bluuebunny/crossref_metadata_2025 huggingface dataset:
Stratification of Children with Autism Spectrum Disorder Through Fusion of Temporal Information in Eye-gaze Scan-Paths
Authors: Atyabi Adham , Shic Frederick , Jiang Jiajun , Foster Claire E. , Barney Erin , Kim Minah , Li Beibin , Ventola Pamela , Chen Chung Hao
Published: June 2022

Background:

Looking pattern differences are shown to separate individuals with Autism Spectrum Disorder (ASD) and Typically Developing (TD) controls. Recent studies have shown that, in children with ASD, these patterns change with intellectual and social impairments, suggesting that patterns of social attention provide indices of clinically meaningful variation in ASD.

Method:

We conducted a naturalistic study of children with ASD (n = 55) and typical development (TD, n = 32). A battery of eye-tracking video stimuli was used in the study, including Activity Monitoring (AM), Social Referencing (SR), Theory of Mind (ToM), and Dyadic Bid (DB) tasks. This work reports on the feasibility of spatial and spatiotemporal scanpaths generated from eye-gaze patterns of these paradigms in stratifying ASD and TD groups.

Algorithm:

This article presents an approach for automatically identifying clinically meaningful information contained within the raw eye-tracking data of children with ASD and TD. The proposed mechanism utilizes combinations of eye-gaze scan-paths (spatial information), fused with temporal information and pupil velocity data and Convolutional Neural Network (CNN) for stratification of diagnosis (ASD or TD).

Results:

Spatial eye-gaze representations in the form of scanpaths in stratifying ASD and TD (ASD vs. TD: DNN: 74.4%) are feasible. These spatial eye-gaze features, e.g., scan-paths, are shown to be sensitive to factors mediating heterogeneity in ASD: age (ASD: 2–4 y/old vs. 10–17 y/old CNN: 80.5%), gender (Male vs. Female ASD: DNN: 78.0%) and the mixture of age and gender (5–9 y/old Male vs. 5–9 y/old Female ASD: DNN:98.8%). Limiting scan-path representations temporally increased variance in stratification performance, attesting to the importance of the temporal dimension of eye-gaze data. Spatio-Temporal scan-paths that incorporate velocity of eye movement in their images of eye-gaze are shown to outperform other feature representation methods achieving classification accuracy of 80.25%.

Conclusion:

The results indicate the feasibility of scan-path images to stratify ASD and TD diagnosis in children of varying ages and gender. Infusion of temporal information and velocity data improves the classification performance of our deep learning models. Such novel velocity fused spatio-temporal scan-path features are shown to be able to capture eye gaze patterns that reflect age, gender, and the mixed effect of age and gender, factors that are associated with heterogeneity in ASD and difficulty in identifying robust biomarkers for ASD.
The Joubert–Meckel–Nephronophthisis Spectrum of Ciliopathies
Authors: Van De Weghe Julie C. , Gomez Arianna , Doherty Dan
Published: June 2022

The Joubert syndrome (JS), Meckel syndrome (MKS), and nephronophthisis (NPH) ciliopathy spectrum could be the poster child for advances and challenges in Mendelian human genetics over the past half century. Progress in understanding these conditions illustrates many core concepts of human genetics. The JS phenotype alone is caused by pathogenic variants in more than 40 genes; remarkably, all of the associated proteins function in and around the primary cilium. Primary cilia are near-ubiquitous, microtubule-based organelles that play crucial roles in development and homeostasis. Protruding from the cell, these cellular antennae sense diverse signals and mediate Hedgehog and other critical signaling pathways. Ciliary dysfunction causes many human conditions termed ciliopathies, which range from multiple congenital malformations to adult-onset single-organ failure. Research on the genetics of the JS-MKS-NPH spectrum has spurred extensive functional work exploring the broadly important role of primary cilia in health and disease. This functional work promises to illuminate the mechanisms underlying JS-MKS-NPH in humans, identify therapeutic targets across genetic causes, and generate future precision treatments.
Translating Microbiome Research From and To the Clinic
Authors: Zhang Zhenrun J. , Lehmann Christopher J. , Cole Cody G. , Pamer Eric G.
Published: June 2022

Extensive research has elucidated the influence of the gut microbiota on human health and disease susceptibility and resistance. We review recent clinical and laboratory-based experimental studies associating the gut microbiota with certain human diseases. We also highlight ongoing translational advances that manipulate the gut microbiota to treat human diseases and discuss opportunities and challenges in translating microbiome research from and to the bedside.
Development and characterization of a mass cytometry panel for detecting the effect of acute doxorubicin exposure on murine cardiac nonmyocytes
Authors: Iskra Brian S. , Davis Logan , Miller Henry E. , Chiu Yu-Chiao , Bishop Alexander J. R. , Chen Yidong , Aune Gregory J.
Published: June 2022

