bluuebunny/crossref_metadata_2025 huggingface dataset:
Multiple air pollutants exposure and leukaemia incidence in Tehran, Iran from 2010 to 2016: a retrospective cohort study
Authors: Khorrami Zahra , Pourkhosravani Mohsen , Eslahi Marzieh , Rezapour Maysam , Akbari Mohammad Esmail , Amini Heresh , Taghavi-Shahri Seyed Mahmood , Künzli Nino , Etemad Koorosh , Khanjani Narges
Published: June 2022

Objective

Leukaemia is one of the most common cancers and may be associated with exposure to environmental carcinogens, especially outdoor air pollutants. The objective of this study was to investigate the association of ambient air pollution and leukaemia in Tehran, Iran.

Design

In this retrospective cohort study, data about the residential district of leukaemia cases diagnosed from 2010 to 2016 were inquired from the Ministry of Health cancer database. Data from a previous study were used to determine long-term average exposure to different air pollutants in 22 districts of Tehran. Latent profile analysis (LPA) was used to classify pollutants in two exposure profiles. The association between air pollutants and leukaemia incidence was analysed by negative binomial regression.

Setting

Twenty-two districts of Tehran megacity.

Participants

Patients with leukaemia.

Outcome measures

The outcome variables were incidence rate ratios (IRR) of acute myeloid and lymphoid leukaemia across the districts of Tehran.

Results

The districts with higher concentrations for all pollutants were near the city centre. The IRR was positive but non-significant for most of the air pollutants. However, annual mean NOx was directly and significantly associated with total leukaemia incidence in the fully adjusted model (IRR (95% CI): 1.03 (1.003 to 1.06) per 10 ppb increase). Based on LPA, districts with a higher multiple air-pollutants profile were also associated with higher leukaemia incidence (IRR (95% CI): 1.003 (0.99 to 1.007) per 1 ppb increase).

Conclusions

Our study shows that districts with higher air pollution (nitrogen oxides and multipollutants) have higher incidence rates of leukaemia in Tehran, Iran. This study warrants conducting further research with individual human data and better control of confounding.
Laparoscopic versus open left hemicolectomy for left-sided colon cancer: protocol for a systematic review and meta-analysis
Authors: Du Qiang , Yang Yang , Zhang Jianhao , Liu Xueting , Wang Yong , Yang Lie
Published: June 2022

Introduction

Laparoscopic colectomy has been widely used clinically due to its minimally invasive advantages, and many studies have also demonstrated its safety and efficacy. However, the efficacy of laparoscopic left hemicolectomy remains unclear due to the differences in pathogenesis and surgical details between left and right colon cancers. Therefore, we plan to conduct a systematic review and meta-analysis to investigate whether laparoscopic techniques can be safely used in left hemicolectomy.

Method and analysis

This meta-analysis protocol will be completed and reported according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols guidelines. A systematic search was performed for all articles related to laparoscopic left hemicolectomy in PubMed, Web of Science, Medline, EMBASE and the Cochrane Library from inception to 5 November 2021. Article screening and data extraction were performed independently by two authors and cross-checked after completion. The literature to be included will use corresponding tools for bias risk assessment. Subgroup analyses and sensitivity analyses will be used to explore potential heterogeneity.

Ethics and dissemination

Because this systematic review is based on studies with published results and does not involve intervention in patients, no ethical review is required. The results of this study will be published in a peer-reviewed journal.

PROSPERO registration number

CRD42022291526.
Dark matter in the CP-violating NMSSM
Authors: Ahmed Waqas , Goodsell Mark , Munir Shoaib
Published: June 2022

In the Next-to-Minimal Supersymmetric Standard Model there is a strong correlation between the mass terms corresponding to the singlet Higgs and the singlino interaction states, both of which are proportional to the parameter$$\kappa $$κ. If this parameter is complex, explicit CP-violation occurs in the Higgs as well as the neutralino sectors of the model at the tree level, unlike in the minimal scenario. A small magnitude of$$\kappa $$κtypically yields a$${{\mathcal {O}}}$$O(10) GeV lightest neutralino with a dominant singlino component. In such a scenario, the phase of$$\kappa $$κ, beside modifying the properties of the five Higgs bosons, can also have a crucial impact on the phenomenology of the neutralino dark matter. In this study we perform a first investigation of this impact on the relic abundance of the dark matter solutions with sub-100 GeV masses, obtained for parameter space configurations of the model that are consistent with a variety of current experimental data.
Investigation of hidden-charm double strange pentaquark candidate $$P_{css}$$ via its mass and strong decays
Authors: Azizi K. , Sarac Y. , Sundu H.
Published: June 2022

