bluuebunny/crossref_metadata_2025 huggingface dataset:
Trends in direct oral anticoagulant (DOAC) prescribing in English primary care (2014–2019)
Authors: Joy Mark , Williams John , Emanuel Subo , Kar Debasish , Fan Xuejuan , Delanerolle Gayathri , Field Benjamin CT , Heiss Christian , Pollock Kevin G , Sandler Belinda , Arora Jasleen , Sheppard James P , Feher Michael , Hobbs FD Richard , de Lusignan Simon
Published: September 2022

Background

In England, most prescribing of direct-acting oral anticoagulants for atrial fibrillation (AF) is in primary care. However, there remain gaps in our understanding of dosage and disparities in use. We aimed to describe trends in direct oral anticoagulant (DOAC) prescribing, including dose reduction in people with renal impairment and other criteria, and adherence.

Methods

Using English primary care sentinel network data from 2014 to 2019, we assessed appropriate DOAC dose adjustment with creatinine clearance (CrCl). Our primary care sentinel cohort was a subset of 722 general practices, with 6.46 million currently registered patients at the time of this study.

Results

Of 6 464 129 people in the cohort, 2.3% were aged ≥18 years with a diagnosis of AF, and 30.8% of these were prescribed vitamin K antagonist and 69.1% DOACs. Appropriate DOAC prescribing following CrCl measures improved between 2014 and 2019; dabigatran from 21.3% (95% CI 15.1% to 28.8%) to 48.7% (95% CI 45.0% to 52.4%); rivaroxaban from 22.1% (95% CI 16.7% to 28.4%) to 49.9% (95% CI 48.5% to 53.3%); edoxaban from 10.0% (95% CI 0.3% to 44.5%) in 2016 to 57.6% (95% CI 54.5% to 60.7%) in 2019; apixaban from 30.8% (95% CI 9.1% to 61.4%) in 2015 to 60.5% (95% CI 57.8% to 63.2%) in 2019.

Adherence was highest for factor Xa inhibitors, increasing from 50.1% (95% CI 47.7% to 52.4%) in 2014 to 57.8% (95% CI 57.4% to 58.2%) in 2019. Asian and black/mixed ethnicity was associated with non-adherence (OR 1.81, 95% CI 1.56 to 2.09) as was male gender (OR 1.19, 95% CI 1.15 to 1.22), higher socioeconomic status (OR 1.60, 95% CI 1.52 to 1.68), being an ex-smoker (OR 1.12, 95% CI 1.06 to 1.19) and hypertension (OR 1.07, 95% CI 1.03 to 1.17).

Conclusions

The volume and quality of DOAC prescribing has increased yearly. Future interventions to augment quality of anticoagulant management should target disparities in adherence.
Asymptomatic carotid artery stenosis: a summary of current state of evidence for revascularization and emerging high-risk features
Authors: Kim Hyun Woo , Regenhardt Robert W , D'Amato Salvatore A , Nahhas Michael I , Dmytriw Adam A , Hirsch Joshua A , Silverman Scott B , Martinez-Gutierrez Juan Carlos
Published: September 2022

Carotid artery stenosis is a leading cause of ischemic stroke. While management of symptomatic carotid stenosis is well established, the optimal approach in asymptomatic carotid artery stenosis (aCAS) remains controversial. The rapid evolution of medical therapies within the time frame of existing landmark aCAS surgical revascularization trials has rendered their findings outdated. In this review, we sought to summarize the controversies in the management of aCAS by providing the most up-to-date medical and surgical evidence. Subsequently, we compile the evidence surrounding high-risk clinical and imaging features that might identify higher-risk lesions. With this, we aim to provide a practical framework for a precision medicine approach to the management of aCAS.
Fermi’s favorite figure: the history of the pseudopotential concept in atomic physics and neutron physics
Authors: Gould Christopher R. , Sharapov Eduard I.
Published: September 2022

In the early 1930’s, Fermi wrote two papers in which he introduced the concepts of “scattering length” and “pseudopotential.” Since that time, these terms have become universally associated with low energy scattering phenomena. Even though the two papers are very different—one in atomic physics, the other in neutron physics—a simple figure underlies both. The figure appears many times in Fermi’s work. We review how the two papers came about and briefly discuss modern developments of the work that Fermi initiated with these two remarkable papers.
Multicriteria ABC Inventory Classification Using a Group Decision Making Method with Individual Preferences
Authors: Xu Yang , Fu Yelin , Chen Yu , Lai Kin Keung
Published: September 2022

This paper proposes a group decision making model with individual preferences to investigate the multicriteria ABC inventory classification problem. We first propose a preliminary group decision matrix by means of identifying the individual preference among the classification criteria as a typical decision maker; then analyze the endogenous individual preference structure in terms of exploring the preferential difference and preferential priority, a revised group decision matrix is therefore presented; thirdly, make the use of SMAA-2 to derive the holistic acceptability index for classifying the SKUs. A satisfaction index is developed to manifest the merits of proposed method. A numerical illustration using the data drawn from previous studies is performed to indicate the applicability and feasibility of our method.
Self-similar behavior of the neutron fracture functions
Authors: Mohsenabadi Samira Shoeibi , Taghavi-Shahri F.
Published: September 2022

