bluuebunny/crossref_metadata_2025 huggingface dataset:
Models of Artificial Intelligence-Assisted Diagnosis of Lung Cancer Pathology Based on Deep Learning Algorithms
Authors: Chen Su
Published: March 2022

In this article, in order to explore the application of a diagnosis system for lung cancer, we use an auxiliary diagnostic system to predict and diagnose the good and evil attributes of chest CT pulmonary nodules. This research improves the new diagnosis method based on the convolutional neural network (CNN) and the recurrent neural network (RNN) and combines the dual effects of the two algorithms to process the classification of benign and malignant nodules. By collecting H-E-stained pathological slices of 652 patients' lung lesions from two hospitals between January 2018 and January 2019, the output results of the improved 3D U-net system and the consistent results of two-person reading were compared. This article analyzes the sensitivity, specificity, positive flammability rate, and negative flammability rate of different lung nodule detection methods. In addition, the artificial intelligence system’s and the radiologist's judgment results of benign and malignant pulmonary nodules are used to draw ROC curves for further analysis. The improved model has an accuracy rate of 92.3% for predicting malignant lung nodules and an accuracy rate of 82.8% for benign lung nodules. The new diagnostic method using the convolutional neural network and the recurrent neural network can be very effective for improving the accuracy of predicting lung cancer diagnosis. It can play a very effective role in the disease prediction of lung cancer patients, thereby improving the treatment effect.
α-Completely Regular and Almost α-Completely Regular Spaces
Authors: Azzam A.A. , Nasef A.A.
Published: March 2022

This work is aimed at studying some of the characterizations of α-completely regular and almost α-completely regular spaces through the new concept of α-zero sets and α-continuous functions. 2010 Mathematics Subject Classification: primary 05C38, 15A15; Secondary 05A15, 15A18.
Particulate Matter Exposure and the Changes in Immune Biomarkers: Effects of Biyeom-Go on the Nasal Mucosa of Patients with Allergic Rhinitis and a Particulate Matter-Treated Mouse Model
Authors: Park Bongkyun , Kang Byoung-Kab , Kim Ae-Ran , Kang Jung In , Lee Dong‐Hyo , Yang Chang Sop , Kim Young Sook , Kim Chan-Sik
Published: March 2022

This study was to investigate the effects of Biyeom-go (BYG, an herbal formula) on immune biomarkers present in the nasal mucosa of patients with allergic rhinitis under exposure to particulate matter 2.5 (PM2.5), and on changes in goblet cells and immune biomarkers in mice under exposure to Korea diesel particulate matter (KDP20). Thirty patients showing characteristic allergic rhinitis symptoms were enrolled in Jeonju-si, Korea, and treated with BYG thrice a day for four weeks. Changes in the expression of immune biomarkers (interleukin 4 (IL-4), IL-5, IL-8, IL-13, IL-33, and thymic stromal lymphopoietin (TSLP) mRNA), total nasal symptom scores (TNSS), mini-rhinitis-specific quality of life questionnaire (RQLQ) results, and visual analog scale scores were evaluated after 4 weeks of treatment. Additionally, the difference in PM2.5 concentrations in the air in Jeonju-si, Korea (November, 2019 ∼ March, 2020), was analyzed to determine the change in TNSS. KDP20 (100 μg/mL) was exposed to C57BL/6 mice for 10 days; 0.05% Nasonex (a positive control, mometasone furoate), or BYG was administrated for 5 days twice a day. The expression of inflammatory factors was detected via qRT-PCR using nasopharynx tissue samples of mice. BYG treatment was found to be associated with significant improvement in total nasal symptoms, especially itching and sneezing (

p
<
0.0001

), and mini-RQLQ after 4 weeks. IL-8 (

p
<
0.01

), IL-33 (

p
<
0.01

), and TSLP (

p
<
0.001

) expression levels decreased after BYG treatment. In mice, administration of BYG reduced the number of goblet cells increased through KDP20 treatment. KDP20-induced immune biomarkers (IL-33, TSLP, tumor necrosis factor alpha, and IL-8) were also significantly downregulated in the nasopharynx tissue after BYG treatment. Therefore, BYG may show therapeutic effects against allergic rhinitis in humans, and it was confirmed that the expression of PM-induced inflammatory factors in mice was decreased via BYG treatment.
Experimental Testing on Mechanical, Durability, and Adsorption Dispersion Properties of Concrete with Multiwalled Carbon Nanotubes and Silica Fumes
Authors: Chukka Naga Dheeraj Kumar Reddy , Reddy B. Sudharshan , Vasugi K. , Reddy Yeddula Bharath Simha , Natrayan L. , Thanappan Subash
Published: March 2022

The major goal of this research is to see how carbon nanotubes and silica fume affect the durability and mechanical qualities of high-performance concrete (HPC). Mechanical properties, such as split tensile strength, compressive strength, elasticity modulus, and flexural strength, and durability properties like water absorption, abrasion, chloride penetration, acid, and sea water resistance, impact resistance of HPC consisting silica fume (SF), and carbon nanotubes (CNT) were examined in this study. Varied trail combinations with different proportions of CNT and SF admixtures were created for this reason. Portland cement was partially replaced with 1 percent, 1.5 percent, 2 percent, and 3 percent CNT, while SF was substituted with 5 percent, 7.5 percent, and 10 percent. Both CNT and SF outperform conventional concrete in terms of mechanical and durability attributes, according to the findings. CNT produces superior results than SF due to its smaller size.
Improved Multiple Lyapunov Functions of input-to-output Stability and input-to-state Stability for Switched Systems
Authors: Chen Shizhang , Ning Chongyang
Published: March 2022

