syedzayyan/paper_mill_benchmark huggingface dataset:
Wearable Sensor-Based Edge Computing Framework for Cardiac Arrhythmia Detection and Acute Stroke Prediction

Internet of things‐based smart healthcare systems have gained attention in recent years for improving healthcare services and reducing data management costs.However, there is a requirement for improving the smart healthcare system in terms of speed, accuracy, and cost.An intelligent and secure edge‐computing framework with wearable devices and sensors is proposed for cardiac arrhythmia detection and acute stroke prediction.Latency reduction is highly essential in real‐time continuous assessment, and classification accuracy has to be improved for acute stroke prediction.In this paper, preprocessing and deep learning‐based assessment is performed in the edge‐computing layer, and decisions are communicated instantly to the individuals.In this work, acute stroke prediction is performed by a deep learning model using heart rate variability features and physiological data.Classification accuracy is improved in this approach when compared to other machine learning approaches.Cloud servers are utilized for storing the healthcare data of individuals for further analysis.Analyzed data from these servers are shared with hospitals, healthcare centers, family members, and physicians.The proposed edge computing with wearable sensors approach outperforms existing smart healthcare‐based approaches in terms of execution speed, latency time, and power consumption.The deep learning method combined with dwt performs better than other similar approaches in the assessment of cardiac arrhythmia and acute stroke prediction.The proposed classifier achieves a sensitivity of 99.4%, specificity of 99.1%, and accuracy of 99.3% when compared with other similar approaches.

Journal: Journal of Sensors (2023)
Publication types: Research Article;
Minocycline plus Zinc Oxide Eugenol Cement Might Be A Promising Alternative for Acute Pulpitis

To investigate the clinical effect of minocycline plus zinc oxide eugenol cement in the treatment of acute pulpitis and its effect on the levels of hif-1α, bcl-2, and tumor necrosis factor α.Methods.A total of 286 patients with acute pulpitis who were treated in our hospital from january 2019 to october 2020 were recruited and assigned (1 : 1) via random number table method to receive either minocycline (control group) or minocycline plus zinc oxide eugenol cement (study group).Outcome measures included treatment effect, tooth mobility, tooth percussion pain score, hypoxia-inducible factor (hif)-1α and b-lymphocyte tumor (bcl)-2 positive rate, and tumor necrosis factor (tnf-α).Results.Minocycline plus zinc oxide eugenol cement was associated with significantly lower scores of teeth mobility and percussion pain versus minocycline alone ( p &lt; 0.05 ).Minocycline plus zinc oxide eugenol cement resulted in a significantly higher treatment efficacy (97.20%) versus minocycline alone (72.73%) ( p &lt; 0.05 ).Minocycline plus zinc oxide eugenol cement was associated with significantly lower positive rates of hif-1α and bcl-2 and lower levels of tnf-α versus minocycline alone ( p &lt; 0.05 ).The patients receiving minocycline plus zinc oxide eugenol cement showed significantly lower visual analogue scale (vas) scores and faster pain relief versus those given minocycline alone ( p &lt; 0.05 ).Conclusion.Minocycline plus zinc oxide eugenol cement offers a viable alternative for acute pulpitis as it mitigates the pain of patients, alleviates inflammatory responses, and lowers the positive rate of hif-1α and bcl-2, so it is worthy of clinical promotion.

Journal: Evidence-Based Complementary and Alternative Medicine (2022)
Publication types: Clinical Study;
MicroRNA-8126-Mediated Antioxidant Stress Attenuates Isoflurane-Induced Hippocampal Neurotoxicity in Developing Rats

