bluuebunny/crossref_metadata_2025 huggingface dataset:
A Generative Adversarial Network Fused with Dual‐Attention Mechanism and Its Application in Multitarget Image Fine Segmentation
Authors: Yin Jian , Zhou Zhibo , Xu Shaohua , Yang Ruiping , Liu Kun
Published: December 2021

Aiming at the problem of insignificant target morphological features, inaccurate detection and unclear boundary of small‐target regions, and multitarget boundary overlap in multitarget complex image segmentation, combining the image segmentation mechanism of generative adversarial network with the feature enhancement method of nonlocal attention, a generative adversarial network fused with attention mechanism (AM‐GAN) is proposed. The generative network in the model is composed of residual network and nonlocal attention module, which use the feature extraction and multiscale fusion mechanism of residual network, as well as feature enhancement and global information fusion ability of nonlocal spatial‐channel dual attention to enhance the target features in the detection area and improve the continuity and clarity of the segmentation boundary. The adversarial network is composed of fully convolutional networks, which penalizes the loss of information in small‐target regions by judging the authenticity of prediction and label segmentation and improves the detection ability of the generative adversarial model for small targets and the accuracy of multitarget segmentation. AM‐GAN can use the GAN’s inherent mechanism that reconstruct and repair high‐resolution image, as well as the ability of nonlocal attention global receptive field to strengthen detail features, automatically learn to focus on target structures of different shapes and sizes, highlight salient features useful for specific tasks, reduce the loss of image detail features, improve the accuracy of small‐target detection, and optimize the segmentation boundary of multitargets. Taking medical MRI abdominal image segmentation as a verification experiment, multitargets such as liver, left/right kidney, and spleen are selected for segmentation and abnormal tissue detection. In the case of small and unbalanced sample datasets, the class pixels’ accuracy reaches 87.37%, the intersection over union is 92.42%, and the average Dice coefficient is 93%. Compared with other methods in the experiment, the segmentation precision and accuracy are greatly improved. It shows that the proposed method has good applicability for solving typical multitarget image segmentation problems such as small‐target feature detection, boundary overlap, and offset deformation.
Exploration of Using Modern Information Technology to Realize College English Distance Teaching
Authors: Hou Zhirong
Published: December 2021

China is gradually evolving to a knowledge-based society of computer information technology, knowledge economy, and learning. The modern information construction of college English is to realize the distance teaching of College English with the help of modern information technology, which is conducive to the continuous development of network education in China in the direction of modern information. This paper summarizes the research objectives and contents of college English modern information technology construction. We analyze the significance of implementing college English modern information technology and realize distance teaching. We put forward important measures for college English information technology to realize distance teaching, in order to bring some reference to relevant professionals. Finally, the sharing of high-quality educational resources will be realized, so as to provide reference for further improving the situation of rural English teaching.
Diagnosis and Classification Decision Analysis of Overheating Defects of Substation Equipment Based on Infrared Detection Technology
Authors: Shi Zhigang , Zhao Yunlong , Liu Zhanshuang , Zhang Yanan , Ma Le
Published: December 2021

Substation equipment is not only the main part of the power grid but also the essential part to ensure the development of the national economy and People's Daily life of one of the important infrastructure. How to ensure its normal operation and find the sudden failure has become a hot issue to be solved urgently. For thermal fault diagnosis needs to classify and identify different power equipment first, this paper designed an SVM infrared image classifier, which can effectively identify three types of common power equipment. The classifier extracts HOG features from the infrared images of power equipment processed by the above segmentation and combines them with SVM multiclassification to achieve the purpose of improving the recognition accuracy. The experiment uses the classifier to identify three kinds of equipment, and the results show that the comprehensive recognition accuracy of the classifier is more than 95.3%, which is better than the traditional classification method and meets the demand for classification accuracy. In this paper, the traditional method of relative temperature difference is improved by using the temperature data of the infrared image, which can automatically judge the thermal failure level of electric power equipment. Experiments show that the diagnosis system designed in this paper can classify faults and give treatment suggestions while judging whether there are thermal faults for three types of power equipment, which verifies the feasibility and effectiveness of the substation infrared diagnosis technology designed in this paper.
Acute Mania and Catatonia in a Teenager Successfully Treated with Electroconvulsive Therapy and Diagnosed with Turner Syndrome and Bipolar Disorder
Authors: Ygland Rödström Maria , Johansson Björn Axel , Bäckström Beata , Movahed Pouya , Forslund Carl-Magnus , Rask Olof
Published: December 2021

