bluuebunny/crossref_metadata_2025 huggingface dataset:
The Association between Long Noncoding RNA over Expression and Poor Prognosis of Liver Cancer: A Meta-Analysis
Authors: Wang Leiqing , Sheng Junzhi , Zhang Haojie , Xie Baoyuan , Xiang Linbiao , Liu Dong , Zhang Xinyuan , Zhang Peihao , Liu Jinjin
Published: November 2021

Background. Long noncoding RNA (lncRNA) is considered to be a mediator of carcinogenesis, which may be associated with liver cancer survival. However, the relationship remains inconclusive. Meta-analysis was conducted to analytically review the association between the lncRNA expression level and clinicopathological characteristics and prognostic value of hepatic carcinoma. Materials and Methods. Four databases including Embase, PubMed, Web of Science, and the Cochrane Library were searched to collect studies about the relation between lncRNA overexpression and prognosis of liver cancer, dating from the earliest records of these databases to March 2021. Two researchers independently screened the data and literature to perform a stringent evaluation of the quality of material involved in the study. Meta-analysis was performed by Stata 16.0 software on 42 case-control studies with 6293 samples. Results. The outcomes of meta-analysis are presented as follows: lncRNA overexpression patients had later TNM stage (OR = 0.36, 95% CI (0.31, 0.41),P < 0.001), lower histological grade (OR = 0.56, 95%CI (0.49, 0.65),P < 0.001), more vascular invasion (OR = 2.02, 95% CI (1.74, 2.35),P < 0.001), bigger tumor size (OR = 2.28, 95% CI (2.00, 2.60),P < 0.001), more severe liver cirrhosis (OR = 1.39, 95% CI(0.1.16, 1.66),P < 0.001), more likely to metastasize (OR = 1.80, 95%CI(1.49, 2.18),P < 0.001), and more tumor numbers (OR = 0.72, 95% CI (0.62, 0.84),P < 0.05). lncRNA over expression patients had shorter OS (HR = 2.32, 95 CI% (2.08, 2.59),P < 0.01, RFS (HR = 2.19, 95 CI% (1.72, 2.78),P < 0.01), and DFS (HR = 2.01, 95 CI% (1.57, 2.57),P < 0.01). Conclusions. Overexposure of lncRNA is a poor prognostic feature for patients with hepatic carcinoma. The scope of our study was limited because of a lack of relevant research and the poor representativeness and varying quality of the studies involved in the current meta-analysis. Our conclusion still requires higher studies for further validation. This trial is clinically registered with CRD4201920620.
A Coordinated and Optimized Mechanism of Artificial Intelligence for Student Management by College Counselors Based on Big Data
Authors: Yang Zhen , Talha Muhammad
Published: November 2021

The purpose of this article is to perform in-depth research and analysis on the artificial intelligence coordination and optimization mechanism of college counseling student management using big data technology. This study places the collaborative ideological and political work of colleges and universities in the context of big data, and by analyzing its basic connotation and changes in the real situation, it explores the development progression of colleges and universities making full use of big data resources to cultivate a collaborative education model, which is conducive to promoting colleges and universities to cultivate a whole staff, whole process, and all-round accurate ideological education and value-led services and to shape excellent young college students with comprehensive growth. The first is to scientifically build a multilevel linked big data management platform for counselor professionalization construction, plan the technical architecture of the organizational platform, build a cloud database of counselor career files, and extract valuable information and data from the organizational activities at the macrolevel and personal activities at the microlevel with counselor professionalization construction activities; the second is to realize the integrated application of information resources for counselor team construction. The second is to realize the integrated application of counselor team construction information resources, visualise and accurately analyze and evaluate the counselor group’s focus on career development and individual counselors’ feedback on career capacity construction, and improve the overall construction, personalized education management level, and self-improvement development ability. Fourth, in the professionalization of counselors, attention should be paid to the scientific selection and prevention of risks of big data application, ensuring the authenticity and reliability of data and leakage prevention and control, etc.
Predicting Joint Effects on CubeSats to Enhance Internet of Things in GCC Region Using Artificial Neural Network
Authors: Almalki Faris A. , Ben Othman Soufiene
Published: November 2021

Satellite telecommunication systems promise to bridge digital gaps and deliver wireless communication services to any corner of the world. However, despite satellites’ global connectivity and wide footprint, still atmospheric and dust impairments are open challenges that face satellite systems, especially at high-frequency bands in arid and semiarid regions. Therefore, this paper aims to predict joint effects of atmospheric and dust attenuations in Gulf Cooperation Council (GCC) countries on CubeSat communications using Artificial Neural Network (ANN). The prediction model has been carried out using a massive Multiple-Input Multiple-Output (MIMO) antenna payload at K-frequency Bands. Consider these joint effects have positive relations in calculating satellites link margin, which leads to obtaining efficient communication system, delivering better quality of service (QoS), and enhancing Internet of Things (IoT) connectivity, or even Internet of Space Things (IoST). Predicated results infer that the ANN attenuation predictions, along with the 5G MIMO antenna on-board the CubeSat, offer much promise channel model for satellite communications, which in turn leads to not only supporting IoT connectivity but also reducing power consumption, thus enhancing lifetime of CubeSat. Also, this study can provide a reference for CubeSat engineers to guarantee large-capacity communication.
A Secure and Efficient Image Transmission Scheme Based on Two Chaotic Maps
Authors: Feng Wei , Zhang Jing , Qin Zhentao
Published: November 2021

