bluuebunny/crossref_metadata_2025 huggingface dataset:
Dynamic Rendering-Aware VR Service Module Placement Strategy in MEC Networks
Authors: Liu Chunyu , Zhang Heli , Li Xi , Ji Hong
Published: August 2022

Combining multiaccess edge computing (MEC) technology and wireless virtual reality (VR) game is a promising computing paradigm. Offloading the rendering tasks to the edge node can make up for the lack of computing resources of mobile devices. However, the current offloading works ignored that when rendering is enabled at the MEC server, the rendering operation depends heavily on the environment deployed on this MEC serve. In this paper, we propose a dynamically rendering-aware service module placement scheme for wireless VR games over the MEC networks. In this scheme, the rendering tasks of VR games are offloaded to the MEC server and closely coupled with service module placement. At the same time, to further optimize the end-to-end latency of VR video delivery, the routing delay of the rendered VR video stream and the costs of the service module migration are jointly considered with the proposed placement scheme. The goal of this scheme is to minimize the sum of the network costs over a long time under satisfying the delay constraint of each player. We model our strategy as a high-order, nonconvex, and time-varying function. To solve this problem, we transform the placement problem into the min-cut problem by constructing a series of auxiliary graphs. Then, we propose a two-stage iterative algorithm based on convex optimization and graphs theory to solve our object function. Finally, extensive simulation results show that our proposed algorithm can ensure low end-to-end latency for players and low network costs over the other baseline algorithms.
The Application of Big Data Technology in the Construction of Financial Shared Service Center of Agricultural Enterprise Group
Authors: Wang Chen
Published: August 2022

The prerequisite for the reasonable construction and successful implementation of the financial sharing center of the agricultural enterprise group is that the agricultural enterprise group must fully understand the financial sharing center, understand the steps and key points of its construction, and comprehensively design and re-engineer the business process. This paper combines the big data technology to construct the financial sharing center system of agricultural enterprise groups, combines the machine learning algorithm to improve the big data processing algorithm, and builds the intelligent financial sharing platform with the support of the improved algorithm, and builds the overall system architecture and operation process. After constructing the system, the performance verification and practical verification of this system are carried out through experimental research. From the research results, it can be seen that the system constructed in this paper has good data processing effects and data sharing effects, and has good security, which meets the financial sharing needs of agricultural enterprise groups.
Determining the Pricing Strategy and Pricing the Products of Mobile Games: Mathematical Model Approach
Authors: Budak Gerçek , Özen Barış
Published: August 2022

In the technology era, new sectors, occupations, and products or services related to technology arise. Mobile gaming industry is one of those sectors with the technological developments of personal mobile devices. This sector is rapidly growing in terms of the number of companies, employees, games, and financial income; however, this situation increases the competition and companies in this sector survive as if they succeed a sustainable profit from the game by selling their products or services. These products can be grouped into four which are the game itself, cosmetic products, in-application purchases, and advertisements or product placements during the gameplay. This study outlines a two-staged decision process for deciding which products should be priced and how much they should be charged for every customer. The first stage is an enumeration of all sixteen alternatives of pricing strategies for four products which are game, in-game boost-ups, cosmetics and advertisements, and expert decision to choose among those alternatives which would fit to the concerned mobile game. In the second stage, a mathematical model is used to price for obtaining the maximum profit for the company. Another mathematical model is also proposed for pricing the products differently for each customer according to their psychological player profile as if the decision-maker prefers such a pricing strategy. Implication and extensions of the models are discussed, and their real-life application is also presented in the study.
Understanding User-Level IP Blocks on the Internet
Authors: Ren Yimo , Li Hong , Li Ruinian , Zhu Hongsong , Sun Limin
Published: August 2022

Generally, the devices on the Internet are identified by IP addresses. The users of IPs are those who use IPs on the Internet and are always different from their registers and operators. Since IPs are used as unique identifiers of devices, knowing users of IPs according to their multisource data is critical for experts to protect the security of the network. At present, there are only few methods to mine the users of IPs from their public data. To make matters worse, the existing methods do not make effective use of a large amount and multisource data, such as certificates, protocol banner, rDNS, location, topology, etc. As a result, the performances of existing methods are largely limited. To tackle this issue, we proposed ULIB, short for “Understanding User-Level IP Blocks on the Internet.” ULIB is based on improved community detection to mine the users for as many blocks of IPs as possible. By analysing comprehensive attributes of IPs, ULIB is able to recognize users effectively. Meanwhile, we evaluated our methodology in the real world and the experiments demonstrated that the accuracy of ULIB is 74.20% and the coverage is 28.90% in a city of China, which outperforms other existing methods.
Building Information Modeling Assisted Carbon Emission Impact Assessment of Prefabricated Residential Buildings in the Design Phase: Case Study of a Chinese Building
Authors: Wang Haining , Zhao Liang , Zhang Hong , Liu Pei , Sun Bo , Hou Keming
Published: August 2022