Background. Turner syndrome (TS) is an X-linked chromosomal abnormality with a global prevalence of 1/2000 live-born girls. The physiological symptoms of TS have been thoroughly characterized, but only a few studies have described associated psychiatric symptoms. We report a case of an adolescent girl who presented with acute mania with psychotic features and was successfully treated with electroconvulsive therapy (ECT). She was subsequently diagnosed with bipolar syndrome and TS. Case Presentation. A 17-year-old girl presented to us with manic symptoms, including disorganized speech, auditory hallucinations, and affect lability. Initially, she was treated with antipsychotics and benzodiazepines, whereby the positive affective symptoms declined. However, the psychotic symptoms progressed, and she developed a catatonic state. ECT was started 6 days after admission, with improvement after two treatments. When ECT was tapered after seven sessions, she relapsed, and the treatment was extended to twelve sessions, with successful outcome. Following discharge, she was diagnosed with TS with partial loss on one of the X-chromosomes (46X, del (X)(p21)), which might have contributed to the development of her sudden acute manic episode. Conclusions. This case demonstrates for the first time that ECT may be a safe and efficient treatment strategy for acute mania in adolescents with concomitant TS and that severely affected adolescents may require a prolonged series with gradual tapering of ECT. The present case also demonstrates a possible association between TS and bipolar syndrome and that the clinical presentation of a manic episode in a patient with this comorbidity could be more complex and the treatment response slower.
The Evaluation of Synergy between University Entrepreneurship Education Ecosystem and University Students’ Entrepreneurship Performance
Authors: Wang Sheng-Yuan , Wu Xiao-Lan , Xu Meng , Chen Quan-Xin , Gu Ying-Jing
Published: December 2021

The interactive mechanism between college and university entrepreneurship education ecosystem and their students’ entrepreneurial performance needs to be further discussed, as college and university students are an important force in entrepreneurship. Since there is a lack of symbiotic mechanism analysis and interactive optimization research using ecological methods, this paper constructs the evaluation index system of entrepreneurship education ecosystem and entrepreneurship performance evaluation index system and uses the entropy weight method to determine the weight of various indicators in the index system more objectively. In this paper, Lotka–Volterra model in ecology is used to deeply study the mechanism between college and university entrepreneurship education ecosystem and entrepreneurship performance. Lotka–Volterra multichoice goal programming (MCGP) model is used to optimize the collaborative relationship between college and university entrepreneurship education ecosystem and entrepreneurship performance. Finally, a numerical example is given to illustrate the feasibility and effectiveness of the research method. The results show that Lotka–Volterra multichoice goal programming (MCGP) method is effective in evaluating the synergy between college and university entrepreneurship education ecosystem and the students’ entrepreneurship performance.
Human Motion Posture Detection Algorithm Using Deep Reinforcement Learning
Authors: Qi Limin , Han Yong
Published: December 2021

To address problems of serious loss of details and low detection definition in the traditional human motion posture detection algorithm, a human motion posture detection algorithm using deep reinforcement learning is proposed. Firstly, the perception ability of deep learning is used to match human motion feature points to obtain human motion posture features. Secondly, normalize the human motion image, take the color histogram distribution of human motion posture as the antigen, search the region close to the motion posture in the image, and take its candidate region as the antibody. By calculating the affinity between the antigen and the antibody, the feature extraction of human motion posture is realized. Finally, using the training characteristics of deep learning network and reinforcement learning network, the change information of human motion posture is obtained, and the design of human motion posture detection algorithm is realized. The results show that when the image resolution is 384 × 256 px, the motion pose contour detection accuracy of this algorithm is 87%. When the image size is 30 MB, the recognition time of this method is only 0.8 s. When the number of iterations is 500, the capture rate of human motion posture details can reach 98.5%. This shows that the proposed algorithm can improve the definition of human motion posture contour, improve the posture detailed capture rate, reduce the loss of detail, and have better effect and performance.
Different Testing Results on SVM with Double Penalty Parameters
Authors: Yao Chengkuan , Cao Liyong , Xu Jianhua , Yang Mingya
Published: December 2021

The Support Vector Machine proposed by Vapnik is a generalized linear classifier which makes binary classification of data based on the supervised learning. SVM has been rapidly developed and has derived a series of improved and extended algorithms, which have been applied in pattern recognition, image recognition, etc. Among the many improved algorithms, the technique of regulating the ratio of two penalty parameters according to the ratio of the sample quantities of the two classes has been widely accepted. However, the technique has not been verified in the way of rigorous mathematical proof. The experiments based on USPS sets in the study were designed to test the accuracy of the theory. The optimal parameters of the USPS sets were found through the grid-scanning method, which showed that the theory is not accurate in any case because there is absolutely no linear relationship between ratios of penalty parameters and sample sizes.
Hydrodynamic Lubrication of Partially Textured Gas Parallel Slider Bearings with Orientation Ellipse Dimples
Authors: Liu Fuxi , Li Zhanlong , Yang Chunjie , Wu Hongbao , Yin Huazhu , Jiang Shan
Published: December 2021