This work presents an analysis of a hidden charmed pentaquark candidate state with double strange quark in its quark content. The investigation is performed in two parts, which provide the mass prediction of the considered state and its partial decay widths for the$$P_{css}\rightarrow \Xi ^0 J/\psi $$Pcss→Ξ0J/ψand$$P_{css}\rightarrow \Xi _c^+ D_s^-$$Pcss→Ξc+Ds-channels. For the analyses, two-point and three-point QCD sum rule methods are applied to get the mass and the widths, respectively. The mass for this candidate state is obtained as$$m_{P_{css}}=4600 \pm 155$$mPcss=4600±155 MeV with corresponding current coupling constant$$\lambda _{P_{css}}=(0.81 \pm 0.21)\times 10^{-3}$$λPcss=(0.81±0.21)×10-3 GeV$$^6$$6. These results are used in the analysis of the partial widths of this state for the decays$$P_{css}\rightarrow \Xi ^0 J/\psi $$Pcss→Ξ0J/ψand$$P_{css}\rightarrow \Xi _c^+ D_s^-$$Pcss→Ξc+Ds-. From these decays, the total width is obtained as$$\Gamma = 12.29\pm 2.94 $$Γ=12.29±2.94 MeV. These results may shed light on the future experimental searches in which such types of states are probed and may provide information to discriminate between such possible observations.
Therapeutic Effects of Xianlu Oral Solution on Rats with Oligoasthenozoospermia through Alleviating Apoptosis and Oxidative Stress
Authors: Jin Zi-Run , Cao Ya-Lei , Luo Zhi-Chao , Zhao Qian-Cheng , Xi Yu , Weng Jia-Ming , Zhang Zhe , Jiang Hui
Published: June 2022

Idiopathic oligoasthenozoospermia (iOAZS) is one of the major causes of male infertility, and the ideal therapies for iOAZS have not been established yet. Traditional Chinese medicine (TCM), including Xianlu oral solution (XL), has been widely used as an adjunct treatment for male infertility in the clinic. However, the underlying mechanisms of XL treatment on iOAZS are still not known. Here, we found that XL treatment has therapeutic effects on ornidazole (ORN)-induced OAZS model rats through the amelioration of testis tissues spermatogenesis and the improvement of sperm concentration and motility. Moreover, XL treatment ameliorated the serum hormone levels, mitochondrial membrane potential, apoptosis status, and oxidative stress status in the testis tissues of iOAZS model rats. These findings identify a potential mechanism underlying the therapeutic effects of Xianlu oral solution on iOAZS, and Xianlu oral solution may be used as a traditional Chinese medicine (TCM) therapy for male infertility caused by iOAZS in clinical practice.
Software-Defined Networks and Named Data Networks in Vehicular Ad Hoc Network Routing: Comparative Study and Future Directions
Authors: Wahid Ishtiaq , Tanvir Sadaf , Hameed Abdul , Ahmad Masood
Published: June 2022

Routing protocols are an essential component of vehicular ad hoc networks. Software-defined networks and name data networks are new aspects of routing that are coming to the fore as Vehicular Ad Hoc Network technology evolves. Data Network-based VANET routing protocols and Software Defined Network-based VANET routing protocols have been developed in recent research. These newly developed protocols must be part of VANET routing protocol surveys. The taxonomy of traditional routing protocols must take these innovations into account. To the best of our knowledge, no such taxonomy exists at the moment. We present a new taxonomy of routing protocols based on the additional routing aspects of Software-Defined Networks and Named Data Networks. All traditional routing protocols are kept in a single category. This research work aims to update the existing taxonomy of routing protocols with the newly adopted aspects of research in routing. Advanced routing schemes are selected for the survey from each category to evaluate new research results in VANET routing. This article also describes future directions for VANET/ITS routing research.
Key Technologies of Lightweight Materials for New Energy Vehicles Based on Ant Colony Algorithm
Authors: Mei Lin , Xiaoke Li
Published: June 2022

From the perspective of the new energy vehicle, application of lightweight technology can effectively improve the endurance level of new energy vehicles and promote the steady improvement and rapid development of China’s new energy vehicle industry. By keeping in view the importance of lightweight effect of new energy vehicles, in this paper, we have carried out an in-depth analysis of key contents such as new materials, battery weight, carbon fiber technology, and structural design technology in the process of lightweight development of new energy vehicles. Furthermore, this paper introduces the pseudorandom proportional rule to improve the selection method of the seed solution, makes appropriate random disturbance to the center of the pheromone distribution, and reforms the standard deviation of the pheromone distribution. Taking the lightweight of new energy vehicle doors as an example, this paper verifies the new energy vehicle lightweight algorithm based on ant colony algorithm. It is found that the improved continuous domain basic ant colony algorithm is superior to the other two algorithms and it has the capacity to solve optimization problems and has the advantages of high reliability.
The Application of Internet of Things in Robot Route Planning Based on Multisource Information Fusion
Authors: Yao Yunfeng , He Na , Zhang Min
Published: June 2022

With the advent of the Internet of Everything era, multi-information integration, and development, technology has penetrated into all aspects of life, promoting the continuous progress of social development, and people’s requirements for a happy life are getting higher and higher. In this, robots play an extremely important role. It is especially important for the route planning of robots. This paper analyzes the DWA dynamic window algorithm through the verification of the global route planning algorithm, namely, the Dijkstra algorithm and the

