bluuebunny/crossref_metadata_2025 huggingface dataset:
Arteannuin B Enhances the Effectiveness of Cisplatin in Non-Small Cell Lung Cancer by Regulating Connexin 43 and MAPK Pathway
Authors: Huang Weijuan , Wang Yanqing , He Tingsha , Zhu Jianhua , Li Jianhuan , Zhang Sirui , Zhu Yong , Xu Yafang , Xu Lv , Wang Haoran , Yu Rongmin , Song Liyan
Published: August 2022

Cisplatin (DDP)-based chemotherapy is the first-line regimen for advanced non-small cell lung cancer (NSCLC) patients. However, advanced NSCLC patients may have innate resistance to DDP or develop resistance during DDP treatment. We investigated a natural compound, arteannuin B (Art B), for its potential effects on DDP resistance in NSCLC. Art B was isolated from Artemisia annua by chromatographic purification and spectral elucidation. The activities of Art B on DDP-mediated effects were examined using in vitro and in vivo assays. We observed significant correlations in T stage, clinical stage, chemotherapy resistance and poor survival of NSCLC patients with low Cx43 expression. Art B enhanced the effectiveness of cisplatin by increasing Cx43 expression in normal and DDP-resistant NSCLC cells. Art B also increased DDP uptake through up-regulating Cx43. The combination of DDP and Art B showed better therapeutic effect than individual treatments both in vitro and in vivo. Art B increased intracellular Fe[Formula: see text] level, promoted calcium influx, and activated gap junction and MAPK pathways, which might contribute to Art B-mediated effects. Art B may serve as a new drug candidate to enhance the antitumor effect of DDP on NSCLC.
DISCRETE HERMITE–HADAMARD-TYPE INEQUALITIES FOR (s,m)-CONVEX FUNCTION
Authors: QI YONGFANG , WEN QINGZHI , LI GUOPING , XIAO KECHENG , WANG SHAN
Published: August 2022

The Hermite–Hadamard (HH)-type inequality plays a very important role in the fields of basic mathematics and applied mathematics. In recent years, many scholars have expanded and improved it. Although we have achieved some research results about HH-type inequality, the research on discrete HH-type inequalities has just begun, and a lot of work needs to be improved. In this paper, we introduce [Formula: see text]-convex function and present discrete HH-type inequalities on time scale with discrete substitution method. In addition, the Hermite–Hadamard–Fejér(HHF)-type inequalities on time scale will be obtained, where the integrand is [Formula: see text], [Formula: see text] is [Formula: see text]-convex function on [Formula: see text] and [Formula: see text] is symmetric with respect to [Formula: see text], our results in some special cases yield the well-known classic HHF-type inequalities. Finally, through the discrete substitution method, we get discrete fractional HH-type inequality and discrete fractional HHF-type inequality for [Formula: see text]-convex function.
Addressing Confounding Feature Issue for Causal Recommendation
Authors: He Xiangnan , Zhang Yang , Feng Fuli , Song Chonggang , Yi Lingling , Ling Guohui , Zhang Yongdong
Published: August 2022

In recommender systems, some features directly affect whether an interaction would happen, making the happened interactions not necessarily indicate user preference. For instance, short videos are objectively easier to finish even though the user may not like the video. We term such feature as
confounding feature
, and video length is a confounding feature in video recommendation. If we fit a model on such interaction data, just as done by most data-driven recommender systems, the model will be biased to recommend short videos more, and deviate from user actual requirement.

This work formulates and addresses the problem from the causal perspective. Assuming there are some factors affecting both the confounding feature and other item features, e.g., the video creator, we find the confounding feature opens a backdoor path behind user-item matching and introduces spurious correlation. To remove the effect of backdoor path, we propose a framework named
Deconfounding Causal Recommendation
(DCR)
, which performs intervened inference with
do-calculus
. Nevertheless, evaluating
do-calculus
requires to sum over the prediction on all possible values of confounding feature, significantly increasing the time cost. To address the efficiency challenge, we further propose a
mixture-of-experts (MoE)
model architecture, modeling each value of confounding feature with a separate expert module. Through this way, we retain the model expressiveness with few additional costs. We demonstrate DCR on the backbone model of
neural factorization machine (NFM)
, showing that DCR leads to more accurate prediction of user preference with small inference time cost. We release our code at:
https://github.com/zyang1580/DCR
.
Pied-Piper: Revealing the Backdoor Threats in Ethereum ERC Token Contracts
Authors: Ma Fuchen , Ren Meng , Ouyang Lerong , Chen Yuanliang , Zhu Juan , Chen Ting , Zheng Yingli , Dai Xiao , Jiang Yu , Sun Jiaguang
Published: August 2022

With the development of decentralized networks, smart contracts, especially those for ERC tokens, are attracting more and more Dapp users to implement their applications. There are some functions in ERC token contracts that only a specific group of accounts could invoke. Among those functions, some even can influence other accounts or the whole system without prior notice or permission. These functions are referred to as contract backdoors. Once exploited by an attacker, they can cause property losses and harm users’ privacy.

