bluuebunny/crossref_metadata_2025 huggingface dataset:
Gender-related factors and out-of-hospital cardiac arrest incidence in women and men: analysis of a population-based cohort study in the Netherlands
Authors: Smits Robin L A , van Dongen Laura H , Blom Marieke T , Tan Hanno L , van Valkengoed Irene G M
Published: July 2022

Background

The incidence of out-of-hospital cardiac arrest (OHCA) differs consistently between women and men. Besides sex-related (biological) factors, OHCA risk may relate to gender-related (sociocultural) factors. We explored the association of selected gender-related factors with OHCA incidence in women and men.

Methods

We combined data on emergency medical services-attended OHCA with individual-level data from all women and men aged ≥25 years living in North Holland, the Netherlands. We estimated the associations between employment status, primary earner status, living with children and marital status and the OHCA incidence with Cox proportional hazards models stratified by sex and adjusted for age and socioeconomic status. To determine if metabolic factors explain the associations, we added hypertension, diabetes mellitus and dyslipidaemia to the models. Population attributable fractions (PAF) for all gender-related factors were calculated.

Results

All four gender-related factors were associated with OHCA incidence (eg, unemployed vs employed; HR 1.98, 95% CI 1.67 to 2.35 in women; HR 1.60, 95% CI 1.44 to 1.79 in men). In both sexes, those unemployed, those who are not primary earners, those living without children, and married or divorced individuals had an increased OHCA risk. The PAF ranged from 4.9 to 40.3 in women and from 4.4 to 15.5 in men, with the highest PAF for employment status in both sexes. Metabolic risk factors did not explain the observed associations.

Conclusion

Gender-related factors were associated with risk of OHCA and contributed substantially to the OHCA burden at the population level, particularly in women. Employment status contributed most to the OHCA burden.
Impact of an extrafascial versus intrafascial injection for supraclavicular brachial plexus block on respiratory function: a randomized, controlled, double-blind trial
Authors: Grape Sina , Kirkham Kyle , Zemirline Nadjib , Bikfalvi Alexis , Albrecht Eric
Published: July 2022

Introduction

Hemidiaphragmatic paresis after ultrasound-guided supraclavicular brachial plexus block is reported to occur in up to 67% of patients. We tested the hypothesis that an injection outside the brachial plexus sheath reduces the incidence of hemidiaphragmatic paresis compared with an intrafascial injection while providing similar analgesia.

Methods

Fifty American Society of Anesthesiologists I–III patients scheduled for elective upper limb surgery received a supraclavicular brachial plexus block using 30 mL of 1:1 mixture of mepivacaine 1% and ropivacaine 0.5%. The block procedures were randomized to position the needle tip either within the brachial plexus after piercing the sheath (intrafascial injection) or outside the brachial plexus sheath (extrafascial injection). The primary outcome was the incidence of hemidiaphragmatic paresis 30 min after the injection, measured by M-mode ultrasonography. Additional outcomes included time to surgery readiness, and resting and dynamic pain scores at 24 hours postoperatively (Numeric Rating Scale, 0–10).

Results

The incidence of hemidiaphragmatic paresis 30 min after the injection was 9% (95% CI 1% to 29%) and 0% (95% CI 0% to 15%) in the intrafascial and extrafascial groups respectively (p=0.14). Extrafascial injection was associated with a longer time to surgery readiness (intrafascial: 18 min (95% CI: 16 to 21 min); extrafascial: 37 min (95% CI: 31 to 42 min); p<0.001). At 24 hours, resting and dynamic pain scores were similar between groups.

Discussion

Ultrasound-guided supraclavicular brachial plexus block with an extrafascial injection does not reduce the incidence of hemidiaphragmatic paresis although it provides similar analgesia, when compared with an intrafascial injection. The longer time to surgery readiness is less compatible with contemporary operating theater efficiency requirements.

Trial registration number

NCT03957772.
Comparative study of magnetic moment of leptons in hot and dense media
Authors: Masood Samina , Mein Holly
Published: July 2022

We study the magnetic moment of leptons in extremely hot universe and superdense media of stars at high temperatures. Anomalous magnetic moment of charged leptons is inversely proportional to its mass, whereas the induced dipole moment of neutral leptons is directly proportional to their mass. Neutral massive point particles exert nonzero magnetic moment as a higher order effect, which is smaller than the anomalous magnetic moment of a charged particle of their same flavor partner. All leptons acquire some extra mass due to their interaction with the medium and affect the magnetic moment accordingly. We compare the contribution to the magnetic moment of various leptons due to their temperature and chemical potential dependent masses. It is shown that the magnetic moment contributions are nonignorable for lighter leptons and heavy neutrinos. These calculations are very important to study the particle propagation in the early universe and in superdense stellar media.
LRS Bianchi type-I cosmological models with periodic time varying deceleration parameter in f(R,T) gravity
Authors: Pradhan Anirudh , Dixit Archana , Varshney Gunjan
Published: July 2022