A

∗

algorithm; the verification of the local route planning algorithm; the application of the DWA mobile robot algorithm in the robot route planning. The three aspects of the evaluation function are described by a formula, the experimental simulation is carried out, the relationship between the evaluation function terms is obtained, and the feasibility of the algorithm is verified.
Spatial Characteristics of Sports Tourism Destination System Based on Data Fusion and Data Mining
Authors: Yu Shu , Qiu Chenggang , Yang Ruizhu
Published: June 2022

With the development of information technology around the world, the research on the integration of data mining and data fusion is becoming more and more in-depth. In recent years, sports tourism has developed better and better, with the growing demand for tourism, and the tourism industry has developed by leaps and bounds. Tourism is a new economic growth point in many regions. But it also faces many challenges from both internal and external sources. The tourism destination system is an extremely important subsystem in the tourism system. The quality of its spatial structure not only affects the quality of tourism activities, but also affects the effective operation of the tourism function of the destination system. This paper studies the spatial characteristics of sports tourism destination system based on data fusion and data mining technology. The external environment of sports tourism development, the distribution of sports tourism resources, and the spatial structure of sports tourism are deeply studied by using Gini coefficient, nearest neighbor index, and other technical methods. A questionnaire was also designed to study the physical activity preferences of different age groups. The results show that the nearest neighbor index R of fitness sports tourism destinations is less than 1, which is in a clustered distribution state. The main group of sports tourism activities is mainly concentrated in the age group of 16–45.
A Fast Direct Position Determination Algorithm for LFM Signal Based on Spectrum Detection
Authors: Ren Han , Liu Huijie , Guo Rujiang
Published: June 2022

For the purpose of simultaneously estimating and locating the linear frequency modulation (LFM) emitter with unknown parameters, an innovative approach, i.e., Fast Direct Position Determination (FDPD), is introduced. The proposed algorithm is based on maximum likelihood estimation (MLE) and spectrum detection. To improve the accuracy and overcome the dramatic complexity of plain maximum likelihood formulation, we further derive the objective function equation of Direct Position Determination (DPD) algorithm and present an enhanced strategy to solve the highly nonlinear optimization problem. By combining the two-step localization method, one-step localization method, and short-time Fourier transform (STFT), our approach realizes jointly estimation of the transmitted signal parameters and emitter localization. Simulation results show that the proposed method is superior compared to the existing DPD, and two-step localization algorithms in terms of localization error and computational complexity, especially for low signal-to-noise ratio (SNR).
Applications of Game Theory and Advanced Machine Learning Methods for Adaptive Cyberdefense Strategies in the Digital Music Industry
Authors: Jing Jing
Published: June 2022

As the likelihood and impact of cyber-attacks continue to grow, organizations realize the need to invest in specialized methods to protect their digital data and the information they circulate or manage. Due to its broad use, game theory has evolved into a concept that can be applied practically while analyzing and modifying existing cyber protection methods to arrive at the best possible conclusions. This study presents an innovative hybrid model that combines game theory and advanced machine learning methods for adaptive cyber defense strategies. Specifically, a repetitive game methodology is implemented to analyze cyber-attacks and model behaviors and study how defenders and attackers make decisions in a competing field. Based on Bayesian inference, the proposed method can predict the next steps in the game to produce the appropriate countermeasures and implement the best cyber defense strategies that govern an organization. The suggested system introduced to the academic literature for the first time was successfully tested in a particular application scenario involving the digital music industry and coping with impending cyber-attacks.
Assessment of Respiratory Function and Need for Noninvasive Ventilation in a Cohort of Patients with Myotonic Dystrophy Type 1 Followed at One Single Expert Center
Authors: Ferrari Aggradi Carola R. , Falcier Elisa , Lizio Andrea , Pirola Alice , Casiraghi Jacopo , Zanolini Alice , Carraro Elena , Mauro Luca , Rao Fabrizio , Roma Elisabetta , Iannello Antonino , De Mattia Elisa , Barp Andrea , Lupone Sara , Gatti Valentina , Italiano Cristina , Sansone Valeria A.
Published: June 2022

Introduction. Respiratory insufficiency is one of the main causes of death in myotonic dystrophy type 1 (DM1). Although there is general consensus that these patients have a restrictive ventilatory pattern, hypoventilation, chronic hypercapnia, and sleep disturbances, the prevalence of respiratory disease and indication for the effects of noninvasive ventilation (NIV) need to be further explored. Objectives. To describe respiratory function and need for NIV at baseline and over time in a cohort of adult patients with DM1. Methods. A total of 151 adult patients with DM1 were subjected to arterial blood gas analysis, sitting and supine forced vital capacity (FVC), peak cough expiratory flow (PCEF), nocturnal oximetry, and maximal inspiratory pressure and expiratory pressure (MIP/PEP). Results. On first assessment, 84 of 151 had normal respiratory function (median age: 38 years, median BMI: 23.9, and median disease duration: 11 years); 67 received an indication to use NIV (median age: 49 years, median BMI: 25,8, and median disease duration: 14 years). After a median time of 3.85 years, 43 patients were lost to follow-up; 9 of 84 required NIV; only 17 of 67 with the new NIV prescription were adherent. Conclusions. We provide additional data on the natural history of respiratory function decline and treatment adherence in a relatively large cohort of well-characterized patients with DM1. A high proportion (28%) was lost to follow-up. A minority (11%) required NIV, and only 25% were treatment adherent, irrespective of specific demographics and respiratory features. Our results also confirm previous findings, showing that age, disease duration, and higher BMIs are predisposing factors for respiratory impairment.
Artificial Intelligence Enterprise Management Using Deep Learning
Authors: Liu Xiaofeng , Han Li
Published: June 2022

