribution model, the excess demand method is used to transform the elastic demand problem into an equivalent fixed demand problem based on the extended network, and the artificial bee colony algorithm based on risk perturbation is designed to solve the two-level planning model. The case study gives a one-way traffic organization optimization scheme that integrates three factors, namely, the average load degree overload limit of arterial roads, the detour coefficient, and the number of on-street parking spaces on feeder roads, and performs sensitivity analysis on the demand scaling factor.
In Situ LID and Regeneration of PERC Solar Cells from Different Positions of a B-Doped Cz-Si Ingot
Authors: Yuan Shuai , Ding Siqi , Ai Bin , Chen Daming , Jin Jingsheng , Ye Jiaxing , Qiu Depeng , Sun Xiaopu , Liang Xueqin
Published: January 2022

In order to investigate the light-induced-degradation (LID) and regeneration of industrial PERC solar cells made from different positions of silicon wafers in a silicon ingot, five groups of silicon wafers were cut from a commercial solar-grade boron-doped Czochralski silicon (Cz-Si) ingot from top to bottom with a certain distance and made into PERC solar cells by using the standard industrial process after measuring lifetimes of minority carriers and concentrations of boron, oxygen, carbon, and transition metal impurities. Then, the changes of their

I

-

V

characteristic parameters (efficiency

η

, open-circuit voltage

V

oc

, short-circuit current

I

sc

, and fill factor

FF

) with time were in situ measured by using a solar cell

I

-

V

tester during the 1st LID (45°C, 1 sun, 12 h), regeneration (100°C, 1 sun, 24 h), and 2nd LID (45°C, 1 sun, 12 h). The results show that the LID and regeneration of the PERC solar cells are caused by the transition of B-O defects playing a dominant role together with the dissociation of Fe-B pairs playing a secondary role. The decay of

η

during the 1st LID is caused by the degradation of

V

oc

,

I

sc

, and

FF

, while the increase of

η

during the regeneration is mainly contributed by

V

oc

and

FF

, and the decay of

η

during the 2nd LID is mainly induced by the degradation of

I

sc

. After regeneration, the decay rate of

η

reduces from 4.43%–5.56% (relative) during the 1st LID to 0.33%–1.75% (relative) during the 2nd LID.
Potential Effects of Metformin on the Vitality, Invasion, and Migration of Human Vascular Smooth Muscle Cells via Downregulating lncRNA-ATB
Authors: Jia Wei , Zhou Yue , Sun Lina , Liu Jianlong , Cheng Zhiyuan , Zhao Shuofang
Published: January 2022

Objective. To elucidate the role of metformin in influencing VSMCs via the involvement of lncRNA-ATB. Methods. qRT-PCR was conducted to detect serum levels of lncRNA-ATB and p53 in CHD patients (

n
=
50

) and healthy subjects (

n
=
50

). Correlation in serum levels of lncRNA-ATB and p53 in CHD patients was assessed by Pearson correlation test. ROC curves were depicted for analyzing the predictive potential of lncRNA-ATB in the occurrence of CHD. After metformin induction in VSMCs overexpressing lncRNA-ATB, relative levels of lncRNA-ATB and p53 were detected. Meanwhile, proliferative, migratory, and invasive abilities in VSMCs were, respectively, examined by CCK-8 and transwell assay. The interaction between lncRNA-ATB and p53 was tested by RIP. In addition, the coregulation of lncRNA-ATB and p53 in cell functions of VSMCs was finally determined. Results. Increased serum level of lncRNA-ATB and decreased p53 level were detected in CHD patients than those of healthy subjects. LncRNA-ATB could interact with p53 and negatively regulate its level. In addition, lncRNA-ATB could serve as a potential biomarker for predicting the occurrence of CHD. The overexpression of lncRNA-ATB triggered viability, migratory, and invasive abilities in VSMCs, and the above trends were abolished by metformin induction. The overexpression of p53 partially abolished the promotive effects of lncRNA-ATB on proliferative, migratory, and invasive abilities in VSMCs. Conclusions. Metformin induction inhibits proliferative, migratory, and invasive abilities in VSMCs by downregulating lncRNA-ATB, which may be related to p53 activation.
Physicochemical Properties of Red Beetroot and Quince Fruit Extracts Instant Beverage Powder: Effect of Drying Method and Maltodextrin Concentration
Authors: Hajiaghaei Marziyeh , Sharifi Akram
Published: January 2022

