syedzayyan/paper_mill_benchmark huggingface dataset:
Research on Emergency Logistics Vehicle Route Scheduling and Optimization Method Based on Multi-Intelligent Decision System

Logistics distribution vehicle planning is an important issue in logistics transportation activities, and it is also a research hotspot in theoretical circles at home and abroad.At present, many studies have focused on establishing vehicle planning models and optimizing vehicle planning in different environments and have achieved rich results.As an important part of transportation production process, the efficiency of logistics distribution is very important to the whole production process.Especially for emergency logistics, every minute is very critical for emergency situations such as disaster relief.In order to improve the efficiency of emergency logistics, this paper applies multiagent technology to emergency logistics and puts forward an integrated modeling method of enterprise macromodeling, business process mesomodeling, and micromodel design.Using the agent-oriented system development method, an emergency logistics distribution vehicle planning model system is established.The development process of multiagent automatic trading system is described.The results show that it is feasible and effective to use multi-intelligent fuselage technology for emergency logistics distribution vehicle planning and decision-making.The algorithm proposed in this paper has advantages over the container order sequence processing scheme, and the total cost of order acceptance decreases sharply in the initial stage, which shows the practical convergence of the algorithm.The adjacency search method and tabu search method deal with the calculation of total labor cost, and the tabu neighborhood search algorithm obtains better results with lower labor cost.

Journal: Journal of Sensors (2022)
Publication types: Research Article;
MEK inhibitors induce apoptosis via FoxO3a-dependent PUMA induction in colorectal cancer cells

Mutations in braf are common to many cancers, including crc.The mek inhibitors are being investigated in braf -mutant crc.In this study, we aimed to investigate how mek inhibitor suppresses growth of braf -mutated crc cells as well as its potential mechanisms.Our findings indicated that mek inhibitor promote puma expression via erk/fox o3a signaling pathway.In addition, puma induction is essential for mek inhibitor-induced apoptosis.Moreover, puma induction is required for mek inhibitors to induced apoptosis in combination with cisplatin, dabrafenib, or gefitinib.Knockdown of puma suppressed the anticancer effect of the mek inhibitor in vivo.Our findings indicate a novel role for puma as a regulator of the antitumor effects of mek inhibitor, suggesting that puma induction may modulate mek inhibitor sensitivity.

Journal: Oncogenesis (2018)
Publication types: Research Article;
The Application of “Internet+” in the Ageing Adaptation of Elderly People with Disabilities at Home

This paper focuses on the role of the internet in empowering social work to intervene in ageing-in-place services for the disabled elderly in terms of time, space, and resources.Through the practical analysis of home care service providers, the advantages and characteristics of the “internet” for ageing-in-place services for the disabled elderly are identified, as well as some of the problems that exist in the current intelligent home care service platform.This paper proposes to improve and optimize the “internet+” by fully enhancing the technical empowerment of the internet, improving the integration and spanning of space, and giving full play to the role of social work on the internet.This paper proposes to improve and optimize the “internet+” elderly home care services for the disabled, so as to solve to a certain extent the practical problems faced by the “internet+” elderly home care services in the early stage of development.The significance of this paper is that, through the study of the “internet+” home care services for the elderly with disabilities, the process of the services is sorted out and summarized, and suggestions and measures are put forward for its shortcomings, providing practical methods and feasible paths for future generations, which are of great significance for other social work agencies using internet tools.

Journal: Journal of Mathematics (2021)
Publication types: Research Article;
Real-Time Analysis of Basketball Sports Data Based on Deep Learning

This paper focuses on the theme of the application of deep learning in the field of basketball sports, using research methods such as literature research, video analysis, comparative research, and mathematical statistics to explore deep learning in real‐time analysis of basketball sports data.The basketball posture action recognition and analysis system proposed for basketball movement is composed of two parts serially.The first part is based on the bottom‐up posture estimation method to locate the joint points and is used to extract the posture sequence of the target in the video.The second part is the analysis and research of the action recognition algorithm based on the convolution of the space‐time graph.According to the extracted posture sequence, the basketball action of the set classification is recognized.In order to obtain more accurate and three‐dimensional information, a multitraining target method can be used in training; that is, multiple indicators can be detected and feedback is provided at the same time to correct player errors in time; the other is an auxiliary method, which is compared with ordinary training.The method can actively correct technical movements, train players to form muscle memory, and improve their abilities.Through the research of this article, it provides a theoretical basis for promoting the application of deep learning in the field of basketball and also provides a theoretical reference for the wider application of deep learning in the field of sports.At the same time, the designed real‐time analysis system of basketball data also provides more actual reference values for coaches and athletes.

