bluuebunny/crossref_metadata_2025 huggingface dataset:
XNAS: A Regressive/Progressive NAS for Deep Learning
Authors: Kung S. Y.
Published: June 2022

Deep learning has achieved great and broad breakthroughs in many real-world applications. In particular, the task of training the network parameters has been masterly handled by back-propagation learning. However, the pursuit on optimal network structures remains largely an art of trial and error. This prompts some urgency to explore an architecture engineering process, collectively known as Neural Architecture Search (NAS). In general, NAS is a design software system for automating the search of effective neural architecture. This article proposes an X-learning NAS (XNAS) to automatically train a network’s structure and parameters. Our theoretical footing is built upon the subspace and correlation analyses between the input layer, hidden layer, and output layer. The design strategy hinges upon the underlying principle that the network should be coerced to learn how to structurally improvethe input/output correlation successively (i.e., layer by layer). It embraces both Progressive NAS (PNAS) and Regressive NAS (RNAS). For unsupervised RNAS, Principal Component Analysis (PCA) is a classic tool for subspace analyses. By further incorporating teacher’s guidance, PCA can be extended to Regression Component Analysis (RCA) to facilitate supervised NAS design. This allows the machine to extract components most critical to the targeted learning objective. We shall further extend the subspace analysis from multi-layer perceptrons to convolutional neural networks, via introduction of Convolutional-PCA (CPCA) or, more simply, Deep-PCA (DPCA). The supervised variant of DPCA will be named
Deep-RCA
(DRCA). The subspace analyses allow us to compute optimal eigenvectors (respectively, eigen-filters) and principal components (respectively, eigen-channels) for optimal NAS design of multi-layer perceptrons (respectively, convolutional neural networks). Based on the theoretical analysis, an
X-learning
paradigm is developed to jointly learn the structure and parameters of learning models. The objective is to reduce the network complexity while retaining (and sometimes improving) the performance. With carefully pre-selected baseline models, X-learning has shown great successes in numerous classification-type and/or regression-type applications. We have applied X-learning to the ImageNet datasets for classification and DIV2K for image enhancements. By applying X-learning to two types of baseline models, MobileNet and ResNet, both the low-power and high-performance application categories can be supported. Our simulations confirm that X-learning is by and large very competitive relative to the state-of-the-art approaches.
Babies, Bugs, and Barriers: Dietary Modulation of Intestinal Barrier Function in Early Life
Authors: Wells Jerry M. , Gao Yifan , de Groot Nanda , Vonk Marlotte M. , Ulfman Laurien , van Neerven R.J. Joost
Published: June 2022

The intestinal barrier is essential in early life to prevent infection, inflammation, and food allergies. It consists of microbiota, a mucus layer, an epithelial layer, and the immune system. Microbial metabolites, the mucus, antimicrobial peptides, and secretory immunoglobulin A (sIgA) protect the intestinal mucosa against infection. The complex interplay between these functionalities of the intestinal barrier is crucial in early life by supporting homeostasis, development of the intestinal immune system, and long-term gut health. Exclusive breastfeeding is highly recommended during the first 6 months. When breastfeeding is not possible, milk-based infant formulas are a safe alternative. Breast milk contains many bioactive components that help to establish the intestinal microbiota and influence the development of the intestinal epithelium and the immune system. Importantly, breastfeeding lowers the risk for intestinal and respiratory tract infections. Here we review all aspects of intestinal barrier function and the nutritional components that impact its functionality in early life, such asmicronutrients, bioactive milk proteins, milk lipids, and human milk oligosaccharides. These components are present in breast milk and can be added to milk-based infant formulas to support gut health and immunity.
The Effect of Mild Renal Dysfunction on the Assessment of Plasma Amino Acid Concentration and Insulin Resistance in Patients with Type 2 Diabetes Mellitus
Authors: Ikeda Hideki
Published: June 2022

Background. An increase in the levels of branched-chain amino acids (BCAAs) and certain aromatic amino acids, such as alanine, in plasma is correlated with insulin resistance (IR) in type 2 diabetes mellitus (T2DM). T2DM is a leading risk factor for chronic kidney disease. Meanwhile, renal dysfunction causes changes in plasma amino acid levels. To date, no study has examined how mild renal dysfunction and IR interact with plasma amino acid levels. This study examines the effects of IR and renal dysfunction on plasma amino acid concentrations in T2DM. Methods. Data were collected from healthy male participants (controls) and male patients with T2DM between May 2018 and February 2022. Blood samples were collected after overnight fasting. IR and renal function were evaluated using the homeostasis model assessment of IR (HOMA-IR) and serum cystatin C (CysC), respectively. Results. A total of 49 and 93 participants were included in the control and T2DM groups, respectively. In the T2DM group, eight amino acids (alanine, glutamic acid, glutamine, glycine, isoleucine, leucine, tyrosine, and valine) and total BCAA showed a significant correlation with HOMA-IR (

p
<
0.01

), whereas six amino acids (γ-aminobutyric acid, citrulline, cysteine, glycine, methionine, and valine) and total BCAA showed a significant correlation with 1/CysC (

p
<
0.02

). However, only alanine, glutamic acid, and each BCAA showed significant differences between the control group and the IR T2DM subgroup. Increases in the BCAA levels with T2DM were canceled by renal dysfunction (