This paper investigates the Lyapunov characterizations of input-to-output stability (IOS) and input-to-state stability (ISS) for nonlinear switched systems. The restriction on the negativity of derivatives of Lyapunov functions is relaxed; additionally, subsystems are not restricted to be ISS/IOS throughout the state space. These problems are overcome by a newly proposed method, which extends multiple Lyapunov functions (MLFs) to an indefinite form. Indefinite multiple Lyapunov functions (iMLFs) are proposed on the basis of an inequality to estimate the upper boundary of the system state. Moreover, we apply the iMLFs method to verify the extended notions of IOS in a switched system. More relaxed sufficient conditions for ISS and IOS are proposed, a simulation experiment is carried out on a numerical example of the system, which demonstrates their effectiveness and superiority.
Natural Backdoor Attacks on Deep Neural Networks via Raindrops
Authors: Zhao Feng , Zhou Li , Zhong Qi , Lan Rushi , Zhang Leo Yu
Published: March 2022

Recently, deep learning has made significant inroads into the Internet of Things due to its great potential for processing big data. Backdoor attacks, which try to influence model prediction on specific inputs, have become a serious threat to deep neural network models. However, because the poisoned data used to plant a backdoor into the victim model typically follows a fixed specific pattern, most existing backdoor attacks can be readily prevented by common defense. In this paper, we leverage natural behavior and present a stealthy backdoor attack for image classification tasks: the raindrop backdoor attack (RDBA). We use raindrops as the backdoor trigger, and they are naturally merged with clean instances to synthesize poisoned data that are close to their natural counterparts in the rain. The raindrops dispersed over images are more diversified than the triggers in the literature, which are fixed, confined, and unpleasant patterns to the host content, making the triggers more stealthy. Extensive experiments on ImageNet and GTSRB datasets demonstrate the fidelity, effectiveness, stealthiness, and sustainability of RDBA in attacking models with current popular defense mechanisms.
Determinants of Intimate Partner Violence against Pregnant Women in Ethiopia: A Systematic Review and Meta‐Analysis
Authors: Bifftu Berhanu Boru , Guracho Yonas Deressa
Published: March 2022

Background. Intimate partner violence (IPV) against pregnant women is a recognized global public health problem affecting all spheres of women and unborn infants. In Ethiopia, although inconsistent, individual studies avail; there is a dearth of systematic reviews and meta‐analysis about the prevalence and associated factors of intimate partner violence. Thus, the present study was aimed at determining the pooled prevalence of IPV and its determinant factors during pregnancy. Methods. The report of meta‐analysis follows the Preferred Reporting Items for Systematic Review and Meta‐Analysis 20 guideline (PRISMA 20). Databases including PubMed/Medline, CINAHL, SCOPUS, HINARI (research4life), AJOL, IRIS, and AIM were searched. Heterogeneity test was assessed by the Cochrane chi‐square (χ2) and quantified by I2 statistics test. Publication bias was tested by funnel plots and Egger’s test. Sensitivity test and subgroup analysis were also performed. Effect size was calculated by random effects model. Results. A total of 26 studies, including data from 13, 912 participants, were included in the analysis. The prevalence of IPV ranged from 7% to 81% with overall estimated pooled prevalence of 37% (30% ‐44%, I2 = 96.5%, p ≤ 0.001). Of this, the prevalence of physical, sexual, and psychological violence was 24% (95% CI; 19%‐30%), 21% (95% CI; 16%‐26%), and 27% (95% CI; 22%‐32%), respectively. Factors such as lack of formal education, childhood violence, rural residency, low decision‐making power, family history of violence, attitude, unplanned and unwanted pregnancy by women and partners, late initiation of antenatal care, partner alcohol, and khat use were associated with IPV. Conclusion. More than one‐third of pregnant women experienced IPV. The most prevalent form of IPV was psychological violence followed by physical and sexual violence. The identified risk for IPV including victim, pregnancy, and perpetrator‐related factors indicated the need of a holistic approach in the promotion, prevention, and treatment of IPV. The finding of this study suggests the need of strengthening women empowerments (capacity building) against traditional beliefs, attitudes, and practices. This study also suggests the need of evaluation and strengthening the collaborative work among different sectors such as policy‐makers, service providers, administrative personnel, and community leaders, including the engagement of men partners.
Signal-to-Noise Ratio Comparison of Several Filters against Phantom Image
Authors: Siddiqi Muhammad Hameed , Alhwaiti Yousef
Published: March 2022

