bluuebunny/crossref_metadata_2025 huggingface dataset:
Formability Characteristics and Penetration Performance of Micro-Jets from Different Materials
Authors: Han Yangyang , Yin Jianping , Wang Zhijun , Li Xudong , Bi GuangJian , Jia Zijian
Published: April 2022

A micro-unmanned aerial vehicle (UAV) swarm has high flexibility and intelligent unmanned flight and stealth capabilities. Moreover, it can attack both single and group targets, which will occupy dominant positions in the future information war. To satisfy the new micro-UAV swarm information combat mode and contribute to the advances in ammunition flexibility, efficiency, miniaturization, and multipurpose applicability, a 10 mm caliber micro-shaped charge warhead was designed in this study. The results indicate that the micro-shaped charge can be assembled with a micro-UAV swarm to efficiently damage the targets without relying on the weapon launch velocity. To realize a lightweight and high-efficiency micro-shaped charge structure, the formability of Teflon, nylon, polycarbonate (polycarb), and metallic copper liners was studied using the finite element analysis. The penetration efficiencies of different micro-jets on gelatin targets were compared and analyzed. It was found that the micro-shaped charge nylon and Teflon jets could pass through the gelatin target and transfer more energy to it compared with copper. The observed penetration aperture was also larger. Although the penetration depth of the polycarb jet to the target was the smallest, the penetration aperture was the largest. The findings of this study can serve as a basis for the development of micro-shaped charge technology.
Hyers–Ulam Stability Results for a Functional Inequality of

s
,
t

-Type in Banach Spaces
Authors: Suparatulatorn Raweerote , Chaobankoh Tanadon
Published: April 2022

We introduce an additive

s
,
t

-functional inequality where

s

and

t

are nonzero complex numbers with

2

s

+

t

<
1
.

Using the direct method and the fixed point method, we give the Hyers–Ulam stability of such functional inequality in Banach spaces.
Coot Optimization Algorithm for Optimal Placement of Photovoltaic Generators in Distribution Systems Considering Variation of Load and Solar Radiation
Authors: Kien Le Chi , Bich Nga Truong Thi , Phan Tan Minh , Nguyen Thang Trung
Published: April 2022

In this paper, photovoltaic generators (PVGs) are placed in radial distribution networks (RDNs) for reducing active power loss of one operation day by using three recently published metaheuristic algorithms including coot optimization algorithm (COOA), transient search algorithm (TSA), and crystal structure algorithm (CRSA). In one operation day, the variation of loads is considered, and the change of solar radiation over daytime is also taken. The study has two main contributions regarding the effectiveness of COOA: energy loss reduction and voltage improvement. COOA can reach high energy loss reduction, better solutions, and faster search speed than TSA and CRSA. In fact, COOA finds better energy loss than the algorithms by 1% and 1.77% for the IEEE 69-node system and 0.75% and 1.4% for the IEEE 85-node system. Furthermore, COOA is at least three times faster than CRSA and two times faster than TSA. As compared to a base system without PVGs, COOA can find better energy loss up to 60.96% and improve voltage up to 4.5%. Thus, COOA is a highly effective optimization tool with the optimal solution, high stability, and fast computation process for placing PVGs in RDNs.
Role of miR-584-5p in Lipopolysaccharide-Stimulated Human Bronchial Epithelial Cell Inflammation and Apoptosis
Authors: Zhang Bo , Zhang Qing , Yang Linying , Zheng Hongfei , Pang Guifen , Zhao Mingzhen , Sun Bo , Cao Jie
Published: April 2022

Acute lung injury (ALI)/acute respiratory distress syndrome is a common clinical syndrome characterized by respiratory failure. MicroRNAs (miRNAs) are closely related to ALI and acute respiratory distress syndrome. TargetScan software analysis showed that miR-584-5p can bind to the 3ʹ noncoding region of TLR4, which is involved in the occurrence and development of ALI, thereby affecting the inflammatory pathway and inflammation development. Thus, we aimed to determine whether miR-584-5p affects ALI. Human bronchial epithelial (16-HBE) cells were transfected with miR-584-5p mimics or inhibitors and then stimulated with lipopolysaccharide (LPS).The cell viability, apoptosis, release of proinflammatory factors, mTOR, and NF-κB pathway protein expression were evaluated respectively. Mimic584 increased, whereas inhibitor584 decreased, LPS-stimulated inflammation. The protein expression of inflammatory factors was significantly increased in 16-HBE cells in the mimic584 + LPS group and decreased in the inhibitor584 + LPS group. Mimic584 activated mTOR and the NF-κB-related proteins P65 and p-p65, whereas inhibitor584 inactivated the proteins in 16-HBE cells. Overexpression of miR-584 significantly promoted apoptosis in LPS-stimulated 16-HBE cells. There were no differences in the proliferation and cell cycle of LPS-stimulated 16-HBE cells regardless of mimic584 or inhibitor584 transfection. Collectively, we demonstrated that inhibitor584 can alleviate ALI-induced expression of inflammatory factors via mTOR signaling and the NF-κB pathway. In conclusion, we found that inhibitor584 transfection could be a potential therapeutic strategy for ALI.
Multiple Roles of Paeoniflorin in Alzheimer’s Disease
Authors: Meng Zeyu , Chen Huize , Deng Chujun , Meng Shengxi
Published: April 2022

