bluuebunny/crossref_metadata_2025 huggingface dataset:
Problems and Countermeasures of China’s Greenway Economic Development from the Perspective of Computer Internet
Authors: Zhang Shuping
Published: August 2022

Given the advantages of urban greenways (UGCs) to urban populations’ health and well-being, the growing usage of UGCs has gotten a lot of attention. However, most studies on UGCs have been undertaken in Western nations, but the understanding of greenway usage in underdeveloped countries is scarce. China’s current environmental change in urban enhancement has been emphasized by a rush of urban green projects. The greenway is a kind of green infrastructure that has lately been the focus of many municipal governments. The federal government’s new, ecologically friendly approach to urbanization is the subject of this article, which offers a preliminary assessment of the role played by greenways in that strategy. UGCs are green landscape routes designed for walkers and bicycles in cities, according to landscape design. A growing number of regions and cities in China are participating in the development of UGC, with some projects meeting their goals on an annual basis. UGCs are being built in China; however, a number of challenges exist, including a lack of legal basis, the public’s incorrect understanding of UGCs, and insufficient scientific investigation. According to research on UGC construction and analysis of the peculiarities of various urban developments, the article highlighted current challenges in China’s UGC construction and provided corresponding remedies in order to enhance China’s UGC construction. In this survey, we performed statistical analysis using the chi-square test as well as the ANOVA test.
[Retracted] Relationship between Urban Landscape Design and Ecological Environment Protection in the Application of Environmental Protection and Renewable New Energy Materials
Authors: Wu Shengnan , Yu Xiwen , Cao Yejun , Wang Guangrong
Published: August 2022

With the economic growth in recent years, urban construction has also developed rapidly. In developing countries, the pursuit of rapid development has also brought about huge energy consumption, energy shortage, and environmental pollution. It is urgent to find and develop renewable energy. In order to understand the role of renewable energy materials in urban landscape design and ecological environment protection, replace nonrenewable materials with renewable energy materials, and reduce urban pollution, we analyze the available energy for buildings in urban areas and optimize the allocation of various available resources. Energy, improve energy efficiency, so as to save energy, protect the environment, and coordinate the development of energy, economy, and environment. Renewable energy is also known as alternative energy, sustainable energy, or nontraditional energy. It is energy that can be obtained from nature and can be replenished naturally. Experimental results prove that the energy required for traditional material consumption is much higher than the consumption of renewable energy, and its range is more than 50%. Renewable energy can replace the role of nonrenewable energy. This article hopes to stimulate more relevant architects to think about this subject through the research and analysis of renewable energy.
Navigation Control Method of Indoor Mobile Robot Based on Visual Servo
Authors: Huang Chongfu , Zhang Wei
Published: August 2022

In order to improve the navigation control effect of indoor mobile robot, this paper studies the navigation control method of indoor mobile robot combined with visual servo technology. For the problem that the target may be out of the camera’s field of view during the servo process, a control algorithm with field-of-view constraints is proposed, which assigns a certain weight to the image feature error at each moment. Moreover, this paper realizes the servo process that the image features are always located in the field of view by setting the variable values involved in the weight value calculation method. Through the simulation test, it is verified that the indoor mobile robot navigation control method based on visual servo has certain effects.
The Effects of Minor Element Addition on the Structural Heterogeneity and Mechanical Properties of ZrCuAl Bulk Metallic Glasses
Authors: Sivaraman R. , Patra Indrajit , Najm Zainab Mohsen , Hameed Noora M. , Alawsi Taif , Hashemi Seyedmasoud
Published: August 2022

The present study reveals the role of Nb and Ni minor addition on the nanomechanical properties and nanostructure of ZrCuAl bulk metallic glass (BMG). For this purpose, atomic force microscopy (AFM) was used to evaluate the viscoelastic response of the BMG surface at the nanoscale, while the nanoindentation technique was applied to show the mechanism of plastic deformation. The results indicated that minor Nb addition decreased the relaxation of enthalpy accompanied by the weakening of structural heterogeneity. On the other hand, Ni addition improved the stored energy of the material and intensified the distribution of loosely packed regions in the microstructure. Moreover, the mechanical test unveiled that Ni addition enhanced the viscoelastic response; however, it came at the expense of creep resistance. The evaluation of the magnitude of the derivative in the nanoindentation test also demonstrated that the Ni-added sample exhibited a multiple shear-band mode for plastic deformation.
Ptr4BERT: Automatic Semisupervised Chinese Government Message Text Classification Method Based on Transformer-Based Pointer Generator Network
Authors: Li Mingxin , Yin Kaiqian , Wang Minghao
Published: August 2022