Here, we describe the first mass cytometry studies of murine cardiac nonmyocytes. The mass cytometry panel is compared with single-cell RNA sequencing data using a novel approach of joint clustering with a deep neural network to assist in mass cytometry data labeling. Cardiac nonmyocytes in homeostasis are characterized by mass cytometry to identify replicating cells and variability in percent cellular composition of four major cell populations: endothelial cells, fibroblasts, leukocytes, and pericytes. The single-cell acute nonmyocyte response to doxorubicin is studied at 24 h and 72 h time points after doxorubicin exposure given daily for 5 days at a dose of 4 mg/kg/day, representative of acute, critical toxicity.
COVID-19 Propagation Prediction Model Using Improved Grey Wolf Optimization Algorithms in Combination with XGBoost and Bagging-Integrated Learning
Authors: Duan Yonghui , Mao Yaqi , Guo Yibin , Wang Xiang , Gao Shen
Published: June 2022

Toward solving the slow convergence and low prediction accuracy problems associated with XGBoost in COVID-19-based transmission prediction, a novel algorithm based on guided aggregation is presented to optimize the XGBoost prediction model. In this study, we collect the early COVID-19 propagation data using web crawling techniques and use the Lasso algorithm to select the important attributes to simplify the attribute set. Moreover, to improve the global exploration and local mining capability of the grey wolf optimization (GWO) algorithm, a backward learning strategy has been introduced, and a chaotic search operator has been designed to improve GWO. In the end, the hyperparameters of XGBoost are continuously optimized using COLGWO in an iterative process, and Bagging is employed as a method of integrating the prediction effect of the COLGWO-XGBoost model optimization. The experiments, firstly, compared the search means and standard deviations of four search algorithms for eight standard test functions, and then, they compared and analyzed the prediction effects of fourteen models based on the COVID-19 web search data collected in China. Results show that the improved grey wolf algorithm has excellent performance benefits and that the combined model with integrated learning has good prediction ability. It demonstrates that the use of network search data in the early spread of COVID-19 can complement the historical information, and the combined model can be further extended to be applied to other prevention and control early warning tasks of public emergencies.
Application of Digital Image Processing and GIS Technology in the Evaluation of Rationality of Urban and Rural Planning Spatial Layout
Authors: Jingfeng Hao , Xiaoyu Shen
Published: June 2022

This work investigates digital image processing technology and presents a super-resolution image reconstruction approach to increase the logic of urban and rural planning spatial layout. Furthermore, this work integrates GIS technology with super-resolution image reconstruction techniques to create a digital image processing and GIS-based urban and rural spatial layout design model. In addition, this paper mathematically expresses the objects and scenes that need to be simulated as a collection of three-dimensional graphic objects stored in the computer. The platform is constructed with a three-tier system of B/S architecture, and the logical structure of the entire system is composed of the client, application server, database server, and other functional servers. Furthermore, this paper constructs the functional structure of urban and rural spatial layout planning model based on digital image processing and GIS technology and verifies the model in this paper through experimental research. The experimental statistical results verify the reasonableness of the model in this paper.
Spiral Computed Tomography Imaging Analysis of Positioning of Lumbar Spinal Nerve Anesthesia under the Concept of Enhanced Recovery after Surgery
Authors: Feng Xue , Zhao Binbin , Wang Yongqiang
Published: June 2022

The objective of this research was to explore the effect of perioperative anesthesia management for patients based on the concept of enhanced recovery after surgery (ERAS) and the application value of the computed tomography (CT) localization method in lumbar spinal nerve anesthesia, reducing the damage caused by anesthesia. One hundred and twenty patients who underwent the lumbar spinal anesthesia in lower limb surgery were selected as the research subjects. According to puncture positioning and nursing intention, the patients were classified into the control group with 30 patients (method of anatomical landmarks), CT group with 50 patients (the CT localization), and ERAS group with 40 patients (the CT localization and the ERAS management). The effects of the anesthesia positioning method and the ERAS management were compared and analyzed. The results showed that d (0.32) and r (0.27) of exponential filtering function were notably smaller than those of R‐L filtering function (d = 0.40, r = 0.39) and of S‐R filtering function (d = 0.37, r = 0.36) (P < 0.05). Puncture time ((9.23 ± 0.32) min vs. (13.11 ± 0.45) min), puncture direction change (20% vs. 33.33%), abnormal puncture sensation (22% vs. 40%), and nerve root touch (4% vs. 23.33%) in the CT group were all lower than those in the control group. The proportion of Degree I anesthesia effect (94%) of the CT group was greatly higher than that of the control group (76.67%) (P < 0.05). The VAS score, time of activity and gastrointestinal function recovery, and the incidence of adverse reactions (2.5% vs. 28%) in the ERAS group were lower than those in the CT group (P < 0.05). All in all, the CT localization method can improve the difficulty of anesthesia puncture and improve the anesthetic effect; the ERAS nursing concept can improve the postoperative pain of patients and contribute to the prognosis of patients and have a good clinical value.
Image Classification and Recognition Based on Deep Learning and Random Forest Algorithm
Authors: Xi Erhui
Published: June 2022

Convolutional neural network (CNN) is an important way to solve the problems of image classification and recognition. It can realize effective feature representation and make continuous breakthroughs in the field of image recognition, but it needs a lot of time in the training process. At the same time, random forest (RF) has the advantages of fast training speed and high classification accuracy. Aiming at the problem of image classification and recognition, this paper proposes a hybrid model based on CNN, which inputs the features extracted by CNN into RF for classification. Since the random weight network can also obtain valid results, the gradient algorithm is not used to adjust the network parameters to avoid consuming a lot of time. Finally, experiments are conducted on MNIST dataset and rotated MNIST dataset, and the results show that the classification accuracy of the hybrid model has improved more than RF, and also, the generalization ability has been improved.
Risk Management of Prefabricated Building Construction Based on Fuzzy Neural Network
Authors: Yang Maohua
Published: June 2022