In this study, production of instant beverage powder by the foam-mat drying method (foam-mat freeze- and hot-air drying) from red beetroot, quince fruit, and cinnamon extracts without and with maltodextrin (MD) (0%, 10%, 20%, and 30%) were investigated. The results showed that an increase in the MD level has led to a decrease in the moisture content of powders. Drying method and MD concentration had a significant effect on rehydration time, color, and total phenolic content (

p
≤
0.05

). Foam-mat hot-air-dried powder containing 20% MD had a good flowability. According to the statistical analysis, MD content had a more significant effect on the antioxidant activity of powders than the drying method (

p
≤
0.05

). The total phenolic content of foam-mat hot-air-dried powders was higher than that of foam-mat freeze-dried powders. Based on the results, the produced powder containing 20% MD via foam-mat hot-air drying (60°C) was the optimum sample.
Machine Learning Techniques for Human Age and Gender Identification Based on Teeth X-Ray Images
Authors: Santosh K. C. , Pradeep Nijalingappa , Goel Vikas , Ranjan Raju , Pandey Ekta , Shukla Piyush Kumar , Nuagah Stephen Jeswinde
Published: January 2022

The use of digital medical images is increasing with advanced computational power that has immensely contributed to developing more sophisticated machine learning techniques. Determination of age and gender of individuals was manually performed by forensic experts by their professional skills, which may take a few days to generate results. A fully automated system was developed that identifies the gender of humans and age based on digital images of teeth. Since teeth are a strong and unique part of the human body that exhibits least subject to risk in natural structure and remains unchanged for a longer duration, the process of identification of gender- and age-related information from human beings is systematically carried out by analyzing OPG (orthopantomogram) images. A total of 1142 digital X-ray images of teeth were obtained from dental colleges from the population of the middle-east part of Karnataka state in India. 80% of the digital images were considered for training purposes, and the remaining 20% of teeth images were for the testing cases. The proposed gender and age determination system finds its application widely in the forensic field to predict results quickly and accurately. The prediction system was carried out using Multiclass SVM (MSVM) classifier algorithm for age estimation and LIBSVM classifier for gender prediction, and 96% of accuracy was achieved from the system.
Mechanism of Long Noncoding RNA HOTAIR in Nucleus Pulposus Cell Autophagy and Apoptosis in Intervertebral Disc Degeneration
Authors: Zhang Shujun , Song Sheng , Cui Wei , Liu Xueguang , Sun Zhenzhong
Published: January 2022

Objective. Intervertebral disc degeneration (IDD) contributes to cervical and lumbar diseases. Long noncoding RNAs (lncRNAs) are implicated in IDD. This study explored the mechanism of lncRNA HOTAIR in IDD. Methods. Normal and degenerative nucleus pulposus (NP) cells were isolated from NP tissues obtained in intervertebral disc surgery. Cell morphology was observed by immunocytochemistry staining and toluidine blue staining. NP cell markers were detected by RT-qPCR. Proliferation was detected by MTT assay. Autophagy-related proteins were detected by Western blot. Autophagosome was observed by monodansylcadaverine fluorescence staining. Apoptosis was detected by TUNEL staining and flow cytometry. si-HOTAIR and/or miR-148a inhibitor was introduced into degenerative NP cells. Binding relationships among HOTAIR, miR-148a, and PTEN were predicted and verified by dual-luciferase reporter assay and RNA pull-down. Finally, IDD rat models were established. Rat caudal intervertebral discs were assessed by HE staining. Expressions of HOTAIR, miR-148a, and PTEN were determined by RT-qPCR. Results. HOTAIR was highly expressed in degenerative NP cells

p
<
0.05

. si-HOTAIR inhibited degenerative NP cell apoptosis and autophagy

p
<
0.05

. HOTAIR upregulated PTEN as a sponge of miR-148a. miR-148a was poorly expressed in degenerative NP cells. miR-148a deficiency partially reversed the inhibition of si-HOTAIR on degenerative NP cell autophagy and apoptosis (all

p
<
0.05

). In vivo assay confirmed that si-HOTAIR impeded autophagy and apoptosis in intervertebral disc tissues, thus improving pathological injury in IDD rats (all

p
<
0.05

). Conclusion. LncRNA HOTAIR promoted NP cell autophagy and apoptosis via promoting PTEN expression as a ceRNA of miR-148a in IDD.
Research on Electrostatic Monitoring of Tribo-Contacts with Dynamic Adaptive Fusion Method
Authors: Liu Ruochen , Wang Han , Zhang Jinwu , Gu Shuangshuang , Sun Jianzhong
Published: January 2022