With the development of Internet technology, government affairs can be handled online. More and more citizens are using online platforms to report to government departments, which is generating a lot of textual data. Among them, the basic but important problem is to automatically classify the different categories of messages, so that staff from different departments can process relevant information quickly. However, government messages have problems such as fast update rate, a large amount of information, long texts, and difficulty in capturing key points, which make supervised learning methods unsuitable for processing such texts. To address these problems, we propose a semisupervised text classification method based on a transformer-based pointer generator network named Ptr4BERT, which uses the pointer generator network with BERT(bidirectional encoder representation from transformers) embedding as a preprocessor for feature extraction. In this method, text classification can achieve very good results with a small set of labeled data, by extracting features exclusively from the message text. In order to verify the effect of our proposed model, we performed some experiments. Besides, we designed a crawler program and obtained two datasets from different websites, which are named HNMes and QDMes. Experimental results have shown that the proposed method outperforms the state-of-the-art methods significantly.
Blasting Law of Liquid CO2 Phase Change in Coal Mine Based on Numerical Simulation
Authors: Fang Bo
Published: August 2022

In order to obtain the best CO2 blasting drilling efficiency and improve the gas permeability coefficient of the coal seam in the mining area, a research method of liquid CO2 phase change blasting in the coal seam based on electrochemical numerical simulation is proposed. In this paper, the electrochemical numerical simulation of coalbed methane caused by liquid CO2 phase change blasting is studied through theoretical analysis, the antireflection mechanism of liquid carbon dioxide gas explosion on broken coal seam is obtained, and the initial fracture length of coal body caused by gas explosion stress wave is deduced by the mathematical model. A method for improving CBM desorption with nonmechanical coal was proposed, namely, a method for electrochemically strengthening CBM desorption. A comprehensive theory and application system of liquid carbon dioxide phase change gas explosion and anti-reflection technology are established by combining theoretical analysis, experimental research, and numerical simulation with field industrial comparative experiment. According to the gas tracing method, the precise measurement of the working face shows that the impact radius of the collision caused by the explosion of the liquid carbon dioxide phase change gas is 2 m. Gas emissions increased the emissions of coal seam drilling in the affected areas by 4 to 8 times, and the gas emission attenuation coefficient decreased from 0.76 times to 0.93 times. The carbon dioxide phase change gas cracking theory and antireflection theory and their application technology system are systematically studied. The research shows that the liquid carbon dioxide phase transfer gas blasting and infiltration technology is not limited by the geological conditions of the coal seam and has the characteristics of high efficiency and inherent climate. In view of the wide area of coal mines and the harsh geological conditions of coal seams, carbon dioxide phase change gas-induced cracking antireflection technology has application prospects and expandability.
Modified Homotopy Perturbation Method and Approximate Solutions to a Class of Local Fractional Integrodifferential Equations
Authors: Xu Bo , Zhang Sheng
Published: August 2022

In this paper, the local fractional version of homotopy perturbation method (HPM) is established for a new class of local fractional integral-differential equation (IDE). With the embedded homotopy parameter monotonously changing from 0 to 1, the special easy-to-solve fractional problem continuously deforms to the class of local fractional IDE. As a concrete example, an explicit and exact Mittag–Leffler function solution of one special case of the local fractional IDE is obtained. In the process of solving, two initial solutions are selected for the iterative operation of local fractional HPM. One of the initial solutions has a critical condition of convergence and divergence related to the fractional order, and the other converges directly to the real solution. This paper reveals that whether the sequence of approximate solutions generated by the iteration of local fractional HPM can approach the real solution depends on the selection of the initial approximate solutions and sometimes also depends on the fractional order of the selected initial approximate solutions or the considered equations.
Adaptive and Personalized Web Blog Searching Technique Using S-ANFIS
Authors: Khatter Harsh , Malik Pooja , Jyoti Amrita , Ahlawat Anil Kumar , Dubey Gaurav , Mishra Anurag , Neupane Sanjeev Chandra
Published: August 2022

Day by day, the number of blog users and microblog users is increasing worldwide. It is easy to say that blogs have captured a significant portion of other web services. In the past few years, the number of users has exponentially increased. User count of Facebook, Twitter, and Instagram applications is not hidden from anyone. Users on such platforms share ideas, experiences, stories, opinions, and views and want to interact with people with the same set of interests. As per the user’s expectation, there is a requirement of two things: content curation and recommendations. The content curation algorithm will find the people and their posts on personalized search results. In addition, the recommendation system will help to find the most appropriate match to interact with. In this paper, both approaches are combined to show the user’s curated and recommended results. The article focuses on the hybrid model named S-ANFIS, and the results are compared with the well-known approaches like ANN, Deep Neural Network (DNN), and Recurrent Neural Network (RNN).
Financing Efficiency Calculation of Energy Enterprises Based on Internet of Things
Authors: Wu JingJing , Zhang YaJuan
Published: August 2022

In order to conduct a special study on the financing efficiency of a certain industry, the authors propose a method for calculating the financing efficiency of energy enterprises based on the Internet of Things. Combining the DEA method with the Bootstrap method, taking the IoT data of 30 SME boards and 30 energy companies listed on the ChiNext listed in 2010 as a research sample, and using R language and Deap2.1 software, the financing efficiency from 2011 to 2015 is calculated. Experimental results show that from 2011 to 2015, only 28.3% of the enterprises reached the effective state of technical efficiency on average, and the financing efficiency of energy enterprises was generally inefficient. The pure technical efficiency value of the whole enterprise decreases year by year, and its technical efficiency value lower than its scale efficiency is the main reason that its technical efficiency is generally not high.
Image Effect Observation of Acanthopanax senticosus on Antifatigue Activity after Exercise
Authors: Zhang Xiangdong , Zhu Wanning
Published: August 2022