In this paper, we explore the application status of deep learning (DL) in enterprise management, with China Merchants Bank as an example, and the role of DL in bank enterprise management. We analysed the application status of AI in marketing, risk control, investment, and other fields of CMB and identified five types of problems encountered in the current practical application of AI. We proposed five countermeasures: strengthening the AI organisation system’s construction, enhancing the financial data guarantee mechanism, concentrating on customer-oriented, tightly managing the danger of AI technology, and building a full AI talent system. Recent data are used to assess the impact of DL in marketing, risk management, and investment consulting. According to the data, by the end of 2019, the number of clients of CMB’s two APP platforms had reached 114 million and 91.2643 million, respectively. In 2019, CMB’s personal savings balance climbed by roughly 53% compared to 2016, and its personal loan amount increased by approximately 61%. These findings indicate that the use of AI improves consumer happiness and trust in businesses.
Biomechanical Analysis of Arm Manipulation in Tai Chi
Authors: Dong Xiaoyan , Hu Xiaofan , Chen Biqing
Published: June 2022

In order to explore the kinematics and muscle force characteristics of competitive Taijiquan arm manipulation, and solve the problems of arm trajectory and control in the process of manipulation, this study puts forward the sports biomechanical analysis of arm manipulation in competitive Taijiquan. The technical characteristics and muscle force characteristics of 15 athletes from the competitive Taijiquan team of Xi’an Institute of physical education were studied. Use Excel 2007 and SPSS17.0 to statistically analyze and process the original data. According to the actual needs, the data indicators are summarized. The combined movements of competitive Taijiquan arm manipulation are captured through high-speed photography, and the kinematic data are statistically analyzed, mainly from the two aspects of action amplitude change and action braking. The results show the action track length, relative track length, and action track length of each plane of the two combined hands. The order of the two combined action tracks is: combination 1 > combination 2, in which the action track in the sagittal plane is the longest in combination 1, and it can also be considered that the motion amplitude in the sagittal plane is the largest in combination 1. The average acceleration of group A in the first beat is 0.51 m/s2 smaller than that of group B, and the value is 0.22 m/s2 smaller. Therefore, the deceleration of group A is larger than that of group B, and the braking capacity of group A is slightly stronger than that of group B. In the second beat, the average acceleration of group B is 1.5722 m/s2 larger than that of group A, and the value is 0.210 m/s2 larger. The average acceleration of group A in the third, fourth, fifth, and sixth beats is 0.9, 3.728, 0.57, and 0.837 m/s2 smaller than that of group B, and the values are 0.466, 0.174, 0.250, and 0.003 m/s2 smaller, indicating that the braking capacity of group A in the third, fourth, fifth, sixth, and eighth beats is slightly stronger than that of group B. In the braking of each beat in combination 1 and combination 2 of group AB, the braking ability of arm manipulation of group A is stronger than that of group B. In competitive Taijiquan, the movement techniques of manipulation include: bouncing technology, braking technology, and control technology. For arm manipulation, athletes should have the ability of “braking” technology. In the correlation analysis of movement track length, RMS and I EMG, the score of athletes in group A is high, and there is no correlation between movement track length and RMS. There is a significant correlation between RMS and movement track length in group B, and the correlation degree is moderate. This shows that when the movement of group B athletes is completed, the muscles are in a state of tension, the movement skills are not mastered well, and the energy saving is not achieved. During training, we should pay more attention to the proprioception of muscles and form a correct way of muscle exertion.
Correlation Analysis between Retention of Gd-DTPA in the Cystic Area of Brain Metastasis and MRI Signs
Authors: Wang Jili , Qu Shanshan , Xu Qinyan , Jin Zhaofeng , Li Tian , Zhang Shuxian , Sun Xihe
Published: June 2022

