bluuebunny/crossref_metadata_2025 huggingface dataset:
Internet penetration and multi‐product exporters: Firm‐level evidence from China
Authors: Ma Shuzhong , Hu Zengxi
Published: August 2022

This study explores the impact of Internet penetration on the firm‐product‐level behaviour of multi‐product exporters. While a substantial body of literature has explored the effect of the Internet on firm performance, especially extensive and intensive margins, few studies examine the product‐level behaviour within firms. Using highly disaggregated firm‐product‐level data covering Chinese manufacturing industrial firms from 2000 to 2007, we provide evidence on the effects of the Internet on product mix and product switching within firms. Specifically, because of the reduction in export market entry costs, the Internet can encourage more firms to enter the export market and increase market competition, which causes multi‐product exporters to skew exports towards best‐performing products and drop the products furthest away from its core competence. Meanwhile, the Internet can increase multi‐exporters' productivity and encourage firms to introduce new products, which are also further away from the core product. Productivity and competition cause multi‐product exporters to exhibit product switching, which results in the expansion of product scope.
Assessment of Exercise-Associated Gastrointestinal Perturbations in Research and Practical Settings: Methodological Concerns and Recommendations for Best Practice
Authors: Costa Ricardo J.S. , Young Pascale , Gill Samantha K. , Snipe Rhiannon M.J. , Gaskell Stephanie , Russo Isabella , Burke Louise M.
Published: August 2022

Strenuous exercise is synonymous with disturbing gastrointestinal integrity and function, subsequently prompting systemic immune responses and exercise-associated gastrointestinal symptoms, a condition established as “exercise-induced gastrointestinal syndrome.” When exercise stress and aligned exacerbation factors (i.e., extrinsic and intrinsic) are of substantial magnitude, these exercise-associated gastrointestinal perturbations can cause performance decrements and health implications of clinical significance. This potentially explains the exponential growth in exploratory, mechanistic, and interventional research in exercise gastroenterology to understand, accurately measure and interpret, and prevent or attenuate the performance debilitating and health consequences of exercise-induced gastrointestinal syndrome. Considering the recent advancement in exercise gastroenterology research, it has been highlighted that published literature in the area is consistently affected by substantial experimental limitations that may affect the accuracy of translating study outcomes into practical application/s and/or design of future research. This perspective methodological review attempts to highlight these concerns and provides guidance to improve the validity, reliability, and robustness of the next generation of exercise gastroenterology research. These methodological concerns include participant screening and description, exertional and exertional heat stress load, dietary control, hydration status, food and fluid provisions, circadian variation, biological sex differences, comprehensive assessment of established markers of exercise-induced gastrointestinal syndrome, validity of gastrointestinal symptoms assessment tool, and data reporting and presentation. Standardized experimental procedures are needed for the accurate interpretation of research findings, avoiding misinterpreted (e.g., pathological relevance of response magnitude) and overstated conclusions (e.g., clinical and practical relevance of intervention research outcomes), which will support more accurate translation into safe practice guidelines.
Practice-Based Teacher Education in Physical Education
Authors: Ward Phillip , Dervent Fatih , Devrilmez Erhan , Iserbyt Peter , Kim Insook , Ko Bomna , Santiago José A. , Tsuda Emi , Xie Xiuye
Published: August 2022

Background: Teacher education is a complex endeavor designed to prepare preservice teachers for the task of teaching physical education to students in K–12 schools. Yet, there is widespread criticism of teacher education outcomes within the United States and around the world. Consequently, teacher educators have been increasingly called upon to use evidence-based approaches in teacher education. Purpose: In this article, we discuss a teacher education reform called practice-based teacher education from macro and micro perspectives. Discussion: Practice-based teacher education emphasizes a curriculum that is focused on relevance defined in terms of what a teacher needs to know and do to be able to teach physical education. Evidence for curricular changes to physical education teacher education and to the content and pedagogies of methods and content classes are presented. We conclude with a discussion of how practice-based teacher education can address social injustice.
Cognitive-Motor Interference and Cortical Activation While Walking in Individuals With Multiple Sclerosis
Authors: VanNostrand Michael , Belanger Brittany , Purin Gabriel , Kasser Susan L. , Cannizzaro Michael
Published: August 2022

The present study expands on current understanding of dual-task cognitive-motor interference, by including cortical activation measures to both traditional and ecologically valid dual-task paradigms. Fifteen individuals with multiple sclerosis and 14 control participants underwent mobility testing while wearing functional near-infrared spectroscopy. In the absence of increased prefrontal cortical activation, subjects with multiple sclerosis performed significantly worse on measures of cognition under both single- and dual-task conditions. These findings suggest that persons with multiple sclerosis may be unable to allocate additional cortical resources to cognition under dual-task conditions, leading to significant cognitive-motor interference and decrements in performance. This study is the first to investigate cortical activation across several commonly used and ecologically valid dual-task assessments.
Results of 40Ar/39Ar Dating of Ores of the Ermakovo F–Be Deposit, West Transbaikalia, Russia
Authors: Damdinov B. B. , Damdinova L. B. , Yudin D. S.
Published: August 2022