The hydrodynamic lubrication performance of partially textured gas parallel slider bearings with orientation ellipse dimples is investigated in this paper. By using the multigrid finite element method, the pressure distribution between a partially textured slider and a smooth slider is obtained. The geometric parameters of the ellipse dimples are optimized to maximize the average pressure under a given sliding speed. The numerical results show that geometric parameters such as orientation angle, depth, slender ratio, and area density have an important impact on hydrodynamic pressure. Besides, the effect of textured fraction on hydrodynamic pressure is investigated under a given sliding speed. It is observed that the optimum textured fraction for maximizing the average pressure is dependent on the sliding speed.
Breast Cancer Survivorship and Level of Institutional Involvement Utilizing Integrative Oncology
Authors: Crudup Terri , Li Linna , Dorr Jennifer Wright , Lawson Elizabeth , Stout Rachel , Niknam Pedram Vazifeh , Jones Judi , Steen Robert G. , Casner Susan , Lu Lynn L. , Wang Yi , Scott James , Zanine Shelby , Robertshaw Stacey , Broderick Gabriella , Singh Simarpreet , Lu Jingsong , Zhou Li , Palommella Vaishali , Harris Tye , Hanamirian Michael , Reddy Mula Shivani , Cowgill Bruce , Rice Jen , Nagaraja Avinash , Jonas Wayne
Published: December 2021

Objective. Integrative oncology is widely used by patients with breast cancer. This study aims to investigate the relationship between the survival outcomes of breast cancer patients and the level of involvement in integrative oncology at the institutions treating them. Methods. Claims-based data were used to find 4,815 newly diagnosed breast cancer patients treated between January 2013 and December 2014 for survival analysis. A scoring system was developed by asking oncologists about their institutions’ efforts to educate, support, and provide funding for 12 complementary and lifestyle approaches. Cohort analysis using two-tailed chi-square and a separate multivariate model using SMOTE and lasso regression were used. Nine variables across patient and institutional profiles were included. The model coefficients were exponentiated and presented as odds ratios. Results. 173 patients mapped to 103 institutions and 103 oncologists. The median patient age was 51, and 8% were metastatic. Institutions were scored for integrative oncology involvement and placed into four cohorts. Low-scoring institutions showed less effort to educate, support, and provide integrative therapies compared to others. The 5-year survival of patients in the low cohort was directionally but not significantly lower than others. In the multivariate model, a composite integrative oncology score was shown to increase 5-year survival odds three times for institutions in the low-mid cohort and 48% in the mid-high, compared to the low. Conclusion. Crossing the threshold beyond ‘low’ involvement in integrative oncology represents a new path to incremental survival benefit for many cancer patients. Entities invested in the survival of breast cancer patients should increase education, access, and funding for a core set of six therapies: nutrition counselling, exercise counselling, patient support groups, spiritual services, meditation, and psycho-oncology support.
Application of Data Mining in WITMED: Identification of Prognostic Genes in Oral Cancer
Authors: Liu Gang , Wang Wei , Qin He , Zhou Qingguo , Ma Jianbing , Zhou Xiaokang , Zhen Haiyan
Published: December 2021

In recent years, the booming development of big data, cloud computing, Internet of Things, and other technologies provides conditions for the popularization and application of smart city. The combination of big data and medical information produces the emerging field of WITMED (Wise Information Technology of Med). WITMED is essential for the prospering growth of smart cities, which assumed a high quality of medical service is the most challenging goal for the city government. In this paper, the main attention is paid to the method of targeted gene therapy, which provides a new method for the treatment of oral cancer in inhibiting the growth, differentiation, invasion, and metastasis of oral cancer cells; therefore, the physical and psychological adverse effects of surgery and chemotherapy on patients are reduced and the survival and prognosis of patients are improved. Targeted gene therapy methods need to select the appropriate gene; that is, data mining methods are used to analyze a large number of complex genetic data from smart cities to obtain appropriate genetic markers, which makes the effect of targeted gene therapy better, and also provide some reference for the research of oral cancer gene direction and provide some basis for clinical treatment.
Analysis and Modelling of Ship Manoeuvring Simulation in Landslide-Generated Waves
Authors: Yuan Peiyin , Zhao Yu
Published: December 2021

The geological conditions of the Three Gorges Reservoir Region are complex and changing, and large- and medium-sized landslides are widely distributed. When a high-speed moving landslide enters the water, the water is significantly disturbed, and a landslide-generated wave will be formed, which will spread along the upstream and downstream of the river, causing significant threats and destruction to the hydraulic structures and the navigation of ships. Based on the typical rock landslide parameters and fracture development, we establish a three-dimensional physics experimental model of the bending section of the landslide-generated wave in the Three Gorges Reservoir Region. This paper primarily studies the variation law of the first wave height of landslide-generated waves with the width, height, and water entry velocity of the landslide body and then provides an empirical formula for the first wave height of landslide-generated waves in the curved section of the Three Gorges Reservoir Region. The ship rolling motion equation in the landslide-generated water area is analysed and established systematically. Additionally, the ship manoeuvring motion model in the landslide-generated water area is built. This paper explains the variation characteristics of ship turning tracks at different sailing speeds and sailing positions and proposes a basis to determine the navigation safety of ships in this area, thus providing new theoretical and technical support for the risk assessment of navigation of ships in the reservoir area.
Simulation Research on Information-Sharing Value of Two-Level Supply Chain
Authors: Zhang Xiaheng , Lin Zekai , Xiao Lin
Published: December 2021