In this paper, we have employed Fractal formalism to calculate the Fracture Functions of the Leading neutron produced in [Formula: see text] collisions. The Fractal concept describes the self-similar behavior of the proton structure at Leading neutron production of semi-inclusive Deep Inelastic Scattering at the low values of the fractional momentum variable [Formula: see text]. The Fracture Functions (FFs) parameterized the non-perturbative part of the fragmentation process at the initial scale of Q[Formula: see text]. In this analysis, we benefit from the Leading neutron (Ln) experimental data published by H1 Collaboration and in order to estimate the uncertainty of neutron FFs and corresponding observables, we used the Hessian method. As a consequence of this Next-to-Leading order QCD analysis, we achieve a nice agreement between the prediction of our model for neutron FFs and experimental data. It seems that the Fractal approach based on the self-similar behavior of these conditional parton distribution functions can nicely describe the experimental data at low [Formula: see text].
On weak zero-clean rings
Authors: Ma Guanglin , Wang Yao
Published: September 2022

An element a of a ring R is called a weak zero-divisor if there exists a nonzero x of R such that xa is nilpotent. As a new generalization of nil clean rings, we define a ring R to be weak zero-clean if each of its elements is a sum of a weak zero-divisor and an idempotent. We give some examples and properties of weak zero-clean rings and discuss the relationships between weak zero-clean rings and related rings. Some extensions of weak zero-clean rings are studied. Also, we define and study uniquely weak zero-clean rings and give some characterizations of such rings.
BiGCN: A bi-directional low-pass filtering graph neural network
Authors: Chen Zhixian , Ma Tengfei , Jin Zhihua , Song Yangqiu , Wang Yang
Published: September 2022

Graph convolutional networks (GCNs) have achieved great success on graph-structured data. Many GCNs can be considered low-pass filters for graph signals. In this paper, we propose a more powerful GCN, named BiGCN, that extends to bidirectional filtering. Specifically, we consider the original graph structure information and the latent correlation between features. Thus BiGCN can filter the signals along with both the original graph and a latent feature-connection graph. Compared with most existing GCNs, BiGCN is more robust and has powerful capacities for feature denoising. We perform node classification and link prediction in citation networks and co-purchase networks with three settings: Noise-Rate, Noise-Level, and Structure-Mistakes. Extensive experimental results demonstrate that our model outperforms the state-of-the-art graph neural networks in both clean and artificially noisy data.
Topological states and continuum model for swarmalators without force reciprocity
Authors: Degond Pierre , Diez Antoine , Walczak Adam
Published: September 2022

Swarmalators are systems of agents which are both self-propelled particles and oscillators. Each particle is endowed with a phase which modulates its interaction force with the other particles. In return, relative positions modulate phase synchronization between interacting particles. In the present model, there is no force reciprocity: when a particle attracts another one, the latter repels the former. This results in a pursuit behavior. In this paper, we derive a hydrodynamic model of this swarmalator system and show that it has explicit doubly periodic traveling wave solutions in two space dimensions. These special solutions enjoy non-trivial topology quantified by the index of the phase vector along a period in either dimension. Stability of these solutions is studied by investigating the conditions for hyperbolicity of the model. Numerical solutions of both the particle and hydrodynamic models are shown. They confirm the consistency of the hydrodynamic model with the particle one for small times or large phase noise but also reveal the emergence of intriguing patterns in the case of small phase noise.
Dispersion of Guided Waves in Complex Waveguides: A Hybrid Modeling Technique Combining Gauss–Lobatto–Legendre Node Collation and Semi-Analytical Finite Element Method
Authors: Liu Menglong , Li Lun , Zhang Yaohui , Chen Gongfa , Cui Fangsen
Published: September 2022

Guided waves (GW) are massively used for structural health monitoring and defect evaluation in plate, pipe, and rail structures. To accurately and efficiently calculate the dispersive natures of GW in complex waveguides, this study proposes a novel Gauss–Lobatto–Legendre-based high-order semi-analytical finite element method (GLL-SAFE). Combining the GLL node collation and Lobatto quadrature into SAFE, the mass matrix in the developed GLL-SAFE is diagonal, which enables a faster solution speed and a reduced error of matrix inversion. Firstly, the GWs in the single-layer isotropic material, composite lamina, and composite laminates are calculated with both GLL-SAFE and the conventional Gauss-SAFE featuring an equidistant node collation and Gaussian quadrature. Before reaching the convergence limit, the calculated average relative errors for GLL-SAFE are smaller than those for Gauss-SAFE, and can reach an order of 10[Formula: see text] and 10[Formula: see text] for the phase and group velocity, respectively. Then a novel mesh automatic reconstruction with arbitrary element polynomial order is developed to calculate GW propagation in waveguides of complex cross section. As a hollow cylinder for validation, the calculated average relative errors reach below [Formula: see text] and [Formula: see text] for the phase and group velocity, respectively. Finally, with a complex rail track as the waveguide, the calculated dispersion characteristics with GLL-SAFE show an excellent match with those from the time-domain finite element analysis, and GLL-SAFE shows its higher calculation efficiency over Gauss–SAFE.
Peg solitaire on graphs — A survey
Authors: de Wiljes Jan-Hendrik , Kreh Martin
Published: September 2022

