syedzayyan/paper_mill_benchmark huggingface dataset:
Innovative Application of Nano-Organic Photochromic New Materials in Hakka Traditional Decorative Pattern Design

Hakka traditional decorative patterns are the epitome of local life and production customs, politics and economy, culture and art and other history and culture.The themes of hakka traditional decorative patterns come from the real world or the imaginary world, expressing the expectation and beautiful vision of life.At the same time, it is also the essence of artists accumulated through life in the past dynasties, which has a certain impact on the integration of modern art design and traditional culture.Photochromic materials have the characteristics of reversible color change under the action of light.They have relevant applications in many fields, such as architecture, currency anti-counterfeiting, clothing decoration and so on.Firstly, this paper briefly expounds the hakka traditional culture.According to the introduction of hakka traditional culture, this paper leads to the design of hakka traditional decorative patterns based on hakka traditional culture, and discusses the decorative technology, decorative parts, application scope and development history of hakka traditional decorative patterns.Secondly, this paper briefly summarizes the photochromic materials, and leads to the category, principle and mechanism of organic photochromic materials.In this paper, electrospinning technology is introduced, and relevant experiments are designed.The results show that the composites with mape have better flexural, compressive and impact strength when the length of carbon nanofibers changes consistently.In the bending performance comparison experiment, the experimental data show that the lowest value of the group with mape is 15mpa higher than the highest value without mape.In the comparative test of compressive properties, the experimental data show that there is a difference of 30mpa between the composites with mape and those without mape.Moreover, when the length of carbon nanofibers is 40um, the overall performance of the composites is the best.This paper takes the design of hakka traditional architectural decoration pattern with nano organic photochromic new materials as an experiment.Experiments show that nano organic photochromic new materials have better properties than traditional building materials in flexural modulus, compressive modulus and thermal stability.

Journal: Advances in Materials Science and Engineering (2022)
Publication types: Research Article;
Predicting the Spread of Vessels in Initial Stage Cervical Cancer through Radiomics Strategy Based on Deep Learning Approach

Novel methods and materials are used in healthcare applications for finding cancer in various parts of the human system.To select the most suitable therapy plan for individuals with domestically progressed cervical cancer, robustness metrics are required to estimate their early phase.The goal of the research is to increase the effectiveness of cervical cancer patients' detection by using deep learning-based radiomics assessment of magnetic resonance imaging (mri).From march 2016 to november 2019, 125 patients with early-stage cervical cancer provided 980 dynamic x1 contrast-enhanced (x1dce) and 850 x2 weighted imaging (x2wi) mri images for training and testing.A convolutional neural network model was used to estimate cervical cancer state based on the specified characteristics.The x1dce exhibited high discriminative outcomes than x2wi mri in terms of prediction ability, as calculated by the confusion matrix assessment and receiver operating characteristic (roc) curve approach.The mean maximum region under the curve of 0.95 was found using an attentive ensemble learning method that included both mri sequencing (sensitivity = 0.94, specificity = 0.94, and accuracy = 0.96).Whenever compared with conventional radiomic approaches, the results show that a variety of radiomics based on deep learning might be created to help radiologists anticipate vascular invasion in patients with cervical cancer before surgery.Based on radiomics technique, it has proven to be an effective tool for estimating cervical cancer in its early stages.It would help people choose the best therapy method for them and make medical judgments.

Journal: Advances in Materials Science and Engineering (2022)
Publication types: Research Article;
Using Convolutional Neural Networks for Segmentation of Multiple Sclerosis Lesions in 3D Magnetic Resonance Imaging

