bluuebunny/crossref_metadata_2025 huggingface dataset:
Sensor Design Based on Wireless Measurement of Corrosion Monitoring of Reinforced Concrete Structure
Authors: Ren Zhenxing , Zhong Bin , Xiong Rong
Published: April 2022

Reinforced concrete structures are widely used in modern buildings such as buildings, bridges, and tunnels. However, the structural damage caused by reinforcement corrosion seriously affects the service life of the buildings. Because the corrosion of reinforcement in concrete is a very slow process, the continuous detection of reinforcement corrosion is very important. In view of the slow development of steel corrosion detection equipment in China, which cannot meet the application requirements of concrete structures in China, wireless monitoring technology has more advantages than traditional monitoring technology. In this paper, combined with wireless transmission technology, a concrete reinforcement corrosion detection system based on wireless sensor network is designed. Embedded sensors based on the principle of electromagnetic coupling are used to collect steel corrosion information. It is determined that the 16-bit ultralow power consumption microcontroller MSP430F149 is the main control chip, the AD9850 based on DDS technology is the signal generation chip, and the nRF905 is the detection circuit scheme of the wireless transceiver chip. The star network is determined by polling the entire network topology and MAC protocol. The embedded sensor is designed through simulation. This article discusses the principle of using embedded sensors to detect steel corrosion and determines the feasibility of its low-cost implementation. The embedded sensor and steel corrosion detection system were tested. The simulation method of the embedded sensor is verified through actual measurement. The test results show that the system network is normal and all parts work stably, which can meet the requirements of the project.
Ethanol-Extracted Cameroonian Propolis Counteracts Tamoxifen-Induced Endometrial Hyperplasia by Modulating Apoptosis and Proliferation-Regulating Proteins in the Ovaries of Intact Wistar Rats
Authors: Awounfack Charline Florence , Zingué Stéphane , Koumabas Bruno , Tueche Alain Brice , Tata Charlotte Mungho , Tchuenguem Fohouo Fernand-Nestor , Njamen Dieudonné , Ndinteh Derek Tantoh
Published: April 2022

Tamoxifen is the most common adjuvant that has been widely used in the treatment of positive estrogen receptor (ER+) breast cancer for over 20 years. However, long term exposure to tamoxifen doubles the risk of endometrial cancer. The association of tamoxifen with antiproliferative substances could abrogate its side effects on the endometrium. Recently, we demonstrated that ethanol-extracted Cameroonian propolis (EECP) has chemopreventive effects on ER+ breast cancer in rats. This study evaluated the capability of EECP to counteract tamoxifen-induced endometrial hyperplasia, without altering its effect on the breast. Thirty-six rats of ∼2 months were coadministered either EECP (16.5, 50, and 150 mg/kg BW) or fulvestrant (300 μg/kg BW) and tamoxifen (10 mg/kg BW) for 8 weeks. Afterward, the relative weights and histomorphometry of the uterus, vagina, ovaries, and mammary gland were assessed. The expression of some proteins of proliferation (PCNA), angiogenesis (VEGF), and apoptosis (Bax, Bcl-2, and caspase-3) was measured by immunohistochemistry. Rats that received only tamoxifen had endometrial hyperplasia compared to normal rats. EECP and fulvestrant protected the rats against tamoxifen-induced endometrial hyperplasia. A significant decrease in uterine wet weight (

p
<
0.01

); endometrial height (

p
<
0.001

); and expression of PCNA, Bcl-2, and VEGF proteins as well as a significant increase in the expression of Bax and caspase-3 proteins was observed in the EECP group compared to the Tamox group. EECP did not change the effects of tamoxifen on the breast. In summary, Cameroonian propolis which is efficacious in preventing breast cancer can also be a good complementary medicine to prevent tamoxifen-induced endometrial cancer in tamoxifen users.
Bu Shen Yi Sui Capsules Promote Remyelination by Regulating MicroRNA-219 and MicroRNA-338 in Exosomes to Promote Oligodendrocyte Precursor Cell Differentiation
Authors: Ji Jing , Sun Ya-Qin , Zha Zheng , Xue Bing , Li Jun-Ling , Jin Liang-Yun , Qi Fang , Zhang Nan , Zhao Hui , Fan Yong-Ping , Wang Lei
Published: April 2022

