bluuebunny/crossref_metadata_2025 huggingface dataset:
Nursing Effect and Prognosis Analysis of Self-Management Education Model Based on Protective Motivation Theory on Patients with Hematological Tumor after PICC Catheterization
Authors: Jiang Lili , Yang Xiuying , Xi Lu , Zhang Chaolang
Published: May 2022

Objective. To analyze the nursing effect and prognostic value of self-management education model based on protective motivation theory on patients with hematological malignancies (HM) after peripheral venous catheterization (PICC). Methods. A total of 90 patients with HMs treated with PICC catheterization in our hospital from October 2019 to October 2021 were included in the study. The patients were randomly assigned into experimental group (

n
=
45

) and control group (

n
=
45

). On the basis of the control group, the experimental group implemented the self-management education model based on the theory of protective motivation, and the control group implemented routine nursing health education measures. The self-nursing ability scale (ESCA), Hamilton anxiety scale (HAMA), the average cost of PICC catheter maintenance, the incidence of PICC-related complications, and the score of Newcastle nursing satisfaction scale (NSNS) were observed 1 month before and after nursing. Results. After one month of nursing, there was no significant difference in ESCA self-concept (

p
>
0.05

). After one month of nursing, the scores of self-care responsibility, self-nursing skills, and health knowledge in the experimental group were significantly higher compared to those before nursing (

p
<
0.05

) and higher compared to those in the control group (

p
<
0.05

). After one month of nursing, the score of HAMA scale was significantly lower compared to that before nursing (

p
<
0.05

), and the score of HAMA scale in the experimental group was lower compared to the control group (

p
<
0.05

). After one month of nursing, the average cost of PICC pipeline maintenance in the test group was lower than that in the control group (

p
<
0.05

). One month after nursing, the incidence of PICC-related complications in the experimental group was lower than that in the control group (

p
<
0.05

). One month after nursing, the score of NSNS scale was significantly higher than that before nursing (

p
<
0.05

). After one month of nursing, the score of NSNS scale in the experimental group was higher than that in the control group. Conclusion. The self-management education model based on protective motivation theory is effective in nursing patients with peripheral venous catheterization and PICC catheterization of HMs. It is more beneficial to promote patients’ self-nursing management ability, reduce anxiety, reduce the average cost of PICC pipeline maintenance, reduce the incidence of PICC-related complications, and enhance nursing satisfaction.
A Hybrid Model for Intrusion Detection in IoT Applications
Authors: Alghamdi Mohammed I.
Published: May 2022

Internet of Things (IoT) networks has recently become an important component of smart cities, smart buildings, health care, and other applications. It finds it beneficial due to the inherent characteristics of low cost, compact, and low-powered IoT devices. At the same time, security remains a challenging issue in the design of IoT networks. Intrusion detection systems (IDS) can be used to identify the occurrence of intrusions in the network, i.e., abnormal activities in the network. The latest advances in machine learning (ML) and metaheuristics can be employed to design effective IDS models for IoT networks. This article develops a novel political optimizer with cascade forward neural network (PO-CFNN-)-based IDS in the IoT environment. The major intention of the PO-CFNN technique is to determine the occurrence of intrusions from the IoT environment. The PO-CFNN technique follows three major processes, namely, preprocessing, classification, and parameter optimization. Initially, the networking data is preprocessed to transform it into a useful format. Following that, the CFNN technique is employed for the identification and classification of intrusions in the IoT environment. In the final stage, the PO algorithm is applied for the optimal adjustment of the parameters involved in the CFNN model. The experimental validation of the PO-CFNN technique on a benchmark dataset stated the better outcomes of the PO-CFNN technique over recent approaches.
[Retracted] Cigarette Smoke Regulates the Expression of EYA4 via Alternation of DNA Methylation Status
Authors: Almutairi Bader O. , Almutairi Mikhlid H. , Alrefaei Abdulwahed F. , Ali Daoud , Alkahtani Saad , Alarifi Saud
Published: May 2022

Cigarette SMOKE (CS) considerably contributes to causing some diseases such as cancer, and it has a role in the alternation of gene expression through several mechanisms including epigenetics modification, particularly DNA methylation. EYA4 is one of the genes, that whose expression has been dysregulated in lung, colon, bladder, and breast cancer, leading to tumor progression. The alternation of DNA methylation levels has been implicated in regulating the expression of the EYA4 gene. Thus, in this study, we have shown the effect of CS on the DNA methylation level of the EYA4 promoter region as well as the methylation level on EYA4 expression. To determine the level of DNA methylation on the promoter region of the EYA4 gene, we have employed the bisulfite conversion treatment followed by the Sanger Sequence for 100 DNA samples taken from Saudi people (50 smokers and 50 nonsmokers). We found that 26% of DNA extracted from smoker samples is methylated, while there was no methylation identified in nonsmoker samples. Also, using the demethylating agents such as AZA on LoVo and Caco‐2 cancer cell lines causes induction of transcription level of EYA4, implying the possible mechanism of DNA methylation in the upregulation of EYA4. These findings suggest the possible mechanism of CS in controlling the expression of EYA4 via changing the status of DNA methylation.
Effects of Individualized Nursing Based on Zero-Defect Theory on Perioperative Patients Undergoing Laparoscopic Cholecystectomy
Authors: Lan Lihong , Zhu Xiaozheng , Ye Bili , Jiang Huizhen , Huang Yuntao
Published: May 2022