One decade ago, Beeler and Hoilman introduced the game of peg solitaire to arbitrary graphs. Since then, some progress has been made characterizing solvable graphs. Furthermore, several variants of the original game have been considered. The main goal of this paper is to give a proper overview of the results that have been obtained so far (until December 2021) as well as to show which methods are used to prove these. We also present important open questions and research directions, including some new results. The content should be helpful to mathematicians already interested in this topic, but, on the other hand, will provide a perfect starting point for (also early career) researchers looking for a fruitful topic in combinatorial game theory.
Cooperative Localization Using the 3D Euler–Lagrange Vehicle Model
Authors: Oliveros Juan Carlos , Ashrafiuon Hashem
Published: September 2022

Kalman filter-based cooperative localization (CL) algorithms have been shown to significantly improve pose estimations within networks of vehicles but have relied predominantly on two-dimensional kinematic models of the member agents. An inherent deficiency of the commonly employed kinematic vehicle model is the ineffectiveness of CL with only relative position measurements. In this work, we present a singularity-free CL using the full three-dimensional (3D) nonlinear dynamic vehicle model suitable for decentralized control and navigation of heterogeneous networks. We develop the algorithm, present Monte Carlo simulation results with relative pose measurements, and assess the algorithm performance as the number of measurements increases. We further demonstrate that CL with only relative position measurements is effective when using the dynamic model and benefits from increasing number of measurements. We also evaluate the performance of CL with respect to measurement task distribution, which is important in cooperative control of autonomous vehicles.
An integrated framework for surface deformation modelling and induced seismicity forecasting due to reservoir operations
Authors: Meyer Hadrien , Smith Jonathan D. , Bourne Stephen , Avouac Jean-Philippe
Published: September 2022

Induced seismicity and surface deformation are common observable manifestations of the geomechanical effect of reservoir operations whether related to geothermal energy production, gas extraction or the storage of carbon dioxide, gas, air or hydrogen. Modelling tools to quantitatively predict surface deformation and seismicity based on operation data could thus help manage such reservoirs. To that effect, we present an integrated and modular modelling framework which combines reservoir modelling, geomechanical modelling and earthquake forecasting. To allow effective computational cost, we assume vertical flow equilibrium, semi-analytical Green's functions to calculate surface deformation and poroelastic stresses and a simple earthquake nucleation model based on Coulomb stress changes. We use the test case of the Groningen gas field in the Netherlands to validate the modelling framework and assess its usefulness for reservoir management. For this application, given the relative simplicity of this sandstone reservoir, we assume homogeneous porosity and permeability and single-phase flow. The model fits the measured pressure well, yielding a root mean square error (RMSE) of 0.95 MPa, and the seismicity observations as well. The pressure residuals show, however, a systematic increase with time that probably reflects groundwater ingression into the depleted reservoir. The interaction with groundwater could be accounted for by implementing a multiphase-flow vertical flow equilibrium (VFE) model. This is probably the major factor that limits the general applicability of the modelling framework. Nevertheless, he modelled subsidence and seismicity fit very well the historical observations in the case of the Groningen gas field.
Lexical Complexity Prediction: An Overview
Authors: North Kai , Zampieri Marcos , Shardlow Matthew
Published: September 2022

The occurrence of unknown words in texts significantly hinders reading comprehension. To improve accessibility for specific target populations, computational modeling has been applied to identify complex words in texts and substitute them for simpler alternatives. In this article, we present an overview of computational approaches to lexical complexity prediction focusing on the work carried out on English data. We survey relevant approaches to this problem which include traditional machine learning classifiers (e.g., SVMs, logistic regression) and deep neural networks as well as a variety of features, such as those inspired by literature in psycholinguistics as well as word frequency, word length, and many others. Furthermore, we introduce readers to past competitions and available datasets created on this topic. Finally, we include brief sections on applications of lexical complexity prediction, such as readability and text simplification, together with related studies on languages other than English.
Assessment Framework for the Identification and Evaluation of Main Features for Distributed Usage Control Solutions
Authors: Gil Gonzalo , Arnaiz Aitor , Higuero Mariví , Diez Francisco Javier
Published: September 2022

Data exchange between organizations is becoming an increasingly significant issue due to the great opportunities it presents. However, there is great reluctance to share if data sovereignty is not provided. Providing it calls for not only access control but also usage control implemented in distributed systems. Access control is a research field where there has been a great deal of work, but usage control, especially implemented in distributed systems as Distributed Usage Control (DUC), is a very new field of research that presents great challenges. Moreover, little is known about what challenges must really be faced and how they must be addressed. This is evidenced by the fact that existing research has focused non-specifically on different features of DUC, which are not formalized. Therefore, the path for the development of DUC solutions is unclear and it is difficult to analyze the scope of data sovereignty attained by the wide range of DUC solutions. In this context, this article is based on an initial in-depth analysis of DUC related work. In it, the challenges posed by DUC in terms of data sovereignty and the features that must be provided to address them are identified and analyzed for the first time. Based on these features, an initial DUC framework is proposed to assess in a practical and unified way the extent to which DUC solutions provide data sovereignty. Finally, the assessment framework is applied to compare the scopes of the most widespread DUC solutions and identify their limitations.
GraphQL: A Systematic Mapping Study
Authors: Quiña-Mera Antonio , Fernandez Pablo , García José María , Ruiz-Cortés Antonio
Published: September 2022