Alzheimer’s disease (AD) is a geriatric disease with the morbidity and mortality continuing to grow, partly due to the aging of the world population. As one of the most common types of primary neurodegenerative dementia, it is mainly due to environmental, epigenetic, immunological, and genetic factors. Paeoniflorin (PF), the main component of paeony extract, plays a more and more important role in the prevention and treatment of AD, including regulating protein, anti-inflammation, antioxidation, and antiapoptosis, protecting glial cells, regulating neurotransmitters and related enzymes and receptors, and inhibiting or activating related signal pathways. This article summarizes the latest researches on the multiple effects and the mechanisms of PF in the treatment to cure AD, providing new insights and research basis for further clinical application of traditional Chinese medicine (TCM) in the treatment of AD.
Research on Numerical Simulation of Top‐Down Construction Effect of Diaphragm Wall of Deep and Large Foundation Pit under Different Working Conditions in Complex Stratum
Authors: Sun Fuxue , Liu Mingqing , Zhu Yunhui , Li Xiaochun , Ge Gang
Published: April 2022

In order to study the construction effect of deep and large foundation pit excavation and its impact on the surrounding environment under complex stratum conditions, the deep and large foundation pit of the top‐down construction method of shield exit shaft of S2 line of Wenzhou City railway is taken as the research object in this paper. According to the complex geological conditions of deep soft soil layer with underlying inclined rock surface in Wenzhou, the numerical simulation method is used to carry out the related research. The simulation results of the deformation characteristics of the diaphragm wall under two different working conditions which are the same length diaphragm wall and the suspended foot diaphragm wall are compared and analyzed. According to the analysis results, the suspended foot diaphragm wall is determined as the final construction scheme of the diaphragm wall, and it is verified by field measurement. The research results can provide technical support for the construction of similar projects. At the same time, it can also provide basic accumulation for the construction of major projects in Wenzhou.
Condition Monitoring of Mechanical Components Based on MEMED-NLOPE under Multiscale Features
Authors: Wang Xuan , She Bo , Shi Zhangsong , Sun Shiyan , Qin Fenqi
Published: April 2022

An increasing popularity of researches focuses on the vibration signal with the characteristics of nonstationary, nonlinear, and strong noise interference. A nonlinear dimension and feature reduction method called multiple empirical mode entropy decomposition-nonlocal orthogonal preserving embedding (MEMED-NLOPE) is proposed to implement condition monitoring in this paper. Different from multiple empirical mode decomposition (MEMD), MEMED adopts maximum entropy method, which can directly output the subsignal with the maximum correlation and realize nonlinear dimensionality reduction. Besides, multiscale feature extraction method is used during preprocessing nonlinear data process, which realizes feature reduction. Finally, nonlocal orthogonal preserving embedding algorithm-exponentially weighted moving average (NLOPE-EWMA) realizes the automatic detection of the fault. Taking the laboratory rolling bearing test and naval gun pendulum mechanism test as cases, the effectiveness of MEMED-NLOPE is verified.
Comparison of Clinical Efficacy and Safety between Misoprostol and Oxytocin in the Prevention of Postpartum Hemorrhage: A Meta-Analysis
Authors: Xu Renmei , Guo Yongjie , Zhang Qinggui , Zeng Xiaokang
Published: April 2022

In order to systematically evaluate the clinical efficacy and safety of misoprostol versus oxytocin in the prevention of postpartum hemorrhage, this paper provides evidence-based reference for clinical medication, computerized retrieval of Chinese biomedical literature database (CBM), PubMed, Embase, Cochrane Library, and clinical trials. The retrieval period is from the establishment of each database to October 1, 2021. Published randomized controlled trials (RCTS) are included in this study. The literature is screened and evaluated according to inclusion and exclusion criteria, and meta-analysis is performed using RevMan 5.3 software. A total of 13 RCTS are included, with a total of 24754 parturients. The meta-analysis shows the average blood loss (SMD = 0.10, 95% CI (−0.11, 0.32),

P
=
0.35

), the time of the third stage of labor (SMD = 0, 95% CI (−0.07, 0.08),

P
=
0.95

), and blood transfusion rate (RR = 0.80, 95% CI (0.63, 1.02),

P
=
0.07

). However, the incidences of shivering (RR = 2.61, 95% CI (1.79, 0.81),

P
<
0.00001

) and vomiting (RR = 2.78, 95% CI (1.85, 4.18),

P
<
0.00001

) are significantly higher than those in oxytocin group. The effect of misoprostol on preventing postpartum hemorrhage is similar to that of oxytocin, but the incidence of adverse reactions is high, and the occurrence of adverse reactions should be closely watched in the use process. Due to the limitations of the included studies, multicenter, large-sample, and high-quality RCTS are still needed in the future to further verify this conclusion.
The Color Planning Method of Shanghai New City Based on Big Data and Artificial Intelligence
Authors: Zhuang Yi
Published: April 2022