With the rapid development of society, the risk management of personal health and assets has become an important content that cannot be ignored in all walks of life. With the in-depth advancement of risk management, most of the construction risks of prefabricated buildings adopt qualitative research based on experience and intuitive judgment and quantitative research on quantitative mathematical statistics, but there are few models for risk assessment of prefabricated buildings with dynamic characteristics to adapt to the rapid development of prefabricated buildings and the lack of prefabricated construction in various stages and complex environments, with risk prediction and effective response capabilities. Based on this, this paper attempts to propose a fuzzy neural network risk research method for prefabricated building construction, making full use of the fuzzy neural network’s qualitative knowledge expression and quantitative numerical computing advantages, to establish a set of strong fault tolerance and better adaptive ability: fuzzy neural network evaluation model for extensive prefabricated building construction risk. Through the design of the fuzzy network model structure, the membership vector of the qualitative and quantitative indicators of the fuzzy comprehensive evaluation of the risk of prefabricated building construction is used as the input vector of the neural network, and the evaluation result is used as the output of the neural network. The samples were trained, programmed, and debugged, and it was found that the training results of the samples were in good agreement with the expected output results, which further verified the feasibility and applicability of the fuzzy neural network in the risk assessment process of prefabricated buildings. It is of good guiding significance to conduct continuous observation and formulate effective risk aversion and response plans.
FSIP1 Is Associated with Poor Prognosis and Can Be Used to Construct a Prognostic Model in Gastric Cancer
Authors: Yan Xiuchun , Dai Junzhu , Han Ying , You Qi , Liu Yao
Published: June 2022

Gastric cancer (GC) is one of the most common upper gastrointestinal malignant tumors, and the incidence of the GC shows an increasing trend in the past years. Finding more sensitive markers will help to reveal the mechanism of GC progression and clinic diagnoses. This study first analyzed the mRNA expression level of FSIP1 in TCGA GC samples and the significance in predicting the prognosis. KEGG and GO analyses were used to explore the molecular mechanism of FSIP1 in GC progression. This study further retrospectively analyzed 166 clinical samples of GC from Harbin Medical University Cancer Hospital and evaluated the expression level of FSIP1 by immunohistochemistry. Kaplan-Meier and Cox multivariate analysis was used to investigate the prognostic value of FSIP1 expression in GC patients. We also identified correlations between FSIP1 and clinicopathological characteristics. This study found that the mRNA level of FSIP1 was significantly upregulated in GC compared with nontumor specimens and correlated with poor prognosis. Immunohistochemistry confirmed the results of bioinformatics analysis of the TCGA GC database. FSIP1 was associated with pTNM pathological stage, tumor location, and neural invasion. In addition, multivariate Cox regression analysis showed that FSIP1, T classification, and N classification were independent posterior factors of patients and could be combined with pathological features to construct a nomogram prognostic model. Overall, our results suggest that FSIP1 is expected to be an independent prognostic indicator of GC.
Aberrant Spontaneous Brain Activity in Coronary Heart Disease Using Fractional Amplitude of Low-Frequency Fluctuations: A Preliminary Resting-State Functional MRI Study
Authors: Lin Simin , Han Yi , Duan Shaoyin , Wu PuYeh , Wu Naiming , Xie Ting , Li Qin , Lu Qing , Zhao Hengyu
Published: June 2022

Objective. This study is aimed at exploring the spontaneous brain activity changes by measuring the fractional amplitude of low-frequency fluctuations (fALFF) and their relationship with clinical characteristics in patients with coronary heart disease (CHD). Methods. Coronary heart disease patients (

n
=
25

) and age, gender, and education level-matched control subjects (controls,

n
=
35

) were included. The grey matter volume (GMV) and fALFF values were calculated to assess the difference in brain structure and function between the two groups, respectively. Correlation analyses between the fALFF values and clinical characteristics were further assessed in CHD patients. In addition, receiver operating characteristic (ROC) curves were conducted to access the diagnostic ability of the fALFF method. Results. There was no significant difference in GMV between the CHD and control groups. Compared with the control group, patients with CHD showed significantly decreased fALFF in the left precentral/postcentral gyrus and increased fALFF in the right inferior cerebellum. Patients with a history of myocardial infarction (MI) showed significantly decreased fALFF values of the right inferior cerebellum than patients without MI. There was no significant correlation between the fALFF values in specific brain regions and disease duration. Furthermore, the ROC curves of abnormal brain regions showed the perfect accuracy of the fALFF value in distinguishing between CHD patients and controls. Conclusion. CHD demonstrated aberrant neural activity in specific brain regions mainly related to sensorimotor networks and pain processing, which may contribute to understanding the underlying neurological mechanism of CHD.
[Retracted] Automatic Segmentation of Calcification Areas in Digital Breast Images
Authors: Abdulrazzaq Ammar Akram , Muhammed Yasser , Al-Douri Asaad T. , Mohamad A. A. Hamad , Ibrahim Abdelrahman Mohamed
Published: June 2022