GraphQL is a query language and execution engine for web application programming interfaces (APIs) proposed as an alternative to improve data access problems and versioning of representational state transfer APIs. In this article, we thoroughly study the GraphQL field, first describing the GraphQL paradigm and its conceptual framework, and then conducting a systematic mapping study of 84 primary studies selected from an original set of 3,185. Our work analyzes trends or knowledge gaps about GraphQL by general classification of the studies and specific classification of this research topic. The study’s main conclusions show that GraphQL adoption is growing in the community as a strong alternative to implement APIs. However, we identified the need to strengthen the amount and rigor of empirical evidence collection in applied industry and government studies. In addition, we revealed the opportunity for specific studies on most GraphQL components, especially the consumption of GraphQL API services.
Modulation of Magnetism and Optical Properties of Hematite (α-Fe2O3) Nanorods Fabricated via Thermal Conversion of Hydrothermally Synthesized Akaganeite (β-FeOOH)
Authors: Aalim Malik , Shah M A
Published: September 2022

A simple hydrothermal approach was used to effectively synthesize high-quality single crystal hematite (α-Fe2O3) nanorods with an average diameter of ∼59.40 nm. Rietveld refinement analysis was used to examine the crystal structure and phase purity of hematite that displayed a hexagonal crystal structure with a single phase in the R-3c space group. Unit cell and other reliability parameters were also determined using Rietveld refinement. In addition, magnetic measurements using a vibrating sample magnetometer (VSM) have been conducted at room temperature from which magnetic hysteresis loops reveal that the material is weakly ferromagnetic with lowered magnetic parameter values. In the synthesized sample, both ferromagnetic (FM) and antiferromagnetic (AFM) contributions were observed and separated by applying a theoretical modification of the measured M-H loop.
Increasing myocardial edema is associated with greater microvascular obstruction in ST-segment elevation myocardial infarction
Authors: Bonfig Nicole L. , Soukup Chase R. , Shah Ananya A. , Olet Susan , Davidson Sarah J. , Schmidt Christian W. , Peterson Rose , Henry Timothy D. , Traverse Jay H.
Published: September 2022

Patients with STEMI ( n = 385) had cardiac MRIs 2 to 3 days following reperfusion with primary PCI to determine the relationship between myocardial edema, LV mass, and MVO. We observed that MVO increased linearly with LV mass and that myocardial edema measured by T2-imaging also increased linearly with LV mass. Patients with MVO had greater edema and LVEDP than subjects without MVO. These findings suggest that myocardial edema which arises from ischemia-reperfusion injury may result in extravascular compression of the microcirculation manifested as MVO on cardiac MRI.
To Study the Effect of Individualized Nursing Model Based on MDT Concept on Limb Function Recovery and Quality of Life in Patients with Breast Cancer
Authors: Chen Yue , Luo Feng , Shi Guo
Published: September 2022

Objective. To study the value of the individualized nursing model based on the concept of multidisciplinary team (MDT) on recovery of limb function and quality of life in patients with breast cancer. Methods. A total of 110 breast cancer patients admitted to our hospital from January 2021 to December 2021 were selected as the research objects. The 110 breast cancer patients were divided into the research group (

n
=
55

) and the control group (

n
=
55

) according to the random number table method. The control group received routine care. The research group implemented individualized nursing based on the MDT concept on the basis of routine nursing. The disabilities of the arm, shoulder, and hand (DASH) scores before nursing and 1 month after nursing were studied in the two groups, Hamilton anxiety scale (HAMA) score, Hamilton depression scale (HAMD) score, and Functional Assessment of Cancer Therapy-B (FACT-B) score. Results. After 1 month of nursing, the DASH score of the research group was lower than that of the control group, and the difference was statistically significant (

P
<
0.05

), and after 1 month of nursing, the HAMA score of the research group was lower than that of the control group (

P
<
0.05

). After 1 month of nursing, the HAMD scale score of the research group was lower than that of the control group, and the difference was statistically significant (

P
<
0.05

). After 1 month of nursing, the FACT-B score of the research group was higher than that of the control group, and the difference was statistically significant (

P
<
0.05

). Conclusion. The individualized nursing model based on the MDT concept has high application value for breast cancer patients. This nursing model can improve the function of limb movement, relieve the patient’s anxiety and depression, and improve the patient’s quality of life. This nursing model is worthy of clinical promotion.
A Consensus-Based Distributed Two-Layer Control Strategy with Predictive Compensation for Islanded Microgrid CPS against DoS Attack
Authors: Liu Xinrui , Hou Min , Yang Jianjun , Sun Yufei
Published: September 2022