The Ermakovo F–Be deposit, the largest Be deposit in Russia and one of the world’s largest deposits, is located in West Transbaikalia. The ores of the deposit are diverse in their morphology and composition; mostly there are phenakite–bertrandite–fluorite metasomatites after limestones. The origin of Be mineralization is related to the stock of leucocratic subalkali aegirine-bearing granites, the age of which corresponds to 224–226 Ma. The available age of ores of 225.5–219 Ma is close to the age of ore-generating granites. To specify the age of the ores, we determined the 40Ar/39Ar age of K-feldspar and, for the first time, of the Be mineral milarite, a K- and H2O-bearing Be silicate (KCa2(Be2AlSi12O30)·H2O), from different ore bodies of the Ermakovo deposit. The age spectrum of milarite (sample Er-17) has a stable plateau in the high-temperature part, which consists of four consecutive steps composing ~50% of the released 39Ar with an age of 182.5 ± 3.0 Ma. The age of K-feldspars is similar (169.8–170.6 Ma). The results of 40Ar/39Ar dating of minerals from ores of the Ermakovo F–Be deposit indicate that the processes of mineral formation occurred over a long period from 225 to 170 Ma.
Experimental Study of the Solubility of Natural Tantalite and Pyrochlore and Tantalum and Niobium Oxides in Hydrothermal Fluoride–Chloride Solutions
Authors: Kotova N. P. , Korzhinskaya V. S. , Shapovalov Yu. B.
Published: August 2022

The concentration and temperature dependences of the solubility of tantalite, pyrochlore, and tantalum and niobium oxides in fluoride–chloride aqueous (mHF + mHCl) solutions at 300–550°C and 100 MPa (Co–CoO buffer) were studied experimentally. The initial concentration of HF varied from 0.01m to 2m, while the HCl concentration remained constant and was 0.5m. A comparative analysis of the equilibrium contents of Nb and Ta upon dissolution of tantalum and niobium oxides and natural tantalite and pyrochlore in fluoride, chloride, and mixed (mHF + mHCl) solutions was carried out.
A Hundred Years of the “Living Matter” Concept: Its Amount, Quality, and Distribution in the Ocean
Authors: Vereshchaka A. L.
Published: August 2022

Abstract

The paper discusses advances and failures in solving the problems posed by V.I. Vernadsky 100 years ago. The quantity and quality of “living matter” along with its distribution on Earth are analyzed. In accordance with the competence of the author, the paper is focused on the most voluminous biogeochemical reservoir of the planet, i.e., the World Ocean. In a number of cases, the presented literature and original data demonstrate a progress in the solution of V.I. Vernadsky problems: the estimation of the quantity and the description of the distribution of living matter. In particular, new data on the role and distribution of the living matter in the oceanosphere are presented. In other cases such as the analysis of the amount of homogeneous living matter and its biogeochemical role, there is no visible progress over the past decades but possible solutions to the problem are suggested.
Conduction properties of semiconductive multiwalled carbon nanotubes
Authors: Ahlskog M. , Herranen O. , Leppäniemi J. , Mtsuko D.
Published: August 2022

We have undertaken low-temperature conduction measurements on arc-discharge synthesized, semiconducting multiwalled carbon nanotubes (MWNT). The diameters of these are in the range 2.5–10 nm, corresponding to the sizes just above single-walled carbon nanotubes (SWNT), up to middle-sized MWNTs. The energy gap, inversely related to the diameter, varies strongly in this range, and consequently there is a strong dependence of the transport on tube diameter. Certain transport characteristics are much alike those found in SWNTs, such as the ON-state resistance and Coulomb blockade. However, the transport gap has a more complex behavior than the corresponding one in semiconducting SWNTs, and a number of features, such as negative differential resistance are commonly observed. Different models for the small bias transport behavior are briefly discussed, and we consider especially the possibility of conduction via the second layer.

Graphical abstract
Impact of curvature based geometric constraints on F(R) theory
Authors: Loo Tee-How , De Avik , Arora Simran , Sahoo P. K.
Published: August 2022

Theories of gravity are fundamentally a relation between matter and the geometric structure of the underlying spacetime. So once we put some additional restrictions on the spacetime geometry, the theory of gravity is bound to get the impact, irrespective of whether it is general relativity or the modified theories of gravity. In the present article, we consider two curvature-based constraints, namely the almost pseudo-Ricci symmetric and weakly Ricci symmetric condition. As a novel result, such spacetimes with non-null associated vectors are entirely classified, and then applying the obtained results, we investigate these spacetimes as solutions of the F(R)-gravity theory. The modified Friedmann equations are derived and analysed in a model-independent way first. Finally, two F(R) gravity models are examined for recent observational constrained values of the deceleration, jerk, and Hubble parameters. We further discuss the behavior of energy conditions.
Integration of the Lane–Emden equation for relativistic anisotropic polytropes through gravitational decoupling: a novel approach
Authors: Santana D. , Fuenmayor E. , Contreras E.
Published: August 2022