Objective. This study is aimed at analyzing the effects of individualized nursing based on the zero-defect theory on perioperative patients undergoing laparoscopic cholecystectomy. Methods. 174 patients who underwent laparoscopic cholecystectomy from 1st November 2019 to 30th November 2020 were enrolled as the research subjects and randomly divided into control and observation groups. The patients in the control group received conventional perioperative nursing care, and the patients in the observation group were treated with individualized nursing based on the zero-defect theory. Results. The heart rate, diastolic blood pressure, and systolic blood pressure level of patients in two groups after nursing decreased significantly, and the reduction in the observation group was more significant than that in the control group. The depression and anxiety scores of the two groups after nursing were decreased, and the decrease in the observation group was significantly greater than that in the control group. The time to first postoperative exhaust, return to normal intake, out-of-bed activity, and hospital stay in the observation group was less than that in the control group. The incidence of postoperative complications in the observation group was substantially lower than that in the control group. The satisfaction degree of nursing care in the observation group was significantly higher than that in the control group. Conclusion. Individualized nursing care based on zero-defect theory can effectively reduce the perioperative psychological stress response of patients with laparoscopic cholecystectomy. It helps to improve the negative emotions of depression and anxiety, promotes the recovery of disease, reduces postoperative complications, and improves nursing satisfaction, which is worthy of clinical promotion.
Optimization of the Index System of the Sports Social Organization Development Ability Relying on Image Optimization, Recognition, and Simulation
Authors: Sun Wei
Published: May 2022

Sports social organizations refer to nonprofit, nongovernmental, and group organizations that achieve specific service goals and common aspirations and spontaneously form various sports and fitness activities in accordance with the rules. This article aims to study how to optimize the index system of the capacity developments by relying on image optimization and recognition simulation. This article puts forward the relevant theoretical knowledge of image optimization and recognition and capacity developments and proposes two algorithms based on image optimization and recognition. In 2019, the percentage of growth of sports social organizations rose from 6.7% to the final 27%; in 2020, the growth rate of sports social organizations is getting higher and higher, from 9% at the beginning to 34% at the end. It can be seen that people’s love for sports activities is getting higher and higher, and the state is paying more and more attention to sports social organizations. The factors that affect the development ability of sports social organizations include the quality, education, and management capabilities of the members of the organization, and the country and the government should also take corresponding measures. The improvement of the development ability of sports social organizations is of great significance to the development of sports social organizations.
Research and Application of Color of Qiuci Murals Based on Intelligent Digital Image Processing Technology
Authors: Kong Qianqian , Qiao Yong
Published: May 2022

In order to improve the color research effect of Qiuci murals, this paper combines digital technology, applies intelligent digital image processing technology to the color research of Qiuci murals, and builds an intelligent system. Moreover, this paper analyzes the color mural pixel digitization of murals from the perspective of digitization and conducts research from a microscopic perspective. In addition, in this paper, the expansion operation is performed for particularly small cracks, and the extraction area of the crack is correspondingly increased, which reduces the bad influence on the subsequent repair due to incomplete crack extraction. Finally, this paper constructs an intelligent mural analysis system based on the improved algorithm. The experimental research results show that the color research system of Qiuci murals based on intelligent digital image processing technology proposed in this paper has good effects and can play an important role in the digital protection and digital restoration of art.
Reservoir Physical Properties and Micropore Nanocharacteristics of Cores in the Shihezi Formation, Sudong District, Sulige Gas Field, Ordos Basin
Authors: Zhang Xin , Wang Feng , Liang Shuyi , Guo Qintao , Tian Jingchun , Shen Bingyue
Published: May 2022

Sulige gas field is a very complex large-scale gas field with low porosity, low permeability, low abundance, and strong heterogeneity. In this study, the nanopore structure of the reservoir in the study area was analyzed. The analysis of reservoir physical properties and core microscopic pore characteristics of Shihezi formation in Sudong District, Sulige gas field, Ordos Basin, was put forward. According to core observation, thin section identification, and grain size analysis, the lithology of gas reservoirs in Shan-1 member and He-8 member in the study area is mainly lithic sandstone, lithic quartz sandstone, and quartz sandstone. According to the analysis of physical data in the study area, the reservoirs in Shan-1 member and He-8 member have typical characteristics of low porosity and low permeability. According to that microscopic observation of sandstone thin section and cast thin section combined with the analysis of scan electron microscope, the results show that both Shan-1 member and He-8 member of Sudong area 2 in Sulige gas field are dominated by class I reservoirs and class II reservoirs. Especially, class I reservoirs are widely distributed, with the cumulative area of this type of reservoirs accounting for 70.12% of the total area in Shan section and 64.12% in He-8 section. Class I reservoirs are scattered in the study area, accounting for 0.27% of the total area in the mountain section and 0.36% in the He-8 section. Class IV reservoirs are distributed dispersedly and have a small distribution area. The cumulative area of reservoirs in mountain section accounts for 5.38% of the total area and that in He-8 section accounts for 5.46%. Therefore, Sudong area 2 in Sulige gas field is a typical low porosity and low permeability reservoir. On the basis of geological background, sedimentary microfacies, diagenesis, and pore structure characteristics of the study area, it is considered that the pore structure of sandstone in the study area is mainly controlled by sedimentary characteristics and diagenesis of sandstone.
[Retracted] Modification in Silver Staining Procedure for Enhanced Protein Staining
Authors: Jiang Yibo , Zheng LinLin , Lin Lulin , Lin Shan , Xu Kui , Deng SiJie , Zhang QiQing
Published: May 2022