The construction industry is energy-intensive and labor-intensive, which has great potential in reducing energy demand and carbon emissions. The construction method of off-site prefabricated components has many advantages to make it a good substitute for traditional methods. The purpose of this paper is to reduce the carbon emissions of prefabricated residential concrete members by improving the standardization rate of prefabricated components in the architectural design stage. In addition, this paper also uses building information modeling technology to establish Revit models and develops Revit using C# language to achieve rapid calculation of the prefabrication rate of building and standardization rate of components. The calculation results of the case show that, in the design stage, the carbon emissions are reduced by 2034.16 kg CO2e by improving the standardization rate of prefabricated components, accounting for 0.1552% of the carbon emissions of all prefabricated components. This study can help the designer reduce the carbon emissions of prefabricated components, and this technology may make a significant contribution in improving the environmental sustainability of prefabricated buildings.
Analysis of Rational Drug Use Effect under Hospital Drug Control System
Authors: Huo Haoli , Li Xiaoyan , Li Hui , Wang Haiye , Ma Xin , Chen Chen , Zhang Hongfeng
Published: August 2022

Objective. To describe and assess the hospital drug control system’s measures. Methods. From 2017 to 2019, examine the changes in medication percentage, important monitoring drug amount, top 10 medications amount, and usage rate of prophylactic antibiotics for type I incisions. Results. The proportion of pharmaceuticals remains below 30%, the number of significant monitoring drugs has decreased, the top ten drugs have shifted from adjuvant to therapeutic drugs, and the use of prophylactic antibiotics for type I incisions has decreased by 10%. Conclusion. The percentage of medications that met requirements by using the drug control system has steadily decreased, and the number of pharmaceuticals for important monitoring pharmaceuticals has steadily decreased, in accordance with national medical insurance policy, as well as improved rational drug usage.
Exploring Early Physical Examination Diagnostic Biomarkers for Alzheimer’s Disease Based on Least Absolute Shrinkage and Selection Operator
Authors: Lin Hua , Tang Shiting , Liang Ling , Chen Liechun , Zou Chun , Zou Donghua
Published: August 2022

Neurodegenerative diseases such as Alzheimer’s disease (AD) are an increasing public health challenge. There is an urgent need to shift the focus to accurate detection of clinical AD at the physical examination stage. The purpose of this study was to identify biomarkers for AD diagnosis. Differential expression analysis was performed on a dataset including prefrontal cortical samples and peripheral blood samples of AD to identify shared differentially expressed genes (DEGs) shared between the two datasets. In addition, a minimum absolute contraction and selection operator (LASSO) model based on shared-DEGs identified nine signature genes (MT1X, IGF1, DLEU7, TRIM36, PTPRC, WNK2, SPG20, C8orf59, and BRWD1) that accurately predict AD occurrence. Enrichment analysis showed that the signature gene was significantly associated with the AD-related p53 signaling pathway, T-cell receptor signaling pathway, HIF-1 signaling pathway, AMPK signaling pathway, and FoxO signaling pathway. Thus, our results identify not only biomarkers for diagnosing AD but also potentially specific pathways. The AD biomarkers proposed in this study could serve as indicators for prevention and diagnosis during physical examination.
The Predictive Value of Changes in the Absolute Counts of Peripheral Lymphocyte Subsets for Progression and Prognosis in Breast Cancer Patients
Authors: Liu Aqing , Xia Ying , Li Wentao , Zhang Guan , Liu Yunhe , Ye Songshan , Zhao Zhijie-ruo , Yang Yanjie , Jia Yingjie , Guo Yongtie , Liu Xu , Chen Huayu , Yu Jianchun
Published: August 2022

Background. As the number and proportion of lymphocyte subsets are an important indicator of the immune function, an in depth understanding of the immune function of patients with malignant tumor has important clinical values for the treatment, prognosis, and evaluation of the disease. This retrospective study was to evaluate the clinical value of the absolute counts of lymphocyte subsets as potential blood biomarkers for progression and prognosis in breast cancer patients. Methods. A total of 237 BC patients and 55 age‐matched female normal healthy donors were included in this study. Flow cytometry was used to determine the absolute counts and the percentages of CD3+, CD4+, CD8+, B, and NK cells. The receiver operating characteristic curve (ROC) was used to evaluate the accuracy of absolute count of lymphocyte subsets in the curative efficacy assessment. The clinicopathological parameters influencing the disease progression were determined by Cox proportional hazards regression. Progression‐free survival (PFS) was estimated using the Kaplan–Meier method with the log‐rank test. Results: Compared with the healthy donors, the absolute counts of lymphocyte subsets in patients decreased significantly. ROC analysis showed that the area under the curve of the CD4+ absolute count was 90% (95% confidence interval 0.859–0.940), and the sensitivity and specificity were 80.9% and 85.3%, respectively. The analysis of Cox regression showed that the cutoff value of the CD4+ absolute count ≥451 cells/μL might be a favorable prognostic factor. Multivariate analysis of prognostic factors of PFS showed that the CD4+ and CD8+ absolute count were independent factors for predicting PFS. Conclusions. The remarkably impaired absolute counts of the CD3+, CD4+, CD8+, B, and NK cells in patients with breast cancer can be used as potential susceptible biomarkers to evaluate the patient’s immune status. The higher level of CD4+ and CD8+ absolute counts probably contributed to the longer PFS and favorable outcome of BC patients.
Application of Nursing Intervention Plan Based on Symptom Management Theory among Breast Cancer Patients
Authors: Xu Qingqing , Chen Yu , Shen Xiaping , Fang Qunying
Published: August 2022