To investigate the effect of micro rna-8126 (mi r-8126) on isoflurane-induced hippocampal neurotoxicity in rats.Methods.A rat isoflurane nerve injury model was constructed.The expression of mi r-8126 in the hippocampal region of normal and injured rats was measured by q rt-pcr; synaptic density protein-95, pak-3 (p21-activated kinase-3) and apoptosis-related proteins cytochrome c, cleaved caspase-3, and cleaved parp were detected by western blot.The cytochrome c, cleaved-caspase-3, and cleaved parp expression was detected by wb, as well as gsh-px, cat, sod, and ros.Results.Mi r-8126 was lowly expressed in the isoflurane-treated rat hippocampal region and in rat hippocampal neuronal cells, and the expression of apoptosis-related proteins and apoptosis levels were significantly increased, and neural activity, cell activity, and proliferation capacity were significantly decreased.Oxidative stress levels and ros content were significantly increased; overexpression of mi r-8126 in the rat hippocampal region significantly inhibited oxidative stress and apoptosis.Overexpression of mi r-8126 in rat hippocampal neural progenitor cells significantly increased cell activity, proliferative capacity, and significantly smaller mitochondrial size and it decreased ros content and oxidative stress levels and apoptosis-related protein expression compared to isoflurane-treated cells; while inhibition of mi r-8126 expression in rat hippocampal neuronal cells significantly decreased cell activity, proliferative capacity, and mitochondrial size compared to the control group.In contrast, inhibition of mi r-8126 expression in rat hippocampal neuronal cells resulted in a further decrease in cell activity, proliferation capacity, and significantly larger mitochondrial size and increased expression of apoptosis-related proteins compared with the control group.Mi r-8126 regulates the activity of rat hippocampal neuronal cells by targeting atf4.Conclusions.Mi r-8126 attenuates isoflurane-induced hippocampal neurotoxicity in rats by mediating antioxidative stress.

Journal: Evidence-Based Complementary and Alternative Medicine (2022)
Publication types: Research Article;
MicroRNA-1306-5p Regulates the METTL14-Guided m6A Methylation to Repress Acute Myeloid Leukemia

Mi rna and m6a methylation are two key regulators in cancers.However, in acute myeloid leukemia (aml), the relationship of mi rna and m6a methylation remains unclear.The present work is aimed at determining the effect of m6a methylation induced by mi rnas on aml and its underlying mechanism.The expression of mettl14 was detected by q rt-pcr and western blot.The growth of hl-60 cells was analyzed by cck-8, transwell assay, and flow cytometry.Tumor-bearing mice were established, and ki-67 staining assay was used to detect the proliferation in vivo.Dual luciferase reporter system detected the effect of mi r-1306-5p on mettl14 luciferase activity.Dot blot analysis detected m6a methylation.We found that mettl14 was upregulated in aml patients and overexpressed mettl14 promoted aml development.Further analysis indicated that mettl14 was directly targeted by mi r-1306-5p and overexpressed mi r-1306-5p alleviated aml progression.In addition, m6a methylation level regulated by mettl14 could be affected by mi r-1306-5p.In conclusion, we found that suppressed mi r-1306-5p enhanced aml progression by elevating m6a methylation level via upregulating mettl14.These findings provided basis for the development of new strategies for treating aml.

Journal: Computational and Mathematical Methods in Medicine (2022)
Publication types: Research Article;
Melanoma Molecular Subtypes and Development of Prognostic and Immunotherapy-Related Genetic Characteristics by Ferroptosis Gene Analysis

The dissimilarity is a major problem in clinical therapy of skin cutaneous melanoma (skcm).Objective and reproducible classification systems may help decode skcm heterogeneity.Consensus cluster plus was used to establish a stable immune molecular classification based on ferroptosis-related genes that had been acquired from ferr db.Moreover, the prognosis, somatic mutations, immune microenvironment characteristics, functional enrichment, and clinical responsiveness to the immune checkpoint blockade of different subtypes in two independent melanin datasets were compared.Kaplan-meier curves, univariate, multivariate, least absolute contraction, and selection operator (lasso) cox regression analysis were used to develop a molecular model for predicting survival, which was verified by a nomogram on the basis of independent prognostic indicators.Two molecular subtypes (c1 and c2) for skcm were first identified according to ferroptosis-related genes; c1 showed a poor prognosis, with lower infiltration degree of immune cells and tied score and higher homologous recombination defects, fraction altered, the number of segments, and copy number amplification and deletion.These characteristics of c2 were the opposite of c1.A ferroptosis-related prognosis risk score (fprs) model was constructed using 6 of 463 genes with differential expression between c1 and c2.This model splits patients into low- and high-risk cohorts.There were significant differences in the infiltration and proportion of immune cells, immune checkpoint gene expression, responsiveness to immune checkpoint therapy, and sensitivity to chemotherapeutic medications between low- and high-risk cohorts.This model was an independent prognostic marker for skcm and has a high auc.In summary, we have identified two subtypes of skcm with different molecular and immune characteristics on the basis of ferroptosis-related genes and further developed and verified an fprs model, which might independently serve as a prognostic marker for skcm.