Summary.Aiming at the problems of insufficient scalability and slow response speed of the traditional three-layer control structure based on the time scale, this study proposes a distributed two-layer control structure. The primary control uses traditional power-frequency droop control, and the second-level control adopts a consensus protocol to simultaneously achieve the goals of frequency synchronization, frequency non-difference, and power optimization in a distributed manner, which can effectively improve the performance of microgrid frequency adjustment and power optimization. The cyber layer of the AC microgrid cyber-physical system (CPS) is extremely vulnerable to denial-of-service (DoS) attacks, resulting in the inability to achieve control objectives. For this reason, this paper designs a consensus algorithm based on event-triggered and a predictive compensation control link that combines empirical mode decomposition (EMD) and extreme learning machine (ELM) on the basis of the two-layer control structure. Finally, a 4-node islanded microgrid simulation example is used to verify the effectiveness of the proposed strategy. The simulation results show that the two-layer control strategy can achieve microgrid frequency recovery and power optimization while effectively responding to different degrees of DoS attacks.
[Retracted] Optimization Simulation of Supply‐Side Structure of Agricultural Economy Based on Big Data Analysis in Data Sharing Environment
Authors: Sui Yuan , Zhao Jizhu
Published: September 2022

Big data is transforming how people live their lives, and the widespread use of information technology has tremendously aided in the development and deployment of big data technologies. The use of big data technology can lower agricultural production and distribution costs, increase agricultural modernization’s effectiveness, and support the transformation and upgrading of the agricultural economy. Big data technology has garnered a lot of attention as a burgeoning technological area. Big data has revolutionised the service model for “agriculture, rural areas, and farmers” and given agricultural economy supply‐side structure optimization new life. In the age of big data, we should reexamine the way agricultural economic information is currently released, propose more scientific techniques for doing so, and improve the effectiveness of implementation across the board. In light of the background of big data, this research investigates and evaluates the supply‐side structure of the agricultural sector. The big data method is combined in this work to explore and analyse it. This study shows that the supply‐side structure of the agricultural economy, when seen against the backdrop of big data, has a definite impact, with an impact as high as 56.56%. This essay lays the groundwork for future agricultural economy research and development.
[Retracted] Analysis of the Development Level of Green Economy in Different Regions Based on the GA‐BP Model
Authors: Pu Yanping , Cai Yonghui
Published: September 2022

The low‐carbon economy is a green development mode of modern social and economic development. In this paper, an evaluation model of the green economy development level based on GA‐BP is constructed, and the related parameters and network structure of the two algorithms are designed and optimized. The test results show that the predicted value of GA‐BP has a high degree of fit to the actual value, and the data fitting performance is good. The prediction results are in good agreement with the objective reality, which is helpful to put forward appropriate development modes and development path suggestions for the regional development of the low‐carbon economy.
Comparison of Different First‐Line Systemic Therapies in Advanced Biliary Tract Cancer Based on Updated Random Controlled Trials: A Systematic Review and Network Meta‐Analysis
Authors: Feng Long , Wang Ying , Xu Haoqian , Yi Fengming
Published: September 2022

Background and Aim. The prognosis of advanced biliary tract cancer (BTC) is relatively poor, with limited survival. Currently, the first‐line standard of care treatment is gemcitabine plus cisplatin, whereas numerous trials are trying to explore new regimens and prolong the life span of these patients. Herein, we aim to compare the effectiveness of different treatments and conclude more promising regimens for patients with advanced BTC. Methods. We searched PubMed, Web of Science, and Cochrane Library for abstracts and full‐text articles published from database inception through May 2022. All the random controlled trials (RCTs) were assessed and collected as eligible studies. The primary outcome was overall survival (OS). The second outcome was progression‐free survival (PFS). Results. Seventeen studies, including 3632 patients, were selected from 1361 records. In the network meta‐analysis for OS, gemcitabine + cisplatin (GemCis) + cediranib (HR, 0.11; 95% CI, 0.00‐2.88), GemCis+durvalumab (HR, 0.27; 95% CI, 0.06‐1.29), and GemCis + merestinib (HR, 0.37; 95% CI, 0.03‐4.36) showed the trend of OS benefit over standard treatment (GemCis), although there was no significant difference. GemCis, GemOxa, and gemcitabine+S1 (GemS1) did not differ when comparing OS. In the network meta‐analysis for PFS, GemCis+merestinib (HR, 0.67; 95% CI, 0.54‐0.83) and GemCis+durvalumab (HR, 0.22; 95% CI, 0.08‐0.62) showed PFS benefit over standard treatment (GemCis) with a significant difference. GemCis, GemOxa, and GemS1 did not differ when comparing PFS. Conclusion. GemCis+durvalumab might be the most promising regimen for advanced BTC when considering OS and PFS. GemOxa and GemS1 could be alternative options for advanced BTC patients with nontolerance to GemCis.
Insulator and Burst Fault Detection Using an Improved Yolov3 Algorithm
Authors: Fangrong Zhou , Hao Pan , Guochao Qian , Yutang Ma , Gang Wen , Chao Xu , Peng Kong , Guobo Xie , Xiaofeng Zheng
Published: September 2022

