syedzayyan/paper_mill_benchmark huggingface dataset:
A Novel Curcumin-Based Drug Powder Inhalation Medicine for Chronic Obstructive Pulmonary Disease

The dry powder inhaler is a new form of drug delivery that is widely used as an alternative to traditional drug delivery methods, addressing the shortcomings of traditional drug delivery methods and obtaining better therapeutic results.This mode of delivery is also one of the most rational ways to treat pulmonary diseases such as chronic obstructive pulmonary disease (copd).Curcumin, a natural polyphenol, has been shown to be effective in the treatment of copd.In this study, different concentrations of curcumin ethanol solution were spray dried with mannitol as a carrier to obtain dry powder particles with different particle size distribution for the preparation of curcumin dry powder inhaler.The solubility and physicochemical properties were further characterized by differential scanning calorimetry (dsc), x-ray diffraction (xrd), and scanning electron microscopy.The characterization results showed that the product obtained in the experiment had reasonable particle size distribution and excellent solubility properties, which were positive for the treatment of copd or other pulmonary diseases.

Journal: Bioinorganic Chemistry and Applications (2021)
Publication types: Research Article;
The Impact of Online Learning System on Students Affected with Stroke Disease

Stroke, also known as a cerebrovascular accident, is a medical emergency that causes temporary or permanent behavioral dysfunction in people.Sleep deprivation affects our brains in a variety of ways.The advantages of sleep much justify the risks of not having enough sleep.Sleep deprivation (sd) includes a variety of factors, including prolonged awake.Neuroimaging investigates sd’s impact on attention, working memory, mood, and hippocampal learning.We analyzed how this data enriches our mechanistic understanding of these alterations and the clinical illnesses linked with sleep disruption.We have used cronbach’s alpha to test the reliability of a scale, so we then have 19 individual attributes responding to 174 participants via survey.The evaluated result shows the reliability statistics; the value for cronbach’s alpha is .962, which is very excellent as it reaches 1.So, there is very strong reliability.If the value falls under .6, we look back to the mean and standard deviation table and remove the attribute with low values for mean or standard deviation and try the remaining attributes.Cronbach’s alpha tells us which attribute or item to delete to increase the reliability, and we also have analyzed the correlation among the class students while watching the same video lecture.We have collected data for at least ten students watching the same video using a webcam.Once the data is collected, we then have applied some correlation techniques to determine the class students’ behavior towards the same video lecture.This way, we can see the overall behavior of the class upon a specific video lecture.The study further reveals that subjective happiness is influenced by its efficiency, entertainment value, and effectiveness.Does the research offer an original emphasis on analyzing how does lack of sleep affect our brains?Sleep loss frameworks are minimal compared to the benefits of sleep.

Journal: Behavioural Neurology (2022)
Publication types: Research Article;
Customer Experience towards the Product during a Coronavirus Outbreak

Nowadays, sentimental analysis of consumers’ review is becoming much crucial in the marketing world.It is not just giving ideas to the firms that how consumers like their product or service, but it would also help them make their service better.In this article, the statistical method identifies the relationship of many factors in consumer feedback.It introduces a deep-based learning method called dsc (deep sentiment classifier) to determine whether or not to recommend the reviewed product thoroughly.Our suggested method also investigates the effect sizes of the feedback, such as positives, negatives, and neutrals.We used the women’s clothing review dataset containing 22,642 records after preprocessing of the results.Experimental studies show that the recommendations are an excellent positive sentiment indicator.In comparison, ratings become fuzzy performance metrics in product reviews.The 10-fold cross-validation analysis shows that the recommended form has the top f1 score (93.56%) in the sentimental classification on average and the recommended classification (88.32%) on average.A comparative description of other classifiers focused on machine learning, for example, knn, random forest, logistic regression, decision tree, support vector machine multilayer perceptron, and naïve bayes, also demonstrates that dsc gives the best possible result.We have tested dsc on the dataset imdb (internet video database), which includes the sentiment of the 50,000 movie reviews (25000 for training and 25000 for testing).In comparison to other baseline methods, dsc obtained an excellent classification score for this experiment.