In this research, we examine a spatially homogeneous anisotropic locally rotationally symmetric (LRS) Bianchi type-I cosmological model in [Formula: see text] gravity, for some choices of the function [Formula: see text] (arXiv:1104.2669 [gr-qc]). The precise solutions of the field equations are introduced for the periodic-time varying deceleration parameter that can adjust to meet the [Formula: see text]CDM model. We have reviewed the physical and dynamic characteristics of these models to understand the accelerated expansion of the Universe in the current era. Furthermore, SNe Ia union data (arXiv:0811.2379 [astro-ph]), SN Ia with BAO and CMB observations (arXiv:1203.3213 [astro-ph.CO]) and OHD[Formula: see text]JLA data (arXiv:1711.03437 [astro-ph.CO]) are used to estimate the statefinder diagnostics to get the geometric dynamics of the Universe at distinct stages and also to find the luminosity distance, angular-diameter distance, and distance modulus. We have also investigated the transit points for the deceleration parameter (q) in the framework of these three observations within the range of redshift [Formula: see text].
Crow Search with Adaptive Awareness Probability-Based Deep Belief Network for Detecting Ransomware
Authors: P A Shemitha , Dhas Julia Punitha Malar
Published: July 2022

“Crypto ransomware is defined as malware that blocks the user file’s access by encrypting them and demands them with a ransom for obtaining the decryption key”. This causes some major threats in many of the companies. Therefore, the detection of ransomware is needful for reducing the workloads of the analysts and also for finding the variations in unknown samples. The adopted scheme encompasses 3 phases: (i) feature extraction, (ii) feature selection and (iii) classification. Initially, the sequential frequent patterns are extracted using the apriori framework. However, the major challenge in this extracted sequential pattern is the curse of dimensionality. To overcome this, the selection of optimal features is very important, which is done as the second stage. In this, the optimization concept is evolved for the optimal selection of these extracted sequential patterns. Furthermore, the optimal patterns are given for classification, where DBN is deployed. Particularly, for the selection of the optimal sequential pattern, this work proposes a new crow search with adaptive awareness probability (CS-AAP) model. In the end, analysis is performed to authorize the supremacy of the developed scheme.
Levi-type Schur–Sergeev duality for general linear super groups
Authors: Wang Di
Published: July 2022

In this paper, we investigate a kind of double centralizer property for general linear supergroups. For the super space [Formula: see text] over an algebraically closed field [Formula: see text] whose characteristic is not equal to [Formula: see text], we consider its [Formula: see text]-homogeneous one-dimensional extension [Formula: see text], and the natural action of the supergroup [Formula: see text] on [Formula: see text]. Then we have the tensor product supermodule ([Formula: see text], [Formula: see text]) of [Formula: see text]. We present a kind of generalized Schur–Sergeev duality which is said that the Schur superalgebras [Formula: see text] of [Formula: see text] and the so-called weak degenerate double Hecke algebra [Formula: see text] are double centralizers. The weak degenerate double Hecke algebra is an infinite-dimensional algebra, which has a natural representation on the tensor product space. This notion comes from [B. Shu, Y. Xue and Y. Yao, On enhanced reductive groups (I): Parabolic Schur algebras and the dualities related to degenerate double Hecke algebras, preprint (2013), arXiv:2005.13152 [Math. RT]], with a little modification.
Mechanical Properties of Metal Nanolaminates
Authors: Beyerlein Irene J. , Li Zezhou , Mara Nathan A.
Published: July 2022

This article reviews recent basic research on two categories of metal-based nanolaminates: those composed of metal/metal constituents and those composed of metal/ceramic constituents. We focus primarily on studies that aim to understand—via experiments, modeling, or both—the biphase interface structure and its role in changing the mechanisms that govern strength and deformability at a fundamental level. We anticipate that, by providing a broad perspective on the latest advances in nanolaminates, this review will aid design of new metallic materials with unprecedented combinations of mechanical and physical properties.
Observation of Visual Quality after Femtosecond Laser-Assisted Cataract Surgery Combined with Trifocal Intraocular Lens Implantation
Authors: Ma Jianli , Sun Xuequan , Liu Yang , Liu Yumei
Published: July 2022

Objective. This study is the first observation of Alcon’s PanOptix trifocal intraocular lens (IOL) implanted in 55 cataract patients with femtosecond laser-assisted cataract surgery. Methods. Fifty-five patients (63 eyes) with cataract were treated with femtosecond laser-assisted cataract surgery combined with trifocal IOL implantation. Visual acuity, defocus curve, higher order aberration (HOA), refractive stability, eyeglass removal rate, and satisfaction were evaluated and analyzed. Results. We found that the visual acuity of patients with near, intermediate, and distance vision was better than 0.1 LogMAR at 1, 3, and 6 months after the completion of surgery. The uncorrected near visual acuity (UCNVA), uncorrected intermediate visual acuity (UCIVA), and uncorrected distance visual acuity (UCDVA) of patients at 1, 3, and 6 months after surgery were compared with those before operation, showing statistical significance. Six months after the operation, all patients’ surgical eyes had a smooth transition in the defocus range from +0D to -2.5D, and the visual acuity of the surgical eyes reached a level better than 0.1 LogMAR. The statistical results of 6-month follow-up showed that the eyeglass removal rate at near, intermediate, and far distances was 100%. At 6 months postoperatively, only 1 case had nocturnal glare, which affected life; 3 cases developed glare and halo but did not affect life. The patient satisfaction rate was 98.18%. Conclusions. Femtosecond laser-assisted cataract surgery with trifocal IOL implantation can remove the lens from the patient with satisfactory visual quality and significantly improve the postoperative satisfaction of the patient.
Radiative Flow of Copper and Aluminum Nanoparticles with Heat Source Phenomenon: Dual Numerical Simulations and Stability Analysis
Authors: Dero Sumera , Lund Liaquat Ali , Kamel Al-Khaled , Imran Asjad Muhammad , Muhammad Taseer , Khan Sami Ullah , Abbasi A
Published: July 2022