In this work we propose a novel approach to integrate the Lane–Emden equations for relativistic anisotropic polytropes. We take advantage of the fact that Gravitational Decoupling allows to decrease the number of degrees of freedom once a well known solution of the Einstein field equations is provided as a seed so after demanding the polytropic equation for the radial pressure the system is automatically closed. The approach not only allows to extend both isotropic or anisotropic known solutions but simplifies the computation of the Tolman mass whenever the Minimal Geometric Deformation is considered given that the $$g_{tt}$$

g

tt

component of the metric remains unchanged. We illustrate how the the method works by analyzing the solutions obtained from Tolman IV, Durgapal IV and Wymann IIa isotropic systems as a seed for the integration.
A simple protocol to construct solutions with vanishing complexity by Gravitational Decoupling
Authors: Contreras E. , Stuchlik Z.
Published: August 2022

In this work we develop a simple protocol to construct interior solutions through Gravitational Decoupling by the Minimal Gemetric Deformation extended satisfying the vanishing complexity condition. The method is illustrated by using Tolman VII and Tolman IV solutions as isotropic seeds.
Human-Computer Collaborative Visual Design Creation Assisted by Artificial Intelligence
Authors: Huang Lihua , Zheng Peng
Published: August 2022

With the support and promotion of big data and cloud computing, AI has penetrated into every field of people's lives more and more deeply, with its characteristics of sustainable work, extremely fast computing speed, and a certain intelligence. This is an effective way to solve the general lack of demand and productivity of visual design, and relieve the pressure off designers to deal with relatively low-quality and high-demand designs. Therefore, the combination of design and artificial intelligence technology is a necessity. Research on the application of artificial intelligence technology for visual design is also in full swing at home and abroad However, at present, teams at home and abroad are in the exploratory stage. This paper considers whether it is possible to build an intelligent visual design and creation system by using artificial intelligence technology to help graphic communication designers achieve high-quality, high-efficiency, and high-quantity design output. Additionally, this paperexplores how to combine artificial intelligence technology with designers' design workflow so as to form a complementary human-computer cooperation mode. We will explore how to integrate AI technology with designers' design workflow and then create a human-machine collaboration model with complementary advantages to achieve the high quality, high efficiency, and high quantity of design output required by the intelligent visual design creation system being built. Finally, a basic framework of a generative smart human-computer collaborative visual design creation system based on a subset of neural network expert systems in multiple domains and an aggregate of different modules supported by the system is formed, and the working principle and usage process of the system are further elaborated with the example of packaging design.
Edge-Weighted Online Bipartite Matching
Authors: Fahrbach Matthew , Huang Zhiyi , Tao Runzhou , Zadimoghaddam Morteza
Published: August 2022

Online bipartite matching is one of the most fundamental problems in the online algorithms literature. Karp, Vazirani, and Vazirani (STOC 1990) gave an elegant algorithm for unweighted bipartite matching that achieves an optimal competitive ratio of 1-1/e . Aggarwal et al. (SODA 2011) later generalized their algorithm and analysis to the vertex-weighted case. Little is known, however, about the most general edge-weighted problem aside from the trivial 1/2-competitive greedy algorithm. In this article, we present the first online algorithm that breaks the long-standing 1/2 barrier and achieves a competitive ratio of at least 0.5086. In light of the hardness result of Kapralov, Post, and Vondrák (SODA 2013), which restricts beating a  1/2 competitive ratio for the more general monotone submodular welfare maximization problem, our result can be seen as strong evidence that edge-weighted bipartite matching is strictly easier than submodular welfare maximization in an online setting.

The main ingredient in our online matching algorithm is a novel subroutine called
online correlated selection
 (OCS), which takes a sequence of pairs of vertices as input and selects one vertex from each pair. Instead of using a fresh random bit to choose a vertex from each pair, the OCS negatively correlates decisions across different pairs and provides a quantitative measure on the level of correlation. We believe our OCS technique is of independent interest and will find further applications in other online optimization problems.
Application and Prospect Analysis of Artificial Intelligence in the Field of Physical Education
Authors: Xiang Wujun
Published: August 2022

The development of AI technology has a significant impact on every sector of business. Artificial intelligence uses this technology to reduce the amount of work required, duplicate work, and increase the accuracy of work by modelling human behaviour and thought. On the basis of a thorough analysis of artificial intelligence technology, the technology is applied to teaching, specialised training, and specialised testing in response to the current issues in the field of physical education and the business that can be improved through auxiliary tools. The paper discusses how artificial intelligence technology can be used in physical education. After that, it examines how physical education is currently taught in classrooms and discusses how artificial intelligence is affecting this field. Following a thorough demonstration of the aforementioned material, the commonly used artificial intelligence technologies are introduced in turn, along with the methodology used in physical education. The use of computer models in physical education is then explained, and future analysis is conducted on the basis of this information.
Novel Crow Swarm Optimization Algorithm and Selection Approach for Optimal Deep Learning COVID-19 Diagnostic Model
Authors: Mohammed Mazin Abed , Al-Khateeb Belal , Yousif Mohammed , Mostafa Salama A. , Kadry Seifedine , Abdulkareem Karrar Hameed , Garcia-Zapirain Begonya
Published: August 2022