CysC
≥
0.93

) in patients with intermediate IR. Conclusion. To use plasma BCAA concentration as a marker of IR, renal function must be considered, even in mild renal dysfunction. Increased alanine and glutamic acid levels indicate IR, regardless of mild renal dysfunction.
Sulfhydryl Functionalized Magnetic Chitosan as an Efficient Adsorbent for High-Performance Removal of Cd(II) from Water: Adsorption Isotherms, Kinetic, and Reusability Studies
Authors: Algethami Jari S. , Alqadami Ayoub Abdullah , Melhi Saad , Alhamami Mohsen A. M. , Fallatah Ahmed M. , Rizk Moustafa A.
Published: June 2022

In this study, dimercaptosuccinic acid-functionalized magnetic chitosan (Fe3O4@CS@DMSA) was synthesized via in situ coprecipitation process and amidation reaction, aiming to eliminate cadmium (Cd(II)) ions from an aqueous environment. The structure, morphology, and particle size of the Fe3O4@CS@DMSA adsorbent were investigated using FTIR, TEM, EDX, TGA, zeta potential, and XRD techniques, and the obtained results approved the successful synthesis of the Fe3O4@CS@DMSA nanocomposite. The influence of external adsorption conditions such as pH solution, adsorbent mass, initial Cd(II) concentration, temperature, and contact time on the adsorption process was successfully achieved. Accordingly, pH: 7.6, contact time: 210 min, and adsorbent mass:10 mg were found to be the optimal conditions for best removal. The adsorption was analyzed using nonlinear isotherm and kinetic models. The outcomes revealed that the adsorption process obeyed the Langmuir and the pseudo-first-order models. The maximum adsorption capacity of Fe3O4@CS@DMSA toward Cd(II) ion was 314.12 mg/g. The adsorption mechanism of Cd(II) on Fe3O4@CS@DMSA nanocomposite is the electrostatic interaction. The reusability test of Fe3O4@CS@DMSA nanocomposite exhibited that the adsorption efficiency was 72% after the 5th cycle. Finally, this research indicates that the Fe3O4@CS@DMSA exhibited excellent characteristics such as high adsorption capacity, effective adsorption-desorption results, and easy magnetic separation and thus could be an effective adsorbent for removing Cd(II) ions from aqueous solutions.
Value of 4D CT Angiography Combined with Whole Brain CT Perfusion Imaging Feature Analysis under Deep Learning in Imaging Examination of Acute Ischemic Stroke
Authors: Tao Jingshan , Cai Yong , Dai Yisheng , Xie Yingdi , Liu Hailing , Zang Xiaojin
Published: June 2022

This study was aimed at investigating the application of deep learning 4D computed tomography angiography (CTA) combined with whole brain CT perfusion (CTP) imaging in acute ischemic stroke (AIS). A total of 46 patients with ischemic stroke were selected from the hospital as the research objects. Image quality was analyzed after the 4D CTA images were obtained by perfusion imaging. The results showed that whole brain perfusion imaging based on FCN can achieve automatic segmentation. FCN segmentation results took a short time, an average of 2-3 seconds, and the Dice similarity coefficient (DSC) and mean absolute distance (MAD) were lower than those of other algorithms. FCN segmentation distance was 17.87. The parameters of the central area, the peripheral area, and the mirror area of the perfusion map were compared, and the mean transit time (MTT) and time to peak (TTP) of the lesion were prolonged compared with the mirror area. Moreover, the peripheral CBV was increased, and the differences between the parameters were significant (

P
<
0.05

). In conclusion, using the deep learning FCN network, 4D CTA combined with whole brain CTP imaging technology can effectively analyze the perfusion state and achieve clinically personalized treatment.
UTP14A, DKC1, DDX10, PinX1, and ESF1 Modulate Cardiac Angiogenesis Leading to Obesity-Induced Cardiac Injury
Authors: Pan Xiaoyu , Chen Shuchun , Chen Xing , Ren Qingjuan , Yue Lin , Niu Shu , Li Zelin , Zhu Ruiyi , Chen Xiaoyi , Jia Zhuoya , Zhen Ruoxi , Ban Jiangli
Published: June 2022