Remyelination is a refractory feature of demyelinating diseases such as multiple sclerosis (MS). Studies have shown that promoting oligodendrocyte precursor cell (OPC) differentiation, which cannot be achieved by currently available therapeutic agents, is the key to enhancing remyelination. Bu Shen Yi Sui capsule (BSYSC) is a traditional Chinese herbal medicine over many years of clinical practice. We have found that BSYSC can effectively treat MS. In this study, the effects of BSYSC in promoting OPCs differentiation and remyelination were assessed using an experimental autoimmune encephalomyelitis (EAE) model in vivo and cultured OPCs in vitro. The results showed that BSYSC reduced clinical function scores and increased neuroprotection. The expression of platelet-derived growth factor receptor α (PDGFR-α) was decreased and the level of 2′,3′-cyclic nucleotide 3′-phosphodiesterase (CNPase) was increased in the brains and spinal cords of mice as well as in OPCs after treatment with BSYSC. We further found that BSYSC elevated the expression of miR-219 or miR-338 in the serum exosomes of mice with EAE, thereby suppressing the expression of Sox6, Lingo1, and Hes5, which negatively regulate OPCs differentiation. Therefore, serum exosomes of BSYSC-treated mice (exos-BSYSC) were extracted and administered to OPCs in which miR-219 or miR-338 expression was knocked down by adenovirus, and the results showed that Sox6, Lingo1, and Hes5 expression was downregulated, MBP expression was upregulated, OPCs differentiation was increased, and the ability of OPCs to wrap around neuronal axons was improved. In conclusion, BSYSC may exert clinically relevant effects by regulating microRNA (miR) levels in exosomes and thus promoting the differentiation and maturation of OPCs.
Discussion on the Transoral Vestibular Approach Endoscopy for TC Patients and the Significance of Serum 25-Hydroxyvitamin D Classification
Authors: Yang Chunjiang , Yu Leitao , Xiao Yong , Ouyang Longhong , Huang Xiaohua
Published: April 2022

In order to discuss the transoral vestibular approach endoscopy through oral vestibular approach in TC and the efficacy of 25(OH)D classification, a total of 110 TC patients from January 2020 to June 2021 are selected. The endoscopic group and the control group are respectively established according to different surgical approaches, with 55 cases in each group. The control group received conventional TC resection, while the endoscopic group received endoscopic assisted TC resection through oral vestibular approach. The differences of intraoperative and postoperative indicators, clinical efficacy, incidence of adverse complications, VAS score, and total satisfaction are observed. TC resection assisted by endoscopy through oral vestibular approach can effectively improve all intraoperative indicators and reduce postoperative pain and has high safety in clinical application. In addition, this study conducted in-depth analysis and classification of serum 25(OH)D index level in postoperative TC patients, indicating that the serum 25(OH)D index level is closely related to prognosis, providing a basis for follow-up clinical monitoring of TC patients’ signs and optimization of diagnosis and treatment plans.
Real Estate Marketing Adaptive Decision-Making Algorithm Based on Big Data Analysis
Authors: Lv Sheng
Published: April 2022

Aiming at the problems of low stability and efficiency of marketing decision-making and large complexity of marketing decision-making in the current marketing adaptive decision-making algorithm, a real estate marketing adaptive decision-making algorithm based on Big Data analysis is proposed. By analyzing the concept of Big Data, using the Big Data distributed computing architecture, researching the data mining-related algorithms. By constructing an association rule algorithm, mining the rules between real estate marketing and related factors. Based on the Spark-distributed computing platform, an optimization idea of association mining is designed. Decision tree algorithm is used to select discrete and continuous attribute features. According to the characteristics of real estate marketing data and the weight-based discrimination method, the decision tree pruning algorithm is optimized using the classification accuracy, stability, and complexity criteria, and the adaptive decision-making model of real estate marketing is constructed to realize the adaptive decision-making of real estate marketing. The experimental results show that the proposed algorithm has high stability and efficiency in real estate marketing adaptive decision-making and can effectively reduce the complexity of marketing decision-making.
Artificial Intelligence in Recording the Number of Times the Ball Has Crossed the Net in a Badminton Game
Authors: Zhu Xingmin
Published: April 2022