Image denoising methods are important in order to diminish various kinds of noises, which are presented either capturing the image or distorted during image transmission. Signal-to-noise ratio (SNR) is one of the main barriers which avoids the theoretical observations to be accomplished in practice. In this study, we have utilized various kinds of filtering operators against three various noises, which are the signal-to-noise ratio comparison against the phantom image in spatial and frequency domain. In frequency domain, the average filter is used to smooth the image and frequency domain, and Gaussian low-pass filter is applied with empirically determined cutoff frequency. This work has six major parts such as applying average filter, determining the SNR of region of interest, transforming the image in frequency domain by discrete Fourier transform, obtaining the rectangular Gaussian low-pass filter along with a cutoff frequency, multiplying them, and carrying out the inverse Fourier transform. These steps are repeated accordingly until the resulting image SNR is equal to or greater than the spatial domain SNR. In order to achieve the goal of this study, we have analyzed the proposed approach against some of complex phantom images. The performances of these filters are compared against signal-to-noise ratio.
Lymph Node Abscessation Secondary to Neoplasia in Two Dogs
Authors: Close Erin , Lumbrezer-Johnson Sarah , Hostnik Eric , Burge Rhonda , Jennings Ryan , Selmic Laura
Published: March 2022

A 5-year-old male neutered mixed breed dog and an 8-year-old female spayed golden retriever presented for cervical swelling which was later diagnosed as abscessation of the retropharyngeal lymph node with a malignant round cell tumor and carcinoma with multifocal squamous differentiation, respectively. In veterinary medicine, there is limited published information regarding abscessation of lymph nodes secondary to a neoplastic process. While more common in humans, there are only limited case reports available. Advanced imaging (computed tomography), cytology, surgical excision, and histopathology lead to the final diagnosis. Both dogs underwent surgical extirpation of the lymph nodes and adjuvant chemotherapy protocols. Six weeks postsurgical excision, dog one was euthanized due to quality-of-life concerns. The second dog successfully completed 18 treatments of radiation therapy and was still alive at 388 days postsurgical excision. At the time of manuscript submission, the second dog was doing well clinically.
Power System Reactive Power Optimization Sensor Dispatching Digital Grid Based on Improved Cuckoo Algorithm
Authors: Wang Shun
Published: March 2022

In order to ensure the economic, safe, and stable operation of the power grid in the power system, the author proposes a power system reactive power optimization sensor dispatching digital grid based on an improved cuckoo algorithm. Use this improved cuckoo algorithm to optimize the solution, optimal dispatch model of power system considering economy and environmental protection. The main improvement strategies are as follows: on the basis of the original algorithm, the exchange operator in the particle swarm algorithm is introduced, promoting communication between bird’s nests; at the same time, two fixed parameters of probability and step size will be found and set to dynamic quantity to improve the convergence speed of the algorithm; in the process of updating the location of the bird’s nest, use nondominant sorting and calculation of crowding distance to maintain the archives; after generating the optimal solution, use the satisfaction evaluation theory of fuzzy mathematics to obtain the optimal solution. The result said that the cost of power generation and pollutant emissions is USD 125.1 million/h and 0.3361 t/h, respectively. Compared with the optimization results of the other three traditional algorithms, power generation costs and pollutant emissions reduced. The algorithm shows that the improved algorithm has better optimization speed and accuracy, and at the same time, it can effectively improve the global convergence, to ensure the diversity of Pareto’s noninferior solutions.
Research on Ethanol Coupling to Prepare C4 Olefins Based on BP Neural Network and Cluster Analysis
Authors: Zhang Sheng-Mei , Zhan Wen-Li , Hu Han , Liu Yu-Shu , Zhu Jia-Ming
Published: March 2022

Ethanol, as a clean energy source, is an ideal raw material for the preparation of C4 olefins, but there are few studies on the preparation of C4 olefins by the coupling of ethanol. This research is based on the data from Question B of the 2021 Chinese Contemporary Undergraduate Mathematical Contest in Modeling. The researchers firstly perform data interpolation and visualization processing on the original data. Secondly, based on the two-dimensional visualization analysis, we cluster the different catalyst combinations; divide the influencing factors into temperature, Co/SiO2 and HAP loading ratio, Co loading, and ethanol concentration; and construct a quaternary linear regression equation that affects ethanol conversion rate and C4 olefin selectivity. Finally, according to the three-dimensional spatial visualization analysis and using the BP neural network model training data, we obtain that under the conditions of using loading method I, catalyst combination type 200 mg 0.5 wt% Co/SiO2-200 mg HAP-ethanol concentration 0.9 ml/min and temperature 450°C, the yield of C4 olefins can reach the maximum. This study provides new research ideas and methods for the preparation of C4 olefins from ethanol.
Five Years Follow-Up of Acrysof Cachet® Angle-Supported Phakic Intraocular Lens Implantation for Myopia Correction
Authors: Musayeva Aytan , Riedl Jana C. , Gericke Adrian , Vossmerbaeumer Urs
Published: March 2022