In order to explore the application effect of nursing intervention based on symptom management theory in breast cancer patients, a total of 120 breast cancer patients who were hospitalized in the Thyroid and Breast Surgery Department of Zhejiang Xiaoshan Hospital from July 2018 to July 2021 were selected as the research subjects. Patients from the control group received routine nursing, while patients from the intervention group underwent nursing interventions based on symptom management theory. Before and after the intervention, symptom distress, Herth Hope Index, quality of life, self‐rating anxiety scale (SAS), self‐rating depression scale (SDS), visual analogue score (VAS), and Pittsburgh sleep quality index (PSQI) were evaluated in two groups. The results showed that the symptom severity score and the symptom distress score, SAS scores, SDS scores, VAS scores, and PSQI scores in the intervention group were significantly lower than those in the control group, while the Herth Hope Index scores and FACT‐B scores in the intervention group were obviously higher than those in the control group (all P < 0.05) after intervention. In conclusion, nursing interventions based on symptom management theory could decrease symptom distress among breast cancer patients, increase their hope levels, improve their life quality, relieve the negative emotions, enhance the sleep quality, and reduce their pain. It is worthy of clinical application.
Sensor Vegetable Greenhouse and Agricultural Product Supply Chain Management Based on Improved Neural Network
Authors: Dou Dandan
Published: August 2022

In recent years, people have begun to collect environmental data in vegetable greenhouses. Therefore, this article studies the current internal control technology of vegetable greenhouses, and improves the sensor application in vegetable greenhouses, in a targeted manner by combining with the improved neural network algorithm. The model has more accurate prediction accuracy than traditional BP. By using the Android client and ZigBee artificial intelligence control technology it creates the most suitable living conditions for the vegetables, fruits, and other crops in the vegetable greenhouse by controlling the various valves, sun visors, and light supplementary switches inside the vegetable greenhouse. The simulation results show that the model proposed in this article has higher convergence accuracy. In addition, this article applies the improved neural network to the management of the agricultural product supply chain, starting from the agricultural product supply chain and agricultural product supply chain management. Based on this, the analytic hierarchy process is used to explore the influencing factors of agricultural product supply chain management, and the analysis shows that consumers are targeting different consumer demand raised by the agricultural product supply chain. The improved neural network provides new ideas for the research of sensor vegetable greenhouses and agricultural product supply chain management.
Macro Education Approach to Improve Learning Interest under the Background of Artificial Intelligence
Authors: Hou Jianfeng , Li Zhaohong , Liu Guangying
Published: August 2022

With the advent of the “Internet+” era, with the rapid development of emerging technologies such as the Internet of Things, cloud computing, big data, and artificial intelligence, the era of the technological change in education has arrived, with diversification of resources and large-scale data. And the intelligence of computing provides an opportunity for the research and practice of personalized support services. Personalized learning is the future learning method under the demands of smart education, and the learner’s interest feature model is the core of personalized learning services. Although the research on smarter classrooms has achieved certain results, there are still shortcomings that cannot be ignored, that is, how to use smarter classrooms to meet the “personalized needs” of learners and give students “personalized feedback” is still an urgent problem to be solved. Therefore, building a student interest model in a smart learning environment will help teachers better capture students’ learning interests and personalized needs, so as to provide them with personalized learning services.
Research on the Factors Damaging Hydrogen Peroxide Low-Temperature Plasma Sterile Packaging Bags and the Control of Link Quality
Authors: Shen Yanfen , Wu Ying , Sun Haijuan , Wang Shengao
Published: August 2022

Objective. After discussing the factors damaging hydrogen peroxide low-temperature plasma sterile packaging bags (hereinafter referred to as Tyvek packaging bags), the damage rate of Tyvek packaging bags is lowered through the control of link quality, so as to guarantee the quality of sterile packaging bags and the safety of patients. Methods. Design questionnaire and registration form by investigating 8606 instrument packaging bags sterilized by hydrogen peroxide low-temperature plasma from January 2019 to December 2019, the controllable factors damaging Tyvek packaging bags are analyzed from four aspects: instrument packaging, sterilization, transfer, and storage. By taking targeted interventions on 8155 instrument packaging bags sterilized from January 2020 to December 2020, the intervention effects of the key links and the damage rate are evaluated. Results. The main factors damaging Tyvek packaging bags mainly include improper transfer, storage, and management of instrument packing bags; improper use of instrument boxes; improper loading and uploading operations of sterilization; and the wrong size of packaging bags. For these factors, related intervention measures shall be adopted to control the link quality so as to lower the damage rate from 3.54% in the control group to 0.20% in the experimental group. The differences in damage rate are of statistical significance (