Journal: Computational and Mathematical Methods in Medicine (2022)
Publication types: Research Article;
Management Strategies and Imaging Observation of Early and Delayed Intelligent Treatment of Meniscus Sports Injury under Knee Osteoarthroscopy

To investigate the meniscus characteristics of knee osteoarthritis and its guiding significance for minimally invasive surgery.Methods.A total of 100 patients with knee meniscus sports injuries who were treated in our hospital from january 2019 to january 2022 were selected as the research subjects and were grouped according to the interval between injury and surgery, with an interval of 2 months: the early group (53 cases) within 2 months and the delayed group (47 cases) with an interval of more than 2 months.The distribution of intraoperative complications in the two groups was observed and recorded, and the changes in pain degree, joint range of motion, knee joint function, and quality of life scores before and after operation were compared between the two groups.Results.The postoperative vas score, range of motion, lysholm score, ikdc knee subjective function score, and quality of life score were significantly improved in both groups ( p &lt; 0.05 ).The incidence of intra-articular cartilage injury in the delayed group was significantly higher than that in the early group ( p &lt; 0.05 ).The patellofemoral cartilage injury was the main part of intra-articular cartilage injury in the two groups, and the incidence of patellofemoral cartilage injury in the delayed group was significantly higher than that in the early group ( p &lt; 0.05 ).The cartilage damage was mainly cartilage damage, and the grades i-ii and iii-iv cartilage damages were significantly increased in the extension group.Conclusion.Meniscal injury in knee osteoarthritis has certain microscopic characteristics.In this paper, the microscopic classification of meniscus injury in knee osteoarthritis is helpful to guide microscopic surgery and improve the minimally invasive knee osteoarthritis effect of surgical treatment.

Journal: Scanning (2022)
Publication types: Research Article;
Risk Identification and Application of Farmland Management Right Mortgage Loan Based on Neural Network

There are a series of problems in china, such as low farmers’ income, difficulty in financing for farmers, and relatively lag in rural financial reform.The mortgage financing of farmland management rights is one of the important ways to solve these thorny problems and promote economic development.From the perspective of farmers, combined with empirical analysis, this paper fully considers farmers’ ideas, carries out risk identification and risk assessment for the mortgage loan of farmland management rights, and continuously improves the relevant risk prevention mechanism to reduce the operation risk of farmers’ farmland mortgage.This paper expounds the establishment principles of the risk evaluation index system in detail, lays a theoretical foundation for the selection of indicators, determines the risk evaluation system of land management right mortgage financing from the perspective of farmers, and builds a fuzzy-level comprehensive evaluation model.Based on the practical research data, the fuzzy hierarchy (f-ahp) comprehensive evaluation method is used to conduct an empirical comprehensive evaluation on the risk of the mortgage loan of the farmland management right and analyze the evaluation results.Among the surveyed farmers in the survey area, 242 have not actually participated in the mortgage loan of farmland management rights, accounting for 94.16% of the sample farmers.However, there are only 15 farmers who actually use the farmland management right for mortgage financing, accounting for 5.84% of the sample.