Purpose. The Acrysof Cachet® angle-supported phakic intraocular lens (pIOL) (Alcon Laboratories, Inc., Fort Worth, TX) is designed to correct high refractive errors in human eyes. The aim of this study was to evaluate the outcome of AcrySof Cachet® angle-supported pIOL implantation with particular regard to efficacy and safety of the implant over a 60-month follow-up period. Design. Retrospective consecutive clinical case study. Methods. Prior to pIOL implantation, patients had a complete ophthalmologic examination including objective and subjective refraction, uncorrected visual acuity (UCVA) and corrected distance visual acuity (CDVA), endothelial cells density (ECD), slit lamp photography, optical coherence tomography (OCT), Scheimpflug digital videokeratoscopy, optical biometry, slit lamp examination, intraocular pressure (IOP) measurement, and pupillometry. Postoperatively, patients received yearly a complete eye examination. Results. Thirty-one eyes of 16 patients were included in this study. The mean age was 36.2 ± 8.1 years. UCVA (logMAR) improved from 1.33 ± 0.20 before surgery to 0.08 ± 0.14 one year after surgery and was 0.20 ± 0.20 five years after surgery. CDVA (logMAR) improved from 0.10 ± 0.10 before surgery to 0.05 ± 0.13 one year after surgery and was 0.04 ± 0.14 five years postoperatively. The mean percentage of endothelial cells loss (ECL) was 11.51% over the first year and 15.95% five years after surgery. There were no intraoperative complications in any of the eyes. Conclusions. Our results up to five years after implantation of the AcrySof Cachet® angle-supported pIOL demonstrated very good outcomes in all above shown measurements, including CDVA, UCVA, and ECD. However, since major endothelial cell loss may occur in some patients with this type of pIOL, regular follow-up visits are required.
Identification of lncRNAs and Their Regulatory Relationships with mRNAs in Response to Cryptococcus neoformans Infection of THP‐1 Cells
Authors: Gao Rui , Yao Guotai , Wang Xiaolie , Wang Yilin , Lin Wenting , Teng Liang , Wang Yan , Jin Yi , Wang Zhongzhi , Chen Jianghan
Published: March 2022

Aims. Cryptococcosis is an invasive fungal disease that is associated with an increasing prevalence along with a very high fatality and is primarily caused by Cryptococcus. However, its mechanism to cause pathogenicity is not yet completely understood. In this study, we aim to screen the lncRNA markers in human monocytic (THP‐1) cells infected by Cryptococcus neoformans (C. neoformans) through high‐throughput sequencing technology and to explore its effects on biological functions. Methods. We initially conducted an lncRNA microarray analysis of the THP‐1 cells infected by C. neoformans and normal THP‐1 cells. Based upon these data, RT‐qPCR was used to verify the expressions of the selected lncRNAs and mRNAs. We then performed functional and pathway enrichment analyses. Lastly, target prediction was performed by using the lncRNA target tool which was based on the differentially expressed lncRNAs. Results. We determined 81 upregulated and 96 downregulated lncRNAs using microarray. In addition, the profiling data showed 42 upregulated and 57 downregulated genes and discovered that neuroactive ligand‐receptor interaction, tyrosine metabolism, and phenylalanine metabolism are extremely impaired in the regulation of C. neoformans infection. GO enrichment analysis of the 99 differentially expressed mRNAs exhibited that these modules showed different signaling pathways and biological mechanisms like protein binding and metal ion binding. Moreover, lncRNAs and mRNAs were analyzed for their coexpression relations. A qRT‐PCR analysis confirmed that the expression of the top 10 differently expressed mRNA and lincRNA. The expressions of the lncRNAs after C. neoformans infection in THP‐1 cells were detected by RNA‐sequence, suggesting that microarray analysis could reveal lncRNAs having functional significance that might be linked with the progression of patients. Conclusion. The current study analyzed the differential lncRNAs and mRNAs in C. neoformans infection and predicted the corresponding pathways and their correlations that can offer new potential insights into the mechanistic basis of this condition.
Efficient Data Integrity Auditing Supporting Provable Data Update for Secure Cloud Storage
Authors: Yang Changsong , Song Bowen , Ding Yong , Ou Jiangtao , Fan Chengyuan
Published: March 2022

Cloud storage, an economically attractive service offered by cloud service providers (CSPs), has attracted a large number of tenants. However, because the ownership and management of outsourced data are separated, outsourced data faces a lot of security challenges, for instance, data security, data integrity, data update, and so on. In this article, we primarily investigate the problem of efficient data integrity auditing supporting provable data update in cloud computing environment. Subsequently, on the basis of the Merkel sum hash tree (MSHT), we introduce an efficient outsourced data integrity auditing scheme. Our designed scheme could synchronously meet the requirements of provable data update and data confidentiality without dependency on a third authority. At the same time, the numerical analysis shows that the computing complexity logarithmically grows with the number of outsourced subfiles. Finally, a prototype implementation is developed to simulate our designed scheme and measure its performance. The consequences of experiments present that compared with some previous solutions, our designed scheme has much more attractive practicality and higher efficiency in practical applications.
Detection Algorithm of Wind Power Equipment Video Image Sequence Based on Artificial Intelligence
Authors: Li Qun , Kamruzzaman M.M.
Published: March 2022