Background. This study is aimed at exploring the key genes and the possible mechanism of heart damage caused by obesity. Methods. We analyzed the GSE98226 dataset. Firstly, differentially expressed genes (DEGs) were identified in heart tissues of obese and normal mice. Then, we analyzed DEGs using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Thirdly, we constructed a protein-protein interaction (PPI) network and key modules and searched hub genes. Finally, we observed the pathological changes associated with obesity through histopathology. Results. A total of 763 DEGs were discovered, including 629 upregulated and 134 downregulated genes. GO enrichment analysis showed that these DEGs were mainly related to the regulation of transcription, DNA-templated, nucleic acid binding, and metal ion binding. KEGG pathway analysis revealed that the DEGs were enriched in long-term depression, gap junction, and sphingolipid signaling pathways. Finally, we identified UTP14A, DKC1, DDX10, PinX1, and ESF1 as the hub genes. Histopathologic analysis showed that obesity increased the number of collagen fibers and decreased the number of microvessels and proliferation of the endothelium and increased endothelial cell damage which further leads to dysfunction of cardiac microcirculation. Conclusion. UTP14A, DKC1, DDX10, PinX1, and ESF1 have been identified as hub genes in obesity-induced pathological changes in the heart and may be involved in obesity-induced cardiac injury by affecting cardiac microcirculatory function.
[Retracted] A Spatial Spectrum Estimation Method for Optimization and Improvement of Resource Allocation and Management of Public Sport and Health Facilities
Authors: Sun Yongsheng
Published: June 2022

With the improvement of people’s health awareness, the state increases the construction of public sport facilities, which complicates the allocation and management of resources. The existing spatial spectrum estimation method cannot eliminate the relevant interference data, resulting in duplicate data in the results of resource allocation and management, reducing the accuracy of resource allocation and management. In order to optimize the allocation and management of public sport facilities resources, this study proposes a spatial spectrum estimation method, which is used to deeply tap the potential information in public sport facilities resources and optimize the allocation and management. First, analyze the resources of public sport facilities and put forward the feature vector of allocation and management optimization. Then, use the spatial spectrum estimation method to learn the test samples, get the optimal threshold and weight, and build the resource allocation and management model of public sport facilities. Finally, the accuracy of spatial spectrum estimation method is 98% and the variation range is (0, 10), which is better than the accuracy of the original algorithm is 80% and the variation range is (0, 20). Moreover, change of the spatial spectrum estimation method is smoother, and the correlation between various analyses is better. In unit time, the amount of configuration and management data of spatial spectrum estimation method is higher than that of existing algorithms, which indirectly indicate that the configuration and management time of the spatial spectrum estimation method is short. At the same time, unstructured data account for a large proportion of the data tested this time. Therefore, the accuracy and variation range of the spatial spectrum estimation method is good, which is suitable for the construction of public sport facilities and realizes the optimization of resource allocation and management.
Numerical Investigation of the Nonlinear Coupled Fractional Massive Thirring Equation Using Two‐Scale Approach
Authors: Liu Jinxing , Nadeem Muhammad , Habib Mustafa , Karim Shazia , Or Roshid Harun
Published: June 2022

In this paper, we investigate the numerical solution of the coupled fractional massive Thirring equation with the aid of He’s fractional complex transform (FCT). This study plays a significant aspect in the field of quantum physics, weakly nonlinear thrilling waves, and nonlinear optics. The main advantage of FCT is that it converts the fractional differential equation into its traditional parts and is also capable to handle the fractional order, whereas the homotopy perturbation method (HPM) is employed to tackle the nonlinear terms in the coupled fractional massive Thirring equation. An example is illustrated to present the efficiency and validity of the two‐scale theory. The solutions are obtained in the form of series with simple and easy computations which confirm that the present approach is good in agreement and is easy to implement for such type of complex systems in science and engineering.
Effects of Lactobacillus plantarum P9 Probiotics on Defecation and Quality of Life of Individuals with Chronic Constipation: Protocol for a Randomized, Double-Blind, Placebo-Controlled Clinical Trial
Authors: Liu Wenjun , Lu Nong-Hua , Zhou Xu , Li Yingmeng , Xie Yong , Zheng Longjin , Zhu Weifeng , Xiao Qiuping , Yang Ni , Zuo Kexuan , Wu Qingni , Xu Tielong , Zhang Heping
Published: June 2022

Background. Although probiotics have been shown to improve constipation-related symptoms, a clear consensus on the use of probiotics as a constipation-relieving agent has not been reached, which is attributed to the limited available evidence and inconsistent protocols used in existing studies. Method. A randomized, double-blind, placebo-controlled clinical trial is designed to study the efficiency and possible mechanism of action of probiotics for chronic constipation, in which 200 eligible volunteers with chronic constipation will be randomly assigned to a probiotic group (oral Lactobacillus plantarum P9 probiotic powder, 100 billion colony-forming units (CFUs)/day) or a placebo group. Volunteers, treatment distributors, data collectors, and data analysts will be blinded. The primary outcome is the weekly mean frequency of complete spontaneous bowel movements (CSBMs), and secondary outcomes include weekly mean frequency of CSBMs ≥3, weekly mean frequency of spontaneous bowel movements (SBMs), weekly mean stool appearance score, weekly mean difficulty of passing stool score, weekly percentage of volunteers who use auxiliary measures to assist with defecation (WPUAMA), quality-of-life (QOL) score, emotional status score, gut microbiome, and faecal metabolome. Each outcome measure will be assessed at the time points of preadministration (day 0), administration (day 14 and/or 28), and postadministration (day 42) to identify inter- and intragroup differences. Adverse events will be recorded to evaluate the safety of L. plantarum P9. Discussion. The protocol will provide methodological guidance for other similar studies, avoiding methodological bias and ultimately facilitating the formulation of consensus on the use of probiotics as a constipation-relieving agent. In addition, the results are more comprehensive than those of existing studies and may objectively and scientifically reflect the effectiveness of L. plantarum P9 on constipation. If the expected study findings are obtained, L. plantarum P9, taken as a probiotic, may become a complementary choice for chronically constipated patients. This trial is registered with Chinese Clinical Trial Registry (ChiCTR) (no. ChiCTR2000038396) registered on November 22, 2020, https://www.chictr.org.cn/showproj.aspx?proj=54024.
Optimization of River Sand with Spent Garnet Sand in Concrete Using RSM and R Programming Packages
Authors: Murugadoss Jayaraju Raja , Balasubramaniam Nachimuthu , Gokulan Ravindiran , Rajesh Kanta Naga , Sreelal Gurusamy Pandian , Sudam Pupalwad Arti , Rahman Dhaleelur Rahman Zunaithur , Ali Razack Nasar
Published: June 2022