In the two-stage supply chain model, the incentive effect to the supplier’s sharing of demand information and performance evaluation and the effect of various parameters on the incentive effect of the supply chain are studied through a multiagent simulation model constructed for the purpose. It is found that the incentive coefficient of demand information-sharing degree, the number of selected suppliers, the order allocation coefficient, and the order proportion are positively related to the incentive effect of demand information sharing. So, the greater the demand information sharing is, the greater the impact of these parameters on the incentive effect is. Based on the demand information sharing, the supplier performance evaluation rules are shared, and when the actual evaluation rules are inconsistent with the supplier’s expectations, the incentive effect is further enhanced. Other parameters do not affect the incentive effect of demand information sharing and performance evaluation rule sharing.
A Comprehensive Survey on Sharding in Blockchains
Authors: Xi Jinwen , Zou Shihong , Xu Guoai , Guo Yanhui , Lu Yueming , Xu Jiuyun , Zhang Xuanwen
Published: December 2021

Blockchain technology has been widely used in many fields, such as smart cities, smart health care, and smart manufacturing, due to its anonymity, decentralization, and tamper resistance in peer-to-peer (P2P) networks. However, poor scalability has severely affected the widespread adoption of traditional blockchain technology in high-throughput and low-latency applications. Therefore, based on the three-layer architecture, this study presents a variety of solutions to improve the scalability of the blockchain. As the scale of the network expands, one of the most practical ways to achieve horizontal scalability is sharding, where the network is divided into multiple subnetworks to avoid repeated communication overhead, storage, and calculations. This study provides a systematic and comprehensive introduction to blockchain sharding, along with a detailed comparison and evaluation for primarily considered sharding mechanisms. We also provide the detailed calculations and then analyze the characteristics of existing solutions along with our insights.
Effects of Size, Section Pattern, and Material on the Tensile Performance of Filled Thin‐Walled Tubes
Authors: Gao Yue , Shao Fei , Xu Qian , Bai Linyue , Gao Lei , Ma Qingna , Shen Mei , Yan Xintong
Published: December 2021

The tensile performance of ductile tubes can be enhanced by the application of fillers. Research studies on the mechanical performance of filled tensile tubes have mainly focused on experiments and numerical simulations on concrete‐filled steel tube (CFST) components, while the effects of factors such as size, section pattern, and material of filled tensile tubes on their performance have rarely been studied. In this research, the effects of size, section pattern, and material on the tensile performance of filled tubes have been evaluated through theoretical studies, simulations, and experiments. The tensile strength reinforcement and deformation weakening coefficients of filled circular thin‐walled tubes corresponding to hollow tubes were theoretically deduced, and the influencing factors of the two were parametrically evaluated. Tensile performances of filled tubes with circular and square sections were compared with each other through numerical methods. In the current research, the circular section was optimized and prestressed circular hollow support section was proposed. Tensile fracture tests were performed on circular thin‐walled tubes made of six different materials to determine material effects on the tensile performance of these structures. It was also found that metallic materials with good ductility significantly enhanced the tensile performance, fracture toughness, and energy consumption of test components containing prestressed filler.
Serum Legumain Is Associated with Peripheral Artery Disease in Patients with Type 2 Diabetes
Authors: Wei Wen , Chen Shujin , Huang Jianqing , Tong Yan , Zhang Jushun , Qiu Xiuping , Zhang Wenrui , Chen Hangju , Huang Rong , Cai Jin , Tu Mei
Published: December 2021

Background. Legumain is related to carotid atherosclerotic plaques and may be a new biomarker of carotid atherosclerosis. However, the association between legumain and peripheral artery disease (PAD) of lower extremity has been less studied. This study is aimed at exploring the potential link between legumain and PAD in patients with type 2 diabetes mellitus (T2DM). Methods. A cross-sectional study was conducted on 483 hospitalized T2DM patients. The serum legumain level was measured by a sandwich enzyme-linked immunosorbent assay. PAD was evaluated by color Doppler sonography. The association between legumain and PAD was tested by logistic regression. The predictive power of legumain for PAD was evaluated with the receiver-operating-characteristic (ROC) curve. Results. Overall, 201 (41.6%) patients suffered from PAD. Patients with PAD had significantly higher serum legumain level than those without PAD [11.9 (6.3, 17.9) μg/L vs. 7.6 (3.2, 14.2) μg/L,

p
<
0.001

]. Logistic regression showed that a higher serum legumain level was independently associated with a greater risk of PAD in T2DM patients [adjusted odds ratio (aOR): 1.03; 95% confidence interval (CI): 1.01-1.06]. The area under the ROC curve was 0.634 (95% CI, 0.585 to 0.684). Conclusion. High serum legumain level was significantly correlated with an increased risk of PAD in T2DM patients.
Temporal Weighted Averaging for Asynchronous Federated Intrusion Detection Systems
Authors: Agrawal Shaashwat , Chowdhuri Aditi , Sarkar Sagnik , Selvanambi Ramani , Gadekallu Thippa Reddy
Published: December 2021