P
<
0.01

). Conclusion. Tyvek packaging bags are influenced by controllable factors. Through reasonable link control and standard operations, the sterile packaging bags can be kept sterile from the end of sterilization to the usage by patients, which guarantees the safety of patients and is worthy of reference.
Inspiratory Muscle Rehabilitation Training in Pediatrics: What Is the Evidence?
Authors: Bhammar Dharini M. , Jones Harrison N. , Lang Jason E.
Published: August 2022

Pulmonary rehabilitation is typically used for reducing respiratory symptoms and improving fitness and quality of life for patients with chronic lung disease. However, it is rarely prescribed and may be underused in pediatric conditions. Pulmonary rehabilitation can include inspiratory muscle training that improves the strength and endurance of the respiratory muscles. The purpose of this narrative review is to summarize the current literature related to inspiratory muscle rehabilitation training (IMRT) in healthy and diseased pediatric populations. This review highlights the different methods of IMRT and their effects on respiratory musculature in children. Available literature demonstrates that IMRT can improve respiratory muscle strength and endurance, perceived dyspnea and exertion, maximum voluntary ventilation, and exercise performance in the pediatric population. These mechanistic changes help explain improvements in symptomology and clinical outcomes with IMRT and highlight our evolving understanding of the role of IMRT in pediatric patients. There remains considerable heterogeneity in the literature related to the type of training utilized, training protocols, duration of the training, use of control versus placebo, and reported outcome measures. There is a need to test and refine different IMRT protocols, conduct larger randomized controlled trials, and include patient-centered clinical outcomes to help improve the evidence base and support the use of IMRT in patient care.
Mechanism of Zhinao Capsule in Treating Alzheimer’s Disease Based on Network Pharmacology Analysis and Molecular Docking Validation
Authors: Ma Yanzhen , Huang Shaopeng , Jiang Hui , Yang Wenming
Published: August 2022

Objective. This study aimed to determine the active components of Zhinao capsule (ZNC) and the targets in treating Alzheimer’s disease (AD) so as to investigate and explore the mechanism of ZNC for AD. Methods. The active components and targets of ZNC were determined from the traditional Chinese medicine systems pharmacology database (TCMSP). The target genes of AD were searched for in GeneCards. Cytoscape was used to construct an herb-component-target-disease network. A protein-protein interaction (PPI) network was constructed by STRING. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the OmicShare. UCSF Chimera and SwissDock were used for molecular docking verification. Finally, four key target genes were validated by Western blotting. Results. In total, 55 active components, 287 targets of active components, 1197 disease genes, and 134 common genes were screened, which were significantly enriched in 3975 terms of biological processes (BP), 284 terms of cellular components (CC), 433 terms of molecular functions (MF), and 245 signaling pathways. Caspase-3 (CASP3) and beta-sitosterol, tumor necrosis factor-alpha (TNF-α) and quercetin, vascular endothelial growth factor A (VEGFA) and baicalein, and mitogen-activated protein kinase 1 (MAPK1) and quercetin showed good-to-better docking. Moreover, ZNC not only downregulated CASP3 and TNF-α protein expression but also upregulated the protein expression of VEGFA and MAPK1. Conclusions. The active components of ZNC, such as beta-sitosterol, quercetin, and baicalein may act on multiple targets like CASP3, VEGFA, MAPK1, and TNF-α to affect T cell receptor (TCR), TNF, and MAPK signaling pathway, thereby achieving the treatment of AD. This study provides a scientific basis for further exploring the potential mechanism of ZNC in the treatment of AD and a reference for its clinical application.
An Optimization Method of High-Speed Railway Rescheduling to Meet Unexpected Large Passenger Flow
Authors: Zhao Junduo , Li Haiying , Meng Lingyun , Miao Jianrui
Published: August 2022

In the rapidly changing multimodal transportation market, not only the obligation in providing train services but also the responsibility in helping other transportation modes to meet emergencies are instrumental for maximizing the generalized benefit of railway companies, leading to an increased utilization. This paper proposes an optimization framework, which includes multiple dispatching measures of arranging residual seats, modifying stopping plans, and inserting additional trains, to design a rescheduling operation plan on a high-speed rail corridor to meet the passenger demand of unexpected large passenger flow (ULPF), which is generated from the disruption of other transportation modes. Considering the revenues of shifting passengers and the costs of the three dispatching measures as two objectives, we formulate a linear integer programming (LIP) model by employing a time-space network to obtain an optimization rescheduling operation plan. Several experiments based on the Beijing-Shanghai high-speed railway corridor are conducted to evaluate the effectiveness and efficiency of the proposed model. The experimental results demonstrate that the proposed model can be used to obtain a reasonable rescheduling operation plan for serving the passengers from ULPF within an acceptable calculation timeframe.
Analysis and Application of Data Mining Technology for College English Education Integration
Authors: Chen Jing
Published: August 2022

