bluuebunny/crossref_metadata_2025 huggingface dataset:
A Method to Improve the Performance of Arrays for Aperture-Level Simultaneous Transmit and Receive
Authors: Hu Dujuan , Wei Xizhang , Xie Mingcong , Tang Yanqun
Published: July 2022

The simultaneous transmit and receive (STAR) system needs to establish sufficiently high isolation between the transmitter and the receiver in order to play its role. However, due to the nonlinear characteristics and the accompanying noise of the active devices in the system, the coupling from the transmit channel to the receive channel cannot be accurately estimated in massive arrays, making it hard to improve the isolation between the transmit and receive channels. This paper proposes a new method to enhance isolation for aperture-level transmitting array and receiving array. The method uses the transmit and receive beamforming technology and aperture optimization technology to enhance the isolation between the transmitting aperture and the receiving aperture. The experimental results show that when the transmit power of an 8-element Vivaldi array is 30 W, the effective isotropic isolation (EII) peak value reaches 153.9 dB. The noise floor of the system is −89.9 dBm. Compared to only using aperture optimization and only using beamforming technology, the scheme in this paper, respectively, improves the isolation of 20.69 and 6.17 dB.
Risk Factors and Prognostic Analysis of Gastrointestinal Stromal Tumor Recurrence-Metastasis
Authors: Chen Shan , Sang Kanru , Chen Wenjing , Jin Jinji , Chen Xiaolei , Zhu Guanbao , Wang Pengfei , Cai Yiqi
Published: July 2022

Objective. Gastrointestinal stromal tumors (GISTs) are potential malignancies that occur in the digestive tract. This study aimed to investigate the risk factors and prognosis of recurrence and metastasis of gastrointestinal stromal tumor (GIST). Methods. From January 2018 to December 2019, 422 patients with GIST who received surgery in the First Affiliated Hospital of Wenzhou Medical University were enrolled. Their clinical data were retrospectively analyzed, and their follow-ups were continued until March 31, 2022. Subsequently, univariate and multivariate Cox analyses, survival curves, and nomograms were adopted to explore the relationship between clinicopathological characteristics and recurrence or metastasis in patients with GIST. Results. Univariate and multivariate Cox analysis exhibited that the prognosis of patients was affected by tumor rupture (

P
=
0.040

), tumor location (

P
<
0.001

), tumor diameter (

P
=
0.016

), mitotic figures (

P
<
0.001

), and risk grade (

P
<
0.009

). The above variables were selected to create the nomogram for 3-year disease-free survival (DFS). The 3-year the ROC (receiver operating characteristic) curves of the nomogram were (0.878 95% confidence interval [CI]: 0.871–0.939). Conclusion. Collectively, risk factors affecting postoperative recurrence or metastasis of GIST consist of primary site of tumors, tumor rupture, tumor diameter >10 cm, high-risk tumor classification, and mitotic figures ≥10 per 50 HPFs. And the application of nomogram may help physicians provide individualized diagnosis and treatment for patients with GISTs following surgical resection.
Research on Remaining Oil Characterization in Superheavy Oil Reservoir by Microgravity Exploration
Authors: Lv Qijun , Zheng Aiping , Liang Xiangjin , Chen Hongfei , Ju Shichang , Meng Yanchong , Zhang Hongyuan , He Guolin , Deng Shenshen , Li Junfang
Published: July 2022

Some physical processes such as oil and gas development, metal deposit collection, and groundwater resource migration can cause density changes, for which microgravity monitoring is the most intuitive method to monitor the density change process. Based on the basic principle of microgravity measurement and the idea of multiscale separation, a multiscale, second-order, surface-fitting, residual gravity anomaly extraction method is proposed to separate superimposed microgravity fields. In this method, regional fields of different scales are fitted and calculated successively with the measurement points as the center, so as to separate the gravity anomalies produced by different-depth density bodies. Results from actual data show that this method extracts the reservoir’s residual density characteristics of plane gravity anomaly on the basis of remaining oil distribution characteristics, consistent with reservoir numerical simulation results. A three-dimensional least-squares inversion of the method for extracting residual gravity anomaly was carried out, with the inversion results consistent with the results of vertical remaining oil distribution characteristics and well-test production results.
Design and Application of Legally Valid Payment Templates Based on Linking Contracts
Authors: Zhu Yue
Published: July 2022

Smart contracts are widely employed in many industries as a result of the high-quality development of science and economic technology, as well as the introduction of blockchain, which can automatically conduct retrieval, verification, and payment tasks. Smart contracts as an emerging topic, particularly the study of smart legal contracts, must remain forward-looking, and the smart contract sector cannot wait for the legal status of smart contracts to be resolved before advancing. The relative lag of the law becomes unavoidable due to the unassembled and unpredictable character of the law and thus its legislation. In this paper, we explore the incorporation of smart contracts into the scope of legal regulation, the construction of a series of systems for smart contracts, and the prognosis of smart contracts in terms of contract logic, arbitration process, and formal verification from the current law. Furthermore, a smart contract payment template based on semantic-aware graph neural networks is proposed to address the traditional smart contract vulnerability detection payment template method’s low detection accuracy and high false alarm rate, as well as the neural network-based method’s insufficient mining of bytecode-level smart contract features. Experiments comparing the method described in this research to comparable methods reveal that the strategy proposed in this study improves all types of indicators significantly.
Phytochemical Analysis, Acute Toxicity, as well as Antihyperglycemic and Antidiabetic Activities of Corchorus olitorius L. Leaf Extracts
Authors: Nakaziba Rebecca , Lubega Aloysius , Ogwal-Okeng Jasper , Alele Paul E.
Published: July 2022