Due to the rapid development of my country’s urbanization construction, today’s cities, as a complex and unified combination of humanities, technology, and innovation, most of their core competitiveness highlights the color charm of the city. Urban color reflects the long history and rich urban life of a city. Only by combining the regional and cultural characteristics of the city can it be tailored to fully reflect the charm of the city. In recent years, the livability of cities has gradually attracted the attention of the public. Monotonous colors will not only make the city lose its overall beauty, but also make the residents living in it feel boring. Therefore, in recent years, many cities have carried out research on overall color planning, hoping to improve the overall beauty of the city through efforts and create a color matching scheme that is consistent with the urban culture. Taking Shanghai New City as an example, this paper uses big data technology and modern artificial intelligence technology to analyze the color matching strategies adopted in this area and puts forward suggestions for color optimization in combination with the current construction status and development planning in this area.
Multiobjective Particle Swarm Optimization Based on Ideal Distance
Authors: Wang Shihua , Liu Yanmin , Zou Kangge , Li Nana , Wu Yaowei
Published: April 2022

Recently, multiobjective particle swarm optimization (MOPSO) has been widely used in science and engineering, however how to effectively improve the convergence and distribution of the algorithm has always been a hot research topic on multiobjective optimization problems (MOPs). To solve this problem, we propose a multiobjective particle swarm optimization based on the ideal distance (IDMOPSO). In IDMOPSO, the adaptive grid and ideal distance are used to optimize and improve the selection method of global learning samples and the size control strategy of the external archive, and the fine‐tuning parameters are introduced to adjust particle flight in the swarm dynamically. Additionally, to prevent the algorithm from falling into a local optimum, the cosine factor is introduced to mutate the position of the particles during the exploitation and exploration process. Finally, IDMOPSO, several other popular MOPSOs and MOEAs were simulated on the benchmarks functions to test the performance of the proposed algorithm using IGD and HV indicators. The experimental results show that IDMOPSO has the better convergence, diversity, and excellent solution ability compared to the other algorithms.
Climate Change Adaptation Strategies by Indonesian Vegetable Farmers: Comparative Study of Organic and Conventional Farmers
Authors: Irham Irham , Fachrista Irma Audiah , Masyhuri Masyhuri , Suryantini Any
Published: April 2022

Some experts believe that organic agriculture is more adaptable compared to conventional agriculture. Accordingly, the purpose of this study is to assess organic and conventional farmers’ perception and adaptation to climate change and analyse the factors that influence such decisions. The survey was conducted in Java, involving 112 organic farmers and 112 conventional farmers. The chi-square test was used to differentiate climate change perceptions and adaptation strategies applied by farmers. The factors that influenced the selection of the adaptation strategies were analysed using logistic regression. The results of analysis found that organic farmers have more precise perceptions of climate change than that of conventional farmers. Organic farmers more commonly implement mixed cropping, crop rotation, increasing organic manure, using shade, and changing irrigation techniques as their adaptation strategies, while conventional farmers more commonly prefer to adjust planting and harvesting dates and use traditional climate prediction called Pranata Mangsa. The selection of farmers’ adaptation strategies is influenced by age, education, experience, distance to extension services, access to credit, information about climate and farmer groups, as well as farmers’ perceptions of climate change. The results of the study recommend that policy makers increase farmers’ adaptive capacity through investment in education and institutions to support climate change adaptation.
Interaction Context-Aware Network Behavior Anomaly Detection for Discovering Unknown Attacks
Authors: Qin Zhi-Quan , Xu Hong-Zuo , Ma Xing-Kong , Wang Yong-Jun
Published: April 2022

Network behavior anomaly detection is an effective approach to discover unknown attacks, where generating high-efficacy network behavior representation is one of the most crucial parts. Nowadays, complicated network environments and advancing attack techniques make it more challenging. Existing methods cannot yield satisfied representations that express the semantics of network behaviors comprehensively. To tackle this problem, we propose XNBAD, a novel unsupervised network behavior anomaly detection framework, in this work. It integrates the timely high-order host states under the dynamic interaction context with the conversation patterns between hosts for behavior representation. High-order states can better summarize latent interaction patterns, but they are hard to be obtained directly. Therefore, XNBAD utilizes a graph neural network (GNN) to automatically generate high-order features from series of extracted base ones. We evaluated the detection performance of XNBAD in a publicly available benchmark dataset ISCX-2012. To report detailed and precise experimental results, we carefully refined the dataset before evaluation. The results show that XNBAD discovered various attack behaviors more effectively, and it significantly outperformed the existing representative methods by at least

3.8
%

relative improvement in terms of the overall weighted AUC.
Single‐Step Acer pentapomicum‐Mediated Green Synthesis of Silver Nanoparticles and Their Potential Antimicrobial and Antioxidant Activities
Authors: Khan Shehla , Almarhoon Zainab M. , Bakht Jehan , Mabkhot Yahia N. , Rauf Abdur , Shad Anwar Ali
Published: April 2022

