syedzayyan/paper_mill_benchmark huggingface dataset:
Application of 24 h Dynamic Electrocardiography in the Diagnosis of Asymptomatic Myocardial Ischemia with Arrhythmia in Elderly Patients with Coronary Heart Disease

To investigate the application effect of 24 h dynamic electrocardiogram in the diagnosis of asymptomatic myocardial ischemia with arrhythmia in elderly patients with coronary heart disease.Methods.A total of 206 elderly patients suspected of coronary heart disease (chd) with asymptomatic myocardial ischemia and arrhythmia were selected as the research subjects.24 h dynamic electrocardiogram and conventional electrocardiogram examinations were conducted.Coronary angiography was used as the gold standard to observe the performance of the two examination methods in the diagnosis of asymptomatic myocardial ischemia with arrhythmia in elderly patients with chd.Results.Coronary angiography showed 174 positive cases and 32 negative cases among the 206 patients.The diagnostic results of a conventional electrocardiogram showed 150 positive cases and 20 negative cases.Its sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were 86.21%, 62.50%, 82.52%, 92.59%, and 45.45%, respectively.The diagnostic results of 24 h dynamic electrocardiograms showed 168 positive cases and 29 negative cases.Its sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were 96.55%, 96.63%, 95.63%, 98.25%, and 82.86%, respectively.The above results indicated that 24 h dynamic electrocardiogram was significantly better ( p &lt; 0.05 ).The detection rate of arrhythmia types by 24-hour dynamic electrocardiogram was significantly higher than that of conventional electrocardiogram ( p &lt; 0.05 ).Conclusion.24 h dynamic electrocardiogram is helpful for the diagnosis of asymptomatic myocardial ischemia with arrhythmia in elderly patients with chd and can improve the detection rate, thereby providing a basis for clinical diagnosis and treatment.

Journal: Emergency Medicine International (2022)
Publication types: Research Article;
Application and the Effect of the Triple Prerehabilitation Nursing Model in the Perioperative Period of Knee Arthroplasty in Diabetic Patients

The aim of the study was to explore the application and the effect of the triple prerehabilitation nursing model in the perioperative period of knee arthroplasty in diabetic patients.Methods.The prospectively included 60 patients with diabetes who underwent total knee replacement were admitted from august 2021 to april 2022 and were divided into 2 groups according to the (1 : 1) ratio.The control group was mainly given routine nursing care.On the basis of the control group, the observation group received triple prerehabilitation nursing.The postoperative knee flexion, hospital for the special surgery knee score (hss), the daily living ability (barthel) score, the modified fall efficacy scale (mfes) score, the recovery of the lower-limb muscle strength, and the incidence of complications were compared between the two groups.Results.The knee flexion degree and lower-limb muscle recovery of the observation group were better than those of the control group at 3 d, 7 d, and 14 d after operation ( p &lt; 0.05 ).The hss score, barthel score, and mfes score of the observation group were higher than those of the control group ( p &lt; 0.05 ).There was no significant difference in postoperative complications between the two groups ( p &gt; 0.05 ).Conclusion.The triple prerehabilitation nursing care for diabetic patients undergoing total knee replacement can promote the recovery of limb function.

Journal: Emergency Medicine International (2022)
Publication types: Clinical Study;
Application of Convolution Neural Network Algorithm Based on Intelligent Sensor Network in Target Recognition of Corn Weeder at Seedling Stage

