syedzayyan/paper_mill_benchmark huggingface dataset:
Occupational Health Development and Safety Management of Enterprise Employees Based on the Perspective of Sustainable Environment

In recent years, the economy of enterprises has developed rapidly.Most enterprises focus on economic interests and ignore the occupational health of employees, resulting in an increase in the occupational morbidity rate of employees.Occupational insecurity of corporate employees will reduce the work efficiency of employees.In turn, it will affect the economic development of the enterprise.Paying attention to the occupational health and safety development of corporate employees is a necessary measure for corporate economic development.The main reasons that endanger the occupational health of employees are the unreasonable discharge of pollutants and the substandard treatment of pollutants.The sustainable environmental strategy of enterprise development can well control the risk factors that endanger the occupation of enterprise employees, and it is conducive to the health and safety development of enterprise employees and enterprises.This paper studied the impact of sustainable environmental factors on the occupational health and safety development of enterprise employees through the fuzzy analytic hierarchy process and analyzed the impact on the occupation of enterprise employees according to the larger influencing factors.The experimental results showed that heavy metal wastewater, dust, hydrogen sulfide gas, and high‐temperature radiation are the four most weighted impact indicators.Different concentrations of these four indicators are tested; when the concentration value of these impact indicators is low, it has little impact on the occupational safety and development of enterprise employees.However, when the concentration increases, the occupational safety and development of enterprise employees are seriously reduced.When the safety is the lowest, it is only 20%, and the development is only 23%.Carrying out sustainable environmental development can reduce the discharge of industrial waste; hence, while protecting the environment, the occupational health and safety and development potential of employees can be improved.

Journal: Journal of Environmental and Public Health (2022)
Publication types: Research Article;
Obstructive Sleep Apnea Syndrome Treated Using a Positive Pressure Ventilator Based on Artificial Intelligence Processor

With the acceleration of people’s life rhythm, obstructive sleep apnea syndrome appears more and more frequently.This research mainly discusses the treatment of obstructive sleep apnea syndrome with a positive pressure ventilator based on artificial intelligence processor.The information storage function of the smart positive pressure ventilator is included in the local medical terminal, presented after logging in with the user authority.It is mainly composed of data collection, data processing, and medical interface design, which embeds data request, data transmission, data analysis, and detailed tasks such as data compression and storage, and functions such as data display, image drawing, and alarm notification are realized by the medical interface.When the cpap ventilator transmits respiratory data to the local medical terminal, it sends real-time respiratory information data packets.The data packet is collected and sent in real time in a fixed period and then received and analyzed by the local medical terminal.In the cpap ventilator telemedicine system, the function of alarm message processing is mainly used to detect the patient’s breathing status in real time, extract the alarm-related information, and generate an alarm.This function specifically includes several tasks such as alarm detection, alarm prompt, alarm storage, and remote transmission of alarm messages.The confirmed osas patients were pressure-titrated with a smart cpap ventilator and then treated for 5 hours a day, followed by echocardiography after 5 months of continuous treatment.During the study, the average bmi was (28.9 ± 7.2) kg/m2 and the average ahi index was (53.1 ± 37.8) times/h.This study may help improve the quality of life of patients with obstructive sleep apnea syndrome.

Journal: Journal of Healthcare Engineering (2021)
Publication types: Research Article;
Nutritional Management Mode of Early Cardiac Rehabilitation in Patients with Stanford Type A Aortic Dissection

Malnutrition and metabolic disorders are common problems faced by patients with stanford type a aortic dissection after surgery.Some patients have dietary problems such as malnutrition, unbalanced diet, and poor eating habits before surgery.Therefore, the nutritional management of early heart health can improve the nutritional support for perioperative recovery, to improve the pertinence.Therefore, active nutritional support after surgery will help to change malnutrition and metabolism and is of great significance to postoperative recovery and quality of life.This paper is aimed at studying the nutritional management mode of early cardiac rehabilitation in patients with stanford type a aortic dissection.Based on the analysis of the pathogenesis of aortic dissection and the diagnosis of aortic dissection, two groups of patients were given individualized nutritional management scheme and routine nutritional scheme, respectively, and the nutritional risk differences between the two groups under different schemes were compared.The results showed that there was a statistical difference between the two groups at discharge.The nrs-2002 score of 14 cases in the observation group was less than 3 after nutritional intervention, indicating that there was no nutritional risk at discharge.