The current investigation is aimed at synthesizing nonhazardous, ecofriendly silver nanoparticles (AgNPs) from aqueous leaf extract of Acer pentapomicum and at evaluating its antibacterial, antifungal, and antioxidant activities. In the present study, AgNPs were synthesized at room temperature by mixing 7 mL of 1 mM AgNO3 with 1 mL of A. pentapomicum leaf extract. The synthesized AgNPs were then characterized via various techniques, including UV/visible spectrophotometry showing maximum absorbance at 450 nm. Scanning electron microscopy (SEM) reveals a spherical shape of AgNPs with a size range of 19‐25 nm, while the average crystalline nanosize of 9.5 nm and crystalline nature were confirmed by XRD. FTIR showing a broad signal of 3394.71 which confirmed the coating of phenolic and alcoholic compounds on AgNPs, indicating their possible role in the capping and stabilization of silver nanoparticles. EDX showed the elemental composition of the synthesized nanoparticles. Our AgNPs were also found stable at a temperature of 55°C and pH range of 6‐7 and in the presence of a salt solution. Furthermore, the green synthesized AgNPs were found to exhibit potent antibacterial activity against various bacterial species, with a maximum of 66% inhibition against Pseudomonas aeruginosa and 50.5% against E. coli and Xanthomonas campestris. These nanoparticles also possess good antifungal activity against various fungal species. Regarding the antioxidant activity, the AgNPs were found to possess a maximum of 93% antioxidant activity against DPPH at a concentration of 250 μg/mL and a minimum of 74% scavenging activity at 5 μg/mL.
Research on the Impact of Digital Finance on the Green Development of Chinese Cities
Authors: Zhao Jianhua , He Guohua
Published: April 2022

This paper takes 286 prefecture‐level Chinese cities from 2011 to 2019 as research objects. It empirically examines the influence of digital finance on green development by using the EBM model, two‐way fixed effect model, and instrumental variable method. It is found that digital finance can significantly promote the green development of Chinese cities, and this conclusion is still valid after the robustness tests, such as the instrumental variable method dealing with endogeneity and two‐sided winsorization. The mechanism analysis results suggest that only the breadth of digital finance can significantly promote green development in the internal mechanism of digital finance, but the effect of coverage depth and digitization degree is not significant. The external mechanism of industrial structure upgrading assumes the mediating role of digital finance in improving the level of green development. The heterogeneity analysis results show that digital finance has a stronger impact on green development in the central and western cities and small‐scale cities. This paper contributes to the study of the relationship between digital finance and green development and puts forward relevant suggestions.
Humeral Capitellum Fractures in Adolescents: A Study of 6 Cases Treated by Open Reduction and Internal Fixation with Bioabsorbable Nails
Authors: Wiktor Łukasz , Tomaszewski Ryszard
Published: April 2022

Purpose. The purpose of our study was to evaluate the clinical outcome following open reduction and internal fixation of humeral capitellum fractures in adolescents and to assess the usefulness of bioresorbable implants in that procedure. Due to the rarity of these fractures, there are not many studies dealing with the problem in the literature. Methods. We retrospectively evaluated a group of 6 skeletally immature patients aged 10.6–15.3 treated at our department from January 2015 to December 2021. Four type I and two type IV were diagnosed based on the Bryan and Morrey classification. Our patients underwent an open reduction and internal fixation of coronal shear fractures with the use of SmartNail®. Results. All patients were satisfied with the treatment outcome and had full pronation and flexion after surgery. Two patients presented minor deficits of extension and supination compared with the contralateral elbow. At the one-year follow-up, all patients scored 100 on the Mayo Elbow Performance Score. Conclusions. Correct diagnosis and early surgical intervention in humeral capitellum fractures are crucial. That fractures should be anatomically reduced with no articular cartilage damage in order to prevent osteoarthritis. Based on our experience, SmartNail® implant is accurate for the osteochondral fragment fixation.
CRITIC‐Based Vertical Collusion Control Quality Prediction Based on the Coupling and Coordination Degrees of Socioenvironmental and Public‐Investment Bidding Systems in China
Authors: Ma Chongsen , Chen Yun , Ou Liang , Jiang Kangyang
Published: April 2022

Currently, in China, the bidding processes for government socioenvironmental projects face threats of collusion between officials and vendors. This study introduces a coupling and coordination degree‐measurement model to study the relationship between the quality of vertical collusion controls and the socioenvironmental system of China based on bidding data taken from 2006 to 2020. The coupling degree describes the socioeconomic influence felt between systems, and the coordination degree refers to their sustainable focused cooperation and mutual influence. The criteria importance through intercriteria correlation method was used to quantify these degrees. To smooth out periods of missing data, the autoregressive integrated moving average model was employed, and the first‐order, one‐variable, time‐series forecasting method was then used to project the trend to 2025. The results revealed that the quality of vertical collusion controls based on the degrees of coupling and coordination between external socioenvironmental and public investment systems ranged from 0.151 to 0.700. Dissonance was detected from 2006 to 2015, but the overall coupling degree has been on an upward trend, peaking in 2020. Currently, the quality of vertical collusion controls is in its primary coordination stage, although it is improving rapidly. From the projected years, both coupling and coordination degrees will enter an intermediate coordination stage by 2022, when the growth rate of the coupling degree is overtaken by that of the coordination degree, as long as active strategies are applied to harmonize the systems in terms of anticollusion measures.
Image Segmentation Techniques for Intelligent Monitoring of Putonghua Examinations
Authors: Liu Hui
Published: April 2022