Magnetic resonance imaging to detect its lesions is used to diagnose multiple sclerosis.Experts usually perform this detection process manually, but there is interest in automating it to speed up the diagnosis and monitoring of this disease.A variety of automatic image segmentation methods have been proposed to quickly detect these lesions.A gaussian mixture model is first constructed to identify outliers in each image.Then, using a set of rules based on expert knowledge of multiple sclerosis lesions, those outliers of the model that do not match the lesions' characteristics are discarded.Furthermore, segmented lesions usually correspond to gray matter-rich brain regions.In some cases, false positives can be detected, but the rules used cannot eliminate all errors without jeopardizing the segmentation’s quality.The second method involves training a convolutional neural network (cnn) that can segment lesions based on a set of training images.This technique can learn a set of filters that, when applied to small sections of an image called “patches,” produce a set of characteristics that can be used to classify each voxel of the image as a lesion or healthy tissue.On the other hand, the results show that the networks are capable of producing results in the worked database comparable to those produced by the algorithms in the literature.

Journal: Advances in Materials Science and Engineering (2022)
Publication types: Research Article;
Application of Digital Painting Technology in the Creation of an Oil Painting Containing Graphene

Art and science and technology are two different ways people understand and reflect the objective world.The mutual penetration of science, technology, and art has promoted the development of art and the innovation of forms.Technology has become the carrier of social and cultural exchanges and spiritual world exchanges for artists, providing new ideas for modern art.In recent years, with the active development of various new media technologies, new media technologies represented by image technology and digital technology have gradually developed and are closely integrated with various fields.With the development and progress of image and digital technology, digital painting technology has had a great impact on the field of artistic creation.Of course, oil painting creation in the field of art has also encountered unprecedented challenges.This article introduces various functional methods in digital painting technology, and also introduces the preparation method of graphene graphite for printing.And through experiments, graphite with good performance was prepared, which showed that when ethylene glycol was used as a solvent and the mass fraction of graphene was 37.5%, the performance of the ink was relatively best.Finally, this paper designs a digital painting system and compares it with ordinary digital painting systems.It is concluded that the average satisfaction of painters in the designed system is 1.5 points higher than that of ordinary ones.These data show that the application of digital painting technology in the creation of graphene oil paintings has better applications than ordinary digital painting systems.

Journal: Advances in Materials Science and Engineering (2022)
Publication types: Research Article;
ECG Signal Detection and Classification of Heart Rhythm Diseases Based on ResNet and LSTM

Arrhythmia is one of the most threatening diseases in all kinds of cardiovascular diseases.It is important to achieve efficient and accurate automatic detection of arrhythmias for clinical diagnosis and treatment of cardiovascular diseases.Based on previous research on electrocardiogram (ecg) automatic detection and classification algorithm, this paper uses the res net34 network to learn the morphological characteristics of ecg signals and get the significant information of signals, then passes into a three-layer stacked long-term and short-term memory network to get the context dependency of the features.Finally, four classification tasks are implemented on the physio net challenge 2017 test dataset by using the softmax function.The activation function is changed from the re lu function to the mish function in this model.Negative information of ecg signals is considered in the training process, which makes the model have more stable and accurate classification ability.In addition, this paper calculates and compares the average information entropy of correctly classified samples and incorrectly classified samples in the test set.Moreover, it eliminates the impact of obvious signal abnormalities (redundancy or loss) on the model classification results, to more comprehensively and accurately explain the classification effect and performance of the model.After eliminating the possibility of abnormal signal, the res net34-lstm3 model obtained an average f 1 score of 0.861 and an average area under the receiver operating characteristic curve (roc) of 0.972 on the test dataset, which indicates that the model can effectively extract the characteristics of ecg signals and diagnose arrhythmia diseases.Comparing the results of the res net34 model and res net-18 model on the same test dataset, we can see that the improved model in this paper has a better classification and recognition effect on ecg signals as a whole, which can identify atrial fibrillation diseases more effectively.