The thermally developed flow of nanoparticles due to bidirectional moving space has been presented numerically. The additional impact of heat source and sink are also incorporated for enhancing the heat transfer rate. The copper and aluminum nanoparticles are selected for enhancing the thermal diffusion system. The thermal stability of nanoparticles is carefully addressed. The moving surface allows the shrinking and stretching phenomenon. The system of resulting equations with nonlinear nature is numerically swapped via shooting technique with help of MATLAB software. The dual numerical simulations for the thermally radiative problem with external heating phenomenon are being performed. It is noted from results that thermal stability of nanoparticles is more stable in the upper branch of shrinking/stretching surface. The presence of heat source provides extra heat and improves the thermal transportation phenomenon which is more progressive in upper branch. The enhancement in temperature profile due to copper nanoparticles is more stable as compared to aluminum nanoparticles. Moreover, the increasing change in the velocity is resulted upon increasing the rotation constant. The obtained results reflect applications in thermal sciences, heating systems, energy production, solar applications, nuclear reactions, biomedical applications, etc.
A Nomogram to Predict Noninflammatory Skin Involvement of Invasive Breast Cancer
Authors: Zhu Xueli , Tian Shaolin , Jiang Ran , Gao Dan , Chen Bo , Lu Wenliang
Published: July 2022

Purpose. The aim of this study was to develop and assess a nomogram to predict noninflammatory skin involvement of invasive breast cancer. Methods. We developed a prediction model based on SEER database, a training dataset of 89202 patients from January 2010 to December 2016. Multivariable logistic regression analysis was applied to build a predicting model incorporating the feature selected in the least absolute shrinkage and selection operator regression model. Discrimination, calibration, and clinical usefulness of the predicting model were assessed using the C‐index, calibration plot, and decision curve analysis. Internal validation was assessed using the bootstrapping validation. Results. Predictors contained in the prediction nomogram included use of age, race, grade, tumor size, stage‐N, ER status, PR status, and Her‐2 status. The model shows good discrimination with a C‐index of 0.857 (95% confidence interval: 0.807–0.907) and good calibration. High C‐index value of 0.847 could still be reached in the internal validation. Conclusion. This study constructed a novel nomogram with accuracy to help clinicians access the risk of noninflammatory skin involvement by tumor. The assessment of clinicopathologic factors can predict the individual probability of skin involvement and provide assistance to the clinical decision‐making.
English Speech Recognition and Pronunciation Quality Evaluation Model Based on Neural Network
Authors: Wang Li
Published: July 2022

An in-depth neural network-based approach is proposed to better develop an assessment model for English speech recognition and call quality assessment. By studying the structure of a deep nonlinear network, you can approximate complex functions, define distributed representations of input data, demonstrate a strong ability to learn important data set characteristics from some sample sets, and better simulate human brain analysis, and learning. The author uses in-depth learning technology to recognize English speech and has developed a speech recognition model with a deep belief network using the characteristics of the honey frequency centrum based on human hearing patterns. The test results show that examples include 210 machine and manual evaluations and 30 samples with first-grade differences. The overall compatibility level of the machine and human evaluation is 90.65%, and the adjacency consistency level is 90.65%. This is 100%, and the correlation coefficient is 0.798. We need to evaluate the quality of speech and pronunciation in English, which indicates a strong correlation between machine estimates and human estimates.
Treatment of Fracture of the Calcaneus via Bone Axial X-Ray Image-Based Minimally Invasive Approach
Authors: Xiao Jie , Xin Zengfeng , Fu Xiaojun , Huang Jiaqi , Zhang Bi , Yu Haiping
Published: July 2022