Due to the COVID-19 pandemic, computerized COVID-19 diagnosis studies are proliferating. The diversity of COVID-19 models raises the questions of which COVID-19 diagnostic model should be selected and which decision-makers of healthcare organizations should consider performance criteria. Because of this, a selection scheme is necessary to address all the above issues. This study proposes an integrated method for selecting the optimal deep learning model based on a novel crow swarm optimization algorithm for COVID-19 diagnosis. The crow swarm optimization is employed to find an optimal set of coefficients using a designed fitness function for evaluating the performance of the deep learning models. The crow swarm optimization is modified to obtain a good selected coefficient distribution by considering the best average fitness. We have utilized two datasets: the first dataset includes 746 computed tomography images, 349 of them are of confirmed COVID-19 cases and the other 397 are of healthy individuals, and the second dataset are composed of unimproved computed tomography images of the lung for 632 positive cases of COVID-19 with 15 trained and pretrained deep learning models with nine evaluation metrics are used to evaluate the developed methodology. Among the pretrained CNN and deep models using the first dataset, ResNet50 has an accuracy of 91.46% and a F1-score of 90.49%. For the first dataset, the ResNet50 algorithm is the optimal deep learning model selected as the ideal identification approach for COVID-19 with the closeness overall fitness value of 5715.988 for COVID-19 computed tomography lung images case considered differential advancement. In contrast, the VGG16 algorithm is the optimal deep learning model is selected as the ideal identification approach for COVID-19 with the closeness overall fitness value of 5758.791 for the second dataset. Overall, InceptionV3 had the lowest performance for both datasets. The proposed evaluation methodology is a helpful tool to assist healthcare managers in selecting and evaluating the optimal COVID-19 diagnosis models based on deep learning.
Design and Application of Art Education Communication Platform Based on Machine Vision
Authors: Chen Bingyan , Lu Yao , Tang Bangbei , Zhang Wenya
Published: August 2022

There are some problems in the design and application of the art education exchange platform. In order to further analyze the relevant content of the art education exchange, based on machine vision theory, model calibration, and coordinate change are adopted to modify the original model, so as to obtain the optimized model. This model can be used to analyze the design and application of art education platform. Relevant studies show that, according to the coordinate parameter curve, the parameter α plays a promoting role on the coordinate value, while the parameter β plays a promoting role on the coordinate value first and then plays an inhibiting role. The parameter γ also promotes and inhibits coordinate values. The curve corresponding to parameter M1 shows a gradual decline, and the curve of parameter M2 has little influence on coordinate data. The curve corresponding to parameter M3 also shows a linear trend of change. Through analysis, it can be seen that M3 has the greatest influence on coordinate data. By using machine vision model to design and analyze the communication platform of art education, the changing trend of different indicators can be obtained. It can be seen from the analysis that both language and vocal music have obvious stability in the calculation process, which is an inherent attribute of communication platform. Finally, the accuracy of the optimization model is verified by analyzing and predicting the data. This research can provide theoretical support for the application of machine vision model in other fields.
Mean Square Consensus of General Linear Multiagent Systems with Communication Noises under Switching Topologies
Authors: Chen Kairui , Yan Chuance , Ren Qijun , Zeng Xianxian , Wang Junwei
Published: August 2022

This paper investigates the distributed consensus problem of general linear multiagent systems (MASs) with communication noises under fixed and Markovian switching topologies, respectively. Each agent can obtain full state of itself and receive its neighbors’ state with noises, where intensities of noises are vector functions of relative states of agents. Bearing in mind the above constrains, a consensus protocol is proposed, where the gain matrix is obtained by the algebraic Riccati equation and the coupling strength is restricted in a given interval. By using the stochastic stability theorem, we show that mean square consensus is achieved in fixed topology case and switching topologies case, respectively. Furthermore, an estimation of the exponential convergence rate of consensus is given explicitly. Finally, simulation examples are given to show the correctness of the proposed results.
lncRNA SNHG12 Inhibition Based on Microsystem Cell Imaging Technology Protects the Endothelium from LPS‐Induced Inflammation by Inhibiting the Expression of miR‐140‐3p Target Gene fndc5
Authors: Zhang Lei , Li Bin , Zhang Degang , Zhao Ye , Yu Qin
Published: August 2022

Acute lung injury (ALI) is a serious disease with a high incidence rate, characterized by uncontrolled inflammation and apoptosis. At present, long‐chain noncoding RNA (lncRNA) is a noncoding RNA with a length of more than 200 nucleotides. It plays an important role in ALI, cell cycle regulation, cell differentiation regulation, and many other life activities. Therefore, the current focus is to identify and evaluate the possible functions and potential molecular mechanisms of lncRNA small nuclear host gene 12 (SNHG12). Lipopolysaccharide (LPS)‐induced mice model and in vitro cell model were established. Gene knockout is to use the principle of DNA homologous recombination to replace the target gene fragment with the designed homologous fragment, so as to achieve the purpose of gene knockout. The relationship between lncRNA SNHG12 expression and ALI was studied through knockdown and overexpression experiments. The qRT‐PCR, ROS, immunohistochemistry, histopathology, TUNEL, and cell permeability tests were performed to further verify the possible targets and mechanisms of action. The expression of lncRNA SNHG12 in lung tissue was lower than that in normal tissue. The results showed that lncRNA SNHG12 could reduce lung cell injury and inflammatory cytokines induced by ALI. Bioinformatics analysis showed that lncRNA SNHG12 interacted with miR‐140‐3p. Subsequent experiments confirmed the link between lncRNA SNHG12, miR‐140‐3p, and fndc5. Furthermore, this study indicates that lncRNA SNHG12 has a key function in ALI. The results of this study demonstrated the role of lncRNA SNHG12 in the pathological process of ALI and provided a reference for developing novel anti‐ALI treatments so that patients can get timely treatment, avoid causing multiple organ failure, and will not endanger their life safety.
Jewelry Packaging User Demand Analysis Based on Fuzzy Kano Model
Authors: Hu Zhanmei
Published: August 2022