In today’s intelligent age, the research and development of intelligent equipment are now an important direction, and the combination of artificial intelligence and sports is also a very popular research nowadays. This article uses the current popular artificial intelligence technology to record the number of times the ball crosses the net in a badminton game and provide real-time feedback to ensure the fairness and justice of the game. In this paper, artificial intelligence technology is the center. Experiments were conducted to record the number of times badminton crossed the net in official competitions, and the very popular artificial intelligence technology was analyzed. The algorithm we designed was first applied to amateur competitions. Recording real-time data lays a solid foundation for subsequent research and will be used in professional competitions later. The experimental results of this article have developed a function based on artificial intelligence to record the number of times the ball has crossed the net in a badminton game. We have studied traditional games and found that badminton has an average of more than 3000 times over the net in a game, and there are also some in amateur competitions. Nearly 2,000 times, and more than 50% of people like this sport in our daily lives, so our research is very meaningful and can be implemented in concrete terms.
Research on Library Book Information Resource Management Based on Artificial Intelligence and Sensors
Authors: Liu Chunyu
Published: April 2022

In order to explore the research on library book information resource management, the author proposes a method based on artificial intelligence and sensors. Using an improved SVM algorithm, in order to realize the personalized data mining of the library, the support vector machine algorithm has supervised, scalable, and nonlinear high-efficiency characteristics in the use process, able to achieve nonlinear multicore data clustering effect, thereby improving the learning ability of data mining. The experimental results show the following: BP neural network was used to adaptively train the processed data samples, users give certain positive feedback during use, the sensor system is based on the result of feedback, continuous self-learning was carried out, sample data were updated and optimized, and a closed virtuous circle has been realized. In the classification experiment of Sogou Chinese text corpus data set, the classification effect of several classification models in the “sports” category is significantly higher than that of other categories; it shows that the text classification characteristics of the “sports” category are more significant. Among them, KNN (

K

-Nearest Neighbor) has a classification accuracy of 99.7% in the “sports” category; this shows that some classification algorithms, in a specific category, can achieve its best classification performance. Prove the method based on artificial intelligence; it can better realize library book information resource management.
MDST-DGCN: A Multilevel Dynamic Spatiotemporal Directed Graph Convolutional Network for Pedestrian Trajectory Prediction
Authors: Liu Shaohua , Liu Haibo , Wang Yisu , Sun Jingkai , Mao Tianlu
Published: April 2022

Pedestrian trajectory prediction is an essential but challenging task. Social interactions between pedestrians have an immense impact on trajectories. A better way to model social interactions generally achieves a more accurate trajectory prediction. To comprehensively model the interactions between pedestrians, we propose a multilevel dynamic spatiotemporal digraph convolutional network (MDST-DGCN). It consists of three parts: a motion encoder to capture the pedestrians’ specific motion features, a multilevel dynamic spatiotemporal directed graph encoder (MDST-DGEN) to capture the social interaction features of multiple levels and adaptively fuse them, and a motion decoder to produce the future trajectories. Experimental results on public datasets demonstrate that our model achieves state-of-the-art results in both long-term and short-term predictions for both high-density and low-density crowds.
Depth Vision-Based Assessment of Bone Marrow Mesenchymal Stem Cell Differentiation Capacity in Patients with Congenital Scoliosis
Authors: Liang Ning , Zhang Qiwen , He Bin
Published: April 2022