Silver staining is an excellent technique for detecting proteins that are separated by sodium dodecyl sulfate‐polyacrylamide gel electrophoresis (SDS‐PAGE). Protein silver staining technology has higher sensitivity and is suitable for the detection of low‐concentration proteins compared to other staining techniques including the Coomassie brilliant blue detection method. The present study was conducted to enhance the detection ability of the protein staining method. Herein, we modified the recipe of silver staining, a very reproducible method, by adding AMP, PVP, Tween‐80, and xylene to enhance the detection ability of protein staining. Furthermore, the particle size and potentiometer were used to detect the particle size and potential difference of the silver ions in the prepared dyeing materials, and then, the morphology, transparency, and size of the dyed silver particles in different dyeing solutions were studied using a transmission electron microscopy (TEM). The obtained results revealed that the use of 0.5% of AMP, PVP, Tween‐80, and xylene improved the staining ability of protein silver staining, compared with the original method. Furthermore, 0.5% AMP, 0.5% PVP, 0.5% Tween‐80 reagents significantly influenced the morphology, size, potential, and dispersion of silver ions. These results suggested a new idea for further improving the detection ability of protein silver staining.
[Retracted] Albiflorin Alleviates Ox‐LDL‐Induced Human Umbilical Vein Endothelial Cell Injury through IRAK1/TAK1 Pathway
Authors: Liu Yeling , Sun Yilai , Bai Xue , Li Lingxing , Zhu Guihua
Published: May 2022

Introduction. Atherosclerosis (AS) is a chronic inflammatory disease characterized by lipid metabolism disorder and vascular endothelial damage. Albiflorin (AF) has been certified to be effective in the therapy of certain inflammatory diseases, while the therapeutic effect and mechanism of AF on AS have not been fully elucidated. Material and Methods. Model cells for AS were created by inducing oxidized low‐density lipoprotein (Ox‐LDL) in human umbilical vein endothelial cells (HUVECs). After processing with AF and interleukin‐1 receptor‐associated kinase 1‐ (IRAK1‐) overexpressed plasmid, cell viability was assessed by CCK‐8; cholesterol efflux was tested using liquid scintillation counter; IL‐6 and TNF‐α levels were determined with ELISA kits; ROS and apoptosis were confirmed using Flow cytometry. Besides, IRAK1‐TAK1 pathway and apoptosis‐ and mitochondrial fusion‐related proteins were monitored with western blotting analysis. Results. Our results verified that AF could not only dramatically accelerate viability and cholesterol efflux but also attenuate inflammation, ROS production, and apoptosis in Ox‐LDL‐induced HUVECs. Meanwhile, AF could prominently prevent the activation of IRAK1‐TAK1 pathway, downregulate apoptosis‐related proteins, and upregulate mitochondrial fusion‐related proteins in Ox‐LDL‐induced HUVECs. Moreover, we testified that IRAK1 overexpression memorably could reverse suppression of AF on inflammation, apoptosis, and IRAK1‐TAK1 pathway and enhancement of AF on viability, cholesterol efflux, and mitochondrial fusion in Ox‐LDL‐induced HUVECs. Conclusions. By blocking the IRAK1/TAK1 pathway, AF can significantly slow the course of AS, suggesting that it could be a viable therapeutic option for AS.
The Association of Serum AIM2 Level with the Prediction and Short-Term Prognosis of Coronary Artery Disease
Authors: Zhang Wenkang , Yan Gaoliang , Xu Chunyang , Tang Chengchun
Published: May 2022

Objective. Coronary artery disease (CAD), one of the commonest cardiovascular diseases, has high morbidity and mortality. Absent in melanoma 2 (AIM2) is involved in atherosclerosis, and no clinical trials have explored the association between AIM2 and CAD. Therefore, this study was aimed at evaluating the predictive and short-term prognostic value of AIM2 for CAD. Methods. 279 patients who underwent coronary angiography were enrolled in this study. The AIM2 level was detected from the serum of collected artery blood samples. The association of serum AIM2 level with the prediction and short-term prognosis of CAD was further assessed. Results. The serum AIM2 level of the CAD group was significantly higher than the control group ([Formula: see text] vs. [Formula: see text]; [Formula: see text]). AIM2 was demonstrated to be the risk factor of CAD [odds ratio, 1.589; 95% confidence interval (CI), 1.346-1.876; [Formula: see text]]. The area under the receiver operating characteristic (ROC) curve of 0.738 showed the diagnostic value of AIM2 in CAD. Additionally, AIM2 was an independent predictor of major adverse cardiovascular events (hazard ratio, 1.453; 95% CI, 1.086-1.945; [Formula: see text]), and CAD patients with high AIM2 levels (>4.9 ng/mL) had a markedly lower survival rate (log-rank [Formula: see text]). Conclusions. The serum AIM2 [Formula: see text] ng/mL can predict CAD to a certain extent. AIM2 might be an independent predictor of its short-term poor prognosis.
Synthesis and Characterization of New Catalysts Grains Based on Iron(Oxy)Hydroxides supported on Zirconium for the Degradation of 4-Nitrophenol in Aqueous Solution
Authors: Loumi Hafsa , Zermane Faiza , Cheknane Benamar , Bouchenafa Naima , Bouras Omar , Bonilla-Petriciolet Adrián
Published: May 2022