Backgroundand Aim. Diabetes mellitus is a metabolic disorder that has no known cure with continuous endeavors to find a therapy for the condition. According to some studies, traditional leafy vegetables could prevent and manage diabetes by modifying the carbohydrate and lipid metabolism. In this study, a phytochemical analysis, acute toxicity, as well as antihyperglycemic and antidiabetic activity testing of the methanolic, diethyl ether, and aqueous leaf extracts of Corchorus olitorius L. was performed. Materials and Methods. Methanolic, diethyl ether, and aqueous leaf extracts of Corchorus olitorius L. were prepared by serial extraction. Phytochemical analysis was performed following standard methods. 52 mice were separated into 13 groups (A–M) of 4 and received extracts’ doses ranging from 1000 mg/kg to 5000 mg/kg for the acute toxicity testing. For the antihyperglycemic and antidiabetic activities testing, 48 rats were divided into 8 groups of 6 and received 500 mg/kg of each extract. 10 mg/kg of glibenclamide and distilled water were used as controls. Data were analyzed using Prism GraphPad version 8.0.2 (263). Results. Phytochemical analysis revealed the presence of alkaloids, reducing sugars, saponins, and terpenoids. There were no acute toxicity signs observed in this study. Corchorus olitorius L. extracts demonstrated moderate antihyperglycemic and antidiabetic activities. The methanolic extract exhibited the highest degree of antihyperglycemic activity. However, there was no statistically significant difference between the extracts and the negative control (

p
>
0.05

), but with glibenclamide (

p
<
0.01

). Conclusion. Corchorus olitorius L. is a safe and potential postprandial antidiabetic vegetable that could minimize the rise in blood glucose after a meal. We therefore recommend further investigations into the antidiabetic properties of the vegetable using purified extracts.
TSTELM: Two-Stage Transfer Extreme Learning Machine for Unsupervised Domain Adaptation
Authors: Zang Shaofei , Li Xinghai , Ma Jianwei , Yan Yongyi , Gao Jiwei , Wei Yuan
Published: July 2022

As a single-layer feedforward network (SLFN), extreme learning machine (ELM) has been successfully applied for classification and regression in machine learning due to its faster training speed and better generalization. However, it will perform poorly for domain adaptation in which the distributions between training data and testing data are inconsistent. In this article, we propose a novel ELM called two-stage transfer extreme learning machine (TSTELM) to solve this problem. At the statistical matching stage, we adopt maximum mean discrepancy (MMD) to narrow the distribution difference of the output layer between domains. In addition, at the subspace alignment stage, we align the source and target model parameters, design target cross-domain mean approximation, and add the output weight approximation to further promote the knowledge transferring across domains. Moreover, the prediction of test sample is jointly determined by the ELM parameters generated at the two stages. Finally, we investigate the proposed approach in classification task and conduct experiments on four public domain adaptation datasets. The result indicates that TSTELM could effectively enhance the knowledge transfer ability of ELM with higher accuracy than other existing transfer and non-transfer classifiers.
Effects of Resistant Starch on Patients with Chronic Kidney Disease: A Systematic Review and Meta-Analysis
Authors: Du Xinyi , Wu Jing , Gao Chenlin , Tan Qinqin , Xu Yong
Published: July 2022

Background. Chronic kidney disease (CKD) is a main health problem associated with increased risk of cardiovascular disease, morbidity, and mortality. Recent studies shown that the progression of CKD may be related to the change of intestinal flora. Resistant starch (RS) is a type of dietary fiber that can act as a substrate for microbial fermentation. Some studies have found that the supplementation of RS can improve the intestinal flora disorder in CKD patients. However, the specific effect of RS on CKD patients remains controversial. Objective. We designed this meta-analysis to identify and assess the effects of RS on patients with CKD. Methods. A comprehensive search of MEDLINE, Embase, Web of Science, and Cochrane systematic review databases was conducted in January 2020, and all new trials were updated in August 2021. Randomized trials were collected to assess the effects of RS on patients with CKD. The weighted average effect size of the net change was calculated by using the random-effects model. Results. The meta-analysis included 8 studies involving 301 participants. RS intake significantly reduced serum indolephenol sulfate (IS), blood phosphorus, IL-6, and uric acid levels in dialysis patients. The mean difference (MD) of serum IS (

P
=
0.0002

) in the dialysis subgroup was -12.57 μmol/L (95% CI: -19.28, -5.86 μmol/L). The MD of blood phosphorus (

P
=
0.03

) was -0.39 mg/dl (95% CI: -0.78, -0.01 mg/dl). The MD of serum uric acid (

P
=
0.004

) between the dialysis subgroup and the nondialysis subgroup was -31.58 mmol/L (95% CI: -52.99, -10.17 mmol/L). The mean difference (MD) of IL-6 (