In this work, we propose Pied-Piper, a hybrid analysis method that integrates datalog analysis and directed fuzzing to detect backdoor threats in Ethereum ERC token contracts. First, datalog analysis is applied to abstract the data structures and identification rules related to the threats for preliminary static detection. Then, directed fuzzing is applied to eliminate false positives caused by the static analysis. We first evaluated Pied-Piper on 200 smart contracts, which are injected with different types of backdoors. It reported all problems without false positives, and none of the injected problems was missed. Then, we applied Pied-Piper on 13,484 real token contracts deployed on Ethereum. Pied-Piper reported 189 confirmed problems, four of which have been assigned unique CVE ids while others are still in the review process. Each contract takes 8.03 seconds for datalog analysis on average, and the fuzzing engine can eliminate the false positives within one minute.
Inferring Activity Patterns from Sparse Step Counts Data with Recurrent Neural Networks
Authors: Shi Keqin , Chen Zhen , Li Xuejing , Xiao Zhifei , Sun Weiqiang , Hu Weisheng
Published: August 2022

As an accurate measurement of physical activity, step counts data can be collected expediently by smartphones and wearable devices. Complete and high time-resolution step counts data record the time and intensity of individuals’ physical activity in a day, and can be used to mine activity habits or to recommend customized workout plans. However, sparse step counts data are common in practice due to hardware and software limitations. Understanding the value of sparse step counts data can contribute to its application in healthcare, and also can help us design cost-effective hardware and software. In this article, we aim to infer activity patterns from sparse step counts data. We design a deep learning model based on recurrent neural networks, namely MLP-GRU, which considers bidirectional short-term dependency and long-term regularity of sparse step counts data, and implements data-driven imputation and classification. We also develop an interpretable and elastic method to obtain sparse step counts data labeled with multi-granular activity patterns to train MLP-GRU. Evaluations on real-world datasets reveal that MLP-GRU outperforms other strong baseline methods. The results also show that activity patterns can be inferred from extremely sparse step counts data with high accuracy, provided that proper granularity is used for data of different sparsity.
Physiological Needs: Sensations and Predictions in the Insular Cortex
Authors: Prilutski Yael , Livneh Yoav
Published: August 2022

Physiological needs create powerful motivations (e.g., thirst and hunger). Studies in humans and animal models have implicated the insular cortex in the neural regulation of physiological needs and need-driven behavior. We review prominent mechanistic models of how the insular cortex might achieve this regulation and present a conceptual and analytical framework for testing these models in healthy and pathological conditions.
The Prediction Model of Dance Talent Training in Fuzzy Neural Network Algorithm
Authors: Zhong HuaLong
Published: August 2022

In view of the existing problems in the training of dance talents, particularly in China, the focal and key goal of this investigation is to examine and train a predictive model using the fuzzy neural network algorithm. In order to enhance the training, improve the quality of dance talents, and further promote the development of dance professional education, this paper implements the fuzzy neural network procedure to train prediction models for dance talents. Moreover, we carry out research and, then, establish a prediction model, through the fuzzy neural network algorithm, to predict the quality and effect of dance talent training. The model can be, then, used to deliver a fundamental and a key reference for the training of dance talents in the social sectors across the world. The experimental setup and obtained outcomes show that the suggested algorithm has good usability for the training and prediction of dance talents in terms of accuracy. We observed that the fuzzy-based technique is approximately 17.6% more precise than the classical scheme. Moreover, the prediction correctness was observed more than 98.5%.
ResNet-Enabled cGAN Model for Channel Estimation in Massive MIMO System
Authors: Yadav Jyoti Deshwal , Dwivedi Vivek K. , Chaturvedi Saurabh
Published: August 2022

Massive multiple-input multiple-output (MIMO), or large-scale MIMO, is one of the key technologies for future wireless networks to exhibit a large accessible spectrum and throughput. The performance of a massive MIMO system is strongly reliant on the nature of various channels and interference during multipath transmission. Therefore, it is important to compute accurate channel estimation. This paper considers a massive MIMO system with one-bit analog-to-digital converters (ADCs) on each receiver antenna of the base station. Deep learning (DL)-based channel estimation framework has been developed to reduce signal processing complexity. This DL framework uses conditional generative adversarial networks (cGANs) and various convolutional neural networks, namely reverse residual network (reverse ResNet), squeeze-and-excitation ResNet (SE ResNet), ResUNet++, and reverse SE ResNet, as the generator model of cGAN for extracting the features from the quantized received signals. The simulation results of this paper show that the trained residual block-based generator model of cGAN has better channel generation performance than the standard generator model in terms of mean square error.
Network Pharmacology and Molecular Docking Analysis Explores the Mechanisms of Cordyceps sinensis in the Treatment of Oral Lichen Planus
Authors: Ma Hexin , Wang Guofang , Guo Xiaomeng , Yao Yao , Li Chunshen , Li Xibo , Xin Mingzhe , Xu Xiaohui , Zhang Shilong , Sun Zhi , Zhao Hongyu
Published: August 2022