Electrostatic monitoring is a unique and rapid developing technique applied in the prognostics and health management of the tribological system based on electrostatic charging and sensing phenomenon. It has considerable advantages in condition monitoring of tribo-contacts with high sensitivity and resolution. Unfortunately, the monitoring result can be affected due to the switch of operating conditions that reduces its accuracy. This paper presents a dynamic adaptive fusion approach, moving window local outlier factor based on electrostatic features to overcome the influence. Life cycle experiments of rolling bearings and railcar gearbox were carried out on an electrostatic monitoring platform. The MWLOF method was used to extract and analyze the experimental data, combined with the Pauta criterion to judge wear faults quantitatively, and compare with other feature extraction results. It is verified that the proposed method can overcome the influence of changes in working conditions on the monitoring results, improve the monitoring sensitivity, and provide an accurate reference for friction and wear faults.
Synthesis and Characterization of Mechanical Properties of AA8014 + Si3N4/ ZrO2 Hybrid Composites by Stir Casting Process
Authors: Ramesh Kannan C. , Venkatesh R. , Vivekanandan M. , Phani Krishna J. , Manivannan S. , Rajkumar S. , Vijayan V.
Published: January 2022

Lightweight materials are extremely needed for the manufacturing of industrial parts and are used in aerospace, automobile body shops, biomedical instruments, etc. Aluminium alloy is one of the light-weight materials, and it fulfills the industrial demands based on their natural strength/stiffness, enhanced temperature permanence, superior wear, and corrosion resistance. This experimental work considered aluminium alloy (AA8014) with reinforced particles of silicon nitride (Si3N4) and zirconium dioxide (ZrO2) for preparing aluminium hybrid composites. Hybrid composites are prepared by a stir casting process involving different process parameters. L27 orthogonal array is used for optimizing the stir casting parameters with the assistance of the statistical Taguchi approach. Stir casting parameters are the percentage of reinforcement (4%, 6%, and 8%), stir speed (400 rpm, 500 rpm, and 600 rpm), stir time (20 min, 25 min, and 30 min), and molten temperature (700 oC, 800 oC, and 900 oC). Mechanical performance such as wear and microhardness of the hybrid composites is evaluated. Minimum wear and higher microhardness are encountered at a percentage of reinforcement = 6%, stir speed = 400 rpm, stir time = 30 min, and molten temperature = 900°C. In wear analysis, the percentage of reinforcement highly influences the wear properties (7.06% contribution). In microhardness analysis, molten temperature parameter is the extreme influencer (11.15% contribution).
CTI View: APT Threat Intelligence Analysis System
Authors: Zhou Yinghai , Tang Yi , Yi Ming , Xi Chuanyu , Lu Hai
Published: January 2022

With the development of advanced persistent threat (APT) and the increasingly severe situation of network security, the strategic defense idea with the concept of “active defense, traceability, and countermeasures” arises at the historic moment, thus cyberspace threat intelligence (CTI) has become increasingly valuable in enhancing the ability to resist cyber threats. Based on the actual demand of defending against the APT threat, we apply natural language processing to process the cyberspace threat intelligence (CTI) and design a new automation system CTI View, which is oriented to text extraction and analysis for the massive unstructured cyberspace threat intelligence (CTI) released by various security vendors. The main work of CTI View is as follows: (1) to deal with heterogeneous CTI, a text extraction framework for threat intelligence is designed based on automated test framework, text recognition technology, and text denoising technology. It effectively solves the problem of poor adaptability when crawlers are used to crawl heterogeneous CTI; (2) using regular expressions combined with blacklist and whitelist mechanism to extract the IOC and TTP information described in CTI effectively; (3) according to the actual requirements, a model based on bidirectional encoder representations from transformers (BERT) is designed to complete the entity extraction algorithm for heterogeneous threat intelligence. In this paper, the GRU layer is added to the existing BERT-BiLSTM-CRF model, and we evaluate the proposed model on the marked dataset and get better performance than the current mainstream entity extraction mode.