syedzayyan/paper_mill_benchmark huggingface dataset:
A Double-Layered Belief Rule Base Model for Driving Anger Detection Using Human, Vehicle, and Environment Characteristics: A Naturalistic Experimental Study

“road rage,” namely, driving anger, has been becoming increasingly common in auto era.As “road rage” has serious negative impact on road safety, it has attracted great concern to relevant scholar, practitioner, and governor.This study aims to propose a model to effectively and efficiently detect driving anger states with different intensities for taking targeted intervening measures in intelligent connected vehicles.Forty-two private car drivers were enrolled to conduct naturalistic experiments on a predetermined and busy route in wuhan, china, where drivers’ anger can be induced by various incentive events like weaving/cutting in line, jaywalking, and traffic congestion.Then, a data-driven model based on double-layered belief rule base is proposed according to the accumulation of the naturalistic experiments data.The proposed model can be used to effectively detect different driving anger states as a function of driver characteristics, vehicle motion, and driving environments.The study results indicate that average accuracy of the proposed model is 82.52% for all four-intensity driving anger states (none, low, medium, and high), which is 1.15%, 1.52%, 3.53%, 5.75%, and 7.42%, higher than c4.5, bpnn, nbc, svm, and k nn, respectively.Moreover, the runtime ratio of the proposed model is superior to that of those models except for c4.5.Hence, the proposed model can be implemented in connected intelligent vehicle for detecting driving anger states in real time.

Journal: Computational Intelligence and Neuroscience (2022)
Publication types: Research Article;
A Crop Growth Prediction Model Using Energy Data Based on Machine Learning in Smart Farms

In the recent past, the agricultural industry has rapidly digitalized in the form of smart farms through the broad usage of data analysis and artificial intelligence.Commonly, high operating costs in a smart farm are primarily due to inefficient energy usage.Therefore, accurate estimation of agricultural energy usage and environmental factors is considered as one of the significant tasks for crop growth control.The growth sequences of crops in agricultural environments like smart farms are related to agricultural energy usage and consumption.This study aims to develop and validate an algorithm that can interpret the crop growth rate response to environmental and solar energy factors based on machine learning, and to evaluate the algorithm’s accuracy compared to the base model.The proposed model was determined through a comparative experiment of three representative machine learning techniques, which are random forest (rf), support vector machine (svm), and gradient boosting machine (gbm), considering the energy usage for environmental control is highly associated with the paprika crop growth.Through the experiment performance with real data gathered from a paprika smart farm in south korea, the multi-level rf can effectively predict paprika growth with an accuracy of 0.88, considering data analysis of factors that use solar energy.As a result of the experiment with the suggested model, the growth factors such as leaf length, leaf width, and environmental factors were found.Furthermore, the proposed algorithm can contribute to the development of applications through analysis of the crop growth big data for various plants in agricultural environments such as a smart farm.

Journal: Computational Intelligence and Neuroscience (2022)
Publication types: Research Article;
A Clinical Study on the Brain Protection Effect of Propofol Anesthesia on Patients Undergoing Acute Craniocerebral Trauma Surgery Based on Blockchain

In order to explore the effects of propofol anesthesia system based on block chain on brain tissue and brain function protection, 88 patients undergoing craniocerebral trauma surgery are selected for prospective study.The anesthetic dose of propofol during operation in the control group is determined according to general information and personal situation.The team uses blockchain to process the patient’s clinical data and general information to calculate the optimal dose of propofol.The changes of hemodynamic indexes of patients in the two groups are compared, including dural incision (t1), 1 h after craniotomy (t2), end of surgery (t3), and 6 h after surgery (t4).The changes of neuron-specific enolase (nse) and central neuron-specific protein (s100β) at t1, t2, t3, and t4 in 2 groups are observed and recorded.The changes of malondialdehyde (mda) at t1, t2, t3, and t4 are compared between the two groups.Based on the analysis of clinical data and general information of patients on blockchain, the optimal intraoperative anesthetic dose of propofol for patients can effectively protect the brain function of patients, and the intraoperative anesthesia state is relatively stable, and the changes and improvements of intraoperative indicators are good.