To discuss the values of two bone axial X-ray image-based minimally invasive approach surgeries in the diagnosis and treatment of fracture of the calcaneus, 80 patients diagnosed with fracture of the calcaneus by bone axial X-ray examination were selected and divided equally into the minimally invasive longitudinal approach (MILA) group (40 cases) and the sinus tarsal approach (STA) group (40 cases). Besides, the duration of operation, the incidence of complications, the time-to-start weight training, and the American Orthopaedic Foot and Ankle Society (AOFAS) foot function scoring system between the patients in the two groups were compared. The results showed that the duration of operation and incidence of complications among the patients in the MILA group (42.87±5.12minutes, 20%) were both superior to those among the patients in the STA group (60.43±7.31minutes, 32.5%). The time-to-start weight training in the MILA group was 5.2 weeks, which was obviously shorter than that in the STA group (5.7 weeks). The difference in AOFAS scores between the two groups was not significant. The walking pavement score in the MILA group (4.2±0.37points) was slightly higher than that in the STA group (3.3±0.45points), and the differences demonstrated statistical meaning (P<0.05). To sum up, the bone axial X-ray image is an essential examination method of diagnosing fracture of the calcaneus. The two minimally invasive methods both showed good clinical therapeutic effects. The operation of MILA was relatively shorter with fewer complications and is worthy of being promoted as an effective treatment method of fracture of the calcaneus.
Advancements and Future Prospects of Electric Vehicle Technologies: A Comprehensive Review
Authors: Hossain M. S. , Kumar Laveet , El Haj Assad Mamdouh , Alayi Reza
Published: July 2022

Greenhouse gas (GHG) emissions are one of the major problems that the world is facing nowadays. The transportation sector, where vehicles run on oil, contributes a large amount of GHG. The development of electric vehicles to meet the allowed GHG limits has recently been the main focus of research worldwide. Research in electric vehicles (EVs) has observed a tremendous upsurge in recent years. However, reviews that analyze and present the demand and development of EVs comprehensively are still inadequate, and this integrative review is an effort to fill that gap. This study has revealed many thought‐provoking understandings related to specific developments, specifically global demand and growth of EVs along with electricity and battery demand, current technological developments in EVs, energy storage technologies, and charging strategies. It also details the next generation of EVs and their technological advancements, such as wireless power transfer. The development of a smart city concept by EV implementation added a new aspect to this review. The summary would be advantageous to both scholars and policymakers, as there has been a lack of integrative reviews that assessed EVs’ global demand and development simultaneously and collectively. This review concludes the intuitions for investors and policymakers to envisage electric mobility.
Neural Network-Based Routing Energy-Saving Algorithm for Wireless Sensor Networks
Authors: Pang Lili , Xie Jiaye , Xu Qiqing
Published: July 2022

With the evolvement, standards have changed, mobile Internet technology has also been upgraded, and it has also driven the development of smart objects mobile. With the continuous development of smart objects mobile, the bottleneck of small node size and low battery energy storage has not been solved in the end, which makes the research of wireless sensor network energy-saving technology become the focus, and the improvement of routing technology is an effective way to improve energy-saving technology. From the data transmission energy consumption of smart objects mobile, the routing algorithm of smart objects mobile is discussed and analyzed and the classical representative LEACH is the object of in-depth research. Routing algorithms can easily and reliably process network data and make the network work well and are widely used in highly secure military systems and smaller commercial networks. Aiming at these deficiencies, a corresponding improved algorithm is proposed, and it is tested through simulation and specific experiments to verify the correctness and the system’s reliability. The SMPSO-BP algorithm converges when the number of iterations is about 600, which is earlier than the LEACH algorithm and the improved LEACH algorithm, so the SMPSO-BP algorithm is due to the other two algorithms. In the wireless sensor network routing energy consumption experiment, in addition, the SMPSO-BP algorithm uses less energy than the other two methods. Therefore, the energy-saving algorithm under the neural network data fusion mechanism is still feasible.
Correlation Analysis between Atmospheric Environment and Public Sentiment Based on Multiple Regression Model
Authors: Duan Lei
Published: July 2022

In recent years, with the gradual improvement of the public’s demands for ecological and environmental services, changes in environmental quality, especially atmospheric environmental quality, have been highly concerned by the public. Public environmental emotions belong to psychological space information. How to quantify the changes in public environmental emotions caused by changes in environmental quality, comprehensively analyze the atmospheric physical and chemical factors that have a key impact on public environmental emotions, and achieve quantifiable and predictable public environmental emotions are difficult points of current research in the field of public environment. Based on the public participation perception method, this paper proposes a public environmental sentiment prediction model based on the analysis of the relationship between atmospheric environment and public environmental sentiment by using the collected public environmental satisfaction data. Taking the data of a city as an example, using atmospheric environmental factors and public environmental satisfaction, a multiple regression model (OLS) was established, and PM2.5, PM10, temperature (TMP), and humidity (HUM) were used as key factors to conduct Pearson correlation analysis with public environmental satisfaction. The results showed that PM2.5 and PM10 showed a strong negative correlation with public environmental satisfaction (-0.82 and -0.67), while TMP and HUM showed a weak positive correlation with public environmental satisfaction (0.3 and 0.19). Therefore, reducing the concentration of PM2.5 and PM10 in the city has a positive effect on improving public environmental satisfaction.
Effect Analysis of Positive Molecular Therapy in Surgical Nursing Based on Data Transformation Analysis
Authors: Liu Yuan , Wu Sumei , Wang Guifen , Sun Xiaoxue , Liu Lei , Zhao Yaling
Published: July 2022