With the development and application of information fusion technology, English education can realize intelligent application under multi-information fusion technology. In view of the low degree of educational informationization and single application of intelligent methods in the process of education, this paper puts forward the application of multi-technology in English education, so as to improve the education level and application skills. Firstly, this paper explains the educational application technology, especially the analysis of decision tree and linear regression method in data mining technology, and puts forward the framework and system structure diagram of English education system. In the experiment, the application of different methods is compared, and the results show that the decision number method has higher weight in weight analysis. According to the situation of different course quantity, 50%–80% of the course workload can be completed under multi-information fusion. However, in the amount of homework completion, most of the personnel can complete the homework, which has a good application effect. In different English majors, different research methods have different educational purposes and different teaching effects. Through the system interface and system performance testing, using the data mining method has better UI test results and shorter test time.
Human Capital Digital Incentive Mechanism Construction Based on Deep Learning
Authors: He Jie , Zhang Jianhua
Published: August 2022

The introduction of human capital can be traced back to the ancient Greek period, emphasizing the important role of knowledge and skills in the production and life process. Human capital reward mechanism promotes modern social and economic development and is an important part of social and economic growth. The core management of the enterprise is the management of human capital, and the central work of human capital management is the incentive of human capital. Many enterprises are now facing difficulties in industrial operation, serious brain drain, and lack of core competitiveness in the market. As a result, enterprises cannot adapt to the speed and requirements of today’s social and economic development. One of the important reasons is that the enterprise lacks attention to the value of the human capital incentive system, or the human capital incentive system of the enterprise is unreasonable, which leads to a series of problems such as poor employee enthusiasm and low enterprise performance. How to establish a reasonable and effective incentive mechanism to mobilize the enthusiasm and creativity of employees has become a problem that enterprises must pay attention to. Taking the technical managers and general technicians of a high-tech enterprise as an example, combined with the deep learning method, the article made a detailed analysis of the four major incentive factors of enterprise human capital. It made employees’ satisfaction with corporate cultural incentives reaching 56.1%, which showed that emotional motivation was also one of the key factors for employees to be satisfied with the corporate incentive system.
Density Functional Theoretical Computational Studies on 3-Methyl 2-Vinyl Pyridinium Phosphate
Authors: Kanagathara N. , Thanigaiarasu V. J. , Sabari V. , Elangovan S.
Published: August 2022

The molecular structure of 3-methyl 2-vinyl pyridinium phosphate (3M2VPP) has been optimized by using Density Functional Theory using B3LYP hybrid functional with 6-311++G (d, p) basis set in order to find the whole characteristics of the molecular complex. The theoretical structural parameters such as bond length, bond angle, and dihedral angle are determined by DFT methods and are well agreed with the single crystal X-ray diffraction parameters. Theoretical vibrational, highest occupied molecular orbital - lowest unoccupied molecular orbital (HOMO-LUMO), natural bonding orbital (NBO), and electrostatic potential (ESP) analyses have also been performed. Based on the potential energy distribution (PED), the complete vibrational assignments, analysis, and correlation of the compound’s fundamental modes have been determined. Natural bonding orbital (NBO) analysis is used to evaluate the intramolecular charge transfer and hyper-conjugative interaction of the molecule. B3LYP/6-311++G (d, p) basis set determines the electronic properties such as HOMO–LUMO energies and is used to understand the kinetic stability and chemical reactivity of the studied compound. Molecular electrostatic potential (MEP) is used to investigate the electron density distribution and chemical reactive sites of 3M2VPP. The dipole moment, total polarizability, and the first-order hyperpolarizability calculations have been carried out for the studied molecule. Hirshfeld surface analysis has been done to study the intermolecular interactions in the studied complex.
Factorization
Q
-Learning Initialization for Parameter Optimization in Cellular Networks
Authors: Zeng Bosen , Zhong Yong , Niu Xianhua , Tang Ji
Published: August 2022

Q

-value initialization significantly influences the efficiency of

Q

-learning. However, there have been no precise rules to choose the initial

Q

-values as yet correctly, which are usually initialized to a default value. This paper proposes a novel

Q

-value initialization framework for cellular network applications and factorization

Q

-learning Initialization (FQI). The proposed method works as an add-on of

Q

-learning that automatically and efficiently initializes the nonupdated

Q

-values by utilizing the correlation model of the visited experiences built on factorization machines. In an open-source VoLTE network, FQI was introduced into