Federated learning (FL) is an emerging subdomain of machine learning (ML) in a distributed and heterogeneous setup. It provides efficient training architecture, sufficient data, and privacy‐preserving communication for boosting the performance and feasibility of ML algorithms. In this environment, the resultant global model produced by averaging various trained client models is vital. During each round of FL, model parameters are transferred from each client device to the server while the server waits for all models before it can average them. In a realistic scenario, waiting for all clients to communicate their model parameters, where client models are trained on low‐power Internet of Things (IoT) devices, can result in a deadlock. In this paper, a novel temporal model averaging algorithm is proposed for asynchronous federated learning (AFL). Our approach uses a dynamic expectation function that computes the number of client models expected in each round and a weighted averaging algorithm for continuous modification of the global model. This ensures that the federated architecture is not stuck in a deadlock all the while increasing the throughput of the server and clients. To implicate the importance of asynchronicity in cybersecurity, the proposed algorithm is tested using NSL‐KDD intrusion detection system datasets. The performance accuracy of the global model is about 99.5% on the dataset, outperforming traditional FL models in anomaly detection. In terms of asynchronicity, we get an increased throughput of almost 10.17% for every 30 timesteps.
Research on a Critical Hydraulic Gradient of Piping in Noncohesive Soils
Authors: Zhang Can-Hong , Ji En-Yue , Wang Bao-Tian
Published: December 2021

The critical hydraulic gradient of cohesive soil is an important condition for judging soil piping. For force analysis of movable particles in pore channels of soil, this study proposes to consider the influence of surrounding particles on the drag force of movable particles by water flow. According to the principle of relative motion, considering the interaction force between moving objects in still water, the value of the drag force of water flow that is affected by surrounding particles is calculated, to derive the method of the critical hydraulic gradient. This calculation method is suitable for the results of previous piping tests, and the method is accurate and concise.
Multivariate and Online Prediction of Closing Price Using Kernel Adaptive Filtering
Authors: Mishra Shambhavi , Ahmed Tanveer , Mishra Vipul , Kaur Manjit , Martinetz Thomas , Jain Amit Kumar , Alshazly Hammam
Published: December 2021

This paper proposes a multivariate and online prediction of stock prices via the paradigm of kernel adaptive filtering (KAF). The prediction of stock prices in traditional classification and regression problems needs independent and batch‐oriented nature of training. In this article, we challenge this existing notion of the literature and propose an online kernel adaptive filtering‐based approach to predict stock prices. We experiment with ten different KAF algorithms to analyze stocks’ performance and show the efficacy of the work presented here. In addition to this, and in contrast to the current literature, we look at granular level data. The experiments are performed with quotes gathered at the window of one minute, five minutes, ten minutes, fifteen minutes, twenty minutes, thirty minutes, one hour, and one day. These time windows represent some of the common windows frequently used by traders. The proposed framework is tested on 50 different stocks making up the Indian stock index: Nifty‐50. The experimental results show that online learning and KAF is not only a good option, but practically speaking, they can be deployed in high‐frequency trading as well.
Machine Learning-Based Detection of Spam Emails
Authors: Siddique Zeeshan Bin , Khan Mudassar Ali , Din Ikram Ud , Almogren Ahmad , Mohiuddin Irfan , Nazir Shah
Published: December 2021

Social communication has evolved, with e-mail still being one of the most common communication means, used for both formal and informal ways. With many languages being digitized for the electronic world, the use of English is still abundant. However, various native languages of different regions are emerging gradually. The Urdu language, coming from South Asia, mostly Pakistan, is also getting its pace as a medium for communications used in social media platforms, websites, and emails. With the increased usage of emails, Urdu’s number and variety of spam content also increase. Spam emails are inappropriate and unwanted messages usually sent to breach security. These spam emails include phishing URLs, advertisements, commercial segments, and a large number of indiscriminate recipients. Thus, such content is always a hazard for the user, and many studies have taken place to detect such spam content. However, there is a dire need to detect spam emails, which have content written in Urdu language. The proposed study utilizes the existing machine learning algorithms including Naive Bayes, CNN, SVM, and LSTM to detect and categorize e-mail content. According to our findings, the LSTM model outperforms other models with a highest score of 98.4% accuracy.
Characterizing Selected Sorghum Grain Varieties and Evaluating the Suitability of Their Malt Extracts for Cultivating Microbial Biomass
Authors: Byakika Stellah , Mukisa Ivan Muzira , Byaruhanga Yusuf Byenkya
Published: December 2021