This paper briefly introduces the concept, classification, and mechanism of action of positive thinking therapy; reviews the application and research progress of positive thinking therapy in perioperative care of surgical patients at home and abroad; presents the shortcomings and defects in the development; and aims to provide intervention, reference, and basis for the development of positive thinking therapy in perioperative care of surgical patients. One hundred and eight patients are undergoing PCI surgery in our cardiology department; 50 patients undergoing percutaneous coronary intervention were selected as the control group, and 58 patients undergoing percutaneous coronary intervention were selected as the observation group. Traditional health education was employed in the control group, while empowerment education based on timing theory was used in the observation group. The two groups were observed and compared in terms of self-care competence, anxiety and depression, medication adherence score, and exercise adherence. Conclusion. Empowerment education based on timing theory can improve self-care ability of PCI patients, reduce patients’ anxiety and depression, and improve patients’ medication and exercise compliance.
Subthreshold Micropulse Treatment Laser versus Half-Dose Photo Dynamic Therapy for the Chronic Central Serous Chorioretinopathy with Parafoveal or Subfoveal Leakage STML versus PDT for Treatment of Chronic CSC
Authors: Chen Qingshan , Zhao Xia , Yin Qiuju , Li Zhi , Zhao Zimei , Ning Jiafeng
Published: July 2022

Purpose. The study aimed to compare the efficacy and safety outcomes of a subthreshold micropulse treatment laser (SMTL) versus half-dose photodynamic therapy (PDT) for treatment of chronic central serous chorioretinopathy (cCSC) with parafoveal or subfoveal leakage to persistent subretinal fluid. Methods. One hundred and forty-eight patients (148 eyes) with persistent cCSC were enrolled in this retrospective study and treated with SMTL or half-dose PDT. All patients were diagnosed according to clinical characteristics and findings on multimodal imaging. The medical records including patients with a minimum follow-up period of 3 months were reviewed. The patients were divided into two groups according to the application of the SMTL or PDT. The group of the SMTL or PDT was also divided into two subgroups according to parafoveal or subfoveal leakage. The primary outcomes included best-corrected visual acuity (BCVA) and central retinal thickness (CRT) before and 1, 2, and 3 months after treatment. The repeat treatment and resolution of subretinal fluid were also collected. Results. Seventy-nine patients (79 eyes) treated with half-dose PDT and 69 Patients (69 eyes) treated with the STML were included. The mean age was 44.20 ± 7.42 years and 80% were male. No significant difference in age, gender, baseline logMAR BCVA or CRT between the half-dose PDT group and the SMTL group (

P
=
0.201

; 0.051) can be defined. The BCVA of the SMTL group improved at 1, 2, and 3 months after treatment, while that of the half-dose PDT group improved like the SMTL group. There were no significant differences between the SMTL and the PDT group at 1, 2, and 3 months (

P
=
0.723

; 0.139; 0.896). The CRT for the SMTL group decreased at 1, 2, and 3 months after treatment, while that of the half-dose PDT group changed like the SMTL group. However, there were significant differences between the SMTL group and the PDT group at 1and 3 months (

P
=
0.010

; 0.009). 13/69 (18.84%) and 9/79 (11.39%) patients underwent treatment at least twice in the SMTL and half-dose PDT group, respectively, and achieved resolution of SRF after treatment. The results of subgroups analysis showed no significant differences between the logMAR BCVA of the SMTL and PDT group which were divided into parafoveal and subfoveal leakage groups after treatment, but significant difference in CRT between subgroups can be found after treatment at 1and 3 months (

P
=
0.003

; 0.04). Conclusions. The SMTL can be an effective candidate for the treatment of persistent cCSC where leakage occurred at parafoveal or subfoveal and improvement of logMAR BCVA, but half-dose PDT has been more effective for resolution of SRF.
Clinical Knowledge Mining Based on Image Enhancement Algorithm: Endoscopic Clinical Analysis of Peptic Ulcer in Children
Authors: Qiao Lina , Zhou Yarui , Shen Ying , Sun Qi
Published: July 2022

The incidence rate of peptic ulcer is increasing gradually. Medical images can meet the needs of patients as an auxiliary diagnosis and treatment method for peptic ulcer. However, in the long-term treatment, the actual effect is average, and the diagnosis effect of gastrointestinal diseases will gradually deteriorate. In this paper, we use an image enhancement algorithm to study the mechanism of peptic ulcer from the perspective of a medical image. In this paper, 56 images of children with peptic ulcer were selected, and the gastroscopy based on the image enhancement algorithm provided technical support for the rapid diagnosis of patients with peptic ulcer. Experimental results show that the clinical features of peptic ulcer have different characteristics according to the age difference of patients, which can play a positive role in promoting the treatment of patients of different ages.
Enterprise Human Resource Allocation under the Background of Wireless Communication and Internet of Things
Authors: Cao Yi
Published: July 2022