Journal: Complexity (2021)
Publication types: Research Article;
Readiness for Hospital Discharge and Its Correlation with the Quality of Discharge Teaching among the Parents of Premature Infants in NICU

S.To assess the extent of the readiness for hospital discharge and the correlation with discharge teaching quality among parents of premature infants’ in the nicu.Background.Low readiness for discharge from the hospital can lead to negative outcomes in healthcare for infants born prematurely and their parents.Discharge guidelines are a basic approach to ensure the readiness of the parents for discharge from the hospital.No investigation has ever been conducted into the sufficiency of hospital discharge guidelines for premature infants and their impact on parental readiness for hospital discharge.Design.Data was collected from four hospitals in china using a correlational descriptive study.Methods.Two hundred and eight parents of premature nicu-hospitalized infants of four tertiary hospitals in henan province from may to october 2020 were enrolled.The general information questionnaire, the readiness for hospital discharge scale- (rhds-) parent form, and the quality of discharge teaching scale- (qdts-) parent form were used for data collection.Spearman correlation analysis and descriptive statistics were used to analyze the data.Results.The total score for hospital discharge readiness was high ( 8.05 ± 1.11 ).The total score of the quality of discharge guidelines was moderate ( 7.44 ± 1.44 ).Moreover, the discharge teaching quality was positively correlated with the parents’ readiness.Positive correlations were found between prhds and qdts subscales, including content received and delivery, physical-emotional status, knowledge, and expected support.Conclusion.The quality of the discharge guidelines perceived by parents of premature infants was moderate, which may have reduced their readiness for hospital discharge.Relevance to clinical practice.This study furnishes basic information on the importance of readiness of discharge for the parents of premature infants.The teaching guides nurses to enhance the quality of discharge teaching and the readiness of parents for discharge from the hospital.

Journal: Applied Bionics and Biomechanics (2022)
Publication types: Research Article;
Purification and Analysis of the CREPT Antibody from Mouse Ascites

And objective.The cell cycle-related and expression-elevated protein in tumor (crept) is overexpressed in several human cancers.Establishing a method for purifying crept from mouse ascites is vital for further research.This study was aimed at establishing a method for purifying crept from mouse ascites.Methods.Cells were cultivated properly to obtain 3e10 crept monoclonal antibody cells in the logarithmic growth stage.Monoclonal antibody cells were injected into the abdominal cavity of sensitized mice.The flowing ascites were observed for 7-15 days.The antibody protein was obtained by collection, filtration, dilution, loading, and chromatography.Furthermore, its binding force was detected by sds-page and western blot techniques.Results.The antibody protein was successfully obtained with a purity of 1895 μg/m l with high liveness.Conclusion.This study establishes a one-step purification method for obtaining monoclonal antibody with high liveness and purity for crept ascites antibody.This method is simple to perform and lays a foundation for the preparation and purification of humanized monoclonal antibodies in the future.In addition, it provides a basis for further research to investigate how crept affects the occurrence and development of different tumors.

Journal: Applied Bionics and Biomechanics (2022)
Publication types: Research Article;
Prognostic Comparison between cTACE and H101-TACE in Unresectable Hepatocellular Carcinoma (HCC): A Propensity-Score Matching Analysis

Transarterial chemoembolization (tace) is the most common treatment for patients with hcc who are unsuitable for radical therapies.Conventional tace (c tace) takes advantage of the preferential hepatic arterial supply of hcc for the targeted delivery of chemotherapeutic agents suspended in lipiodol, followed by embolization or reduction of arterial flow using various types of particles while sparing the surrounding liver parenchyma.Aims and objectives.The current study is aimed at comparing the efficacy and safety profiles of transarterial infusion of recombinant human type-5 adenovirus (h101-tace) with conventional transarterial chemoembolization (c tace) in patients with unresectable hepatocellular carcinoma (hcc).Methods.Unresectable hcc patients that received h101-based tace or c tace from august 2018 to september 2021 were retrospectively evaluated.Propensity score matching (psm) has a 1 : 1 ratio to eliminate possible confounder imbalances across cohorts.The main outcome was overall survival (os), while secondary outcomes were progression-free survival (pfs) and tumor response.Results.This study included 111 patients classified across two cohorts: the h101-tace cohort ( n = 37 ) and the c tace cohort ( n = 74 ).Median os within the h101-tace cohort was 9.0 months longer than within the c tace cohort before psm (22.1 vs.13.1 months, p = 0.043 ) and 9.3 months longer following psm (22.1 vs.12.8 months, p = 0.004 ).The median pfs within the h101-tace cohort was 3.2 months longer compared to the c tace cohort before psm (6.5 vs.3.3 months, p = 0.046 ) and 2.5 months after psm (6.5 vs.4.0 months, p = 0.012 ).The disease control rate for h101 and control cohorts was 81.1% and 59.5%, accordingly ( p = 0.039 ).Conclusion.The present study demonstrated that the h101-tace is safe and efficient and can considerably enhance prognostic results for unresectable hcc compared to c tace.

