bluuebunny/crossref_metadata_2025 huggingface dataset:
Recognition of Chinese Legal Elements Based on Transfer Learning and Semantic Relevance
Authors: Zhang Dian , Zhang Hewei , Wang Long , Cui Jiamei , Zheng Wen
Published: April 2022

In recent years, LegalAI has rapidly attracted the attention of AI researchers and legal professionals alike. Elements of LegalAI are known as legal elements. These elements can bring intermediate supervisory information to the judicial trial task and make the model’s prediction results more interpretable. This paper proposes a Chinese legal element identification method based on BERT’s contextual relationship capture mechanism to identify the elements by measuring the similarity between legal elements and case descriptions. On the China Law Research Cup 2019 Judicial Artificial Intelligence Challenge (CAIL-2019) dataset, the final result improves 4.2 points over the method based on the BERT model but without using similarity metrics. This research method makes full use of the semantic information of text, which is essential in the judicial field of document processing.
Atraumatic Deltoid Rupture with a Chronic Massive Rotator Cuff Tear: A Case Report and Surgical Technique
Authors: Alben Matthew G. , Gambhir Neil , Boin Michael A. , Virk Mandeep S. , Kwon Young W.
Published: April 2022

Case. We report a rare case of a spontaneous, atraumatic rupture of the anterior and middle heads of the deltoid with an underlying massive rotator cuff tear. Unique clinical findings included a palpable mass of torn deltoid distally with a proximal tissue defect. Magnetic resonance imaging of the deltoid demonstrated complete tear of the anterior head; involvement of the middle head was found intraoperatively. Given the acute nature of injury and potential impact on the feasibility of future reverse shoulder arthroplasty, surgical repair of the torn deltoid was discussed with the patient and performed via superior approach. Conclusion. Direct surgical repair is a viable treatment option if diagnosed early.
Effect of New Nursing on Patients with Acute Cerebral Infarction
Authors: Gu Shengqin , Gao Xiaomei , Gu Wei , Jiang Mulei , Qi Dongmei
Published: May 2022

Objective. To explore the effect of the comfortable intervention-based nursing mode under the quality nursing intervention combined with Internet mobile health on the quality of life (QOL) and psychological status of patients with acute cerebral infarction (ACI). Methods. 90 ACI patients treated in our hospital (June 2019-June 2020) were chosen and equally split into the experimental group (EG) and control group (CG) according to the order of admission. CG received routine nursing, while EG received the comfortable intervention-based nursing mode under the quality nursing intervention combined with Internet mobile health to compare the clinical indexes between the two groups. Results. Compared with CG, EG after intervention achieved obviously higher SS-QOL, ESCA, and GCQ scores (

P
<
0.001

), and lower MSSNS and NIHSS scores (

P
<
0.001

). Conclusion. The application of the comfortable intervention-based nursing mode under the quality nursing intervention combined with Internet mobile health effectively improves QOL and alleviates the negative emotions of patients. Compared with routine nursing, this model has higher application value, and further research of the joint intervention will help build better a solution for patients.
The Patient Health Engagement Model in Cancer Management: Effect of Physical Activity, Distress Management, and Social Support Intervention to Improve the Quality of Life in Breast Cancer Patients
Authors: Changizi Maryam , Ghahremani Leila , Ahmadloo Niloofar , Kaveh Mohammad Hossein
Published: April 2022

Background. Providing better care and encouraging behaviors promoting health are effective measures to manage breast cancer patients. The present research was conducted to carry out an intervention based on the PHE model to promote physical activity, distress management, social support, and quality of life in breast cancer patients. Methods. This randomized control trial study was conducted on 123 women with breast cancer and their caregivers (group 1=61andgroup 2=62). Subjects entered the study from the oncology ward of a specialized clinic in Shiraz, Iran. The education was done through clips, pamphlets, and lectures in 8 sessions with a duration of 15 to 25 minutes. A posttest was carried out in the both groups in 2 times (the end and 3 months) after intervention. The SPSS25 software was used to analyze the data. Results. The mean and SD of age of group 1 were (45.77±8.84) and control group 2 (45.58±77.64). The fiding showed a significant difference between the mean scores of distress management, social support, physical activity, and cancer self-efficacy in group 1 vs. group 2 after intervention (P<0.001). Also, the educational intervention improved quality of life (P=0.003). Conclusion. Intervention program based on the PHE model may facilitate the cognitive, emotional, and behavioral processes in breast cancer patient. Thus, it appears that the PHE model might promote patients’ quality of life.
Optimization Design of Ferry Material Performance Test System Based on Artificial Intelligence
Authors: Zhai Hui , Zhai Yujin
Published: April 2022