With the rapid development of computer software and hardware technology, new progress has been made in wireless communication technology, and the Internet of Things technology has gradually penetrated into the daily work of citizens, which has led to a comprehensive upgrade of the work mode. In the context of increasing technological progress, market competition in various industries has gradually intensified, and enterprises also need to make corresponding adjustments to adapt to the development of the times. Human resource management, as the most important management link of contemporary enterprises, has a non-negligible influence on the development of enterprises, especially large and medium-sized enterprises. In order to adapt to the development of the times, most enterprises will choose to make timely adjustments to human resource allocation strategies. If an enterprise wants to develop in the fiercely competitive market, it needs to excavate talents and configure a reasonable human resource system. Starting from the related concepts of wireless communication, Internet of Things technology, and enterprise human resource allocation, this paper adopts the method of questionnaire survey to analyze the current situation and existing problems of human resource allocation in a large banking enterprise and then proposes targeted solutions for the existing problems. The ultimate goal of the plan is to optimize the allocation of human resources in the enterprise. The contribution of this paper is to select the relatively special field of banking for investigation and analysis, which fills the research gap to a large extent.
Load Frequency Control for Interconnected Multi-area Power Systems with the Semi-Markov Jumping Parameter and Actuator Failure
Authors: Jiang Yanjun , Wang Jinfeng , Bai Zeyang , Ren Zhengmou , Sun Xiaochen , Yu Guangliang
Published: July 2022

In this study, we study the load frequency control (LFC) problem for interconnected multiarea power systems (IMAPSs) with quantization and actuator failure. To effectively reduce the amount of data in the channel, input signals will be quantized before being transmitted from a controller to a system through the digital communication channel. To reveal the asynchronous phenomenon between the original plant and LFC with actuator failure, a hidden semi-Markov model is formulated. In addition, the stability of the jump system under network attack is discussed. On the basis of the Lyapunov theory, sufficient conditions are derived to ensure the stochastic stability of IMAPSs. Finally, the validity of the theoretical results is tested via a simulation example.
The Strategy of How to Deeply Integrate Technology and Finance in the Internet Environment
Authors: Xu Yunyan
Published: July 2022

To solve some problems existing in the mechanism of the combination of science and technology and finance, this study studies the deep integration of science and technology and finance combined with the Internet. At present, there are many problems in the development of science and technology finance in terms of bank credit, capital market, service system, and risk supervision. To solve these problems, we need to innovate bank credit products and service modes, expand the breadth and depth of capital market services, establish a new science and technology financial service system, improve science and technology financial supervision regulations and means, and comprehensively promote the deep integration of science and technology and finance in the new era. Based on this, this study first expounds on the importance of the deep integration of science and technology and finance, comprehensively analyzes the problems existing in the deep integration of science and technology and finance, and finally puts forward the construction strategy of science and technology and finance integration platform. In the development of market economy, the deep integration of science and technology and finance and the development of platform model effectively improve the innovation ability of science and technology enterprises. The research shows that the high integration of science and technology and finance is the inevitable trend of the future development of the economic market. Therefore, enterprises need to constantly improve their financial operation ability, pay attention to the ways and means of the development of science and technology finance, strengthen the construction of their own platform, improve their operation ability, and improve their development status, so that enterprises can obtain a higher position in the market competition and achieve the purpose of sustainable development.
Visual Analysis of College Sports Performance Based on Multimodal Knowledge Graph Optimization Neural Network
Authors: Zheng Nan , Sun Meng , Yang Ye
Published: July 2022

In this paper, through data analysis of multimodal knowledge graph optimized neural network and visual analysis of college students’ sports performance, we use huge graph, a graph database supporting distributed storage, to store domain knowledge in the form of the knowledge graph, use Spring Boot to build a server-side framework, use Vue framework combined with vis.js to visualize relational network graphs, and design and implement a knowledge-oriented. This paper proposes a visual analytics system based on the theory of visual analytics. Based on the idea of visual analytics, this paper presents a visual analytics framework combining predictive models. This framework combines the automated analysis capability of predictive models with interactive visualization as a new idea to explore the visual analysis of student behavior and performance changes. Using relevant predictive algorithms in machine learning, corresponding models are built to refine the importance of features for visual analysis and correlate behavioral data with achievement data. In this process, multiple prediction algorithms are used to build prediction models. The model effects are analyzed and compared to select the optimal model for use in the visual analytics framework. The graphical analytic view is integrated. EduRedar, an optical analytical system for sports data based on the performance prediction model, is designed and implemented to support multidimensional and multiangle data analysis and visualize the changes in college students’ sports and performance based on accurate campus exercise data.
An Assisted Teaching Method of College English Translation Using Generative Adversarial Network
Authors: Zhang Lin
Published: July 2022

College English translation instruction is an important part of developing students’ English application skills. The generation network in GAN (generative adversarial network) is combined with reinforcement learning technology in this paper to create a basic text generation model that solves the problem that the original GAN model cannot handle discrete data. The correctness of students’ English translation ability is analyzed using a neural network model trained by PSO (particle swarm optimization), which can help teachers estimate students’ translation ability and provide a reference for the next teaching. The results show that the proposed model’s accuracy rate is clearly higher than the comparison model’s, with a maximum accuracy rate of over 85%. The findings indicate that this research model has the potential to improve the quality of English translation instruction.
A Performance of a Nanofiber Polymer in Geotechnical Engineering Support
Authors: Liu Yang , Chen Haiyu
Published: July 2022

