bluuebunny/crossref_metadata_2025 huggingface dataset:
A New Early Rumor Detection Model Based on BiGRU Neural Network
Authors: Chen Xiangning , Wang Caiyun , Li Dong , Sun Xuemei
Published: August 2021

With the progress of society and the rapid development of computer technology, rumors arise on social media, which seriously affects the social economy. How to detect rumors accurately and rapidly has become one hot research topic. In this paper, a new early rumor detection model is proposed. The aim of this model is to increase the efficiency and the accuracy of rumor detection simultaneously. Specifically, in this model, the input data is firstly refined through account filtering and data standardization, then the BiGRU is used to consider the context relationship, and a reinforcement learning algorithm is applied to detection. Experimental results show that compared with other early rumor detection models (e.g., checkpoints), the accuracy of the proposed model is improved by 0.5% with the same speed, which testifies the effectiveness of this model.
Inhibitory Effect of Gualou Guizhi Decoction on Microglial Inflammation and Neuron Injury by Promoting Anti-Inflammation via Targeting mmu-miR-155
Authors: Hu Haixia , Zhong Xinghua , Lin Xinjun , Yang Jinbo , Zhu Xiaoqin
Published: August 2021

Gualou Guizhi decoction (GLGZD) treatment exerts neuroprotective effects and promotes spasticity following ischemic stroke. However, the molecular mechanism of GLGZD treatment on ischemic stroke remains unclear. Our previous study indicated that GLGZD ameliorates neuronal damage caused by secondary inflammatory injury induced by microglia. In the present study, we investigate the potential mechanism of GLGZD treatment on neuron damage induced by neuroinflammation via mmu-miR-155 in vitro. The HT22 cell line and the BV2 cell line were exposed to oxygen/glucose-deprive (OGD) conditions; the conditioned medium was prepared using the supernatants from OGD-stimulated BV2 cells after pretreating with GLGZD. Cell viability was determined by MTT assays; levels of released inflammatory cytokines were assessed using the BioPlex system. mmu-miR-155 and its targeting genes were detected using real-time reverse transcription polymerase chain reaction (RT-PCR). The expression of anti-inflammatory proteins was evaluated by Western blotting. DAPI staining was used to test the apoptotic cells. Our results showed that GLGZD pretreatment significantly induced IL10 release and decreased the production of TNF-α, IL6, and IFN-γ. In addition, GLGZD markedly attenuated mmu-miR-155 expression and its downstream SOCS1, SMAD2, SHIP1, and TAB2 expression levels. The DAPI-stained apoptotic cell death and caspase-3 activation in HT22 cells exposed to the conditioned medium were reversed by GLGZD treatment. Our findings suggested that GLGZD pretreatment downregulates the mmu-miR-155 signaling, which inhibits microglial inflammation, thereby resulting in the suppression of neuron apoptosis after OGD stress. The underlying mechanisms may provide the support for GLGZD treatment of cerebral ischemic injury.
Pushed SOLID: Deploying SOLID in Smartphones
Authors: Jesús-Azabal Manuel , Moguel Enrique , Laso Sergio , Murillo Juan Manuel , Galán-Jiménez Jaime , García-Alonso José
Published: August 2021

Personal information has become one of the most valuable coins on the Internet. Companies gather a massive amount of data to create rich profiles of their users, trying to understand how they interact with the platform and what are their preferences. However, these profiles do not follow any standard and are usually incomplete in the sense that users provide different subsets of information to distinct platforms. Thus, the quality and quantity of the data vary between applications and tends to inconsistency and duplicity. In this context, the Social Linked Data (SOLID) initiative proposes an alternative to separate the user’s information from the platforms which consume it, defining a unique and autonomous source of data. Following this line, this study proposes Pushed SOLID, an architecture that integrates SOLID in the user’s smartphone to store and serve their information from a single entity controlled by the users themselves. In this study, we present an implementation of the Pushed SOLID proposal with the aim of experimentally assessing the technical viability of the solution. Satisfactory performance results have been obtained at battery consumption and response time. Furthermore, users have been interviewed about the proposal, and they find the solution attractive and reliable. This solution can improve the way data are stored on the Internet, empowering users to manage their own information and benefiting third party applications with consistent and update profiles.
3D Deployment of Unmanned Aerial Vehicle‐Base Station Assisting Ground‐Base Station
Authors: Hayajneh Khaled F. , Bani-Hani Khaled , Shakhatreh Hazim , Anan Muhammad , Sawalmeh Ahmad
Published: August 2021

Unmanned aerial vehicles (UAVs), also named as drones, have become a modern model to provide a quick wireless communication infrastructure. They have been used when conventional base stations’ capacity is suffering in some extreme cases such as congestion inside the cell or a special event. This paper proposes an efficient three‐dimension (3D) placement of a single UAV‐assisted wireless network in such cases. Our proposed model assists the ground base station (GBS) using the UAV to serve arbitrary distributed users considering the impact of the obstacle blockage over the well‐known air‐to‐ground (A2G) path model. This work is aimed at optimizing the percentage of available bandwidth that must be provided to the UAV in order to maximize the number of served users. In addition, it finds the 3D placement of the UAV base station (UAVBS) that maximizes the number of served users, each with maximum quality‐of‐service (QoS). The exhaustive search and particle swarm optimization (PSO) algorithms are used to find the problem’s solution.
LncRNA GSTM3TV2 Promotes Cell Proliferation and Invasion via miR‐597/FOSL2 Axis in Hepatocellular Carcinoma
Authors: Hu Yuting , Qiu Wei , Kong Zhijun , Wu Siyuan , Liu Yi , Zhu Chunfu , Qin Xihu
Published: August 2021