In this study, the authors hope to demonstrate that when mammography is combined with intelligent segmentation techniques, it can become more effective in diagnosing breast abnormalities and aiding in the early detection of breast cancer. In conjunction with intelligent segmentation techniques, mammography can be made more effective in diagnosing breast abnormalities and aiding in the early diagnosis of breast cancer, hence increasing its overall effectiveness. The methodology, which includes some concepts of digital imaging and machine learning techniques, will be described in the following section after a review of the literature on breast cancer (categories, prevention involving the environment and lifestyle, diagnosis, and tracking of the disease) has been completed (neural networks and random forests). It was possible to achieve these results by working with an image collection that previously had questionable regions (per the given technique). Fiji software extracted problematic candidate regions from mammography images, which were subsequently subjected to further examination. To categorize the results of the picture segmentation, they were sorted into three groups, which were as follows: random forest and neural networks both generated promising results in the segmentation of suspicious parts that were emphasized in the highlight of the image, and this was true for both algorithms. Detection of contours of the regions was carried out, indicating that cuts of these segmented sections may be created. Later on, automatic categorization of the targets can be carried out using a learning algorithm, as illustrated in the experiment.
Transcutaneous Electrical Acupoint Stimulation Ameliorates Cognitive Function through PINK1/Parkin Mediated Mitophagy in VD Rats
Authors: Hu Ziwei , Wen Tianshan , Hu Ke , Wang Rui , Su Xinda , Ouyang Wei , Zhou Junjie , Wen Youliang
Published: June 2022

In this study, we investigated whether transcutaneous electrical acupoint stimulation (TEAS) could improve cognitive function in VD rats by regulating PINK1/Parkin-mediated mitophagy. VD rat model was prepared by modified 2-vessel occlusion (2-VO) and randomly divided into four groups: Sham group (Sham), Model group (Model), TEAS group (TEAS), and TEAS + 3-MA group (T +3 -MA). In the T +3 -MA group, autophagy inhibitor (3-MA) was injected into the lateral ventricle. After modeling, Y maze (YM), new object recognition test (NORT), Morris water maze (MWM), immunofluorescence, and Western blot were used to observe the effects of TEAS on VD rats. Behavioral experiments revealed that TEAS effectively improved the learning and memory ability of VD rats. Immunofluorescence results showed that TEAS could upregulate LC3 expression. Western blot results showed that TEAS upregulated the expression of PINK1, Parkin, and LC3-II, and downregulated the expression of LC3-I and p62 in VD rats. T +3 -MA group shows the opposite trend to TEAS group. This study demonstrates that TEAS ameliorates cognitive function through PINK1/Parkin-mediated mitophagy in VD rats.
Inbound Tourists’ Perception of Tourist Destination Image Classified by UGC Picture Computer Program
Authors: Fu Xiuqing , Wan Fang , Wu Ying
Published: June 2022

Travel has become a way of life for more and more people. The rapid development of technologies such as the Internet and 5G brings convenience to life, so recording one’s travel through social media has become the main way of sharing. Based on the classification of UGC pictures by computer program, this paper studies the perception of tourist destination image by inbound tourists from different regions so as to find the factors that potentially affect tourists’ decision-making. This study collects a large number of UGC pictures and classifies them according to computer programs. It conducts UGC data picture research through two different aspects of cognitive image and emotional image and finally analyzes the specific image perception of Shanghai tourism. The research results show that, in the analysis of specific inbound tourists’ perception of tourist destination image, in the eyes of Western inbound tourists, Shanghai is a very modern cultural city with very distinctive architectural features; inbound tourists from East Asia are more and more interested in the cultural landscape and natural scenery of Shanghai. In the eyes of inbound tourists from East Asia, Shanghai is a city full of vitality. Among them, the Huangpu River is the place that receives the most tourists. 21.5% of inbound tourists will visit, and 13.7% of inbound tourists choose to visit Lujiazui.
Study on Thermal Performance Measurement and Construction of Passive Exterior Wall with Low Energy: Teaching and Laboratory Building of Shandong Jianzhu University
Authors: Lan Yirui , Zou Ran
Published: June 2022

It can provide theoretical support for the optimal design of low-energy walls by measuring the actual thermal conditions inside the walls of passive low-energy buildings and studying the rationality of the wall structure design. Taking the teaching and laboratory building of Shandong Jianzhu University as an example, this paper explores the method of using temperature and humidity sensor to measure the air temperature and humidity inside the wall to represent the solid temperature and humidity of the wall. Based on the measured data and calculation results, the rationality of the structure of the test external wall is analyzed from four aspects: the performance of insulation, the moisture drain performance of wall, the ability of preventing the penetration of the hot and humid air of the inner wall, and the waterproof performance of the outer wall. Results show that the external wall structure of polystyrene board (200 mm thick) for external insulation and thin plastering has good practical operation effect in three aspects of thermal insulation, internal moisture discharge, and external wall waterproof, which basically meets the design requirements of external wall of passive house in Germany. In terms of moisture protection of the inner wall, the inner wall of cement mortar (15 mm thick) may not be able to effectively prevent the infiltration of indoor hot and humid air. Thus, the insulation layer should be added into the external wall. In addition, the moisture inside the wall is obviously affected by the season. The drain performance of moisture inside the wall mainly occurs in the sweltering heat, and the drain direction is from the indoor side to the outdoor side. In the external insulation structure, there are two layers of graphite polystyrene plate (100 mm thick), and the insulation effect of polystyrene plate near the outdoor side is better than that near the indoor side. The combination of anticrack mortar (5 mm thick) and paint cannot completely prevent the infiltration of rainwater, but the infiltration of rainwater in the wall will be quickly discharged in a short time.
Probabilistic Analysis of Search Performance of Differential Evolution Algorithm in Low-Dimensional Case
Authors: Wang Congjiao , Wei Yuhan , Hou Yanlin , Wu Wenjia , Huang Cong , Chen Jing
Published: June 2022