Lead titanate in titanium‐titanium mine and lead (solid solution optimized ferroelectric) is one of the most widely used multifunctional material systems, and they are outside the field (such as light, electricity, and heat) Structure, domain, and phase evolution characteristics are important for ferroelectric, piezoelectric, photoelectric, and memory applications. Functional materials are those high‐tech materials with excellent electrical, magnetic, optical, and thermal functions, special physical, and chemical and biological effects, capable of completing functional interconversion, mainly used to manufacture various functional components and are widely used in various high‐tech fields. This paper mainly analyzes iron and electrical materials and artificial intelligence technology by studying the characteristics of ferroelectric materials and research status at home and abroad and using artificial intelligence technology and the calculation of ferroelectric materials for artificial intelligence technology and Dexie optimization model. Artificial intelligence is a new technical science that studies and develops theories, methods, technologies, and application systems for simulating, extending, and expanding human intelligence. For artificial intelligence before the optimization of the hardware and software of the ferroelectric material performance test system, the optimized system is performed; the optimized system is subjected to safety testing; all test results show that the performance test of the ferroelectric material after optimization. The system data is well operating, and the artificial intelligence technology is suitable for optimization of the performance test system of ferroelectric material.
Application Research of Music Education to Improve the Mental Health of College Students under the Background of 5G
Authors: Zou Yi , Kim JongDu
Published: April 2022

Fifth-generation (5G) communication technology, with its high speed, low latency, and wide coverage, will open up new possibilities for the extension of online collaborative learning as the society improves with the times. The 5G era’s intelligent information environment has begun to influence our way of life and work, and it has now spread to include our learning habits. In today’s world, with the rapid advancement of computer and communication technologies, a big number of high-tech subjects in our traditional curriculum have had a considerable influence. This study proposes a method of integrating soft computing techniques to the advancement of music education to enhance the mental health of college students in the conditions of 5G in order to help music education stay updated with the progress trends of the periods in this modern generation. Conventional control techniques and new accurate mathematical model control approaches both fail to accurately assess students’ mental health. To enhance the assessment impact of mental health of the students, this study uses an intelligent fuzzy system as the regulation center and offers an assessment method based on an improved fuzzy neural network to assess the impact of music instruction in boosting mental health of the students. When compared to standard ways, the system developed in this work has a better effect, according to the empirical research findings.
Expression of CDK6 in Stomach Cancer and the Effect of CDK4/6 Inhibitor PD-0332991 on the Function of Stomach Cancer Cells
Authors: Liu Yu , Zhao Yan , Han Chongxu , Ren Chuanli
Published: April 2022

Objective. To study the expression and prognostic value of CDK6 in stomach cancer and the function of CDK4/6 inhibitor PD-0332991 on the proliferation of stomach cancer cells. Methods. Immunohistochemistry was used to detect the expression of CDK6 in stomach cancer tissues and adjacent normal tissues and to analyze the effect of CDK6 on clinicopathological parameters of stomach cancer patients. Kaplan-Meier plotter was employed to study the relationship between CDK6 and overall survival in stomach cancer. Western blot and RT-PCR were used to detect protein and gene expression of CDK6 in different cells. The effects of CDK4/6 inhibitor PD-0332991 on apoptosis and aging of stomach cancer cells were detected by flow cytometry and β-galactosidase aging staining assay. The effects of CDK4/6 inhibitor PD-0332991 on the invasion and migration of stomach cancer cells were explored by the wound healing experiment and the Transwell experiment. The supernatant of stomach cancer cells was collected, and the effect of CDK4/6 inhibitor PD-0332991 on tumor markers of stomach cancer cells was detected by biochemical immunoassay. Results. (1) CDK6 was highly expressed in stomach cancer tissues and cells. (2) Abnormally elevated CDK6 expression results in shorter survival in stomach cancer patients. (3) CDK4/6 inhibitor PD-0332991 could block the proliferation of stomach cancer cells, but not stomach epithelial proliferation. PD-0332991 could inhibit the secretion of pro-GRP by MGC 823. (4) PD-0332991 could advance the development of the apoptosis and senescence of stomach cancer cells and suppressed the invasion and migration of stomach cancer cells. Conclusion. CDK6 expression is elevated in gastric cancer, and the CDK4/6 inhibitor PD-0332991 can remarkably promote apoptosis and senescence of stomach cancer cells and effectively inhibit the migration and invasion of stomach cancer cells.
Comparative Efficacy of Antihypertensive Agents in Flow-Mediated Vasodilation of Patients with Hypertension: Network Meta-Analysis of Randomized Controlled Trial
Authors: Ding Hong , Liu Shu , Zhao Ke-Xin , Pu Jie , Xie Ya-Fei , Zhang Xiao-Wei
Published: April 2022

Hypertension induces both structural and functional changes in blood vessels, thereby increasing endothelial dysfunction, which in turn, contributes to an increase in blood pressure. A popular and widely used noninvasive tool, flow-mediated dilation (FMD), is used to examine peripheral artery endothelium-dependent dilation. This study aimed to compare the efficacies of different classes of antihypertensive agents based on their effects on FMD. PubMed, Embase, and Cochrane Library were queried till November 1, 2020. Comparative studies on the efficacies of two or more antihypertensive agents or placebos for hypertensive patients were included. The outcomes were variations in mean systolic and diastolic blood pressure. Two reviewers independently reviewed and filtered the literature and extracted the data; the Cochrane “risk of bias” method was used to evaluate the methodological quality of the randomized controlled trials. A network meta-analysis was performed using Stata 15.0 software with a total of 49 studies. Subgroup analysis based on age and duration of treatments was performed. As compared to the placebo group, patients receiving the antihypertensive drugs exhibited significantly enhanced FMD (ARB + CCB: 4.01%, 95% CI, 0.92–7.11%,