Microbial biomass is cultivated for different technological applications including food processing, medicine, waste management, and research. The conventional growth media used are generally expensive thus necessitating the development of more affordable alternatives. In this study, four sorghum grain varieties, SESO 1, SESO 3, Epuripur, and Eyera, and their malt extracts were characterized which is aimed at determining their suitability for growing microbial biomass. The varieties had kernel length, kernel width, kernel thickness, and thousand kernel weigh equivalent to 3.8-4.3 mm, 3.2-4.5 mm, 2.4-2.8 mm, and 12.4-20.2 g, respectively. SESO 1 and Epuripur had corneous endosperm textures whereas those of SESO 3 and Eyera were intermediate and floury, respectively. Varieties had

germinative
 
energies
>
90

% and

total
 
defects
<
8

%. SESO 3 had the highest (

p
<
0.05

) crude protein (

10.8
±
0.3

%) and dietary fiber (

22.5
±
0.4

%) whereas Epuripur had the highest (

p
<
0.05

) starch (

81.6
±
0.0

%) and crude fat (

2.9
±
0.1

%). There was no significant difference (

p
>
0.05

) in the ash contents (

2.1
±
0.0

%). The total sugars, free amino nitrogen, condensed tannins, and pH of the malt extracts were 106-116 g/L, 70-78 mg/L, 0.1-0.6 mg/mL, and 5.5-5.7, respectively. The composition of the sorghum malt extracts suggests their potential for use in cultivating microbial biomass.
A Novel Approach of Label Construction for Predicting Remaining Useful Life of Machinery
Authors: Lin Hailong , Lei Zihao , Wen Guangrui , Tian Xiaojun , Huang Xin , Liu Jinsong , Zhou Haoxuan , Chen Xuefeng
Published: December 2021

Rolling bearings are key components of rotating machinery, and predicting the remaining useful life (RUL) is of great significance in practical industrial scenarios and is being increasingly studied. A precise and reliable remaining useful life prediction result provides valuable information for decision‐makers, which is essential to ensure the safety and reliability of mechanical systems. Generally, the RUL label is considered to be an ideal life curve, which is the benchmark for RUL prediction. However, the existing label construction methods make more use of expert experience and seldom mine knowledge from data and combine experience to assist in constructing a health index (HI). In this paper, a novel and simple approach of label construction is proposed for predicting the RUL accurately. More specifically, the degradation index of the multiscale frequency domain is first extracted. Furthermore, the fuzzy C‐means (FCM) algorithm is innovatively used to divide the degradation data into several stages to obtain the turning point of degradation. Then, a nonlinear degradation index, the RUL label with the turning point, was constructed based on principal component analysis (PCA). Finally, the recurrent neural network (RNN) is used for prediction and verification. In order to verify the effectiveness of the proposed approach, two different bearing lifecycle datasets are gathered and analyzed. The analysis result confirms that the proposed method is able to achieve a better performance, which outperforms some existing methods.
Optimizing Locations of Primary Schools in Rural Areas of China
Authors: Chen Yulong
Published: December 2021

Scientific location selection of schools is an important way to optimize the allocation of educational resources, improve the efficiency of operating schools, and realize the balanced development of education, especially in rural areas. Many studies have considered the location of schools, but most have omitted the impact of transportation network conditions and the time cost differences caused by different travel speeds under different road conditions. The object of this study is to minimize the total transportation costs for students, construction costs for new schools, and the construction and upgrading costs for roads on a traffic network with travel time uncertainty indicated by different travel time scenarios. A mixed‐integer programming model for this problem was proposed. Furthermore, a hybrid simulated annealing algorithm was used to solve the problem. Finally, a practical case study was used to illustrate the application of the proposed mathematical model. The results showed that the traffic network has an important influence on the optimization location of rural schools, and the improvement of traffic network conditions can greatly reduce the time required for students to travel to school.
Effects of Personality Characteristics of Different Genders and Quality of Life Analysis on Risk Factors for Suicide in Depressive Patients
Authors: Xu Xuebing , Jiang Jing , Bai Hongjuan , Tian Tao
Published: December 2021

Objective. The study was to explore the roles of personality characteristics of different genders and analyze the risk factors of quality of life (QOL) analysis in suicide among depressive patients. Methods. One hundred and eighty-six depressive patients from January 2018 to March 2019 in the Department of Psychiatry of our hospital were enrolled and divided into Groups A and B considering whether they had a suicidal tendency or not. Among them, 90 in Group A had a suicidal tendency and consisted of 42 males and 48 females, while 96 in Group B had no suicidal tendency and consisted of 44 males and 52 females. Forward and backward selection and then backward selection were performed on all the variables of gender characteristic factors and QOL factors that may cause suicide, on which stepwise regression was finally conducted. Next, univariate logistic regression analysis was first performed to select important variables from the related risk factors that may cause suicide, and then, the multivariate logistic regression model was used to select important independent risk factors. Results and Conclusion. The age of onset, degree of anxiety, moral support, positive mental attitude, and family independence were the independent risk factors that may cause a suicidal tendency for male depressive patients. The age of onset, degree of anxiety, negative life events, moral support, positive mental attitude, family intimacy, psychoticism, and neuroticism were the independent risk factors for female depressive patients. Physiological function, role physical, bodily pain, social function, and emotional role in QOL may be the independent risk factors for a suicidal tendency.
Regularized Multiframe Super-Resolution Image Reconstruction Using Linear and Nonlinear Filters
Authors: Khattab Mahmoud M. , Zeki Akram M. , Alwan Ali A. , Bouallegue Belgacem , Matter Safaa S. , Ahmed Abdelmoty M.
Published: December 2021