P
=
0.02

) in the dialysis subgroup was -1.16 μmol/L (95% CI: -2.16, -0.16 μmol/L). However, there was no significant change of RS on hs-CRP, serum creatinine, blood urea nitrogen (BUN), blood paracresol sulfate, and blood lipid. Conclusions. The intake of RS reduced the serum IS, serum phosphorus, IL-6, and uric acid levels significantly in dialysis patients, while hs-CRP, serum creatinine, BUN, serum paracresol sulfate, and blood lipid showed no significant changes.
Enhanced Path Routing with Buffer Allocation Method Using Coupling Node Selection Algorithm in MANET
Authors: Bharti Rajendra Kumar , S Soundarajan , Sumant Sushma V. , Durai C. Anand Deva , Kumar Relangi Anil , Singh Kamlesh , Palivela Hemant , Kumar B. Rajesh , Debtera Baru
Published: July 2022

In a mobile network, nodes are placed in infrequent manner, which are moved along network in abruptly. Communication flaw between sender node and accepting node in path, the node having restricted energy and restricted transmission rate. It does not provide perfect route for communication among mobile nodes. It increases the packet drop rate and minimizes the lifetime of network. This work has proposed enhanced path routing with buffer allocation (IPBA) scheme which is implemented to obtain better communication; it protects the node from packet loss, and the buffer is used to maintain the temporary details of nodes and data packets that are ready to broadcast and receive. The coupling node selection algorithm is constructed to offer the path which frequently communicates data packets in normal case; the two efficient nodes are coupled with each other, and this type of nodes is selected to perform communication. It reduces the packet loss rate and increases network lifetime. End-to-end delay, communication overhead, throughput, network lifetime, packet loss, and energy consumption are the parameters considered for performance evaluations.
Decompositions of Circulant-Balanced Complete Multipartite Graphs Based on a Novel Labelling Approach
Authors: El-Mesady A. , Bazighifan Omar
Published: July 2022

For applied scientists and engineers, graph theory is a strong and vital tool for evaluating and inventing solutions for a variety of issues. Graph theory is extremely important in complex systems, particularly in computer science. Many scientific areas use graph theory, including biological sciences, engineering, coding, and operational research. A strategy for the orthogonal labelling of a bipartite graph

G

with

n

edges has been proposed in the literature, yielding cyclic decompositions of balanced complete bipartite graphs

K

n
,
n

by the graph

G

. A generalization to circulant-balanced complete multipartite graphs

K

n
,
n
,
⋯
,
n

⏟

m

;
m
,
n
≥
2
,

is our objective here. In this paper, we expand the orthogonal labelling approach used to generate cyclic decompositions for

K

n
,
n

to a generalized orthogonal labelling approach that may be used for decomposing

K

n
,
n
,
⋯
,
n

⏟

m

. We can decompose

K

n
,
n
,
⋯
,
n

⏟

m

into distinct graph classes based on the proposed generalized orthogonal labelling approach.
Study on Vertical Joint Performance of Single-Faced Superposed Shear Wall Based on Finite Element Analysis and Calculation
Authors: Fang Gao-Ni , Hou Rong-Cheng , Ma Wei , Xu Kai
Published: July 2022

In this paper, a new type of single-faced superposed shear wall system is proposed based on the single-faced superposed shear wall structure. The nonlinear finite element analysis of a new splicing form of single-faced superposed shear wall components is carried out by using the method of combining experimental research and ABAQUS finite element software analysis. The impact of noncolumn on the connection performance of vertical seam is studied. The analysis shows no significant difference in the effect of eliminating concealed column on the hysteretic performance and bearing capacity of the single-faced superposed shear wall with the joint. The single-faced composite shear wall with two different splicing forms presents bending-shear failure. The single-faced composite shear wall model without concealed column design can also maintain good overall performance and seismic behavior.
A Dual-Polarized Dual-Band Patch Antenna Based on Orthogonal Modes Manipulation
Authors: Liu Run , Tian Xiaoqing , Sima Boyu , Sun Zhiwei , Yu Yantao , Cao Hailin
Published: July 2022

In this paper, a co-caliber structure for dual-polarized dual-band (DPDB) radiation is presented through cross-polarized modes manipulation. After introducing slots and a connection branch into a typical patch antenna, two orthogonal radiation modes with different electrical-length achieved a meandered current mode at the lower frequency and a patch radiation mode at the higher frequency. The radiation patterns at both frequencies are patch-like, benefitting from certain feeding designs. The dual frequencies can be manipulated independently since their working modes are independent. In addition, compared with the traditional patch, the proposed antenna performs a higher aperture efficiency with a miniaturized antenna dimension. The antenna is finally fabricated and measured. The measured results showed that the antenna is evidently cross-polarized working at 10.38 GHz and 14.2 GHz and the gains are 5.57 dB and 6.82 dB, respectively. With the advantages of being compact, easily fabricated, and integrated, the proposed antenna can be potentially utilized in antenna research, polarization manipulation, multichannel communication system, and so on.
Performance Comparison of GeneXpert MTB/RIF, Gene Chip Technology, and Modified Roche Culture Method in Detecting Mycobacterium tuberculosis and Drug Susceptibility in Sputum
Authors: Xie Changli , Hu Xin , Liu Yali , Shu Chengfeng
Published: July 2022