Objective. Oral lichen planus (OLP) is the most common potentially malignant disorder of the oral cavity. This study aimed to investigate the mechanism of action of Cordyceps sinensis in the treatment of OLP and provides a theoretical support for improving current treatment regimens for OLP. Methods. The active components and therapeutic targets of Cordyceps sinensis were predicted and screened using the TCMSP, SymMap, PubMed, HIT 2.0, and PharmMapper databases, while the relevant OLP targets were predicted and screened using the DisGeNET and GeneCards databases. Protein-protein interactions (PPI) were examined using the String database, and Cytoscape was used to combine and illustrate the findings. GO and KEGG pathway enrichment analyses were carried out using RStudio, and AutoDock Vina and Pymol were used for molecular docking and visualization, respectively. Results. A total of 404 potential target genes were discovered after evaluating 21 active compounds from Cordyceps sinensis. Potential therapeutic targets included 67 targets that matched and overlapped with OLP, including TNF, IL-6, CD4, EGFR, and IL1B. Key targets were predominantly engaged in the PI3K-Akt signaling pathway and the MAPK signaling pathway, according to the GO and KEGG analyses. These targets have a connection to biological processes including apoptosis signaling pathway regulation, T cell activation, and oxidative stress response. The molecular docking results showed that TNF, IL-6, CD4, EGFR, and IL1B could bind to their corresponding active components. Conclusions. Cordyceps sinensis contains multiple components and acts on multiple targets and multiple pathways. Particularly, Cordyceps sinensis targets TNF, IL-6, CD4, EGFR, and IL1B, regulates PI3K-Akt and MAPK signaling pathways, as well as takes part in biological processes including apoptosis, T cell activation, and oxidative stress. Cordyceps sinensis could be a crucial choice in the therapy of OLP.
Clinical Observation on Therapeutic Effect of Electroacupuncture Combined with Diclofenac Sodium in Treatment of Acute Gouty Arthritis: A Randomized Controlled Study
Authors: Liu Lumin , Yin Ping , Hu Junwei , Li Xu , Chen Yuelai
Published: August 2022

Objective. To observe the clinical effect of electroacupuncture (EA) combined with diclofenac sodium (DS) in the treatment of acute gouty arthritis (AGA). Methods. Patients with AGA were randomly divided into three groups: the EA + DS treatment group (i.e., EA + DS group), the low-dose DS treatment group (i.e., low-dose DS group), and the conventional-dose DS treatment group (i. e., conventional DS group). Patients in the low-dose DS group took 50 mg of DS sustained-release capsules once a day. Patients in the conventional DS group took 100 mg of DS sustained-release capsules once a day. Patients in the EA + DS group were treated with EA three times in 7 days combined with 50 mg of DS sustained-release capsules once a day. For all the three groups, 7 days were regarded as a course of treatment. Outcome indicators included pain visual analog scale (VAS), joint tenderness, joint swelling and activity limitation, and levels of inflammatory indicators (C-reactive protein (CRP)/white blood cells (WBC)/percentage of neutrophils (NE%)), level of serum uric acid (SUA), gout impact scale (GIS), and frequency of adverse reactions). Results. After a course of treatment, indicators regarding the VAS, joint tenderness, joint swelling, activity limitation, GIS, inflammatory indicators (CRP/WBC/NE%), and SUA were all improved (

P
<
0.05

) with no adverse reactions in the EA + DS group. The EA + DS group performed better than the low-dose DS group in improving indicators regarding the VAS, joint tenderness, activity limitation, GIS, inflammatory markers (WBC/NE%), and SUA (

P
<
0.05

). Similarly, the EA + DS group performed better than the conventional DS group in improving indicators regarding GIS, SUA, and adverse reactions (

P
<
0.05

). Conclusion. EA combined with DS can improve AGA patients’ joint pain and functional status, thus improving their quality of life. Moreover, this combined treatment can reduce the levels of inflammatory markers and SUA, leading to fewer adverse reactions in AGA patients.
Comparative Study of Swarm‐Based Algorithms for Location‐Allocation Optimization of Express Depots
Authors: Zhang Yong-Wei , Xiao Qin , Sun Xue-Ying , Qi Liang
Published: August 2022

The location and capacity of express distribution centers and delivery point allocation are mixed‐integer programming problems modeled as capacitated location and allocation problems (CLAPs), which may be constrained by the position and capacity of distribution centers and the assignment of delivery points. The solution representation significantly impacts the search efficiency when applying swarm‐based algorithms to CLAPs. In a traditional encoding scheme, the solution is the direct representation of position, capacity, and assignment of the plan and the constraints are handled by punishment terms. However, the solutions that cannot satisfy the constraints are evaluated during the search process, which reduces the search efficiency. A general encoding scheme that uses a vector of uniform range elements is proposed to eliminate the effect of constraints. In this encoding scheme, the number of distribution centers is dynamically determined during the search process, and the capacity of distribution centers and the allocation of delivery points are determined by the random proportion and random key of the elements in the encoded solution vector. The proposed encoding scheme is verified on particle swarm optimization, differential evolution, artificial bee colony, and powerful differential evolution variant, and the performances are compared to those of the traditional encoding scheme. Numerical examples with up to 50 delivery points show that the proposed encoding scheme boosts the performance of all algorithms without altering any operator of the algorithm.
Clinical Considerations in the Selection of Preexposure Prophylaxis for HIV Prevention in Canada
Authors: Knox David C. , Pilarski Robert , Dhunna Harvinder S. , Kaushal Amit , Adachi Jonathan D.
Published: August 2022