Congenital scoliosis (CS) is a lateral curvature of one or more segments of the spine due to spinal dysplasia during fetal life. CS is clinically defined as a curvature of the spine >10° due to structural abnormalities of the vertebrae during the embryonic period. Its etiology is unknown, but recent studies suggest that it may be closely related to genetic factors, environmental factors, and developmental abnormalities. The induction methods and modern applications of bone marrow MSCs provide a reference for in-depth human research on the induction of differentiation of bone marrow MSCs into osteoblasts. In this paper, by reviewing and organizing the literature on bone marrow MSCs, we summarized and analyzed the biological properties and preparation of bone marrow MSCs, the methods of inducing osteoblasts, the applications in tissue engineering bone, the problems faced, and the future research directions and proposed a method to assess the differentiation ability of bone marrow MSCs in patients with congenital scoliosis based on depth visual characteristics and the change of the method. The method reveals and evaluates the multidirectional differentiation potential of bone marrow MSCs, which can be induced to differentiate into osteoblasts in vitro and can be used to construct bone tissue engineering scaffolds in vitro using tissue engineering techniques. Based on the properties of bone marrow MSCs, their application in congenital scoliosis patients for trauma repair, cell replacement therapy, hematopoietic support, and gene therapy is quite promising. It is necessary to carry out research on the mechanism of osteogenic differentiation of bone marrow MSCs to provide guidance and reference value for their induced differentiation into osteoblasts.
Digital Protection and Development of Intangible Cultural Heritage Relying on High-Performance Computing
Authors: Ding Hong
Published: April 2022

The protection of intangible cultural heritage has gradually attracted people's attention. In today's digital information age, the use of digital technology in the protection of intangible cultural heritage has become the focus of research in the field of intangible cultural heritage protection. For the protection of intangible cultural heritage to become the key goal of the continuous inheritance of China's traditional culture, this paper fully analyzes the problems existing in the inheritance and protection of intangible cultural heritage, and applies the high-performance computing method to the digital protection and development of intangible cultural heritage, which provides a strong basis for the protection of intangible cultural heritage. The accurate identification and protection of intangible cultural heritage can be achieved by using high-performance computing methods. In addition, the digital protection and development system of intangible cultural heritage is also designed. Finally, the example results show that the digital protection and development system of intangible cultural heritage proposed in this paper can effectively protect intangible cultural heritage and promote the continuous development of domestic local economy. At the same time, it can also strengthen the public awareness of the protection of intangible cultural heritage and effectively promote the inheritance and development of the protection of intangible cultural heritage.
Clothing Modular Design Based on Virtual 3D Technology
Authors: Wang Jiao , Zhong Yijun
Published: April 2022

In order to improve the effect of online clothing modular design, this paper adopts the improved linear skinning technology. Moreover, without changing the original input value, this paper uses the QLERP interpolation method to interpolate the rotations of multiple joints into one and determines the rotation angle through the calculation of the rotation center point, so as to subtly solve the problem of skin depression and distortion, and greatly improving the authenticity of the experiment. In addition, this paper combines the virtual 3D technology to build a clothing modular design system to improve the effect of online clothing design. The simulation test results show that the clothing modular design system based on virtual 3D technology proposed in this paper basically meets the current online clothing modular design requirements.
Multidomain Feature Fusion Network for Fault Diagnosis of Rolling Machinery
Authors: Yang Dewei , Zhou Kefa , Qi Feng , Dong Kai
Published: April 2022

Mechanical vibration constitutes a valuable cue for performing fault diagnosis as it is directly related to the transient regime of rolling machinery. This study establishes a multidomain feature fusion network (MFFN) to extract and fuse multidomain features through a novel multistream architecture. Three primary features are simultaneously extracted from the time, frequency, and time-frequency domains. Then, highly representative features are extracted via three convolutional branches in one- or two-dimensional spaces. A novel squeeze-connection-excitation (SCE) module is proposed to adaptively fuse features in the three domains. The advantage offered by the proposed method is that it can leverage cues from the raw vibration signal, resulting in accurate fault diagnosis. Experimental results comprehensively demonstrate and analyze the high accuracy and generalization achieved by this MFFN-based fault diagnosis method.
Detection of Diseases Using Machine Learning Image Recognition Technology in Artificial Intelligence
Authors: Huang Jian , Li Jing , Li Zheming , Zhu Zhu , Shen Chen , Qi Guoqiang , Yu Gang
Published: April 2022