In order to explore the effect of Acanthopanax senticosus on antifatigue activity after exercise, this paper proposes an image effect observation based on the effect of Acanthopanax senticosus on antifatigue activity after exercise. This method recommends key technical problems and solutions based on the information represented by image effect observation and explores the influence of Acanthopanax senticosus on antifatigue after exercise. Through the retrospective analysis of certain personnel, it is shown that the image effect observation based on the influence of Acanthopanax senticosus on the antifatigue activity after exercise is about 25% more accurate than the traditional method. Most of the active ingredients of Acanthopanax senticosus have phenolic hydroxyl groups, which can resist oxidation, fatigue, focus attention, and reduce work mistakes. This experiment shows that after sleep deprivation, the antioxidant capacity of the body decreases with time. Acanthopanax senticosus extract can significantly improve the above symptoms and fight fatigue.
A Novel Prognostic Nomogram and Risk Classification System for Predicting Cancer-Specific Survival of Postoperative Fibrosarcoma Patients: A Large Cohort Retrospective Study
Authors: Huang Chao , Huang Zhangheng , Zhou Zongke
Published: August 2022

Background. Fibrosarcoma (FS) is a typically invasive sarcoma formed by fibroblasts and collagen fibers. Currently, the standard treatment for FS is the surgical resection, but the high recurrence rate and poor prognosis limit the benefits of postoperative patients. Exploring what factors affect the benefit of postoperative patients is significant for guiding the implementation of surgical resection. Therefore, this study aims to construct a novel nomogram to predict the cancer-specific survival (CSS) of postoperative fibrosarcoma (POFS) patients. Methods. The included patients were randomly assigned to the training and validation sets at a ratio of 7 : 3. CSS was indexed as the research endpoint. Firstly, univariate and multivariate Cox regression analyses were used on the training set to determine independent prognostic predictors and build a nomogram for predicting the 1-, 3-, and 5-year CSS of POFS patients. Secondly, the nomogram's discriminative power and prediction accuracy were evaluated by receiver operating characteristic (ROC) and the calibration curve, and a risk classification system for POFS patients was constructed. Finally, the nomogram's clinical utility was evaluated using decision curve analysis (DCA). Results. Our study included 346 POFS patients, divided into the training (244) and validation sets (102). Multivariate Cox regression analysis demonstrated that tumor size, SEER stage, and tumor grade were independent prognostic predictors of CSS for POFS patients. They were used to create a nomogram. In the training and validation sets, the ROC curve showed that the 1-, 3-, and 5-year area under the curve (AUC) were higher than 0.700, indicating that the nomogram had good reliability and accuracy. DCA also showed that the nomogram has high application value in clinical practice. Conclusion. The larger tumor size, higher tumor grade, and distant metastasis were independently related to the poor prognosis of POFS patients. The nomogram constructed based on the above variables could accurately predict the 1-, 3-, and 5-year CSS of POFS patients. So, the nomogram and risk classification system we built might help make accurate judgments in clinical practice, optimize patient treatment decisions, maximize postoperative benefits, and ultimately improve the prognosis of POFS patients.
Bayesian Approach for Confidence Intervals of Variance on the Normal Distribution
Authors: Araveeporn Autcha
Published: August 2022

This research aims to compare estimating the confidence intervals of variance based on the normal distribution with the primary method and the Bayesian approach. The maximum likelihood is the well-known method to approximate variance, and the Chi-squared distribution performs the confidence interval. The central Bayesian approach forms the posterior distribution that makes the variance estimator, which depends on the probability and prior distributions. Most introductory prior information looks for the availability of the prior distribution, informative prior distribution, and noninformative prior distribution. The gamma, Chi-squared, and exponential distributions are defined in the prior distribution. The informative prior distribution uses the Markov Chain Monte Carlo (MCMC) method to draw the random sample from the posterior distribution. The Fisher information performs the Wald confidence interval as the noninformative prior distribution. The interval estimation of the Bayesian approach is obtained from the central limit theorem. The performance of these methods considers the coverage probability and minimum value of the average width. The Monte Carlo process simulates the data from a normal distribution with the true parameter of mean and several variances and the sample sizes. The R program generates the simulated data repeated 10,000 times in each situation. The results showed that the maximum likelihood method employed on the small sample sizes. The best confidence interval estimation was when sample sizes increased the Bayesian approach with an available prior distribution. Overall, the Wald confidence interval tended to outperform the large sample sizes. For application in real data, we expressed the reported airborne particulate matter of 2.5 in Bangkok, Thailand. We used the 10–1000 records to estimate the confidence interval of variance and evaluated the interval width. The results are similar to those of the simulation study.
An Optimal Algorithm for Renewable Energy Generation Based on Neural Network
Authors: Zhao Weihua , Khan Imran , Akhtar Shelily F. , Al-Dhaifallah Mujahed
Published: August 2022