In this paper, a method of establishing and analyzing the probability model of its mutation and crossoperation process for differential evolution (DE) algorithm is proposed; especially, the escape ability and further optimization ability of individuals trapped in the local optimal neighborhood are deduced in detail, and the characteristic curves of the influence of key parameters such as population size, scaling factor, and crossfactor on the search performance of the algorithm are obtained. It provides a theoretical reference for the application of the algorithm.
Strategies of Applying Visual Element Combination to Improve Visual Cognitive Efficiency in the Era of Big Data Network
Authors: Zhang Qiaohe , Lai Huijuan
Published: June 2022

Fundamentally, visual cognition refers to a way of thinking in which the objective information of the external world is transmitted to the brain through the visual nerve and then processed by the brain. In the evolutionary history of human beings, the pressure brought by the environment has led to the rapid development of the visual system and visual cognition. As with language ability and logical ability, the understanding of visual cognition is the key to the analysis of human intelligence. Therefore, research on improving the efficiency of visual cognition is urgently needed. The purpose of this paper is to find methods and strategies to improve the efficiency of visual cognition based on the application of visual element combination. This article first gives a general introduction to visual elements and design methods. Then, the eye movement behavior and visual saliency calculation model are established. Using Gaussian analysis and channel saliency test method based on “where” and “what” principles, the cognitive effect of pictures in visual elements is specifically analyzed. Then, the questionnaire survey method was used to conduct experiments on the problem that visual elements affect the efficiency of visual cognition, and finally the results were obtained. At the macro level, dynamic pictures with color and auxiliary text can effectively improve the cognitive efficiency of vision. It enables people to grasp cognitive objects quickly and form stronger cognitive ability. However, at the micro level, due to the intuitiveness and meaning of words, the visual cognitive efficiency of the recognition effect is high. In terms of image scale, the two scale parameters [4 × 4] and [6 × 6] perform better. The human eye is relatively optimal at 4/90∼6/90 on the attention scale of the image. At the same time, under the [4 × 4] scale parameter, even if the image loses some features, it can save about 95% of the cognitive time overhead.
Diagnostic Challenges of Helicobacter pylori Infection in Ethiopia: A Community-Based Cross-Sectional Study
Authors: Gudina Esayas Kebede , Amare Hiwot , Ali Solomon , Berhane Arefayine Melkamu , Tewolde Dagmawi , Tesfaye Eshete Million , Jebena Mulusew Gerbaba , Wieser Andreas , Froeschl Guenter , Tesfaye Markos , Desalegn Hailemichael , Gashaw Mulatu
Published: June 2022

Background. In resource-constrained countries, accurate diagnosis of Helicobacter pylori infection remains a challenge. This study aimed to assess the clinical utility of locally available serological and stool antigen test kits in the management of people with suspected H. pylori infection in Ethiopia. Methods. A community-based cross-sectional study was conducted with apparently healthy adults and children living in southwest Ethiopia. Participants were interviewed for dyspepsia symptoms and related clinical conditions. H. pylori infection was examined using commercially available serological and stool antigen tests. The association between H. pylori tests and dyspepsia symptoms was analyzed using logistic regression models. Results. Out of 1392 participants included in the final analysis, 49.1% and 6.5% tested positive for H. pylori infection with serology and stool antigen test kits, respectively. Participants reporting epigastric symptoms in the past three months (AOR = 1.93, 95% CI = 1.28–2.91) and those with recent dyspepsia treatment (AOR = 1.51, 95% CI = 1.05–2.18) were likely to have positive serology test. However, no association between dyspepsia symptoms and H. pylori stool antigen positivity was observed in our study. Conclusion. ccurate detection of H. pylori infections using commercially accessible diagnostics remains difficult in Ethiopia. With these methods, it will be hard to ensure adequate diagnosis and early treatment of H. pylori infection, as well as rational antibiotic use.
An Operation Plan Optimization Model for Integrated Customized and Conventional Bus Services Based on Cost Analysis
Authors: Lu Xi , Han Junru , Xu Peng , Liu Haode , Chen Xumei
Published: June 2022