The application of multimedia sensors is widespread, and people need to transmit images more securely and efficiently. In this paper, an image transmission scheme based on two chaotic maps is proposed. The proposed scheme consists of two parts, secure image transmission between sensor nodes and sink nodes (SIT‐SS) and secure image transmission between sensor nodes and receivers (SIT‐SR). For resource‐constrained environments, SIT‐SS utilizes Tent‐Logistic Map (TLM) to generate chaotic sequences and adopts TLM‐Driven permutation and transformation to confuse image pixels. Then the cipher image is obtained through TLM‐Driven two‐dimensional compressed sensing. Compared with existing schemes, the secret key design of SIT‐SS is more reasonable and requires fewer hardware resources. When sampling ratio is greater than 0.6, its image reconstruction quality has obvious advantages. For environments with huge security threats, SIT‐SR adopts dynamic permutation and confusion based on discrete logarithms to confuse the image and exploits dynamic diffusion based on discrete logarithms to generate final cipher image. Similarly, compared with some existing schemes, the design of SIT‐SR is more practical, and the statistical characteristics of the cipher image are better. Finally, extensive simulation tests confirm the superiority of the proposed scheme.
Image Recognition Technology with Its Application in Defect Detection and Diagnosis Analysis of Substation Equipment
Authors: Luo Long , Ma Rukuo , Li Yuan , Yang Fangnan , Qiu Zhanfei
Published: November 2021

Detection of substation equipment can promptly and effectively discover equipment overheating defects and prevent equipment failures. Traditional manual diagnosis methods are difficult to deal with the massive infrared images generated by the autonomous inspection of substation robots and drones. At present, most of the infrared image defect recognition is based on traditional machine learning algorithms, with low recognition accuracy and poor generalization capability. Therefore, this paper develops a method for identifying infrared defects of substation equipment based on the improvement of traditional ones. First, based on the Faster RCNN, target detection is performed on 6 types of substation equipment including bushings, insulators, wires, voltage transformers, lightning rods, and circuit breakers to achieve precise positioning of the equipment. Afterwards, different classes are identified based on the sparse representation-based classification (SRC), so the actual label of the input sample can be obtained. Finally, based on the temperature threshold discriminant algorithm, defects are identified in the equipment area. The measured infrared images are used for experiments. The average detection accuracy achieved by the proposed method for the 6 types of equipment reaches 92.34%. The recognition rate of different types of equipment is 98.57%, and the defect recognition accuracy reaches 88.75%. The experimental results show the effectiveness and accuracy of the proposed method.
Evaluation of the Efficacy of Budesonide Combined with Pulmonary Surfactants on the Neonatal Respiratory Distress Syndrome by Pulmonary Ultrasonography
Authors: Zhang Chuanlong
Published: November 2021

Objective. This study aimed to investigate the value of lung ultrasound images in evaluating the efficacy of budesonide combined with pulmonary surfactant (PS) in the treatment of neonatal respiratory distress syndrome (NRDS) in premature infants. Methods. 76 NRDS premature infants admitted to the hospital were randomly divided into experimental group and control group, with 38 children in each group. The premature infants in control group underwent PS, and those in experimental group underwent budesonide combined with PS. After treatment, lung ultrasound imaging was used to evaluate the curative effect, and X-ray results were used as a reference. The changes in clinical signs of two groups were detected, and the pulmonary ultrasound was used to evaluate the clinical efficacy of two groups. The changes in the lung ultrasound score (LUS) and arterial blood gas (ABG) indexes of two groups were compared before and after treatment. Results. LUS and improvement of patients of experimental group were obviously higher than those of the control group after treatment. LUS of experimental group was 12.1 ± 3.7, and that of control group was 18.2 ± 2.3, respectively. The differences were statistically significant (

P

 < 0.05). The arterial partial oxygen pressure (PaO2) and oxygenation index (PaO2/FiO2) levels of two groups of patients increased dramatically after treatment. PaO2 and PaO2/FiO2 levels of experimental group were 65.59 ± 12.46 mmHg and 112.57 ± 19.3 mmHg, and those of control group were 45.12 ± 11.21 mmHg and 101.28 ± 21.36 mmHg, respectively. However, arterial partial pressure of carbon dioxide (PaCO2) level was significantly decreased in two groups after treatment. PaCO2 level of experimental group was 40.24 ± 8.92 mmHg, and that of control group was 41.22 ± 9.24 mmHg, respectively (

P

 < 0.05). The diagnostic accuracy of lung ultrasound images in two groups was 95.3% and 96.2%, respectively. Conclusion. Pulmonary ultrasonography showed a high diagnostic accuracy in evaluating the efficacy of budesonide combined with PS in the treatment of NRDS in premature infants. It can evaluate the cardiopulmonary function of premature infants with NRDS and effectively improve the respiratory status of premature infants. In conclusion, this study provided some reference value for upgrading the clinical treatment of NRDS in premature infants.
Deepfake Detection Method Based on Cross-Domain Fusion
Authors: Sun Fang , Zhang Niuniu , Xu Pan , Song Zengren
Published: November 2021