Journal: Advances in Mathematical Physics (2021)
Publication types: Research Article;
Relationship between Peripheral Blood miR-181c, miR-101, and Cognitive Impairment in Patients with Diabetes Mellitus Complicated with Acute Stroke

S.To explore the relationship between peripheral blood micro rna-181c (mi r-181c), micro rna-101 (mi r-101), and cognitive impairment (ci) in patients with diabetes mellitus (dm) complicated with acute stroke (as).Methods.A retrospective analysis was performed on 70 patients with dm complicated with as admitted to the hospital between january 2019 and december 2021.According to presence or absence of ci, they were divided into ci group (41 cases) and non-ci group (29 cases).The clinical characteristics and general data (blood glucose and blood lipid) of patients were statistically analyzed.The relative expression levels of mi r-181c and mi r-101 in peripheral blood were detected by real-time fluorescence quantitative pcr.The risk factors of ci were analyzed by logistic regression analysis.The diagnostic value of peripheral blood mi r-181c and mi r-101 for ci was evaluated by receiver operating characteristic (roc) curves.Results.The relative expression levels of peripheral blood mi r-181c and mi r-101 in the ci group were lower than those in the non-ci group ( p &lt; 0.05 ).The occurrence of ci was related to age, course of dm, as location, time from onset to admission, hb a1c, tg, ua, and hcy levels ( p &lt; 0.05 ).Logistic regression analysis showed that age, as location, hb a1c, mi r-181c, and mi r-101 were related influencing factors of ci in patients with dm complicated with as ( p &lt; 0.05 ).The results of roc curves analysis showed that auc, sensitivity, and specificity of mi r-181c combined with mi r-101 for predicting ci were 0.865, 73.17%, and 89.66%, respectively ( p &lt; 0.05 ).Conclusions.The peripheral blood mi r-181c and mi r-101 are low expressed in patients with dm complicated with as, and advanced age, intracortical as lesions, increased hb a1c, and low expression of mi r-181c and mi r-101 are all independent risk factors for ci in patients with dm complicated with as.Besides, the combined detection of mi r-181c and mi r-101 expression has a good diagnostic value for ci.

Journal: Emergency Medicine International (2022)
Publication types: Research Article;
The Role of TAMs in Tumor Microenvironment and New Research Progress

Tumor-associated macrophages (tams) are an important part of tumor microenvironment (tme) and play a key role in tme, participating in the process of tumor occurrence, growth, invasion, and metastasis.Among them, metastasis to tumor tissue is the key step of malignant development of tumor.In this paper, the latest progress in the role of tams in the formation of tumor microenvironment is summarized.It is particularly noteworthy that cell and animal experiments show that tams can provide a favorable microenvironment for the occurrence and development of tumors.At the same time, clinical pathological experiments show that the accumulation of tams in tumor is related to poor clinical efficacy.Finally, this paper discusses the feasibility of tams-targeted therapy as a new indirect cancer therapy.This paper provides a theoretical basis for finding a potentially effective macrophage-targeted tumor therapy.

Journal: Stem Cells International (2022)
Publication types: Research Article;
Multiobject Detection Algorithm Based on Adaptive Default Box Mechanism

Multiobject detection tasks in complex scenes have become an important research topic, which is the basis of other computer vision tasks.Considering the defects of the traditional single shot multibox detector (ssd) algorithm, such as poor small object detection effect, reliance on manual setting for default box generation, and insufficient semantic information of the low detection layer, the detection effect in complex scenes was not ideal.Aiming at the shortcomings of the ssd algorithm, an improved algorithm based on the adaptive default box mechanism (adb) is proposed.The algorithm introduces the adaptive default box mechanism, which can improve the imbalance of positive and negative samples and avoid manually set default box super parameters.Experimental results show that, compared with the traditional ssd algorithm, the improved algorithm has a better detection effect and higher accuracy in complex scenes.