A proper public transportation system should be economically efficient to improve its sustainability and competitiveness. The superfluous provision of conventional bus services in areas with a weak or scattered travel demand distribution might result in a waste of transport capacity. This study proposes an operation plan optimization model based on the characteristics and cost composition of conventional and customized bus services, which systematically analyzes the feasibility of fully or partially replacing conventional bus services with customized bus services. A mixed-integer planning model and a hybrid genetic algorithm are used to optimize the operation plan for specific travel demands and supply capacities. Then, a sensitivity analysis of key factors is carried out to identify the optimal operation mode under different circumstances. The results show that with an optimized fleet size, service frequency, and service area, integrated operation modes can reduce operating costs without sacrificing the passenger time.
[Retracted] C‐myc/TSPEAR‐AS2 Axis Facilitates Breast Cancer Growth and Metastasis in a GLUT1‐Dependent Glycolysis Manner
Authors: Xu Jian , Li Tao , Zhang Yang , Qiu Donghai , Chen Nan , Chai Xupeng , PengLi  , Li Jia
Published: June 2022

A large number of facts have shown that epigenetic modification and metabolic reprogramming represented by noncoding RNA play an important role in the invasion and metastasis of breast cancer, but the mechanism is not clear. The purpose of our study is to find a new biomarker of breast cancer and to provide a new perspective for regulating glucose metabolism and aerobic glycolysis of BC. In this paper, by downregulating C‐myc protein, our team found that the expression of long‐chain noncoding RNATSPAR‐AS2 was significantly downregulated. However, the expression of long‐chain noncoding RNASPAR‐AS2 in BC is relatively high, and the prognosis is poor. TSPEAR‐AS2 can promote the malignant phenotype of BC cells, including proliferation, apoptosis, invasion and metastasis, and glycolysis. At the same time, TSPEAR‐AS2 can also upregulate the expression of GLUT1, an important regulator of glycolysis, thus promoting the metabolic reprogramming of BC. Molecular mechanism experiments show that TSPEAR‐AS2 may promote the expression of GLUT1 by participating in IGF2BP2 modified by the GLUT1 gene. Our results suggest that the C‐myc/TSPEAR‐AS2/GLUT1 axis promotes the invasion and metastasis of BC by inducing glucose metabolism reprogramming. However, more phenotypic and molecular mechanism results need to be further verified.
Predictive Value of Monocyte Chemoattractant Protein-1 in the Development of Diastolic Dysfunction in Patients with Psoriatic Arthritis
Authors: Bursać Iva Uravić , Kehler Tatjana , Drvar Vedrana , Babarović Emina , Pejčinović Vesna Pehar , Baršić Antonija Ružić , Peršić Viktor , Laskarin Gordana
Published: June 2022

We aimed to evaluate the diagnostic accuracy of the proinflammatory monocyte chemotactic protein-1 (MCP-1) in the diagnosis of asymptomatic diastolic dysfunction (DD) in patients with psoriatic arthritis (PsA). The disease activity in psoriatic arthritis (DAPSA) was determined using clinical and laboratory parameters, and echocardiography was performed to estimate DD. Serum MCP-1 concentrations were elevated in PsA patients with DD diagnosed with ultrasound (median (25th percentile, 75th percentile): 366.6 pg/mL (283, 407.1 pg/mL) vs. 277.5 pg/mL (223.5, 319.1 pg/mL) in controls;

P
<
0.0017

). PsA patients with serum MCP-1 concentration higher than the cut-off value of 347.6 pg/mL had a 7.74-fold higher chance of developing DD than PsA patients with lower serum MCP-1 concentrations (controls), with a specificity of 86.36% and sensitivity of 55%, as verified using ultrasound. The group with MCP-1 concentrations above the cut-off value also showed a higher late peak diastolic mitral inflow velocity, A-wave value (

P
=
0.000005

), E/E

′

ratio (

P
=
0.00005

), and a lower E/A ratio (

P
=
0.000002

), peak systolic left atrial reservoir strain, SA value (

P
=
0.0066

), early peak diastolic displacement of the mitral septal annulus, E

′

wave value (

P
=
0.003

), than controls. Systolic blood pressure (

P
=
0.01

), LDL cholesterol concentration (

P
=
0.012

), glucose concentration (

P
=
0.011

), and DAPSA (

P
=
0.0000

) increased in the PsA group with higher MCP-1 concentrations, although there were no differences in comorbidities and therapy between the groups compared. Thus, the serum MCP-1 concentration was a significant and independent prognostic indicator for asymptomatic DD in PsA patients (

area
 
under
 
the
 
curve
=
0.730

,

P
=
0.001

). The DAPSA score in PsA patients might indicate the need for echocardiography and adjustment of anti-inflammatory treatment in terms of DD prevention.
Performance of the CORB (Confusion, Oxygenation, Respiratory Rate, and Blood Pressure) Scale for the Prediction of Clinical Outcomes in Pneumonia
Authors: Reyes Luis F. , Bastidas Alirio R. , Quintero Eduardo Tuta , Frías Juan S. , Aguilar Álvaro F. , Pedreros Karen D. , Herrera Manuela , Saza Laura D. , Nonzoque Alejandra P. , Bello Laura E. , Hernández Maria D. , Carmona Germán A. , Jaimes Anyelinne , Ramírez Silvia M , Murillo Natalia
Published: June 2022