China’s jewelry sales maintain a good momentum of annual growth, and consumption potential is huge. However, jewelry packaging design faced many problems. Even through China has many jewelry brands, the packaging is poorly designed. The fundamental reason lies in the lack of targeted design of jewelry packaging and the lack of detailed analysis and research, only to meet the functional use. Fuzzy front-end is suitable for the initial stage of product design and determines the success or failure of product design. In view of the uncertain factors, such as consumer demand, technical characteristics, and competitive environment that need to be considered in jewelry packaging design, this paper takes jewelry packaging products, jewelry brands, and fuzzy front-end as research objects, analyzes the existing problems, and makes quantitative analysis by using methods such as questionnaire survey, brainstorming, and scenario analysis. Rough set theory and Kano Model are used to classify and analyze user demand information and determine the realization opportunity. Finally, the research ideas of this topic are formed, and the corresponding research methods and models for ring packaging in jewelry are put forward and verified by examples, so as to form a research method suitable for fuzzy front-end design of jewelry packaging and improve the quality of jewelry packaging design.
Optimisation of Graphene Nanofiller Addition on the Mechanical and Adsorption Properties of Woven Banana/Polyester Hybrid Nanocomposites by Grey-Taguchi Method
Authors: Natrayan L. , Kumar P. V. Arul , Kaliappan S. , Sekar S. , Patil Pravin P. , Velmurugan G. , Gurmesa Murtesa Dabesa
Published: August 2022

Throughout history, techniques have shifted from mainstream metals and minerals to nanocomposites to generate smaller, more practical elements for particular purposes. Natural fibres have greater advantages than glass fibres, such as being cheaper, recyclable, and nonflammable. The main objective of the current experiment is to determine how the accumulation of graphene to hybrid polyester composites reinforced with woven banana fibre affects their mechanical properties. Composites were constructed utilising the hand lay-up process with the following limitations: (i) graphene filler weightiness, (ii) woven banana fibre thickness in gsm, and (iii) number of woven banana layers, all at three different levels. Using the L9 (33) orthogonal design, nine composite samples are generated and tested according to the ASTM standard. According to the grey research, hybrid composites having 5% graphene powder and 350 grammes per square metre of woven banana fibre in three layers have high mechanical strength. Adding fibre content to immaculate polyester increased its mechanical properties in general. As the fibre and filler concentrations grew, more energy was required to break the fibre bundles between the matrix and its resin. The confirmation test by the optimal process value utilising the grey relation analysis is considerably better than the actual test data. Tension strength has improved by 17.14%, bending strength has improved by 96.75%, and impact energy has increased by 16.17%.
Research on SDN Fingerprint Attack Defense Mechanism Based on Dynamic Disturbance and Information Entropy Detection
Authors: Fang Xing , Zhang Wenhui , Lin Jiming , Liu Yuming
Published: August 2022

As an emerging type of network architecture, SDN is widespread used and security issues have also received more and more attention. Fingerprint attacks represent one of the most significant threats to network security. Attackers obtain key fingerprint information of the target network, which lays the foundation for subsequent more threatening attacks. Currently, research on domestic and international SDN fingerprint attacks focuses on how to attack, and less research is being done on how to defend against fingerprinting attacks. This paper proposes a mechanism for defending fingerprint attacks that combines dynamic disturbance and information entropy detection. This mechanism adopts the principle of fingerprint attack, combined with a moving average algorithm, Bloom Filter, and packet delay tool, to confuse opponents by disturbing a small number of packets, simultaneously, combined with the information entropy detection to make real-time processing feedback to the network. The experimental results show that this mechanism works effectively to defend SDNs against fingerprint attacks without affecting the normal network communication.
A Transformer-Based Network for Change Detection in Remote Sensing Using Multiscale Difference-Enhancement
Authors: Ailimujiang Gulinazi , Jiaermuhamaiti Yiliyaer , Jumahong Huxidan , Wang Huiling , Zhu Shuangling , Nurmamaiti Pazilaiti
Published: August 2022