According to the Public Health Agency of Canada, approximately 62,050 people were living with HIV in Canada in 2018, and of those, 13% were undiagnosed. Currently, no single strategy provides complete protection or is universally effective across all demographic groups at risk for HIV. However, HIV preexposure prophylaxis (PrEP) is the newest HIV prevention strategy that shows promise. To date, two products have received an indication for PrEP by Health Canada: emtricitabine/tenofovir disoproxil fumarate (Truvada®; FTC/TDF) and emtricitabine/tenofovir alafenamide (Descovy®; FTC/TAF). Despite the high efficacy of these PrEP intervention methods, access to PrEP in Canada remains low. Identifying and addressing barriers to PrEP access, especially in high-risk groups, are necessary to reduce HIV transmission in Canada. While guidelines published by the Center for Disease Control and Prevention (CDC) include FTC/TAF information, the efficacy of FTC/TAF for PrEP has not yet been considered in Canada’s clinical practice guidelines. Thus, the current paper reviews data regarding the use of FTC/TDF and FTC/TAF for PrEP, which may be useful for Canadian healthcare providers when counseling and implementing HIV prevention methods. The authors highlight these data in relation to various at-risk populations and review ongoing clinical trials investigating novel PrEP agents. Overall, FTC/TDF PrEP is effective for many populations, including men who have sex with men, transgender women, heterosexuals with partners living with HIV, and people who use drugs. While there is fewer data reported on the efficacy of FTC/TAF to date, recent clinical trials have demonstrated noninferiority of FTC/TAF in comparison to FTC/TDF. Notably, as studies have shown that FTC/TAF maintains renal function and bone mineral density to a greater extent than FTC/TDF, FTC/TAF may be a safer option for patients experiencing renal and/or bone dysfunction, for those at risk of renal and bone complications, and for those who develop FTC/TDF-related adverse events.
Investigating the Relationship between Knowledge and Hepatotoxic Effects with Medication Adherence of TB Patients in Banyumas Regency, Indonesia
Authors: Perwitasari Dyah A. , Setiawan Didik , Nguyen Thang , Pratiwi Arum , Rahma Fauziah Laila , Saebrinah Erin , Safaria Triantoro , Nurulita Nunuk Aries , Arfianti Wiraagni Idha
Published: August 2022

Tuberculosis (TB) still remains the burden in Indonesia. One of the factors that may influence the treatment success of TB is patient’s adherence. However, the hepatotoxicity of the TB medicine may decrease the patient’s adherence. Our study’s aim is to investigate the relationship between the patient's knowledge and the hepatotoxicity with medication adherence of TB patients in Banyumas Regency. This study was conducted at one Community Lung Health Center and two hospitals in Banyumas Regency, Purwokerto, Center of Java, Indonesia. The respondents were 91 TB patients with hepatotoxicity characterized by an increased aspartate transaminase (AST) and alanine aminotransferase (ALT). The level of the patients’ knowledge about the hepatotoxicity effect was determined using a questionnaire. The patients’ adherence was determined using the Medication Adherence Rating Scale -5 (MARS) questionnaire and pill count methods. Most of the patients were male (53.8%), the age was in the range of 18–29 years old (3.5%), they have no smoking history (59.3%), and their last education majorly was senior high school (46.2%). Most TB patients had poor knowledge (47.3%) and the hepatotoxic effect often appeared in grade 1 (61.5%). The TB patients with a good and moderate level of knowledge were 17.6% and 35.2%, respectively. The TB patients with moderate and severe hepatotoxicity were 39.4% and 1.1%, respectively. The measurement of the level of respondents’ adherence using MARS-5 showed that 51.6% of patients had good adherence. We determined the rest of the drug-using pill count method, which resulted in 62.6% of patients adhering to taking antituberculosis drugs. TB patients with a sufficient knowledge and those with mild hepatotoxicity show the higher adherence (

p
<
0.001

). There is a significant relationship between a high level of the patient’s knowledge about hepatotoxicity effect, less severity of the hepatotoxic effect, and increased patient adherence in taking the medication.
Migration Path Tracking Algorithm of Egret Birds Based on Intelligent Remote Sensing Monitoring
Authors: Li Liping
Published: August 2022

There are billions of migratory birds migrating between breeding grounds and wintering grounds in the world every year. Egret is no exception. During the migration period, they need to travel for a long time and long distances. At present, the protection strategies of egrets and the dynamic mechanism of migration routes are concerned by experts in related fields. Researchers generally explore the above problems by tracking the migration paths of egrets. Most of the existing path tracking algorithms use some classical tracking algorithms, but the tracking accuracy of the classical algorithms is low. Therefore, this paper has applied the intelligent remote sensing monitoring technology to the improvement of the path tracking algorithm, used artificial intelligence technology to remove the redundant information of the image, and combined the Kalman filter with the single-target long-term algorithm to improve the tracking algorithm. 100 samples were simulated, and the experimental results showed that the tracking accuracy of the egret bird migration path tracking algorithm based on intelligent remote sensing monitoring was improved by 8.37% compared with the algorithm before improvement, which has better utilization value.
National Consensus for the Management of Acute Gastroenteritis in Jordanian Children: Consensus Recommendations Endorsed by the Jordanian Paediatric Society
Authors: Rawashdeh Mohammed , Al-Zoubi Basim , Aliwat Maha Barbar , Burayzat Salma , Alhindawi Esam , Al-Matti Ali Attia , Altamimi Eyad
Published: August 2022