Geotechnical engineering is a new technical system established by European and American countries in the practice of civil engineering in the 1960s. There are many methods to manufacture nanofibers, such as stretching, template synthesis, self-assembly, microphase separation, and electrospinning. Among them, electrospinning is widely used because of its simple operation, wide application range, and relatively high production efficiency. This paper aims to study how to analyze and study the properties of engineering scaffolds along the way based on nanofiber polymers. In this paper, the performance of geotechnical scaffolds is proposed, which is based on nanofibers. This paper focuses on the concept of nanofibers and geotechnical physical mechanics. In this paper, the performance of geotechnical support is designed and analyzed. The experimental results show that the initial thermal decomposition temperature of the pure SF collagen nanofiber membrane is about 250°C and that of the pure PLLA nanofiber membrane is about 330°C. When SF collagen/PLLA = 70 : 30, the initial thermal decomposition temperature of the material is about 260°C. When the mass ratio is 50 : 50, the initial thermal decomposition temperature increases to about 270°C. When the mass ratio is 30 : 70, the initial thermal decomposition temperature increases to about 280°C. This is because PLLA is a semi-crystalline polymer with certain thermal stability. Its heat resistance is better than that of pure SF collagen. With the increase in the amount of PLLA, it can effectively improve the thermal stability of blended composite nanofiber scaffolds.
Curcuma longa L. Extract and Photodynamic Therapy are Effective against Candida spp. and Do Not Show Toxicity In Vivo
Authors: Marques Meccatti Vanessa , de Souza Moura Larissa , Guerra Pinto Juliana , Ferreira-Strixino Juliana , Abu Hasna Amjad , Alves Figueiredo-Godoi Lívia Mara , Campos Junqueira Juliana , Marcucci Maria Cristina , Paula Ramos Lucas de , Carvalho Claudio Antonio Talge , Pucci Cesar Rogério , de Oliveira Luciane Dias
Published: July 2022

Radiotherapy induces a higher level of Candida spp. colonization, resulting in oral candidiasis. This study aimed to evaluate the phototransformation potential of the glycolic extract of Curcuma longa (C. longa); the antifungal activity of C. longa, curcumin, and antifungal photodynamic therapy (aPDT) with blue light-emitting diodes “LED” on Candida albicans and Candida tropicalis in vitro; and the toxicity of C. longa and curcumin in Galleria mellonella model. In order to confirm the light absorption capacity of the C. longa extract, its phototransformation potential was evaluated. The antifungal effect of C. longa, curcumin, and aPDT was evaluated over Candida spp. Finally, the toxicity of C. longa and curcumin was evaluated on the Galleria mellonella model. The data were analyzed using the GraphPad Prism 5.0 software considering α = 5%. It was found that C. longa, curcumin, and aPDT using blue LED have an antifungal effect over C. albicans and C. tropicalis. The extract of C. longa 100 mg/mL and curcumin 200 μg/mL do not show toxicity on Galleria mellonella model.
Patient Perception of Informed Consent and Its Associated Factors among Surgical Patients Attending Public Hospitals in Dessie City Administration, Northeast Ethiopia
Authors: Gebrehiwot Hana , Estifanos Nathan , Zenebe Yosef , Anbesaw Tamrat
Published: July 2022

Background. Poor perception of informed consent compromises patients’ autonomy and self-determination; as a result, they feel powerless and unaccountable for their treatment. This study aimed to assess patients’ perception of informed consent and its associated factors among surgical patients attending public hospitals in Dessie City Administration, Northeast Ethiopia. Methods. Facility-based cross-sectional study was conducted on 422 surgical patients. A systematic sampling technique was used to select the study participants. Data were collected using a pretested structured interviewer-administered questionnaire. EpiData version 3.1 was used for data entry, and then data were exported to SPSS version 25 for analysis. Multivariable logistic regression analysis was done to identify factors associated with the outcome variable among the participants. Variables with

p

value less than 0.05 were considered statistically significant factors. Results. The prevalence of poor perception of informed consent for surgical procedures was found to be 33.2% (95% CI: 28.8–37.8). In multivariable analysis, educational status with inability to read and write (AOR = 5.71; 95% CI: 2.76–11.80) and basic ability to read and write (AOR = 6.03; 95% CI: 2.57–14.16), rural residence (AOR = 3.71; 95% CI: 1.94–7.07), marital status being widowed and divorced (AOR = 3.85; 95% CI: 1.83–8.08), language of written informed consent different from mother tongue (AOR = 4.196; 95% CI: 1.12–15.78), poor patient-physician relationship (AOR = 2.35; 95% CI: 1.31–4.24), and poor knowledge of surgical informed consent (AOR = 3.05; 95% CI: 1.56–5.97) were significantly associated with poor perception of surgical informed consent. Conclusion. In this study, one-third of surgical patients appear to have poor perceptions of informed consent for surgical procedures. Educational status, being rural residents, being widowed/divorced, language of written informed consent, poor patient-physician relationship, and poor knowledge of surgical informed consent were variables that are independent predictors of poor perception of informed consent for surgical procedures. The ministry of health and healthcare providers should develop a plan to raise patients’ awareness about the informed consent process for surgical procedures.
Performance Improvement for Single-Photon LiDAR with Dead Time Selection
Authors: Feng Lei , Wang Fenglin , An Meng , Zhang Qiang
Published: July 2022