Journal: Behavioural Neurology (2022)
Publication types: Research Article;
A Rapid Artificial Intelligence-Based Computer-Aided Diagnosis System for COVID-19 Classification from CT Images

The excessive number of covid-19 cases reported worldwide so far, supplemented by a high rate of false alarms in its diagnosis using the conventional polymerase chain reaction method, has led to an increased number of high-resolution computed tomography (ct) examinations conducted.The manual inspection of the latter, besides being slow, is susceptible to human errors, especially because of an uncanny resemblance between the ct scans of covid-19 and those of pneumonia, and therefore demands a proportional increase in the number of expert radiologists.Artificial intelligence-based computer-aided diagnosis of covid-19 using the ct scans has been recently coined, which has proven its effectiveness in terms of accuracy and computation time.In this work, a similar framework for classification of covid-19 using ct scans is proposed.The proposed method includes four core steps: (i) preparing a database of three different classes such as covid-19, pneumonia, and normal; (ii) modifying three pretrained deep learning models such as vgg16, res net50, and res net101 for the classification of covid-19-positive scans; (iii) proposing an activation function and improving the firefly algorithm for feature selection; and (iv) fusing optimal selected features using descending order serial approach and classifying using multiclass supervised learning algorithms.We demonstrate that once this method is performed on a publicly available dataset, this system attains an improved accuracy of 97.9% and the computational time is almost 34 (sec).

Journal: Behavioural Neurology (2021)
Publication types: Research Article;
Effects of Acupuncture and Rehabilitation Training on Limb Movement and Living Ability of Patients with Hemiplegia after Stroke

Stroke is a disease with a high disability rate, having a serious impact on that patient’s working and daily survival quality and bringing economic burden to the family and society.Patients with stroke hemiplegia are mostly tetraplegic and have difficulty regulating their balance, and their long-term symmetry has been destroyed.The application in the rehabilitation process of acupuncture in patients with hemorrhagic stroke may produce unexpected effects.It is very effective to study the effect of acupuncture combined with rehabilitation training on limb movement and patient survival.It is very helpful in improving normal motor function and normal life, increasing joint mobility and muscle strength, and reducing muscle tension.In this paper, it is found that the observational group has a complication rate of 2.13%, in contrast to 17.02% as in the group of control, and the pin-prick combined with a rehabilitative training makes a significant improvement to the patients.This study provides suggestions for the study to investigate acupuncture combined with recovery exercise on limb movement and living capacities of people with stroke paraparesis.

Journal: Behavioural Neurology (2022)
Publication types: Research Article;
Early Warning Model of Sports Injury Based on RBF Neural Network Algorithm

Sports injury is a common problem in athletes ’ training.The sports injury assessment model is a physical method to determine the sports injury attributes of specific parts by predicting and evaluating the risk of sports injury.In this paper, we use a neural network to realize big data analysis of sports injury data.Big data network is a method of capturing internet information by means of cloud computing, which is usually used in the construction of wan and lan.This paper analyzes the source of sports risk and the main injury factors, designs the sports injury estimation model based on big data analysis, establishes a new assessment model based on rbf neural network, and builds the big data network environment required for the model operation by improving the topological structure, combining big data and deep neural network.In the built environment, the risk assessment of sports injury can be completed by determining the risk source and identifying the risk factors.The realization of the model can be constrained by the uncertainty conditions so that it can achieve a good operation state.

Journal: Complexity (2021)
Publication types: Research Article;
Research on Complex Classification Algorithm of Breast Cancer Chip Based on SVM-RFE Gene Feature Screening

Screening and classification of characteristic genes is a complex classification problem, and the characteristic sequences of gene expression show high-dimensional characteristics.How to select an effective gene screening algorithm is the main problem to be solved by analyzing gene chips.The combination of knn, svm, and svm-rfe is selected to screen complex classification problems, and a new method to solve complex classification problems is provided.In the process of gene chip pretreatment, log fc and p value equivalents in the gene expression matrix are screened, and different gene features are screened, and then svm-rfe algorithm is used to sort and screen genes.Firstly, the characteristics of gene chips are analyzed and the number between probes and genes is counted.Clustering analysis among each sample and pca classification analysis of different samples are carried out.Secondly, the basic algorithms of svm and knn are tested, and the important indexes such as error rate and accuracy rate of the algorithms are tested to obtain the optimal parameters.Finally, the performance indexes of accuracy, precision, recall, and f1 of several complex classification algorithms are compared through the complex classification of svm, knn, knn-pca, svm-pca, svm-rfe-svm, and svm-rfe-knn at p = 0.01,0.05 , 0.001 .Svm-rfe-svm has the best classification effect and can be used as a gene chip classification algorithm to analyze the characteristics of genes.