How to detect the data in the video image sequence and analyze it efficiently by using the artificial intelligence method is a frontline topic in the field of computer vision. Global wind energy resources are abundant, widely distributed, clean, and pollution-free and meet the requirements of sustainable economic and social development, so relying on the large-scale development and utilization of wind energy has been the common choice of many countries. A major goal of artificial intelligence research is to enable machines to perform complex tasks that normally require human intelligence to perform. The purpose of this study is to detect the video image sequence of wind power equipment based on artificial intelligence and analyze the effectiveness of the algorithm. In this study, augmented reality is used as an auxiliary means. According to the characteristics of the video image inside the fan, a moving target region detection algorithm based on the background difference method is proposed. The algorithm uses the difference between the current image and the background image, uses the first-order Kalman filter to update the dynamic background image, and then uses the adaptive threshold method to segment the moving region. After filtering, the moving target area can be obtained. The results show that the positive detection rate of 980 test samples is 99.6%, and the training time is only 3.785. It is concluded that the accuracy and the number of support vectors of this algorithm are better than other algorithms in the case of the same value of C. It shows that this study has a good detection effect. It provides an effective method for video image sequence detection of wind power equipment.
Valorization of Moroccan Pistacia lentiscus L. Leaves: Phytochemical and In Vitro Antioxidant Activity Evaluation Compared to Different Altitudes
Authors: Hadini Abderrahmane , Azdimousa Amal , Khoulati Amine , El bekkaye Khalid , Saalaoui Ennoumane
Published: March 2022

This study examined the secondary metabolite content and the antioxidant activities of hydromethanolic P. lentiscus L. leaves extracts at different altitudes. The results indicated that the contents of polyphenols and flavonoids were significantly (

p
≤
0.05

) high in the low altitude, unlike the Chl (chlorophyll), tannins, and ascorbic acid, which were reported to have higher content in the high altitude. These results showed that the P. lentiscus L. is more adaptable to higher elevations than low elevation, where the plant was probably stressed. On the other hand, the analyses of correlation between the antioxidant activity and phytochemical content affirmed that the antiradical activity (DPPH) correlated with the content of polyphenols; however, the total antioxidant activity is correlated with the flavonoid content. These results revealed the importance of P. lentiscus L. leaves as a natural antioxidant and gave an idea of the altitude effect on the biochemical parameters of leaves.
Design of New Word Retrieval Algorithm for Chinese-English Bilingual Parallel Corpus
Authors: Zhang Liting
Published: March 2022

Natural language processing is an important direction in the field of computer science and artificial intelligence. It can realize various theories and methods of effective communication between humans and computers using natural language. Machine learning is a branch of natural language processing research, which is based on a large-scale English-Chinese database. Due to the relatively poor alignment corpus of English and Chinese bilingual sentences containing unknown words, machine translation is unprofessional and unbalanced, which is the problem studied in this paper. The purpose of this paper is to design and implement a length-based system for sentence alignment between English and Chinese bilingual texts. The research content of this paper is mainly divided into the following parts. First, the evaluation function of bilingual sentence alignment is designed, and on this basis, the bilingual sentence alignment algorithm based on the length and the optimal sentence pair sequence search algorithm is designed. In this paper, China National Knowledge Infrastructure (CNKI) is selected as an English-Chinese bilingual candidate website and English-Chinese bilingual web pages are downloaded. After analyzing the downloaded pages, nontext content such as page tags is removed, and bilingual text information is stored so as to establish an English-Chinese bilingual corpus based on segment alignment and retain English-Chinese bilingual keywords in the web pages. Second, extract the dictionary from the software StarDict, analyze the original dictionary format, and turn it into a custom dictionary format, which is convenient and better to use the double-sentence sentence alignment system, which is conducive to expanding the number of dictionaries and increasing the professionalism of vocabulary. Finally, we extract the stems of English words from the established corpus to simplify the complexity of English word processing, reduce the noise caused by the conversion of word parts of speech, and improve the operation efficiency. A bilingual sentence alignment system based on length is implemented. Finally, the system parameters are adjusted for comparative experiments to test the system performance.
Improved Genetic Algorithm for Intelligent Grinding Trajectory of Industrial Robot Sensor
Authors: Lu Yaping
Published: March 2022

In order to study the improved genetic algorithm for intelligent grinding trajectory of industrial robot, a trajectory planning method with optimal energy consumption is proposed. Firstly, the trajectory of the robot is regarded as a series of type value points in space, and each adjacent type value point is connected by a quintic

B

-spline curve to obtain the trajectory function of the robot. Then, the kinetic energy is taken as the target energy consumption function, and the kinematic and dynamic constraints of each joint are considered at the same time. Finally, the genetic algorithm is improved to optimize the objective energy consumption function. The improved genetic algorithm improves the operation efficiency, local search ability, and real-time performance of the algorithm. Front and rear times during handling were 15.034 s and 17.456 s for 2.422 s. The optimal secondary trajectory planning algorithm is called in the single workstation of the welding robot and the robot welding the bucket with spatial straight line and spatial curve, respectively. Through the time difference, the time used in the spatial linear welding is 5.462 s, and the spatial curve welding time is 12.981 s. The proposed algorithm can be applied to the production of various industrial sensor robots such as welding robot, cutting robot, and spraying robot and improves the working efficiency of robot operation. In addition, the genetic method of multichromosome structure also has a certain reference for solving the general GSTP problem.
Toxic Metal Recovery from Waste Printed Circuit Boards: A Review of Advanced Approaches for Sustainable Treatment Methodology
Authors: Manikkampatti Palanisamy Murugesan , Myneni Venkata Ratnam , Gudeta Badhane , Komarabathina Srikanth
Published: March 2022