Solar energy is a costless and readily available form of energy that has shown to be one of the cleanest and most plentiful renewable energy sources. Various large-scale solar photovoltaic (PV) facilities are being utilized to minimize pollution and carbon emissions generated by fossil energy in many nations across the world. The power sequence of PV is influenced by a variety of diverse variables, and it is very unpredictable and volatile. Unlike the distributed PVs, the centralized PVs have the same intensity and location. The obstruction of clouds causes minor variations in the output power of the PV, making the power forecasting more difficult. To solve the aforementioned difficulties, this article provides a new neural network-based technique for PV power optimization and forecasting. The first stage is to create a cloud trajectory tracking system based on cloud photos taken from the ground. Second, a cloud trajectory tracking-based irradiance coefficient prediction model was built. Then, to increase forecast accuracy, build an error correcting model. For verification, data from a centralized solar power station was used. The results show that the proposed algorithm has technological applications and may greatly improve prediction accuracy.
The Regulation of miR-206 on BDNF: A Motor Function Restoration Mechanism Research on Cerebral Ischemia Rats by Meridian Massage
Authors: Shi Guofeng , Zeng Ping , Zhao Qing , Zhao Jinju , Xie Yunhui , Wen Danguo , Yan Lu , Gu Hao , Ma Shuai , Cai Xiongwei
Published: August 2022

As a frequent disease affecting the nervous system, cerebral infarction has emerged as a major cause of disability and elicits disorders in motor, sensation, and cognition as sequelae. No clear mechanism has been known in meridian massage despite it having been proved to be an effective therapeutic option. The study was carried out to explore the treatment of meridian massage on cerebral ischemia in rats and its effects on motor function restoration and nerve cell’s ultrastructure in the ischemic territory. The alleviated nerve damages and recovered injured brain tissues were found in the cerebral infarction model of SD rats after meridian massage. Expressions of miR-206 and the brain-derived neurotrophic factor (BDNF) in the gastrocnemius muscle were all well observed. The effects of miR-206 on BDNF were testified by overexpressed and interfered miR-206 in the C2C12 myoblast. Moreover, at the molecular level, meridian massage downregulated miR-206 expression at an elevated level of BDNF. Consequently, meridian massage exerts a vital role in promoting cerebral ischemia restoration, which is expected to provide an addition to the application of traditional Chinese medicine (TCM) in the reconstruction and treatment of cerebral ischemia.
An Ensemble Semantic Textual Similarity Measure Based on Multiple Evidences for Biomedical Documents
Authors: Li Meijing , Zhou Xianhe , Ryu Keun Ho , Theera-Umpon Nipon
Published: August 2022

With the increasing volume of the published biomedical literature, the fast and effective retrieval of the literature on the sequence, structure, and function of biological entities is an essential task for the rapid development of biology and medicine. To capture the semantic information in biomedical literature more effectively when biomedical documents are clustered, we propose a new multi-evidence-based semantic text similarity calculation method. Two semantic similarities and one content similarity are used, in which two semantic similarities include MeSH-based semantic similarity and word embedding-based semantic similarity. To fuse three different similarities more effectively, after, respectively, calculating two semantic and one content similarities between biomedical documents, feedforward neural network is applied to integrate the two semantic similarities. Finally, weighted linear combination method is used to integrate the semantic and content similarities. To evaluate the effectiveness, the proposed method is compared with the existing basic methods, and the proposed method outperforms the existing related methods. Based on the proven results of this study, this method can be used not only in actual biological or medical experiments such as protein sequence or function analysis but also in biological and medical research fields, which will help to provide, use, and understand thematically consistent documents.
A Novel Routing Protocol for Low-Energy Wireless Sensor Networks
Authors: Suresh Sebastin , Prabhu V. , Parthasarathy V. , Boddu Rajasekhar , Sucharitha Yadala , Teshite Gemmachis
Published: August 2022

The battery power limits the energy consumption of wireless sensor networks (WSN). As a result, its network performance suffered significantly. Therefore, this paper proposes an opportunistic energy-efficient routing protocol (OEERP) algorithm for reducing network energy consumption. It provides accurate target location detection, energy efficiency, and network lifespan extension. It is intended to schedule idle nodes into a sleep state, thereby optimising network energy consumption. Sleep is dynamically adjusted based on the network’s residual energy (RE) and flow rate (FR). It saves energy for a longer period. The sleep nodes are triggered to wake up after a certain time interval. The simulation results show that the proposed OEERP algorithm outperforms existing state-of-the-art algorithms in terms of accuracy, energy efficiency, and network lifetime extension.
Multicriteria Model for Shared Parking and Parking Route Recommender Systems
Authors: Zhao Pengfei , Wei Lingxiang , Pan Dong , Dong Shuai
Published: August 2022