Journal: Journal of Healthcare Engineering (2022)
Publication types: Research Article;
3D Kinematic Analysis of Intelligent Vision Sensor Image in Football Training

With its advantages of high precision, noncontact, and high intelligence, intelligent visual sensor detection technology meets the requirements for online detection of motion status and intelligent recognition of motion images during sports activities, and its applications are becoming more and more extensive.In order to deeply explore the feasibility of using intelligent vision sensor technology to analyze the three‐dimensional action of football, this article uses algorithm analysis method, technology summary method, and physical assembly method, collects samples, analyzes the motion model, streamlines the algorithm, and then creates a model based on intelligent visual sensor technology that can analyze the three‐dimensional movement in football training.After the experimental objects are selected, the model is established in the adm environment.All athletes do a uniform motion, the standard input motion speed is 5 m/s, they all move in the opposite direction relative to their respective coordinate axes, and the motion time is 6 seconds.The results show that the movement curves of the athletes in the three coordinate axis directions are basically the same.When the exercise time is 6 seconds, the coordinate values of the athletes on the three coordinate axes are all 0.992 m.We set six intensities in the experiment: 5%, 15%, 25%, 35%, 45%, and 55%.It can be found that as the noise intensity increases from 5% to 45%, the estimation error gradually increases, but as a whole, it is still at a relatively small level.It shows that the algorithm in this paper still has practical significance.It is basically realized that under the guidance of intelligent vision sensor technology, a model can be designed to successfully and efficiently analyze the three‐dimensional movement pattern in training.

Journal: Journal of Sensors (2021)
Publication types: Research Article;
(5E,7E)-4,5,6 Trihydroxy-3-(hydroxymethyl)tetrahydro-2H-pyran-2-ylheptadeca-5,7-dienoate from Euclea crispa (L.) Inhibits Ovarian Cancer Cell Growth by Controlling Apoptotic and Metastatic Signaling Mechanisms

Bioactive compound (5e,7e)‐4,5,6 trihydroxy‐3‐(hydroxymethyl)tetrahydro‐2h‐pyran‐2‐ylheptadeca‐5,7‐dienoate (compound 2) was isolated from euclea crispa ( e.Crispa ) by the chromatographic methods.Further, the compound was confirmed by spectroscopic techniques such as ultraviolet‐visible (uv/vis) spectrometer, fourier transform infrared (ftir) spectrometer, and 1 h and 13 c nuclear magnetic resonance (nmr).Compound 2 exhibited a significant antioxidant activity with ic 50 values.It restrained the auxesis of ho‐8910 cells in a shot‐dependent mode.Cxcr4, her2, and akt proteins involved in cell proliferation and metastasis were found to be significantly reduced ( p &lt; 0.05).The protein that is responsible for the death of cells (bcl‐2 and bcl‐x l) was reduced ( p &lt; 0.05), while the protein expression of p53 and caspase‐9 was increased ( p &lt; 0.05) in compound 2‐treated ho‐8910 cells.The results of molecular docking analysis showed the binding affinity with cxcr4 and her2.Thus, compound 2 can serve as a promising chemotherapeutic agent for the intervention of ovarian cancer.The findings of this study conclude that compound 2 from e.Crispa might work as a potential antioxidative and chemotherapeutic agent.The in vivo studies and attempts will pave way for this compound to be an effective drug hereafter.