Mounting evidence has recently shown that role of long noncoding RNA is critical in many human cancers. lncRNA GSTM3TV2 was first proven to play a vital role in pancreatic cancer. However, the mechanism of lncRNA GSTM3TV2 in hepatocellular carcinoma (HCC) is still uncovered. Here, we object to distinguish the expression of lncRNA GSTM3TV2 and reveal its mechanistic relationship with HCC. We observed that the expression of lncRNA GSTM3TV2 and FOSL2 were upregulated in HCC. Knockdown of lncRNA GSTM3TV2 significantly inhibited cell proliferation. Meanwhile, the migration and invasion of HCC cells were greatly decreased by the downregulated lncRNA GSTM3TV2. The luciferase reporter assays showed that lncRNA GSTM3TV2 could be directly bound to miR‐597, and the level of miR‐597 was also decreased in the tumor tissues. lncRNA GSTM3TV2 could stabilize FOSL2 expression, resulting in the oncogenic properties of lncRNA GSTM3TV2 in HCC. Our study indicated the oncogenic activities of lncRNA GSTM3TV2 and emphasized the role of the miR‐597/FOSL2 signaling pathway.
Study on the Dynamic Evolution of Through‐Crack in the Double Hole of Elliptical Bipolar Linear‐Shaped Charge Blasting
Authors: Wu Bo , Xu Shixiang , Meng Guowang , Cui Yaozhong , Cai Junhua , Zhang Yao
Published: August 2021

Seeking the law of through‐crack in the double hole of shaped charge can help reveal the rock failure mechanism of directional controlled blasting. Using LS‐DYNA numerical simulation analysis, the dynamic mechanical behaviors of double‐hole crack development and double‐hole crack penetration in elliptical bipolar linear‐shaped charge blasting and ordinary blasting were compared and studied. The results showed that it was difficult to form a straight line through the double holes under ordinary blasting, while easy to cause over‐under‐excavation problems. The blasting of the elliptical bipolar linear‐shaped charge had a significant effect on the formation of directional crack. The crack penetrated along the connecting center line of the two holes. The main crack growth form was tensile fracture mode, and the explosion gas was the important driving force for continuous crack growth. The elliptical bipolar linear‐shaped charge blasting produced fewer cracks in the nonenergy‐accumulating direction, which could effectively reduce the damage of the retained rock mass.
Some Rational Coupled Fuzzy Cone Contraction Theorems in Fuzzy Cone Metric Spaces with an Application
Authors: Rehman Saif Ur , Talha Waheed Muhammad , Jan Naeem , Gumaei Abdu , Al-Rakhami Mabrook
Published: August 2021

In this paper, we establish the new concept of rational coupled fuzzy cone contraction mapping in fuzzy cone metric spaces and prove some unique rational-type coupled fixed-point theorems in the framework of fuzzy cone metric spaces by using “the triangular property of fuzzy cone metric.” To ensure the existence of our results, we present some illustrative unique coupled fixed-point examples. Furthermore, we present an application of a Lebesgue integral-type contraction mapping in fuzzy cone metric spaces and to prove a unique coupled fixed-point theorem.
Plant‐Based Synthesis of Zinc Oxide Nanoparticles (ZnO‐NPs) Using Aqueous Leaf Extract of Aquilegia pubiflora: Their Antiproliferative Activity against HepG2 Cells Inducing Reactive Oxygen Species and Other In Vitro Properties
Authors: Jan Hasnain , Shah Muzamil , Andleeb Anisa , Faisal Shah , Khattak Aishma , Rizwan Muhammad , Drouet Samantha , Hano Christophe , Abbasi Bilal Haider
Published: August 2021

The anti‐cancer, anti‐aging, anti‐inflammatory, antioxidant, and anti‐diabetic effects of zinc oxide nanoparticles (ZnO‐NPs) produced from aqueous leaf extract of Aquilegia pubiflora were evaluated in this study. Several methods were used to characterize ZnO‐NPs, including SEM, FTIR, XRD, DLS, PL, Raman, and HPLC. The nanoparticles that had a size of 34.23 nm as well as a strong aqueous dispersion potential were highly pure, spherical or elliptical in form, and had a mean size of 34.23 nm. According to FTIR and HPLC studies, the flavonoids and hydroxycinnamic acid derivatives were successfully capped. Synthesized ZnO‐NPs in water have a zeta potential of ‐18.4 mV, showing that they are stable solutions. The ZnO‐NPs proved to be highly toxic for the HepG2 cell line and showed a reduced cell viability of 23.68 ± 2.1% after 24 hours of ZnO‐NP treatment. ZnO‐NPs also showed excellent inhibitory potential against the enzymes acetylcholinesterase (IC50: 102 μg/mL) and butyrylcholinesterase (IC50: 125 μg/mL) which are involved in Alzheimer’s disease. Overall, the enzymes involved in aging, diabetes, and inflammation showed a moderate inhibitory response to ZnO‐NPs. Given these findings, these biosynthesized ZnO‐NPs could be a good option for the cure of deadly diseases such as cancer, diabetes, Alzheimer’s, and other inflammatory diseases due to their strong anticancer potential and efficient antioxidant properties.
[Retracted] An Intelligent Diagnosis System for English Writing Based on Data Feature Extraction and Fusion
Authors: He Yizhou
Published: August 2021