In many congested areas, shared parking has gotten increasing attention because of its potential to alleviate parking resource shortages. However, managing parking resources remains a challenge when simultaneously considering multiple decision-making criteria of public travelers in allocating parking spaces and recommending optimal parking routes. To fill this gap, from four perspectives, i.e., driving, among shared parking lots, at a shared parking lot, between shared parking spaces and destinations, we proposed nine criteria for shared parking space allocations and parking route recommendations, and we also gave the quantitative models for different criteria. Furthermore, an analytic hierarchy process Entropy-TOPSIS grey relational analysis (AHP-Entropy-TOPSIS-GRA) method and an improved ant colony algorithm were proposed to solve the proposed allocation of parking spaces and recommend optimal parking routes, respectively. Finally, the validity of our proposed models and algorithms was tested by empirical parking data and road traffic data collected in Huai’an City, Jiangsu province, China. The research helps provide a theoretical foundation for implementing shared parking initiatives and improving public travelers’ parking satisfaction.
An Immune-Related Genetic Feature Depicted the Heterogeneous Nature of Lung Adenocarcinoma and Squamous Cell Carcinoma and Their Distinctive Predicted Drug Responses
Authors: Li Qiuyuan , Jiang Yan , Song Nan , Zhou Bin , Li Zhao , Lin Lei
Published: August 2022

One of the primary causes of global cancer-associated mortality is lung cancer (LC). Current improvements in the management of LC rely mainly on the advancement of patient stratification, both molecularly and clinically, to achieve the maximal therapeutic benefit, while most LC screening protocols remain underdeveloped. In this research, we first employed two algorithms (ESTIMATE and xCell) to calculate the immune/stromal infiltration scores. This helped identify the altered immune infiltration landscapes in lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC). Afterward, based on their immune-related characteristics, we successfully stratified the LUAD and LUSC into 2 and 3 clusters, respectively. Different from the conventional bioinformatic approaches that start from the investigation of differential expression of single genes, differentially enriched curated gene sets identified through gene set variation analyses (GSVA) were curated, and gene names were reconstructed afterward. Furthermore, weighted gene correlation network analyses (WGCNA) were used to reveal hub genes highly connected with the clustering process. Actual expression levels of critical hub genes among different clusters were compared and so were the functional pathways these genes enriched into. Lastly, a computational method was applied to predict and compare the responses of each cluster to primary therapeutic agents. The heterogeneity presented in our study, along with the drug responses expected for identified clusters, may shed light on future exploration of combination immunochemotherapy that facilitates the optimization of individualized therapy.
Parameterized

H

∞

Controller Design for Switched Polynomial Hamiltonian Systems Subject to Actuator Saturation
Authors: Zhu Huawei
Published: August 2022

This paper is concerned with the global asymptotical stabilization and

L

2

disturbance attenuation problem for the switched polynomial Hamiltonian systems subject to actuator saturation. To achieve the above objective, a parameterized controller is designed and a parameter solution algorithm is presented. Compared with the controller designed with the existing method, the parameterized controller has greater functionality. By choosing an appropriate value for the parameter according to its obtained feasible interval value, a better performance can be achieved. At last, two numerical examples are provided to verify the effectiveness of the proposed approach.
An Empirical Analysis of Piano Performance Skill Evaluation Based on Big Data
Authors: Zhang Yuyu
Published: August 2022

Teachers often guide the rhythm and coherence of piano performance in the teaching process. It is of great significance to use computer technology to automatically evaluate piano performance skills. In this paper, computer technology is used to automatically evaluate the accuracy of piano music classification based on the high-dimensional data collaborative filtering recommendation algorithm, and the K-means model algorithm is used for comparative testing. By comparing the classification results of the high-dimensional data collaborative filtering recommendation algorithm with the piano music classification results of the K-means algorithm, the piano learning burden can be reduced and the piano learning effect can be improved. The research results of this paper show that the accuracy rate of the automatic piano performance evaluation system based on the high-dimensional data collaborative filtering recommendation algorithm reaches 95%, which has a good evaluation effect.
The Relationship between Serum CXCL8 and ET-1 Expression Levels and Sepsis Complicated with Heart Failure
Authors: Zhu Jianlong , Song Changjun , Cai Tingting , Yi Lulu , Zhang Wei , Zhong Jing , Shen Meirong
Published: August 2022

Objective. The objective is to investigate the relationship between sepsis complicated with heart failure and the expression levels of CXC chemokine ligand 8 (CXCL8) and endothelin-1 (ET-1). Methods. A total of 128 sepsis patients accepted by the Ganzhou People’s Hospital from March 2019 to December 2021 were collected as observation objects, and they were separated into a simple sepsis group (86 cases) and a complicated heart failure group (42 cases) according to whether they were accompanied by heart failure or not. General data such as Sequential Organ Failure Assessment (SOFA) score and Acute Physiology and Chronic Health Evaluation II (APACHE II) were collected; the expression levels of serum CXCL8 and ET-1 were detected by enzyme-linked immunosorbent assay (ELISA); the cardiac function parameters such as left ventricular ejection fraction (LVEF), stroke volume (SV), cardiac output (CO), and cardiac index (CI) were measured by color Doppler ultrasound; the correlation between serum CXCL8 and ET-1 expression levels with clinical data and cardiac function parameters in patients with sepsis complicated with heart failure was analyzed by the Pearson correlation; and the influencing factors of sepsis complicated with heart failure were analyzed by the logistic regression analysis. Results. The serum CXCL8 and ET-1 expression levels, SOFA score, and APACHE II score in the complicated heart failure group were higher than those in the simple sepsis group (