Objective. The aim of this study is to investigate gadolinium-diethylenetriaminepentacetate (Gd-DTPA) retention in the cystic area of brain metastasis and its correlation with MRI signs. Methods. Clinical and MRI data of 76 patients with brain metastasis in the cystic area were collected. The contrast signal intensity (CSI) of the cystic area and edema area in the plain scan, enhanced scan, and plain scan after enhancement within 1 month (hereafter referred to as “enhanced plain scan”) were analyzed to determine whether Gd-DTPA was retained in these areas. The lesions with higher CSI values on the enhanced plain scan were classified as the Gd-DTPA retention group and the remaining lesions as the Gd-DTPA-free group. The two groups were compared to determine significant differences in primary lesion type, tumor size, tumor location, capsule wall thickness and morphology, peritumoral edema, and renal function. Results. A total of 123 lesions were detected. The CSI of the enhanced plain scan exceeded that of the plain scan and enhanced scan in the cystic area (

P
<
0.05

). There were 54 lesions (43.9%) with Gd-DTPA retention in the cystic area and 69 lesions (56.1%) without Gd-DTPA retention. Significant differences were observed in tumor size and cystic wall thickness between the two groups (

P
<
0.05

), while no significant differences in primary lesion type, cystic wall shape, peritumoral edema, or function were observed. Conclusion. The retention of Gd-DTPA was found in the cystic area of some brain metastases, which was correlated with tumor size and cystic wall thickness.
Effect of Different Glucose Monitoring Methods on Bold Glucose Control: A Systematic Review and Meta-Analysis
Authors: Wang Yeling , Zou Congcong , Na Han , Zeng Weixin , Li Xiaoyan
Published: June 2022

Objective. To evaluate the effectiveness of different glucose monitoring methods on blood glucose control and the incidence of adverse events among patients with type 1 diabetes mellitus. Methods. Using the method of literature review, the databases PubMed, Cochrane, and Embase were retrieved to obtain relevant research literature, and the selected studies were analyzed and evaluated. This study used Cochrane software RevMan5.4 to statistically analyze all the data. Results. A total of 15 studies were included in this study, including 10 randomized controlled trials and 5 crossover design trials, with a total of 2071 patients. Meta-analysis results showed that continuous blood glucose monitoring (CGM) could significantly reduce the HbA1c level of patients, weighted mean difference

WMD

=
−
2.69

, 95% confidence interval (CI) (-4.25, -1.14), and

P
<
0.001

compared with self-monitoring of blood glucose (SMBG). Meanwhile, the incidence of severe hypoglycemia in the CGM group was significantly decreased, risk ratio

RR

=
0.52

, 95% CI 0.35-0.77, and

P
=
0.001

. However, there was no statistical difference in the probability of diabetic ketoacidosis between CGM and SMBG groups,

RR
=
1.34

, 95% CI 0.57-3.15, and

P
=
0.5

. Conclusion. Continuous blood glucose monitoring is associated with lower blood glucose levels than the traditional blood glucose self-test method.
Selection of Characteristic Particle Size of Drilling Cuttings Based on Adsorption-Desorption Properties: Experiment and Simulation
Authors: Ma Shouye
Published: June 2022

The direct method for measuring gas content based on image processing, that is, comparing the desorption curves of drilling cuttings with the characteristic particle size with the desorption image in the database to determine the gas content of coal seams, can solve the problems of long measurement time and larger measurement errors of the traditional direct method. However, the precondition to realize this method is to define the characteristic particle size of drilling cuttings. Therefore, this paper performed adsorption and desorption experiments under different particle size ranges and dissimilar adsorption equilibrium pressures, solved the gas migration control equation in coal particles, and determined the characteristic particle size from experimental results and simulation effect. The results showed that gas desorption quantity was positively correlated with adsorption equilibrium pressure, while negatively correlated with the size of a particle size range. The greater the adsorption equilibrium pressure, the better the linear fitting relationship with the maximum desorption quantity, and the maximum correlation coefficient could reach 0.9658. Based on Darcy’s law, Langmuir adsorption equation, and mass conservation law, the theoretical control equation of gas migration in coal particles was derived and solved by Open source Field Operation and Manipulation (OpenFOAM). The accuracy of the calculation results of the solver was verified by the derived analytical solution of the gas pressure change of coal particles without considering the adsorption. From the experimental results and simulation results, the characteristic particle size of drilling cuttings was determined to be 0.5-1 mm. The research can provide help for the subsequent development of direct gas content measurement technology based on image processing.
Improved Fuzzy C-Means Clustering Algorithm-Based Dynamic Contrast-Enhanced Magnetic Resonance Imaging Features in the Diagnosis of Invasive Breast Carcinoma before and after Menopause
Authors: Mei Li , Wang Kaixiang , Gu Yongjian
Published: June 2022

The application effect of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) based on the improved fuzzy C-mean clustering (GA-PFCM) algorithm in analyzing premenopausal and postmenopausal invasive breast carcinoma was discussed. 159 patients with breast carcinoma were selected and divided into the postmenopausal group (71 patients) and the premenopausal group (88 patients) according to their menstrual status. The magnetic resonance images of the two groups were processed and analyzed using GA-PFCM algorithm, and the imaging characteristics and relevant parameters of DCE-MRI examination of the two groups were analyzed. Besides, the sensitivity, specificity, and accuracy of the diagnosis of invasive breast carcinoma by DCE-MRI examination were investigated. The results showed that the percentage of patients with lobulated lumps, patients with burrs on lesion edge, and patients with uniformly enhanced tumors in the premenopausal group was larger than that in the postmenopausal group (