Insulators play an important role in the operation of outdoor high-voltage transmission lines. However, insulators are installed in outdoor environments for long periods and thus failures are inevitable. It is necessary to conduct timely insulator inspection and maintenance. In this paper, an improved Yolov3 target detection network (Yolov3-CK) is proposed in order to achieve higher detection accuracy and speed. First, Yolov3-CK uses the CIOU loss function instead of the mean square error loss function from Yolov3. Second, the Yolov3-CK model uses cluster analysis of the priori box via the

k

-means++ algorithm to obtain a priori box size that is more suitable for the detection of insulators and their burst faults. Finally, we use a dataset obtained by performing data enhancement on the China power line insulator dataset to train and test the data-enhanced Yolov3-CK model. The mean precision of Yolov3-CK reaches 91.67% with 47.9 frames processed per second. Yolov3-CK provides better detection accuracy and a higher processing rate than Faster RCNN, SSD, and Yolov3. Therefore, the Yolov3-CK model is more suitable for the detection of insulators and their burst faults.
Cognitive Function and Vitamin D Status in the Chinese Hemodialysis Patients
Authors: Zhang Jing , Hu Jun , Zhou Ru , Xu Yuzhen
Published: September 2022

Objective. Vitamin D insufficiency and the cognitive function decline are both common in patients receiving hemodialysis (HD). The present study evaluated the relation between cognitive function and circulating vitamin D levels in HD patients in Wannan Medical College Affiliated Yijishan Hospital, China. Methods. This study was conducted in 80 patients receiving HD in Wannan Medical College Affiliated Yijishan Hospital. To measure cognitive function, Montreal Cognitive Assessment-Basic (MoCA-B) Chinese Version was used. The 25-hydroxyvitamin D [25(OH)D], which is applied to assess vitamin D status, was tested. One-way ANOVA, Tukey post hoc test, and the correlation and regression analysis were used in this study. Results. Based on the MoCA-B, cognitive function decline (the scores below 26) was present in 28 HD patients, accounting for 35% (28/80). The mean age of these patients is

50.5
±
10.9

years old. The mean level of 25(OH)D was

16.1
±
7.3
 
ng
/
ml

in 80 HD patients. In univariate analysis, there was a significant relationship between MoCA-B score and serum 25(OH)D level (

p
<
0.05

). The level of 25(OH)D was positively correlated with MoCA-B score (

r
=
0.312

,

p
=
0.023

), and the association was independent of demographic and clinical features. Conclusions. Vitamin D insufficiency may contribute to cognitive function decline in HD patients. Serum level of 25(OH)D is an independent protective factor of cognitive function in the HD patients.
The Sharp Upper Bounds of the Hankel Determinant on Logarithmic Coefficients for Certain Analytic Functions Connected with Eight-Shaped Domains
Authors: Sunthrayuth Pongsakorn , Iqbal Naveed , Naeem Muhammad , Jawarneh Yousef , Samura Sallieu K.
Published: September 2022

The present study’s intention is to produce exact estimations of some problems involving logarithmic coefficients for functions belonging to the considered subcollection

B

T

sin

of the bounded turning class. Furthermore, for the class

B

T

sin

, we look into the accurate bounds of the Zalcman inequality, Fekete-Szegö inequality along with

D

2
,
1

G

g

/
2

and

D

2

,

2

G

g

/

2

. Importantly, all of these bounds are shown to be sharp.
Exercise and Metformin Intervention Prevents Lipotoxicity-Induced Hepatocyte Apoptosis by Alleviating Oxidative and ER Stress and Activating the AMPK/Nrf2/HO-1 Signaling Pathway in db/db Mice
Authors: Zhang Yuan , Liu Yuting , Liu Xiaowei , Yuan Xinmeng , Xiang Mengqi , Liu Jingjing , Zhang Liumei , Zhu Shouqian , Lu Jiao , Tang Qiang , Cheng Sulin
Published: September 2022

Objective. Nonalcoholic fatty liver disease (NAFLD) and type 2 diabetes (T2DM) commonly coexist and act synergistically to drive adverse clinical outcomes. This study is aimed at investigating the effects of exercise intervention and oral hypoglycaemic drug of metformin (MET) alone or combined on hepatic lipid accumulation. To investigate if oxidative stress and endoplasmic reticulum stress (ERS) are involved in lipotoxicity-induced hepatocyte apoptosis in diabetic mice and whether exercise and/or MET alleviated oxidative stress or ERS-apoptosis by AMPK-Nrf2-HO-1 signaling pathway. Methods. Forty db/db mice with diabetes (