Image recognition and image processing usually contain the technique of image segmentation. Excellent segmentation results can directly affect the accuracy of image recognition and processing. The essence of image segmentation is to segment each frame of a certain image or a video into multiple specific objects or regions and represent them with different labels. This paper focuses on the segmentation results obtained in image segmentation of images used for intelligent monitoring of Mandarin exams are usually visualized for image analysis. In this paper, we first investigate the performance improvement techniques for semantic segmentation in the image segmentation task for intelligent monitoring of Mandarin exams, improve the pixel classification capability by performing semantic migration, and, for the first time, extend the dataset substantially by style transformation to improve the model’s recognition of advanced features. In addition, to further address the shortcomings of the dataset, this paper improves the performance of image segmentation using synthetic datasets by investigating synthetic dataset image segmentation improvement techniques that reduce the reliance on manually annotated datasets. Image segmentation techniques continue to advance, and there are even thousands of commonly used segmentation methods for image segmentation development to date. Among them, they can be broadly classified as region-based segmentation methods, threshold-based segmentation methods, edge-based segmentation methods, specific theory-based segmentation methods, and deep learning-based segmentation methods. However, the methods used in this paper have all been experimentally demonstrated to improve the effectiveness of the techniques and proved to outperform other existing methods in the same field in the publicly available datasets LSUN, Cityscapes, and GTA5 datasets, respectively.
Oxygen Dependence of Formation, Electronic State Transition, and Spin Polarization for Anatase TiO2: A Comprehensive Study
Authors: Shan L. L. , Fan R. M. , Sun Y. , Zhang F. P. , Zhang G. L. , Qin G. Q.
Published: April 2022

The stability, geometry, microstructure, and specie combination together with the electronic states of the anatase TiO2 with oxygen defect content of 0%, 3.125%, 6.25%, and 12.5% have been intensively studied within the framework of the density functional theory method. The results show that the TiO2 with an oxygen defect is not as stable as intrinsic TiO2. The compound formation enthalpy Ef and the oxygen defect formation energy value tend to be larger for a higher defect content, and the oxygen defect gets harder to be formed. The bonds within the TiO6 polyhedron are different and not geometrically symmetrical. The bond strengths show distinct diversity, and the primitive cell of anatase TiO2 show spatial expansion when there are oxygen defects. All bands moved down to the low energy region, and two impurity energy band levels emerged for the anatase TiO2 with oxygen defect. The energy band gap is decreased from 3.085 eV to 1.165 eV, 1.0015 eV, and 0.43 eV. There are generally 7 peaks for the spin density of states function, corresponding to their 5 main bands. For the anatase TiO2 with an oxygen defect content of 12.5%, the spin density of states functions are not horizontal ordinate symmetrical near −1.12 eV and 0.31 eV. They are formed by oxygen defect energy levels, which is the result of the Ti d and O p state electron polarization. Transitions from weak paramagnetic to antiferromagnetic are found for the anatase TiO2 with oxygen defect.
Research on Electrical Automation Monitoring System Model of Power Plant Based on CAN Bus
Authors: Chen Shu-chun
Published: April 2022

Using the traditional manual operation mode to control the electrical equipment of the power plant was not only inefficient and unsafe but also difficult to adapt to the use of new equipment. Therefore, this article puts forward the research on the model of power plant electrical automation monitoring system based on CAN bus, which was of great significance to improve the operation monitoring ability and management efficiency of power plant electrical equipment. Based on the analysis of the design mode and main functions of electrical equipment automation control system in power plant, this article expounded on the characteristics of CAN bus communication mode and its advantages in realizing electrical equipment automation control. According to the hierarchical management and structural characteristics of the electrical automation monitoring system, the real-time database architecture of the monitoring system was established, the real-time data monitoring and processing method of the electrical monitoring system was given, and then the electrical automation monitoring system model of the power plant was proposed. The experimental results showed that the electrical automation monitoring system proposed in this article was effective and feasible for real-time monitoring of the operation of electrical equipment. The model construction method of the electrical automation monitoring system proposed in this article can provide theoretical reference and technical support for improving the control mode of electrical equipment in power plants.
Bioactive Compounds and Their Derivatives: An Insight into Prospective Phytotherapeutic Approach against Alzheimer’s Disease
Authors: Islam Fahadul , Khadija Jannatul Fardous , Harun-Or-Rashid Md. , Rahaman Md. Saidur , Nafady Mohamed H. , Islam Md. Rezaul , Akter Aklima , Emran Talha Bin , Wilairatana Polrat , Mubarak Mohammad S.
Published: April 2022

Alzheimer’s disease (AD) is a common neurodegenerative brain disorder that causes cellular response alterations, such as impaired cholinergic mechanism, amyloid-beta (Aβ) AD aggregation, neuroinflammation, and several other pathways. AD is still the most prevalent form of dementia and affects many individuals across the globe. The exact cause of the disorder is obscure. There are yet no effective medications for halting, preventing, or curing AD’s progress. Plenty of natural products are isolated from several sources and analyzed in preclinical and clinical settings for neuroprotective effects in preventing and treating AD. In addition, natural products and their derivatives have been promising in treating and preventing AD. Natural bioactive compounds play an active modulatory role in the pathological molecular mechanisms of AD development. This review focuses on natural products from plant sources and their derivatives that have demonstrated neuroprotective activities and maybe promising to treat and prevent AD. In addition, this article summarizes the literature pertaining to natural products as agents in the treatment of AD. Rapid metabolism, nonspecific targeting, low solubility, lack of BBB permeability, and limited bioavailability are shortcomings of most bioactive molecules in treating AD. We can use nanotechnology and nanocarriers based on different types of approaches.
The Evaluation of DDoS Attack Effect Based on Neural Network
Authors: Guo Wei , Qiu Han , Liu Zimian , Zhu Junhu , Wang Qingxian
Published: April 2022