With the continuous development and improvement of artificial intelligence technology, machine learning technology has also been extensively developed, which has promoted the development of computer vision, image processing, natural language processing, and other fields. Purpose. This article aims to apply the image processing technology based on machine learning in the detection of childhood diseases and propose the application of image processing technology to the detection of childhood diseases. This article introduces machine learning, image recognition technology, and related algorithms in detail and experiments on image recognition technology based on machine learning. The experimental results show that image recognition technology based on machine learning can well identify white blood cells that are difficult to distinguish with the naked eye, with a recognition rate of up to 90%. Applying image recognition technology based on machine learning in disease diagnosis has greatly improved the level of medical diagnosis.
Gallic Acid Inhibits Mesaconitine-Activated TRPV1-Channel-Induced Cardiotoxicity
Authors: Han Shu , Bao Liyuan , Li Weifei , Liu Kaiyang , Tang Ya’nan , Han Xitao , Liu Ziqin , Wang Hongyue , Zhang Fengting , Mi Shuo , Du Hong
Published: April 2022

Aconiti Kusnezoffii Radix (Caowu) is often combined or processed with Chebulae Fructus (Hezi) to achieve attenuation purposes in Mongolian medicine. Mesaconitine (MA), a main bioactive ingredient of Caowu, is also famous for its high cardiotoxicity while exerting good anti-inflammatory and analgesic properties. Gallic acid (GA), one of the leading chemical components in Hezi, possesses cardiac protection. This study aimed to clarify the detoxification effects of GA from Hezi on MA-induced cardiotoxicity and whether the detoxification mechanism is related to the TRPV1 channel. Cell viability was determined by methyl thiazol tetrazolium (MTT), and lactate dehydrogenase (LDH) leakage rate was determined by ELISA. Hoechst 33258, JC-1, DCFH-DA, and Fluo-3 AM staining were conducted to detect apoptosis, mitochondrial membrane potential, reactive oxygen species (ROS), and Ca2+ respectively; TRPV1 channel current was recorded by whole-cell patch-clamp technology to observe the effect of GA and MA alone or in combination on TRPV1 channel. The results showed that GA exhibited pronounced detoxification effects on MA-induced cardiotoxicity. GA significantly inhibited the MA-induced decrease in cell viability; suppressed the MA-induced LDH leakage rate, apoptosis, and the release of ROS and Ca2+; and alleviated the reduction of mitochondrial membrane potential. We found that MA-induced cardiotoxicity was significantly attenuated in H9c2 cells pretreated with the TRPV1 antagonist BCTC. In the whole-cell patch-clamp experiment, the TRPV1 channel current increase was caused by the GA and MA treatment, whereas it was reduced by the cotreatment of GA and MA. Our data demonstrate that GA in Hezi can reduce MA-induced cardiotoxicity by inhibiting intracellular Ca2+ influx, restoring mitochondrial membrane potential, and reducing apoptosis. The detoxification mechanism may be related to the desensitization of the TRPV1 channel by the combined application of MA and GA.
Application of Low-Frequency Processing Method Based on VMD Algorithm in Blasting Signal Processing
Authors: Jia Bei , Li Shenglin , Liu Dianshu , Wu Shuaifeng
Published: April 2022