English writing is conducive to the online communication and communication of language; the current diagnosis system of English writing is difficult to accurately find and diagnose the wrong words, which leads to a low diagnosis rate of wrong words in English writing system. To solve this problem, this paper designs an intelligent diagnosis system for English writing based on data feature extraction and fusion. First of all, B/S architecture is introduced on the basis of the conventional intelligent diagnosis system structure of English writing, which makes up for the problem that the C/S mode is prone to diagnostic errors. Secondly, the features of English lexical data are extracted and fused to provide better input for the diagnostic model, which effectively solves the problems of complex vocabulary and feature redundancy in English writing. The simulation results show that the proposed intelligent diagnosis system for English writing has higher diagnostic accuracy and faster query speed.
DRL‐Based Intelligent Resource Allocation for Diverse QoS in 5G and toward 6G Vehicular Networks: A Comprehensive Survey
Authors: Nguyen Hoa TT. , Nguyen Minh T. , Do Hai T. , Hua Hoang T. , Nguyen Cuong V.
Published: August 2021

The vehicular network is taking great attention from both academia and industry to enable the intelligent transportation system (ITS), autonomous driving, and smart cities. The system provides extremely dynamic features due to the fast mobile characteristics. While the number of different applications in the vehicular network is growing fast, the quality of service (QoS) in the 5G vehicular network becomes diverse. One of the most stringent requirements in the vehicular network is a safety‐critical real‐time system. To guarantee low‐latency and other diverse QoS requirements, wireless network resources should be effectively utilized and allocated among vehicles, such as computation power in cloud, fog, and edge servers; spectrum at roadside units (RSUs); and base stations (BSs). Historically, optimization problems have mostly been investigated to formulate resource allocation and are solved by mathematical computation methods. However, the optimization problems are usually nonconvex and hard to be solved. Recently, machine learning (ML) is a powerful technique to cope with the complexity in computation and has capability to cope with big data and data analysis in the heterogeneous vehicular network. In this paper, an overview of resource allocation in the 5G vehicular network is represented with the support of traditional optimization and advanced ML approaches, especially a deep reinforcement learning (DRL) method. In addition, a federated deep reinforcement learning‐ (FDRL‐) based vehicular communication is proposed. The challenges, open issues, and future research directions for 5G and toward 6G vehicular networks, are discussed. A multiaccess edge computing assisted by network slicing and a distributed federated learning (FL) technique is analyzed. A FDRL‐based UAV‐assisted vehicular communication is discussed to point out the future research directions for the networks.
Green Supply Chain Management, Environmental Degradation, and Energy: Evidence from Asian Countries
Authors: Yu Yi , Zhu Wanwan , Tian Yuan
Published: August 2021

The purpose of this study is to test the relationship among green logistics, environmental degradation, and energy demand. The system generalized method of moment (system GMM) is used to study the data of Asian countries and four subregions in Asia. The estimation results show that logistics operation consumes nonrenewable energy such as fossil fuels, which has a negative impact on environmental sustainability and energy demand. The service quality and capability (LPITC) in the logistics performance index has a significant contribution to reducing carbon dioxide emissions. The logistics infrastructure (LPIIN) has significantly reduced the energy consumption in Asia, while the customs (LPIC) has significantly increased the energy demand. Other indicators of LPI also have a significant impact on the environment and energy in different subregions of Asia. Industrialization and urbanization both increase carbon emissions in Asia, while trade opening reduces carbon emissions. At the same time, these three variables have a positive impact on reducing energy consumption. The results show that logistics performance is significantly related to environmental degradation and energy, and renewable energy and green supply chain management can reduce the harmful effects of logistics activities on environment and energy. Therefore, Asian countries should give priority to environmental sustainability in supply chain management and encourage the application of green practices in logistics.
Evolutionary Game Analysis of BIM Adoption among Stakeholders in PPP Projects
Authors: Jia Chong , Zhang Ruixue , Wang Dan
Published: August 2021

With the development of building information technology, Building Information Modeling (BIM) has become an important way to effectively solve the cross‐organization information collaboration of Public‐Private Partnership (PPP) projects, and how to promote the adoption of BIM in PPP projects has become a realistic problem to be solved urgently. This study discusses the adoption of BIM among stakeholders in PPP projects based on prospect theory and evolutionary game theory. A tripartite evolutionary game model including governments, social capitals, and contractors is established. The behavioral evolution mechanism of each stakeholder on BIM adoption is explored by analyzing the evolutionary equilibrium, and the key influencing factors of equilibrium strategy are analyzed by using numerical simulation. The results demonstrate that first, the degree of the cost to all stakeholders involved in the adoption of BIM, as well as the punishment for governments’ passive promotion of BIM, the punishment for social capitals’ passive adoption of BIM and the reward for contractors’ active application of BIM are the key factors affecting evolutionary stability. Second, according to prospect theory, the main stakeholders usually make decisions through subjective judgment and perceived value which ultimately lead to deviation in their behaviors. The deviations will hinder the establishment of ESS point (1, 1, 1) and make the system difficult to converge to the optimal state. Finally, from the perspective of governments, social capitals, and contractors, countermeasures and management implications are put forward to effectively promote the adoption of BIM in PPP projects.
Reliability Analysis of Loess Cave Dwellings Based on Fuzzy Failure Criterion
Authors: Guo Pinggong
Published: August 2021