This study reports the preparation of catalyst grains based on oxyhydroxides of iron and zirconium via the coprecipitation method and their application in the degradation of 4-nitrophenol. The morphology, microstructure, and surface composition of these catalysts were characterized by scanning electron microscopy, X-ray diffraction, nitrogen physisorption, and Fourier transform infrared spectroscopy. The catalytic activity of the grains was assessed in the degradation of 4-nitrophenol in a heterogeneous system at different operating conditions. Degradation rates up to 93% were obtained after 4 h of contact time where the catalytic activity of tested materials was higher at pH 7 than in acidic and basic conditions. Amorphous iron hydroxide with a ratio of 75% Zr+25%Fe showed the best catalytic properties. These novel materials are an interesting alternative for facing the water pollution caused by organic compounds.
[Retracted] Research on Maximizing Influence of Blockchain Social Network Based on BCLT Model
Authors: Liu Chang , Bin Sheng
Published: May 2022

In the blockchain social network, the traditional influence maximization algorithm has the problem of insufficient accuracy of the influence spread. To solve the above problem, a BCLT model including the characteristics of the blockchain is established based on the linear threshold model. The BC‐RIS algorithm is proposed based on the reverse reachable set. The BC‐RIS algorithm's influence spread and running time and the traditional algorithm is compared using the real blockchain social network data set. The experimental results show that the BC‐RIS algorithm can obtain a larger influence spread range, which is more in line with the influence propagation law of the blockchain social network.
Wound Complication and Neuropraxia of the Posterior Cutaneous Nerve of the Arm after Primary Repair of a Latissimus Dorsi and Teres Major Tear
Authors: Alben Matthew G. , Gambhir Neil , Boin Michael A. , Campbell Kirk A. , Virk Mandeep S.
Published: May 2022

We present a case of a surgically treated latissimus dorsi (LD) and teres major (TM) tear with a one-year outcome. The postoperative course was complicated by wound dehiscence requiring operative intervention and neuropraxia of the posterior cutaneous nerve of the arm. The report highlights previously unreported surgical risks associated with repair of LD/TM tendons.
IRePf: An Instruction Reorganization Virtual Platform for Kernel Stack Overflow Detection
Authors: Wang Kunpeng , Li Jingmei , Fu Zhongchuan , Chen Tianyu
Published: May 2022

Stack overflow vulnerabilities are among the most common security issues. However, the existing stack overflow detection solutions only protect the return address and ignore the imbalance between function calls and returns in the system, which will lead to a higher false-positive rate. In this paper, we propose an instruction reorganization virtual platform technique for kernel stack overflow detection, named IRePf. It can dynamically monitor the kernel stack when the system is running through dynamic reorganization instructions, thread creation and termination, call instructions, and RET instructions. IRePf uses backup stack creation and destruction technology to back up the return address and the address of the return address at the same time. IRePf determines whether the stack overflow occurs in the system when the function call and return are unbalanced to realize the kernel stack overflow detection. The experimental results show that IRePf can effectively detect stack overflow attacks, has low system resource occupancy and high real-time performance, and effectively improves the ability and security of defense stack attacks.
Comparative Insights into the Skin Beneficial Properties of Probiotic Lactobacillus Isolates of Skin Origin
Authors: Lim Hye-Won , Huang Yu-Hua , Kyeong Gyuri , Park Minsik , Lim Chang-Jin
Published: May 2022

In recent times, probiotics have been emerging as one of valuable cosmetic resources. This work was undertaken to evaluate and compare the skin beneficial properties of three Lactobacillus strains, namely, L. plantarum SB202, L. fermentum SB101, and L. paraplantarum SB401, originally isolated from the healthy skins of Koreans. The Lactobacillus isolates were individually grown in MRS broth, and the corresponding cell‐free conditioned mediums (CMs), LP202, LF101 and LPP401, were prepared for analyzing diverse cosmetic potentials at a comparative perspective. The superoxide radical and nitrite ion scavenging activities of the CMs were in the orders of LPP401 ≥ LF101 > LP202 and LPP401 > LF101≒LPP202, respectively. They attenuated the lipopolysaccharide‐induced reactive oxygen species (ROS) and nitrite ion levels in RAW264.7 murine macrophages both in the order of LPP401 ≥ LF101 > LP202, implying their anti‐inflammatory properties. They exhibited antityrosinase activities in the order of LPP401 > LF101 ≥ LP202 and diminished α‐melanocyte‐stimulating hormone‐induced melanin levels in B16F10 melanoma cells in the order of LPP401≒LF101 > LP202, suggesting their skin whitening activities. They enhanced cornfield envelope formation in HaCaT keratinocytes in the order of LPP401 > LF101 > LP202. They inhibited the in vitro hyaluronidase and elastase activities in the orders of LPP401 > LP202 ≥ LF101 and LPP401 ≥ LP202 > LF101, respectively. Their enhancing properties on the synthesis of procollagen type I in normal human dermal fibroblasts were in the order of LF101≒LPP401 > >LP202. The CMs possess various cosmetic characteristics, such as antioxidant, skin whitening, antiaging, barrier improving, and anti‐inflammatory activities. LPP401, the CM prepared from L. paraplantarum SB401, has been evaluated to be more desirable cosmetic resource than LP202 and LF101.
Efficacy of Dapagliflozin Combined with Lifestyle Intervention in Obesity Control
Authors: Dai Wenhui , Peng Qiaolin
Published: May 2022