Q

-learning and four improved variants (Dyna

Q

-learning,

Q

λ

-learning, double

Q

-learning, and speedy

Q

-learning) for performance comparison. The experiment results demonstrate that the factorized algorithms based on FQI substantially outperform the original algorithms, often learning policies that attain 1.5-8 times higher final performance measured by the episode reward and the convergence episodes.
Preoperative Prediction of Axillary Lymph Node Metastasis in Breast Cancer Based on Intratumoral and Peritumoral DCE‐MRI Radiomics Nomogram
Authors: Liu Ying , Li Xing , Zhu Lina , Zhao Zhiwei , Wang Tuan , Zhang Xi , Cai Bing , Li Li , Ma Mingrui , Ma Xiaojian , Ming Jie
Published: August 2022

Objective. To investigate the value of preoperative prediction of breast cancer axillary lymph node metastasis based on intratumoral and peritumoral dynamic contrast enhancement magnetic resonance imaging (DCE‐MRI) radiomics nomogram. Material and Methods. In this study, a radiomics model was developed based on a training cohort involving 250 patients with breast cancer (BC) who had undergone axillary lymph node (ALN) dissection between June 2019 and January 2021. The intratumoral and peritumoral radiomics features were extracted from the second postcontrast images of DCE‐MRI. Based on filtered radiomics features, the radiomics signature was built by using the least absolute shrinkage and selection operator method. The Support Vector Machines (SVM) learning algorithm was used to construct intratumoral, periatumoral, and intratumoral combined periatumoral models for predicting axillary lymph node metastasis (ALNM) in BC. Nomogram performance was determined by its discrimination, calibration, and clinical value. Multivariable logistic regression was adopted to establish a radiomics nomogram. Results. The intratumoral combined peritumoral radiomics signature, which was composed of fifteen ALN status‐related features, showed the best predictive performance and was associated with ALNM in both the training and validation cohorts (P < 0.001). The prediction efficiency of the intratumoral combined peritumoral radiomics model was higher than that of the intratumoral radiomics model and the peritumoral radiomics model. The AUCs of the training and verification cohorts were 0.867 and 0.785, respectively. The radiomics nomogram, which incorporated the radiomics signature, MR‐reported ALN status, and MR‐reported maximum diameter of the lesion, showed good calibration and discrimination in the training (AUC = 0.872) and validation cohorts (AUC = 0.863). Conclusion. The intratumoral combined peritumoral radiomics model derived from DCE‐MRI showed great predictive value for ALNM and may help to improve clinical decision‐making for BC.
Marine-Derived Piericidin Diglycoside S18 Alleviates Inflammatory Responses in the Aortic Valve via Interaction with Interleukin 37
Authors: Li Shunyi , She Jianglian , Zeng Jingxin , Xie Kaiji , Luo Zichao , Su Shuwen , Chen Jun , Xian Gaopeng , Cheng Zhendong , Zhao Jing , Li Shaoping , Xu Xingbo , Xu Dingli , Tang Lan , Zhou Xuefeng , Zeng Qingchun
Published: August 2022

Calcific aortic valve disease (CAVD) is a valvular disease frequently in the elderly individuals that can lead to the valve dysfunction. Osteoblastic differentiation of human aortic valve interstitial cells (HAVICs) induced by inflammation play a crucial role in CAVD pathophysiological processes. To date, no effective drugs for CAVD have been established, and new agents are urgently needed. Piericidin glycosides, obtained from a marine-derived Streptomyces strain, were revealed to have regulatory effects on mitochondria in previous studies. Here, we discovered that 13-hydroxypiericidin A 10-O-α-D-glucose (1→6)-β-D-glucoside (S18), a specific piericidin diglycoside, suppresses lipopolysaccharide- (LPS) induced inflammatory responses of HAVICs by alleviating mitochondrial stress in an interleukin (IL)-37-dependent manner. Knockdown of IL-37 by siRNA not only exaggerated LPS-induced HAVIC inflammation and mitochondrial stress but also abrogated the anti-inflammatory effect of S18 on HAVICs. Moreover, S18 alleviated aortic valve lesions in IL-37 transgenic mice of CAVD model. Microscale thermophoresis (MST) and docking analysis of five piericidin analogues suggested that diglycosides, but not monoglycosides, exert obvious IL-37-binding activity. These results indicate that S18 directly binds to IL-37 to alleviate inflammatory responses in HAVICs and aortic valve lesions in mice. Piericidin diglycoside S18 is a potential therapeutic agent to prevent the development of CAVD.
Discrete Dynamic Modeling Analysis Based on English Learning Motivation
Authors: Tang Hengyao , Wang Qingdong , Jiang Guosong
Published: August 2022