Journal: Computational and Mathematical Methods in Medicine (2022)
Publication types: Research Article;
Nursing Analysis Based on Medical Imaging Technology before and after Coronary Angiography in Cardiovascular Medicine

With the advancement of technology, medical imaging technology has been greatly improved.This article mainly studies the nursing before and after coronary angiography in cardiovascular medicine based on medical imaging technology.This paper proposes a multimodal medical image fusion algorithm based on multiscale decomposition and convolution sparse representation.The algorithm first decomposes the preregistered source medical image by nsst, takes the subimages of different scales as training images, and optimizes the subdictionaries of different scales; then convolution and sparse the subimages on each scale encoding to obtain the sparse coefficients of different subimages; secondly, the combination of improved l1 norm and improved spatial frequency (novel sum-modified sf (nmsf)) is used for high-frequency subimage coefficients, and the fusion of low-frequency subimages improved the rule of combining the l1 norm and the regional energy; finally, the final fused image is obtained by inverse nsst of the fused low-frequency subband and high-frequency subband.Experimental analysis found that the bifurcation angle has nothing to do with the damage of the branch vessels after the main branch stent is placed.The bifurcation angle greater than 50° is an independent predictor of mace after stent extrusion for bifurcation lesions.Experimental results show that the proposed method has good performance in contrast enhancement, detail extraction, and information retention, and it improves the quality of the fusion image.

Journal: Applied Bionics and Biomechanics (2022)
Publication types: Research Article;
Establishment and Application of Pressure Injury Assessment Module in Operating Room Based on Information Management System

A pressure injury is a common and painful health condition, particularly among people who are elderly or surgical patients.In order to explore how to use the information management system to optimize the pressure injury management process of surgical patients, this work establishes an integrated pressure injury management information platform for surgical patients, which can effectively control the key links in the process and realize the multistep full-process monitoring of surgical patients from admission to discharge.A total of 578 patients before the operation of the information platform were selected as the control group (cg), and after the operation of the information platform, 662 cases became the observation group (og).Various evaluation metrics are employed to evaluate pressure injury in terms of single-pass rate, high-risk pressure injury, transfer skin condition description matching rate, hospital pressure injury incidence, and incidence of pressure injury in surgical patients at various stages.The results showed that the qualified rate of the pressure injury assessment in the og was 99.2%, the accuracy rate of high-risk pressure injury screening and reporting was 100.0%, and the matching rate of the transfer skin description was 100.0%, which was higher than that of the cg.The integrated pressure injury management information platform for surgical patients based on the information management system realizes the full, continuous, accurate, and dynamic evaluation and monitoring of patients’ skin.Furthermore, it can effectively improve the quality of pressure injury care and facilitate care management.

Journal: Journal of Healthcare Engineering (2022)
Publication types: Clinical Study;
Generalized Zero-Adjusted Models to Predict Medical Expenditures

In healthcare research, medical expenditure data for the elderly are typically semicontinuous and right‐skewed, which involve a point mass at zero and may exhibit heteroscedasticity.The problem of a substantial proportion of zero values prevents traditional regression techniques based on the gaussian, gamma, or inverse gaussian distribution, which may lead to understanding the standard errors of the parameters and overestimating their significance.A common way to counter the problem is using zero‐adjusted models.However, due to the right‐skewness in the nonzeros’ response, conventional zero‐adjusted models such as zero‐adjusted gamma, zero‐adjusted inverse gaussian, and classic tobit may not perform well.Here, we firstly generalize those three types of the conventional zero‐adjusted model to solve the problem of right‐skewness in health care.The generalized zero‐adjusted models are very flexible and include the zero‐adjusted weibull, zero‐adjusted gamma, zero‐adjusted inverse gaussian, and classic tobit models as their special cases.Using the chinese longitudinal healthy longevity survey, we find that, according to the aic, sbc, and deviance criteria, the zero‐adjusted generalized gamma model is the best one of these generalized models to predict the odds of zero cost accurately.In order to depict the predictors affecting the amount expenditure, we further discuss the situations where the mean, dispersion of a nonzero amount expenditure and model the probability of a zero amount of zagg in terms of predictor variables using suitable link functions, respectively.Our analysis shows that age, health, chronic diseases, household income, and residence are the main factors influencing the medical expenditure for the elderly, but the insurance is not significant.To the best of our knowledge, little study focused on these situations, and this is the first time.