Recently, transformer-based change detection methods have achieved remarkable performance by sophisticated architectures for extracting powerful feature representations. However, due to the existence of various noises in bitemporal images, there are problems such as loss of semantic objects and incompleteness that will occur in change detection. The existing transformer-based approaches do not fully address this issue. In this paper, we propose a transformer-based multiscale difference-enhancement U-shaped network and call it TUNetCD, for change detection in remote sensing. The encoder, which is composed of a multilayer Swin-Transformer block structure, can extract multilevel feature maps, further enhance these multilevel feature maps using a Swin-Transformer feature difference map processing module, and finally obtain the final change map using a lightweight decoder. We conducted comprehensive experiments on two publicly available benchmark datasets, LEVIR-CD and DSIFN-CD, to verify the effectiveness of the method, and our method outperformed other advanced transformer-based methods.
On Study of 1D Depth Scans as an Alternative Feature for Human Pose Detection in a Sensor Network
Authors: Rasoulidanesh Maryamsadat , Payandeh Shahram
Published: August 2022

Inspired by the notion of swarm robotics, sensing, and minimalism, in this paper, we study and analyze how a collection of only 1D depth scans can be used as a part of the minimum feature for human body detection and its segmentation in a point cloud. In relation to the traditional approaches which require a complete point cloud model representation for skeleton model reconstruction, our proposed approach offers a lower computation and power consumption, especially in sensor and robotic networks. Our main objective is to investigate if the reduced number of training data through a collection of 1D scans of a subject is related to the rate of recognition and if it can be used to accurately detect the human body and its posture. The method takes advantage of the frequency components of the depth images (here, we refer to it as a 1D scan). To coordinate a collection of these 1D scans obtained through a sensor network, we also proposed a sensor scheduling framework. The framework is evaluated using two stationary depth sensors and a mobile depth sensor. The performance of our method was analyzed through movements and posture details of a subject having two relative orientations with respect to the sensors with two classes of postures, namely, walking and standing. The novelty of the paper can be summarized in 3 main points. Firstly, unlike deep learning methods, our approach would require a smaller dataset for training. Secondly, our case studies show that the method uses very limited training dataset and still can detect the unseen situation and reasonably estimate the orientation and detail of the posture. Finally, we propose an online scheduler to improve the energy efficiency of the network sensor and minimize the number of sensors required for surveillance monitoring by employing a mobile sensor to recover the occluded views of the stationary sensors. We showed that with the training data captured on 1 m from the camera, the algorithm can detect the detailed posture of the subject from 1, 2, 3, and 4 meters away from the sensor during the walking and standing with average accuracy of 93% and for different orientation with respect to the sensor by 71% accuracy.
[Retracted] Application of Visual Artificial Airway in Patients with ARDS Assisted by Pulmonary Ultrasound
Authors: Xia Liuqin , Ma Jianping , Hu Lingli , Zhu Ying , Diao Mengyuan
Published: August 2022

Objective. To explore the application of pulmonary ultrasound in visual nursing of artificial airway in patients with acute respiratory distress syndrome (ARDS). Methods. Seventy‐eight ARDS patients with mechanical ventilation admitted from February 2021 to January 2022 were included and divided into the intervention group and the control group. The control group was given routine airway nursing, and the intervention group was given visual airway nursing management through lung ultrasound. The arterial blood gas analysis indexes, mechanical ventilation time, ICU treatment time, total hospitalization time, aspiration, and the incidence of ventilator‐associated pneumonia (VAP) were compared between the two groups. Results. After treatment, PaO2, PaCO2, SPO2, and oxygenation indexes were significantly improved compared with those before treatment, and the indexes in the intervention group were better than those in the control group after treatment, and the differences were statistically significant (P < 0.05). The mechanical ventilation time (5.39 ± 0.68 vs. 7.92 ± 0.59 days), ICU treatment time (8.05 ± 1.14 vs. 10.71 ± 1.16 days), and total hospitalization time (12.05 ± 2.20 vs. 15.68 ± 2.18 days) in the intervention group were significantly shorter than those in the control group (P < 0.05). The incidences of aspiration (2.56% vs. 15.38%) and VAP (5.13% vs. 20.51%) in the intervention group was significantly lower than that in the control group (P < 0.05). Conclusion. The application of visual artificial airway management assisted by lung ultrasound in ARDS patients can shorten the treatment time and hospitalization time of mechanical ventilation, reduce the incidence of aspiration and VAP, and improve the prognosis of patients.
sCD40L Is Increased and Associated with the Risk of Gestational Diabetes Mellitus in Pregnant Women with Isolated TPOAb Positivity
Authors: Chen Xinxin , Wang Qingyao , Cong Xiangguo , Jiang Shuyi , Li Shuxiang , Shen Qiong , Chen Lei
Published: August 2022

Background. Autoimmune disorders are associated with gestational diabetes mellitus (GDM) in pregnant women who were positive for thyroid peroxidase antibody (TPOAb). Soluble CD40 ligand (sCD40L) and soluble interleukin-2 receptor (sCD25) are abnormally expressed in autoimmune diseases and are reliable markers of inflammation. The purpose of this study was to evaluate sCD40L and sCD25 in early pregnancy and investigate their correlation with GDM and TPOAb. Methods. A total of 126 pregnant women in the first trimester were enrolled for analysis: 93 were positive for TPOAb and 33 were negative for TPOAb. Demographical and clinical data in early pregnancy were collected. A total of 123 participants underwent a 75 g oral glucose tolerance test in the second trimester. Serum sCD40L and sCD25 levels were measured by ELISA. Results. The incidence of GDM was 24.4% in pregnant women with isolated TPOAb positivity in our study. Both sCD40L and sCD25 were positively correlated with TPOAb (r = 0.476,