Objective. To explore the best treatment of obesity in middle and old age. Methods. 80 obese patients in our hospital from January 2020 to December 2021 were randomly divided into the control group and the intervention group according to the numerical table method. The control group was treated with lifestyle intervention, while the intervention group was treated with dapagliflozin combined with lifestyle intervention. The effects of body weight, body mass index (BMI), waist circumference, and blood lipids (LDL, HDL, TC, and TG) were measured and compared. Anxiety and depression scores were assessed using the 2018 Revised Anxiety and Depression Scale. Results. There were no significant differences in body weight, BMI, and waist circumference between the control group and the intervention group before treatment. After treatment, the weight, BMI, and waist circumference of the intervention group were lower than those of the control group, and the difference was statistically significant (

P
<
0.05

). After treatment, LDL, TC, and TG in the two groups were decreased, and HDL was significantly increased (

P
<
0.05

). After treatment, the blood lipid level in the intervention group was significantly lower than that in the control group (

P
<
0.05

). Anxiety and depression symptoms improved in both groups, and there were no serious adverse effects. Conclusion. Dapagliflozin in combination with a lifestyle intervention effectively and safely treats excess weight in middle-aged and older adults, reverses obesity-related markers, and improves psychological symptoms. Its curative effect is better than that of using lifestyle intervention alone.
Swarm Intelligence with Adaptive Neuro-Fuzzy Inference System-Based Routing Protocol for Clustered Wireless Sensor Networks
Authors: A-Matarneh Feras Mohammed , Alqaralleh Bassam A. Y. , Aldhaban Fahad , AlQaralleh Esam A. , Kumar Anil , Gupta Deepak , Joshi Gyanendra Prasad
Published: May 2022

Wireless sensor network (WSN) comprises numerous compact-sized sensor nodes which are linked to one another. Lifetime maximization of WSN is considered a challenging problem in the design of WSN since its energy-limited capacity of the inbuilt batteries exists in the sensor nodes. Earlier works have focused on the design of clustering and routing techniques to accomplish energy efficiency and thereby result in an increased lifetime of the network. The multihop route selection process can be treated as an NP-hard problem and can be solved by the use of computational intelligence techniques such as fuzzy logic and swarm intelligence (SI) algorithms. With this motivation, this article aims to focus on the design of swarm intelligence with an adaptive neuro-fuzzy inference system-based routing (SI-ANFISR) protocol for clustered WSN. The proposed SI-ANFISR technique aims to determine the cluster heads (CHs) and optimal routes for multihop communication in the network. To accomplish this, the SI-ANFISR technique primarily employs a weighted clustering algorithm to elect CHs and construct clusters. Besides, the SI-ANFISR technique involves the design of an ANFIS model for the selection process, which make use of three input parameters, namely, residual energy, node degree, and node history. In order to optimally adjust the membership function (MF) of the ANFIS model, the squirrel search algorithm (SSA) is utilized. None of the earlier works have used ANFIS with SSA for the routing process. The design of SSA to tune the MFs of the ANFIS model for optimal routing process in WSN shows the novelty of the study. The experimental validation of the SI-ANFISR technique takes place, and the results are inspected under different aspects. The simulation results highlighted the significant performance of the SI-ANFISR technique compared to the recent techniques with a maximum throughput of 43838 kbps and residual energy of 0.4800J, respectively.
Construction of Knowledge Graph English Online Homework Evaluation System Based on Multimodal Neural Network Feature Extraction
Authors: Liao Danlu
Published: May 2022

This paper defines the data schema of the multimodal knowledge graph, that is, the definition of entity types and relationships between entities. The knowledge point entities are defined as three types of structures, algorithms, and related terms, speech is also defined as one type of entities, and six semantic relationships are defined between entities. This paper adopts a named entity recognition model that combines bidirectional long short-term memory network and convolutional neural network, combines local information and global information of text, uses conditional random field algorithm to label feature sequences, and combines domain dictionary. A knowledge evaluation method based on triplet context information is designed, which combines triplet context information (internal relationship path information in knowledge graph and external text information related to entities in triplet) through knowledge representation learning. The knowledge of triples is evaluated. The knowledge evaluation ability of the English online homework evaluation system was evaluated on the knowledge graph noise detection task, the knowledge graph completion task (entity link prediction task), and the triplet classification task. The experimental results show that the English online homework evaluation system has good noise processing ability and knowledge credibility calculation ability, and has a stronger evaluation ability for low-noise data. Using the online homework platform to implement personalized English homework is conducive to improving students’ homework mood, and students’ “happy” homework mood has been significantly improved. The implementation of English personalized homework based on the online homework platform is conducive to improving students’ homework initiative. With the help of the online homework platform to implement personalized English homework, students’ homework time has been reduced, and the homework has been completed well, achieving the purpose of “reducing burden and increasing efficiency.”
Joint Beamforming Design for Intelligent Reflecting Surface Aided Terahertz Wireless Network
Authors: Bian Jinhong , Wang YuanYuan , Zhou Feng
Published: May 2022