In recent years, despite its wide use in various fields, deepfake has been abused to generate hazardous contents such as fake movies, rumors, and fake news by manipulating or replacing facial information of the original sources and, thus, exerts huge security threats to the society. Facing the continuous evolution of deepfake, research on active detection and prevention technology becomes particularly important. In this paper, we propose a new deepfake detection method based on cross-domain fusion, which, on the basis of traditional spatial domain features, realizes the fusion of cross-domain image features by introducing edge geometric features of the frequency domain and, therefore, achieves considerable improvements on classification accuracy. Further evaluations of this method have been performed on publicly deepfake datasets, and the results show that our method is effective particularly on the Meso-4 DeepFake Database.
A Design Method for the Roadside Clear Zone Based on Accident Simulation Analysis
Authors: Cheng Rui , Pan Ye , Wang Tao
Published: November 2021

In order to improve the safety design of roadside areas and reduce the loss of roadside accidents, this paper uses PC-Crash software to perform an accident simulation analysis. By recording the track of the vehicle after entering the roadside, the recommended widths of the roadside clear zone for different operating speeds and horizontal curve radii in straight and curved sections are given. According to our previous research data, the conditions for setting the roadside clear zone are proposed. Finally, based on a cost-benefit ratio analysis, a comprehensive risk index method is adopted to evaluate the social stability risk of the project and conduct research on the design method of the roadside clear zone. The results show that the width of the roadside clear zone has an exponential relation with the departure speed and a power relation with the horizontal curve radius. The research results realize the accurate calculation of the roadside clear zone width and fill in the gaps of the relevant specifications and guidelines in the setting conditions of the roadside clear zone.
Study on the Applicability of Neutron Radiation Damage Method Used for High-Temperature Superconducting Tape Based on Geant4 and SRIM
Authors: Zheng Ying , Zheng Jinxing , Wang Xudong
Published: November 2021

High-temperature superconducting material is a promising candidate to fabricate superconducting magnet for magnetic confinement fusion reactors. The DPA number of the 1 µm thick superconducting layer in a high temperature superconducting tape under neutron irradiation needs to be calculated to predict the property changes. The DPA cross sections, which ignore the spatial distribution of vacancies caused by PKAs, are commonly used to obtain the results of the damage energy and DPA. However, for geometric models with the thickness as small as 1 µm, the energy and angular distribution of PKAs reveal that a significant number of PKAs with relatively high energy tend to scatter forward and cross the boundary of model, so the thickness of model has the potential to affect the number of displaced atoms. In this paper, we developed a method based on Geant4 and SRIM to evaluate the deviation of the traditional analytic method caused by the thickness. Geant4 is used to obtain the location, direction, and energy of PKAs, while SRIM is used to track every PKA and obtain damage energy and the number of displaced atoms. The radiation damage calculation of simple thin plate models with different thicknesses and the tape model are conducted with the neutron energies from 1 to 14 MeV. The results show that PKAs need to be tracked continuously for models with thickness less than 10 µm and the deviation of the analytic formulas increases rapidly with the decrease of thickness. For the superconducting layer composed of four different elements in the tape, the deviation also depends on the proportion of each atomic species and the neutron-atom interaction cross sections under different incident neutron energy.
Mitigation of Iron Irradiation‐Induced Genotoxicity and Genomic Instability by Postexposure Dietary Restriction in Mice
Authors: Wang Bing , Katsube Takanori , Tanaka Kaoru , Murakami Masahiro , Nenoi Mitsuru
Published: November 2021

Background and Purpose. Postexposure onset of dietary restriction (DR) is expected to provide therapeutic nutritional approaches to reduce health risk from exposure to ionizing radiation (IR) due to such as manned space exploration, radiotherapy, or nuclear accidents as IR could alleviate radiocarcinogenesis in animal models. However, the underlying mechanisms remain largely unknown. This study is aimed at investigating the effect from postexposure onset of DR on genotoxicity and genomic instability (GI) induced by total body irradiation (TBI) in mice. Materials and Methods. Mice were exposed to 2.0 Gy of accelerated iron particles with an initial energy of 500 MeV/nucleon and a linear energy transfer (LET) value of about 200 keV/μm. After TBI, mice were either allowed to free access to a standard laboratory chow or treated under DR (25% cut in diet). Using micronucleus frequency (MNF) in bone marrow erythrocytes, induction of acute genotoxicity and GI in the hematopoietic system was, respectively, determined 1 and 2 months after TBI. Results and Conclusions. TBI alone caused a significant increase in MNF while DR alone did not markedly influence the MNF. DR induced a significant decrease in MNF compared to the treatment by TBI alone. Results demonstrated that postexposure onset of DR could relieve the elevated MNF induced by TBI with high‐LET iron particles. These findings indicated that reduction in acute genotoxicity and late GI may be at least a part of the mechanisms underlying decreased radiocarcinogenesis by DR.
Healthcare Data-Based Prediction Algorithm for Potential Knee Joint Injury of Football Players
Authors: Yu Yue , Ye Zi
Published: November 2021