The primary goal of the multiframe super-resolution image reconstruction is to produce an image with a higher resolution by integrating information extracted from a set of corresponding images with low resolution, which is used in various fields. However, super-resolution image reconstruction approaches are typically affected by annoying restorative artifacts, including blurring, noise, and staircasing effect. Accordingly, it is always difficult to balance between smoothness and edge preservation. In this paper, we intend to enhance the efficiency of multiframe super-resolution image reconstruction in order to optimize both analysis and human interpretation processes by improving the pictorial information and enhancing the automatic machine perception. As a result, we propose new approaches that firstly rely on estimating the initial high-resolution image through preprocessing of the reference low-resolution image based on median, mean, Lucy-Richardson, and Wiener filters. This preprocessing stage is used to overcome the degradation present in the reference low-resolution image, which is a suitable kernel for producing the initial high-resolution image to be used in the reconstruction phase of the final image. Then, L2 norm is employed for the data-fidelity term to minimize the residual among the predicted high-resolution image and the observed low-resolution images. Finally, bilateral total variation prior model is utilized to restrict the minimization function to a stable state of the generated HR image. The experimental results of the synthetic data indicate that the proposed approaches have enhanced efficiency visually and quantitatively compared to other existing approaches.
Study on Cold Chain Transportation Model of Fruit and Vegetable Fresh-Keeping in Low-Temperature Cold Storage Environment
Authors: Jiao Xiaolong , Xu Wen , Duan Lintong
Published: December 2021

Due to the limitation of later stage intelligent algorithms, the fruit and vegetable fresh-keeping cold chain transportation scheme did not meet the expectation and could not achieve the dual objectives of the shortest time and the lowest consumption at the same time. In order to solve the above problems, a cold chain transportation model of fruit and vegetable fresh-keeping in a low-temperature cold storage environment is proposed. The model is based on the topology of the cold chain transportation network. By setting the assumptions of the fruit and vegetable fresh-keeping cold chain transportation model, the objective model is composed of three parts: vehicle power fuel consumption cost, cold chain transportation refrigeration cost, and total fruit and vegetable loss cost. Under six constraints, the improved ant colony algorithm is used to find the optimal fruit and vegetable fresh-keeping cold chain transportation route. The experimental results show that compared with the methods based on ALNS, genetic algorithm, and quantum bacterial foraging optimization algorithm, the research method can bring the best comprehensive benefit by accomplishing the fruit and vegetable transportation task in the shortest time at the lowest cost, and the research goal is thus achieved.
Efficacy and Safety of Afatinib in the Treatment of Advanced Non-Small-Cell Lung Cancer with EGFR Mutations: A Meta-Analysis of Real-World Evidence
Authors: Zhang Lemeng , Luo Yongzhong , Chen Jianhua , Cheng Tianli , Yang Hua , Pan Changqie , Li Haitao , Jiang Zhou
Published: December 2021

Introduction. The purpose of this study was to explore the efficacy and safety of afatinib in advanced non-small-cell lung cancer (NSCLC) patients with epidermal growth factor receptor (EGFR) mutations based on real-world evidence. Materials and Methods. Eligible real-world studies were identified from PubMed, Cochrane Library, and Embase. Cochrane guidelines were used to assess the quality of included studies. Cochran’s Q test and I2 statistics were used for the heterogeneity analysis. Results. Twenty-five studies were included in this meta-analysis; nine studies were included in the qualitative descriptive analysis. The summarized disease control rate (DCR) was 87.6% (81.5%, 92.7%), and the overall response rate (ORR) was 58.9% (48.8%, 68.7%). The pooled median progression-free survival (PFS) was 12.4 (10.3, 14.5) months, mean time to failure (TTF) was 15.4 (13.6, 17.2) months, and median overall survival (OS) was 31.6 (26.7, 36.5) months. The total incidences of adverse events (AEs) for skin rashes, diarrhea, paronychia, and mucositis were 71.4% (64.4%, 77.9%), 70.4% (60.1%, 79.8%), 52.1% (41.9, 62.3%), and 36.5% (29.5%, 43.8%), respectively. The incidences of severe adverse events (SAEs, Grade ≥3) for diarrhea, skin rashes, paronychia, and mucositis were 9.7% (6.8%, 13.1%), 5.8% (4.5%, 7.2%), 3.8% (2.0%, 6.2%), and 2.1% (1.0%, 3.6%), respectively. Differences in PFS and OS between the afatinib non-full-dose (<40 mg) and full-dose (>40 mg) groups were not significant (P>0.05). However, the ORR in the full-dose group was 78.5% (66.7%, 88.4%), which was significantly higher than that in the non-full-dose group (67.8% [56.8%, 77.9%]). Conclusion. The efficacy and safety of afatinib has been confirmed by real-world evidence in advanced NSCLC with EGFR mutation, consistent with randomized controlled trial results. In real-world setting, tolerability-guided dose adjustment might not affect the afatinib efficacy.
βLact‐Pred: A Predictor Developed for Identification of Beta‐Lactamases Using Statistical Moments and PseAAC via 5‐Step Rule
Authors: Ashraf Muhammad Adeel , Khan Yaser Daanial , Shoaib Bilal , Khan Muhammad Adnan , Khan Faheem , Whangbo T.
Published: December 2021