P
<
0.001

; r = 0.188,

P
<
0.05

). sCD40L was highest in (

P
<
0.001

) Ab-positive women with GDM group (

P
<
0.05

). After adjusting for TPOAb, age, TSH, FT4, triglycerides, and low-density lipoprotein cholesterol, multivariate logistic regression analysis showed that sCD40L was an independent risk factor for GDM in pregnant women with TPOAb positivity (odds ratio = 3.235, 95% confidence interval 1.024–10.218,

P
<
0.05

). Conclusions. About a quarter of pregnant women with isolated positive TPOAb might have GDM. sCD40L was an independent risk factor for GDM in women with isolated TPOAb positivity.
Treatment Adherence among HIV and TB Patients Using Single and Double Way Mobile Phone Text Messages: A Randomized Controlled Trial
Authors: Kibu Odette Dzemo , Siysi Vincent Verla , Albert Legrand Same Ekobo , Asangbeng Tanue Elvis , Nsagha Dickson Shey
Published: August 2022

Background. Research has shown that patients fail to adhere to ART and TB treatment due to the long duration of both therapies, side effects, and forgetfulness. Objective. To assess the role of the double-way and single-way SMS on adherence to HIV and TB treatment. Materials and Methods. A randomized controlled trial among adult HIV and TB patients on treatment at the Buea Regional and Kumba District Hospitals, South West Region, Cameroon, was conducted. Participants were randomly allocated to the control, single-way, and double-way SMS intervention groups. HIV and TB participants were followed independently for a period of 6 months and 3 months, respectively. Baseline and post-intervention data were collected and analyzed using the chi-square and Student’s t-tests with statistical significance set at

p
<
0.05

. Results. A total of 210 HIV participants and 84 TB were recruited into the study with a mean age of 41.25 ± 10 years and 37.89 ± 13.27 years, respectively. Optimal adherence to ART and TB treatment at baseline was [65 (31%) CI: 0.247–0.372] and [35 (41.7%) CI: 0.311-0.522], respectively, and after the intervention, it increased to [72 (42.6%) CI: 0.347-0.495] and 41 (61.2%), respectively. There was an increase in adherence to ART among participants in the double-way SMS intervention group from 23 (32.9%) (RR: 1.04, CI: 0.8-1.31,

p
=
0.716

) to 29 (48.3%) (RR: 1.06, CI: 0.75-1.50,

p
=
0.746

). Combined single-way and double-way SMS significantly increased adherence to ART. Conclusions. The level of adherence was low among HIV and TB participants. The single-way and double-way SMS did not significantly increase adherence. However, a combination of both the double-way and single-way SMS intervention significantly improved adherence to ART.
Predictive Modeling of Short-Term Poor Prognosis of Successful Reperfusion after Endovascular Treatment in Patients with Anterior Circulation Acute Ischemic Stroke
Authors: Zhang Zhuo , Song Cheng , Zhang Li , Yang Weimin
Published: August 2022

This study aimed to propose and internally validate a prediction model of short-term poor prognosis in patients with acute ischemic stroke (AIS). In the retrospective study, 356 eligible AIS patients receiving endovascular treatment (EVT) were included and divided into the good prognosis group and the poor prognosis group. Data from 70% of patients were collected as training set and the 30% as validation set. Univariate analysis and multivariate logistic regression were used for identifying independent predictors. The performance of the model was evaluated by receiver operating characteristic (ROC) curve and the paired Chi-square test was used for internal validation. A model for the prediction of short-term poor prognosis in atherosclerotic AIS patients who successfully underwent endovascular reperfusion was developed: log (Pr/1 − Pr) = 3.500 + Blood glucose 

∗

 0.174 + Infarct volume 

∗

 0.128 + the National Institutes of Health Stroke Scale score × Onset-to-reperfusion time (NIHSS-ORT) 

∗

 0.014 + Intraoperative hypotension (Yes) 

∗

 1.037 + Mean arterial pressure (MAP) decrease from baseline (>40%)

∗

2.061 (Pr represented the probability of short-term poor prognosis). The area under the curve (AUC) was 0.806 (0.748 − 0.864) in the training set and 0.850 (0.779 − 0.920) in the testing set, which suggested the good performance of the model. We proposed and validated a combined prediction model to predict the short-term poor prognosis of AIS patients after EVT, which could provide reference for clinicians to identify AIS patients with a higher risk of poor outcomes and thus improving the prognosis of EVT.
Bi4Ti3O12 Ferroelectric Nanomaterials on Volatile Substances of Acrylic Pigment Diluted Coatings
Authors: Lu Pei
Published: August 2022