Journal: Wireless Communications and Mobile Computing (2022)
Publication types: Research Article;
Meta-Analysis of the Effect of Nursing Intervention on Children with Type 2 Diabetes

To systematically evaluate the effect of nursing intervention on children with type 2 diabetes.Methods.The randomized controlled trials (rcts) on nursing intervention in children with type 2 diabetes in cnki, vip, wan fang, chinese biomedical database (cbm), pub med, the cochrane library, embase, and science were searched by the computer until july 2022.Two evaluators reviewed the articles, selected the information, and assessed their quality according to the inclusion criteria and exclusion criteria and then carried out meta-analysis with rev man 5.3.Results.A total of 5 rct studies were kept, including 319 patients with type 2 diabetes (≤21 years old), where 162 patients were in the nursing group and 157 patients were in the control group.Meta-analysis revealed that, compared with routine nursing, nursing intervention could effectively control children’s fasting blood glucose (fbg) ( md = − 1.68 , 95% ci (-2.19, -1.17), p &lt; 0.00001 ), 2 h postprandial blood glucose (2h pg) ( md = − 4.01 , 95% ci (-4.70, -3.33), p &lt; 0.00001 ), fasting insulin (fins) ( md = − 7.42 , 95% ci (-10.63, -4.20), p &lt; 0.00001 ), 2 h postprandial insulin (2h ins) ( md = − 58.18 , 95% ci (-103.24, -13.11), p = 0.01 ), triglycerides (tg) ( md = − 0.41 , 95% ci (-0.56, -0.25), p &lt; 0.00001 ), and systolic blood pressure (sbp) ( md = − 8.85 , 95% ci (-14.67, -3.03), p = 0.003 ) and effectively maintain patients’ blood glucose at a normal level ( md = − 8.85 , 95% ci (-14.67, -3.03), p = 0.003 ), where all the differences were statistically significant.Conclusion.The existing evidence showed that nursing intervention has a significant effect in controlling normal blood glucose and improving insulin utilization in children with type 2 diabetes, which can effectively improve the therapeutic effect on children.

Journal: Computational and Mathematical Methods in Medicine (2022)
Publication types: Meta-Analysis;
Research on PKIM Energy Construction Engineering Software System Based on Building BIM Technology

In order to study building bim technology pkim energy building engineering software system, firstly, the building collaborative platform based on bim technology and pkpm professional software bim technology application is constructed.Then, it introduces that pkpm connects all aspects of construction projects through the core 3d data model and takes the lead in realizing the bim concept of information datalization, data modeling, and model generalization, thus realizing the full utilization of building model data in the whole life cycle.Finally, this paper introduces the seismic analysis method of structure based on bim platform, taking a complex building with a transfer storey structure as an example.The experiment shows that the bim model can be used to analyze and calculate the building performance, such as sunshine, energy consumption, daylighting, and evacuation of people, and complete the green building design.The bim model can also generate professional construction drawings of buildings, structures, and equipment.

Journal: Wireless Communications and Mobile Computing (2022)
Publication types: Research Article;
Research on Computer-Aided Product Design Technology

As globalization picks up speed, product innovation—the driving force behind business growth and market competition—becomes increasingly important for advancing product design technology.Computer-aided technology is one of the key components of product design, including issues with scientific analysis, creative thinking, problem-solving, and handling conflicts.Product design technology is gaining more and more attention.Computer-aided technology is now a trendy topic that is being studied by many academics due to the quick growth of computer technology.However, most of them focus on the product information model and solution and do not start from the technical methods and innovation of product design, resulting in many problems in the later solution and information description.Therefore, this paper studies product technology problems based on computer-aided technology and briefly explains the cai technology-driven technology and the establishment of integrated process model.In this model, the assembly information model diagram is constructed to analyze the conflicts and problems in the assembly model, and then, the cai-driven integrated innovation technology is called to complete the assembly model design.Conflicts in the assembly design can be minimized by using this paradigm.Finally, the qualitative examination of product design reveals that brainstorming is the process that uses the least amount of energy.The shafting assembly system is reviewed and examined at the same time, and the assembly accuracy accounts for the highest 35 percent of the system, completely indicating the extraordinary impact of computer-aided product design.