It is important to predict the potential harm to the knee joint in order to prevent football players from inflicting numerous injuries to the knee during activity. Numerous professionals have been drawn to this subject, and many viable prediction systems have been developed. Prediction of potential knee joint injury is critical to effectively avoid knee joint injury during exercise. The current prediction algorithms are mainly implemented through expert interviews, medical reports, and historical documents. The algorithms have problems with low prediction accuracy or precision values. There is a need to understand more knee injury factors and improve the prediction accuracy; hence, the intelligent prediction algorithm for potential injury of knee joints of football players is proposed in this paper. Firstly, the characteristics of the knee joint injury and the injury factors of the football players are gathered and analyzed. Then, the damage is predicted by the similarity measurement. The experimental results show that the proposed algorithm has higher prediction accuracy and shorter time. According to the findings of a survey that collected healthcare data, several key factors contribute to football knee injuries. To a degree, this algorithm can predict the likelihood of a football player’s knee injury.
Artificial Intelligence Algorithm-Based Analysis of Ultrasonic Imaging Features for Diagnosis of Pregnancy Complicated with Brain Tumor
Authors: Wu Lin , Wei Donghui , Yang Ning , Lei Hong , Wang Yun
Published: November 2021

This research was to explore the accuracy of ultrasonic diagnosis based on artificial intelligence algorithm in the diagnosis of pregnancy complicated with brain tumors. In this study, 18 patients with pregnancy complicated with brain tumor confirmed by pathology were selected as the research object. Ultrasound contrast based on artificial bee colony algorithm was performed and diagnosed by experienced clinicians. Ultrasonic image will be reconstructed by artificial bee colony algorithm to improve its image display ability. The pathological diagnosis will be handed over to the physiological pathology laboratory of the hospital for diagnosis. The doctor’s ultrasonic diagnosis results were compared with the pathological diagnosis stage results of patients, and the results were analyzed by statistical analysis to evaluate its diagnostic value. The comparison results showed that the number and classification of benign tumors were the same, while in malignant tumors, the number diagnosis was the same, but there was one patient with diagnostic error in classification. One case of mixed glial neuron tumor was diagnosed as glial neuron tumor, and the diagnostic accuracy was 94.44% and the K value was 0.988. The diagnostic results of the two were in excellent agreement. The results show that, in the ultrasonic image diagnosis of patients with brain tumors during pregnancy based on artificial intelligence algorithm, most of them are benign and have obvious symptoms. Ultrasound has a good diagnostic accuracy and can be popularized in clinical diagnosis. The results can provide experimental data for the clinical application of ultrasonic image feature analysis based on artificial intelligence as the diagnosis of pregnancy complicated with brain tumors.
Continuous Use Behavior of Knowledge Payment Platform Based on Edge Computing under Mobile Information System
Authors: Huo Hong , Li Quanxi
Published: November 2021

From 2015 to the end of 2016, the Internet set off a wave of payment for knowledge. Pay-for-knowledge platforms such as Fenda, iGet, and Qianliao went online quickly, and platforms such as Himalaya FM, Zhihu, and Qingting FM gathered to launch paid columns. The number of users increased rapidly, and payment for knowledge was considered to have reached the trend of development. This article aims to study the introduction of edge computing in the mobile information system into the existence and inevitability of the knowledge payment platform; analyze the advantages, dilemmas, and optimization paths of the knowledge payment platform; and try to provide a theoretical reference for promoting its development. This article puts forward an explanation of the related content of mobile edge computing and RFID technology overview, using comparative experiment and behavior analysis methods. The experimental results show that there are 98 people under the age of 18 in the questionnaire, accounting for 19.1% of the total, 201 people aged 18–29, accounting for 39.1% of the total, 142 people aged 30–39, accounting for 27.6% of the total, and 73 people over 40 years old, accounting for 14.2% of the total number. It can be seen from the data that the sample age is mainly concentrated in the 18–29 years old, followed by the 30–39 years old; the sample age is biased towards young people. It has well completed the continuous use behavior analysis of the knowledge payment platform based on edge computing under the mobile information system.
Role of Nanofibers in Encapsulation of the Whole Cell
Authors: Sahu Sudarshan , Sharma Avinash , Mukherjee Soham , Kumar Deepak , Sen Fatih , Nagraik Rupak , Kumar Avvaru Praveen
Published: November 2021

In the field of biomaterial research, the electrospinning device is now used to manufacture nanofibers that can be used to encapsulate whole microorganisms such as bacterial cells, funguses, viruses, and even spores. The nanofiber encapsulated cells will have greater significance in the coming future because of their wide variety of applications in various fields. Nanofibers act as microorganism reservoir systems that enhance their properties such as viability, controlled release of products, biomedical applications, and bioremediation. The effect of electrostatic forces on a droplet of liquid polymer or polymer solution is based on electrospinning. Electrospun nanofibers act as ideal native extracellular matrices for microorganisms and have also had a tremendous advantage in drug delivery systems where modern research is still underway. During electrospinning, nearly all microorganisms may be inserted into a polymer matrix that forms a composite nanofiber. The evolution in electrospinning technique over the past few decades has become promising. New ideas have been generated to enhance the techniques and improve the overall applications and properties of nanofibers. This technique has been transformed by the advent of the electrospinning machine. The electrospun nanofibers can be chemically characterized by a wide variety of procedures such as scanning electron microscopy (SEM), transmission electron microscopy (TEM), thermogravimetric analysis (TGA), X-ray diffraction (XRD), and Fourier-transform infrared spectroscopy (FTIR). Electrospinning has various applications, for example, in wastewater treatment, tissue engineering, food industry, drug delivery, agriculture, and cosmetics. Nanofiber encapsulation of microorganisms increased the shelf life of the microorganisms; the cells remain viable for months. It also helps in the control release of bacterial products. The present review demonstrates the role of nanofiber in the encapsulation of the whole cell.
Sympathetic Nerve Activity and Baroreflex are Strongly Altered in a Context of Severe Hypertension Using the Spontaneously Hypertensive Rat Model Associated with Chronic Reduction of Nitric Oxide
Authors: Vayssettes-Courchay Christine , Melka Jonathan , Philouze Clothilde , Harouki Najah
Published: November 2021