With the popularization of the Internet, various online learning platforms have developed rapidly, providing users with abundant learning resources, and realizing personalized resource recommendation has become the development trend of online learning platforms. In this paper, a personalized learning recommendation model based on improved collaborative filtering is proposed. Firstly, a multilayer interest model of learners is established to accurately describe learners’ interest in knowledge topics, courses, and knowledge areas; then, in view of the sparse scoring matrix and cold-start problems of traditional collaborative filtering recommendation algorithms, an improved collaborative filtering-based personality is proposed. The personalized learning recommendation model is used to improve the similarity calculation of users by introducing user initialization tags and solve the cold-start problem of new users. Finally, the effectiveness of the algorithm is proved by experimental comparison, and the improved algorithm improves the recommendation effect of personalized learning.
Monitoring and Analysis of Cotton Planting Parameters in Multiareas Based on Multisensor
Authors: Fan Zehua , Zhang Nannan , Wang Desheng , Zhi Jinhu , Zhang Xuedong
Published: August 2022

In order to realize cotton growth monitoring, a cotton planting monitoring system based on image processing technology was proposed. The system requires camera to collect cotton canopy images, leaf areometer to detect the leaf area index, and spectrometer to detect the normalized vegetation index (

NDVI

) and the vegetation index (

RVI

). Due to different types of data, based on the establishment of the output transmission system, the canopy coverage was calculated by the image processing method, and there was a linear relationship between canopy coverage

NDVI

and

RVI

. The leaf area index (LAI) of N content was established, and the model of dry matter accumulation and canopy coverage was exponential. The experiment result shows that the linear and exponential coefficients of the model

k

and

b

increased with the increase of the nitrogen application rate. The fitting determination coefficient remained high under different nitrogen application rates. The fitting coefficient R2 of the three models in the two test fields ranged from 0.83 to 0.923, which also met the needs of model evaluation. The system was used to detect the cotton field with good accuracy.
Design an Effective Blood Distribution Network with Minimal Impacts on the Environment and Blood Supply Assurance
Authors: Zheng Xiaojin , Qin Shengkun , Zhang Yanxia
Published: August 2022

As the world’s population grows, resulting in the aggravating trend of aging population, it brings with it an increase in the demand for blood. Nowadays, in most cities, the blood distribution network is based on a single distribution centre pattern, with the blood centre acting as distribution centre for one‐to‐one distribution. However, despite its convenience, this pattern has a high frequency of delivery, increased risk of blood shortage, and generates high carbon emissions. This paper aims to understand the real‐life problems of the current blood distribution network and to design a more rational blood distribution network by taking the characteristics of the blood supply chain into account. Two blood distribution network patterns are considered, the current single distribution centre pattern and the proposed multiple distribution centre pattern. In order to minimise environmental impacts, we introduce open vehicle routing problem for blood delivery routes planning, using mixed integer programming for modelling, to compare the carbon emissions between the two blood distribution network patterns. Numerical experimental results demonstrate that applying the proposed BDN can reduce carbon emissions by an average of 25.84% and up to 29.59%, and the delivery time in emergency situations is significantly reduced by an average of 33.15%. Such studies are essential for both reducing carbon emissions and safeguarding patients’ lives.
Experimental and Numerical Investigation on Infilled Vertical Well LASER-Assisted SAGD
Authors: Chao Ding , Yongbin Wu , Guo Yang , Chihui Luo
Published: August 2022

In the SAGD process with dual horizontal wells in heterogeneous reservoirs, the injection pressure of steam huff-n-puff by infilled interwell vertical wells is too high, and the heat communication between SAGD wellpairs and infilled wells is too long, which leads to a series of problems. The solvent-assisted vertical well stimulation (LASER) technology is proposed to solve the problems above. The solvent formula was optimized, and its key mechanism was studied by viscosity reduction experiments, multicomponent phase behavior experiments at high temperature and high pressure, and scaled two-dimensional physical experiments. The experimental results show that when adding 10% 2# or 3# solvent oil, the viscosity reduction of crude oil can reach 96.65% and 96.73%, respectively. The HTHP visualized phase behavior experiment results show that the mixture of low flash point solvent oil 2# with high flash point solvent oil 3# (volumetric ratio 3 : 2) has excellent high temperature oil solubility stability and is similar to water vapor phase behavior, so it is determined as the ideal formula. The scaled two-dimensional physical experiment results show that the solvent-assisted vertical well huff-n-puff has the key mechanism of reducing injection pressure and porous flow resistance, expanding the sweep region of injected fluid and accelerating thermal communication. The cycle of huff-n-puff was reduced from 6 to 3, which greatly shortened the thermal communication time. From the scaled physical experiments, the oil rate and the oil recovery of SAGD were improved by 19.86% and 6.3%, respectively. Field-scale numerical simulation was performed, and the production performance compared with SAGD and conventional infilled CSS-SAGD was investigated, which shows that by adding solvent into steam stimulation, 6 cycles were reduced, and the incremental oil recovery factor was 27.3% and 13.2%, respectively. The performance of accelerating thermal communication and production improvement by LASER has been validated by 4 SAGD wellpairs in field practice, and its long-term prediction result shows significant potential in similar heterogeneous SAGD reservoirs.
Efficient Key Management Mechanism with Trusted Gateways for Wireless Mesh Networks
Authors: Karri Ganesh Reddy , Prabu A. V. , Routray Sidheswar , Sumathi D. , Rajasoundaran S. , Mukherjee Amrit , Chatterjee Pushpita , Alnumay Waleed
Published: August 2022