Journal: Computational Intelligence and Neuroscience (2022)
Publication types: Review Article;
Molecular Descriptors on Line Graphs of Cactus Chains and Rooted Products Graphs

The application of graph theory in the study of molecular physical and chemical properties involves theoretical mathematical chemistry.Atoms, represented by vertices, and edges, represented by bonds between them, are detailed in simple graphs called chemical graphs.The mathematical derivation of the numerical value of a graph is called the molecular descriptor of the graph.Any connected graph wherein no edge is contained in exclusive of a single cycle is called a cactus graph.In the research in this article, expressions for various molecular descriptors of line graph of the graph obtained by the rooted product of the cycle and path graphs are constructed.This article obtained the calculation of molecular descriptors for line graphs of chain ortho cactus and chain para cactus graphs.To predict the biological activity of a compound, the generalized zagreb index, the first zagreb index m 1 g , the second zagreb index m 2 g , the f-index, the general randic index, the symmetric division, the atom bond connectivity (abc), and the geometric arithmetic (ga) descriptors are created.

Journal: Journal of Chemistry (2022)
Publication types: Research Article;
Novel Prediction Model for COVID-19 in Saudi Arabia Based on an LSTM Algorithm

The rapid emergence of the novel sars‐co v‐2 poses a challenge and has attracted worldwide attention.Artificial intelligence (ai) can be used to combat this pandemic and control the spread of the virus.In particular, deep learning‐based time‐series techniques are used to predict worldwide covid‐19 cases for short‐term and medium‐term dependencies using adaptive learning.This study aimed to predict daily covid‐19 cases and investigate the critical factors that increase the transmission rate of this outbreak by examining different influential factors.Furthermore, the study analyzed the effectiveness of covid‐19 prevention measures.A fully connected deep neural network, long short‐term memory (lstm), and transformer model were used as the ai models for the prediction of new covid‐19 cases.Initially, data preprocessing and feature extraction were performed using covid‐19 datasets from saudi arabia.The performance metrics for all models were computed, and the results were subjected to comparative analysis to detect the most reliable model.Additionally, statistical hypothesis analysis and correlation analysis were performed on the covid‐19 datasets by including features such as daily mobility, total cases, people fully vaccinated per hundred, weekly hospital admissions per million, intensive care unit patients, and new deaths per million.The results show that the lstm algorithm had the highest accuracy of all the algorithms and an error of less than 2%.The findings of this study contribute to our understanding of covid‐19 containment.This study also provides insights into the prevention of future outbreaks.

Journal: Computational Intelligence and Neuroscience (2021)
Publication types: Research Article;
Model and Simulation of Engineering Safety Risk Control Based on Artificial Intelligence Algorithm

The implementation of engineering projects has a profound impact on the national economy and people’s livelihood.The current engineering projects are in full swing with the vigorous development of the economy.However, due to the high complexity of the engineering project environment, a large number of participants, the high technical standards, and the high labor intensity, it is easy to induce engineering safety risk accidents.Therefore, the demand for research on safety risks in engineering construction is becoming more and more urgent.However, the traditional construction safety risk management lacks systematicness and standardization, and it has limitations in engineering safety risk early warning and control.In order to solve this problem, this paper applies artificial intelligence algorithms to engineering construction safety risk management and establishes an engineering safety risk early warning control model.The bayesian formula, information entropy theory, and other algorithms provide the theoretical basis and feasibility analysis for the model.Four engineering safety risk factors, including human factors, physical factors, management factors, and environmental factors, are analyzed through simulation experiments.The results show that the probability of injury to construction personnel has been reduced by 51.3%, the qualified rate of production materials in construction projects has increased by 6.5%, the risk factors of management have been reduced by 7%, and the environmental risk factors have been reduced by 7.7%; the final risk early warning control effect has increased by 7.45%.

Journal: International Transactions on Electrical Energy Systems (2022)
Publication types: Research Article;