Diarrhoeal diseases are one of the leading worldwide preventable causes of death among children under 5 years of age. Almost half of children do not receive optimal acute gastroenteritis (AGE) treatment in Jordan. With neither regional nor local guidelines available for AGE, consensus recommendations on the management of paediatric AGE in Jordan were developed by a panel of senior paediatricians and paediatric gastroenterologists and are endorsed by the Jordanian Paediatric Society. Recommendations are based on international guidelines and available relevant literature in relation to the AGE landscape and the healthcare system in Jordan. The prevention of diarrhoeal diseases should focus on the improvement of nutrition, hygiene, and sanitation, the introduction of routine vaccination against rotavirus, and the adoption of a standardised approach for AGE management (oral rehydration solution (ORS) use±adjunct therapies, continued feeding, and avoiding routine antibiotic use). Ondansetron, diosmectite, racecadotril, probiotics, and zinc can be considered adjunct to ORS, if needed. Local data gaps should be addressed. The clinical algorithm for the management of paediatric AGE could promote adherence to practice recommendations and by extension improve health outcomes in children.
Effect of Comprehensive Nursing on Traumatic Paraplegia Patients by Evaluation of Magnetic Resonance Imaging Features
Authors: Xiang Rui , Xu Fengqin , Yin Zhaoyang , Ji Lili , Xu Qin
Published: August 2022

This research aimed to discuss the comprehensive nursing under the Omaha system in the treatment of patients with traumatic paraplegia (TP) and the changes in magnetic resonance imaging (MRI) features of patients. In total, 60 patients with TP were included as the research objects, and they were randomly divided into the experimental group (Omaha system‐based comprehensive nursing) and the control group (routine nursing). All the objects underwent parallel MRI multisequence scanning. The scores of the quality of life, role change, mental health, care, oral hygiene, skin, neuromusculoskeletal (NMS) system, defecation function, urination function, contagion/infection, nutrition, healthcare supervision, and rest/sleep pattern in the experimental group were all significantly higher than those in the control group 3 months and 6 months after discharge (P < 0.05). The caregiving burden scores in the experimental group 3 months and 6 months after discharge from the hospital were 48.67 ± 6.97 and 43.40 ± 4.97, respectively, statistically lower than those in the control group (52.83 ± 6.37; 50.07 ± 7.14) (P < 0.05). On admission, MRI showed that the white lines disappeared from the compression of the dural sac, the spinal cord was compressed, and the intramedullary signal was abnormal. Then, six months after discharge, MRI showed that the compression of the dural sac was relieved, and the double white lines recovered. The apparent diffusion coefficient (ADC) of patients in the experimental group 6 months after discharge (1.063 ± 0.148) was highly lower than that in the control group (1.325 ± 0.245), with a difference of statistical significance (P < 0.05). In conclusion, comprehensive nursing under the Omaha system could improve the clinical treatment effect of patients with spinal cord injury (SCI) effectively, reduce the incidence of complications, and improve the quality of life and nursing outcomes of patients.
Prevalence of Squamous and Basal Cell Carcinomas in African Albino Skin Cancer Lesions: A Systematic Review and Meta-Analysis of Proportion
Authors: Onyishi Nnaemeka T. , Ohayi Samuel R.
Published: August 2022

Context. Keratinocyte carcinomas are the most common malignant condition in Caucasian populations. African albinos have hypomelanized sensitive skin that is quite susceptible to photocarcinogenesis. Of the keratinocyte carcinomas, squamous cell carcinoma (SCC) has been found more frequent in pigmented Africans, while basal cell carcinoma (BCC) predominates in Caucasians. While some studies report a preponderance of SCC over BCC in African albinos, congruent with the situation in pigmented Africans, other reports have found BCCs to be more frequent and consistent with the pattern in Caucasians. Objective. To estimate the prevalence of cutaneous SCC and BCC in all histologically confirmed skin cancer lesions in African albinos.The following five databases are as follows: African Journals Online (AJOL), PubMed, Europe PMC, and Google Scholar were searched for relevant articles. Study Selection: included studies were case series and cross-sectional studies of histologically confirmed skin cancers in African albinos. Data extraction and synthesis: data extraction and synthesis was informed by the meta-analysis of observational studies in epidemiology guideline. By random effect meta-analysis, we calculated the pooled prevalence of SCC and BCC in skin cancer lesions of the African albinos. Result. We abstracted 695 skin cancer lesions from 540 African albinos (275 male and 241 female albinos with sex not stated in 24 subjects). There were 419 SCCs and 249 BCCs. By meta-analysis, the pooled prevalence of SCC is 64% (95% CI; 50–77%). The prevalence for BCC is 31% (95% CI; 19–45%). Conclusion. Overall, squamous cell carcinoma is the predominant type of keratinocyte carcinoma reported in African albinos. SCC is preponderant in case series of surgical excision biopsies while BCC predominates in studies reporting on albino skin surveillance programmes.
Viral RNA Load in Symptomatic and Asymptomatic COVID-19 Omicron Variant-Positive Patients
Authors: Wu Qian , Shi Lixia , Li Haomin , Huang Shuping , Li Hongwei , Li Li , Han Jin , Wu Qi , Pei Zhengcun
Published: August 2022