The main ingredients of concrete are derived from natural resources such as cement, sand, and coarse aggregate. Rapid urbanization leads to the high demand for concrete causing depletion of natural deposits of sand. In this study, the optimized quantities of sand with spent garnet sand are compared in Design Expert’s Response Surface Method and R Programming’s RStudio packages in terms of predicted and actual compressive and flexural strength at 28 days of curing. Optimization of sand with spent garnet sand at various percentages such as 20, 40, 60, and 80 is proposed. The findings revealed that the correlation coefficient (R2) of 28 days compressive strength is 0.976 and 28 days flexural strength is 0.969 in both software. It indicates that both software can effectively predict and optimize.
The Peer Effects of the Usage of Credit Cards in Rural Areas of China: Evidence from Rural China
Authors: Cai Dongliang , Ou Jun , Han Kefei , Lyu Yang
Published: June 2022

This paper aims to explore whether the usage of credit cards has peer effects in rural areas of China. The results suggest that the usage of credit cards will be affected by the behavior of other farmers; namely, the usage of credit cards has peer effects in rural areas. We also verify that women, older, and low‐academic farmers show stronger peer effects. The results emphasize that, compared with the mass farmers and vulnerable farmers, the usage of elite farmers is more likely to affect the same behaviors of other farmers. Our study contributes to prior literature by giving empirical insights into the consequences of peer effects on the credit card usage of farmers, which conduces to a better understanding of the financial decision‐making of farmers. The research may provide a practical implication for the optimal design of policy interventions. On the one hand, banks and other financial institutions can promote innovative financial products in rural areas with the help of peer effects; on the other hand, regulators can regulate farmers’ wrong financial behaviors by the social multiplier of peer effects to reduce systemic risks in rural finance.
Magnetic Resonance Imaging Data Features to Evaluate the Efficacy of Compound Skin Graft for Diabetic Foot
Authors: Wang Chunlei , Yu Xiaomei , Sui Ying , Zhu Junhui , Zhang Bo , Su Yongtao
Published: June 2022

This study aimed to analyze the role of magnetic resonance imaging (MRI) data characteristics based on the deep learning algorithm in evaluating the treatment of diabetic foot (DF) with composite skin graft. In this study, 78 patients with DF were randomly rolled into the experimental group (composite skin graft) and control group (autologous skin graft) with 39 patients in each group. MRI scans were performed before and after treatment to compare the changes of experimental observation indicators such as healing time, recurrence rate, and scar score. The results showed that T1‐weighted imaging (T1WI) of the scanning sequence was considerably increased in the experimental group after treatment. The signal intensity of fat‐suppressed T2‐weighted imaging (T2WI) and fat‐suppressed T1WI enhancement sequences was considerably decreased (P < 0.05). In addition, compared with the control group, the recurrence rate, healing time, and scar score in the experimental group were considerably decreased (P < 0.05). The accuracy, specificity, and sensitivity of MRI imaging information in evaluating the therapeutic effect of DF patients were 85.2%, 89.75%, and 86.47%, respectively. According to the specificity and sensitivity, the subject operating characteristic curve was drawn, and the area under the curve was determined to be 0.838. In summary, MRI image data characteristics based on the deep learning algorithm can provide auxiliary reference information for the efficacy evaluation of compound skin transplantation for DF.
[Retracted] Effect of Aluminium Tetrahydrate Nanofiller Addition on the Mechanical and Thermal Behaviour of Luffa Fibre‐Based Polyester Composites under Cryogenic Environment
Authors: Velmurugan G. , Siva Shankar V. , Kaliappan S. , Socrates S. , Sekar S. , Patil Pravin P. , Raja S. , Natrayan L. , Bobe Ketema
Published: June 2022