p
<
0.001

; ACEI + ARB: 2.81%, 95% CI, 1.19–4.43%,

p
<
0.001

; ACEI: 2.55%, 95% CI, 1.34–3.77%,

p
<
0.001

; ARB: 2.22%, 95% CI, 1.05–3.38%,

p
<
0.001

; β-blocker: 2.23%, 95% CI, 0.93–3.52%,

p
<
0.001

). In the SUCRA curve for network meta-analysis, the combination of CCB and ARB was found to be the most effective in increasing FMD (SUCRA = 89.0%), followed by ACEI monotherapy (SUCRA = 74.2%). ARB combined with CCB was superior in improving the endothelial function measured as the FMD; ACEI monotherapy was the most effective treatment among the antihypertension medications. There were no significant differences between antihypertensive drug-based monotherapies.
Modal Investigation on a Large-Scale Containership Model for Hydroelastic Analysis
Authors: Lu Ye , Liu Juan , Teng Bei , Tian Chao , Si Hailong , Zhou Qingyun , Ni Xinyun
Published: April 2022

A 20,000 TEU containership with an overall length of about 400 m is designed as a target ship to investigate ship hydroelastic characteristics in the joint industry project (JIP) of CSSRC-20,000 TEU. A set of systematic model tests are carried out in the seakeeping wave basin of CSSRC. The large-scale ship model data for hydroelastic experiments are presented with the determination of modal features. The modal test of the containership model is the premise of the hydroelastic analysis. The test of the natural frequency and modal shape of the ship model can be used to corroborate the accuracy of the finite element modelling. A three-dimensional finite element model (FEM) of the ship is employed to carry out modal analysis in a vacuum and provide modal parameters to decide the large-scale ship model data for hydroelastic experiments. Through the analysis of hydroelasticity, the wet frequency corresponding to the motion of each elastic mode is obtained. Good agreement is achieved between the numerical results and the measurement data, particularly for the lower-order modes. Only when the numerical calculations of the dry and wet modes are consistent with the experimental results, the containership model's calculated motion responses and structural loads are comparable to the experimental results. Therefore, examining the modal tests is extremely important for hydroelastic analysis. As the input data, the FEM will be shared with JIP members for further comparative studies of linear and nonlinear hydroelastic analyses. The experiments help provide reliable and accurate benchmark model test data for comparative studies using numerical software and methods.
Increasing miR‐126 Can Prevent Brain Injury after Intracerebral Hemorrhage in Rats by Regulating ZEB1
Authors: Liu Yue , Mo Chuangqi , Mao Xiaoman , Lu Ming , Xu Li
Published: April 2022

Background. Studies have found that microRNA (miR) is abnormally expressed in intracerebral hemorrhage (ICH) and is considered a therapeutic target for ICH. Objective. To investigate the expression and role of miR‐126 in the ICH rat model. Methods. The ICH rat model was established, and miR‐126 agomir and ZEB1 antagomir were injected into the lateral ventricle of ICH rats. The neurological function and water content of brain tissue were evaluated 48 hours later. Brain tissue around the hematoma of rats was taken to detect the expression of miR‐126, ZEB1, glial fibrillary acidic protein (GFAP), and inflammatory cytokines (TNF‐α, IL‐1β, and IL‐6). The luciferase reporter gene was applied to analyze the relationship between miR‐126 and ZEB1. Results. miR‐126 was downregulated in the ICH rat model, while ZEB1 was upregulated. miR‐126 agomir or ZEB1 antagomir injection could improve neurological function and cerebral edema in ICH rats. In addition, it could also reduce the expression of TNF‐α, IL‐1β, IL‐6, and GFAP in the brain tissue of ICH rats. Luciferase reporter gene showed that ZEB1 could be targeted and regulated by miR‐126. Conclusion. miR‐126 is downregulated in ICH rats, and miR‐126 can reduce brain injury in ICH rats by inhibiting ZEB1 expression.
Blockchain-Empowered High-Frequency Spectrum Management IoT: A Multilayer PBFT Consensus Perspective
Authors: Chen Xi , Yang Jian , Qiu Junfei
Published: April 2022

High frequency (HF) is an important method for long-range communications and even the only mean when satellites are destroyed or interfered, which play an essential role in defense and economic construction. However, noncooperative frequency competition accompanied with power competition results in the continuously deterioration of HF electromagnetic environment. This article endeavors to resolve this issue through proposing blockchain-empowered HF spectrum management. Specifically, massive personal HF devices are organized around the preselected nodes to construct HF spectrum management IoT, further monitor, and share HF data through PBFT (Practical Byzantine Fault Tolerance) protocol. To address the scalability problem during the consensus, a multilayer PBFT consensus protocol is employed. Scalability evaluations show that increasing consensus layers of PBFT greatly reduces the communication complexity. Security assessments illustrate that the security performance will decline with the increase of layers. Tradeoff has been made between the communication complexity and security performance, indicating 2-4 layers PBFT is sufficient, which bring down the communication complexity and also achieve acceptable security performance.
A Nonlinear Fractional Problem with a Second Kind Integral Condition for Time-Fractional Partial Differential Equation
Authors: Abdelouahab Benbrahim , Oussaeif Taki-Eddine , Ouannas Adel , Saad Khaled M. , Jahanshahi Hadi , Diar Ahmed , Aljuaid Awad M. , Aly Ayman A.
Published: April 2022