Securing wireless mesh networks (WMNs) is a crucial issue due to its intrinsic characteristics. Several endangered features might emerge due to the exposure of the networks to a diversity of medium access control (MAC) layers such as distributed denial of service (DDoS) attacks, false reply attacks, and other identity attacks. Against these attacks, the determination of existing techniques is insufficient to ensure the complete security solutions to protect the backbone network at multiple levels. As a result, effective, scalable, and integrated security solutions for WMNs are required. In WMNs, protecting legitimate gateway nodes and internal mesh routers against malicious attacks at the MAC layer remains a difficult problem. Our proposed trust-based security mechanism includes distributed authentication and deauthentication algorithms that validates backbone mesh routers as well as gateway nodes. Particularly, this proposed model targets DDoS attacks in the network. The proposed DDoS attack prevention mechanism (DAPM) uses distributed authentication and deauthentication algorithms to build trusted group heads for managing secure data communication in the network. Our research and practical results show that the proposed mechanism decreases the severity of malicious nodes and strengthens the security compared to existing centralized schemes such as digital signature authentication (DSA-Mesh, MENSA, Mobisec, and AHKM). The experimental solutions show the significance of the proposed work with 10% to 12% of better performance than the existing techniques.
Clinical Effect of Tongmai Fuming Decoction on Neovascular Ophthalmopathy
Authors: Yang Lei lei , Zhou Feng , Xu Qi , Ye Ting , Xiong Hong
Published: August 2022

Background. The incidence of neovascular eye disease is increasing year by year, seriously threatening human vision health and becoming an urgent public health problem. Tongmai fuming decoction as an experienced prescription can treat ischemic eye disease. Objective. To investigate the therapeutic effect of Tongmai fuming decoction combined with anti-VEGF therapy on neovascular ophthalmopathy. Methods. 52 patients (62 eyes) with neovascular ophthalmopathy who met the inclusion criteria from January 2018 to July 2020 were randomly divided into the control and observation groups. The control group was given an intravitreal injection of antivascular endothelial growth factor (VEGF) drugs once a day combined with on-demand treatment. The observation group was treated with traditional Chinese medicine Tongmai fuming decoction in addition to the treatment of anti-VEGF drugs. The best-corrected visual acuity (BCVA) was examined before and after treatment, and optical coherence tomography angiography (OCTA) was used to examine the mean retinal thickness and neovascularization in the macular area. Patients were followed for one year and the number of anti-VEGF injections was recorded. Results. After treatment, the average thickness of BCVA and macular retina in the two groups significantly improved. The BCVA of the control group was 0.59 ± 0.39 3 months after treatment, and that of the experimental group was 0.42 ± 0.25 3 months after treatment. The average thickness of the macular retina in the control group was 304.8 ± 79.7 3 months after treatment, and that in the experimental group was 267.7 ± 64.6 3 months after treatment; The average number of injections of anti-VEGF therapy in the control group was 2.32 ± 1.15 times, and that in the experimental group was 1.74 ± 0.76 times. There was a significant difference between the two groups. Conclusion. Tongmai fuming decoction and anti-VEGF therapy have a synergistic effect in the treatment of neovascular ophthalmopathy, which can reduce the treatment times of anti-VEGF drugs.
An Intelligent Cost-Efficient System to Prevent the Improper Posture Hazards in Offices Using Machine Learning Algorithms
Authors: Arshad Jehangir , Asim Hafiza Mahnoor , Ashraf Muhammad Adil , Jaffery Mujtaba Hussain , Zaidi Khurram Shabih , Amentie Melkamu Deressa
Published: August 2022

In this research, an intelligent and cost-efficient system has been proposed to detect the improper sitting posture of a person working at a desk, mostly in offices, using machine learning classification techniques. The current era demands to avoid the harms of an improper posture as it, when prolonged, is very painful and can be fatal sometimes. This study also includes a comparison of two arrangements. Arrangement 01 includes six force-sensitive resistor (FSR) sensors alone, and it is less expensive. Arrangement 02 consists of two FSR sensors and one ultrasonic sensor embedded in the back seat of a chair. The K-nearest neighbor (KNN), Naive Bayes, logistic regression, and random forest algorithms are used to augment the gain and enhanced accuracy for posture detection. The improper postures recognized in this study are backward-leaning, forward-leaning, left-leaning, and right-leaning. The presented results validate the proposed system as the accuracy of 99.8% is achieved using a smaller number of sensors that make the proposed prototype cost-efficient with improved accuracy and lower execution time. The proposed model is of a dire need for employees working in offices or even at the residential level to make it convenient to work for hours without having severe effects of improper posture and prolonged sitting.