In recent times, research has shifted away from conventional materials and alloys and more towards nanocomposites to create lighter, more efficient materials for specific applications. The major goal of this research is to see how successful adding aluminium tetrahydride (ATH) filler to a luffa fibre/polyester‐based hybrid composite is. The compression moulding process was used to create the nanocomposite. The following limitations were used to achieve the goals mentioned above: (i) weight percent of ATH, (ii) weight percent of luffa fibres, and (iii) cryogenic treatment hours. The mechanical properties of the materials, such as flexural, tensile, and impact, were examined. The scanning electron microscope observed the morphology pictures, revealing flaws such as interface behaviour, fibre pullouts, voids, and interior cracks. As a result, the current study found that adding nanofiller to a natural fibre composite can improve its mechanical properties, because it established a strong link between the matrix and its reinforcements, which would aid in the effective transmission of stress in the hybrid system. It also improved moisture resistance, which might be useful in construction and commercial industries. The composite with 1 wt.% of ATH, 24 wt.% of luffa fibres, and 30 minutes of cryogenic treatment showed better mechanical strength. Cryogenic treatment reduces compressive interface stresses, which helps maintain fibre and matrix in contact and improve adhesion, resulting in superior results. TGA analysis was used to confirm it.
Mask R-CNN-Oriented Pottery Display and Identification System
Authors: Wei Chuantao
Published: June 2022

Traditional pottery identification methods are time consuming and costly. In order to cater to more pottery industry needs, we propose a Mask R-CNN-based pottery identification method to build an automatic pottery identification system. We first improve the loss function of Mask R-CNN by using generalized intersection over union loss function, through the pattern of migration learning, to compensate for the disadvantage of a small collective amount of pottery data. For different types of pottery, we use the mask algorithm to enhance the features of the outer contour of the pottery. In addition, we use the minimum external matrix algorithm to accurately extract the outer contour bit pose features of pottery to improve the model’s accuracy in recognizing the outer contour of pottery. To meet the testing conditions of pottery, with the support of potters and archaeologists, we make our pottery data set according to pottery categories. The experimental results prove that our method performs best in the comprehensive recognition accuracy of pottery, with the recognition accuracy above 90%. The recognition accuracy is also the best in pottery color decoration and grain decoration, and the grain recognition accuracy stays above 87%, which is better than other pottery recognition methods.
Imperative Role of Technology Intervention and Implementation for Automation in the Construction Industry
Authors: Srivastava Amit , Jawaid Sajjaf , Singh Rajesh , Gehlot Anita , Akram Shaik Vaseem , Priyadarshi Neeraj , Khan Baseem
Published: June 2022

According to sustainable development goals, the construction industry is one of the vital industries that can build resilient and sustainable infrastructure for human settlements. As the traditional approaches in the construction industry are causing distinct challenges including environmental pollution and excess energy usage, however, the integration of emerging technologies will assist us to reduce the impact and also enhance the activities in the construction industry. Motivated by the facts, this study aims to address the significance of automation in the construction industry with distinct emerging technologies like the Internet of things (IoT), automation, radio frequency identification (RFID), building information modeling (BIM), augmented reality (AR), and virtual reality (VR). The large amount of data generated from the IoT, RFID, BIM, and AR/VR provided an opportunity for big data and artificial intelligence (AI) to extract meaningful insights related to the events in the construction industry. Furthermore, edge and fog computing technology encourages us to implement AI at the edge network for analytics at the end of the edge device. Based on the above analysis, the article discussed recommendations that could assist in further enhancement and implementation of automation in the construction industry. Cloud‐assisted AR/VR, integration of AI with IoT infrastructure, 4D printing, adopting blockchain in the construction industry, and smart robotics are the recommendation addressed in this article.
Teaching Application and Evaluation of Ideological and Political Courses Based on Multisource Data Fusion
Authors: Zhou Jieqiong , Wei Zhenhua , Shi Jianwei
Published: June 2022

Domestic education and scientific nature of realization automatic evaluation have become issues of concern. The integration of information technology in the teaching field of ideological and political theory courses in colleges and universities (hereinafter referred to as “ideological and political courses”) inevitably has an important impact on the teaching of traditional ideological and political courses. ASP.NET is the main interface technology of .NET. .NET is an environment that can provide support for building development and execution in multiple languages, and realizes the functions of language development, code compilation, building configuration, program operation, and object interaction. The system development tool is ASP.NET (Visual Studio 2013), the background database development tool is Microsoft SQL Server 2008, and the system development environment is Windows 7 ×64. The core of the system is multisource data fusion. Firstly, the data are preprocessed to extract useful information data to form data object fusion. Then, convert the code table into a transaction library. In view of the large amount of data to be mined and easily affect mining quality, the improved Apriori-P algorithm based on partitioning in association with rule technology is applied. This algorithm is used to generate frequent itemsets. According to the given minimum confidence, a data fusion rule is generated. Then, the fusion result is generated from the corresponding data report. Before data fusion, system administrators should select data sources from historical databases or existing evaluation databases. When querying rules, different users can log in to the system to query their own data content, students can query the teacher’s evaluation results, teachers can query their own evaluation results, and school administrators can view the data fusion results. After evaluating teachers through the campus network, all evaluation data can be integrated and analyzed, and the system automatically generates analysis results corresponding to users. The stability of the teaching evaluation system is better, and the system performance can reach 89% at 5,000 person-hours. The degree of integration between the form of informatization teaching and the teaching content of ideological and political courses, and the information literacy of teachers of ideological and political courses in colleges and universities need to be further improved. This research helps in scientific education. For the problems existing in the current research, starting from the three aspects of teaching concept, teaching mode, and teachers’ information literacy, it proposes corresponding effective ways to promote the deep integration of information technology and ideological and political teaching in colleges and universities.
Promising Health Benefits of Adjuvant Acmella and Zingiber Extracts Combined with Coenzyme Q10 Phytosomes, Supplementation in Chronic Pain Treated with Medical Cannabis: A Prospective and Open-Label Clinical Study
Authors: Poli Paolo , Carnevale Simona , Scocca Antonella , Davolio Pier Luigi , Busi Simona , Meneghin Martino , Petrangolini Giovanna , Riva Antonella
Published: June 2022