The aim of this research is to demonstrate the existence and the uniqueness of the weak solution for a semilinear fractional parabolic problem with the special case of the second integral boundary condition. For this aim, we split the proof into two parts; to study the main linear problem part, we used the variable separation method, and concerning the semilinear problem part, we apply an iterative method and a priori estimate for the study of the weak solution.
A Low-Cost Multistage Cascaded Adaptive Filter Configuration for Noise Reduction in Phonocardiogram Signal
Authors: Pauline S. Hannah , Dhanalakshmi Samiappan , Kumar R. , Narayanamoorthi R. , Lai Khin Wee
Published: April 2022

Phonocardiogram (PCG), the graphic recording of heart signals, is analyzed to determine the cardiac mechanical function. In the recording of PCG signals, the major problem encountered is the corruption by surrounding noise signals. The noise-corrupted signal cannot be analyzed and used for advanced processing. Therefore, there is a need to denoise these signals before being employed for further processing. Adaptive Noise Cancellers are best suited for signal denoising applications and can efficiently recover the corrupted PCG signal. This paper introduces an optimal adaptive filter structure using a Sign Error LMS algorithm to estimate a noise-free signal with high accuracy. In the proposed filter structure, a noisy signal is passed through a multistage cascaded adaptive filter structure. The number of stages to be cascaded and the step size for each stage are adjusted automatically. The proposed Variable Stage Cascaded Sign Error LMS (SELMS) adaptive filter model is tested for denoising the fetal PCG signal taken from the SUFHS database and corrupted by Gaussian and colored pink noise signals of different input SNR levels. The proposed filter model is also tested for pathological PCG signals in the presence of Gaussian noise. The simulation results prove that the proposed filter model performs remarkably well and provides 8–10 dB higher SNR values in a Gaussian noise environment and 2-3 dB higher SNR values in the presence of colored noise than the existing cascaded LMS filter models. The MSE values are improved by 75–80% in the case of Gaussian noise. Further, the correlation between the clean signal and its estimate after denoising is more than 0.99. The PSNR values are improved by 7 dB in a Gaussian noise environment and 1-2 dB in the presence of pink noise. The advantage of using the SELMS adaptive filter in the proposed filter model is that it offers a cost-effective hardware implementation of Adaptive Noise Canceller with high accuracy.
A Randomized Controlled Trial for Prevention of Postoperative Nausea and Vomiting after Laparoscopic Sleeve Gastrectomy: Aprepitant/Dexamethasone vs. Mirtazapine/Dexamethasone
Authors: Ashoor Tarek M. , Kassim Dina Y. , Esmat Ibrahim M.
Published: April 2022

Background. Coadministration of different antiemetics proved to decrease postoperative nausea and vomiting (PONV) after laparoscopic sleeve gastrectomy (LSG). This trial compared aprepitant/dexamethasone (A/D) combination vs mirtazapine/dexamethasone (M/D) combination vs dexamethasone (D) alone for prevention of PONV in morbidly obese patients undergoing LSG. Methods. Ninety patients scheduled for LSG were randomly allocated to receive 8 mg dexamethasone intravenous infusion (IVI) only in the D group or in addition to 80 mg aprepitant capsule in the A/D group or in addition to 30 mg mirtazapine tablet in the M/D group. Assessment of PONV was carried out at 0–2 h (early) and 2–24 h (late). The primary outcome was the complete response 0‐24 h after surgery. Collective PONV, postoperative pain, side effects and patient satisfaction score were considered as secondary outcomes. Results. The A/D and M/D groups were superior to the D group for a complete response within 0–24 h after surgery (79.3% for the A/D group, 78.6% for the M/D group, and 20.7% for the D group). The D group was inferior to the A/D and M/D groups regarding collective PONV and use of rescue antiemetic 0–24 h after surgery (

P
<
0.001

,

P
<
0.001

, respectively). The peak nausea scores (2–24 h) were significantly reduced in the M/D group in comparison to the D group (

P
=
0.005

). Patients in the M/D group showed high sedation scores, while those in the A/D group showed low pain scores (2–24 h) and less analgesic requirements (

P
<
0.001

,

P
<
0.001

,

P
<
0.001

, respectively). The A/D and M/D groups were superior to the D group with regard to the patient satisfaction score (

P
<
0.001

). Conclusion. Aprepitant/dexamethasone combination and mirtazapine/dexamethasone combination were superior to dexamethasone alone in alleviating postoperative nausea and vomiting in morbidly obese patients scheduled to undergo laparoscopic sleeve gastrectomy. Trial Registration: ClinicalTrials.gov identifier: NCT04013386.
Modulation of Interhemispheric Synchronization and Cortical Activity in Healthy Subjects by High-Definition Theta-Burst Electrical Stimulation
Authors: Nguyen Van-Truong , Wu Chun-Wei , Chen Chien-An , Lo Chao-Chen , Chen Fu-Yu , Wu Chun-I , Sung Pi-Shan , Lin Chou-Ching , Chen Jia-Jin
Published: April 2022