Compared with the impulse LiDAR, the single-photon LiDAR has higher measurement sensitivity in the prominent feature, especially for space-based long-distance imaging. The distance measurement and the detection probability are the critical performance for LiDAR. The ranging of single-photon LiDAR is mainly different from the photon ranging of pulsed LiDAR. Dead time has a significant effect on distance measurement accuracy and detection probability, which are key parameters for detectors when implementing sound control. Therefore, the model of detector dead time, measurement accuracy, and detection probability should be established, and simulation results that meet application requirements should be achieved. Based on the single-photon ranging theory, the dead time, measurement accuracy, and detection probability model of single-photon LiDAR are studied. Furthermore, the systematic simulation of different contrasts is carried out according to the model. The simulation results demonstrate that the model can accurately perform the relationship between dead time and single-photon LiDAR system parameters. The research results can prove the design and verification of single-photon LiDAR dead time.
The Adoption Factors of Mobile Games in the Wireless Environment
Authors: Li Bo
Published: July 2022

The factors that influence how people play mobile games have been studied from a variety of perspectives in the wireless broadband environment. The original data in the background of the game, such as user operation records, consumption records, and social behavior records, are converted into user attributes, user tags are generated, and data sets are constructed in this study, which primarily uses data mining technology to study user behavior and form user portraits. By incorporating the similarity of players’ subspace interests into the CFR (collaborative filtering recommendation) algorithm, a personalized game recommendation model, as well as the relationship management level of mobile game players, is created. The final fusion model’s ROC-AUC value is 0.921, which has a percentile enhancement effect, according to the results. The findings show that using a personalized game recommendation model can help to improve the scalability of the CFR algorithm and the impact of data scarcity on the quality of mobile games recommended by players.
Retrospective Analysis of Infection Factors in Secondary Internal Fixation after External Fixation for Open Fracture of a Long Bone: A Cohort of 117 Patients in a Two‐Center Clinical Study
Authors: Zhao Shanwen , Ye Zelin , Zeng Canjun , Zhang Lei , Huang Juanyu , Zhang Wensheng , Li Runguang
Published: July 2022

Purpose. To investigate infection risk factors after secondary internal fixation (IF) of open fracture of a long bone with removed fixation frame and explore the safe range of feasible operation for abnormal inflammatory indicators. Methods. Clinical data of 117 cases of open fracture of a long bone that underwent temporary external fixation (EF) in one stage and IF in two stages were retrospectively analyzed. Collected data included age, sex, Gustilo type, multiple injuries, debridement time, duration of EF, needle infection, interval of conversion to IF after external fixator, preoperative white blood cell (WBC), erythrocyte sedimentation rate (ESR), C‐reactive protein (CRP), albumin (ALB), blood glucose, and prognosis. We selected these factors for univariate analysis of postoperative surgical site infection (SSI) and multivariate logistic regression analysis of statistically significant risk factors and created receiver operating characteristic (ROC) curves to compare the diagnostic efficiency of each index and determine the optimal screening point. Results. We followed up 117 patients, with 130 limbs affected. Univariate analysis showed that ESR, CRP, ALB, WBC, EF time, and Gustilo fracture type were significantly associated with SSI. Multivariate logistic regression analysis showed that CRP, duration of EF, and Gustilo fracture type were independently associated with postoperative infection. Area under ROC curves for WBC, ESR, and CRP were 69.7%, 73.2%, and 81.2%. Conclusions. We demonstrated the role of Gustilo classification of open fractures in predicting postoperative infection, especially for open fractures above type III. If the inflammatory indexes return to normal or show a downward trend, and the second‐stage IF operation is performed within the cutoff values, postoperative recurrent infection was reduced.
Analysis of the Influence of Economic Complexity on Regional Economic Management Based on Computer Informatization Model
Authors: Fang Yu , Wang Wenyan
Published: July 2022

This study adheres to the principle of combining empirical analysis and normative analysis and establishes an analytical framework according to the research ideas from theoretical analysis to empirical analysis to countermeasures. Suggestions for high-quality economic growth in my country and paths for promoting coordinated regional development were made. This study will take the data from 1993 to 2020 as a unit, taking into account factors such as education, consumption, investment, and labor costs and using SAR model, SEM model, and spatial panel data model to measure the degree of economic complexity in my country. For the research on the difference of regional economic growth in my country, this study is refined to the county level to measure the degree of regional economic development and compare and analyze the regional development differences, and we strive to use empirical evidence to scientifically analyze the degree of economic complexity and regional development differences, using the spatial panel model, SAR model, and SEM model to comprehensively consider the impact of my country’s economic complexity on regional economic growth differences; finally, combined with theoretical analysis and empirical test results, based on the perspective of economic complexity, coordinated development provides countermeasures and provides corresponding suggestions for the high-quality development of my country’s economy, the continuous optimization of industrial structure, and the establishment of regional cooperation mechanisms.