Background. Chronic pain is a condition where pain persists for months or even years. Nowadays, several drugs comprising of medical cannabis are utilized for chronic pain relief. Even if there are some associated side effects, the use of supplements can widen the reliable tools available for improving an individual’s quality of life. Objective. The aim of the present study was to evaluate the efficacy in terms of pain intensity, psychological well-being, and quality of life of a new dietary supplement in chronic pain subjects under current treatment with medical cannabis. Methods. In this pilot study, 48 medical cannabis-treated subjects were supplemented with a dietary supplement containing a combination of standardized Zingiber officinalis and Acmella oleracea extracts in phytosome (Mitidol), coenzyme Q10 phytosome (Ubiqsome), and group B vitamins (B1, B6, and B12), twice daily for 90 days. In order to explore the benefits of the product as an adjuvant supplementation for pain relief, the pain intensity, measured by the visual analogue scale (VAS), the pain type, and quality, evaluated by the Italian Pain Questionnaire (QUID) and the possible reduction of therapeutic and/or painkiller doses were recorded. Results. After 90 days, significant pain relief was detected in almost 70% of the subjects receiving the new dietary supplement, with sensory, emotional, and pain amelioration in one-third of them. A reduction in both tetrahydrocannabinol (THC) and cannabidiol (CBD) doses was also observed after 3 months of supplementation. These findings demonstrate new perspectives for the use of an innovative dietary supplement that combines Acmella and Zingiber extracts, Coenzyme Q10, and group B vitamins resulting in a beneficial long-term adjuvant in cannabis-treated pain subjects.
Design of Optimum Portfolio Scheme Based on Improved NSGA-II Algorithm
Authors: Zhou Yiqian , Chen Weinan , Lin Deqin
Published: June 2022

In the financial industry, it is of great significance to study the multiobjective portfolio optimization for obtaining a reasonable investment strategy. This paper designs the financial portfolio scheme based on the multiobjective optimization algorithm that is based on the framework of the NSGA-II algorithm. In order to introduce convergence information, aiming at the actual problem of the portfolio, the mixed individual coding mechanism with asset information expands the application of the multiobjective evolutionary algorithm in portfolio optimization. The portfolio scheme obtained is effective, which is helpful to improve the decision-making efficiency of financial investors and enriches the application of modern financial theory.
Iminodisuccinic Acid Relieved Cadmium Stress in Rapeseed Leaf by Affecting Cadmium Distribution and Cadmium Chelation with Pectin
Authors: Tian Hui , Zhu Zihan , Song Haixing , Wu Xiuwen
Published: June 2022

Rapeseed ( Brassica napus L.) is a nutritious vegetable, while cadmium (Cd) pollution threatens the growth, productivity, and food security of rapeseed. By studying the effects of iminodisuccinic acid (IDS), an easily biodegradable and environmental friendly chelating agent, on Cd distribution at the organ and cellular level, we found IDS promoted dry matter accumulation of rapeseed and increased the contents of photosynthetic pigment in leaves. Inhibited root-shoot Cd transport resulted in higher activity of antioxidant enzymes and decreased hydrogen peroxide (H2O2) and malondialdehyde (MDA) accumulation in leaves, which indicated that IDS contributed to alleviating Cd-caused oxidative damage in leaf cells. Additionally, IDS increased Cd subcellular distribution in cell wall (CW), especially in covalently bound pectin (CSP), and relieved Cd toxicity in organelle of leaves. IDS also enhanced demethylation of CSP. The Cd content in CSP, demethylation degree, and pectin methylesterase activity of CSP increased by 37.95%, 13.34%, and 13.16%, respectively, while IDS did not change the contents of different CW components. The improved Cd fixation in leaf CW was mainly attributed to enhance demethylation of covalently bound pectin (CSP) and Cd chelation with CSP.
AdipoR1 Regulates Ionizing Radiation-Induced Ferroptosis in HCC cells through Nrf2/xCT Pathway
Authors: Feng Hao , Liu Yi , Gan Yuhan , Li Mengke , Liu Rui , Liang Zhenzhen , Liu Lianchang , Li Lan , Chen Huajian , Li Guanghui , Tian Zhujun , Liu Xiaodong , Ma Shumei
Published: June 2022