This paper investigates the transmission design in a multiple-input single-output (MISO) Terahertz network assisted by an intelligent reflecting surface (IRS). Specifically, we consider the sum-rate maximization design by jointly optimizing the active beamforming (BF) and the phase shifters. To solve the formulated nonconvex problem, we utilize the Lagrangian dual transform based method to obtain an equivalent problem. Then, an alternating optimization (AO) algorithm is proposed, where the unit modulus constraint (UMC) of the IRS is handled by a computational efficient adaptive gradient descent (AGD) method. Finally, simulation results demonstrate the promising performance of the proposed design.
Computational Study of the Phytochemical Constituents from Uncaria tomentosa Stem Bark against SARS-CoV-2 Omicron Spike Protein
Authors: Herrera-Calderon Oscar , Saleh Abdulrahman M. , Yepes-Perez Andres F. , Aljarba Nada H. , Alkahtani Saad , Batiha Gaber El-Saber , Hañari-Quispe Renan Dilton , Chavez Haydee , Pari-Olarte Josefa Bertha , Loyola-Gonzales Eddie , Almeida-Galindo José Santiago , Kong-Chirinos José Francisco , Benali Taoufiq
Published: May 2022

The SARS-CoV-2 Omicron variant has spread rapidly and is considered the predominant variant in the world, and its main characteristic is related to evade immunity from natural infection or vaccines, due to its multiple mutations in the spike protein. On the other hand, medicinal plants have been used as alternatives therapies to ameliorate some signs and symptoms in COVID-19, and in our previous work, the cat’s claw (Uncaria tomentosa) stem bark has been studied in vitro and showed antiviral activity on SARS-CoV-2 as well as in silico studies on the 3CLpro protein and as disruptor between the ACE-2 human receptor and the spike protein. The aim in this computational study was to determine the main phytochemical constituents from U. tomentosa stem bark against the SARS-CoV-2 Omicron spike protein based on molecular modeling. A molecular docking was carried out on the isolated phytochemicals in a previous work against the SARS-CoV-2 Omicron spike protein-binding domain (PDB ID: 7T9K). Next, a molecular dynamic study was carried out to monitor the stability during the MD simulations. As results proanthocyanidin-C1 (-10.76 kcal/mol), quinovic acid-type 2 (-9.86 kcal/mol), and proanthocyanidin-B2 (-9.82 kcal/mol) were the constituents with the best binding free energy on the SARS-CoV-2 Omicron spike protein, and the best compound was stable during the dynamic simulation under physiological conditions. It is concluded that the anthocyanidin-based compounds determined in the stem bark ethanol extract could be responsible for the potential antiviral activity on SARS-CoV-2 Omicron variant, and the proanthocyanidin-C1 emerged as a powerful candidate to combat new variants.
The Levels of TNF-α, Tissue Factor, and Coagulation Function in Rats with Pulmonary Hypertension and the Intervention Effect of Sildenafil Encapsulated by Targeted Nanocarriers
Authors: Ma Xuan , Wang Xue-E , Xie Lin-Xia , Lu Sha , Jiang Cheng
Published: May 2022

Pulmonary hypertension (PAH) is a proliferative disease of pulmonary blood vessels, but the pathogenesis of pulmonary hypertension is still unclear. This article explores the role of tumor necrosis factor-α (TNF-α), tissue factor (TF), and coagulation function (CF) in the pathogenesis of PAH. PAH is often accompanied by vascular intima injury and muscular arterial media thickening. Coupled with the wide application of nanotargeted drugs in recent years, a targeted nanocarrier encapsulating sildenafil was prepared in this study. The particle size, PDI, zeta potential, drug loading, and encapsulation efficiency were

194.32
±
17.31
 
nm

,

0.28
±
0.02

,

−
6.34
±
0.33

, 24.61%, and 70.52%. The monocrotaline PAH rat model was constructed, and it was found that the levels of TNF-α, TF, and CF in the peripheral blood of PAH rats were abnormally increased. 30 PAH rats were randomly divided into 5 groups and injected with saline (NS group), sildenafil (sildenafil group), target the nanoempty carrier (TNC-E group), ordinary nanocarrier encapsulated sildenafil (CNC-sildenafil group), and targeted nanocarrier encapsulate sildenafil (TNC-sildenafil group). Compared with the NS group, the mean pulmonary artery pressure in the TNC-sildenafil group was lower (

P
<
0.05

). Compared with the normal rat group, the pulmonary small blood vessel media thickness, TNF-α level, TF level, and the area of myocardial cells were increased in the NS group, sildenafil group, TNC-E group, and CNC-sildenafil group (

P
<
0.05

). Compared with the NS group, the pulmonary small blood vessel media thickness, myocardial cell area, and the levels of TNF-α and TF in the TNC-sildenafil group were reduced (

P
<
0.05

). Targeting nanocarrier encapsulation of sildenafil can obviously reduce the average pulmonary artery pressure in rats with pulmonary hypertension, improve pulmonary vascular media proliferation and myocardial hypertrophy, and restore the levels of TNF-α, TF, and CF to a normal state.
MicroRNA-299a-5p Protects against Spinal Cord Injury through Activating AMPK Pathway
Authors: Zhang Zong-Ze , Xian Shu-Yue , Bao Chong , Chen Feng
Published: May 2022