P
<
0.05

). In the postmenopausal group, TCI of 33 patients was shown as platform curves, and that of 34 patients was shown as outflow curves. In the premenopausal group, TCI of 39 patients was shown as platform curves, and that of 41 patients was shown as outflow curves with a high proportion. The number of patients with peak height time ranging between 130 s and 260 s and of patients with early signal enhancement rate ranging between 100% and 200% was large. In contrast, the number of patients with ADC value higher than

1.2
×

10

−
3

was the least. In this research, there were 128 patients with positive invasive breast carcinoma and 31 with negative invasive breast carcinoma by pathological examination. Based on DCE-MRI examination, there were 121 patients with positive invasive breast carcinoma and 38 with negative invasive breast carcinoma. The sensitivity, specificity, and accuracy of invasive breast carcinoma by DCE-MRI were 91.41%, 87.1%, and 90.57%, respectively. In addition, the positive and negative predictive values reached 96.69% and 71.05%, respectively. In summary, GA-PFCM algorithm can be applied in the processing and segmentation of DCE-MRI images, and DCE-MRI could better diagnose invasive breast carcinoma with positive guiding value.
Real-Time Generation Method of Oil Painting Style Brushstrokes Based on Inverse Reinforcement Learning
Authors: Zhang MingQian
Published: June 2022

A popular style in modern graphics programs like GIMP, Photoshop, and Painter is brushstroke artwork, a classic artwork that is still extensively practiced today. Regarding successive decision-making situations with ambiguity, reinforcement learning approaches can be quite helpful. In RL, a reward-enabled agent interacts with a dynamic situation to discover a strategy. To use current RL techniques, we must first offer a reward function, a concise depiction of the designer’s purpose. Hence, inverse-RL (IRL), an expansion of RL, was born. It solves this difficulty via developing the reward function from skilled demonstrations. In this article, we present a novel sundry-fidelity Bayesian optimization (SFBO) approach to boost the ability of the IRL regarding oil painting style brushstrokes. Finally, the performance of the proposed approach is examined and compared with the standard approaches to achieve the highest effectiveness in oil painting. The findings are depicted in graphical representation through Origin tool. Approaches based on RL can be quite helpful in ambiguous decision-making situations. Today’s RL approaches must include a reward function, which embodies the designer’s intent. To reduce the dimensions of the data, the proposed SFBO comprises stages of data preprocessing and feature extraction. The proposed technique was evaluated against the existing techniques in terms of accuracy, information loss, average MSE, and time consumption. Compared to the existing approaches, the proposed approach was the most effective.
Research on Teaching Quality Evaluation of Ideological Politics Teachers in Colleges and Universities Based on a Structural Equation Model
Authors: Fu Xinggan , Chen Wenyan
Published: June 2022

With the dawn of a new era, ideological politics education plays an increasingly high role in college education, so the responsibilities given to ideological politics teachers in universities are increasing. The traditional teaching quality estimate model lags behind in accuracy, precision, and recall rate. Therefore, aiming at this phenomenon, this paper puts forward a teaching quality evaluation model for ideological politics teachers in universities based on the structural equation model. The purpose is to improve the estimated test time and improve the evaluation accuracy and accuracy. The research results of the article show the following: (1) The comparison results of the four models show that the estimate results of the model constructed in this paper have the highest accuracy, accuracy, and recall, with an average accuracy of 98.49%, an average accuracy of 98.31%, and an average recall rate of 98.28%. (2) After testing, the structural equation model takes the least time, with an average test time of 9.4 ms, which is far lower than the test time of the other three models. (3) According to the statistics of the weight of each index, among the first-class indexes, the weight of teachers’ self-evaluation is the lowest, and the weight of students’ evaluation is the highest, accounting for 0.625. The weights of the middle class, teaching implementation, and teaching and educating people in the secondary indicators are all above 0.5, and most of the rest are between 0.2 and 0.4. (4) For the formal estimate of teachers’ teaching quality, the results show that the scores of the test subjects are above 90 points, the highest score is 99, and the average score is 94.5, which meets the test standard. (5) Finally, the model is evaluated, and it is concluded that each score is above 4.5, the highest score is 4.9, and the average score is 4.7, indicating that the model meets the standards and is highly recognized in people’s hearts.
Clinicopathological Features of 166 Cases of Invasive Ductal Breast Carcinoma and Effect of Primary Tumor Location on Prognosis after Modified Radical Mastectomy
Authors: Chen Shiman , Yang Liang , Li Yaqiong
Published: June 2022