Radiotherapy has been used for decades in the treatment of liver cancer. We previously found that adiponectin receptor (AdipoR1) is a prognostic biomarker for hepatoma carcinoma (HCC) after stereotactic body radiation therapy (SBRT) and blocking AdipoR1 enhances radiation sensitivity in hepatoma carcinoma cells. In the current study, we aimed to elucidate the roles of AdipoR1 in ionizing radiation- (IR-) induced radiosensitivity by activating ferroptosis pathway in HCC cells. We found that IR upregulated the expression of AdipoR1 and furthermore promoted the protein stability of transcription factor Nrf2, Nrf2 binded to the xCT promoter and increased xCT transcription and expression, and this directly contributed to the protective function in the early stage of radiation in HCC cells. AdipoR1 knockdown significantly inhibited expression of Nrf2 and xCT and, furthermore, increased both IR- and erastin-induced ferroptosis, which could be abolished by the rescue of Nrf2 and xCT. For the first time, we found that radiation-induced ferroptosis was mediated by AdipoR1-Nrf2-xCT pathway in HCC cells. These results provide new insights to the development and application of novel therapeutic strategies for hepatoma carcinoma.
Changes in Physical Function of Shuttlecock Players after Short-Term Intensive Training based on Data Mining
Authors: Zeng Wenyao
Published: June 2022

This paper investigates the changes in body composition and physical fitness of badminton players after short-term high-intensity training. Methods. During an 8-week short-term training camp, 12 nonprofessional badminton players were paired to design training sessions, and body composition and fitness were measured before and after training. Results. After 8 weeks of high-intensity training, there was no significant change in body weight of badminton players

P
>
0.05

, while lean body mass increased significantly and body fat percentage decreased significantly

P
<
0.05

. The time of kicking, lying on the back, and standing forward was increased

P
<
0.05

, and the time of running back and forth 6.1 meters 3 times was shorter than that before training

P
<
0.05

. Conclusion. The increase of lean body mass can promote the energy conversion, oxygen consumption, and exercise capacity of athletes. Short-term training can reduce excess body fat, promote muscle development, and improve physical fitness.
Electrochemical Seismic Design and Artificial Intelligence System Modeling of High-Rise Steel Structure Buildings
Authors: Xia Wenjie
Published: June 2022

This study aims to improve the mechanical earthquake-resistance ability of high-rise buildings’ steel structures so that their safety performance is improved and their service life is prolonged. The simulation experiments on the response of the staggered truss steel structure are conducted in high-rise buildings to earthquake energy waves. First, MATLAB is used to build an experimental platform for earthquake-resistance evaluation of high-rise residential buildings. Through the high-rise building model training, it is found that the model meets the needs of the study. Second, the earthquake-resistance performance parameters, deformation recovery capacity, and dynamic response speed of the staggered truss steel structure are simulated and tested. After earthquake energy waves with different intensities are posed on the high-rise building model, the performance parameters of the staggered truss structure are tested, and the changes in the parameters of the structure are analyzed. Finally, the earthquake-resistance performance and post-earthquake recovery ability of the staggered truss structure are tested through comparative analysis. The results show that the interlayer displacement fluctuation of the staggered truss steel structure is the smallest, and the earthquake resistance performance is better than others under the energy waves of all kinds of earthquakes. Although its earthquake-resistance ability decreases with the duration of earthquakes, the reduction speed is slow. When the quake lasts 12 s, the resistance of the staggered truss structure is still greater than 2500 MPa. This study provides a reference for the staggered truss structure of high-rise buildings.
Analysis of the Effect of Sichs on Gastric Ulcer Rats Based on RNA Sequencing Technique
Authors: Su Lin , Song Hong , Ren Ti , Chen Wen , Zhang Jiaqi , Wang Guiyue , Yang Junfang , Hou Xin , Shen Yan , Liu Xiaogu
Published: June 2022

Objective. To research the mechanism of action and transcriptomic characteristics for the intervention effect of self-made Chaihuang decoction (Sichs) on gastric ulcer (GU) rats with liver qi stagnation and spleen deficiency and to clarify the therapeutic pathway and effective target. Methods. Thirty SD rats were randomly divided into the control group, model group, and Sichs group (10 rats per group). The model of GU rats with liver qi stagnation and spleen deficiency was established through multifactor compound simulation of traditional Chinese medical (TCM) etiology and acetic acid method. Histopathological changes in the gastric antrum tissue were observed with H&E staining. RNA sequencing (RNA-seq) was utilized to check differentially expressed genes (DEGs) in the gastric antrum tissues of rats, and gene ontology (GO) and KEGG pathway enrichment analyses were performed. The key DEGs were validated using qRT-PCR. Results. Sichs could ameliorate gastric antrum tissue injury in GU rats with liver qi stagnation and spleen deficiency. After RNA-seq, it was found that Sichs could reverse 225 upregulated genes and 26 downregulated genes in the model group. And the DEGs between the Sichs group and the model group were related to cell division, complement activation, and phospholipase A2 (Pla2g2a) activity. According to KEGG pathway analysis, DEGs between the two groups were mainly enriched in signaling pathways such as cell cycle, p53 signaling pathway, and linolenic acid metabolism. The validation results of the four key DEGs were consistent with the analysis trend of sequencing results. Conclusion. Sichs can effectively improve GU with liver qi stagnation and spleen deficiency in rats through the signaling pathways related to cell cycle and lipid metabolism.
Effect of High-Quality Nursing Care on Patients with Acute Exacerbation of Chronic Obstructive Pulmonary Disease Complicated with Respiratory Failure: An Observational Cohort Study
Authors: Zhang Junhong , Xu Na , Zheng Dahuan
Published: June 2022