Journal: Computational Intelligence and Neuroscience (2021)
Publication types: Research Article;
Depth Vision-Based Assessment of Bone Marrow Mesenchymal Stem Cell Differentiation Capacity in Patients with Congenital Scoliosis

Congenital scoliosis (cs) is a lateral curvature of one or more segments of the spine due to spinal dysplasia during fetal life.Cs is clinically defined as a curvature of the spine &gt;10° due to structural abnormalities of the vertebrae during the embryonic period.Its etiology is unknown, but recent studies suggest that it may be closely related to genetic factors, environmental factors, and developmental abnormalities.The induction methods and modern applications of bone marrow mscs provide a reference for in-depth human research on the induction of differentiation of bone marrow mscs into osteoblasts.In this paper, by reviewing and organizing the literature on bone marrow mscs, we summarized and analyzed the biological properties and preparation of bone marrow mscs, the methods of inducing osteoblasts, the applications in tissue engineering bone, the problems faced, and the future research directions and proposed a method to assess the differentiation ability of bone marrow mscs in patients with congenital scoliosis based on depth visual characteristics and the change of the method.The method reveals and evaluates the multidirectional differentiation potential of bone marrow mscs, which can be induced to differentiate into osteoblasts in vitro and can be used to construct bone tissue engineering scaffolds in vitro using tissue engineering techniques.Based on the properties of bone marrow mscs, their application in congenital scoliosis patients for trauma repair, cell replacement therapy, hematopoietic support, and gene therapy is quite promising.It is necessary to carry out research on the mechanism of osteogenic differentiation of bone marrow mscs to provide guidance and reference value for their induced differentiation into osteoblasts.

Journal: Journal of Healthcare Engineering (2022)
Publication types: Research Article;
Deep Learning-Based Identification of Spinal Metastasis in Lung Cancer Using Spectral CT Images

In this study, deep learning algorithm-based energy/spectral computed tomography (ct) for the spinal metastasis from lung cancer was used.A dilated convolutional u-net model (dc-u-net model) was first proposed, which was used to segment the energy/spectral ct image of patients with the spinal metastasis from lung cancer.Subsequently, energy/spectral ct images under different energy levels were collected for the signal-to-noise ratio (snr) and contrast-to-noise ratio (cnr) comparison.It was found the learning rate of the model decreased exponentially as the number of training increased, with the lung contour segmented out of the image.Under 40–65 ke v, the ct value of bone metastasis from lung cancer decreased with increasing energy, as with the average rank sum test result.The snr and cnr values were the highest under 60 ke v.The detection rate of the deep learning algorithm below 60 ke v was 81.41%, and that of professional doctors was 77.56%.The detection rate of the deep learning algorithm below 140 ke v was 66.03%, and that of professional doctors was 64.74%.In conclusion, the dc-u-net model demonstrates better segmentation effects versus the convolutional neutral networ k (cnn), with the lung contour segmented.Further, a higher energy level leads to worse segmentation effects on the energy/spectral ct image.

Journal: Scientific Programming (2021)
Publication types: Research Article;
Subdivision of Artistic Objectives of Oil Painting Creation under the Evaluation of Deep Learning Model

In order to fully segment and classify the artistic objectives of painting and realise the needs of automatic classification and retrieval of painting by computer, this paper proposes to establish convolution neural network with dual core compression activation module and deep separation convolution.The dkse module is constructed based on the structural features of sknet.Sknet extracts the overall image and detail features, senet enhances the channel features.Using dkse module and depth separable convolution, a convolution neural network is established to classify paintings.Dkse module can effectively improve the classification performance of the model, fully extract the overall and local detail features of oil painting images, and provide better classification accuracy than the traditional network model.

Journal: Journal of Sensors (2022)
Publication types: Research Article;
Deep Intelligence-Driven Efficient Forecasting for the Agriculture Economy of Computational Social Systems

In the vision of smart cities, everything is highly connected with the aid of computational intelligence.Therefore, the cyber-physical society has been named a computational social system for a long time.Due to the high relation with vast populations’ national livelihood, agriculture will still serve as a core industry in the national economy.As a result, this study focused on an efficient forecasting method for the agriculture economy.In recent years, the conception of deep intelligence has received overall prevalence in academia because of its excellent performance in implementing intelligent information processing tasks.Hence, this paper utilized deep intelligence driven by neural networks and managed to investigate an efficient prediction method for the agriculture economy of computational social systems.To fit the time-series forecasting scene of the long-term development of the agriculture economy, the convolutional neural network model is slightly improved by revising its parallel structure into the recurrent format.Finally, simulations on realistic datasets are carried out to evaluate the proposed forecasting method.