P
<
0.05

), and LVEF, SV, CO, and CI in the complicated heart failure group were lower than those in the simple sepsis group (

P
<
0.05

). Serum CXCL8 was positively correlated with ET-1 in patients with sepsis complicated with heart failure (r = 0.531,

P
<
0.05

), and the two were positively correlated with SOFA score and APACHE II score (

P
<
0.05

) and were negatively correlated with LVEF, SV, CO, and CI (

P
<
0.05

). CXCL8 and ET-1 were independent risk factors for sepsis complicated with heart failure (

P
<
0.05

). Conclusion. The expression levels of serum CXCL8 and ET-1 in sepsis patients with heart failure are significantly increased, and both are risk factors for heart failure in sepsis patients.
Adaptive Super-Twisting Cooperative Guidance Law with Fixed-Time Convergence
Authors: Li Xiaojing , Ma Jianwei , Gao Jiwei , Zang Shaofei
Published: August 2022

For the guidance problem of multiple missiles cooperatively intercepting a maneuvering target, fixed-time cooperative guidance law is proposed with impact angle constraints. First, fixed-time consensus, integral sliding mode technique, and adaptive super-twisting algorithm are implemented to construct cooperative guidance law along the line-of-sight (LOS) direction. Second, based on fixed-time convergence observer and terminal sliding mode control, one fixed-time guidance law along the normal direction of LOS is designed to ensure that the missiles attack the target with expected angles. Finally, simulation results are carried out to demonstrate the effectiveness of the proposed fixed-time cooperative guidance law.
A Consensus Algorithm Based on Risk Assessment Model for Permissioned Blockchain
Authors: Zhang Xiaohui , Xue Mingying , Miao Xianghua
Published: August 2022

Blockchain is characterized by privacy, traceability, and security features as a novel framework of distributed ledger technologies. Blockchain technology enables stakeholders to conduct trusted data sharing and exchange without a trusted centralized institution. These features make blockchain applications attractive to enhance trustworthiness in very different contexts. Due to unique design concepts and outstanding performance, blockchain has become a popular research topic in industry and academia in recent years. Every participant is anonymous in a permissionless blockchain represented by cryptocurrency applications such as Bitcoin. In this situation, some special incentive mechanisms are applied to the permissionless blockchain, such as “mined” native cryptocurrency to solve the trust issues of the permissionless blockchain. In many use cases, permissionless blockchain has bottlenecks in transaction throughput performance, which restricts further application in the real world. A permissioned blockchain can reach a consensus among a group of entities that do not establish an entire trust relationship. Unlike permissionless blockchains, the participants must be identified in permissioned blockchains. By relying on the traditional crash fault-tolerant consensus protocols, permissioned blockchains can achieve high transaction throughput and low latency without sacrificing security. However, how to balance the security and consensus efficiency is still the issue that needs to be solved urgently in permissioned blockchains. As the core module of blockchain technology, the consensus algorithm plays a vital role in the performance of the blockchain system. Thus, this paper proposes a new consensus algorithm for permissioned blockchain, the Risk Assessment-based Consensus (RAC) protocol, combined with the decentralized design concept and the risk-node assessment mechanism to address the unbalance issues of performance in speed, scalability, and security.
[Retracted] The Protective Effect of Sulodexide on Acute Lung Injury Induced by a Murine Model of Obstructive Jaundice
Authors: Ma Penglei , Long Yue , Fu Qiang , Liu Yanhong , Yang Yitian , Zhao Weixing , Liu Qiangwei , Li Yang , Mi Weidong
Published: August 2022

Introduction. The effect of sulodexide (SLX) on obstructive jaundice‐ (OJ‐) induced acute lung injury (ALI) in rats was examined in this study. Methods. In this study, 48 rats were randomly assigned to one of six groups: sham, OJ, OJ+saline, OJ+SLX (0.5 mg/ml/d), OJ+SLX (1 mg/ml/d), and OJ+SLX (2 mg/ml/d). The pathological lung injury was assessed by histological analysis and lung injury grading. ELISA kits were used to evaluate the expression of IL‐6, IL‐1, TNF‐α, and syndecan‐1 (SDC‐1) in bronchoalveolar lavage fluids (BALFs). Commercial assay kits were performed to evaluate malondialdehyde (MDA) production and catalase (CAT) activity in lung tissues. The apoptosis was assessed by TUNEL assay. The lung microvascular permeability was investigated using Evans blue leakage, lung wet/dry weight (W/D) ratio, and lung permeability index (LPI). SDC‐1, claudin‐5, ZO‐1, and VE cadherin expression levels in lung tissues were measured using Western blot. Results. The OJ‐induced ALI rats showed severe lung injury. The value of IL‐6, IL‐1β, TNF‐α, and SDC‐1 in BALFs was remarkedly increased in the OJ group. MDA content, apoptotic area, apoptotic molecules, and SDC‐1 level were all higher in the OJ group’s lung tissues than in the sham group. CAT activity, Evans blue leakage, W/D ratio, LPI, and expression of claudin‐5, ZO‐1, and VE cadherin were all lower in the OJ group compared to the sham group. The degenerative alterations in lung tissue improved after 7 days of treatment with 2 mg/ml SLX. The BALFs had lower amounts of IL‐6, IL‐1, TNF‐α, and SDC‐1. The SLX therapy reduced MDA levels while restoring CAT activity. In lung tissues, SLX reduced apoptotic area and SDC‐1 expression. SLX reduced lung microvascular permeability by raising the expression of Claudin‐5, ZO‐1, and VE‐cadherin in lung tissue when compared to the OJ group. Conclusion. The results suggested that SLX attenuates OJ‐induced ALI in rats by protecting the pulmonary microvascular endothelial barrier.
[Retracted] Application of Multimode Learning Environment Based on the Internet in College English Teaching
Authors: Long Xiaohua
Published: August 2022