The aim of our study is to investigate the sympathetic output and baroreflex via renal sympathetic nerve activity (RSNA) recording in a model of severe hypertension which exhibits arterial, cardiac, and renal damages, the spontaneously hypertensive rat (SHR) under lowered NO bioavailability. SHR are treated from 18 to 20 weeks of age with a low dose of L-NAME, a NO synthase inhibitor, in drinking water (SHRLN) and compared to SHR and normotensive Wistar Kyoto (WKY) rats. After the two-week treatment, rats are anesthetized for RSNA, mean blood pressure (MBP), and heart rate (HR) recording. MBP is higher in SHR than in WKY and higher in SHRLN than in SHR. Compared to WKY, SHR displays an alteration in the baroreflex with a displacement of the sympathoinhibition curve to highest pressures; this displacement is greater in SHRLN rats. The bradycardic response is reduced in SHRLN compared to both SHR and WKY. In hypertensive rats, SHR and SHRLN, basal RSNA is modified, the maximal amplitude of burst is reduced, but minimal values are increased, indicating an increased basal RSNA with reduced bursting activity. The temporal correlation between RSNA and HR is preserved in SHR but altered in 10 SHRLN out of 10. The RSNA inhibition triggered by the Bezold–Jarisch reflex activation is not modified in hypertensive rats, SHR or SHRLN, in contrast to that triggered by the baroreflex. Histological analysis of the carotid bifurcation does not reveal any abnormality in SHRLN at the level of the carotid sinus. In conclusion, data indicate that the sympathetic outflow is altered in SHRLN with a strong reduction of the baroreflex sympathoinhibition and suggest that its central pathway is not involved. These additional results on SHRLN also confirm the usefulness of this model of severe hypertension with multiple target organ damages.
DAP10 Predicted the Outcome of Pediatric B-Cell Acute Lymphoblastic Leukemia and Was Associated with the T-Cell Exhaustion
Authors: Shi Nana , Luo Yingwan , Xu Ying , Liang Junyu , Ma An , Gan Yichao , Wu Bowen
Published: November 2021

B-cell acute lymphoblastic leukemia is the most common malignant tumor in children. About 10–15% of patients will relapse with a 5-year OS of 57.5% for the past 20 years. As tumor microenvironment plays an important role in the disease process, many types of immunotherapy are approached. New immunotherapies including CAR-T cells have been developed for refractory B-ALL treatment. However, CAR-T treatment faces several problems, including loss of the target antigen and in vivo T-cell persistence. Here, we analyzed the tumor microenvironment of pediatric B-ALL patients in TARGET database. Using Cox analysis and PPI network, we finally sorted out the DAP10 gene. We found that DAP10 was hardly expressed in leukemic B cells. DAP10 was downregulated in B-ALL compared with normal individuals, and low expression level of DAP10 predicted poor survival. Furthermore, we found the tumor microenvironment was different in DAP10 high and low expression children. The CD8+ T cells might be hard to activate and more likely to suffer from exhaustion in DAP10 lowly expressed children. In conclusion, our results showed that DAP10 was a well biomarker to indicate the prognosis and tumor microenvironment in pediatric B-ALL. The treatment strategy of immunotherapy for the leukemic children with DAP10 lowly expressed should be adjusted if needed.
On Some Types of Covering-Based

ℐ
,
T

-Fuzzy Rough Sets and Their Applications
Authors: Atef Mohammed , Alcantud José Carlos R. , AlSalman Hussain , Gumaei Abdu
Published: November 2021

The notions of the fuzzy

β

-minimal and maximal descriptions were established by Yang et al. (Yang and Hu, 2016 and 2019). Recently, Zhang et al. (Zhang et al. 2019) presented the fuzzy covering via

ℐ
,
T

-fuzzy rough set model (

FC
ℐ
T
FRS

), and Jiang et al. (Jiang et al., in 2019) introduced the covering through variable precision

ℐ
,
T

-fuzzy rough sets (

CVP
ℐ
T
FRS

). To generalize these models in (Jiang et al., 2019 and Zhang et al. 2019), that is, to improve the lower approximation and reduce the upper approximation, the present paper constructs eight novel models of an

FC
ℐ
T
FRS

based on fuzzy

β

-minimal (maximal) descriptions. Characterizations of these models are discussed. Further, eight types of