Journal: Applied Bionics and Biomechanics (2022)
Publication types: Research Article;
Prediction of Transmission Line Icing Using Machine Learning Based on GS-XGBoost

In recent years, data have shown that transmission line icing is the main problem affecting the operation of power grids in bad weather; it greatly increases operating costs and affects people’s lives.Therefore, the development of a calculation method to predict the risk of ice on transmission lines is of great importance for the stability of the power grid.In this study, we propose a maximum mutual information coefficient (mic) and grid search optimization extreme gradient boosting (gs-xgboost) transmission line ice risk prediction method.First, the mics between the ice thickness and the precipitation, wind speed, wind direction, relative humidity, slope, aspect, and elevation characteristic factors are calculated to filter out the effective features.Second, a grid search method is used to adjust the hyperparameters of xgboost.The resulting gs-xgboost model builds a prediction system based on the best parameters using a training set (70% of the data).Finally, the performance of gs-xgboost is evaluated using a test set (30% of the data).For multiline, cross-regional icing data, our experimental results show that gs-xgboost outperforms other machine learning methods in terms of accuracy, precision, recall, and f 1 score.

Journal: Journal of Sensors (2022)
Publication types: Research Article;
Prediction Model of Rotor Yarn Quality Based on CNN-LSTM

In the whole textile industry chain, yarn production is one of the key links, which has a great impact on the quality of textile and clothing products.For a long time, the textile industry has been hoping for a yarn quality prediction technology, which can accurately predict the final yarn quality indicators according to the known conditions such as raw materials and production processes.Cnn-lstm yarn prediction model is a deep neural network model based on the assumption that the influence of textile processing time series on yarn quality is considered.Cnn optimizes the input eigenvalues through one-dimensional convolution and pooling, and lstm matches the optimized fiber performance indexes and process parameters in time series according to the processing sequence and excavates their laws, thus realizing the goal of predicting yarn quality indexes.The effects of input fiber performance index, process parameters, convolution kernel parameters, pool kernel parameters, lstm unit number, lstm layer number, and optimization algorithm on prediction accuracy were studied, and the parameters of cnn-lstm model were determined.Experiments on the data set of spinning yarn show that the mean square error (mse) of cnn-lstm model in predicting yarn strength, dan qiang unevenness, evenness unevenness, and total neps is lower than that of linear regression model and bp neural network.At the same time, it is found that the prediction accuracy of cnn-lstm model is greatly influenced by process parameters and optimization algorithm.

Journal: Journal of Sensors (2022)
Publication types: Research Article;
Pisonia Alba Assisted Synthesis of Nanosilver for Wound Healing Activity

Wound infection is a major clinical challenge, impacting patient morbidity and mortality, with significant economic implications.Our research focused on how pisonia alba (pa) leaves, which are used to treat wounds, are used to synthesize silver nanoparticles and study their wound healing property.Uv‐visible spectroscopy, x‐ray diffraction analysis, and s electron microscope (sem) analysis were employed to evaluate the synthesized silver nanoparticles.Using dls and zeta potential analysis, the size and stability of the pisonia alba capped silver nanoparticle were investigated.The results showed that pisonia alba extract stabilized silver nanoparticles are 63.88 nm in size and have a spherical shape.Antibacterial and antibiofilm potential of synthesized silver nanoparticles against pathogenic organisms gram‐positive ( staphylococcus aureus ) and gram‐negative ( escherichia coli ) bacteria were investigated.The in vitro cell scratch wounding assay is used to investigate the wound healing properties of synthesized nanoparticles.Pisonia alba stabilized silver nanoparticles (pa@ag nps), in comparison to pisonia alba (pa) extract, show effective wound healing characteristics by inducing the formation of collagen and serving as a capable wound healing agent.

Journal: Bioinorganic Chemistry and Applications (2022)
Publication types: Research Article;
Optimization of Color Enhancement Processing for Plane Images Based on Computer Vision

As the main carrier of information transmission, plane images play an important role in the current network era.In order to enhance the color of the plane image, optimize the image effect, and solve the problem of image distortion with large color difference, a color enhancement processing optimization method is proposed based on the technical support of computer vision.According to computer vision theory, a computer vision model for adjusting perceived color and brightness is constructed.Combining it with the bilateral filtering algorithm, a color enhancement processing optimization model is obtained, which consists of three main stages: illumination information parameter estimation and image color correction, reflection coefficient parameter estimation and image color correction, and adaptive filtering.By estimating illumination information parameters and reflection coefficient parameters, the secondary gamma correction of image color is realized.After being processed by the bilateral filtering algorithm, the final optimized image is obtained.Verified by the subjective and objective evaluation results, the positive correlation index values of this method are all high, 8.0246, 16.4526, 0.9037, and 15.0246, respectively, and the negative correlation index value is low, 49.4169.It is proved that the proposed method can effectively suppress the halo and artifacts and obtain the image color quality that satisfies the visual perception.It not only enhances the image color but also retains the details to the greatest extent.