Objective. To investigate the clinicopathological features of 166 cases of invasive ductal carcinoma (IDC) of the breast and to analyze the effect of the location of the primary tumor on the prognosis of modified radical mastectomy. Materials and Methods. The clinical data of 166 patients with IDC who underwent modified radical mastectomy in our hospital from May 2015 to May 2017 were retrospectively analyzed. The clinicopathological features of IDC patients were recorded. Univariate analysis and the multivariate logistic regression model were used to analyze the relationship between the location of the primary tumor and the prognosis of IDC patients after modified radical surgery. The effect of primary tumor location on the prognosis of modified radical resection was used with Survival curve analysis. Results. Among the patients in the central region, 13.33% had tumors >5 cm in diameter, which was higher than those in the other four groups. Among the patients in the upper inner quadrant, 59.38% received hormone therapy after operation, which was higher than those in the other four groups (

P
<
0.05

). There were no significant differences in age, menopause, histological grading, molecular typing, lymph node metastasis, vascular invasion, radiation therapy, and chemotherapy among different groups (

P
>
0.05

). Univariate analysis showed that molecular typing, lymph node metastasis, vascular invasion, and location of the primary tumor were all related to the prognosis of IDC patients after modified radical surgery, and the differences were statistically significant (

P
<
0.05

). Logistic regression analysis showed that molecular typing, lymph node metastasis, vascular invasion, and primary tumor location were all independent influencing factors for prognosis of IDC patients after modified radical surgery (

P
<
0.05

). As of 31 May 2021, there were 11 patients with recurrence and metastasis and 20 patients with death. The median survival time in the outer upper quadrant group was 80 months, which was higher than that in the outer lower quadrant group by 72 months, the median survival time in the central region group by 71 months, the median survival time in the inner upper quadrant group by 67 months, and the median survival time in the inner lower quadrant group by 61 months. The log-rank test showed all

P
<
0.001

. Conclusion. Patients with primary tumors located in the central area have larger tumor diameters. Patients located in the central area, upper inner quadrant, and lower inner quadrant are more likely to have lymphatic metastasis, have a more serious condition, and have a shorter prognosis survival time. Unluminal type, multiple lymph node metastases, vascular invasion, and the location of the primary tumor in the inner quadrant are all independent risk factors for prognosis in patients after modified radical surgery for IDC.
An Improved Quality Evaluation Method for Foreign Trade English Using GA-RBF Neural Network
Authors: Yang Yueqing , Ge Ren , Huang Jinxue
Published: June 2022

The teaching evaluation of foreign trade English has been in a quite difficult position because some universities have foreign trade courses, but there is no corresponding foreign trade practice base, so the evaluation of this course is currently relatively simple. This research provides an improved BP neural network evaluation method to address the issues of single teaching evaluation and poor accuracy rate of English as foreign trade in English courses. First, an improved genetic algorithm is utilized to obtain the weight factor of the neural network, which is the data input of the neural network. Second, the middle layer of the network is optimized, so that the output efficiency can be further improved. Finally, the improved and optimized neural network is simulated. The experimental simulation shows that the method proposed in this paper has an energy-efficient and objective evaluation of the quality of foreign trade English teaching with certain accuracy.
Mesenchymal Stem Cell Exosomal miR-146a Mediates the Regulation of the TLR4/MyD88/NF-κB Signaling Pathway in Inflammation due to Diabetic Retinopathy
Authors: Gu Cao , Zhang Hongjun , Zhao Shaofei , He Daotong , Gao Yu
Published: June 2022

Diabetic retinopathy (DR) is the main cause of vision loss in diabetic patients, which cannot be completely resolved by typical blood sugar control. Inflammation influences the development of DR, so reducing the inflammatory response in DR patients is crucial to the prevention of DR. Therefore, we explored the regulatory effect of bone marrow mesenchymal stem cell (BMSC) exosomes on inflammation in DR mice. In order to analyze the mechanism of action, we used BMSC exosomal miR-146a to treat microglias in DR mice to observe cellular changes and expression of inflammatory factors. It was found that BMSC exosomal miR-146a reduced the levels of proliferating cell antigen and B-cell lymphoma-2 in microglias of DR mice and increased Bcl-2-related X with cysteine aspartic protease-3. By analyzing the expression of inflammatory factors, we found that BMSC exosomal miR-146a reduced the levels of TNF-α, IL-1β, and IL-6, which suggested that miR-146a can alleviate inflammation in DR mice. Further exploration found that miR-146a reduced the activity of TLR4 and increased the activity of MyD88 and NF-κB. Furthermore, the overexpression of TLR4 reversed the effects of miR-146a on the proliferation, apoptosis, and inflammation of microglias. Our study demonstrated that BMSC exosomal miR-146a can regulate the inflammatory response of DR by mediating the TLR4/MyD88/NF-κB pathway, providing an experimental basis for the prevention and treatment of DR.
Application of Digital Governance Technology under the Rural Revitalization Strategy
Authors: Chen Huiling , Wang Guanning , Mei Chuangshe , Yang Yunqing , Xu Lirui
Published: June 2022