CVP
ℐ
T
FRS

are introduced, and we investigate the related properties. Relationships among these models are also proposed. Finally, we illustrate the above study with a numerical example that also describes its practical application.
Forensic Application Evaluation of a Novel Canine STR System in Pembroke Welsh Corgi and Shiba Inu Groups
Authors: Fang Yating , Yang Jinlong , Deng Yajun , Zhu Bofeng
Published: November 2021

Aim. To evaluate the forensic application values of 19 autosomal short tandem repeat (STR) loci in canines. Methods. The 19 STR loci in two canine groups (Pembroke Welsh Corgis, n = 200; Shiba Inus, n = 175) were analysed by the capillary electrophoresis platform. The allele frequencies and forensic parameters were calculated, and the genetic relationships between these two canine groups and a previously reported Labrador group were analysed. Results. These two canine groups conformed to the Hardy‐Weinberg equilibrium at all STRs except for locus VGL3438 in the Pembroke Welsh Corgi group, and there was no linkage disequilibrium among pairwise loci at the 19 STRs. All STRs were polymorphic in the Pembroke Welsh Corgi and Shiba Inu groups, of which the locus C38 had the highest polymorphism. And it was found that the genetic relationship between the Pembroke Welsh Corgi and Labrador groups were closer in the three canine groups (Pembroke Welsh Corgi, Shiba Inu and Labrador). Conclusion. The 19 STR loci had high genetic polymorphisms and forensic application values in Pembroke Welsh Corgi and Shiba Inu groups.
Survey on Deep Learning-Based Marine Object Detection
Authors: Zhang Ruolan , Li Shaoxi , Ji Guanfeng , Zhao Xiuping , Li Jing , Pan Mingyang
Published: November 2021

We present a survey on marine object detection based on deep neural network approaches, which are state-of-the-art approaches for the development of autonomous ship navigation, maritime surveillance, shipping management, and other intelligent transportation system applications in the future. The fundamental task of maritime transportation surveillance and autonomous ship navigation is to construct a reachable visual perception system that requires high efficiency and high accuracy of marine object detection. Therefore, high-performance deep learning-based algorithms and high-quality marine-related datasets need to be summarized. This survey focuses on summarizing the methods and application scenarios of maritime object detection, analyzes the characteristics of different marine-related datasets, highlights the marine detection application of the YOLO series model, and also discusses the current limitations of object detection based on deep learning and possible breakthrough directions. The large-scale, multiscenario industrialized neural network training is an indispensable link to solve the practical application of marine object detection. A widely accepted and standardized large-scale marine object verification dataset should be proposed.
Drug-Target Interaction Prediction Based on Multisource Information Weighted Fusion
Authors: Liu Shuaiqi , An Jingjie , Zhao Jie , Zhao Shuhuan , Lv Hui , Wang ShuiHua
Published: November 2021

Recently, in most existing studies, it is assumed that there are no interaction relationships between drugs and targets with unknown interactions. However, unknown interactions mean the relationships between drugs and targets have just not been confirmed. In this paper, samples for which the relationship between drugs and targets has not been determined are considered unlabeled. A weighted fusion method of multisource information is proposed to screen drug-target interactions. Firstly, some drug-target pairs which may have interactions are selected. Secondly, the selected drug-target pairs are added to the positive samples, which are regarded as known to have interaction relationships, and the original interaction relationship matrix is revised. Finally, the revised datasets are used to predict the interaction derived from the bipartite local model with neighbor-based interaction profile inferring (BLM-NII). Experiments demonstrate that the proposed method has greatly improved specificity, sensitivity, precision, and accuracy compared with the BLM-NII method. In addition, compared with several state-of-the-art methods, the area under the receiver operating characteristic curve (AUC) and the area under the precision-recall curve (AUPR) of the proposed method are excellent.
Evaluation of Critical Factors of Postoperative Arrhythmia and Preventive Measures of Deep Venous Thrombosis
Authors: Liu Boheng , Wang Mingbo , Dong Jiawei , Wang Hao , Tian Ziqiang
Published: November 2021

The study focused on the risk factors of postoperative arrhythmia and lung infection and the preventive effects of targeted low-molecular-weight heparin (LMWH) on the occurrence of deep venous thrombosis (DVT) in patients with esophageal/cardia cancer. In this article, 82 patients who were pathologically diagnosed with esophageal/cardia cancer and underwent surgical treatment were selected as the research subjects. According to the different preoperative treatment methods, the patients were divided into the control group (without anticoagulant drugs before the operation, 44 cases) and the anticoagulation group (anticoagulant drugs were administered before the operation, 38 cases), and they were compared for basic clinical indicators and disease history. Logistic regression analysis was performed to analyze the risk factors of adverse events, and the Wells and Autar scale scores were calculated. Different groups were compared for the operation time, blood loss, and postoperative drainage volume during the operation. D-dimer was detected on the first 1, 3, 5, and 7 days after the operation, and the lower extremity venous color Doppler ultrasound was performed on the 1st and 7th days after the operation. The results showed that age ≥65 years, abnormal preoperative ECG, preoperative coronary heart disease (CHD), preoperative chronic obstructive pulmonary disease (COPD), operative time ≥4 h, and preoperative blood sodium <4.04.0 mmol/L were all risk factors for postoperative arrhythmia. Age, preoperative diabetes mellitus, preoperative COPD, length of hospital stay, and FEV1 were all risk factors for postoperative lung infections. In the control group and anticoagulation group, 11 cases (13.41%) and 5 cases (16.10%) had lower extremity DVT, respectively. The incidence of lower extremity DVT was lower in the anticoagulation group than in the control group