The reliability of loess cave dwellings based on fuzzy failure criterion is researched to analyze the influence of fuzzy set, membership function, and different combinations of random variables. Due to the strength reduction method, the basic failure criterion is established, the fuzzy property of failure criterion is characterized by fuzzy set and membership function, and the performance function of loess cave dwellings is expressed by a quadratic polynomial without cross terms. Reliability is analyzed with different random variable combinations. The reliability research of loess cave dwellings in Shan Plateau, Henan province, China, shows that the loess property in this area is suitable for loess cave dwelling construction and the reliability index of loess cave dwellings is high, which will be decreased when considering the fuzzy failure criterion and will be increasing sharply when the small cave leg width is improved to average value.
Assessment of Biosecurity Status in Commercial Chicken Farms Found in Bishoftu Town, Oromia Regional State, Ethiopia
Authors: Ismael Abdulbari , Abdella Adem , Shimelis Shihun , Tesfaye Asamenew , Muktar Yimer
Published: August 2021

A survey was undertaken from December 2017 to April 2018 to assess the biosecurity status of 44 commercial chicken farms established in Bishoftu town, Ethiopia, by interviewing farm owners using a structured questionnaire. The obtained data were summarized using frequency tables and analyzed with Pearson’s chi-square test and Fischer’s exact value using Stata 14 statistical software. From the assessed chicken farms, 31 (70.45%) were located within 0–50 m from the main road, 39 (88.64%) situated 500 m from the nearest farms, and 27 (61.36%) placed within 0–20 m from the residential areas. Forty-one (93.18%) participants disclosed that their employees did not receive training on biosecurity. From the assessed chicken farms, 30 (68.18%) had fences, 40 (90.91%) had footbaths at their gates, 31 (70.45%) prohibited visitors entrance, and 39 (88.64%) did not exchange equipment with other farms. In addition, 26 (59.09%) farms were easily accessed by wild birds, each of 42 (95.45%) farms purchased day-old chicks and feed, and 40 (90.91%) shared trucks with other farms as well. Among the assessed farms, only 2 (4.55%) had signages to restrict people’s access, 9 (20.45%) had isolation rooms for diseased chickens, 14 (31.82%) disposed of dead birds properly, and 10 (22.73%) kept various types of records. Occupation (Fischer’s exact value = 8.40;P=0.019), previous training (Fischer’s exact value = 4.40;P=0.044), source of the premises (χ2 = 5.50;P=0.019), and farm capacity (Fischer’s exact value = 13.50;P=0.002) were found statistically significantly associated with the farm biosecurity status. The farm biosecurity status was found to be good in farms that were run by civil servants, had trained employees, are owned premises, and were of large and medium scales. In conclusion, the higher poor biosecurity status on chicken farms calls for the implementation of good biosecurity practices in each farm as well as the provision of training to the farm owners and their employees.
Chitosan-Derived Magnetic Nanomaterials: Synthesis, Characterization, and Nitrite Adsorption in Water
Authors: Liu Tong , Fu Jingyi , Gou Dongxia , Hu Yanbo , Tang Qilong , Zhao Jun , Li Xiaohong
Published: August 2021

Nitrite is one of the main pollutants in the water worldwide. In this study, we have applied the reverse suspension crosslinking methodology based on chitosan (CS) and Fe3O4 (FeO) to synthesize the novel magnetic nanomaterial of chitosan (CS-FeO). The physical and chemical properties of CS-FeO were further characterized by scanning electron microscopy, particle size distribution, thermogravimetry, fluxgate magnetometer, Fourier transform infrared spectroscopy, X-ray diffraction spectroscopy, and energy dispersive spectroscopy. Results revealed that CS-FeO showed high thermal stability in the temperature ranging from 50 to 200°C. CS-FeO showed high crystallinity and magnetism and was easily and quickly separated from aqueous solution in the presence of an external magnetic field. The molecular structure of CS-FeO showed that the core-shell structure of CS-FeO was established with FeO as the core and CS as the shell. Furthermore, the adsorption rate of nitrite by CS-FeO reached

65.83
±
0.76
%

under optimal conditions. Moreover, CS-FeO showed high regeneration capability with Na2SO4 used as the eluent. Our study demonstrated evidently that CS-FeO can be potentially used to remove nitrite from drinking water sources and industrial wastewater, suggesting the promising future of the application of CS-derived magnetic nanomaterials in the areas of environmental protections.
Oscillation of Nonlinear Fractional Dynamic Equations with Forcing Term
Authors: Manikandan S. , Muthulakshmi V. , Harikrishnan S. , Hammachukiattikul Porpattama
Published: August 2021