In the field of blasting vibration signal analysis, accurate removal of low-frequency noise in the signal has important practical significance. In view of the shortcomings of the existing methods, such as cumbersome calculation and limited scope of application, a method based on variational mode decomposition (VMD) to remove low-frequency noise was proposed. In this paper, the parameter selection of VMD algorithm to identify low-frequency noise of blasting signal is optimized by simulation experiment. The results show that frequency has little influence on the decomposition effect. When the frequency of low-frequency noise is between 0 and 5 Hz, the influence of frequency on the decomposition effect remains basically unchanged. The amplitude has a significant effect on the decomposition effect. The smaller the amplitude, the worse the decomposition effect of the VMD method. Taking the excavation of the Badaling Great Wall Station as the background, the LSM method, EMD method, and VMD method are used to remove the low-frequency noise of the randomly selected test signals in order. Compared with the LSM method and the EMD method, the signal processed by the VMD method does not have modal mixing and does not have much low-frequency noise residue. It has more extensive applicability in removing low-frequency noise of blasting signal.
Role of Human-Computer Interaction Healthcare System in the Teaching of Physiology and Medicine
Authors: Li Xiuhong , Xu Yubo
Published: April 2022

With the increasingly severe aging of the population, the difficult and expensive medical treatment problems are becoming more and more prominent; the salary level of domestic doctors is not high, but the cost of training doctors is high, coupled with doctors’ work pressure and mental pressure; the number of candidates for medical school is decreasing year by year; medical talent is rare; and the allocation of medical staff is scarce. Health care is the basic guarantee for people’s good life, and the shortage of medical staff will have many impacts on health care. Human-computer interaction (HCI) is the study of people, computers, and their interaction. HCI refers to the communication between the user and the computer system, which is the two-way information exchange of various symbols and actions between the human and the computer. The purpose of this paper is to study a healthcare system with human-computer interaction through the client, apply the system to the teaching of physiology and medicine, and analyze its effects and functions in combination with various evaluation indicators. This paper selects teaching content, ease of use of human-computer interaction design, technical services, and user subjective satisfaction as evaluation indicators, and constructs an evaluation model for this. And it builds the physiology and medicine teaching system framework and healthcare system, and conducts tests and statistics on the teaching system. This paper combines online questionnaires, in-app survey feedback, and field visits to collect feedback from users and administrators. The final data show that the teaching system meets the requirements in four evaluation indicators: teaching content, ease of use of human-computer interaction design, technical services, and user subjective satisfaction. User satisfaction with these four aspects reached 86.33%, 95.17%, 63.83%, and 81.87%, respectively. It shows that the system is more popular and can meet the needs of most users.
Electronic User Authentication Key for Access to HMI/SCADA via Unsecured Internet Networks
Authors: Abu-Jassar Amer Tahseen , Attar Hani , Yevsieiev Vladyslav , Amer Ayman , Demska Nataliia , Luhach Ashish Kr. , Lyashenko Vyacheslav
Published: April 2022

This paper discusses the development of new hardware and software for protecting access to HMI/SCADA systems via Unprotected Internet Networks (UPN), mainly when working remotely with confidential information. Based on the analysis carried out, it is shown that the existing vulnerabilities can be exploited by cybercriminals to steal passwords and user authentication logins. Modern protection technologies based on the OTP method have been investigated. Moreover, a new concept of information security for user authentication in UPNs when working with information remotely is proposed. The structure of the electronic key and the connection diagram based on the selected hardware modules have been developed. In addition, the two-level user identification algorithms and the firmware program code for the ATmega32U4 microcontroller are considered. Finally, to show the reliability and stability of the of the developed electronic user authentication key against any unexpected software hacking, a number of experiments have been performed.
Comparison of Bone Metastases between 18F‐NaF PET/CT, 18F‐NaF PET, and Planar 99mTc‐MDP Bone Scintigraphy in Patients with Newly Diagnosed Nasopharyngeal Carcinoma
Authors: Wang Dong , Yang YiYang , Zeng ZhenPei , Ye Jing , Guo ChengMao , Huang ShiSang , Guo XuFeng , Xiao JingXing
Published: April 2022