Our aim of this study was to observe and analyze the performance of the real‐time fluorescence quantitative nucleic acid amplification detection of Mycobacterium tuberculosis/rifampicin resistance (GeneXpert MTB/RIF), gene chip technology, and modified Roche culture method in detecting MTB in sputum submitted for inspection and drug susceptibility. Patients with smear‐negative suspected pulmonary TB (n = 120) in our hospital were enrolled in this study using a random number table, and sputum samples submitted for inspection were tested by the GeneXpert MTB/RIF, gene chip technology, and modified Roche culture method. With clinical diagnosis as the gold standard, the performance (mainly sensitivity and specificity) of the above three detection methods in the diagnosis of MTB was compared. Next, the drug susceptibility test (DST) was carried out on sputum samples, tested positive by the three methods. With the solid culture results as the evaluation criteria, the performance of the three detection methods in the diagnosis MTB and DST was compared. When compared with the modified Roche culture method, the GeneXpert MTB/RIF had the highest positive rate and a shorter overall test duration (P < 0.05). In contrast with the gene chip technology, the GeneXpert MTB/RIF exhibited higher sensitivity and negative predictive value (NPV) and lower specificity, accuracy, positive predictive value (PPV), and Kappa value (P < 0.05). According to analysis of the diagnostic performance of the three detection methods, GeneXpert MTB/RIF displayed the highest diagnostic sensitivity, ideal predictive values, and the highest similarity with clinical diagnosis in results (P < 0.05). The detection of susceptibility to isoniazid (INH) and RIF showed that the GeneXpert MTB/RIF and gene chip technology performed ideally in DST of MTB. In comparison with the modified Roche culture method, the GeneXpert MTB/RIF and gene chip technology have more prominent performance in detecting MTB and drug susceptibility. Besides, to further improve the accuracy of clinical diagnosis, various molecular biology detection methods can be combined to avoid delaying of the best time for the diagnosis and treatment of the disease.
Effect of Blueberry Extract on Liver in Aged Rats
Authors: Albrahim Tarfa , Alonazi Mona
Published: July 2022

Aging and age-related disorders are prominent issues. Aging is associated with a gradual impairment of physiology at the genetic, cellular, tissue, and whole organism level that directly influences the development of chronic diseases and organ failure. Blueberries, on the other hand, are well known for their high content of bioactive compounds and have demonstrated positive impacts on metabolic factors that influence health and general well-being. This study is aimed at evaluating the ameliorating the effects of blueberry on the liver of aged rats by monitoring changes in metabolic disturbances, oxidative stress, and inflammatory disruption. The aged group of rats was orally administered with blueberry extract (200 mg/kg) for a period of 4 weeks. The results revealed that aging was associated with an increase in body weight, liver weight, and metabolic parameters like serum insulin, triglycerides, total cholesterol, and liver function markers accompanied with a decrease in vitamin D levels. Furthermore, the results showed a significant diminish in the activities of antioxidant enzymes, glutathione content with an elevation in lipid peroxidation, inflammatory mediators (tumor necrosis factor alpha, interleukin 6, and nuclear factor kappa-light-chain-enhancer of activated B cells) as well as fibrotic markers (TGF-β1) in the liver of aged rats. Compared to the young rats (control group), blueberry effectively reversed age-mediated disruption of the aforementioned parameters. Hence, blueberries can be used as a potential therapeutic strategy for the management of age-related liver dysfunction and disease.
RSM‐Based Optimization of Fermentation Conditions and Kinetic Studies of Glutamic Acid and Lysine Production by Corynebacterium glutamicum
Authors: Bashir Saira , Bashir Rashida , Pervaiz Muhammad , Adnan Ahmad , Al-Qahtani Wahidah H. , Sillanpaa Mika
Published: July 2022

Corynebacterium glutamicum is an authenticated microorganism that supports amino acid production consistent with dietary importance. Fermentation parameters like temperature, agitation speed, and carbon source concentration were optimized using response surface methodology. Surface response model suggested that optimal fermentation parameters including 30°C, 50 g/L glucose concentration, and shaking speed of 120 rpm furnished 14.2 g/L of glutamic acid and 5.1 g/L lysine, comparable with the predicted values. After optimizing fermentation parameters in shake flasks, the fermentation kinetics was studied in a stirred fermenter. The kinetic study revealed that the substrate consumption rate achieved a maximum level of 3.36 g/L/hour between 12 and 18 hours; afterwards, it decreased and fell to 1.9 g/L/hour. Average biomass yield over a period of 48 hours was 0.337 g/L; however, maximum biomass yield of 0.51 g/L was noted between 10 and 20 hours. Overall molar yield coefficient of CO2 () was found to be 0.234. The molar yield coefficient of biomass () was 0.6 in exponential phase which decreased afterwards. This study indicates that the average biomass yield over a time of 48 hours was 0.337 g/L, with a maximum yield within 10 to 20 hours obtained under optimized conditions. The molar yield coefficient of CO2 () was found to be 0.234. The molar yield coefficient of biomass () was 0.6 in exponential phase which decreased and fell to near zero at 48 hrs.
Evaluation Method of Industrial Efficiency of Green Manufacturing Enterprises Based on Machine Learning
Authors: Hao Xiaoyan
Published: July 2022