P
<
0.01

. It suggested that age, preoperative disease history, hospital stay, and operation time were risk factors for postoperative adverse events in patients with esophageal/cardia cancer. The targeted anticoagulant LMWH has a significant preventive effect on the occurrence of lower extremity DVT in patients with esophageal/cardia cancer, providing an effective reference for the prognosis and prevention of esophageal/cardia cancer.
Contagion Risks and Systemic Stability in Financial Networks
Authors: Tian Jingqian , Wang Chao , Liu Xiaoxing , Qiu Longmiao
Published: November 2021

An agent-based model is proposed, constructing an evolutionary banking system, where interbank loans and investment strategies are, respectively, determined by liquidity shortage and utility maximization. The causes of systemic risk are then explored based on the evolutionary banking system, which is calibrated by a sample from China. The regulatory interventions indicate the positive effects of increased investment assets, while the negative but inappreciable effects of increased interbank counterparties on contagion risks decrease. This observation hints at the possibility of promoting systemic stability by incentivizing more diversifications in investment assets instead of interbank counterparties. The results also demonstrate the advantages of prudential liquidity requirements, interbank liquidity facilities, and monetary policies from the central bank in promoting banking system stability.
A Helminth-Derived Chitinase Structurally Similar to Mammalian Chitinase Displays Immunomodulatory Properties in Inflammatory Lung Disease
Authors: Ebner Friederike , Lindner Katja , Janek Katharina , Niewienda Agathe , Malecki Piotr H. , Weiss Manfred S. , Sutherland Tara E. , Heuser Arnd , Kühl Anja A. , Zentek Jürgen , Hofmann Andreas , Hartmann Susanne
Published: November 2021

Immunomodulation of airway hyperreactivity by excretory-secretory (ES) products of the first larval stage (L1) of the gastrointestinal nematode Trichuris suis is reported by us and others. Here, we aimed to identify the proteins accounting for the modulatory effects of the T. suis L1 ES proteins and studied six selected T. suis L1 proteins for their immunomodulatory efficacy in a murine OVA-induced allergic airway disease model. In particular, an enzymatically active T. suis chitinase mediated amelioration of clinical signs of airway hyperreactivity, primarily associated with suppression of eosinophil recruitment into the lung, the associated chemokines, and increased numbers of RELMα+ interstitial lung macrophages. While there is no indication of T. suis chitinase directly interfering with dendritic cell activation or antigen presentation to CD4 T cells, treatment of allergic mice with the worm chitinase influenced the hosts’ own chitinase activity in the inflamed lung. The three-dimensional structure of the T. suis chitinase as determined by high-resolution X-ray crystallography revealed high similarities to mouse acidic mammalian chitinase (AMCase) but a unique ability of T. suis chitinase to form dimers. Our data indicate that the structural similarities between the parasite and host chitinase contribute to the disease-ameliorating effect of the helminth-derived chitinase on allergic lung inflammation.
Analysis of Center of Pressure Signals by Using Decision Tree and Empirical Mode Decomposition to Predict Falls among Older Adults
Authors: Liao Fang-Yin , Wu Chun-Chang , Wei Yi-Chun , Chou Li-Wei , Chang Kang-Ming
Published: November 2021

Falls put older adults at great risk and are related to the body’s sense of balance. This study investigated how to detect the possibility of high fall risk subjects among older adults. The original signal is based on center of pressure (COP) measured using a force plate. The falling group includes 29 subjects who had a history of falls in the year preceding this study or had received high scores on the Short Falls Efficacy Scale (FES). The nonfalling group includes 47 enrollees with no history of falls and who had received low scores on the Short FES. The COP in both the anterior–posterior and mediolateral direction were calculated and analyzed through empirical mode decomposition (EMD) up to six levels. The following five features were extracted and imported to a decision tree algorithm: root-mean-square deviation, median frequency, total frequency power, approximate entropy, and sample entropy. The results showed that there were a larger number of statistically different feature parameters, and a higher classification of accuracy was obtained. With the aid of empirical mode decomposition, the average classification accuracy increased 10% and achieved a level of 99.74% in the training group and 96.77% in the testing group, respectively.
Exploring the Therapeutic Mechanism of Tingli Dazao Xiefei Decoction on Heart Failure Based on Network Pharmacology and Experimental Study
Authors: Zhao Dan-Dan , Zhang Xiao-Qing , Yang Tao , Liu Qian , Lan Zhen-Zhen , Yang Xiao-Li , Qu Hui-Yan , Zhou Hua
Published: November 2021