The rapid advancement of technical advancements has resulted in the generation of substantial amount of electronic trash (e-waste). The volume of e-waste created, as well as the presence of both dangerous and beneficial elements, enhances the business potential of recovery and recycling significantly. Waste printed circuit boards (PCBs) include a number of hazardous heavy metals, including copper (Cu), tin (Sn), lead (Pb), and others (Zn, Ni, Fe, Br, Mn, Mg etc.). These discarded metals without treatment threaten the economy, the environment, and human health. Heavy metal recovery from PCBs is a big difficulty for researchers. The present review focuses on technological advances in the recovery of toxic, precious metals from PCBs.
Influence of Multistage Target Temperature and Cyclic Loading/Unloading on the Permeability of Polypropylene Fiber Concrete
Authors: Cen Peishan , Wei Erjian , Tian Kunyun
Published: March 2022

Due to the combined effect of temperature and cyclic loading and unloading, the gas permeability of polypropylene fiber reinforced concrete structures changes during service. However, the current gas permeability test of polypropylene fiber reinforced concrete is based on a single influencing factor or a single test condition (monotonic loading), and the test conditions are quite different from the actual working conditions of the structure. To explore the permeability of polypropylene fiber reinforced concrete under cyclic loading and unloading under the influence of temperature, based on the stress principle that the specimen does not have structural damage and according to the steady‐state equation of Darcy’s law, the Cembureau method is adopted. The gas permeability of polypropylene fiber reinforced concrete under single loading and unloading and multistage cyclic loading and unloading at eight target temperatures is tested by the triaxial permeability test system. The results showed that (1) when the target temperature was 120°C < T ≤ 200°C and 200°C < T ≤ 280°C, the fiber experienced two stages of “softening, melting‐cooling recovery” and “melting and absorption,” which caused damage to the matrix pore structure. The gas permeability at 200°C and 280°C was 246 times and 350 times that at 22°C, respectively. (2) The damage degree of the matrix strength structure increases during cyclic loading and unloading, and the permeability loss rate during cyclic loading and unloading is 1.24∼1.57 times that of single loading and unloading. (3) The high target temperature leads to pore structure damage of the matrix, which not only affects the permeability of the matrix but also affects the strength structure of the matrix. When the stress ratio R ≥ 0.37, the pore structure damage and the strength structure damage of the specimen are superimposed, resulting in the antipermeability effect of the specimen developing in the unfavorable direction. The test simulated the actual working conditions of polypropylene fiber reinforced concrete, providing a reference for building fire protection, seismic design or postdisaster evaluation.
Application of Lightweight Deep Learning Model in Vocal Music Education in Higher Institutions
Authors: Zhu Zhen , Xu Zhongqiu , Liu Jing
Published: March 2022

The aim is to improve the teaching quality of music majors and cultivate their innovative ability. This article takes Vocal Music Education (VME) method as the research object to explore the teaching reform of Music Major courses. Firstly, this article makes an in-depth study on Big Data Analytics (BDA) and Digital Twins (DTs) technology and constructs a DTs platform connecting real teaching space and virtual teaching space. Secondly, the DTs platform is divided into online learning feature analysis and virtual-real teaching space integration functional modules. This article explores the online immersive education process design and technology application of the DTs platform from the two aspects of teaching and technology. Afterward, it designs a student action and expression recognition network based on the Visual Geometry Group (VGG) Net model and Google Net model in teaching data collection and management. Finally, the proposed system is tested. The test results show that the active and passive interaction curves of the traditional VME system have no obvious fluctuation, indicating that the interaction of the traditional VME system is not strong, and the ability of active feedback information is poor. By contrast, the active and passive interaction curves in the proposed VME have large fluctuations, showing that the proposed VME has more frequent interaction, and the teaching information can get real-time and active feedback. Therefore, the proposed VME system can better stimulate students’ learning desire. Meanwhile, the constructed Neural Network (NN) has the highest recognition accuracy of 99.07% on the student action and expression dataset. When tested with the image data taken by the research experiment, the highest accuracy is 89%, with an average of more than 85%. The proposed VME system provides ideas for applying DTs technology in the college of music education.
Acridine-2,4-Dinitrophenyl Hydrazone Conjugated Silver Nanoparticles as an Efficient Sensor for Quantification of Mercury in Tap Water
Authors: Ali Imdad , Isaac Ibanga Okon , Ahmed Mahmood , Ahmed Farid , Ikram Farhat , Ateeq Muhammad , Alharthy Rima D. , Malik Muhammad Imran , Hameed Abdul , Shah Muhammad Raza
Published: March 2022