Objectives. Viral load is important when evaluating viral transmission potential, involving the use of a polymerase chain reaction (PCR) cycle threshold (Ct) value. We aimed to analyze the PCR Ct values of respiratory tract samples taken from patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant strains to evaluate these strains’ viral dynamics. Methods. This study comprised 361 patients. The Ct values of SARS-CoV-2-related respiratory samples were compared between symptomatic and asymptomatic patients. Results. The median (25th percentile and 75th percentile) nasopharynx and oropharynx SARS-CoV-2 Ct values were 30.5 (24.5–35.0) and 34.5 (30.0–37.0) in the symptomatic group, respectively, and 27.8 (23.4–34.5) and 33.5 (26.0–35.0) in the asymptomatic group, respectively, without significance. In the symptomatic group, subgroup analyses according to age showed the mean nasal Ct value for patients aged >18 years was 29.0 (23.5–34.5), which was significantly lower than that of patients aged 0–4 years and 5–13 years (36.0 (30.5–38.0) and 34.5 (31.0–39.0), respectively). The nasal Ct value for asymptomatic patients aged >18 years was 25.5 (20.9–28.4), which was significantly lower than of patients aged 5–13 years (34.5 (25.6–36.4)). Conclusion. Our findings suggest that the viral loads of asymptomatic and symptomatic patients did not differ significantly. However, adults infected with SARS-CoV-2 had higher nasal viral loads that those of young children.
Analysis of Art Classroom Teaching Behavior Based on Intelligent Image Recognition
Authors: Gu Chihui , Li Yinxing
Published: August 2022

To solve the problem of intelligent image recognition in classroom behavior, this paper proposes a fast target detection based on FFmpeg CODEC, extracts MHI-HOG joint features according to the located foreground target area, and finally completes the behavior recognition model through a BP neural network support vector machine joint classifier based on the look-up table. The results are as follows: the motion detection method based on H.264 FFmpeg CODEC video has the highest detection accuracy, which can reach 95%. The foreground detection method takes about 10 ms and saves 90% of the time. The behavior classification and recognition effect of MHI-HOG joint features based on the model has been significantly improved, and the comprehensive recognition rate has reached 95%. The built-in BP neural network support vector machine has 97% accuracy in extracting, classifying, and recognizing the characteristics of a single sample. This study attempts to identify and analyze the class behavior and validate the effectiveness of the collaborative classifiers proposed in this paper to build an intellectual classroom.
Financial System Design for High-Tech Enterprise Based on Cloud Service and Task Scheduling Algorithm
Authors: Zhang Yi , Fang Zhiyong , Xu Yanling , Bao Zhao
Published: August 2022

So far, with the development of the network, a new era of cloud computing is gradually advancing. Cloud services based on cloud computing technology have long become a new business model with broad application prospects. This paper studies the design of a high-tech enterprise financial system based on cloud service and task scheduling algorithm. The project can fully meet the following requirements: the establishment of a financial management system can improve the degree of automation and computerization of financial management and reduce the labor intensity of financial personnel. It is an analysis and decision-making program for the financial management of high-tech enterprises that can be shared using financial management software. Using a financial management system in actual work can achieve rapid financial data entry and improve the accuracy of data accounting. The high-tech enterprise financial management system is a very suitable and convenient management system, which substantially meets the daily business needs of high-tech financial management of enterprises.
Construction of Intelligent Evaluation Platform Based on Random Matrix iWrite College English Writing
Authors: Gao Lei , Xu Jiatong , Fu Xiaoda , Li Juan
Published: August 2022

The advantages of iWrite English writing teaching and marking system 3.0 and the case study of English writing in higher education based on this system have a positive effect on forming a new model of English writing teaching in higher education under the background of Internet + and improving and solving the main problems of English writing teaching in higher education. Although the current intelligent marking systems have made a lot of achievements, they have not fundamentally solved the problem of the rationality of intelligent marking of subjective questions. In order to better perceive the sense of speech in English essays in depth and improve the rationality problem of intelligent marking, this study proposes a quantification of N-element sense of speech value based on correlation analysis and a scoring fitting algorithm for English essays based on rationality enhancement. The quantification of perceptual value is done by obtaining the N components of the composition and calculating their support in the corpus. In the daily teaching work, teachers should actively cooperate with the marking system to improve their own teaching level and explore ways and methods of students’ writing training, so as to cultivate more English talents. In addition, word features, sentence features, and chapter structure features were extracted from the essays to fit the English essay scores. Since not all students were able to complete the essays according to the requirements of the questions, a streaming scoring model was used to separate the normal essays from the low-scoring essays. The low-scoring essays were scored using the k-nearest neighbor algorithm, while the normal essays were fitted to the test takers’ scores using the support vector regression algorithm. Statistically, it was found that the essay scores also showed a certain normal distribution. The standard support vector regression algorithm is prone to data skewing problems, so this study addresses this problem by using a rationality enhancement method, which gives a corresponding penalty factor according to the distribution of the data set.
Simulation Design of Intelligent Garden Based on Climate Adaptability and Nonlinear Random Matrix
Authors: Lu Yao , Chen Bingyan , Xin Yicheng , Zhu Xiaofei
Published: August 2022