Purpose. Our study aims to compare the diagnostic value of 18F‐NaF positron emission tomography‐computed tomography (PET/CT), 18F‐NaF PET, and planar 99mTc‐MDP bone scintigraphy for detection of bone metastases in patients with newly diagnosed nasopharyngeal carcinoma (NPC). Methods. Our study retrospectively analyzed 58 patients with pathologically proven NPC. They all underwent both 18F‐NaF PET/CT and planar 99mTc‐MDP bone scintigraphy within a 7‐day interval. Bone metastases were confirmed by follow‐up using PET/CT, contrast‐enhanced computed tomography (CT), and magnetic resonance imaging (MRI). These three examinations were compared using per‐patient‐based analysis and per‐lesion‐based analysis. Results. 19 patients (32.7%) were classified as having bone metastatic disease in their final diagnosis. The patient‐based diagnostic performances (sensitivity, specificity, and overall accuracy) were as follows: 18F‐NaF PET/CT (100%, 92.3%, and 94.8%), 18F‐NaF PET (100%, 53.8%, and 69.0%), and planar 99mTc‐MDP bone scintigraphy (78.9%, 74.4%, and 75.9%). The overall accuracy of 18F‐NaF PET/CT was significantly more favorable compared to 18F‐NaF PET (p = 0.002) and to planar 99mTc‐MDP bone scintigraphy (p = 0.044). The lesion‐based diagnostic performances (sensitivity, specificity, and overall accuracy) were as follows: 18F‐NaF PET/CT (98.5%, 93.9%, and 96.6%), 18F‐NaF PET (98.5%, 57.1%, and 81.1%), and planar 99mTc‐MDP bone scintigraphy (69.9%, 85.7%, and 76.4%). Conclusion. 18F‐NaF PET/CT outperforms 18F‐NaF PET or planar 99mTc‐MDP bone scintigraphy in detecting bone metastases with newly diagnosed NPC on a patient‐based and lesion‐based analysis.
Inhibition of APE1 Expression Enhances the Antitumor Activity of Olaparib in Triple-Negative Breast Cancer
Authors: Jian Dan , Li Xue-Mei , Dai Nan , Liang Dan-Dan , Zhang Gang , Mao Cheng-Yi , Wang Dong , Song Guan-Bin , Li Meng-Xia , Luo Hao
Published: April 2022

Triple-negative breast cancer (TNBC) is a highly aggressive subtype of breast cancer that is prone to recurrence and metastasis. Because of the lack of expression of estrogen receptor (ER) and progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2) in TNBC, treatment methods are greatly limited. In this study, the proliferation inhibition and apoptosis-inducing effects of PARP1 inhibitors in TNBC breast cancer cells and in vivo xenograft animal models were examined to investigate the molecular role of APE1 in PARP1-targeted therapy. In TNBC patients, the expression of APE1 and PARP1 were positively correlated, and high expression of APE1 and PARP1 was associated with poor survival of TNBC. Our results indicated that knockdown APE1 could increase the sensitivity of olaparib in the treatment of TNBC. In conclusion, the results of this study will not only clarify the molecular role of APE1 in PARP1-targeted therapy for TNBC but also provide a theoretical basis for the future clinical application of targeting APE1 and PARP1 in the treatment of refractory TNBC.
Recognition, Processing, and Detection of Sensor Fault Signal Based on Genetic Algorithm
Authors: Wang Wei
Published: April 2022

With the development of electronic information science and network transmission technology, signal processing technology is widely used in various fields. The processing of sensor coarse signal is the key of signal processing technology, in order to study the signal detection and transmission function of the sensor. A genetic algorithm-based sensor fault signal identification, processing, and detection are proposed, and three common signal analysis and processing methods are summarized. The methods of optimal arrangement of sensors are as follows: effective independent algorithm, genetic algorithm, simulated annealing algorithm, and ant colony algorithm principle are studied in detail; signal analysis methods are as follows: fast Fourier transform, wavelet transform, and HHT transform are studied in detail. In the experimental system of the sensor’s coarse signal processing mode, the optimal arrangement of the measurement points of the acceleration sensor in this experiment is directly related to the information collection effect of the monitoring system. Combined with numerical simulation and engineering cases, the soft computing (genetic algorithm, simulated annealing algorithm, and ant colony algorithm) is analyzed in detail, out of the MATLAB program for soft computing. Taking four typical functions as the numerical experimental platform, the three algorithms are used for comparative experimental analysis, and their optimized performance and application range are analyzed. Finally, the practical application performance of soft computing is tested by the practical application problem of optimal path optimization of measuring points. When there are only 10 measuring points, all three algorithms can quickly converge to the global optimal solution, but when there are 100 measuring points, only approximate solutions can be obtained.
Adaptive Differential Evolution Algorithm with Simulated Annealing for Security of IoT Ecosystems
Authors: Liu Qianqian , Zhang Xiaoyan , Hua Qiaozhi , Wen Zheng , Li Haipeng
Published: April 2022