Background. Various forms of theta-burst stimulation (TBS) such as intermittent TBS (iTBS) and continuous TBS (cTBS) have been introduced as novel facilitation/suppression schemes during repetitive transcranial magnetic stimulation (rTMS), demonstrating a better efficacy than conventional paradigms. Herein, we extended the rTMS-TBS schemes to electrical stimulation of high-definition montage (HD-TBS) and investigated its neural effects on the human brain. Methods. In a within-subject design, fifteen right-handed healthy adults randomly participated in 10 min and 2 mA HD-TBS sessions: unilateral (Uni)-iTBS, bilateral (Bi)-cTBS/iTBS, and sham stimulation over primary motor cortex regions. A 20-channel near-infrared spectroscopy (NIRS) system was covered on the bilateral prefrontal cortex (PFC), sensory motor cortex (SMC), and parietal lobe (PL) for observing cerebral hemodynamic responses in the resting-state and during fast finger-tapping tasks at pre-, during, and poststimulation. Interhemispheric correlation coefficient (IHCC) and wavelet phase coherence (WPCO) from resting-state NIRS and concentration of oxyhemoglobin during fast finger-tapping tasks were explored to reflect the symmetry between the two hemispheres and cortical activity, respectively. Results. The IHCC and WPCO of NIRS data in the SMC region under Bi-cTBS/iTBS showed relatively small values at low-frequency bands III (0.06–0.15 Hz) and IV (0.02–0.06), indicating a significant desynchronization in both time and frequency domains. In addition, the SMC activation induced by fast finger-tapping exercise was significantly greater during Uni-iTBS as well as during and post Bi-cTBS/iTBS sessions. Conclusions. It appears that a 10 min and 2 mA Bi-cTBS/iTBS applied over two hemispheres within the primary motor cortex region could effectively modulate the interhemispheric synchronization and cortical activation in the SMC of healthy subjects. Our study demonstrated that bilateral HD-TBS approaches is an effective noninvasive brain stimulation scheme which could be a novel therapeutic for inducing effects of neuromodulation on various neurological disorders caused by ischemic stroke or traumatic brain injuries.
Investigation of TiO2 Nanoparticles Using Leaf Extracts of Lippia adoensis (Kusaayee) for Antibacterial Activity
Authors: Gudata Lamessa , Saka Abel , Tesfaye Jule Leta , Shanmugam R. , Dwarampudi L. Priyanka , Nagaprasad N. , Stalin B. , Krishnaraj Ramaswamy
Published: April 2022

Titanium dioxide (TiO2) nanoparticles with the application of pharmaceutical shrub extract are a hopeful unconventional to the old chemical technique. The investigation is intended to synthesis TiO2 NPs in biological approach from homegrown plant Kusaayee Lippia adoensis leaf extraction which is widespread therapeutic plant and sophisticated in home parks of Ethiopia, in Oromia region in Dambi Dollo town. The bioprepared TiO2 nanoparticles written off as by using X‐ray diffraction (XRD), scanning electron microscopy (SEM), and infrared visible spectrum (UV‐Vis) as well as photoluminescence (PL). In addition, this investigation is assessed the antibacterial activities of the prepared TiO2 nanoparticles in illogicality of medical plus standard anxieties Escherichia coli, Klebsiellae preumonia, Staphylococcus aureus, and Enterococcus faecalis through the disc dispersal technique. Furthermore of this work, TiO2 nanoparticles prepared using Lippia adoensis leaf extraction revealed hopeful result in contradiction of in cooperation Gram‐positive (G+) and Gram‐Negative (G‐) bacterial anxieties by means of extreme reserve area of 14 nm and 12 nm, respectively, using uncalcinated system of the prepared TiO2 nanoparticles.
Professional Well-Being and Work Engagement of University Teachers Based on Expert Fuzzy Data and SOR Theory
Authors: Lei Junli
Published: April 2022

The study of the professional well-being of university teachers not only encompasses the quality of teachers’ personal lives but can also reflect satisfaction and loyalty to their careers and has an irreplaceable impact on students’ thinking and political education. The article starts from explaining the connotation of professional happiness of university teachers and analyses the significance of improving the professional happiness of university teachers. Through a questionnaire survey of 504 young teachers in Jiangxi province universities, based on expert fuzzy data and SOR theory, the article analyses various influencing factors in this framework and finds that the current professional happiness of young teachers in universities is positively related to various influencing factors. Based on expert fuzzy data and SOR theory, this paper investigates the professional happiness and work commitment of college teachers. The results of several research tests show that young college teachers have different professional happiness under different conditions, which indicates that material incentives can improve the professional happiness of young college teachers to a certain extent. Therefore, the professional happiness of young university teachers can be improved in terms of enhancing comprehensive quality, improving social status, strengthening humanistic care, broadening growth platform, and establishing scientific system.
Maximum Inclusion Size Evaluation and Fatigue Strength Analysis of 40Cr Structural Steel
Authors: Zhao Yingxin , Zhao Aiguo
Published: April 2022