In this paper, interval oscillation criteria for the nonlinear damped dynamic equations with forcing terms on time scales within conformable fractional derivatives are established. Our approach is determined from the implementation of generalized Riccati transformation, some properties of conformable time-scale fractional calculus, and certain mathematical inequalities. Also, we extend the study of oscillation to conformable fractional Euler-type dynamic equation. Examples are presented to emphasize the validity of the main theorems\enleadertwodots.
Nonmedical Determinants of Congenital Heart Diseases in Children from the Perspective of Mothers: A Qualitative Study in Iran
Authors: Borjali Maryam , Amini-Rarani Mostafa , Nosratabadi Mehdi
Published: August 2021

Introduction. Mortality due to noncommunicable diseases has increased in the world today with the advent of demographic shifts, growing age, and lifestyle patterns in the world, which have been affected by economic and social crises. Congenital heart defects are one of the forms of diseases that have raised infant mortality worldwide. The objective of present study was to identify nonmedical determinants related to this abnormality from the mother’s perspectives. Methods. This research was a qualitative study and the data collection method was a semistructured interview with mothers who had children with congenital heart diseases referring to the Shahid Rajaei Heart Hospital in Tehran, Iran. A thematic analysis approach was employed to analyze transcribed documents assisted by MAXQDA Plus version 12. Results. Four general themes and ten subthemes including social contexts (social harms, social interactions, and social necessities), psychological contexts (mood disorders and mental well-being), cultural contexts (unhealthy lifestyle, family culture, and poor parental health behaviors), and environmental contexts (living area and polluted air) were extracted from interviews with mothers of children with congenital heart diseases. Conclusions. Results suggest that factors such as childhood poverty, lack of parental awareness of congenital diseases, lack of proper nutrition and health facilities, education, and lack of medical supervision during pregnancy were most related with the birth of children with congenital heart disease from mothers’ prospective. In this regard, targeted and intersectorial collaborations are proposed to address nonmedical determinants related to the incidence of congenital heart diseases.
A New Pyrrolidone Alkaloid and Other Constituents from Rourea oligophlebia Stems
Authors: Ngoc Dinh Thuc , Vu Thi Ha Mai , Ngo Xuan Luong , Trinh Thi Huan , Nguyen Thi Huong , Nguyen Thi Ngoc Mai , Tran Huu Giap , Vu Thi Kim Oanh , Le Nguyen Thanh
Published: August 2021

Phytochemical study of Rourea oligophlebia stems led to the isolation of a new 2-pyrrolidone alkaloid (R,S)-N-(5-hydroxyl-pyrrolidin-2-one-1-yl)acetamide (1), together with 14 known compounds including friedelin (2), friedanol (3), taraxerol (4), vanillin (5), coniferyl aldehyde (6), apigenin (7), 7α-hydroxy-3β-sitosterol (8), coniferyl alcohol (9), scopoletin (10), emodin (11), protocatechuic acid (12), catechin (13), procyanidin A1 (14), and (E)-2,3,5,4’-tetrahydroxystilbene-2-β-D-glucoside (15). Several isolated compounds were evaluated for cytotoxicity and antimicrobial activity. Compound 11 exhibited good antimicrobial activity on Gram (+) strains and moderate cytotoxicity against KB, Hep-G2, and LU cancer cell lines. Compounds 6 and 8–10 showed selective activity on HepG-2 and MCF-7 over KB and LU cancer cell lines, while compound 7 exhibited similar effects on KB, HepG-2, and MCF-7 cell lines with IC50 values of 36.46 ± 0.81, 32.00 ± 0.58, and 32.03 ± 0.61 µg/mL, respectively.
Novel MFSD8 Variants in a Chinese Family with Nonsyndromic Macular Dystrophy
Authors: Xiang Qin , Cao Yanna , Xu Hongbo , Yang Zhijian , Tang Liang , Xiang Ju , Li Jianming , Deng Hao , Yuan Lamei
Published: August 2021

Purpose. To identify the molecular etiology of a Chinese family with nonsyndromic macular dystrophy. Methods. Ophthalmic examinations were performed, and genomic DNA was extracted from available family members. Whole exome sequencing of two members (the proband and her unaffected mother) and Sanger sequencing in available family members were performed to screen potential pathogenic variants. Results. Novel compound heterozygous variants, c.1066C>T (p.Pro356Ser) and c.1102+2T>C, in the major facilitator superfamily domain containing 8 gene (MFSD8) were suspected to be involved in this family’s macular dystrophy phenotype. The novel c.1066C>T variant in the MFSD8 gene probably resulted in substitution of serine for proline at the 356th residue and was predicted to be “uncertain significance” through in silico analyses. The novel c.1102+2T>C variant in the MFSD8 gene was likely to affect the splicing form and predicted to be “pathogenic.” Conclusion. The novel compound heterozygous variants, c.1066C>T (p.Pro356Ser) and c.1102+2T>C, in the MFSD8 gene are likely responsible for the isolated macular dystrophy phenotype in this family. This study enlarged the MFSD8 gene mutant spectrum and might provide more accurate genetic counseling for this family.
Constructing Sports Multi-Index Data Analysis Based on 5G IoT Technology
Authors: Wang Hui , Zhao Ben
Published: August 2021