Beta‐lactamase (β‐lactamase) produced by different bacteria confers resistance against β‐lactam‐containing drugs. The gene encoding β‐lactamase is plasmid‐borne and can easily be transferred from one bacterium to another during conjugation. By such transformations, the recipient also acquires resistance against the drugs of the β‐lactam family. β‐Lactam antibiotics play a vital significance in clinical treatment of disastrous diseases like soft tissue infections, gonorrhoea, skin infections, urinary tract infections, and bronchitis. Herein, we report a prediction classifier named as βLact‐Pred for the identification of β‐lactamase proteins. The computational model uses the primary amino acid sequence structure as its input. Various metrics are derived from the primary structure to form a feature vector. Experimentally determined data of positive and negative beta‐lactamases are collected and transformed into feature vectors. An operating algorithm based on the artificial neural network is used by integrating the position relative features and sequence statistical moments in PseAAC for training the neural networks. The results for the proposed computational model were validated by employing numerous types of approach, i.e., self‐consistency testing, jackknife testing, cross‐validation, and independent testing. The overall accuracy of the predictor for self‐consistency, jackknife testing, cross‐validation, and independent testing presents 99.76%, 96.07%, 94.20%, and 91.65%, respectively, for the proposed model. Stupendous experimental results demonstrated that the proposed predictor “βLact‐Pred” has surpassed results from the existing methods.
A Clinical Retrospective Study of Recurrent Painful Ophthalmoplegic Neuropathy in Adults
Authors: Li Cheng , Huang Xinyi , Tan Xiao , Fang Yannan , Yan Jianhua
Published: December 2021

Introduction. Recurrent painful ophthalmoplegic neuropathy (RPON) is quite rare and usually occurs in children. In this report, we describe the clinical features, diagnosis, and treatment of RPON in adults. Methods. A retrospective review was conducted of all RPON cases seen and treated at the Zhongshan Ophthalmic Center of Sun Yat-sen University and the Department of Neurology of the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China, over the period from January 2016 to May 2020. Results. A total of 8 patients (3 males and 5 females) with a mean age of 42.9 years (range: 23–64 years) met the diagnostic criteria of RPON. Headaches were present prior to the onset of ophthalmoplegic neuropathy in 50% of these patients, while in the remaining 50%, headaches occurred simultaneously with eye symptoms. The degree of these headaches was described as being mild or moderate. Abnormalities involving cranial nerve III were the most frequently reported pathologies (6 cases, 75%), followed by nerve VI (4 cases, 50%) and then nerve IV (1 case, 12.5%) (more than one nerve was affected in some cases). Following either with glucocorticoid treatment or with observation only, symptoms and signs within all 8 patients completely dissipated within 3–28 days. Conclusions. All adult cases of RPON along with their clinical features as reported here were similar to those of children.
Risk of Bleeding after Colorectal Endoscopic Resection in Patients with Continued Warfarin Use Compared to Heparin Replacement: A Propensity Score Matching Analysis
Authors: Inagaki Katsuaki , Yamashita Ken , Oka Shiro , Tanino Fumiaki , Yamamoto Noriko , Kamigaichi Yuki , Tamari Hirosato , Shimohara Yasutsugu , Nishimura Tomoyuki , Okamoto Yuki , Tanaka Hidenori , Kotachi Takahiro , Yuge Ryo , Urabe Yuji , Kitadai Yasuhiko , Yoshimura Kenichi , Tanaka Shinji
Published: December 2021

The Japan Gastroenterological Endoscopy Society (JGES) guidelines recommend continued warfarin treatment during gastroenterological endoscopic procedures with a high risk of bleeding as an alternative to heparin replacement in patients on warfarin therapy. However, there is insufficient evidence to support the use of warfarin in colorectal endoscopic resection (ER). The present study is aimed at verifying the risk of bleeding after ER for colorectal neoplasia (CRN) in patients with continued warfarin use. This was a single-center retrospective cohort study using clinical records. We assessed 126 consecutive patients with 159 CRNs who underwent ER (endoscopic mucosal resection, 146 cases; endoscopic submucosal dissection, 13 cases) at Hiroshima University Hospital between January 2014 and December 2019. Patients were divided into two groups: the heparin replacement group (79 patients with 79 CRNs) and the continued warfarin group (47 patients with 80 CRNs). One-to-one propensity score matching was performed to compare the bleeding rate after ER between the groups. The rate of bleeding after ER was significantly higher in the heparin replacement group than in the continued warfarin group for both before (10.1% vs. 1.3%, respectively;

P
=
0.0178

) and after (11.9% vs. 0%, respectively;

P
=
0.0211

) propensity score matching. None of the patients experienced thromboembolic events during the perioperative period. The risk of bleeding after colorectal ER was significantly lower in patients with continued warfarin use than in those with heparin replacement. Our data supports the recommendations of the latest JGES guidelines for patients receiving warfarin therapy.