Background. Community-acquired pneumonia (CAP) is a common cause of morbidity and mortality due to misdiagnosis and inappropriate treatment approaches. Objective. To assess the performance of the CORB score in subjects with CAP for predicting in-hospital mortality, death within 30 days of admission, and requirement for invasive mechanical ventilation (IMV) and vasopressor support. Methods. A retrospective, cohort study with diagnostic test analysis of CORB and CURB-65 scores in subjects with CAP according to ATS criteria was undertaken. An alternative CORB score was estimated by replacing SpO2 ≤90% by the SpO2/FiO2 ratio. Crude and adjusted odd ratios (AOR) were calculated for each variable. The area under the receiver operating characteristics curve (AUROC) was constructed for each score, and outcomes were analyzed. AUROCs were compared with the DeLong test, considering a p value

<
0,05

statistically significant. Results. From 1,811 subjects who entered the analysis, 15.1% (273/1,811) died in hospital, 8.78% required IMV (159/1,811), and 9.77% (177/1,811) needed vasopressor support. CORB had an AUROC of 0,660 (95% CI: 0,623–0,697) for in-hospital mortality; an AUROC of 0,657 (95% CI: 0,621–0,692) for 30-day mortality; an AUROC of 0,637 (CI 95%: 0,589–0,685) for IMV requirement; and an AUROC of 0,635 (95% CI: 0,589–0,681) for vasopressor support. CORB performance increases when the SpO2/FiO2 ratio <300 is used as oxygenation criterion in the prediction of requirement for IMV and vasopressor support, with AUROC of 0,700 (95% CI: 0,654–0,746;

p
<
0.001

) and AUROC of 0,702 (95% CI: 0,66–0,745;

p
<
0.001

), respectively. CURB-65 score presents an in-hospital mortality AUROC of 0,727 (95% CI: 0,695–0,759) and 30-day mortality AUROC of 0,726 (95% CI: 0,695–0,756). Conclusions. CORB score has a good performance in predicting the need for IMV and vasopressor support in CAP patients. This performance improves when the SpO2/FiO2 ratio <300 is used instead of the SpO2 ≤90% as the oxygenation parameter. CURB-65 score is superior in the prediction of mortality.
Improved Adaptive Fault-Tolerant Control of a Variable Structure Fighter with Multiple Faults Based on an Extended Observer
Authors: Hu Kaiyu , Sun Wenjing , Yang Chunxia
Published: June 2022

In this paper, an improved adaptive fault-tolerant control (FTC) scheme is presented based on an extended state observer (ESO) for a highly maneuverable variable structure fighter (VSF) with simultaneous faults of the rudder surface and sensor. The feedback linearization model of the attitude system with faults and external disturbances is introduced. In order to realize the real-time observation of the rudder and sensor faults, a neural network estimator is used to approximate sensor faults, and the ESO is designed to estimate the rudder surface fault and attitude variables. On this basis, the estimated value is used to replace the measured value for state variables to design the adaptive fault-tolerant controller for the inner and outer loop, combined with the second-order command filter to offset the phenomenon of backstepping differential amplification system noise. Finally, the proposed FTC scheme realizes the variable structure self-repairing of multiple positions, multiple types of faults in VSF using fault estimation. The Lyapunov theory and Barbalat’s lemma prove the stability of the designed observer and controller. The effectiveness of the FTC scheme is verified by a simulation experiment.
The Emerging Role of MTHFD Family Genes in Regulating the Tumor Immunity of Oral Squamous Cell Carcinoma
Authors: Wang Wei , Gu Wenli , Tang Hai , Mai Zhaoyi , Xiao Hui , Zhao Jianjiang , Han Jiusong
Published: June 2022

Objective. To investigate the function and regulatory mechanisms of methylenetetrahydrofolate dehydrogenase (MTHFD) family genes in oral squamous cell carcinoma (OSCC), especially focus on their regulating role in tumor immunity. Methods. The publicly available data from the TCGA database were used to investigate the expression pattern and regulatory role of MTHFD family genes in OSCC. More importantly, the involvement of MTHFD family genes in tumor immunity was investigated in terms of immune and stromal cell infiltration in tumor microenvironment, tumor-infiltrating immune cells, and immunomodulatory genes (e.g., immunoinhibitory genes and immunostimulatory genes). Statistical analysis was performed using R software packages and public web servers. Results. MTHFD family genes were considerably upregulated in OSCC as compared with normal oral tissue. Patients with high MTHFD2 expression presented worse survival outcomes than those with low MTHFD2 expression. Functional enrichment analysis showed that the top 100 positively and negatively correlated genes of the MTHFD family genes were significantly enriched in several KEGG pathways, including cell cycle, spliceosome, DNA replication, and Th17 cell differentiation. As a result of tumor immunity analysis, MTHFD2L expression was found to be negatively related to the Estimate-Stromal-Immune score in OSCC; however, there was no statistical significance between the Estimate-Stromal-Immune score and MTHFD1, MTHFD1L, or MTHFD2 in OSCC. Additionally, MTHFD family genes were found to be significantly positively correlated with tumor-infiltrating immune cells, including Treg and Th17 cells. Moreover, MTHFD family genes were significantly correlated with several immune inhibitory genes such as CD274 and CTLA4 and several immune-stimulatory genes such as CXCL12, CXCR4, and TMIGD2. Conclusion. Given the expression pattern, prognostic value, biological functions, and involvement in tumor immunity, MTHFD family genes could serve as potential therapeutic biomarkers in targeting tumor immunity in oral cancer.
Framework to Segment and Evaluate Multiple Sclerosis Lesion in MRI Slices Using VGG-UNet
Authors: Krishnamoorthy Sujatha , Zhang Yaxi , Kadry Seifedine , Yu Weifeng
Published: June 2022