With advancements in information technology taking place every day, the current methods of college English teaching are facing unprecedented great challenges. Meanwhile, most college teachers still use obsolete teaching methods in their practice. It seems like IT development offers both benefits and frustration to college English teaching. That is why the reform in a multimode direction is extremely urgent and necessary. It will be key to improving the quality and efficiency of education, meeting the needs of college students, and cultivating a beneficial learning environment based on the Internet. With the support of models of teaching theory, multimode learning theory, and multimodality theory, using statistical analysis and qualitative and quantitative research methods, this article tries to explore the application and practice of multimode learning based on the Internet in college English teaching. Besides, the article proves that, compared with the traditional teaching mode, the multimode teaching is more conducive to helping students grow learning interest, cultivating their autonomous learning ability, and thus improving their language competence.
Mechanism and Structural Parameter Optimization Method of Linear Energy-Gathering Cutting Device for Towering Steel Structures Based on Computational Intelligence
Authors: Zhou Xiaoguang
Published: August 2022

In the process of urban expansion, due to the advantages of high strength and light weight of steel frame structure, it has replaced concrete structure, and the construction technology of towering steel structure has been paid attention to by the construction industry. With the passage of time, steel structure also needs to be removed. In order to adapt to the efficient cutting of steel frame structures, this paper studies a new technology of linear energy-gathering cutting of towering steel structures based on computational intelligence methods. The research results of the article show the following: (1) The greater the penetration depth, the greater the setting of the cutter parameters. According to the experimental results, the designed towering steel structure cutter can smoothly cut more than 10 kinds of towering steel structure materials. It can be seen that the calculation results are basically accurate and the relative error of the calculation remains around 6%. (2) In the computational intelligent analysis method, the total stress is larger than that of the other two analysis methods, and the support stability force is slightly lower than the stress ratio of the direct analysis method, and the computational intelligent analysis method accounts for the largest axial force. (3) The cutting depth and slit width are different at different cutting speeds. When the cutting speed is 8, the cutting depth reaches the maximum value of 1.2300, and 90% of the experimental data errors can be controlled within 10%.
Abnormalities of the Default Mode Network Functional Connectivity in Patients with Insomnia Disorder
Authors: Xia Guangyuan , Hu Yongxue , Chai Fangxian , Wang Yiming , Liu Xingde
Published: August 2022

Objective. This paper aimed to probe changes in the default mode network (DMN) functional connectivity (DMNFC) of the brain of patients with insomnia disorder (ID) under the resting state. Methods. A total of 67 patients with ID and 67 graphically matched healthy controls were selected. Then, their general information was collected, followed by a psychological scale valuation. Resting state functional magnetic resonance imaging (rs‐fMRI) scanning was conducted. Subsequently, collected statistics were processed, bilateral precuneus and medial superior frontal gyrus were defined as regions of interest (ROI), and the difference in intensity between these two groups was compared. Results. Compared with the healthy control group, the patients in the ID group were observed with abnormalities of DMNFC. Specifically, a significant increase in the functional connectivity (FC) could be observed between the left medial superior frontal gyrus and left central anterior gyrus, the left medial superior frontal gyrus and anterior cingulate gyrus, the right medial superior frontal gyrus and left central anterior gyrus, the left anterior cuneiform and left central anterior/posterior gyrus, the left anterior cuneiform and left superior occipital gyrus, as well as the right anterior cuneiform and left central posterior gyrus. However, the FC between the left anterior cuneiform and the right middle frontal gyrus was weakened, as well as between the left anterior cuneiform and the right angle gyrus and between the right precuneus and the left inferior temporal gyrus. Conclusion. ID patients may suffer changes in FC. The decline of FC in DMN may be one of the underlying causes of ID; the enhancement of FC between DMN and the visual‐spatial attention network may play a key role in the mechanisms of impaired brain functional networks of ID.
Growth Kinetics of Zinc Sulphide Nanocrystals Synthesized by Colloidal Thermolysis of Fatty Acid Carboxylates
Authors: Mensah Michael. B. , Boadi Nathaniel O. , Awudza Johannes A. M.
Published: August 2022