Objective. Inflammation and oxidative stress are implicated in the pathogenesis of spinal cord injury (SCI). The present study is aimed at investigating the function and molecular basis of microRNA-299a-5p (miR-299a-5p) during SCI in mice. Methods. Mice were exposed to SCI surgery and then intrathecally injected with the agomir, antagomir, or matched negative controls of miR-299a-5p to overexpress or silence miR-299a-5p. To inhibit AMP-activated protein kinase (AMPK), mice were intraperitoneally injected with compound C (CC). To overexpress pH domain and leucine-rich repeat protein phosphatase 1 (PHLPP1), lentiviral vectors were used. Results. The miR-299a-5p expression in the spinal cord was dramatically reduced by SCI stimulation. The miR-299a-5p agomir prevents, while the miR-299a-5p antagomir exacerbates inflammation, oxidative stress, and SCI in mice. Mechanistically, we found that miR-299a-5p directly inhibited PHLPP1 and subsequently activated AMPK pathway. The PHLPP1 overexpression of AMPK inhibition with either genetic or pharmacologic methods dramatically abolished the miR-299a-5p agomir-mediated protective effects against SCI. Conclusion. miR-299a-5p protects against spinal cord injury through activating AMPK pathway.
Improved Vessel Trajectory Prediction Model Based on Stacked-BiGRUs
Authors: Xu Yang , Zhang Jilin , Ren Yongjian , Zeng Yan , Yuan Junfeng , Liu Zhen , Wang Lei , Ou Dongyang
Published: May 2022

An intelligent maritime navigation system is expected to play an important role in the realm of Internet of Vessels (IoV). As a key technology in navigation systems, vessel trajectory prediction technology is critical to the IoV. Automatic identification system (AIS), an automated tracking system, is used extensively for vessel trajectory prediction. However, certain characteristics in the AIS data, such as the large number of anchored trajectories in the area, anomalous sharp turns of some trajectories, and the behavioral differences of vessels in different segments, limit the prediction accuracy. In this study, we propose a novel vessel trajectory prediction model for accurate prediction with the following characteristics: (1) an anchor trajectory elimination algorithm to eliminate anchor trajectories; (2) a statistical trajectory restoration algorithm to repair sharp turning; (3) a two-stage clustering algorithm (D-KMEANS) to distinguish vessel behavior; and (4) a deep bidirectional gate recurrent unit (Stacked-BiGRUs) model to predict vessel trajectory and compare the accuracy of the model before and after improvement. The results show that the mean square error and the mean absolute error of the improved model are reduced by 27% and 46%, respectively. This research shows good potential for maritime navigation early warning and safety.
Study on Integration and Application of Artificial Intelligence and Wireless Network in Piano Music Teaching
Authors: Li Jiluo
Published: May 2022

Until 2019, most people had never faced the situation that would be their life-changing moment. Most universities are conducting classes for their students with the help of virtual classrooms indicating massive technological growth. However, this development does not take enough time to reach the students and the teaching person. Within five to six months of successful projects, most application producers have launched their official sites to conduct online classes and test ways for students. The introduction of virtual classes is not the only example of technological advancement; cloud computing, artificial intelligence, and deep learning have collaborated to produce appropriate, fine, and less error-prone results in all such fields of teaching. These technological advancements have given way to design models created with the wireless networks that are being made, particularly for music-related courses. The Quality-Learning (Q-Learning) Algorithm (QLA) is a pillar study for improving the implementation of artificial intelligence in music teaching in this research. The proposed algorithm aids in improving the accuracy of music, its frequency, and its wavelength when it passes. The proposed QLA is compared with the existing K-Nearest Neighbour (KNN) algorithm, and the results show that QLA has achieved 99.23% accuracy in intelligent piano music teaching through wireless network mode.
Study on the Mechanism of Shenjing Guben Prescription Regulating PI3K and NRF2 Signaling Pathway in the Treatment of Immune Infertility
Authors: Liu Handu , Xue Jianguo , Mo Hui
Published: May 2022

Objective. To explore the mechanism of Shenjing Guben prescription (SP) in the treatment of immune infertility by regulating PI3K-NRF2/p38 signal pathway. Methods. 60 adult male SD rats were randomly divided into control group (NC group), ACN group, low concentration AP intervention group (low group), middle concentration SP intervention group (middle group), and high concentration SP intervention group (high group). 12 rats in each group were administered by gavage once a day, 6 days/w, and the rats were killed after 28 days. Bilateral testis and epididymis were removed and weighed and organ coefficients were calculated, and testicular histopathological sections were prepared to evaluate the changes of testicular tissue structure. The relative expression levels of PI3K, MKK7, JNK, p38 mRNA, and protein in testis were measured by QRT-PCR and western blot. Results. (1) Compared with the control group, the proportion of grade A and B sperms in ACN group increased significantly, and the proportion of grade D sperm decreased significantly (

P

 < 0.05). After SP intervention, compared with ACN group, there was no significant difference in the proportion of sperm at all levels in low, medium, and high SP intervention groups (

P

 > 0.05). (2) Compared with the control group, the sperm VCL, VSL, VAP, and mad in ACN group increased significantly, and the BCF decreased significantly (