Statistics of extreme values (SEV) and generalized Pareto distribution (GPD) are adopted to predict the maximum inclusion size in 40Cr structural steel, and the fatigue strength was estimated according to the obtained maximum inclusion size. The estimated results were compared with the experimental results obtained in rotating bending fatigue testing, where all failure-relevant inclusions of the present study were quantitatively analyzed with respect to

area

(square root of the projected inclusion area). Both the estimation results are consistent with the experimental results. Furthermore, a suitable maximum inclusion size equal to the prior austenite grain size is proposed for the material manufacturing process.
Efficacy of Traditional Herbal Medicine Treatment Based on Pattern Identification for Idiopathic Parkinson’s Disease: A Protocol for Systematic Review and Meta-Analysis
Authors: Jun Purumea , Zhao HuiYan , Kwon Ojin , Jang Jung-Hee
Published: April 2022

Parkinson’s disease (PD), the second most common progressive neurodegenerative disease, is characterized by various clinical symptoms and reduced quality of life. The standard dopaminergic therapy for PD has limitations such as drug wear-off, drug-related side effects, and drug-resistant PD symptoms. Traditional oriental medicine, which is a personalized approach based on pattern identification (PI), has been reported to relieve symptoms, halt disease progression, and improve the quality of life in patients with PD. This comprehensive systematic review will be conducted to gather clinical studies related to complementary traditional herbal therapies based on PI for idiopathic PD and assess its effectiveness. Clinical studies, including randomized controlled trials in English, Korean, and Chinese databases related to the efficacy of herbal medicine based on PI for PD will be searched in computer retrieval. In addition, the subdivided PI for each clinical manifestation of PD will be investigated. Two researchers will independently screen and select studies, extract data, and assess bias risk. The risk of bias will be evaluated using the Cochrane risk-of-bias assessment tool. After screening the studies, a meta-analysis will be performed. The primary outcome will be the unified Parkinson's disease rating scale to measure clinical symptom reduction. Secondary outcomes will consist of other validated scales to evaluate the improvement of PD, including improvement of clinical symptoms and quality of life. The quality of evidence will be evaluated through the Grading of Recommendations, Assessment, Development, and Evaluation pro. Complementary traditional medicine is a personalized medicine that classifies individual states based on PI. We expect that the results of this review will provide evidence for the efficacy of traditional herbal medicine based on PI for the treatment of PD. This protocol has been registered in the International Platform of Registered Systematic Review and Meta-Analysis Protocols (INPLASY) 2021 (registration number INPLASY2021100020).
Risk Analysis of Enterprises’ Investment in Infrastructure in Developing Countries Based on Structural Equation Model
Authors: Lu Hongbo , Wang Lifeng
Published: April 2022

In order to control the risks of Chinese enterprises in infrastructure investment in developing countries, the corresponding evaluation system is constructed through a structural equation model algorithm to analyze these risks, so as to achieve risk prediction and risk controllability. Structural equation modeling is a method to establish, estimate, and test causality. It can replace multiple regression, path analysis, factor analysis, covariance analysis, and other methods and clearly analyze the effect of individual indicators on the population and the interrelationship between individual indicators. It is a multivariate statistical modeling technology mainly applied to confirmatory model analysis. Due to the guidance of national policies, there are more and more opportunities for Chinese enterprises to invest abroad. However, due to the influence of political, economic, and environmental factors, overseas investment is facing many difficulties. This paper analyzes the risks from four aspects: bilateral policy risk, legal difference and litigation risk, international economic risk, and technical risk through structural equation model algorithm. Aiming at these risks, the simulation software of the algorithm is constructed in MATLAB big data analysis software, and the risk control measures are put forward. Finally, with the support of China’s policies, in order to ensure the investment income, we should carry out risk intervention for the foreseeable risk and reduce the impact of risk on the investment income as much as possible, so as to improve the risk prevention and management awareness of overseas investment business. By analyzing the characteristics of venture capital and the various kinds of risks affecting venture capital, the risk structure model estimation of risk sneak attack is established by using the principle of structural equation model, and the impact of various risks on investment risks can be analyzed, so that the risk measurement and control of venture capital provides the basis of theoretical knowledge.
Evolutionary Heuristic Computing Paradigm for 2D-DOA Estimation along Circular Array
Authors: Shah Fiaz Hussain , Raja Muhammad Asif Zahoor , Al-Turjman Fadi , Zaman Fawad , Yang Xiaodong
Published: April 2022

Direction of arrival (DOA) estimation problem has growing interest for the researcher investigating in system identification models arising in the field of digital signal processing, mobile communication, controls, and beamforming. In the presented work, evolutionary heuristic computing paradigm is presented for 2D-DOA estimation of plane waves impinging on uniform circular array. Performance metric of mean squared error is utilized as construction of a fitness function for the system, and the optimization strength of three methodologies, genetic algorithms (GAs), Pattern Search (PS), and integration of GAs with PS (GA-PS) is exploited for 2D-DOA estimation based on elevation as well as azimuth angles. Consistent precision, convergence, stability, and robustness of integrated heuristics of GA-PS are endorsed through outcomes of statistical observations.
[Retracted] Relationship between Capital Allocation Efficiency and Diversification Strategy from the Perspective of Internal Control
Authors: Wang Jingjuan , Xia Weili
Published: April 2022