The cultural construction in the process of industrialization is intertwined with the culture required by the development of green manufacturing industry, which has become the growth point of economic construction and the new trend of economic development. Efficiency is the basis for the development of various industries. If we do not improve efficiency, industrial development will cause waste of resources and environmental pollution. Therefore, this study proposes a new evaluation method of green industrial manufacturing efficiency. The proposed method suggests cultural enterprises. In addition, this study examines the cultural green manufacturing industry productivity of cultural enterprises and combines it with machine learning. The excellent performance of neural network in prediction makes it possible to predict the efficiency of green manufacturing industry of cultural enterprises. Genetic algorithm is also proposed to optimize BP network. This algorithm is easy to operate and requires few parameters. In the process of finding the optimal solution, the optimal individual in the group can be used to control the iterative process. The particle swarm optimization algorithm is improved and combined with genetic algorithm to get an improved hybrid algorithm. BP network is optimized, and an improved BP network prediction model is established to evaluate the efficiency of green manufacturing industry of cultural enterprises. A large number of experiments have proved the effectiveness and reliability of this method. Separate simulations and results are presented to verify the effectiveness of the proposed model.
Intelligent Data Processing and Optimization of University Logistics Combined with Block Chain Storage Algorithm
Authors: Li Li
Published: July 2022

The traditional Hadoop-based logistic data processing platform of universities cannot fully collect and control remote data in the process of data processing and has defects such as poor efficiency, high error, and difficult query. In existing designs, devices often need to store complete block data. When retrieving or verifying specific data on the chain, a large number of blocks need to be traversed to find the corresponding data, which reduces the response speed on the user side. In addition, the traditional consensus algorithm is not suitable for resource-constrained terminal devices. Therefore, this paper proposes an intelligent data processing and optimization method of university logistics combined with block chain storage algorithm. For unstructured data on the cloud storage network, the storage information can be obtained through domain analysis, and the storage frequency can be dynamically adjusted based on the estimated data flapping. Moreover, a data storage audit scheme is designed on the cloud storage network to improve data storage efficiency. In order to ensure the integrity verification efficiency of unstructured big data cloud storage, a multilayer block chain network model suitable for university logistics data is designed by introducing block chain technology. The throughput and average occupancy under the same conditions in different environments are evaluated and analyzed, and it is verified that the proposed method is not affected by the initial priority distribution and has good stability and optimization performance. The results show that the proposed method can significantly improve the cloud storage efficiency of unstructured data, can effectively respond to a large number of requests to access data, and has good big data processing capability.
Long Noncoding RNA Zinc Finger Antisense 1 Affects Glucocorticoid-Induced Osteonecrosis of the Femoral Head by Performing as a ceRNA for MicroRNA-124-3p and Accelerating Transforming Growth Factor Type III Receptor
Authors: Lan Xiao Yong , Xiong YiPin , Ma HaiPing , Zou LingFeng , Yuan Zhen , Xiao YuHong
Published: July 2022

In recent years, plentiful studies have uncovered the long noncoding RNA’s (lncRNA’s) momentous functions in osteonecrosis of the femoral head (ONFH), but the specific mechanism has not been fully illustrated. The study was to figure out lncRNA Zinc finger antisense 1 (LncZFAS1)’s biological function and its latent downstream molecular mechanism in glucocorticoid- (GC-) induced ONFH. The results manifested LncZFAS1 and transforming growth factor type III receptor (TGFBR3) were elevated, while microRNA- (miR-) 124-3p was reduced in ONFH tissues and cells. Knockdown LncZFA1 reduced rat femoral cell apoptosis, perfected bone microstructure and bone density, and accelerated osteogenic proteins bone morphogenetic protein- (BMP-) 9, BMP-3, and osteocalcin. In vitro studies manifested knockdown LncZFAS1 prevented GC-induced reduction in osteoblast advancement with facilitating osteoblast calcification capacity, ALP activity, and osteogenic proteins. Elevation of LncZFAS1 further aggravated GC-induced osteoblast injury, but this effect was turned around by enhancement of miR-124-3p or knockdown of TGFBR3. Mechanistically, LncZFAS1 performed as a sponge for miR-124-3p to mediate TGFBR3 expression to motivate GC-induced ONFH. All in all, the results of this study indicate the LncZFAS1/miR-124-3p/TGFBR3 axis is supposed to be a latent therapeutic molecular target for GC-induced ONFH.
Quercetin Promotes TFEB Nuclear Translocation and Activates Lysosomal Degradation of Ferritin to Induce Ferroptosis in Breast Cancer Cells
Authors: An Songbo , Hu Mingyue
Published: July 2022

Objective. To investigate the antiproliferative efficacy of quercetin on breast cell lines and its mechanism of ferroptosis regulation. Cells (MCF-7 and MDA-231) were treated with quercetin at 0.1, 1, and 10 μM, respectively. The cell counting kit-8 (CCK-8) assay was applied to assess cell viability, and the intracellular iron level, malondialdehyde (MDA), and carbonylated protein were measured. After treating the cells with quercetin, western blot was applied to determine the level of transcription factor EB (TFEB) and lysosomal-associated membrane protein 1 (LAMP-1) in cells. Meanwhile, western blot was performed to assess the nuclear translocation of TFEB protein in cells. TFEB siRNA and autophagy lysosomal inhibitor, chloroquine, were used to block ferroptosis induced by quercetin. Quercetin induced breast cancer cell death and upregulated the level of iron, MDA, and carbonyl protein in a concentration-dependent manner. Meanwhile, TFEB was highly expressed in the nucleus and lowly expressed in the cytoplasm. The high expression of TFEB promoted the expression of lysosome-related gene LAMP-1, which in turn promoted the degradation of ferritin and the release of ferric ions. The above pharmacodynamic effects of quercetin can be blocked by TFEB siRNA or chloroquine. Quercetin promotes TFEB expression and nuclear transcription, induces the onset of iron death, and thus exerts a pharmacological effect on killing breast cancer cells.
Some New Inequalities for p‐Convex Functions via a K‐Fractional Conformable Integral
Authors: Dou Yan , Saleem Muhammad Shoaib , Anwar Nimra , Gao Haiping
Published: July 2022