Journal: Computational Intelligence and Neuroscience (2022)
Publication types: Research Article;
Study on the Fusion of Oil Painting Art and Digital Media Based on a Visual Sensor

Digital media art is a new type of art with rich sensory experience.Nowadays, digitization is flooding many areas of life.Under the sprint of a large amount of information, human beings have once again entered the digital age.This article is aimed at studying the fusion of oil painting art and digital media based on visual sensors, analyzing the application of digital imaging art using sensor technology in various fields, especially in the field of oil painting art, and analyzing the effects of digital media with the support of sensor technology.The artistic characteristics and rich forms of presentation are presented, and then, the key points of digital media design are summarized.This paper proposes to bring advanced sensor technology into the field of art for research, turning boring and difficult technical data into an interesting art form, making human-computer interaction more compact and humane, and creating better works of art, so that more and more people and different fields can enjoy the scientific and technological achievements.The sensor is a kind of bionics in modern science, which enables machinery to perceive the human environment like human or animal sensory organs, through the perception and detection of this environmental change, and writing a certain program, the signal data is converted into electricity or signal, and at the same time transmit these signals to receiving organs or devices, such as device sensors that simulate organs.The art of digital photography requires the intervention of sensor technology to make interaction and virtue more complete.The sensor technology also requires the art of digital photography to provide an external display window, which can better serve mankind and create greater social value.The combination of technology and art makes the presentation of art more distinctive.The experimental results of this paper show that the integration of oil painting art and digital media based on visual sensors has made digital media have an impact on more than 58% of oil painting art works and made many oil painting art works show an unprecedented sense of science and technology, which is important for future oil painting art.The development of the company has positive significance.

Journal: Journal of Sensors (2022)
Publication types: Research Article;
Cortical Plasticity Mechanism and Efficacy Prediction of Repeated Transcranial Magnetic Stimulation in the Treatment of Depression with Continuous Short Bursts of Rapid Pulse Stimulation (cTBS)

In order to further explore the therapeutic effects of high-frequency and low-frequency repetitive transcranial magnetic stimulation on depression and cognitive function in the elderly, this paper proposed a study on cortical plasticity mechanism and efficacy prediction of repetitive transcranial magnetic stimulation based on continuous short pulse fast pulse stimulation (ctbs).This paper selected 92 patients with depression in a hospital from january to december 2020 as the research object and divided them into control group, low-frequency group, and high-frequency group, 31 cases, 29 cases, and 32 cases, respectively.The continuous short pulse rapid pulse stimulation (ctbs) mode was used to explore the effect of brain network on patients’ emotional processing.After clinical treatment contrast, there was no significant difference in hamd-24 scores and rbans scores before treatment ( p &gt; 0.05 ), and there was a significant negative correlation between factors of cognitive impairment in patients and rbans scores ( p &lt; 0.01 or p &lt; 0.05 ), so it was proved that the repeated transcranial magnetic stimulation (c tbs) could be used as an effective treatment for depression.

Journal: Mediators of Inflammation (2022)
Publication types: Research Article;
Prediction of Sports Performance and Analysis of Influencing Factors Based on Machine Learning and Big Data Statistics

Performance prediction is one of the important contents of sports future development strategy research.This paper conducts research on sports performance prediction and influencing factor analysis based on machine learning and big data statistics.The purpose of forecasting research is to formulate short-term, medium-term, and long-term sports development planning and policy services for decision-makers of sports development.Advantages and disadvantages make sports workers consciously revise and realize their own sports future plans.First, the analysis of the influencing factors of sports performance is proposed, including the setting and scoring of sports examination items, research on standards, training methods for physical examination items, and physical examination learning.Second, the application of big data statistics based on machine learning algorithms is studied.Based on machine optimization algorithms, it summarizes the naive bayesian classification algorithm and big data statistical classification algorithm.The theoretical idea of rough set algorithm and finally through the comparative analysis experiment based on big data statistics of male and female sports test scores and the comparison experiment of the accuracy of three algorithms to predict the results, it is concluded that the endurance quality of boys is better than that of girls, which indicates the quality of sustainable development.There is a certain gender gap, there are significant differences in the skills of male and female students, and the machine-optimized algorithm can predict sports performance with the highest accuracy among the three algorithms.

Journal: Journal of Sensors (2022)
Publication types: Research Article;