Grass damage in the seedling corn field has always been an important factor affecting the growth and development of crops.The existence of grass not only compresses the living space of corn seedlings but also easily causes insect damage.Therefore, it is essential for weeding in the seedling corn field.The existing weeding methods usually use manual or chemical herbicide spraying, which is not only time-consuming and laborious but also inefficient.With the development of artificial intelligence and modern agricultural technology, the use of robots for field weeding has become an effective means, which has attracted more and more attention of researchers at home and abroad.Therefore, based on the full investigation of the development of relevant technologies at home and abroad, this paper carried out the research on the real-time target recognition and ranging method of field weeding robot and proposed a target recognition method of weeding corn at the seedling stage by using an intelligent sensor network and deep learning convolution neural network.Among them, the intelligent sensor is mainly used for target ranging and obstacle avoidance, and cnn is mainly used for target recognition.Taking the images of corn seedlings and weeds in the seedling stage under natural environmental conditions as samples, the migration training is carried out through the depth network model of the coco data set, and the convolution features are shared by the cnn depth network model and fast-cnn depth network model.Vgg and res net feature extraction networks are compared.The experimental results show that the cnn depth network model based on this paper has obvious advantages in rape and weed target recognition.The target recognition accuracy of rape and weeds can reach 87.64%, and the recall rate can reach 80.23%.Compared with other models, it has obvious advantages, which proves the effectiveness of this model.

Journal: Journal of Sensors (2022)
Publication types: Research Article;
Anticancer and Free Radical Scavenging Competence of Zinc Oxide Nanoparticles Synthesized by Aqueous Leaf Extract of Phyllanthus acidus

The purpose of this study was aimed to investigate the zinc oxide nanoparticles (zn onps) synthesizing efficiency of aqueous leaf extract of phyllanthus acidus.Furthermore, the antioxidant and anticancer activities of synthesized zn onps were also investigated through the in‐vitro approach.The obtained results show that the aqueous extract of p.Acidus can synthesize zn onps, as evidenced by a sharp absorbance peak at 375 nm.The fourier transform infrared spectroscopy (ftir) analysis confirmed that the aqueous extract contained significant numbers of functional groups, which were involved in reducing zinc nitrate into zn onps.Also, they participate in the capping and stabilization of synthesized zn onps and their size ranged from 27.14–35.74 nm with a spherical shape .The results obtained in abts radical scavenging activity 1, 1‐diphenyl‐2‐picryl‐hydroxyl (dpph), hydrogen peroxide (h 2 o 2 ), and 2,2′‐azino‐bis(3‐ethylbenzene thiazoline‐6‐sulfonic acid) (abts) assays declared has excellent in‐vitro radicals scavenging activity with reasonable ic 50 values.Interestingly, these green synthesized zn onps have an excellent anticancer activity against human epidermoid carcinoma (hep3) cell line in an in‐vitro approach.These findings imply that an aqueous leaf extract of p.Acidus can be used to synthesize pharmaceutically valuable zn onps.To consider such nanomaterials as potential therapeutic agents, optimization and in‐vivo biomedical studies are required.

Journal: Bioinorganic Chemistry and Applications (2022)
Publication types: Research Article;
Analysis of the Development Trend and Scheme of Agricultural Electrification Intelligence Based on Big Data Mining and OLAP Tool Analysis Algorithm

To transform from a large agricultural country to a strong agricultural country, china must take the road of modernized, automated, and information-based agriculture.With the advantages of high efficiency, low cost, flexibility, stability, and reliability, electrified production is the material and technical basis for agricultural mechanization, automation, industrialization, and management modernization.Big data mining and olap tool analysis algorithm has powerful data processing ability and occupies a very important part in various fields.This article analyzes the current situation of agricultural electrification development, electrification development dynamics, and electrification application scope based on big data mining and olap tool analysis algorithm, and finally comes up with several suggestions for agricultural electrification development.