The intention of this paper is to develop some new Hermite–Jensen–Mercer type inequalities for p−convex functions via k−fractional conformable integrals. Several existing results are also discussed which can be deduced from our results.
[Retracted] The Impact of Catalpol on Proliferation, Apoptosis, Migration, and Oxidative Stress of Lung Cancer Cells Based on Nrf2/ARE Signaling
Authors: Wang Huanyuan , Wu Jingtao , Fan Haiyin , Ji Yuan , Han Chunbin , Li Chao , Jiang Sicong
Published: July 2022

The effects of catalpol on lung cancer cell proliferation, apoptosis, migration, and oxidative stress via the Nrf2/ARE signaling pathway are investigated in this work. Catalpol‐12 g/mL group, catalpol‐24 g/mL group, catalpol‐48 g/mL group, catalpol − 48 g/mL + vector group, catalpol − 48 g/mL + Nrf2 group, si‐NC group, and si‐Nrf2 group were used to split lung cancer cells A549 into control groups. Proliferation was detected using the CCK‐8 assay; apoptosis was detected using flow cytometry; migration was detected using the transwell chamber; ROS was distinguished using the DCFHDA method; MDA, SOD, and GSH were detected using the microvolume method; and Cleaved Caspase‐3, Cleaved Caspase‐9, Nrf2, HO‐1, MMP‐9, and MMP‐2 were detected using the Western blot method. Catalpol 12 g/mL and 24 g/mL‐48 g/mL treatment decreased the proliferation activity, migration number, and Nrf2, HO‐1, MMP‐9, and MMP‐2 protein levels of lung cancer cells when compared to the control group. SOD and GSH levels of lung cancer cells were decreased, and MDA and ROS levels were increased. Cleaved caspase‐3, cleaved caspase‐9 protein expression levels, and apoptosis were boosted (P < 0.05). The proliferation activity, migration number, and protein levels of Nrf2, HO‐1, MMP‐9, and MMP‐2 in the catalpol − 48 g/mL + Nrf2 group were raised compared to the catalpol − 48 g/mL + vector group, whereas there was an apparent drop in the Cleaved Caspase‐3, Cleaved Caspase‐9, and apoptosis rate. Similarly, SOD and GSH contents increased, whereas MDA and ROS decreased (P < 0.05). The proliferation activity, migration number, and Nrf2, HO‐1, MMP‐9, and MMP‐2 protein levels of lung cancer cells in the si‐Nrf2 group were all decreased when compared to the si‐NC and control groups. Cleaved Caspase‐3 and Cleaved Caspase‐9 protein expression, on the other hand, increased as MDA and ROS levels were raised while SOD and GSH levels dropped (P < 0.05). It reveals that catalpol inhibits the Nrf2/ARE signaling pathway, which causes antiproliferation, migration, apoptosis, and oxidative stress in cancer cells of lungs. The rate of apoptosis was also lowered.
Nicotinamide Mononucleotide Ameliorates Cellular Senescence and Inflammation Caused by Sodium Iodate in RPE
Authors: Ren Chengda , Hu Chengyu , Wu Yan , Li Tingting , Zou Aiqi , Yu Donghui , Shen Tianyi , Cai Wenting , Yu Jing
Published: July 2022

Senescent cells have been demonstrated to have lower cellular NAD+ levels and are involved in the development of various age-related diseases, including age-related macular degeneration (AMD). Sodium iodate (NaIO3) has been primarily used as an oxidant to establish a model of dry AMD. Results of previous studies have showed that NaIO3 induced retinal tissue senescence in vivo. However, the role of NaIO3 and the mechanism by which it induces retinal pigment epithelium (RPE) senescence remains unknown. In this study, RPE cell senescence was confirmed to be potentially induced by NaIO3. The results showed that the number of senescence-associated-β-galactosidase (SA-β-gal-)-positive cells and the protein levels of p16 and p21 increased after NaIO3 treatment. Additionally, the senescent RPE cells underwent oxidative stress and NAD+ depletion. Furthermore, significant DNA damage and mitochondrial dysfunction were also detected in senescent RPE cells. The antioxidant N-acetylcysteine (NAC) could alleviate cellular senescence only by a minimal degree, whereas supplementation with nicotinamide mononucleotide (NMN) strongly ameliorated RPE senescence through the alleviation of DNA damage and the maintenance of mitochondrial function. The protective effects of NMN were demonstrated to rely on undisturbed Sirt1 signaling. Moreover, both the expression of senescence markers of RPE and subretinal inflammatory cell infiltration were decreased by NMN treatment in vivo. Our results indicate that RPE senescence induced by NaIO3 acquired several key features of AMD. More importantly, NMN may potentially be used to treat RPE senescence and senescence-associated pre-AMD changes by restoring the NAD+ levels in cells and tissues.
Construction of Robot Computer Image Segmentation Model Based on Partial Differential Equation
Authors: Zhang Quan
Published: July 2022