The arrival of the new era and the development of 5G Internet of Things (IoT) technology have made our lives and work easier and more convenient. The vigorous development of the IoT has been applied in many fields, among which, especially the data mining technology of the IoT ushered in the spring of this era of information explosion. Full application of data mining technology can provide real data well. Application analysis provides value and decision support. In order to apply 5G Internet of Things technology to the sports industry to help study the multi-index data of various sports activities so as to better help modern people have a healthy sports concept, Nemo builds relevant data analysis based on 5G Internet of Things technology. This article analyzes the research on the construction of sports multi-index data based on 5G IoT, makes full use of the IoT to mine sports-related data, and launches a multi-index discussion on it. First, the literature data method is adopted to learn the theoretical knowledge of IoT, artificial neural network, deep learning, etc., and establish a sports multi-index data analysis research model based on machine learning and massive data processing technology. Finally, for modern people, sports hobbies, types, exercise duration, exercise heart rate, and other aspects are analyzed. The results show that modern people prefer aerobic exercise, especially jogging and cycling, accounting for 47% and 41%, and the proportion of people who spend more than 60 minutes in the gym is as high as 48%. This shows that even though most people are busy at work, they still realize the importance of physical exercise and are willing to do sports.
Dispersion Performance of Polycarboxylate Terpolymers with Different Alkyl Side-Chain Lengths in Pesticide Suspension Concentrate
Authors: Yang Xiaodong , Ren Tianrui , Zhang Bo
Published: August 2021

A versatile dispersant plays a critical role in the suspension stability of pesticide suspension concentrate (SC) systems. Herein, a series of novel acrylate ester-based polycarboxylate terpolymers (PTs) were designed as dispersant for pesticide suspension concentrate and successfully synthesized in aqueous solutions from the copolymerization of α-methacrylic acid, allyl polyoxyethylene ether, and acrylate (methyl acrylate, ethyl acrylate, and n-butyl acrylate). Terpolymers were characterized by FT-IR and 1H-NMR to confirm their structure. The surface activities of PTs were evaluated according to critical micelle concentration (CMC) and the surface tension at CMC (γCMC). PT-3 with the longest alkyl side-chain length displayed the most superior surface activity due to its lowest CMC value compared with that of the other PTs. Additionally, the dispersion properties of PTs as dispersants in a 600 g/L imidacloprid SC were evaluated. Results showed that compared to the other two PTs, PT-3 contributes to the excellent dispersion properties on imidacloprid SC. Meanwhile, the obtained SC system exhibited shear thinning behavior under high-speed shearing showing typical features of pseudo-plastic non-Newtonian fluids, which conforms to the Herschel–Buckley model. Our results revealed that the effect of the alkyl side-chain length of dispersants could be considered the primary modulator of dispersion performance of SCs.
Reconstructing Terrestrial Water Storage Anomalies Using Satellite Data to Evaluate Water Resource Shortages from 1980 to 2016 in the Inland Yongding River Basin, China
Authors: Sun Kangning , Hu Litang , Liu Xin , Yin Wenjie
Published: August 2021

Water resources in the Yongding River basin (YRB) are one of the important fundamental conditions in supporting regional water conservation and ecological development. However, the historical changes in water resources under recent human activities remain unknown due to very limited observation data. In this study, terrestrial water storage anomalies (TWSA) as well as multiple precipitation and actual evapotranspiration products from satellites were collected, and the accuracy of the data was verified by observed data or pairwise comparisons. The TWSA during 1980-2016 was reconstructed by using the water balance method, and the reconstructed TWSA was verified using GRACE-observed TWSA, the average depth to groundwater in the Beijing Plain from historical document records and the observed runoff from Guanting Reservoir. The reconstructed TWSA data indicated that the significant decrease occurred during 2000–2016 and the average rate of decreasing trend was -11 mm/year, which may have been caused by a decrease in groundwater storage due to agricultural development. However, the reconstructed TWSA decreased slightly during 1980-1999. The establishment of the water storage deficit index (WSDI) showed that there was no drought or mild drought during 1980-1999; however, the water resource shortage during 2000-2016 was more serious due to groundwater storage decreases caused by agricultural development. The WSDI was verified by using the commonly used self-calibrated Palmer drought severity index. The findings are valuable for sustainable water resource management in the YRB.
Leptin Induced TLR4 Expression via the JAK2‐STAT3 Pathway in Obesity‐Related Osteoarthritis
Authors: Jiang Mengqi , He Jianyi , Sun Yingxu , Dong Xin , Yao Jiayu , Gu Hailun , Liu Li
Published: August 2021

Obesity is considered as a risk factor of osteoarthritis (OA), but the precise relationship is still poorly understood. Leptin, one of the most relevant factors secreted by adipose tissues, plays an important role in the pathogenesis of OA. Our aim was to investigate the regulation and molecular mechanism of the leptin signaling pathway in obesity‐related OA. SD rats were fed with a high‐fat diet (HFD) for 5, 15, and 27 weeks. The levels of leptin in serum increased from W5, while in the synovial fluid increased from W15. The histological evaluation showed that the pathological changes of OA occurred at 27 weeks rather than 5 or 15 weeks. We also found that leptin induced CD14/TLR4 activation by the JAK2‐STAT3 signaling pathway to promote OA. Moreover, silencing SOCS3 enhanced leptin‐induced JAK2‐STAT3‐CD14/TLR4 activation in rat primary chondrocytes. Our findings indicated that leptin may be one of the initiating factors of obesity‐related OA. TLR4 is at least partially regulated by leptin through the JAK2‐STAT3‐CD14 pathway. Meanwhile, SOCS3 acting as a negative feedback inhibitor of leptin signaling presented a potential therapeutic prospect for obesity‐related OA. Our study provided new evidence suggesting the key role of leptin in mediating obesity‐related OA process and its underlying mechanisms.
Effect of Advancing Direction of Working Face on Mining Stress Distribution in Deep Coal Mine
Authors: Tang Yuesong , Sun Wenchao , Zhang Xin , Liu Pengju
Published: August 2021