random
 
blood
 
glucose
≥
250
 
mg
/
dL

) were randomly allocated into four groups: control (CON), exercise training alone (EX), metformin treatment alone (MET), and exercise combined with metformin (EM) groups. Hematoxylin-eosin and oil red O staining were carried out to observe hepatic lipid accumulation. Immunohistochemical and TUNEL methods were used to detect the protein expression of the binding immunoglobulin protein (BiP) and superoxide dismutase-1 (SOD1) and the apoptosis level of hepatocytes. ERS-related gene expression and the AMPK-Nrf2-HO-1 signaling pathway were tested by western blotting. Results. Our data showed that db/db mice exhibited increased liver lipid accumulation, which induced oxidative and ER stress of the PERK-eIF2α-ATF4 pathway, and hepatocyte apoptosis. MET combined with exercise training significantly alleviated hepatic lipid accumulation by suppressing BiP expression, the central regulator of ER homeostasis, and its downstream PERK-eIF2α-ATF4 pathway, as well as upregulated the AMPK-Nrf2-HO-1 signaling pathway. Moreover, the combination of exercise and MET displayed protective effects on hepatocyte apoptosis by downregulating Bax expression and TUNEL-positive staining, restoring the balance of cleaved-caspase-3 and caspase-3, and improving the antioxidant defense system to prevent oxidative damage in db/db mice. Conclusion. Compared to MET or exercise intervention alone, the combined exercise and metformin exhibited significant effect on ameliorating hepatic steatosis, inhibiting oxidative and ER stress-induced hepatocyte apoptosis via improving the capacity of the antioxidant defense system and suppression of the PERK-eIF2α-ATF4 pathway. Furthermore, upregulation of AMPK-Nrf2-HO-1 signaling pathway might be a key crosstalk between MET and exercise, which may have additive effects on alleviating hepatic lipid accumulation.
Evaluation Method and Implementation of Vocal Music Teaching Performance under a Wireless Communication Environment
Authors: Liu Hengbo
Published: September 2022

With the development of society, modern educational technology and electronic information technology are more and more closely combined. Auxiliary teaching products based on computer technology, multimedia technology, and network technology emerge one after another. How to combine modern wireless communication technology with modern educational technology to evaluate the teaching effect has become one of the hot topics in the field of modern teaching research. In view of the lack of communication between teachers and students and evaluation methods of the teaching effect in traditional vocal music teaching, this paper designs a method of evaluation of vocal music teaching effect in a wireless communication environment. First, this paper designs a feedback system of vocal music teaching based on wireless communication. Second, due to the influence of vocal music teaching effect, the factors are diverse, and the neural network has the advantages in processing the data with nonlinear strong robustness and dynamic characteristics. And we use BP (back propagation) neural network as a mathematical model to receive teaching feedback information. Then, the simulation results show that the proposed method can not only evaluate the effect of vocal music teaching but also has good feasibility and practicability. Finally, the method proposed in this paper can help improve the teaching level and efficiency of the school and has a great theoretical value and practical potential.
DC/DC Modular Multilevel Converters for HVDC Interconnection: A Comprehensive Review
Authors: Erat Abdurrahim , Vural Ahmet Mete
Published: September 2022

High voltage direct current (HVDC) technology is a key component in power systems owing to huge benefits such as long-distance power transmission, lower losses, asynchronous grid interconnections, controllability, system availability, and limited short-circuit currents. HVDC transmission is a cost-effective method of transporting huge amounts of power across long distances with little loss. It can also link asynchronous alternative current (AC) networks while balancing the grid. DC/DC converters are one of the most important components for HVDC power transmission, and DC/DC modular multilevel converters (MMCs) are the backbone of HVDC grid interconnections. The DC/DC MMC is a highly regarded converter architecture for medium/high-voltage DC grid interconnection. DC/DC MMC topologies play a key role in modern HVDC networks with varying voltage levels. This paper’s fundamental aim is to offer a recent comprehensive review of HVDC topologies, current DC/DC modular multilevel converter (MMC) topologies for HVDC interconnection, and DC/DC MMC control techniques.
Analysis and Application of the Business English Translation Query and Decision Model with Big Data Corpus
Authors: Gong Jufang
Published: September 2022

This paper aims to build an English translation query and decision support model using big data corpus and applies it to business English translation. Firstly, the existing convolutional network is improved by using depth-separable convolution, and the input statements are mapped to the depth feature space. Secondly, the attentional mechanism is used to enhance the expressive ability of input sentences in deep feature space. Then, considering the sequential relationship, use long short-term memory (LSTM) neural network as a decoder block to generate the corresponding translation of the input sentence. Finally, nonparametric metric learning module is used to improve the model in an end-to-end way. Wide range of experiments on the multiple corpora have shown the proposed model has better real-time performance while maintaining high precision in translation and query, and it has a certain practical application value.
[Retracted] Correlation Analysis between Emotion Control and Professional Self‐Efficacy of Singing Artists Based on Multidimensional Environment
Authors: Liu Ziyu
Published: September 2022