DDoS attack effect evaluation is the basis of security strategy deployment. The traditional effect evaluation method relies on the original data, ignoring the relationship between features and the evaluation target and indicator data redundancy, which affects the accuracy and reliability of the evaluation result. To this end, we introduce distance entropy to measure the similarity between features and evaluation target and use LSTM and Triplet networks to measure multiple correlations simultaneously. Then, a 2D-CNN is used to mine deep feature information and filter irrelevant information. We also combine 1D-CNN and attention models to achieve hierarchical sampling of different local features. Finally, three fully connected layers’ training obtains a total evaluation value. We conducted experiments on five commonly used DDoS datasets. The results showed that the average ranking accuracy of the neural network-based DDoS attack evaluation method (NNDE) reached 87.2%, 91.3%, 88%, 85.6%, and 94.5%, respectively. Compared with other evaluation methods, an average increase of 19.73% indicates that this method can better evaluate the effect of DDoS attacks.
Peripheral Blood-Derived Mesenchymal Stem Cells Modulate Macrophage Plasticity through the IL-10/STAT3 Pathway
Authors: Pang Qi-Ming , Yang Rui , Zhang Meng , Zou Wang-Hui , Qian Nan-Nan , Xu Qi-Jing , Chen Hui , Peng Jia-Chen , Luo Xiao-Ping , Zhang Qian , Zhang Tao
Published: April 2022

Mesenchymal stem cells (MSCs) are multipotent cells that can skew the balance of M1/M2 macrophage polarization towards the M2 phenotype via their paracrine effects, thereby promoting anatomical and functional recovery after many inflammatory diseases induced by macrophages. However, the underlying mechanism is still poorly understood. This study focused on the IL-10/STAT3 pathway and investigated whether IL-10 secreted by PBMSCs could mediate M2 polarization through the activation of this pathway. In this study, a Transwell system was used for coculturing macrophages and PBMSCs. ELISA and RT-qPCR analysis found that PBMSCs and their conditioned media (P-CM) significantly induced the expression of IL-10, while significantly inhibiting the expression of IL-1β and TNF-α; moreover, this effect could be reversed by adding Ab9969 (an IL-10 neutralizing antibody) and Stattic (a STAT3 inhibitor). Furthermore, western blotting and immunofluorescence assays demonstrated that JAK1/STAT3 signaling was significantly upregulated in macrophages cocultured with PBMSCs or P-CM, accompanied by an increase in the M2 biomarker CD206 and a decrease in the M1 biomarker CD86. This effect could also be reversed by blocking the IL-10/STAT3 pathway with Ab9969 and Stattic. In summary, PBMSCs could mediate the polarization of M2 macrophages by activating the IL-10/STAT3 pathway.
Adaptive Bright and Dark Channel Combined with Defogging Algorithm Based on Depth of Field
Authors: Wang Shiqi , Yang Tingping , Sun Wenxue , Lu Xiao , Fan Di
Published: April 2022

Aiming at the problem that the dark channel prior algorithm is not ideal in removing fog at the distant view and the sudden change of depth, this paper proposes an adaptive bright and dark channel combined with defogging algorithm based on the depth of field. The algorithm divides the image into a distant area and a near area based on the depth of field. The near area uses the dark channel to remove the fog, and the distant area uses the bright channel to remove the fog, combined with the use of adaptive superpixel segmentation to give the content-based local area division and defogging control factor based on depth of field. It better solves the problem of large transmittance deviation and defogging distortion under content changes and sudden depth of field changes. From the subjective and objective indicators, the algorithm in this paper has achieved a good defogging effect, and the main indicators and comprehensive defogging quality are better than common algorithms.
Deep Learning–Based Soft Sensors for Improving the Flexibility for Automation of Industry
Authors: Ayadi Rami , Abd El-Aziz Rasha M. , Taloba Ahmed I. , Aljuaid Hanan , Hamed Nadir O. , Khder Moaiad A.
Published: April 2022

Automation in industries offers the benefits of enhancing quality and productivity while minimizing waste and errors, raising safety and adds stability to the production process. Industrial automation offers high profitability, reliability, and safety. It is beneficial to employ machine learning in the field of industrial automation as it helps in monitoring and performing maintenance on industrial machinery. Rational industrial development is closely associated with efforts for automating industrial techniques in all existing ways. Latest improvements in the automation of industrial systems resulted in decrease in cost of energy consumption and hardware. The proposed system is dealt with deep learning–based soft sensors for automation of industrial processes. The eminent benefits of soft sensors are versatility, flexibility, and low cost. With deep learning, many number of features could be processed. Thus, deep learning–based soft sensor encapsulates the above benefits. Soft sensors offer another way for the measurement of process variables, which are measured offline. Deep learning techniques are famous in the design of soft sensors for tough nonlinear systems due to the robustness and accuracy. The work depicted here designs a soft sensor based on deep learning algorithm for automation of industry. In the proposed system, a soft sensor contemplated on deep learning such as the deep neural network (DNN) is presented. The application of deep learning–based soft sensors in the automation of some industrial processes is also discussed here. The proposed system is tested on automatic control on solar power plants and in the measurement of reactive energy in industries. It was found that the proposed system yielded better results with its application in the automated industrial processes.
Risk Management of New Cosmetic Product Development Based on Data Management of Visualization in Scientific Computing
Authors: Zheng Liyan
Published: April 2022