Deep mining has become the normal state of coal mining; compared with the mine with shallow buried depth, the consequent high level of in situ stress and complex distribution have brought severe threats to the stability of the stope and the surrounding rock of the roadway. In this research, taking the 121304 working face of Kouzidong Mine as the engineering background, the characteristics of mining‐induced stress distribution under complex in situ stress environment in deep mining are analyzed by using on‐site measurement of the original rock stress and mining stress, establishing a theoretical model centered on the middle section of the working face, and establishing large‐scale numerical calculation models for different advancing directions. It was found that under deep mining conditions, the maximum stress of the original rock is 25.12 MPa, and the direction is vertical. The advanced influence range of mining stress is about 150 m, and the abutment pressure presents a three‐peak distribution characteristic in front of the working face. The research results provide important theoretical guiding value for guiding the mining of coal mines with similar geological conditions.
Evolutionary Game Analysis of Three Players on Behavioural Strategy of P2P Lending Participants: A Sustainable Operations Perspective
Authors: You Ge , Guo Hao , Dagestani Abd Alwahed , Deng Shuai
Published: August 2021

In China, most of peer‐to‐peer (P2P) lending platforms do not possess operational sustainability due to excessive defaults. To address this problem, the conflict of interests among P2P lending participants is discussed using a stakeholder approach. An evolutionary game model (EGM) of three players is developed to analyse the interactions among regulatory authorities, P2P lending platforms, and borrowers. Then, the asymptotic of the equilibrium and evolutionary stability strategies of the EGM are analysed. Results indicate that either the P2P lending platforms or borrowers will choose “noncompliant operation” or “default” strategies from a short‐term perspective, and the strict supervision of the P2P lending platform in the short term is necessary for the sustainable operation of the platform. When supervision is intensified in the early stage and regulatory pressure becomes a normal state, P2P lending platforms and borrowers will actively select “compliant operation” and “repayment” strategies even if there is a lack of regulation in the future. Meanwhile, the behavioural strategies of P2P lending participants can be changed to conform to the sustainability of P2P lending by reducing the costs of strict supervision and increasing the damage caused by general supervision, reward and punishment coefficient for P2P lending platforms, repayment incentives of borrowers, and defaulting opportunity costs. Finally, suggestions for regulating the behaviours of P2P lending participants and promoting sustainability of P2P lending industry are discussed.
BLNN: Multiscale Feature Fusion‐Based Bilinear Fine‐Grained Convolutional Neural Network for Image Classification of Wood Knot Defects
Authors: Gao Mingyu , Wang Fei , Song Peng , Liu Junyan , Qi DaWei
Published: August 2021

Wood defects are quickly identified from an optical image based on deep learning methodology, which effectively improves the wood utilization. The traditional neural network technique is unemployed for the wood defect detection of optical image used, which results from a long training time, low recognition accuracy, and nonautomatic extraction of defect image features. In this paper, a wood knot defect detection model (so‐called BLNN) combined deep learning is reported. Two subnetworks composed of convolutional neural networks are trained by Pytorch. By using the feature extraction capabilities of the two subnetworks and combining the bilinear join operation, the fine‐grained features of the image are obtained. The experimental results show that the accuracy has reached up 99.20%, and the training time is obviously reduced with the speed of defect detection about 0.0795 s/image. It indicates that BLNN has the ability to improve the accuracy of defect recognition and has a potential application in the detection of wood knot defects.
[Retracted] English Grammar Detection Based on LSTM‐CRF Machine Learning Model
Authors: Wu Liqin , Pan Meisen
Published: August 2021

Deep learning and neural network have been widely used in the field of speech, vocabulary, text, pictures, and other information processing fields, which has achieved excellent research results. Neural network algorithm and prediction model were used in this paper for the study and exploration of English grammar. Aiming at the application requirements of English grammar accuracy and standardization, we proposed a machine learning model based on LSTM‐CRF to detect and analyze English grammar. This paper briefly summarized the development trend of deep learning and neural network algorithm and designed the structure pattern of radial basis function neural network in grammar semantic detection and analysis on the basis of deep learning artificial neural network theory. Based on the morphological features of English grammar, a grammar database was established according to the rules of English word segmentation. In this paper, we proposed an improved conditional random field CRF (Conditional Random Field) network model based on LSTM (Long Short‐Term Memory) neural network. It can improve the problem that the traditional machine learning model relies on feature point selection in English grammar detection. The machine learning model based on LSTM‐CRF was used to recognize English grammar text entities. The results show that the English grammar detection system based on the LSTM‐CRF model can simplify the process structure in the recognition process, reduce the unnecessary operation cycle, and improve the overall detection accuracy.
Model Predictive Control for Automatic Carrier Landing with Time Delay
Authors: Cui Kaikai , Han Wei , Liu Yujie , Wang Xinwei , Su Xichao , Liu Jie
Published: August 2021