Journal: Journal of Sensors (2022)
Publication types: Research Article;
Optimization of Agricultural Machinery Task Scheduling Algorithm Based on Multiobjective Optimization

In order to improve the effect of agricultural machinery task scheduling, this paper starts from the perspective of multiobjective optimization to achieve task scheduling based on multiobjective particle swarm optimization algorithm.The position of each particle is a combination of resource options for each construction activity, and the displacement range and speed range of the particles are determined.Moreover, this paper uses the method of introducing an external storage library to store the current noninferior solutions and uses the adaptive grid method and the roulette selection method to select the global optimal solution of the particles.In addition, this paper proposes a task scheduling algorithm suitable for modern agricultural machinery based on the actual needs of current agricultural machinery task scheduling.The experimental results show that the agricultural machinery task scheduling algorithm based on multiobjective optimization proposed in this paper has a good agricultural machinery task scheduling effect and meets the basic purpose of optimizing the algorithm in this paper.

Journal: Journal of Sensors (2022)
Publication types: Research Article;
Optimization and Simulation of Controller Area Network Communication Model Based on Industrial Internet of Things Platform

The internet of things (io t) is an information carrier based on network communication, and it can make all general physical objects which can be independently addressed from an interconnected network.Controller area network (can) is a kind of serial communication network which can effectively support distributed control or real-time control.This paper proposes the design of an io t-oriented universal can bus.In order to build a complete can communication simulation model, message sending and message receiving models are constructed, respectively.The simulation experiment proves that the io t-oriented network communication model designed in this paper not only has low power consumption, but it can also solve the front-end compatibility problems caused by different communication protocols.

Journal: Complexity (2020)
Publication types: Research Article;
Optimal Design of Vehicle Structure Based on Computer-Aided Technology

In order to improve the optimization design effect of modern automobile vehicle structure, this paper combines computer-aided technology to carry out vehicle structure optimization design, introduces the material description of the collision process, expounds the boundary conditions in the collision process, and introduces the theory of explicit integration algorithm.In the simulation process, it is necessary to deal with time step control, contact algorithm, hourglass control, etc., and analyze the optimization method of automobile collision, which is divided into experimental design and optimization method.In addition, the experimental design mainly introduces the orthogonal experimental design, which is applied to the lightweight design of automobile structures.The research verifies that computer-aided technology can play an important role in vehicle structure optimization and effectively improve the scientificity of vehicle structure design.

Journal: Journal of Electrical and Computer Engineering (2022)
Publication types: Research Article;
Optical Microscope Rehabilitation Nursing Study of Anterior Cruciate Ligament Injury through Lateral Knee Incision Based on Medical Internet of Things

With the high development of sports, football has attracted more and more attention from the public.However, the hot competition has made football players undergo high-intensity training, and the risk of injury caused by training is also increasing.Lateral incision knee acl injury is one of the most common types of injuries in football players, which has a serious impact on the athlete’s physiology and daily training.The comprehensive, multi-level, convenient and fast medical system brought by the medical internet of things has become the growing demand of the medical industry.Based on the medical internet of things, this paper studies the rehabilitation nursing of football players’ acl injury by lateral cutting and running combined with optical microscope.In this paper, 36 male and female football players were selected for group experiments, and the landing and peak torque indexes of the experimental group and the control group of male and female athletes were analyzed under the observation of an optical microscope.Group (p &lt;0.05), coxa valgus (p &lt;0.01), internal rotation and knee valgus angles were greater than those in the em group.And the peak hip flexion angle and knee valgus moment in nf group were lower than those in ef group (p &lt;0.05).After 12 weeks of rehabilitation training, there was a significant difference in the q/h joint contraction index between the ref group and the con group (p &lt;0.05), and there was no statistical difference in the other groups.After 12 weeks of rehabilitation training, there was a significant difference in the q/h joint contraction index between the ref group and the con group (p &lt;0.05), and there was no statistical difference in the other groups.That is to say, after the systematic rehabilitation training proposed in this paper, the joint contraction performance of the hamstrings/quadriceps in the ref group has been significantly improved.This shows that the rehabilitation nursing under the optical microscope based on the medical internet of things has a good effect on the rehabilitation of the football player’s side-cut running knee joint acl injury.

Journal: Applied Bionics and Biomechanics (2022)
Publication types: Research Article;