Bi4Ti3O12 ferroelectric nanomaterials are mainly used in the manufacture of biosensors, biomedical imaging reagents, or other biomedical applications. Due to the different arrangements of Bi4Ti3O12 ferroelectric nanoparticles, complex nanofibers with specific geometries can be obtained. In this paper, Bi4Ti3O12 ferroelectric nanomaterials were used to study the volatilization state of the acrylic paint used in the coating process. This article explains that some Bi4Ti3O12 nanoparticles were difficult to be dispersed in spinning solution, which made the preparation of composite fibers difficult. Therefore, these issues need further research and resolution. This work proposes to selectively reduce the use of graphene oxide by using an environmentally friendly water solvent to prepare water-reduced graphene oxide (rGO) and then inject octadecylamine into the selectively reduced graphene oxide to prepare octadecylamine-grafted reduced graphene oxide (rG-ODA). The experimental results in this paper showed that through seeding and reduction, functional groups such as carboxyl groups and epoxy groups on the surface of graphene oxide disappeared, and graphene oxide was well reduced. The presence of oxygen-containing functional groups increased the distance between the graphitic layers to 0.713 nm. GS-EDA had a characteristic diffraction peak close to 2θ = 24.3°, indicating that GO was effectively reduced after inoculation reduction.
Exact Solutions and Dynamic Properties of the Perturbed Nonlinear Schrödinger Equation with Conformable Fractional Derivatives Arising in Nanooptical Fibers
Authors: Bao Shuxin , Chen Shuangqing
Published: August 2022

The main idea of this paper is to investigate the exact solutions and dynamic properties of a space-time fractional perturbed nonlinear Schrödinger equation involving Kerr law nonlinearity with conformable fractional derivatives. Firstly, by the complex fractional traveling wave transformation, the traveling wave system of the original equation is obtained, then a conserved quantity, namely, the Hamiltonian, is constructed, and the qualitative analysis of this system is conducted via this quantity by classifying the equilibrium points. Moreover, the existences of the soliton and periodic solution are established via the bifurcation method. Furthermore, all exact traveling wave solutions are constructed to illustrate our results explicitly by the complete discrimination system for the polynomial method.
Health Promotion Combined with Psychological Care Improves Vestibular Function in Patients with Vestibular Neuritis
Authors: Peng Fan , Mei Rui , Liu Chanyuan , Liu Xiu , Xiong Jing , Lv Lu , Wang Fang
Published: August 2022

This study aimed to explore the effect of health education combined with psychological care on patients with vestibular neuritis and the effect on their vestibular function. One hundred patients with vestibular neuritis admitted to our hospital from January 2019 to December 2020 were enrolled and divided into two groups by the random number: the control group (CG) (n= 53, health education) and the study group (SG) (n= 47, health education + psychological care). The Dizziness Handicap Inventory (DHI) scores, Berg Balance Scale (BBS) scores, depression scores (SDS), anxiety scores (SAS), satisfaction with care, compliance, incidence of falls, quality of life (QOF), and clinical symptom scores were compared between the two groups. Compared with the CG, the SG had a more significant reduction in DHI scores and SDS and SAS scores and a significant increase in BBS scores (P < 0.05). Compared with the CG, the SG had higher nursing satisfaction and compliance and a lower incidence of falls (P < 0.05). Nursing efficiency was higher in the SG than in the CG (P < 0.05). QOF scores were higher in the SG than in the CG (P < 0.05). Clinical symptom scores were lower in the SG than in the CG (P < 0.05). Health education combined with psychological care can improve vestibular function and bad mood, reduce the incidence of falls, improve the QOF, and result in high patient satisfaction and compliance, which should be widely promoted.
[Retracted] lncRNA MIR4435‐2HG Accelerates the Development of Bladder Cancer through Enhancing IQGAP3 and CDCA5 Expression
Authors: Yang Tao , Li Yan , Wang Gang , Guo Liuxiong , Sun Fuzhen , Li Shoubin , Deng Xinna , Liu Junjiang
Published: August 2022

Background. Bladder cancer (BCa) is one of the most prevalent cancers occurring in the urinary system. Long noncoding RNAs (lncRNAs), in recent years, have emerged as crucial regulators in various biological processes of tumors. Aim. To identify the role of MIR4435‐2 host gene (MIR4435‐2HG) and uncover its molecular mechanism in BCa. Methods. Firstly, quantitative real‐time PCR (RT‐qPCR) analysis was used to examine MIR4435‐2HG expression in BCa cells. Cell Counting Kit‐8 (CCK‐8), 5‐ethynyl‐2′‐deoxyuridine (EdU), wound healing, and transwell assays were implemented to identify the role of MIR4435‐2HG in BCa. RNA‐binding protein immunoprecipitation (RIP), RNA pull down, and luciferase reporter assays were applied to explore the potential mechanism of MIR4435‐2HG in BCa. Results. MIR4435‐2HG was highly expressed in BCa. Moreover, MIR4435‐2HG silencing abrogated BCa cell proliferation, migration, and invasion. In terms of underlying mechanism, MIR44352HG acted as a microRNA‐2467‐3p (miR‐2467‐3p) sponge to control the expression of IQ motif containing GTPase activating protein 3 (IQGAP3) and cell division cycle associated 5 (CDCA5), resulting in activation of the rat sarcoma virus (Ras)/rapidly accelerated fibrosarcoma (Raf)/mitogen‐activated protein kinase (MEK)/extracellular signal‐regulated kinase (ERK) and PI3K/AKT/mTOR signaling pathways. Conclusion. MIR4435‐2HG involves in the progression of BCa, which might provide novel insights for BCa treatment.