Journal: Complexity (2020)
Publication types: Research Article;
Association between Elderly Sarcopenia and Inflammatory Cytokine Interleukin-17: A Cross-Sectional Study

Aging slows down the mechanisms behind skeletal muscle weakening and mobility.Increases in inflammation brought on by aging may contribute to some characteristics of sarcopenia.As a result of population aging worldwide, sarcopenia, an age‐related disease, has become a huge burden on both individuals and society as a whole.The study of the morbidity mechanism and available sarcopenia treatments has received more attention.The inflammatory response may be one of the most important methods behind the pathophysiology of sarcopenia in the aged, according to the background of the study.This anti‐inflammatory cytokine inhibits the ability of human monocytes and macrophages to induce inflammation as well as the production of cytokines like il‐6.Here, we investigate the association between sarcopenia and interleukin‐17 (il‐17), an inflammatory cytokine in the aged.There were 262 subjects aged 61‐90 years who were screened for sarcopenia in hainan general hospital.The subjects were divided into 45 males and 60 females aged 65‐79 years (average age: 72.00 ± 4.31 years).105 patients without sarcopenia were randomly selected among 157 participants.It included 50 males and 55 females, aged 61‐76 years (mean age: 69.10 ± 4.55 years) as per the standard definition of the asian working group for sarcopenia (awgs).The “skeletal muscle index” (smi), “hand grip strength” (hgs), “gait speed” (gs), “biochemical indexes,” “serum il‐17 level,” nutritional status, and past medical history of the two groups were evaluated and compared.Compared with the participants without sarcopenia, sarcopenia patients had higher average age; less physical exercise; lower total scores of bmi, pre‐alb, il‐17, and sppb; and a higher proportion of malnutrition risk (all p &lt; 0.05).By “roc curve analysis,” the best critical point was il‐17 in the growth of sarcopenia.The area that comes under roc (auroc) value was 0.627 (95% ci = 0.552, 0.702, p = 0.002).The ideal threshold value for il‐17 to estimate sarcopenia was 18.5 pg/m l.In the unadjusted model, il‐17 was considerably linked to sarcopenia (or = 1.123, 95% ci = 1.037‐1.215, p = 0.004).After the covariate adjustment observed in the complete adjustment model (or = 1.111, 95% ci = 1.004‐1.229, p = 0.002), this significance still exists.The results of this study suggest a strong relationship between sarcopenia and il‐17.This study will look at il‐17’s potential to serve as a key sarcopenia indicator.This trial is registered with chi ctr2200022590 .

Journal: BioMed Research International (2023)
Publication types: Research Article;
Significance of Edaravone Combined with Emotion Management Model in Promoting the Recovery Process and Improving Negative Psychology in Patients with Type 2 Diabetes Mellitus Combined with Stroke

And objective .To investigate the significance of edaravone (eda) combined with emotion management model in promoting the recovery process and improving negative psychology in patients with type 2 diabetes mellitus (t2dm) combined with cerebral stroke (cs).Methods .Eighty‐one patients with t2dm combined with cs who attended our hospital and received rehabilitation treatment from march 2020 to may 2021 were enrolled to a prospective nonrandomized controlled analysis.Among them, 46 patients received eda combined with emotional management model and were regarded as the observation group (og), and 35 received eda combined with conventional care and were seen as the control group (cg).The clinical efficacy and glycemic function of the two groups were compared, and the scores of the activities of daily living (adl), pittsburgh sleep quality index (psqi), and self‐assessment scale for anxiety and depression (sas and sds) were investigated before and after treatment.At the time of discharge, patient satisfaction with care was counted.Within six months after prognosis, t2dm self‐management behavior and cs self‐management behavior score surveys were conducted.Results .There was no difference in clinical efficacy between both groups ( p &gt; 0.05); the posttreatment glucose, psqi, sas, and sds scores were lower in the og than in the cg, while adl and emotional management scores were higher than in the cg ( p &lt; 0.05).In addition, both nursing satisfaction and prognosis disease self‐management behavior scores were also higher in the og than in the cg ( p &lt; 0.05).Conclusion .The eda combined with emotion management model can effectively promote the recovery process of patients with type ii t2dm combined with cs, while improving their negative psychology and enhancing their self‐management ability, which has high potential for clinical application.

Journal: BioMed Research International (2022)
Publication types: Clinical Study;
Beta-Sitosterol Facilitates GLUT4 Vesicle Fusion on the Plasma Membrane via the Activation of Rab/IRAP/Munc 18 Signaling Pathways in Diabetic Gastrocnemius Muscle of Adult Male Rats