Background. Tingli Dazao Xiefei decoction (TDXD) has been shown to have a therapeutic effect on heart failure (HF). Nevertheless, its molecular mechanism for treating HF is still unclear. Materials and Methods. TDXD and HF targets were collected from the databases, and protein-protein interaction (PPI) analysis and enrichment analysis were performed on the overlapping targets. Then, AutoDock was employed for molecular docking. Finally, we used the left anterior descending coronary artery (LAD) ligation to induce HF model rats for in vivo experiments and verified the effect and mechanism of TDXD on HF. Results. Network pharmacological analysis showed that the main active components of TDXD in treating HF were quercetin, kaempferol, beta-carotene, isorhamnetin, and beta-sitosterol, and the core targets were IL-6, VEGFA, TNF, AKT1, and MAPK1. Multiple gene functions and signaling pathways were obtained by enrichment analysis, among which inflammation-related, PI3K/Akt, and MAPK signaling pathways were closely related to HF. Furthermore, the molecular docking results showed that the core targets had good binding ability with the main active components. Animal experiments showed that TDXD could effectively improve left ventricular ejection fraction (EF) and left ventricular fractional shortening (FS), decrease left ventricular internal diastolic diameter (LVIDd) and left ventricular internal systolic diameter (LVIDs), reduce the area of myocardial fibrosis, and decrease serum BNP, LDH, CK-MB, IL-6, IL-1β, and TNF-α levels in HF rats. Meanwhile, TDXD could upregulate the expression of Bcl-2, downregulate the expression of Bax, and reduce cardiomyocyte apoptosis. At the same time, it was verified that TDXD could significantly decrease the expression of PI3K, P-Akt, and P-MAPK. Captopril showed similar effects. Conclusions. Combining network pharmacological analysis and experimental validation, this study verified that TDXD could improve cardiac function and protect against cardiac injury by inhibiting the activation of PI3K/Akt and MAPK signaling pathways.
Lycopene Ameliorates Liver Inflammation and Redox Status in Mice Exposed to Long‐Term Cigarette Smoke
Authors: Rocha Daniela Fonseca Abdo , Machado-Junior Pedro Alves , Souza Ana Beatriz Farias , Castro Thalles de Freitas , Costa Guilherme de Paula , Talvani André , Bezerra Frank Silva , Cangussú Silvia Dantas
Published: November 2021

Cigarette smoke (CS) is the major cause of preventable death worldwide, and it can also cause damage to extrapulmonary organs, such as the liver, mainly due the generation of reactive oxygen species (ROS). The liver is an essential organ for human survival since it is mainly responsible for the body metabolism and among other things and it is the place where many endogenous and exogenous substances undergo biological transformation. Lycopene is a nonprovitamin A carotenoid found in red fruits and vegetables, and its role as a potent antioxidant is well known. In this study, we hypothesized that lycopene could protect mouse liver against long‐term CS exposure. Thirty C57BL/6 mice were exposed to twelve cigarette smoke (12 cigarettes per day) for 60 days and pretreated with 25 mg/kg/day or 50 mg/kg/day of lycopene via orogastric gavage. After euthanasia, the hepatic tissue was collected for histopathological, antioxidant defense, oxidative stress, inflammatory, and collagen deposition analysis. Our analysis demonstrated that lycopene results in a suitable outcome to ameliorate the pathological changes, inflammatory and antioxidant profile in a mouse model of long‐term CS exposure, and collagen accumulation in the hepatic extracellular matrix. This study demonstrates for the first time that supplementation of lycopene can be a possible pharmacological tool for the treatment of hepatic damage caused by exposure to long‐term CS.
Replacement Analysis of Mutually Exclusive Projects of Unequal Lives Using Kelly Specific Real Option Criterion
Authors: Kim Gyutai , Kim Seong-Joon , Shin Jong-Ho
Published: November 2021

This paper presents a model to address the uncertainty inherent in replacement problems, whereby a firm must select between mutually exclusive projects of unequal lifespans by applying the Kelly criterion (which is not well known to the engineering economics community) within a binomial lattice option-pricing environment. Assuming that only the interest rate, among many factors, is uncertain, Brown and Davis performed an economic analysis of this problem by employing a real option-pricing method and argued that their model yields results opposite to those yielded by the traditional approach. However, the results yielded by the model proposed herein are consistent with those by the traditional approach, unlike Brown and Davis’s model. The conclusion is that since the investment time horizon is infinite, a firm rationale pertaining to the selection of the best method for the investment problem of such types does not exist.
Overlying Strata Movement and Abutment Pressure Evolution Process of Fully Mechanized Top Coal Caving Mining in Extra Thick Coal Seam
Authors: Zhao Yongqiang , Yang Yingming , Li Xiaobin , Wang Zhiqi
Published: November 2021

Taken overlying strata of fully mechanized top coal caving mining (FMTCCM) in 15 m extra thick coal seam as the research object, the comprehensive research methods such as field investigation, theoretical calculation, and numerical analysis are used to systematically analyze. During the mining of extra thick coal seam, the overlying strata form the structure of lower cantilever beam and upper hinged rock beam. The downward transmission caused by the interaction of this combined structure is the fundamental reason for the strong periodic ground pressure behavior of working face and roadway blow. The movement process of overlying strata movement is divided into four stages, and dynamic distribution characteristics of lateral abutment pressure in different stages are obtained. It is considered that the gob side roadway can be in a relatively stable overburden structure and stress environment during the stable stage of abutment pressure. The distribution range of the internal and external stress fields is determined, which provides a theoretical basis for the reasonable roadway layout. At last, the fracture position and abutment pressure evolution process of overlying strata along the goaf side of the extra thick coal seam are further verified by drilling stress measurement.