Journal: Complexity (2020)
Publication types: Research Article;
Application of the Stratified Nursing Mode of the Prediction Model Constructed Based on Case System Data in the Nursing of Patients with Acute Renal Failure

To explore the application of the stratified nursing mode of the prediction model constructed based on case system data in the nursing of patients with acute renal failure (arf).Methods.A total of 84 patients with arf confirmed in the hospital were enrolled between february 2020 and february 2022.According to the simple random grouping method, they were divided into an observation group and a control group, 42 cases in each group.The control group was given routine nursing while the observation group was given stratified nursing of the prediction model constructed based on case system data.All were nursed for 2 months.Results.There was no significant difference in general data such as gender, age, body mass index (bmi), serum creatinine (scr), hemoglobin (hb), and albumin between the two groups ( p &gt; 0.05 ).Age &gt;60 years, weight fluctuation &gt;2 kg during dialysis, vascular blockage or infection, coronary heart disease, diabetes mellitus, chronic hepatopathy and stroke, bleeding tendency, and neuromuscular abnormalities were high-risk factors for arf patients, hypertension, thyroid abnormalities, hyperlipidemia, persistent or repeated blood volume overload, and usage of antihypertensive drugs were moderate-risk factors for arf patients, and nonpermeability dehydration was a low-risk factor of arf patients.The scores of nursing satisfaction and treatment compliance in the observation group were significantly higher than those in the control group ( p &lt; 0.05 ).After 2 months of nursing, scores of sas, sds, and spbs in both the groups were significantly decreased ( p &lt; 0.05 ), which were significantly lower in the observation group than those in the control group ( p &lt; 0.05 ).Conclusion.The stratified nursing mode of the prediction model constructed based on case system data is conducive to timely and targeted nursing, with high patient satisfaction and cooperation, and a better psychological state.

Journal: Emergency Medicine International (2022)
Publication types: Research Article;
Analysis of the Impact of Big Data on E-Commerce in Cloud Computing Environment

This article starts with the analysis of the existing electronic commerce system, summarizes its characteristics, and analyzes and solves its existing problems.Firstly, the characteristics of the relational database my structured query language (my sql) and the distributed database hbase are analyzed, their respective advantages and disadvantages are summarized, and the advantages and disadvantages of each are taken into account when storing data.My sql is used to store structured business data in the system, while hbase is used to store unstructured data such as pictures.These two storage mechanisms together constitute a data storage subsystem.Secondly, considering the large amount of data in the e‐commerce system and the complex calculation of the data mining algorithm, this paper uses map reduce to realize the parallelization of the data mining algorithm and builds a hadoop‐based commodity recommendation subsystem on this basis.We use java ee technology to design a full‐featured web mall system.Finally, based on the impact of cloud computing, mobile e‐commerce is analyzed, including relevant theories, service mode, architecture, core technology, and the application in e‐commerce, which can realize e‐commerce precision marketing, find the optimal path of logistics, and take effective security measures to avoid transaction risks.This method can avoid the disadvantages of the traditional e‐commerce, where large‐scale data cannot be processed in a timely manner, realize the value of mining data behind, and realize the precision marketing of e‐commerce enterprises.

Journal: Complexity (2021)
Publication types: Research Article;
MFG-E8 Exerts Neuroprotection in Neural Stem Cells Induced by Anesthetic Sevoflurane via Regulating the PI3K/AKT Pathways

Mfg-e8 has shown tissue protection effects in various models of organ injury.In this study, the function of mfg-e8 in sev-induced neural stem cells (nscs) was studied.The cell viability and apoptosis affected by rh mfg-e8 were tested by mtt and flow cytometry analysis, respectively.Then, the m rna expression of mfg-e8 was detected by q rt-pcr.The expression of sod, gsf-px, and mda was assessed using elisa assay.Western blot analysis was applied for assessing the expression of mfg-e8, bcl2, bax, cleaved caspase-3, grp-78, xbp-1, atf-6, atf-4, chop, p-pi3k, pi3k, p-akt, and akt.The pharmacological experiments suggested that both m rna and protein expression of mfg-e8 were significantly decreased after 24 h, 48 h, and 72 h treatment with sev, and the western blot results displayed that 50 and 100 μg/ml rh mfg-e8 could evidently promote the expression of mfg-e8 in nscs induced by sev.Next, rh mfg-e8 reduced the apoptosis of nscs induced by sev through upregulating bcl-2 and cleaved caspase-3 and downregulating bax.Moreover, rh mfg-e8 alleviated the endoplasmic reticulum pressure of nscs induced by sev through decreasing the expression of grp-78, xbp-1, atf-6, atf-4, and chop.In addition, the rh mfg-e8 could promote the expression of sod and gsh-px and inhibit the expression of mda and ldh detected by the elisa assay and ldh kit.Moreover, rh mfg-e8 elevated the expression of p-pi3k/pi3k and p-akt/akt, which were inhibited by sev in nscs.The results of this project supported that rh mfg-e8 protects neural activity in neural stem cells induced by anesthetic sevoflurane via regulating the pi3k/akt pathways.