Compared with the modern intelligent landscape design, traditional landscape design is often limited to landscape level architectural design and traditional functional design, thus ignoring the advantages of ecological factors and scientific and technological factors embodied in intelligent landscape design. Therefore, the traditional landscape design often has some disadvantages, such as waste of design resources, serious design energy consumption, poor adaptability of design products, weak practicality, and fragile ecological structure. Based on this, this paper will fully consider the role of climate factors such as solar radiation, temperature, wind conditions, and relative temperature and humidity and air pollutants in landscape design. At the same time, various design factors in landscape design will be quantified and statistically analyzed by using the principle of nonlinear random matrix, so as to further optimize the index distribution of balanced design factors and optimize the landscape design scheme. In the actual principle design, this paper adopts the logic idea of digital garden design, based on the design process of garden logic design, garden design foundation preparation, garden design environment analysis, and digital garden design results display, and establishes a parametric digital garden forest model, so as to realize the digital design and simulation of intelligent garden. In the corresponding practical simulation part, this paper carried out an example verification based on the interior and exterior landscape design of a company and realized the establishment of the parametric analysis model of the case based on parametric and visual-related programmable software, thus completing the simulation design of functional components such as garden road layout optimization design, garden greening planting design, garden landscape visual creation effect design, and garden numerical service design; the experimental results show that compared with the traditional garden design, the garden designed in this paper has increased the degree of garden intelligence by about 30%, reduced the energy consumption by about 20% in the corresponding degree of energy conservation and environmental protection, and increased the degree of garden comfort by about 30%.
Investigation of Transcript Variant 6 of TPD52L2 as a Prognostic and Predictive Biomarker in Basal-Like MDA-MB-231 and MDA-MB-453 Cell Lines for Breast Cancer
Authors: Zhang Xin , O’Brien Daniel , Zhang Xiaohui
Published: August 2022

Background. Basal-like breast cancer (BLBC) exhibits worse pathological features than other breast cancer subtypes, and patients diagnosed with BLBC have short disease-free and overall survival times. Thus, the identification of novel biomarkers and therapeutic targets for BLBC is of upmost importance. Although TPD52L2 is upregulated in multiple cancers, little is known about its roles in BLBC. Methods. RNA levels were analyzed between breast cancer tissues and paired adjacent normal tissues using RNA-seq data from The Cancer Genome Atlas (TCGA). TPD52L2 stable knockdown and inducible knockout cell lines were established using basal-like MDA-MB-231 and MDA-MB-453 cell lines. Cell proliferation assays in vitro and tumor growth analysis in vivo were performed to determine the function of TPD52L2 during BLBC progression. Transwell assays were used to estimate the regulatory effect of TPD52L2 on BLBC cell migration. The expression profile of all tpd52l2 transcripts was analyzed to assess the functional protein isoform. Association of transcript variant 6 (V6) expression with pathological parameters was carried out using the clinical data of the BRCA cohort. Results. We identified V6 of TPD52L2 as a novel biomarker and regulator of BLBC progression. TPD52L2 is upregulated in BLBCs and associated with patient outcomes. TPD52L2 knockdown suppresses tumor growth, and V6 correlates with cancer-related phenotypes in BLBC. Clinical data further proved that V6 is associated with different pathological features, such as pathological stage and pathological tumor status, and independently predicts patient outcomes and responses to therapies. Conclusions. Our findings demonstrate that V6 of TPD52L2 is a novel biomarker for BLBC patients. V6 promotes cell proliferation and migration and has marked oncogenic roles in determining the malignant phenotypes of BLBC.
c-Myc-Regulated lncRNA-IGFBP4 Suppresses Autophagy in Cervical Cancer-Originated HeLa Cells
Authors: Zhang Lei , Zhang Zongshan , Li Erwei , Xu Poshi
Published: August 2022

LncRNAs are known to regulate a plethora of key events of cellular processes; however, little is known about the function of lncRNAs in autophagy. Here in the current study, we report lncRNA-IGFBP4 which has previously been known to regulate the proliferation and reprogramming of cancer cells, but its role in autophagy is not yet known. We found that serum starvation provokes autophagy-induced downregulation of lncRNA-IGFBP4 levels. Next, we determined that c-Myc can negatively regulate lncRNA-IGFBP4 in HeLa cells. Phenotypically, we found that upon depletion of lncRNA-IGFBP4, the HeLa cells undergo autophagy through ULK1/Beclin1 signaling. Furthermore, through TCGA data analysis, we found lncRNA-IGFB4 overexpressed in most cancers including cervical cancer. Based on these findings, we conclude that c-Myc maintains cellular homeostasis through negatively regulating lncRNA-IGFBP4 in cervical cancer cells.
D-Optimal Design for a Causal Structure for Completely Randomized and Random Blocked Experiments
Authors: Kmail Zaher , Eskridge Kent
Published: August 2022