Excretion of heavy metals especially mercury (Hg2+) from the industries into the environment becomes a major global problem. In this context, mercury is a highly dangerous metal which poses serious impact on human health. In the present study, acridine- (ACR-) based silver nanoparticles (ACR-AgNPs) were prepared and employed as a nanosensor for effective detection and quantification of Hg2+ in tap water. Conjugation between ACR-based coating agent and silver was examined by UV-visible and FT-IR spectroscopy, while morphology and particle size were determined through atomic force microscopy (AFM), dynamic light scattering (DLS), and scanning electron microscopy (SEM). Furthermore, sensing behavior of nanosensor for metal ions was evaluated by mixing different metals such as Mn2+, Ni2+, Ba2+, Mg2+, Cr3+, Pb2+, Pd2+, Al3+, Sn2+, Fe2+, Co2+, Cu2+, Fe3+, Cd2+, and Hg2+with ACR-AgNPs. Among all the added metal ions, only Hg2+resulted in significant quenching in the absorption intensity of ACR-AgNPs. The limit of detection of the ACR-AgNP-based nanosensor was found to be 1.65 μM in a wide pH range (1-14). The proposed mercury sensor worked efficiently in the presence of other interfering agents such as other metal ions. Therefore, the synthesized ACR-AgNPs have proved to be an efficient and robust nanosensor for quantitative detection of Hg2+ in real sample analysis such as tap water. The proposed method does not require expensive instrumentation and trained manpower.
Effect of Hand Intensive Training on Upper Limb Function of Stroke Patients with Hemiplegia
Authors: Gou Xiaoxia , Zhang Xian , Zheng Xiaxia , Zhang Yaozhong , Ma Hongxiang
Published: March 2022

Objective. To analyze the effect of hand intensive training on upper limb function of stroke patients with hemiplegia, Methods. 110 stroke patients were randomly divided into two groups: the reference group and the observation group. 55 patients in the reference group were treated with routine rehabilitation treatment, including routine joint activity training, bed training, exercise therapy, and ADL ability training; 55 cases in the observation group received intensive hand training on the basis of routine rehabilitation treatment, including inducing the patient’s five finger extension, forcibly pulling the fingers and wrist joints, and suddenly opening his fist after clenching his fist. Results. The treatment period of the two groups was 5 weeks. In the comparison results of Fugl-Meyer (FMA), the exercise effect of the observation group with increased hand intensive training was significantly better than that of the control group with stroke hemiplegia treated with conventional methods. The difference was statistically significant,

t
<
10.000

,

P
<
0.05

; In the comparative analysis of upper limb function test (UEFT), the effect of the observation group was significantly higher than that of the reference group treated with routine rehabilitation nursing (all

P
<
0.05

); In the comprehensive comparison of exercise ability results, the observation group was higher than the reference group in the flexibility, fineness, and fineness of activity behavior after treatment. Conclusion. Strengthening hand intensive training can further improve the upper limb motor function of stroke patients with hemiplegia, reduce the severity of hemiplegia, and improve the recovery effect of stroke patients. It is worthy of clinical promotion and application.
Biodiesel Production from Waste Animal Fat by Transesterification Using H2SO4 and KOH Catalysts: A Study of Physiochemical Properties
Authors: Hasan Nasim , Ratnam M. Venkata
Published: March 2022

Biodiesel is marketed as a long-term renewable fuel that may partially replace fossil fuels in transportation while also helping to reduce global warming. The current study is focused on using waste animal fat as a feedstock for biodiesel production. Sulfuric acid (H2SO4) and potassium hydroxide (KOH) are used as catalysts, with methanol as an alcohol. Temperature at 60°C, reaction time 2 hrs for acid catalyst, and 55°C, reaction time 90 min for base catalyst with a methanol to oil ratio of 5 : 1 are the experimental and optimized process conditions. With the H2SO4 catalyst, the biodiesel yield was 65.7%, while with the KOH catalyst, it was 48.8%. The ASTM standards are used to compare and study the physicochemical characteristics. This study offers an environmentally friendly solution to a global problem of atmospheric pollution, and at the same time, it shows a commercial alternative to reduce the ecological impact caused by waste animal fat.
Stability Analysis Model of Expressway Passing through Goaf Based on SBAS-InSAR Technology
Authors: Tao Wenbin , Dai Luxin , Zhang Zhifeng , Tang Bin , Yu Lin
Published: March 2022

Due to the lack of historical subsidence data on goaf sites alongside expressways, it is difficult to comprehensively evaluate the stability of goaf sites and accurately identify potential risk points. An investigation to study the stability of goaf sites in the Huaibei section of the Xu Huaifu Expressway is conducted through SBAS-InSAR technology and field investigation. Initially, the stability of the goaf site around the route is anticipated through field investigation. Afterwards, based on the extraction of Sentinel-1 satellite images, subsidence data of the goaf sites from 2017 to 2021 were extracted. Finally, the stability of risk points is analysed. Results demonstrate that although mining in the area stopped more than five years ago, the goaf site has continued to slowly sink. According to four years of goaf site subsidence data extracted by SBAS-InSAR technology, two subsidence risk areas, namely, Y1-05 and Y1-09, were discovered, and the subsidence areas displayed an obvious inverted “convex” shape. Of these two areas, Y1-05 is a potential risk point that was not found during the field investigation. The subsidence basin in the Y1-05 area has developed gradually, and the residual subsidence is expected to be close to 475 millimetres within the next 15 years. Although it can be considered a stable area, the subsidence value is quite large and may pose risks to route safety. Therefore, a flexible reinforced mesh can be adopted for the route. The subsidence basin of Y1-09 is the largest, but the expected residual subsidence is only 50 millimetres and will have insignificant influence on the route. Engineering practice shows that SBAS-InSAR technology can effectively analyse the surface deformation of goaf sites and has important practical significance in optimising the selection of special geological routes in expressways.
Anatomical Variant of Spinal Accessory Nerve Passing through Fenestrated Internal Jugular Vein
Authors: Takaoka Shohei , Yamagata Kenji , Okubo-Sato Makiko , Fukuzawa Satoshi , Uchida Fumihiko , Ishibashi-Kanno Naomi , Bukawa Hiroki
Published: March 2022