Journal: International Transactions on Electrical Energy Systems (2022)
Publication types: Research Article;
Analysis of the Clinical Value of MAGE-A9 Expressions in Cervical Cancer Tissues and PBMC

The aim of this study is to explore the expressions and clinical significance of melanoma-associated antigen-a9 (mage-a9) in cervical cancer tissues and peripheral blood mononuclear cells (pbmc).Methods.108 patients who were scheduled to undergo cervical conization or extensive hysterectomy between march 2019 and january 2021 due to cervical lesions were selected by convenient sampling.According to postoperative pathological results, the patients were divided into a cervical cancer group (n = 64) and cervical intraepithelial neoplasia (cin) group (n = 44).The expression levels of mage-a9 m rna in cervical lesion tissues and pbmc were detected by real-time fluorescence quantitative pcr, and the expression of mage-a9 protein in lesion tissues was detected by immunohistochemistry.The correlation between mage-a9 m rna expressions in cancer tissues and pbmc and serum tumor markers in patients with cervical cancer and the relationship between mage-a9 protein expression in cancer tissues and clinicopathological characteristics were analyzed, and a receiver operating characteristic curve (roc curve) was drawn to explore the diagnostic value of mage-a9 m rna expressions in cancer tissues and pbmc on cervical cancer.Results.The expression levels of mage-a9 m rna in cervical lesion tissues and pbmc in the cervical cancer group were significantly higher than those in the cin group ( p &lt; 0.05 ), and the levels of serum scc-ag, ca-125, and cea were significantly higher than those in the cin group ( p &lt; 0.05 ).The positive rate of the mage-a9 protein expression in cervical lesion tissues in the cervical cancer group was significantly higher than that in the cin group ( p &lt; 0.05 ).The expression levels of mage-a9 m rna in cancer tissues and pbmc of patients with cervical cancer were positively correlated with serum scc-ag, ca-125, and cea ( p &lt; 0.05 ).The positive rate of the mage-a9 protein expression in cervical cancer tissues was related to figo stage, tumor diameter, degree of differentiation, lymph node metastasis, and high-risk hpv infection ( p &lt; 0.05 ) and was not correlated with age and pathological type ( p &gt; 0.05 ).The areas under the roc curves of mage-a9 m rna in lesion tissue and mage-a9 m rna in pbmc were 0.925 and 0.900 in the diagnosis of cervical cancer ( p &lt; 0.05 ).Conclusion.The expressions of mage-a9 in cancer tissues and pbmc of patients with cervical cancer are upregulated, which is related to the levels of serum tumor markers and the progression of disease.Mage-a9 is expected to become an important marker for the diagnosis of early cervical cancer.

Journal: Emergency Medicine International (2022)
Publication types: Research Article;
Correlation Analysis of Japanese Literature and Psychotherapy Effects Based on an Equation Diagnosis Algorithm

On the basis of inheriting the classical aesthetic orientation of japanese literature, contemporary japanese literature changes the creative methods of traditional japanese writers, strives to transcend the national limitations of japanese literature, and strives to capture literary materials with a “modern feel.” combined with modern western literary techniques to express the “modern self,” and integrating popular literature with pure literature, japanese writers created a “healing” literature that is popular all over the world.There is some value in exploring the correlation between japanese literature and the influence of psychotherapy.Method.In this paper, an equation diagnosis algorithm based on iterative learning for a class of linear discrete systems is studied, and the existing discrete iterative learning diagnostics are improved.We exchange the order of time domain and iterative domain to achieve the purpose of point-by-point equation diagnosis.On this basis, a virtual influence initial value estimation algorithm with a sliding window is proposed.The impact that has not been diagnosed is estimated and used as the initial value of the impact, so as to reduce the number of iterations and improve the efficiency of equation diagnosis.This paper takes the public and readers as different perspectives, based on the use and satisfaction theory and prospect theory, and uses interviews and questionnaires to study the communication effect of japanese literature from the three dimensions of cognition, emotion, and behavior.The cognitive part includes the public’s understanding and readers’ understanding and reading; the emotional part includes the public’s and readers’ impressions and emotional attitudes; the behavioral part includes the public’s reading situation and readers’ behavior changes.Results/discussion.In the survey of loyal readers, although readers’ understanding of japanese literature has improved compared with the general public, it is not high, and their liking and influence on behavior are slightly lower than the preset level.This paper believes that the existing problems of japanese literature dissemination are mainly concentrated in three aspects: the market is somewhat biased, which narrows the cognitive scope of users; as a cross-cultural literary work, japanese literature still makes readers feel that it exists; there is some sense of estrangement, which will affect their enjoyment in reading; as a niche interest, readers lack timely communication and sharing objects after reading, so it is difficult to enhance their sense of identity.