With the continuous development of the social economy, people pay more and more attention to their own protection and maintenance, especially the quality of commodities in terms of usage of the commodity. As commonly used commodities, the quality of their new products in cosmetics is extremely important. In the rapidly developing cosmetics industry, in view of these needs and limitations, the data management method of visualization in scientific computing is introduced in this paper. Multiple risk factors in cosmetics development are established and sorted from the three perspectives of cosmetics development, production, and sales, by combining the new cosmetic product development process. The biggest risks are clarified, the corresponding cosmetic product risk assessment model is constructed, and the new cosmetic product development risk strategy and related management are realized. The simulation experiment results show that the data management method of visualization in scientific computing is effective and can support the risk management of new cosmetic product development.
Artificial Neural Network-Based Identification of Associations between UCP2 and UCP3 Gene Polymorphisms and Meat Quantity Traits
Authors: Ujjan Javed Ahmed , Memon Sapna Waheed , Ruk Majeeda , Akram Zuneera , Ghoto Allahwadhayo , Dugbakie Betty Nokobi
Published: April 2022

In identifying mutations occurring in distinct cow breeds, genetic elements must be taken into consideration. More recently, these hereditary features have gained attention throughout the world. As in many underdeveloped nations, to bridge the deficit in molecular genetics, multiple solutions are required. The inner membrane anion carrier superfamily contains the uncoupling proteins (UCPs), vital to energy regulation. Research on heredity has shown that variations in the UCP2 and UCP3 genes are connected to obesity and metabolic syndrome. This research aimed to investigate if any mutation in the UCP 2 and UCP 3 genes are related to many characteristics in Pakistan’s three indigenous cattle breeds using artificial neural network (ANN). For better analysis, the output of the ANN model is loaded into the Primer Premier 3 software. Using polymerase chain reaction-single strand conformation polymorphism (PCR-SSCP) and sequencing, the results of this study indicated 07 variations in the exon 4 region of the UCP2 gene and 03 variants in the exon 3 area of the UCP3 gene among 215 indigenous cow breeds. The association study revealed that the g.C35G mutation in the UCP3 gene is strongly related to meat quantity characteristics such as carcass weight and drip percentage (P0.05) but not with body height or hip width (

P
>
0.05

). Sequence analysis showed five distinct diplotypes: AA, BC, AC, CC, and CD. Cattle with the novel heterozygous diplotype BC perform better in carcass trait and drip percentage than animals with other genotypes. The study’s findings suggest that the UCP3 gene may be utilized for marker-assisted selection (MAS) and breed mixing in Pakistan cattle breeds to aid in the country’s economic growth.
Research and Application of Haar Wavelet Transformation in Train Positioning
Authors: Wang Pengfei , Diao Xiuhui
Published: April 2022

With the continuous increase of the urban population, urban traffic problems have become increasingly prominent. The subway and light rail have the characteristics of large passenger volume and low pollution, which are the preferred solutions to solve the traffic problems in large and medium cities. Due to the high density of rail transit trains, the close distance between stations, and the high safety requirements, the real-time and accurate determination of the train's position on the line is the premise to ensure safety, maximize efficiency, and provide the best service. How to accurately detect the speed and position of the train to control its the operation is the core content of the rail transit system. Therefore, the in-depth study of train positioning methods has great and far-reaching significance for promoting the research of train operation control system and the development of rail transit system. It has become a research hotspot to rely on computer technology and image recognition technology to realize precise positioning of trains. In order to realize the real-time precise positioning of the train, this paper proposes a train positioning method based on Haar wavelet transform. First, the samples are obtained by the method of video acquisition, and the video images are initially processed by binarization. Second, the image is compressed, denoised, and enhanced by Haar wavelet transform, and the train number is determined. Finally, the orbital electronic map and satellite assistance are used to determine the position of the train and realize the train positioning. The simulation experiments show that the image acquired by Haar wavelet transform can accurately identify the train and track. Based on the satellite aid of the orbital electronic map, the train positioning can be accurately realized, and the proposed Haar wavelet transform is proposed and has good positioning accuracy.
Serum Nerve Growth Factor Levels as a Predictor of Bull Candidate Semen Quality of Madura Cattle
Authors: Rimayanti Rimayanti , Azizah Nurul , Srianto Pudji , Madyawati Sri Pantja , Sardjito Trilas , Mustofa Imam
Published: April 2022