With the mutual promotion of Internet information technology and economic globalization, the information economy has gradually become the focus of national development, and digital governance technology has been deeply integrated into the entire process of agricultural production. Through the reintegration of agricultural information flow, capital flow, business flow, and logistics, the transformation of intelligent agricultural production, networked operations, electronic management, and informatization of services has become an inevitable choice for rural revitalization. The purpose of this paper is to carry out a series of researches on the crowd-sensing and mining push technology of agricultural big data according to the application characteristics of agricultural data in the process of perception acquisition, analysis, and service. Therefore, we propose and study effective ways to collect IoT in rural complex environments, and how to use complex Internet data to mine rural areas vertically and provide a database source of large-scale data about agricultural resources. Experiments show that, from 10% of the death of a node to 90% of the death of a node, AODV passes about 550 laps, ExOR passes about 350 laps, and MWOR passes through less than 100 laps. From the results, the AODV algorithm is poor because it does not solve the problem of energy balance between nodes, while the ExOR algorithm selects the chance path with the least number of jumps.
Innovative Sensor Design Method of Industrial Ceramic Product Modeling Based on Immune Optimization Algorithm
Authors: Gu Chihui
Published: June 2022

A new method based on immune optimization algorithm was proposed for modeling and design of industrial ceramic products. Based on the joint coding of fuzzy rules and membership function parameters, an improved immune optimization algorithm was used to realize the synchronous optimization of industrial ceramic product modeling. A superheated steam temperature control system is taken as an example to carry out simulation tests. The results show that the ratio of the unit volume to the side length is between 0 and 1, which is called the mass of the grid element. Zero is the worst quality and one is the best. Element aspect ratio and distortion degree are also basic inspection indexes. The average mass of vacuum glass is 0.86, the aspect ratio is 1.71, and the element distortion degree is 0.13, indicating that the grid quality is well divided. It is proved that using the improved immune genetic algorithm to optimize fuzzy control can overcome the defects of the traditional genetic algorithm and ensure the faster and more stable search for the optimal rule base and membership function.
Heterogeneity in the Driver Behavior: An Exploratory Study Using Real-Time Driving Data
Authors: Yarlagadda Jahnavi , Pawar Digvijay S.
Published: June 2022

Driver behavior heterogeneity is a significant aspect to understand the individual behavioral variations and develop driver assistance systems. This study characterizes the heterogeneity in driving behavior using real-time driving performance features. In this context, the study investigates the extent of variations in the individual’s driving styles during routine driving. The driving styles are conceptualized using the vehicle kinematic data, that is, speed and accelerations performed during longitudinal control. The data is collected for 42 professional drivers using instrumented vehicle over a defined study stretch. An algorithm is developed for data extraction and total 7548 acceleration and 6156 braking maneuvers and corresponding driving performance features are extracted. The driving maneuver data are analyzed using the unsupervised techniques (PCA and K-means clustering) and three patterns of acceleration and braking are identified, which are further associated with two patterns of speed behavior. The results showed that each driver is found to exhibit different driving patterns in different driving regimes and no driver shows constantly safe or aggressive behavior. The aggression scores are found to be different among drivers, indicating the behavioral heterogeneity. This study results demonstrate that, driver’s level of aggression in different driving regimes is not constant and characterizing the driver by means of abstract driving features is not indicative of the diversified driving behavior. The proposed method identifies the individualized driving behaviors, reflecting the driver’s choice of driving maneuvers. Thus, the insights from the study are highly useful to design driver-specific safety models for driver assistance and driver identification.
A Chebyshev Spectral Collocation Method-Based Series Approach for Boundary Layer Flow and Heat Transfer in a Micropolar Fluid past a Permeable Flat Plate
Authors: Agbaje T. M. , Makanda G.
Published: June 2022

This paper demonstrates the applicability of the large parameter spectral perturbation method (LSPM) to a coupled system of partial differential equations that cannot be solved exactly. The LSPM is a numerical method that employs the Chebyshev spectral collocation method in the solution of a sequence of ordinary differential equations (ODEs) that are derived from decomposing coupled systems of nonlinear partial differential equations (PDEs) using series expansion about a large parameter. The validity of the LSPM is applied to the problem of boundary layer flow and heat transfer in a micropolar fluid past a permeable flat plate in the presence of heat generation and thermal radiation. The coupled nature of the PDEs that define the problem under investigation precludes the option of using series-based methods that seek to generate analytical solutions even in the presence of small or large parameters. The present study demonstrates that the LSPM can easily overcome this limitation while giving very accurate results in a computationally efficient manner. For qualitative validation of the results and the numerical method used, calculations were carried out to graphically obtain the velocity, microrotation, and temperature profiles for selected physical parameter values. The results obtained were found to correlate with the results from a published literature. For quantitative confirmation of our findings, the LSPM numerical solutions were again validated against known results from the literature and against results obtained using the multidomain bivariate spectral quasilinearisation method (MD-BSQLM), and the results were observed to be in perfect agreement. Further accuracy validation is displayed by using residual error and solution error analysis on the governing PDEs and their underlying solutions. This study’s findings indicate that the heat generation and thermal radiation parameters have related effects on the temperature profile, enhancing both the fluid temperature and the thermal boundary layer thickness.