Nutritional overload in the form of high‐fat and nonglycolysis sugar intake contributes towards the accelerated creation of reactive oxygen species (ros), hyperglycemia, and dyslipidemia.Glucose absorption and its subsequent oxidation processes in fat and muscle tissues alter as a consequence of these modifications.Insulin resistance (ir) caused glucose transporter 4 (glut4) translocation to encounter a challenge that manifested itself as changes in glycolytic pathways and insulin signaling.We previously found that beta ( β )‐sitosterol reduces ir in fat tissue via irs‐1/pi3k/akt facilitated signaling due to its hypolipidemic and hypoglycemic activity.The intention of this research was to see whether the phytosterol β ‐sitosterol can aid in the translocation of glut4 in rats fed on high‐fat diet (hfd) and sucrose by promoting rab/irap/munc 18 signaling molecules.The rats were labeled into four groups, namely control rats, hfd and sucrose‐induced diabetic control rats, hfd and sucrose‐induced diabetic rats given oral dose of 20 mg/kg body wt./day of β ‐sitosterol treatment for 30 days, and hfd and sucrose‐induced diabetic animals given oral administration of 50 mg/kg body wt./day metformin for 30 days.Diabetic rats administered with β ‐sitosterol and normalized the titers of blood glucose, serum insulin, serum testosterone, and the status of insulin tolerance and oral glucose tolerance.In comparison with the control group, β ‐sitosterol effectively regulated both glycolytic and gluconeogenesis enzymes.Furthermore, q rt‐pcr analysis of the m rna levels of key regulatory genes such as snap23, vamp‐2, syntaxin‐4, irap, vimentin, and sparc revealed that β ‐sitosterol significantly regulated the m rna levels of the above genes in diabetic gastrocnemius muscle.Protein expression analysis of rab10, irap, vimentin, and glut4 demonstrated that β ‐sitosterol had a positive effect on these proteins, resulting in effective glut4 translocation in skeletal muscle.According to the findings, β ‐sitosterol reduced hfd and sucrose‐induced ir and augmented glut4 translocation in gastrocnemius muscle through insulin signaling modulation via rab/irap/munc 18 and glucose metabolic enzymes.The present work is the first of its kind to show that β ‐sitosterol facilitates glut4 vesicle fusion on the plasma membrane via rab/irap/munc 18 signaling molecules in gastrocnemius muscle.

Journal: Bioinorganic Chemistry and Applications (2022)
Publication types: Research Article;
Assessing Deep Learning Techniques for the Recognition of Tropical Disease in Images from Parasitological Exams

Schistosoma mansoni is one of the tropical diseases with the greatest epidemic reach in the world.One of the who guidelines is the prior and efficient diagnosis for mapping foci and applying the appropriate treatment of infected people.The current process for diagnosis still depends on an analysis of parasitological exams performed by a human being under a laboratory microscope.The area of pattern recognition in images presents itself as a promising alternative to support and automate image‐based exams, and deep learning techniques have been successfully applied for this purpose.In order to automate this process, it is proposed in this work the application of deep learning methods for the detection of schistosomiasis eggs, and a comparison is made between two deep learning techniques, convolutional neural network (cnn) and structured pyramidal neural network (spnn).The results obtained in a real database indicate that the techniques are effective in the recognition of schistosomiasis eggs, in which both obtained auc (area under the curve) above 0.90, with the cnn showing superiority in this aspect.However, the spnn proved to be faster than the cnn.

Journal: Bioinorganic Chemistry and Applications (2022)
Publication types: Research Article;
Medical Multimedia Image Analysis of Scoliosis in Children Aged 3–7 Years Based on Adaptive Multiobjective Differential Evolution Algorithm

Scoliosis is mainly caused by the spinal column deviating from its centerline during the growth process.It usually occurs in children aged 3–7 years old.After a detailed analysis of the existing scoliosis detection methods, this paper compares and analyzes the advantages of using multimedia image processing technology to check scoliosis in children aged 3–7 years and uses an adaptive multiobjective differential evolution algorithm to perform scoliosis comprehensive testing.Finally, the experimental analysis shows that the adaptive multiobjective differential evolution algorithm is applied to scoliosis detection to analyze the characteristics of children's cervical spine curvature and the relationship between the cervical spine curvature and the scoliosis angle.

Journal: Advances in Multimedia (2021)
Publication types: Research Article;
Research on the Optimization of Agricultural Industry Structure Based on Genetic Algorithm

Due to the complexity and importance of optimizing and adjusting the crop planting structure in the jianghuai hilly tangba irrigation area between the upper reaches of the huaihe river from xinyang to the lower reaches of the huaihe river in china, and based on experimental results from the feidong badou irrigation experiment station, the farmland was modeled using rainfall and runoff data from the tangba irrigation area.By examining the water balance of submerged irrigation, an optimization model of the agricultural industry structure was developed using genetic algorithms, and the model was solved using an accelerated genetic algorithm.Developing the research findings may provide scientific and technological support for adjusting the planting structure and formulation of irrigation systems in the jianghuai hills and tangba irrigation area between the upper reaches of the huaihe river and xinyang, as well as significant practical guiding significance and application value.

Journal: Advances in Meteorology (2022)
Publication types: Research Article;