Journal: Occupational Therapy International (2022)
Publication types: Research Article;
Correlation Analysis between Residents’ Income Satisfaction and Mental Health Based on Big Data

This paper presents an in-depth study and analysis of the correlation between satisfaction with rural residents’ income and mental health well-being in the context of industrial structure upgrading.Most of the studies on residents’ subjective well-being from the perspective of relative income or income inequality have started from the happiness of rural residents and the satisfaction of rural residents’ life, and few scholars have focused on the psychological health of rural residents.Subjective well-being is significantly related to external and internal goals in desire.Life satisfaction is significantly and positively correlated with external and internal goals, as well as the six dimensions of desire, except for social identity; positive emotions are significantly and positively correlated with internal goals; negative emotions are only negatively correlated with self-acceptance, and there is a significant positive correlation between income level and desire.In vertical income, there is also a process of judging whether the expected income is achieved.If the expected income growth level is achieved, the income satisfaction will increase.Desire mediates the effect of income level on subjective well-being.Income level influences subjective well-being through internal goals; income level influences life satisfaction and positive emotions through external goals.The relationship between income inequality and mental health is influenced by the characteristics of the population, with women and middle-aged people being the most negatively affected.This relationship is also influenced by income level, with the effect of income inequality on mental health showing a negative effect in the lower and middle-income groups but a positive effect in the higher income groups.Income inequality affects residents’ mental health through the mediating effects of a sense of social justice, life stress, and trust in government.Inequality in household wealth can exacerbate the negative effects of income inequality on mental health.

Journal: Occupational Therapy International (2022)
Publication types: Research Article;
Ancient Stone Inscription Image Denoising and Inpainting Methods Based on Deep Neural Networks

Chinese ancient stone inscriptions contain chinese traditional calligraphy culture and art information.However, due to the long history of the ancient stone inscriptions, natural erosion, and poor early protection measures, there are a lot of noise in the existing ancient stone inscriptions, which has adverse effects on reading these stone inscriptions and their aesthetic appreciation.At present, digital technologies have played important roles in the protection of cultural relics.For ancient stone inscriptions, we should obtain more perfect digital results without multiple types of noise, while there are few deep learning methods designed for processing stone inscription images.Therefore, we propose a basic framework for image denoising and inpainting of stone inscriptions based on deep learning methods.Firstly, we collect as many images of stone inscriptions as possible and preprocess these images to establish an inscriptions image dataset for image denoising and inpainting.In addition, an improved gan with a denoiser is used for generating more virtual stone inscription images to expand the dataset.On the basis of these collected and generated images, we designed a stone inscription image denoising model based on multiscale feature fusion and introduced charbonnier loss function to improve this image denoising model.To further improve the denoising results, an image inpainting model with the coherent semantic attention mechanism is introduced to recover some effective information removed by the former denoising model as much as possible.The experimental results show that our image denoising model achieves better results on psnr, ssim, and cei.The final results have obvious visual improvement compared with the original stone inscription images.