P

 < 0.05). After SP intervention, compared with ACN group, there was no significant difference in sperm motility parameters among low, medium, and high SP intervention groups (

P

 > 0.05). (3) Compared with the control group, the activities of AKP and SDH in testicular tissue of rats in ACN group decreased significantly (

P

 < 0.05). After SP intervention, compared with ACN group, AKP activity increased significantly and LDH activity decreased significantly in low, medium, and high SP intervention groups (

P

 < 0.05). (4) Compared with the control group, the expression levels of PI3K, p-PI3K, MKK7, p-MKK7, JNK, p-JNK, p38, and p-p38 proteins and the ratios of p-JNK/JNK and p-p38/p38 increased in the testis of ACN group (

P

 < 0.05). After SP intervention, compared with ACN group, the protein expression levels of PI3K, p-PI3K, MKK7, p-MKK7, JNK, p-JNK, p38, and p-p38 in testicular tissue of SP intervention group decreased, and the ratio of p-JNK/JNK and p-p38/p38 decreased (

P

 < 0.05). Conclusion. SP can reduce the oxidative stress of testis induced by ACN and inhibit the activation of PI3K-NRF2/p38 signal pathway.
A Multicriteria English Teaching Decision Model Based on Deep Learning
Authors: Zhang Jiachen
Published: May 2022

In any stage of the teaching process, the teaching behavior depends on the decision of teachers. For English teachers, the English teaching decision level directly determines the course quality and the mining of learner potential. The existing studies only focus on a single teaching stage and involve one decision maker. The scientific level of decision is yet to be examined. Therefore, this paper develops a multicriteria English teaching decision (MCETD) model based on deep learning. Specifically, the author summarized the internalization and generation of MCETDs and expounded the generation mechanism of such decisions. Next, the problem of MCETD was described and mathematically modeled. After that, a neural network was constructed to weigh decision criteria and decision makers. In addition, the author explained how to comprehensively rank and generate MCETD schemes. Through experiments, the author obtained the information of decision matrix and preference ranking of decision schemes from decision makers and validated the effectiveness of the proposed model.
Neural Network-Based Dynamic Segmentation and Weighted Integrated Matching of Cross-Media Piano Performance Audio Recognition and Retrieval Algorithm
Authors: Wang Tianshu
Published: May 2022

This paper presents a dynamic segmentation and weighted comprehensive matching algorithm based on neural networks for cross-media piano performance audio recognition and retrieval. The 3D convolutional neural network process is separated to compress the network parameters and improve the computational speed. Skip connection and layer-wise learning rate solve the problem that the separated network is challenging to train. The piano performance audio recognition is facilitated by shuffle operation. In pattern recognition, music retrieval algorithms are gaining more and more attention due to their ease of implementation and efficiency. However, the problems of imprecise dynamic note segmentation and inconsistent matching templates directly affect the accuracy of the MIR algorithm. We propose a dynamic threshold-based segmentation and weighted comprehensive matching algorithm to solve these problems. The amplitude difference step is dynamically set, and the notes are segmented according to the changing threshold to improve the accuracy of note segmentation. A standard score frequency is used to transform the pitch template to achieve input normalization to enhance the accuracy of matching. Direct matching and DTW matching are fused to improve the adaptability and robustness of the algorithm. Finally, the effectiveness of the method is experimentally demonstrated. This paper implements the data collection and processing, audio recognition, and retrieval algorithm for cross-media piano performance big data through three main modules: the collection, processing, and storage module of cross-media piano performance big data, the building module of audio recognition of cross-media piano performance big data, and the dynamic precision module of cross-media piano performance big data.
Early Diagnosis Value of DCE-MRI Hemodynamic Parameters in Hepatocellular Carcinoma
Authors: Mu Xixi , Zhong Yue , Zhang Xuan , Qu Changjun
Published: May 2022

Objective. To probe into the early diagnosis value of transfer coefficient (

K

trans

) and rate constant (

K

ep

) of the dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) hemodynamic parameters in patients with hepatocellular carcinoma (HCC). Methods. Fifty patients with HCC diagnosed in our hospital from May 2017 to May 2020 were studied retrospectively as the patient group (PG), and 45 cases with benign liver nodules diagnosed in our hospital during the same period were collected as the control group (CG).

K

trans

,

K

ep

, and AFP levels were compared between PG and CG. The diagnostic value of

K

trans

and

K

ep

in HCC were observed, and their correlations with patient clinical data were analyzed. The diagnostic value of

K

trans

and

K

ep

combined with AFP in clinical staging, differentiation degree, and distant metastasis was compared. Results.

K

trans

,

K

ep

, and AFP were notably higher in cases than in controls (

P
<
0.05

), indicating their high diagnostic value in HCC.

K

trans

and

K

ep

present elevated expression in HCC patients with clinical stage III-IV, low differentiation, and distant metastasis (

P
<
0.05

). Furthermore, it is found that the combined detection with either

K

trans

or

K

ep

can improve the clinical diagnostic value of AFP in the clinical stage and differentiation of HCC. However, the combined diagnosis showed little effect in raising the sensitivity of AFP in distant metastasis. Conclusion. DCE-MRI hemodynamic parameters

K

trans

and

K

ep

have high clinical value in early diagnosis and differentiation of HCC patients.