Madura cattle are the germplasm of native cattle on the verge of extinction because of crossbreeding. Therefore, the present study was aimed to determine the serum nerve growth factor (NGF) concentration as a predictor of fresh ejaculate fertility parameters in Madura bull candidates. Eleven Madura bull candidates used for frozen semen production were selected for the study. Blood samples were collected using a vacutainer from the jugular vein for analyzing serum NGF and testosterone levels. Meanwhile, semen collection was conducted using an artificial vagina for sperm motility, viability, and concentration assessment. Data were analyzed to determine the correlation among variables and the linear regression of NGF concentration to other significant variables. The result showed that NGF had a significant correlation (

p
<
0.05

) with testosterone levels, sperm motility, viability, and concentration. A significant correlation was observed between testosterone levels, sperm concentration, and sperm viability. The regression equation among significantly correlated variables was determined. For artificial insemination, suitable bull ejaculates for obtaining frozen semen should reach at least 2.12 ng/mL of NGF levels, with sperm viability, sperm concentration, and testosterone levels of more than 78.63%, 1,462.177 million/mL ejaculate, and 25.67 ng/mL, respectively. This is the first study to identify NGF as a predictor of male fertility in bull candidates of Madura cattle. Therefore, NGF levels could be used as a marker of male fertility in Madura bull cattle candidates. Thus, based on the minimum NGF levels, the ejaculate of Madura bull candidate that meets the requirements for frozen semen production could predict fertility.
Well-Conditioning Map for Tensor Spectral Solutions for Eigenvalues in 2D Irregular Planar Domains
Authors: Guimarães O. , Labecca W. , Piqueira José R. C.
Published: April 2022

This study proposes a diffeomorphic map for planar irregular domains, which transforms them into a unitary circle suitable for implementing spectral solutions on a complete and orthogonal basis. The domain must be enclosed by a Jordan curve that is univocally described in polar coordinates by a

C

2

class function. Because of the achieved precision, general eigenvalue problems can be solved, yielding hundreds of eigenvalues and eigenfunctions in a single shot with at least ten-digit precision. In a constructive approach, there is no need for special functions or roots. The examples focus on the Helmholtz equation, but the method applies to other eigenvalue problems such as Hamiltonians. For validation, we compare all the results with the values obtained by finite elements (FE), some with other studies, and discuss sharp error estimate criteria and the asymptotic behavior of the eigenvalues. To demonstrate the generality of the approach, we present several examples with different geometries in which solutions emerge naturally. Considering the spectral accuracy, half of the examples are unpublished solutions, and the other half agree with or expand the precision of previous studies using different approaches.
Strength Prediction of Self‐Consolidating Concrete Containing Steel Fibre with Different Fibre Aspect Ratio
Authors: Ganapathy Ganesh Prabhu , Keshav Lakshmi , Ravindiran Gokulan , Razack Nasar Ali
Published: April 2022

The present study presents the effects of steel fibre aspect ratio on the fresh and strength properties of self‐consolidating concrete (SCC). Steel fibre having three different aspect ratios (50, 65 and 80) with the inclusion rate of 0.2%, 0.4%, 0.6%, 0.8%, and 1.0% was considered, and the effects of aspect ratio and the fibre inclusion rate on the fresh and strength properties of SCC were investigated. Central composite design (CCD) of RSM modeling was considered to propose a regression model to predict the 28‐day compressive strength of SCC and steel fibre‐reinforced SCC (SFSCC) incorporating different supplementary cementitious materials (SCMs). 94 data sets retrieved from various literatures and the experimental data set (SCC and SFSCC) of this present study have been used to develop the regression model. Further, cement content, powder content, water to binder ratio, and coarse aggregate to fine aggregate ratio were considered as basic variables to propose the model, and their influence on the strength properties of SCC was prioritized using analysis of variance (ANOVA) and Pareto chart. The findings of regression model have been compared with the results of 94 data sets, and the experimental data set of this present study and the comparisons confirm that the proposed regression model are very realistic and precise to predict the compressive strength of SCC and SFSCC with different aspect ratio.
BAP31 Promotes Proliferation, Invasion, and Metastasis of Liver Cancer Cells via Activating PI3K/AKT Pathway
Authors: Sun Minmin , Liu Xue , Wei Wanying , Ge Naijian , Luo Shuli , Shen Shuqun , Ge Ruiliang
Published: April 2022

Background. Many breakthroughs have been made in the clinical treatment of liver cancer, but there are still many liver cancer patients with limited treatment methods. Therefore, it is very important to find targets for early diagnosis and specific treatment of liver cancer. Methods. During the operation, 32 pairs of tumor tissues and corresponding normal liver tissues were acquired from patients. The mRNA expression was measured by qPCR. The protein expression was evaluated via Western blot. Flow cytometry assay was performed to measure the cells apoptosis. CCK-8 assay was performed to detect cell proliferation. Transwell chamber assay was applied to detect migration and invasion of SNU-449 cells. Results. BAP31 was upregulated in liver cancer tissues and cells. Knockdown of BAP31 repressed cell proliferation and enhanced cell apoptosis of liver cancer. Knockdown of BAP31 apparently upregulated apoptosis-related proteins (Bax and Caspase-3), while it downregulated antiapoptotic proteins (Bcl-2). Knockdown of BAP31 repressed migration and invasion of SNU-449 cells. In contrast with the control and si-NC group, protein expression of MMP-2 and MMP-9 was obviously lower after si-BAP31 transfection of cells. Knockdown of BAP31 repressed PI3K/AKT signaling pathways in liver cancer cells. Conclusion. Knockdown of BAP31 repressed cell proliferation, migration, and invasion in liver cancer by suppressing PI3K/AKT/mTOR signaling pathways.