Multiple sclerosis (MS) is an autoimmune disease that causes mild to severe issues in the central nervous system (CNS). Early detection and treatment are necessary to reduce the harshness of the disease in individuals. The proposed work aims to implement a convolutional neural network (CNN) segmentation scheme to extract the MS lesion in a 2D brain MRI slice. To achieve a better MS detection, this work implemented the VGG-UNet scheme in which the pretrained VGG19 is considered as the encoder section. This scheme is tested on 30 patient images (600 images with dimension

512
×
512
×
3

pixels), and the experimental outcome confirms that this scheme provides a better result compared to traditional UNet, SegNet, VGG-UNet, and VGG-SegNet. The experimental investigation implemented on axial, coronal and sagittal plane 2D slices of Flair modality confirms that this work provides a better value of Jaccard (>85%), Dice (>92%), and accuracy (>98%).
Edge Cloud and Mobile Auxiliary Equipment of Fine Art Painting Course Teaching Auxiliary System Design
Authors: Wang Huijing
Published: June 2022

Due to the development of information technology, the new type of smart campus integrates teaching, scientific research, office services, and many other applications, and online education information resources show a blowout growth. Art and painting teaching courses in the cloud era also face a series of digital challenges. In view of the development of digital teaching mode, art and painting course is different from other courses and has higher requirements for the transmission of audio and video. How to transmit the audio and video generated during interactive teaching efficiently and with low latency is a challenge. In order to realize the needs of art painting course teaching, based on the characteristics of edge cloud and mobile auxiliary equipment, build the “double cloud” mode of art painting teaching auxiliary system, through the cloud edge deployed different layers and design adaptive code switching mechanism, realize the art painting teaching and remote teaching video flow, help to realize the teaching interaction between teachers and students and instant feedback, and help to improve the art painting course teaching effect.
Effectiveness of Nursing Risk Management in Neonatal Asphyxia Resuscitation Care
Authors: Ye Zhen , Wang Wenjun , Sun Peili
Published: June 2022

Objective. To analyze the effectiveness of nursing risk management in neonatal asphyxia resuscitation care and to observe and summarize the nursing measures and outcomes. Methods. A total of 60 neonatal asphyxia cases from January 2021 to December 2021 were recruited and assigned via a random number table method at a ratio of 1 : 1 to receive either routine care plus nursing risk management (the observation group, n = 30) or routine care (the control group, n = 30). Outcome measures included blood gas index, neonatal Apgar score, neonatal behavioral neurological assessment (NBNA) score, nursing satisfaction, and complications. Results. The differences in partial pressure of oxygen (PaO2) and partial pressure of carbon dioxide (PaCO2) between the two groups before care were not statistically significant (

P
>
0.05

), while after care, PaO2 in the observation group had a higher level of PaO2 and a lower level of PaCO2 than the control group (

P
<
0.01

). The two groups showed similar Apgar scores and NBNA scores before care (

P
>
0.05

), while after care, routine care plus nursing risk management resulted in higher Apgar scores and NBNA scores versus routine care alone (

P
<
0.01

). The nursing satisfaction rate in the observation group (96.67%) was significantly higher than that of the control group (73.33%) (

P
=
0.030

). Nursing risk management plus routine care was associated with a significantly lower incidence of complications (6.67%) compared to routine care (26.67%) (

P
=
0.038

). Conclusion. Nursing risk management in neonatal asphyxia resuscitation care showed outstanding outcomes in improving neonatal blood gas index, neurological function, and Apgar score, while reducing the occurrence of complications and achieving high nursing satisfaction.
Application of Computer Digital Technology and Group Psychological Counseling in Higher Vocational Education Mental Health Education Curriculum under Complex Network Environment
Authors: Han Yun
Published: June 2022

Today’s civilization is a network, with networks covering and organizing it. The important physical carrier of modern human social activities and interactions is a hybrid network formed by the interaction and integration of multiple networks, which is a dynamic and complex network. In the network environment, the mode and efficiency of information dissemination have changed qualitatively, which in turn profoundly affects the evolution of higher vocational education students’ attitudes toward things and their psychological states. At present, there are many problems and difficulties in mental health education in higher vocational education institutions: there are misunderstandings in setting curriculum teaching objectives, teaching methods are not flexible enough, the professionalism and stability of teachers need to be improved, and the follow-up of mental health education for students in schools is insufficient. For this reason, we should take active measures to improve the effectiveness of mental health education in higher vocational education institutions according to the characteristics of the times, establish reasonable mental health education curriculum objectives and evaluation methods, establish diversified teaching methods to adapt to the complex network environment, build a professional mental health education teacher team, actively improve the teaching concept of mental health education, and focus on strengthening mental health education counseling in the process of entrance education and career guidance. This paper proposes a method based on computer digital technology and group counseling in a complex network environment, which can be applied to higher vocational education mental health education courses, and the experimental results show that the designed method has a high accuracy rate and provides support for higher vocational education students’ psychological education and counseling.