The tertiary industry occupies a large area in China’s economic system, and it plays an important function in the growth of China’s economic development. It is of positive significance to study the relationship between emotional labor and occupational self‐efficacy of singing artists in the tertiary industry. This paper mainly studies the correlation between the emotional labor of singing artists and their professional self‐efficacy and analyzes the strength of the correlation. This paper selects 150 singing art personnel in the singing art association in city A to conduct a questionnaire survey and conducts data processing on the questionnaire. This paper explores the influencing factors of emotional labor and four dimensions of occupational self‐efficacy. This paper firstly analyzes the differences of the influencing factors of emotional labor and then tests the interaction of the different factors selected. It then conducts a significant test on the four dimensions of professional self‐efficacy and finally studies the correlation between the two based on the previous analysis results. This paper concludes that there is a highly significant relationship between the emotional labor and professional ego efficacy of singing artists. And the correlation coefficient and determination coefficient are 0.293 and 0.087, respectively. It shows that 8.7% of the total variance in occupational self‐efficacy variables can be explained by emotional labor. There was no significant correlation between surface acting and occupational self‐efficacy. Deep acting has the greatest correlation with the physical and mental efficacy dimension of occupational self‐efficacy, with a correlation coefficient of 0.391. There were significant correlations between natural performance and the four dimensions of occupational self‐efficacy. The highest value is interpersonal efficacy, which is 0.337. The research conclusions of this paper have certain reference value for exploring the relationship between emotional labor and professional self‐efficacy of singing artists.
[Retracted] Tourism Demand Prediction Model Using Particle Swarm Algorithm and Neural Network in Big Data Environment
Authors: Xu Sai , Wang Shuxia
Published: September 2022

Since demand forecasting is the first step in managing and operating a tourism business, its accuracy is very important to tourism businesses. In order to address NN’s drawbacks, such as local optimization, slow convergence, and large sample sizes, this paper organically combines the PSO and NN models and builds a PSO‐NN‐based tourism demand forecasting model. The tourism demand forecasting indexes, the choice of NN forecasting models, the modelling process, and the implementation methods are first analysed and studied along with the fundamental theories and forecasting techniques of PSO and NN. In order to increase the precision of the prediction model, the PSO algorithm is also used to optimise the weights and thresholds of the NN. The final section of the paper compares the performance of the model developed in this paper with the most widely used model for forecasting tourism demand. According to the experimental findings, this model’s prediction accuracy can reach 95.81 percent, or about 10.09 percent higher than the prediction accuracy of the conventional NN model. There are some practical implications to this research. Applying the optimization model to the forecast of tourism demand is doable and practical.
Efficient One-Pot Synthesis of TiO2/ZrO2/SiO2 Ternary Nanocomposites Using Prunus × Yedoensis Leaf Extract for Enhanced Photocatalytic Dye Degradation
Authors: Manikandan Velu , Packialakshmi J. Saranya , Bharti Bandna , Jayanthi Palaniyappan , Dhandapani Ranjithkumar , Velmurugan Palanivel , Elango Duraisamy , Paramasivam Ragul , Mohanavel Vinayagam , Syed Asad , Elgorban Abdhallah M. , Bahkali Ali H. , Muthupandian Saravanan
Published: September 2022

A simple, efficient, and ecofriendly method was employed to synthesize TiO2/ZrO2/SiO2 ternary nanocomposites using Prunus × yedoensis leaf extract (PYLE) that shows improved photocatalytic and antibacterial properties. The characterization of the obtained nanocomposites was done by X-ray powder diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), Raman spectroscopy, field-emission scanning electron microscopy (FE-SEM), and energy-dispersive X-ray spectroscopic (EDS) analysis. The synthesized ternary nanocomposites with nanoscale pore diameters were investigated for the elimination of Reactive Red 120 (RR120) dye. The obtained results showed about 96.2% removal of RR120 dye from aqueous solution under sunlight irradiation. Furthermore, it shows promising antibacterial activity against Staphylococcus aureus and Escherichia coli. The improved photocatalytic and antibacterial activity of TiO2/ZrO2/SiO2 may bring unique insights into the production of ternary nanocomposites and their applications in the environment and biomedical field.
Which Factors Affect User Satisfaction with ETC? Evidence from Shanghai and Beijing
Authors: Xiao Guangnian , Lu Qiongwen , Ni Anning , Zhang Chunqin , Zong Fang
Published: September 2022

Owing to the current development trend of globalization and informatization, traditional transportation technologies and means can no longer meet the needs of economic and social development. Thus, intelligent transportation will be an inevitable and revolutionary choice for the development of the transportation industry. As a subsystem of the intelligent transportation system, the electronic nonstop toll collection (ETC) system provides a good solution to the problems of traffic congestion, environmental pollution, energy consumption, and low toll operation efficiency caused by expressway toll collection. This high-technology system is utilized in many fields, such as radio communication and computer and automatic control in the transportation field. China’s expressway ETC systems have evident effects on congestion reduction at toll stations. Although the advantages of ETC lanes are significant, and China actively implements ETC-handling policies, some drivers are reluctant to install ETC on-board systems or they have negative experiences after handling them. According to a survey, existing literature lacks research on the factors affecting user satisfaction with ETC. On the basis of the questionnaire data of ETC user experience in Shanghai and Beijing, we comprehensively investigate the reasons of banking, ETC equipment, and drivers’ personal factors and travel characteristics to establish an ordinal logistics model. Through cluster analysis, drivers in the two cities are divided into three groups, and the significance of related variables is further analyzed. This research can help us understand the degree of influence of different factors on user satisfaction with ETC to a certain extent. Moreover, effective methods and measures can be used to promote the popularity of ETC vehicle equipment and the utilization rate of ETC-dedicated lanes.