Background. To investigate the efficacy of high-quality nursing care on patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD) complicated with respiratory failure. Methods. A total of 84 AECOPD patients were included in this study. Lung function indexes, nursing satisfaction, and arterial blood gas index were collected to assess the efficacy of high-quality nursing care on patients with acute chronic obstructive pulmonary disease complicated with respiratory failure. Results. The level of lung function after treatment had a statistical difference between the two groups (

P
<
0.05

). On other hand, the nursing satisfaction is improved in the observation group. The PaCO2 and PaO2 level was improved after treatment; there was statistical significance (

P
<
0.05

). Conclusion. High-quality nursing intervention has good therapeutic effect on acute exacerbation of COPD complicated with respiratory failure.
The Combinatory Effect of Spirulina Supplementation and Resistance Exercise on Plasma Contents of Adipolin, Apelin, Ghrelin, and Glucose in Overweight and Obese Men
Authors: Mohammad Malekaneh , Karim Dehghani , Mehdi Mogharnasi , Marziyeh Saghebjoo , Hadi Sarir , Shila Nayebifar
Published: June 2022

Introduction and Objective. Researchers are considering combining exercise and supplementation as a new strategy for weight loss and obesity prevention. This study is aimed at evaluating the effect of eight weeks of circuit resistance training and spirulina supplementation on plasma levels of adipolin, apelin, ghrelin, and glucose in overweight and obese men. Methods. The current investigation was conducted in a single-blind and quasiexperimental fashion. Sixty overweight and obese men (BMI>25) ranging in age from 30 to 55 years were purposefully selected and randomly assigned to one of four groups: training plus spirulina (T+S), training plus placebo (T+P), spirulina (S), or placebo (P). For eight weeks, the (S) and (P) groups consumed two 500 mg spirulina and placebo capsules daily, respectively. Resistance training was performed three sessions a week over eight weeks, consisting of 12 movements with 1-, 2-, 3-, and 4-minute rest intervals and 40-90 percent maximal repetition. Adipolin, apelin, and ghrelin indices were measured before and after exercise using special kits. Results. All variables changed significantly between groups except for apelin. Within-group comparisons revealed a substantial increase in adipolin levels in the (T+S) and (T+P) groups (P<0.05). Apelin levels were decreased in the (T+S) and (T+P) groups. Additionally, FBS levels reduced significantly in (T+S) (P=0.01). Conclusion. It seems that eight weeks of circuit resistance training and spirulina supplementation can lead to reduced weight and apelin and FBS levels as well as increased concentrations of adipolin and ghrelin contents in overweight and obese men.
MOOC and Flipped Classroom Task-Based English Teaching Model for Colleges and Universities Using Data Mining and Few-Shot Learning Technology
Authors: Gong Yujuan , Zhou Jie
Published: June 2022

As a revolutionary education model, the flipped classroom teaching model has unique advantages over the traditional education model. How to change the teaching method of flipped classroom into a teaching method suitable for college English courses is a problem. The goal of this research is to investigate how to use data mining and few-shot learning technology to investigate the impact of MOOC and flipped classroom task-based college English teaching modes. This work provides a data mining-based decision tree algorithm and examines the enhanced decision tree method. The experimental results of this study demonstrate that two students in each of the two groups believe that the English teaching mode, which is mostly taught by traditional teachers, is very favorable to a thorough understanding of basic knowledge, accounting for 4% of the total. There are 17 students that believe the new teaching methodology is really beneficial, accounting for 34% of the total. This mode was determined to be effective for in-depth knowledge of the basics by a total of 25 students. It can be seen that the flipped classroom model is more popular with students.
Evaluation Method of Students’ “Hierarchical” Education Management Effect Based on Data Mining
Authors: Tang Wuming
Published: June 2022

In order to improve the accuracy of students’ hierarchical education management effect evaluation, this paper proposes a method of students’ hierarchical education management effect evaluation based on data mining. Firstly, the effect of data mining technology in the evaluation of students’ “hierarchical” education management effect is analyzed, and the abnormal data of education management is eliminated by cosine determination calculation method to realize the preprocessing of students’ “hierarchical” education management data. Then, establish the index system for the evaluation of students’ “hierarchical” education management effect, design the association rules for the evaluation of students’ “hierarchical” education management effect according to the Apriori algorithm, calculate the evaluation index weight according to the analytic hierarchy process and the average method of expert opinions, and realize the consistency test of the evaluation index weight according to the judgment matrix. Finally, the effect evaluation of students’ “hierarchical” education management is realized through data mining. The experimental results show that the accuracy of this method is up to 98.8%, and the evaluation time is only 1.05 s, which shows that this method can effectively improve the evaluation effect of education management effect.