Based on the quality of internal control, this study discusses the impact of internal control quality on resource allocation in the internal capital market and how capital allocation efficiency affects strategic decision‐making. If the quality of internal control can be correctly evaluated and included into the management's strategic decisions, the enterprise can improve the efficiency of capital allocation and formulate an appropriate development strategy. Using panel data from the Shanghai and Shenzhen stock markets from 2013 to 2017, we investigate the relationship among overall internal control information quality, capital allocation efficiency, and enterprise strategic decision‐making. The results show that when the level of free cash flow is high, the incentive mechanism of corporate governance increases the possibility of diversification; the lower the quality of internal control information is, the more likely it is for enterprises to pursue diversification; improving the quality of internal control helps management to allocate internal resources reasonably. When the efficiency of capital allocation is high, it can effectively prevent diversification. This study contributes by revealing the mechanism of the impact of internal control quality on strategic decision‐making and expands the relationship between internal control and corporate strategic management.
Collocation Approach Based on an Extended Cubic
B
-Spline for a Second-Order Volterra Partial Integrodifferential Equation
Authors: George Reny , Yaseen Muhammad , Khan Sana
Published: April 2022

This paper focuses on an efficient spline-based numerical technique for numerically addressing a second-order Volterra partial integrodifferential equation. The time derivative is discretized using a finite difference scheme, while the space derivative is approximated using the extended cubic

B

-spline basis. The scheme is also tested for stability study to ensure that the errors do not accumulate. The convergence of the proposed scheme is also investigated. The scheme’s key benefit is that the approximate solution is produced as a smooth piecewise continuous function allowing us to approximate the solution at any location in the domain. Numerical study is performed, and the comparison of results is made to previously reported results in the literature to show the efficiency of the suggested scheme.
Prenatal Alcohol Exposure and the Risk of Depression in Offspring: a Meta-Analysis
Authors: Zhang Xiaoming , Liu Yanru , Li Jing , Li Binbin , Yang Xingjie , Sun Qi , Yan Jingyi , Wang Zhiren , Liu Huaqing
Published: April 2022

Background. Prenatal alcohol exposure (PAE) has been related to poor consequences of mental health in offspring. However, it remains unknown whether maternal alcohol drinking during pregnancy is associated with depression in the offspring. Methods. A meta-analysis was performed accordingly. Relevant observational studies were identified from Medline, Embase, and Web of Science databases. A fixed-effect or a random-effect model was selected dependending on the between-study heterogeneity. Results. Eight cohort studies were included. The heterogeneity was not significant (I2 = 14%). A meta-analysis with a fixed-effect model showed that PAE was associated with a higher risk of depression in offspring (odds ratio (OR): 2.28, 95% confidence interval (CI): 1.61 to 3.25,

p
<
0.001

). Subgroup analysis showed that moderate (OR: 1.74, 95% CI: 1.22 to 2.49,

p
=
0.002

, I2 = 0%) or heavy (OR: 2.41, 95% CI: 1.55 to 3.73,

p
<
0.001

, I2 = 0%) maternal alcohol drinking in pregnancy was associated with depression in offspring, but not for those with low maternal alcohol drinking (OR: 1.18, 95% CI: 0.97 to 1.44,

p
=
0.10

, I2 = 0%). Further subgroup analyses according to study design, timing of PAE evaluation, age at depression diagnosis, and quality scores showed consistent results. Univariate metaregression showed a dose-response association between PAE and offspring depression (coefficient: 0.073, 95% CI: 0.019 to 0.127,

p
=
0.014

). Conclusions. Current evidence suggests that PAE may be a risk factor of depression in offspring.
COVID‐19 Lockdown Unravels the Complex Interplay between Environmental Conditions and Human Activity
Authors: Raimondo Sebastian , Benigni Barbara , De Domenico Manlio
Published: April 2022

During the COVID‐19 epidemic, draconian countermeasures forbidding nonessential human activities have been adopted in several countries worldwide, providing an unprecedented setup for testing and quantifying the current impact of humankind on climate and for driving potential sustainability policies in the postpandemic era from a perspective of complex systems. In this study, we consider heterogeneous sources of environmental and human activity observables, considered as components of a complex socioenvironmental system, and apply information theory, network science, and Bayesian inference to analyze their structural relations and nonlinear dynamics between January 2019 and August 2020 in northern Italy, i.e., before, during, and after the national lockdown. The topological structure of a complex system strongly impacts its collective behavior; therefore, mapping this structure is essential to fully understand the functions of the system as a whole and its fragility to unexpected disruptions or shocks. To this aim, we unravel the causal relationships between the 16 environmental conditions and human activity variables, mapping the backbone of the complex interplay between intervening physical observables—such as NO2 emissions, energy consumption, intervening climate variables, and different flavors of human mobility flows—to a causal network model. To identify a tipping point during the period of observation, denoting the presence of a regime shift between distinct network states (i.e., before and during the shock), we introduce a novel information‐theoretic method based on statistical divergence widely used in statistical physics. We find that despite a measurable decrease in NO2 concentration, due to an overall decrease in human activities, locking down a region as a climate change mitigation is an insufficient remedy to reduce emissions. Our results provide a functional characterization of socioenvironmental interdependent systems, and our analytical framework can be used, more generally, to characterize environmental changes and their interdependencies using statistical physics.
Dynamical Behaviour and Chaotic Phenomena of HIV Infection through Fractional Calculus
Authors: Jan Rashid , Khan Amin , Boulaaras Salah , Ahmed Zubair Sulima
Published: April 2022