Journal: Bioinorganic Chemistry and Applications (2022)
Publication types: Research Article;
Identifying and Verifying AR, ERBB2, and VEGFA Are the Targets of Qigesan in the Treatment of Esophageal Adenocarcinoma In Silico and In Vitro

The chinese medicine qigesan can be used to treat esophageal adenocarcinoma in the chinese mainland widely, but its mechanism is unclear.In order to investigate the mechanism of qigesan in the treatment of esophageal adenocarcinoma, the concept of network pharmacology was used in this study.The database named tcmsp was used to identify the active therapeutic components as well as targets of qigesan.The ttd, omim, ctd, drug bank, and gene cards database were used to identify genes related to esophageal adenocarcinoma.In string database, the potential targets were imported to obtain a ppi network, and then cytoscape software has been used to analyse the results.Subsequently, important components and targets were simulated by molecular docking.Finally, experiments on the cell have been done to verify well docking targets.A total of 124 effective compounds and 646 corresponding targets were filtered.1478 genes were found to be related to esophageal adenocarcinoma.68 genes were identified as potential targets for esophageal adenocarcinoma.Gene ontology (go) and kyoto encyclopedia of genes and genomes (kegg) analysis of the 68 potential targets indicated that the genes were mainly involved in cell transcription, translation, and apoptosis and mostly expressed in cancer-related pathways.The molecular docking analysis of the hub targets with their corresponding compounds indicated that the well docking targets were ar, erbb2, and vegfa.The cell experiments showed that qigesan can reduce the expression of ar, erbb2, and vegfa at transcription and translation level.This network pharmacology study described that the possible targets of qigesan in treatment of esophageal adenocarcinoma were ar, erbb2, and vegfa.

Journal: Scientific Programming (2021)
Publication types: Research Article;
Evaluation of Provincial Tourism Competitiveness in the Yellow River Basin Based on Clustering Algorithm

Tourism is an important part of china’s national economy.Promoting the development of regional tourism and improving the level of tourism competitiveness can promote the development of regional economy, society, and people's livelihood.Therefore, in the context of the hqdev of the yrb, it is of great significance to study the evaluation and promotion strategies of tourism competitiveness along the yellow river for promoting their hqdev in terms of ecology, economy, and tourism.Taking the provinces as the research area, this article has constructed an evaluation index system of tourism competitiveness in the provinces and used the entropy weigh, the topsis, and the natural breakpoint classification method.The economic and tourism industry subsystems and the overall tourism competitiveness level are comprehensively evaluated and analyzed, and on this basis, the promotion strategy of tourism competitiveness of the nine provinces along the yellow river is proposed.According to the weight of the evaluation index system, the index weight of the ecological environment competitiveness subsystem is 0.3891, of which the index weight of the ecological protection level is 0.3057, and the environmental quality level is 0.0834.The index weight of the subsystem is 0.2691, of which the index weight of the economic innovation level is 0.1695, and the social and people's livelihood level is 0.0996.For the tourism competitiveness, the index weight of the ecological environment competitiveness subsystem is 0.3891, the index weight of the socioeconomic competitiveness subsystem is 0.2691, and the index weight of the tourism industry competitiveness subsystem is 0.3418.The results show that the level of tourism competitiveness along the nine provinces maintains a relatively stable form, but the overall level is not high and the intraregional differences are small.

Journal: Mobile Information Systems (2022)
Publication types: Research Article;
Effect of Running Pose Control Training on Ground Reaction Force, Lower Limb Kinetics

As a new strength training method, running form control training has been widely used in foreign athletes’ strength training and public rehabilitation.As a means of auxiliary strength training, running form strength has attracted wide attention in china.In order to keep up with the latest international strength training theory and technology, the reaction force of people’s running style on the ground was compared with the kinematics and dynamics of lower limbs and studied deeply.The significantly reduced load rate in the absence of running posture transformation is speculated to increase to the adaptation strategy of social body after changing shoe conditions.After training, the load rate was deep than that of the control group, increasing that even though the load rate could be reduced by the training method adapted to the ground hardness, the training effect with a clear goal was more significant.Through the comparison of lower limb joint kinematics and training effect, some flexor strength training methods can be added, and the load intensity and quantity can be appropriately increased, so that the proportion of the strength level of the extensor muscle of the lower limb joint can be coordinated, so as to better improve the coordination force level.