Neck dissection (ND) is a major surgery for head and neck cancer. Currently, some or all of the spinal accessory nerve (SAN), sternocleidomastoid muscle, and internal jugular vein (IJV) are aggressively preserved during ND to reduce postoperative complications. Since the anatomical relationship between the SAN and IJV has several variations, knowledge of these variations is necessary to avoid iatrogenic damage. In the present case, the SAN was observed to pass through the fenestrated IJV at the level of the posterior belly of the digastric muscle during ND in a patient with squamous cell carcinoma of the mandible. Although the anatomical structure of the SAN and IJV is rare, surgeons must be aware of this anatomical variation.
Research on Application of Sports Training Performance Prediction Based on Convolutional Neural Network
Authors: Li Yunlong , Zhao HaoZhen , Gao JiaYu
Published: March 2022

In order to improve the prediction effect of sports training performance and improve the effect of sports training, this paper classifies the sports training image area, refines the image into different areas, finds suspicious areas, and completes the error prediction. Moreover, this paper calculates the regional similarity of sports training images in the fully connected layer of the convolutional neural network and introduces the local linear weighting method for analysis. In addition, this paper gives a certain weight to each prediction point near the area to be predicted and selects the suspicious area feature based on the multievaluation standard fusion method. Finally, this paper combines the convolutional neural network algorithm to construct a sports training performance prediction system to improve the effect of sports training and design experiments to verify the system proposed in this paper. From the experimental research results, we can see that the sports training performance prediction system based on the convolutional neural network proposed in this paper has good practical effects.
Optimization Distribution Method of Computer Sensor Network Communication Based on the Linear Planning Model
Authors: Li Xiaohui , Su Xin , He Nansi , Sharma Anil
Published: March 2022

In order to explore the optimal allocation method of computer network communication, a linear programming model is proposed. Based on the overall structure of service chain deployment, the integer linear programming model is introduced to make mathematical modeling, so that network resources and load balancing can be effectively utilized under resource and delay constraints. Simulation results showed that in the experiment, 10 to 100 SFC request intensities were generated, respectively, calculating the request acceptance rates of the three deployment algorithms. Under the same conditions, the average request acceptance rate based on the G-kSP algorithm is about 95.4% and about 92.3%, and the greedy deployment algorithm is about 81.7%. We show that the optimized distribution method of computer sensor network communication based on a linear programming model reduces the load balance and time complexity while reducing the request acceptance rate.
Antiplatelet Activity of Tetramethylpyrazine via Regulation of the P2Y12 Receptor Downstream Signaling Pathway
Authors: Guan Baoyi , Gao Jie , Tan Yu , Ma Xiaojuan , Shi Dazhuo
Published: March 2022

Background. Tetramethylpyrazine (TMP) is an alkaloid in Chinese herbal medicine, which possesses antiplatelet activity. TMP inhibits platelet activation in many ways. The platelet P2Y12 receptor for adenosine 5′ diphosphate (ADP) plays a central role in platelet function, hemostasis, and thrombosis. Here, we investigated the inhibitory effect of TMP on P2Y12 receptor-related platelet function. Methods. The inhibitory potential of TMP was assessed using agonist-induced platelet aggregation, flow cytometric analysis of CD62p expression, PAC-1 activation, and fibrin clot retraction. After the P2Y12 receptor-related signaling pathway was inhibited using the blocker, platelet activation was studied by platelet aggregation, CD62p expression, and PAC-1 activation. The secretion of cyclic adenosine monophosphate (cAMP) was measured using enzyme-linked immunosorbent assay (ELISA), and the expression of signaling pathway protein, phosphorylation of vasodilator-stimulated phosphoprotein, and phosphorylation of Akt were investigated using western blotting. The release of platelet inflammatory mediators was measured using ELISA. Results. TMP had an antiplatelet effect by inhibiting ADP-induced aggregation, P-selectin secretion, and glycoprotein (GP) IIb/IIIa expression and reducing the release of atherosclerotic-related inflammatory mediators (sCD40L and IL-1β). TMP decreased the area of clot retraction, reflecting inhibition of GPIIb/IIIa activation. TMP inhibited adenosine diphosphate-induced platelet activation via increased cAMP production, VASPser157 phosphorylation, and Akt dephosphorylation. Conclusion. TMP selectively inhibits ADP-induced platelet activation via P2Y12 receptor-related signaling pathways.