Most experimental design literature on causal inference focuses on establishing a causal relationship between variables, but there is no literature on how to identify a design that results in the optimal parameter estimates for a structural equation model (SEM). In this research, search algorithms are used to produce a D-optimal design for a SEM for three-stage least squares and full information maximum likelihood estimators. Then, a D-optimal design for the estimate of the model parameters of a mixed-effects SEM is obtained. The efficiency of each of the D-optimal designs for SEMs is compared with univariate optimal and uniform designs. In each case, the causal relationship changed the optimal designs dramatically and the new D-optimal designs were more efficient.
Control System and Speech Recognition of Exhibition Hall Digital Media Based on Computer Technology
Authors: Zhao Yu
Published: August 2022

With environmental noise in the exhibition hall, speakers tend to change their speech production to preserve intelligible communication. While great evolution has been prepared in Automatic Speech Recognition (ASR), important performance deprivation occurs in a noisy environment. The assessment of the degree of speech impairment and the efficacy of computer recognition of impaired speech are distinctly and independently executed. Convolutional Neural Networks (CNN) have been effectively employed in speech recognition and computer vision tasks. Hence, this study uses the Deep Convolutional Neural Network-based Automatic Speech Recognition Model (DCNN-ASRM) for effective speech recognition in the noisy exhibition hall. This study configures the filter sizes, poolings, and input feature map. The filter size and pooling are decreased, and the dimension of the input feature is comprehensive to permit increasing convolution layers. Furthermore, an in-depth analysis of the proposed DCNN-ASRM model discloses critical features, like fast convergence speed, compact model scales, and noise robustness in speech recognition. The simulation analysis shows that the suggested DCNN-ASRM model enhances the recognition accuracy ratio of 98.1%, performance ratio of 97.2%, and noise reduction ratio of 96.5% and reduces the word error rate by 9.2% and signal-to-noise ratio by 10.3% compared to other existing models.
Identification of Immune-Related lncRNAs for Predicting Prognosis and Immune Landscape Characteristics of Uveal Melanoma
Authors: Chen Wei , Yan Liying , Long Bo , Lin Li
Published: August 2022

Immune-related genes and long noncoding RNAs (lncRNAs) have a significant impact on the prognostic value and immunotherapeutic response of uveal melanoma (UM). Therefore, we tried to develop a prognostic model on the basis of irlncRNAs for predicting prognosis and response on immunotherapy of UM patients. We identified 1,664 immune-related genes and 2,216 immune-related lncRNAs (irlncRNAs) and structured a prognostic model with 3 prognostic irlncRNAs by co-expression analysis, univariable Cox, LASSO, and multivariate Cox regression analyses. The Kaplan–Meier analysis indicated that patients in the high-risk group had a shorter survival time than patients in the low-risk group. The ROC curves demonstrated the high sensitivity and specificity of the signature for survival prediction, and the one-, three-, and five-year AUC values, respectively, were 0.974, 0.929, and 0.941 in the entire set. Cox regression analysis, C-index, DCA, PCA analysis, and nomogram were also applied to assess the validity and accuracy of the risk model. The GO and KEGG enrichment analyses indicated that this signature is significantly related to immune-related pathways and molecules. Finally, we investigated the immunological characteristics and immunotherapy of the model and identified various novel potential compounds in the model for UM. In summary, we constructed a new model on the basis of irlncRNAs that can accurately predict prognosis and response on immunotherapy of UM patients, which may provide valuable clinical applications in antitumor immunotherapy.
Design and Implementation of Cloud Computing Network Security Virtual Computing and Defense Technology
Authors: Cheng Yongbing
Published: August 2022

In order to improve the defense effect in network security, a research and implementation method of cloud computing network security virtual computing and defense technology is proposed. This architecture makes full use of the structural advantages of the virtualized environment, which can realize the trusted measurement of the user’s virtual machine in a more reliable way and can support the user’s diverse authentication requests. This paper introduces the concept of cloud computing, the classification of cloud computing, and the characteristics of cloud computing network security. In the case of fully considering the coupling relationship between the physical network and the logical network, the topology of the cloud computing network is established, and based on the network topology, the relevant network theory is used to analyze the cloud computing network. The avalanche failure under the computing network is studied. The research results show that the relative performance under different trusted measurement periods can reach more than 97%, which can flexibly meet the needs of user trusted authentication and can effectively provide trusted protection for user virtual machines. Adding additional protection measures to some special nodes in the cloud computing network topology to ensure that they are not damaged when attacked can greatly improve the robustness of the entire cloud computing network topology, therby ensuring that the network can avoid the attack. A large area will not be paralyzed due to the avalanche effect, and at the same time, the function and topology of the network itself have not changed. This method can effectively improve the security protection effect in network security.
An Asymptotic Model for Solving Mixed Integral Equation in Position and Time
Authors: Jan A. R.
Published: August 2022

In this paper, we considered a mixed integral equation (MIE) of the second kind in the space L2[−b, b] × C[0, T], T < 1. The kernel of position has a singularity and takes some different famous forms, while the kernels of time are positive and continuous. Using an asymptotic method of separating the variables, we have a Fredholm integral equation (FIE) in position with variable parameters in time. Then, using the Toeplitz matrix method (TMM), we obtain a linear algebraic system (LAS) that can be solved numerically. Some applications with the aid of the maple 18 program are discussed when the kernel takes Coleman function, Cauchy kernel, Hilbert kernel, and a generalized logarithmic function. Also the error estimate, in each case, is computed.