The application of partial differential equation in robot computer image smoothing and image segmentation based on curve evolution is studied to achieve the breakthrough and innovation of classical methods. First of all, the image is interpolated and enlarged, usually with double primary interpolation and double secondary interpolation. The robot computer image obtained by interpolation has a better effect on the smooth part of the image, but the edge becomes blurred. Then, the model is used to enhance the amplified image and remove the noise introduced during interpolation. In the process of PDE image segmentation, using the level set method, natural continuation cannot guarantee that the embedded function is always a signed distance function in the evolution process. The results show that compared with the classical fourth-order model, this model can well retain the details of the image, smooth bevels, and edges of the image. The proposed new model is better than the second-order model and the classical fourth-order model both in PSNR value and MAE value and in visual effect. Secondly, the model based on piecewise smooth Mumford-Shah not only expresses the original image better but also solves the problem of gradual image segmentation with gray value. Therefore, the robot computer image segmentation model based on partial differential equation can segment the image better.
Unsteady Electroosmotic Flow of Jeffrey Fluid in a Circular Microchannel under the Combined Action of Vertical Magnetic Field, External Electric Field, and Pressure at High Zeta Potential
Authors: Ren Meirong , Zhang Tiange , Cui Jifeng , Chen Xiaogang , Wu Bixia
Published: July 2022

The unsteady electroosmotic flow (EOF) for one kind of linear viscoelastic fluid, which is Jeffrey type fluid, is investigated under the common impact of vertical magnetic field, external electric field, and pressure at high Zeta potential in a circular microchannel. The numerical solutions of the potential and velocity distributions are obtained by solving the nonlinear Poisson-Boltzmann equation, the constitutive equation of the Jeffrey fluid, and the Cauchy momentum equation applying the Chebyshev spectral method and the finite difference method. By contrast, the Chebyshev spectral method has higher accuracy and less computation. The flow characteristics of Jeffrey fluid at high Zeta potential are analyzed with the numerical solution obtained by the Chebyshev spectral method. The results show that the velocity of Jeffrey fluid increases with the increase of the wall Zeta potential and electric width. The oscillation amplitude of velocity distribution increases with the increase of relaxation time but decreases with the increase of retardation time. When the Hartmann number is smaller, the increase of relaxation time leads to the increase of velocity; when the Hartmann number is larger, the increase of relaxation time leads to the decrease of velocity. No matter what the Hartmann number is, the velocity always decreases with the increase of the retardation time. The velocity tends to be stable gradually with the increase of time.
Deep Sentiment Analysis of Twitter Data Using a Hybrid Ghost Convolution Neural Network Model
Authors: Ali Al-Abyadh Mohammed Hasan , Iesa Mohamed A. M. , Hafeez Abdel Azeem Hani Abdel , Singh Devesh Pratap , Kumar Pardeep , Abdulamir Mohamed , Jalali Asadullah
Published: July 2022

Several problems remain, despite the evident advantages of sentiment analysis of public opinion represented on Twitter and Facebook. On complicated training data, hybrid approaches may reduce sentiment mistakes. This research assesses the dependability of numerous hybrid approaches on a variety of datasets. Across domains and datasets, we compare hybrid models to singles. Text tweets and reviews are included in our deep sentiment analysis learning systems. The support vector machine (SVM), Long Short-Term Memory (LSTM), and ghost model convolution neural network (CNN) are combined to get the hybrid model. The dependability and computation time of each approach were evaluated. On all datasets, hybrid models outperform single models when deep learning and SVM are combined. The traditional models were less trustworthy, and deep learning algorithms have recently shown their enormous promise in sentiment analysis. Linear transformations are used in feature maps to eliminate duplicate or related features. The ghost unit makes ghost features by taking away attributes that are both similar and duplicated from each intrinsic feature. LSTM produces higher results but takes longer to process, while CNN needs less hyperparameter adjusting and monitoring. The effectiveness of the integrated model varies depending on the work, and all performed better than the others. For hybrid deep sentiment analysis learning models, LSTM networks, CNNs, and SVMs are needed. Hybrid models are used to compare SVM, LSTM, and CNN, and we tested each method’s accuracy and errors. Deep learning-SVM hybrid models improve sentiment analysis accuracy. Experimental results have shown the accuracy of the proposed model shown 91.3 percent and 91.5 percent for datasets type 1 and 8, respectively.
GMAIR: Unsupervised Object Detection Based on Spatial Attention and Gaussian Mixture Model
Authors: Zhu Weijin , Shen Yao , Liu Mingqian , Aguirre Sanchez Lizeth Patricia
Published: July 2022

Recent studies on unsupervised object detection based on spatial attention have achieved promising results. Models, such as AIR and SPAIR, output “what” and “where” latent variables that represent the attributes and locations of objects in a scene, respectively. Most of the previous studies concentrate on the “where” localization performance. However, we claim that acquiring “what” object attributes is also essential for representation learning. This study presents a framework, GMAIR, for unsupervised object detection. It incorporates spatial attention and a Gaussian mixture in a unified deep generative model. GMAIR can locate objects in a scene and simultaneously cluster them without supervision. Furthermore, we analyze the “what” latent variables and clustering process. Finally, we evaluate our model on MultiMNIST and Fruit2D datasets. We show that GMAIR achieves competitive results on localization and clustering compared with state-of-the-art methods.
Impact of New Mobility Solutions on Travel Behaviour and Its Incorporation into Travel Demand Models
Authors: Garus Ada , Alonso Borja , Alonso Raposo Maria , Ciuffo Biagio , dell’Olio Luigi
Published: July 2022