Journal: Stem Cells International (2022)
Publication types: Research Article;
Experimental Study on Mineral Solid Waste Green Grouting Material Based on Electromagnetic Characteristic Detection

The production processes for the gypsum‐ and cement‐based materials, which are widely used in civil engineering projects, require the consumption of large amounts of energy and natural resources.At the present time, the main development directions of civil engineering material include realizing solid waste recycling and the applications of green building materials, which can be then used in the fields of disaster treatment and ecological restoration, such as grouting materials.In addition, the grouting quality is always difficult to detect.This study examined the gypsum‐ and cement‐based green grouting materials made from mineral solid waste used in disaster and cloud detection by means of electromagnetic characteristics.According to the requirements of electrical testing of grouting quality, first we designed a material made with solid waste.Then, we studied the resistivity, strength, porosity, and other physical and mechanical properties of the material.The test results of the material and its soaking solution indicate that this material is a green material meeting the environmental safety standards.The experimental results show that the rapid detection of grouting quality can be realized.The following effects on electromagnetic characteristics and mechanical properties of the green materials of gypsum‐ and cement‐based were analyzed.The results showed that the resistivity and strength were related to the ratios of the water content to the modified phosphogypsum; the percentages of cement content in the total amount of modified phosphogypsum and marble powder; the percentages of marble powder in the modified phosphogypsum; the percentages of steel fiber content in the phosphogypsum; and the fineness of the marble powder.The field test results also confirm that the green grouting material can be effectively applied in engineering repair imaging monitoring.

Journal: Advances in Civil Engineering (2022)
Publication types: Research Article;
Determination of Adsorption of Methylene Blue Dye by Incense Stick Ash Waste and Its Toxicity on RTG-2 Cells

Incense stick ash (isa) has traces of toxic heavy metals which have an adverse effect on the environment.Every year, tonnes of isa are disposed of in rivers and other water bodies which leads to water pollution and affects the natural water resources.Isa has several value-added minerals which could be modified or functionalized for environmental cleanup.Here, in the current research work, isa was transformed into a flower-like noble porous material by mixing isa and na oh in a 1 : 1 ratio followed by calcination at 600°c for six hours in a muffle furnace.The developed material was analyzed by sophisticated instruments for the identification of the properties.The microscopic techniques revealed the micron-sized flower-like structure, while the xrd showed peaks at 30–33° which indicates the transformation of the calcite and silicate phases into new-phase mineral.Ftir also revealed bands in regions of 500–1200 cm −1 and new bands near 450 cm −1 .Eds confirmed the presence of na in the sintered product and the transformation of the isa.Finally, the sintered product potential was assayed for the removal of methylene blue dye from wastewater using an adsorption mechanism.The removal efficiency of dye reached up to 70% within one hour only.It was found that the isa sintered product has the potential to remove mb dye efficiently from wastewater and also reduce solid waste pollution.Microculture tetrazolium assay (mtt) and lactate dehydrogenase (ldh) assays were performed to evaluate the cytotoxicity of the sintered incense stick ash product on rtg-2 cells.The sintered incense stick ash product induced cytotoxicity on rtg-2 cells in a dose-dependent manner.Sintered isa products have the potential to remove methylene blue dye efficiently from wastewater and reduce solid waste pollution.

Journal: Adsorption Science & Technology (2022)
Publication types: Research Article;