Zinc sulphide (ZnS) is an important semiconductor with widespread electronic and catalytic applications. The growth kinetics of ZnS nanocrystals synthesized by the thermal decomposition of zinc ricinoleate carboxylates in an oleylamine:dodecanethiol (1 : 1) solvent mixture isreported. Crystalline sphalerite ZnS nanocrystals with quantum dot sizes of 2.3–5.3 nm were obtained at temperatures higher than 240°C. The p-XRD patterns showed a clear relationship between the crystallite sizes and the peak broadness at a temperature range of 250–300°C. The optical bandgap energies of the ZnS nanocrystals reduced from 4.27 eV to 3.73 eV as the time of reaction increased from 20 to 60 min at 250°C. The activation energy for the growth kinetics of the ZnS nanocrystals was determined to be 36.24 kJ/mol which compares closely to those reported in the literature for aqueous systems.
Identification of Necroptosis-Related miRNA Signature as a Potential Predictive Biomarker for Prognosis and Immune Status in Colon Adenocarcinoma
Authors: Ma Xiaomei , Yang Baoshun , Dong Hexiang , Lin Hao , Wang Weigang
Published: August 2022

Objective. Increasing studies suggest that necroptosis is correlated with tumor progression. And aberrant microRNA (miRNA) expression plays a vital role in various tumors. Thus, we are committed to exploring a necroptosis-associated miRNA signature to serve as a prognostic biomarker in colon adenocarcinoma (COAD). Data Sources and Methods. In the current study, The Cancer Genome Atlas (TCGA) database was used to download the miRNA and mRNA expression profiles and clinical information of samples. All patients were stochastically assigned to TCGA-train and TCGA-test clusters. Subsequently, we established a prognostic signature comprised of necroptosis-related miRNAs (NR-mis) via LASSO-Cox regression and then developed a nomogram signature composed of the prognostic signature and clinical factors. Corresponding prognostic values were evaluated. Functional analysis, tumor microenvironment (TME), and chemosensitivity of risk subgroups were also identified. Results. The prognostic signature based on miR-141-3p, miR-148a-3p, miR-16-5p, and miR-200a-5p was closely associated with overall survival (OS) of samples and tumor metastasis in COAD. The Area Under Curve (AUC) was 0.605, 0.721, and 0.752 in TCGA-train cluster , 0.661, 0.613, and 0.695 in the TCGA-test cluster at 1, 3, and 5 years, respectively. The C-index for nomogram signature was 0.754. Functional analysis showed the remarkable enrichment of the signature-dependent miRNAs in tumor progression and immune response. And two risk subgroups were correlated with the distinct immune infiltration and immune checkpoints. In addition, the high-risk subgroup is more sensitive to cisplatin, doxorubicin, etoposide, and gemcitabine. Conclusions. Necroptosis-related miRNAs play a crucial role in the prognosis, metastasis, immune status, and drug sensitivity in COAD.
Surface Casing Buckling Effect on the Wellhead Movement of a Subsea Well
Authors: de Souza Charlton O. , de Sousa José Renato M. , Ellwanger Gilberto B. , da Silva Emilio César C. M.
Published: August 2022

In this work, the wellhead axial movement of a subsea well was predicted with a previously presented multi-string model modified to account for a possible buckling of the well’s surface casing. This model represented the structural casing with a nonlinear spring that considers the casing-soil interaction using t-z curves with hysteretic behavior. In addition, the surface casing was modeled with a nonlinear spring that incorporates buckling deformation when the effective force is compressive and may be assumed not fully cemented due to, e.g., its long length, formation characteristics, or limitations of the rig. Finally, the other casing strings were represented with linear springs. Two case studies were conducted to verify the proposed model. In the first, the wellhead movements during each step of a simplified well’s construction and production were compared with those obtained in an equivalent beam-based FE model. Both models yielded the same results, encouraging the analysis of a second case, which investigated an actual well. In this case, the surface casing buckling led to considerable wellhead movement variations, consequently affecting the surface casing stress, especially in scenarios in which the structural casing’s bearing capacity was surpassed, highlighting the need to account for this phenomenon in the design of subsea wells.
Numerical Investigation of an Unsteady Blade Surface Blowing Method to Reduce Rotor Blade-Vortex Interaction Noise
Authors: Sun Yan , Xu Guohua , Shi Yongjie
Published: August 2022

This paper presents a numerical investigation of unsteady surface blowing using periodic variations of jet velocity with azimuthal angle to reduce helicopter rotor blade-vortex interaction (BVI) noise. The unsteady blowing is modeled as the mass flow outlet boundary condition of time-varying jet velocity on the blade surface grid using computational fluid dynamics. The same high-resolution overset grid system and flow/noise solver are used to perform a detailed flow field simulation and noise prediction for the nonblowing baseline case and the steady/unsteady blowing cases under the rotor BVI condition, and a grid convergence study for the steady and unsteady blowing cases is carried out. The BVI noise reduction and rotor thrust coefficient results of the unsteady blowing method and the previously published steady blowing with constant jet velocity are then compared. The noise reduction level of unsteady blowing is approximately equivalent to that of steady blowing (noise reduction is more than 3 dB). However, the loss in rotor thrust coefficient caused by unsteady blowing (3.3%) is only half of that by steady blowing (6.3%); the air mass cost by unsteady blowing is only 63.7% of that by steady blowing per rotation revolution. The results show that unsteady blowing can effectively reduce BVI noise with lower cost and less thrust loss.