Journal: Mobile Information Systems (2022)
Publication types: Research Article;
Distributed 3D Environment Design System Based on Color Image Model

In order to improve the effect of distributed 3d interior design, a distributed 3d interior design method based on color image model is proposed in this paper.In this paper, the author uses the distributed feature information fusion method to construct the color image model of the distributed 3d interior design, and carries out edge contour detection and feature extraction for the distributed 3d interior spatial distribution image.The rgb color decomposition method is used to decompose the color pixel features of the three-dimensional indoor spatial distribution image.Combined with the three-dimensional point cloud feature reorganization method, the color space reconstruction of the distributed three-dimensional interior design is realized, and the optimal combination of color features of the distributed three-dimensional interior design is realized.Based on the design of image and color processing algorithm, the development and design of distributed 3d interior design system is carried out based on virtual reality and visual simulation technology.The 3d modeling of distributed 3d interior design is carried out using 3ds max, and the indoor hierarchical structure design is realized using the modeling software multigen creator.The experimental results show that, according to the color information fusion results, the distributed 3d interior design optimization is realized.Compared with the traditional manual design method, the root mean square error of this method is greatly reduced from 0.232 to 0.023, and the time cost is 82.8% faster.This method has a better visual effect and strong feature expression ability.Conclusion.The visual effect of distributed 3d interior design with this method is good, the error is small, and the visual expression ability is strong.

Journal: Mathematical Problems in Engineering (2022)
Publication types: Research Article;
An Immune-Related Genetic Feature Depicted the Heterogeneous Nature of Lung Adenocarcinoma and Squamous Cell Carcinoma and Their Distinctive Predicted Drug Responses

One of the primary causes of global cancer-associated mortality is lung cancer (lc).Current improvements in the management of lc rely mainly on the advancement of patient stratification, both molecularly and clinically, to achieve the maximal therapeutic benefit, while most lc screening protocols remain underdeveloped.In this research, we first employed two algorithms (estimate and x cell) to calculate the immune/stromal infiltration scores.This helped identify the altered immune infiltration landscapes in lung adenocarcinoma (luad) and squamous cell carcinoma (lusc).Afterward, based on their immune-related characteristics, we successfully stratified the luad and lusc into 2 and 3 clusters, respectively.Different from the conventional bioinformatic approaches that start from the investigation of differential expression of single genes, differentially enriched curated gene sets identified through gene set variation analyses (gsva) were curated, and gene names were reconstructed afterward.Furthermore, weighted gene correlation network analyses (wgcna) were used to reveal hub genes highly connected with the clustering process.Actual expression levels of critical hub genes among different clusters were compared and so were the functional pathways these genes enriched into.Lastly, a computational method was applied to predict and compare the responses of each cluster to primary therapeutic agents.The heterogeneity presented in our study, along with the drug responses expected for identified clusters, may shed light on future exploration of combination immunochemotherapy that facilitates the optimization of individualized therapy.

Journal: Oxidative Medicine and Cellular Longevity (2022)
Publication types: Research Article;
The Value of Serum Exosomal miR-184 in the Diagnosis of NSCLC