Advancement in the fields of electrification, automation, and digitalisation and emerging social trends are fuelling the transformation of road transport resulting in the introduction of various innovative mobility solutions. Yet the reaction of people to many of the new solutions is still vastly unknown. This creates an unprecedented quandary for transport planners who are requested to design future transport systems and create the related investment plans without fully validated models to base the assessment upon. As some evidence on citizens’ behaviour concerning new mobility solutions starts to be progressively made available, first attempts to update the existing models begin to emerge. Nevertheless, a lot more is needed as some of the transpiring mobility solutions have not yet reached the market, making the corresponding behaviour changes imponderable. In this context, the main purpose of this paper is to provide a review on how travel behaviour changes linked to the deployment of new mobility solutions have been considered in travel demand models. The new mobility solutions studied include carsharing, dynamic ridesharing, micromobility sharing services, and personal and shared autonomous vehicles. An overview and comparison of relevant studies implementing activity or trip-based demand models and other methodologies are presented. The analysis shows that the results of the different studies heavily depend on the extent to which behavioural changes are considered. The results of the review thus point to the need for holistic demand models that carefully mimic the urban reality with everything it has to offer and account for the importance of individual traits in the decision-making processes. Such models need an in-depth understanding of the microscopic mechanisms leading to the travel behaviour shifts linked to the most innovative mobility solutions. To achieve this level of detail, mobility living labs and their real-life experiments and experience with citizens, which are flourishing in Europe, are suggested to play a crucial role in the years to come.
Investigating Static Deflection of Non-Prismatic Axially Functionally Graded Beam
Authors: Hashim Walaa Mohammed , Alansari Luay S. , Aljanabi Mohanad , Raheem Hassan Mansour
Published: July 2022

In this study, the static deflection of non-prismatic axial function graded tapered beam (A-FGB) under distribution load has been analyzed using ANSYS workbench (17.2). According to a power-law model, the elastic modulus of the beam varies continuously in the axial direction of the beam. Also, the beam’s geometry, i.e., width, thickness, or both width and thickness of the beam, varies linearly in the axial direction with different values of non-uniformity parameter (1, 0.5,0, −0.5, and −0.75). The effects of martial distribution, i.e., power-law index, and non-uniformity parameter on the static deflection for A-FGB with different boundary conditions, in such free-clamped, clamped-free, and simply-supported, are studied. This research deals with functionally graded materials FGMs in more than one aspect in terms of using different boundary conditions; in addition, it studies the response of the non-prismatic beam non-uniformity parameter (α); therefore, this research studies comprehensively the deflection of the beam. The results show that the increase in power-law index causes decreasing in dimensionless deflection and its rate of change depends on the supporting types of the beam and non-uniformity parameters. The variation in both width and thickness for a free-clamped axial function–graded beam gives a significant decrease in dimensionless deflection at decreasing in non-uniformity parameter, whereas the variation in thickness for clamped-free axial function graded beam gives a significant decrease in dimensionless deflection at decreasing of non-uniformity parameter.
su-Based Shaft Friction Design Method and Evaluation for Pipe Pile
Authors: Huang Bin , Zhang Yuting , Fu Xudong , Ye Ruiyu
Published: July 2022

The shaft friction in clay is essential to bearing capacity of pipe piles. Reasonable selection of design methods and parameters is very important for offshore piles. This paper focuses on the current popular vertical load design methods based on undrained strength for pipe piles, especially for offshore piles. Based on the database, the accuracy and reliability of various pile design methods based on undrained strength su in clay were reviewed. The small-scale model tests were conducted to evaluate su-based methods. For the shortcomings of small-diameter piles in the database, a field test of full-scale offshore pile was carried out and analysed. By comparing the calculated and the measured capacity for each method, the reliability of various design methods is evaluated for large-diameter piles. For the design methods based on undrained strength, it demonstrates the importance and reliability of the determination of undrained strength parameters. In view of the vertical loading conditions of offshore large-diameter steel pipe piles, reasonable suggestions for design methods and parameters determination are given.
Gender and Age Patterns in NSGA Swim Competitions
Authors: Doane David P. , Seward Lori E. , Murphy Kevin
Published: July 2022

We estimate two common nonlinear models (quadratic and semilog) and one new model (exponential) of the time-age relationship in 500-yard freestyle swim times in the U.S. National Senior Games (ages 50 and up) in six biennial NSGA competitions (2009, 2011, 2013, 2015, 2017, and 2019) for 468 men and 587 women. We use OLS and quantile regression (25%, 50%, and 75%) separately for each gender. The semilog model predicts faster times than the quadratic or exponential models. Our hypothesis that women slow down faster than men after age 50 is supported by both models as well as by our unique within-gender comparisons. Our findings of a nonlinear performance decline agree with studies of elite swimmers (Olympic, FINA). Our first-time study of NSGA data provides new guidelines to inform senior competitors. Our findings will assist trainers and community organizations that support NSGA competitions to promote a healthy senior lifestyle.