Journal: Discrete Dynamics in Nature and Society (2021)
Publication types: Research Article;
Complexity Computer Simulation in the Study of the Overall Playing Method of Campus Football

With the mutual exchange and integration of world football, modern football is in an increasingly comprehensive direction.This research mainly discusses complexity computer simulation in the study of the overall play of campus football.Complexity computer simulation is used to design the background of the simulated football field, and the area is divided according to the size ratio of the actual football field.Then, it uses drawing software to draw the football and player controls.The construction of the knowledge base of this paper is mainly combined with the functional modules of rapid formation and response tactics.In the fast formation function, the required formation can be quickly given through football experience and knowledge rules.In the applied tactics function, for the responsibilities of forwards, midfielders, defenders, and other roles, the tactics implemented are given, including partially coordinated offensive and defensive tactics, personal offensive and defensive tactics, and set‐ball tactics.The “holistic play” football tactics studied in this paper use xml files as recording and playback data, which not only greatly reduce the amount of file data but also make the operation of xml files intuitive and simple.Xml can not only realize the recording and playback of player and football track but also be used in the function of rapid formation.The coach uses the “holistic play” football tactics simulation to demonstrate the movement route through the image, guide the players in each position to perceive the game scene by observing the movement route, and analyze and judge the tactical coordination of their respective positions.The computer simulation tactical analysis of the precision of the passing and running and the path coefficient of the passing factor is 0.606 and 0.59, respectively.This research helps to provide guidance on the overall playing tactics of football.

Journal: Complexity (2021)
Publication types: Research Article;
Analysis Method of Agricultural Total Factor Productivity Based on Stochastic Block Model (SBM) and Machine Learning

When analyzing agriculture’s total factor productivity, traditional measurement approaches do not take into account the inefficiency value.The production functions are assumed to be analyzed on basis of the random boundaries, which makes the analysis results inaccurate and unreliable.As a result, this paper proposes an analytical approach for agricultural total factor productivity based on the stochastic block model (sbm), which combines the benefits of statistics and machine learning.It uses the sbm direction distance function and the luenberger productivity index to measure the agricultural efficiency, total factor productivity, and their components.The research study considers the data from 31 provinces from 2006 to 2018 years.First, one output indicator and six input indicators are established.The time-varying variations of the national agricultural inefficiency value and its source decomposition under variable scale returns are then determined using the sbm-based algorithm of agricultural total factor productivity and the obtained sample data.The changes of the agricultural total factor productivity and its components are comprehensively analyzed.Following an examination of the elements impacting agricultural efficiency and productivity, the socioeconomic development of the agricultural total factor productivity is examined in order to achieve efficient growth.

Journal: Journal of Food Quality (2022)
Publication types: Research Article;
A Study on the Impact of Perioperative Pain Care Management on Pain, Comfort, and Defecation of Patients in Anorectal Surgery

The aim of the study is to explore the impact of perioperative pain care management on patients’ pain, comfort, and defecation in anorectal surgery.Methods.From january to december 2021, 126 patients who underwent anorectal surgery in our department were selected for the study and were randomly divided into a study group and a control group of 63 patients each after consent was obtained from the patients.The control group was given the usual care protocol and the study group was given the perioperative pain care management on top of the usual care.The two groups of patients were compared in terms of postoperative anal pain rating, comfort score, time to first bowel movement and time spent in bowel movement, the pittsburgh sleep quality index (psqi) scores at night, related complications, and satisfaction with care.Results.1 postoperative anal pain was less severe in the study group than in the control group ( p &lt; 0.05 ).2 postoperative comfort scores were higher in the study group than in the control group ( p &lt; 0.05 ).3 the time to first bowel movement and its duration after surgery were shorter in the study group than in the control group ( p &lt; 0.05 ).4 patients in the study group had lower postoperative night-time psqi scores than the control group ( p &lt; 0.05 ).5 patients in the study group had a lower rate of postoperative complications than the control group ( p &lt; 0.05 ).6 patients in the study group had higher postoperative care satisfaction scores than the control group ( p &lt; 0.05 ).Conclusion.The application of perioperative pain care management to patients undergoing anorectal surgery plays an important role in reducing anal pain, improving treatment comfort, and relieving difficult defecation symptoms, with significant improvement in postoperative sleep quality and reduction in complications.It is worthy of clinical reference and promotion.

Journal: Emergency Medicine International (2022)
Publication types: Clinical Study;