Lung cancer has the highest morbidity rate (11.6%) and mortality rate (18.4%) among all current tumors.The morbidity rate in china accounts for approximately one-third, and it is still rising.Nonsmall cell lung cancer is the most common type of lung cancer, accounting for 80%–85% of all lung cancers, and approximately 57% of patients with advanced nonsmall cell lung cancer have distant metastases at the time of diagnosis.To explore the expression changes in micro rna-184 (mi r-184) and its clinical value in serum exosomes of patients with nonsmall cell lung cancer (nsclc).This study adopted a case-control study method, selecting 88 patients (nsclc group) from june 2015 to june 2017 in our hospital who are confirmed to have nsclc by fiber-optic bronchoscopy, and 90 patients who are confirmed to have benign lung diseases by pathological examination during the same period (control group).Fluorescence quantitative pcr technology is used to detect the levels of mi r-184 in serum exosomes of the two groups, and the differences in the levels of mi r-184 in serum exosomes of nsclc patients with different pathological characteristics are analyzed.According to the results of the 3-year follow-up, the mi r-184 levels in serum exosomes of nsclc patients are grouped and compared.The expression level of mi r-184 in serum exosomes in the nsclc group is significantly higher than that in the control group, and the difference between the two groups is statistically significant ( p &lt; 0.05).The roc curve is drawn with the expression level of mi r-184 in serum exosomes of the two groups of patients.The results showed that the area under the roc curve for the differential diagnosis of nsclc and benign lung tumors with the expression level of mi r-184 in serum exosomes is 0.927, and the sensitivity is 87.61%, while the specificity is 84.02%.The expression levels of mi r-184 in serum exosomes of nsclc patients with different pathological characteristics, in different tnm stages [(i+ii) vs.(iii+iv)], lymph node metastasis (yes vs.No), and different degrees of differentiation [(high + medium) vs.Poorly differentiated] are compared and showed statistical significance ( p &lt; 0.05).In 88 nsclc patients, after 3 years of follow-up, 33 survived, and 55 died, with a survival rate of 37.50%.The expression of mi r-184 in serum exosomes of the 33 surviving patients is significantly lower than that of the nonsurviving group ( p &lt; 0.05).The expression level of mi r-184 in serum exosomes of nsclc patients is significantly increased, which has a certain value for the differential diagnosis of the nature of benign and malignant lung diseases and is closely related to the prognosis of patients.

Journal: Journal of Healthcare Engineering (2022)
Publication types: Research Article;
Relationship between Platelet-to-Lymphocyte Ratio and Lymphocyte-to-Monocyte Ratio with Spontaneous Preterm Birth: A Systematic Review and Meta-analysis

Spontaneous preterm birth is one of the most common pregnancy complications in obstetric clinical practice, and its etiology is complex.The problems of low survival and high morbidity rates of premature infants need to be solved urgently.The platelet-to-lymphocyte ratio (plr) and lymphocyte-to-monocyte ratio (lmr) are two novel biomarkers of inflammation, and several studies have linked plr and lmr to spontaneous preterm birth.These systematic review and meta-analysis are aimed at analyzing the relationship between plr and lmr in patients with spontaneous preterm birth to provide new ideas for the early prevention and treatment of spontaneous preterm births.Methods.Cochrane library, embase, pub med, and china national knowledge infrastructure databases were inspected to gather plr and lmr in patients with spontaneous preterm birth, all from the database to february 2022.Interstudy heterogeneity was evaluated using cochran’s q test and i 2 statistic.Differences in plr and lmr between patients with spontaneous preterm birth and full-term controls were evaluated by computing standardized mean differences and 95% confidence intervals.Publication bias and sensitivity analyses were also performed.Results.Nine studies were included in the meta-analysis based on the inclusion and exclusion criteria.The meta-analysis showed that serum plr values were remarkably larger for patients with spontaneous preterm birth than for full-term controls ( smd = 0.49 , 95% ci: 0.13 to 0.84, p = 0.007 ), whereas the difference between serum lmr in patients with spontaneous preterm birth and full-term controls was not statistically significant (smd: 0.35, 95% ci: -0.18, 0.88, p = 0.199 ).The results of begg’s and egger’s tests revealed that the publication bias of the meta-analysis was not significant.The outcomes of the sensitivity analysis showed that the individual studies did not influence the meta-analysis results.Conclusions.Current evidence shows that plr is strongly associated with spontaneous preterm birth, whereas lmr is not.Plr has a certain clinical value in diagnosing and treating spontaneous preterm births, and our research will provide strong theoretical support for clinical work.In the future, it will be necessary to further explore the reasons for the increased plr in the serum of patients with spontaneous preterm birth and other mechanisms inducing spontaneous preterm birth.

Journal: Journal of Immunology Research (2023)
Publication types: Meta-Analysis;