The infection of human immunodeficiency virus (HIV) is a serious and potentially incurable infection. There is no cure for HIV and is a public health issue around the world. That is why, it is valuable to investigate the intricate phenomena of HIV infection and provide some control interventions to lessen its economic burden. In this research work, the dynamics of HIV via fractional calculus to conceptualize the intricate phenomena of this viral infection has been formulated and conceptualized. We have shown the rudimentary concept of fractional calculus in Atangana–Baleanu framework. A novel numerical technique is presented for the chaotic and dynamic behaviour of the proposed model. The oscillatory and chaotic phenomena of the system have been shown with the fluctuation of different input factors of the system. Furthermore, we have shown the affect of fractional order on the proposed system of HIV infection. Most critical input parameters are highlighted through numerical simulations and suggested control intervention to the policy makers. Finally, we have shown the stability result and the convergence condition for the proposed numerical scheme.
An Evaluation Method of English Teaching Based on Machine Learning
Authors: Jiaxin Li
Published: April 2022

The evaluation of English teaching is becoming increasingly popular. An English teaching evaluation approach based on machine learning is developed in order to improve the accuracy of the English teaching evaluation and reduce the inaccuracy of the English teaching evaluation. Firstly, the specific meaning of the English classroom teaching evaluation is analyzed, the selection principle of the English classroom teaching evaluation index is designed, and the selection of the English teaching evaluation index is completed. Second, the machine learning technology is examined, and the analytic hierarchy process is used to produce the judgment of the English teaching assessment index. Then, using the principal component analysis, calculate the eigenvalues and eigenvectors of the evaluation indicators to determine the contribution of the English teaching quality assessment indicators. Finally, create the English teaching evaluation weight calculation model using the machine learning approach, and acquire the English teaching evaluation’s complete results using the fuzzy evaluation method. The experimental results show that when the number of iterations is 60, the normalized mean square error of the effectiveness of the method is 0.03, and when the number of tests is 30, the effectiveness of the method is 0.99; this shows that the method can improve the effectiveness of the English teaching evaluation. It can effectively reduce the error of the English teaching evaluation.
Deep Learning in Data Mining Management of Industrial and Commercial Enterprises
Authors: Yi Junnan
Published: April 2022

Due to the frequent use of the Internet and the generation of massive amounts of data, people have entered the era of big data. A large amount of data is generated in people’s daily life. Because these data contain a large amount of information and more complicated content, the process of data analysis and utilization must account for an increasing number of issues. As the problem becomes more complex, the use of deep learning in data mining becomes increasingly important. This article gives a certain introduction and understanding of deep learning and data mining and analyzes and summarizes the application of deep learning in data mining. It introduces a data mining approach for industrial and commercial companies, as well as the requirements of the classic CRISP-DM data mining method. It also exhibits the application of deep learning in industrial time-series data classification in the content of industrial and commercial companies.
Research on the Conversion Relationship between Dynamic Point Load Strength and Dynamic Compressive Strength Based on Energy System
Authors: Zhou Ming , Qiao Lan , Li Qingwen , Yang Shuang , Huang Zhenping
Published: April 2022

Point load test is a simple and fast method to obtain the compressive strength of rock. According to the maximum load at failure and the distance between two cone ends, the compressive strength of specimens can be calculated by the empirical formula. Because the test process does not need to process the sample into laboratory size type, so it is widely used. At the same time, with the rapid development of rock dynamics, the dynamic strength index of rock becomes more and more important under dynamic load. But dynamic point load is seldom mentioned by scholars. In order to explore the correlation between dynamic point load test and dynamic compressive strength, a large number of dynamic point load and uniaxial dynamic compressive strength tests were carried out using a split Hopkinson pressure bar for granite. Based on the energy theory, the crushing energy consumption during dynamic point load and uniaxial dynamic compressive strength tests were statistically analyzed, and the transformational relation between uniaxial dynamic compressive strength and crushing energy consumption during the dynamic point load test was determined. At the same time, the influence of the cone angle on crushing energy consumption during the dynamic point load test was investigated by changing the conical angle. The results show that with the increase in conical angle, the energy consumption of rock crushing decreases gradually during the dynamic point load test. And the decreasing trend tends to be gentle. The conclusion can provide a reference for obtaining the numerical value of the dynamic compressive strength of the rock in the future.