This paper focuses on the problem of automatic carrier landing control with time delay, and an antidelay model predictive control (AD-MPC) scheme for carrier landing based on the symplectic pseudospectral (SP) method and a prediction error method with particle swarm optimization (PE-PSO) is designed. Firstly, the mathematical model for carrier landing control with time delay is given, and based on the Padé approximation (PA) principle, the model with time delay is transformed into an equivalent nondelay one. Furthermore, a guidance trajectory based on the predicted trajectory shape and position deviation is designed in the MPC framework to eliminate the influence of carrier deck motion and real-time error. At the same time, a rolling optimal control block is designed based on the SP algorithm, in which the steady-state carrier air wake compensation is introduced to suppress the interference of the air wake. On this basis, the PE-PSO delay estimation algorithm is proposed to estimate the unknown delay parameter in the equivalent control model. The simulation results show that the delay estimation error of the PE-PSO algorithm is smaller than 2 ms, and the AD-MPC algorithm proposed in this paper can limit the landing height error within ±0.14 m under the condition of multiple disturbances and system input delay. The control accuracy of AD-MPC is much higher than that of the traditional pole assignment algorithm, and its computational efficiency meets the requirement of real-time online tracking.
Shenfu Injection: A Famous Chinese Prescription That Promotes HCN4 Activity in Bone Marrow Mesenchymal Stem Cells
Authors: Zhao Xinjun , Chu Qingmin , Wu Wei , Wu Hui , Wang Song , Qing Lijin , Zhou Xiaoxiong , Luo Zhiyun , Kang Liang , Li Rong
Published: August 2021

We investigated the effects of Shenfu Injection (SFI) on HCN4 activity in bone marrow mesenchymal stem cells (BMSCs). The sample of BMSCs was divided into six groups: a control group, a high-dose SFI group (0.25 ml/ml), a middle-dose SFI group (0.1 ml/ml), a low-dose SFI group (0.05 ml/ml), an adenovirus-encoded control vector group, and an adenovirus-encoded HCN4 group. Cell ultrastructure was observed using a transmission electron microscope. Quantitative reverse transcription PCR (RT-qPCR) was performed to detect HCN4 expression, and HCN4 activity was detected using the whole-cell patch clamp technique. An enzyme-linked immunosorbent assay was performed to detect cAMP content. Application of flow cytometry confirmed that the isolated cells showed BMSC-like phenotypes. Differentiation of BMSCs in both the SFI and the adenovirus-encoding HCN4 groups occurred according to the cellular ultrastructure. Application of the whole-cell patch clamp technique revealed that SFI could activate the inward pacing current of BMSCs in a concentration-dependent manner. The RT-qPCR results showed that HCN4 expression was significantly higher in the high-dose SFI group than in the medium- and low-dose groups, whereas the cAMP content in the overexpressed HCN4 group decreased significantly; this content in the high-dose SFI group increased significantly. In conclusion, SFI promotes HCN4 activity in BMSCs, which could explain its treatment effect when administered to patients with cardiovascular diseases.
On the Kampé de Fériet Hypergeometric Matrix Function
Authors: Verma Ashish , Younis Jihad , Aydi Hassen
Published: August 2021

In this study, we derive recursion formulas for the Kampé de Fériet hypergeometric matrix function. We also obtain some finite matrix and infinite matrix summation formulas for the Kampé de Fériet hypergeometric matrix function.
High mRNA Expression of CENPL and Its Significance in Prognosis of Hepatocellular Carcinoma Patients
Authors: Cui Zhongyuan , Xiao Lijia , Chen Fengsui , Wang Jielong , Lin Haiyan , Li Dongliang , Wu Zhixian
Published: August 2021

Centromere proteins (CENPs) are the main constituent proteins of kinetochore, which are essential for cell division. In recent years, several studies have revealed that several CENPs were aberrantly expressed in hepatocellular carcinoma (HCC). However, numerous centromere proteins have not been studied in HCC. In this study, we used databases of Oncomine, Gene Expression Profiling Interactive Analysis (GEPIA), the Kaplan-Meier Plotter, cBioPortal, the Human Protein Atlas (HPA), and TIMER (Tumor Immune Estimation Resource) and immunohistochemical staining of clinical specimens to investigate the expression of 15 major centromere proteins in HCC to evaluate their potential prognostic value. We found that the mRNA levels of 4 out of 15 centromere proteins (CENPL, CENPQ, CENPR, and CENPU) were significantly higher in HCC than in normal tissues, and their mRNA levels were associated with the tumor stages (

p

values < 0.01). Patients with higher mRNA levels of CENPL had poorer overall survival, progression-free survival, relapse-free survival, and disease-specific survival (

p

values < 0.05). Furthermore, the higher levels of CENPL mRNA were associated with worse overall survival in males without hepatitis virus infection (

p

values < 0.05). The protein expression level of CENPL in human HCC tissue was higher than that in normal liver tissue. In addition, the expression of CENPL was positively correlated with the levels of the tumor-infiltrating lymphocytes. The results suggest that the high mRNA expression of CENPL may be a potential predictor of prognosis in HCC patients.