With the wide application of the Internet of Things (IoT) in real world, the impact of the security on its development is becoming incrementally important. Recently, many advanced technologies, such as artificial intelligence (AI), computational intelligence (CI), and deep learning method, have been applied in different security applications. In intrusion detection system (IDS) of IoT, this paper developed an adaptive differential evolution based on simulated annealing algorithm (ASADE) to deal with the feature selection problems. The mutation, crossover, and selection processes of the self-adaptive DE algorithm are modified to avoid trapping in the local optimal solution. In the mutation process, the mutation factor is changed based on the hyperbolic tangent function curve. A linear function with generation is incorporated into the crossover operation to control the crossover factor. In the selection process, this paper adopts the Metropolis criterion of the SA algorithm to accept poor solution as optimal solution. To test the performance of the proposed algorithm, numerical experiments were performed on 29 benchmark functions from the CEC2017 and six typical benchmark functions. The experimental results indicate that the proposed algorithm is superior to the other four algorithms.
The Development of Internet Finance under the Background of Sharing Economy
Authors: Ma Yan
Published: April 2022

With the development of science and technology, the rapid rise of multimedia technology has led to significant changes in computer network system, including mobile communication system, and plays a more and more important role in people’s life. The shared economy as an emerging business model is rapidly emerging at home and abroad and is strongly affecting and changing the production and lifestyle of people everywhere. The business model of sharing economy promotes the reuse of social resources as multimedia networks in China and has become a prominent highlight of China’s economic transformation and upgrading in the new era. Internet finance is a new product, a new form of integration between the sharing economy and the traditional financial industry. Government work reports have repeatedly mentioned the need to promote Internet financial regulation and healthy development. It is especially important to study the new characteristics of Internet finance development under China’s shared economy, reveal the development of Internet finance, and understand its development trend. This paper takes Internet finance as the research object, discusses its concept and characteristics, and analyzes the development status of Internet finance under the shared economy, it is found that in 2017, the potential market scale of China’s personal credit investigation industry was 26.9 billion yuan, and the actual market scale was 22.2 billion yuan. In this way, problems in the development of the Internet under the Chinese sharing economy were discovered. The purpose of this paper is to explore the development of Internet finance under the sharing economy, to discover its development trends, and to propose improved business models. This paper summarizes the current development difficulties of Internet finance in the sharing economy and puts forward corresponding suggestions for these dilemmas, with a view to have reference value.
UAV Image Small Object Detection Based on Composite Backbone Network
Authors: Liu Wuji , Qiang Jun , Li Xixi , Guan Ping , Du Yunlong
Published: April 2022

Small objects in traffic scenes are difficult to detect. To improve the accuracy of small object detection using images taken by unmanned aerial vehicles (UAV), this study proposes a feature-enhancement detection algorithm based on a single shot multibox detector (SSD), named composite backbone single shot multibox detector (CBSSD), which uses a composite connection backbone to enhance feature representation. First, to enhance the detection effect of small objects, the lead backbone network, VGG16, is kept constant, and ResNet50 is added as an assistant backbone network, and the residual structure in ResNet50 is used to obtain lower feature information. The obtained lower feature information is then fused to the lead network through feature fusion, allowing the lead network to retain rich lower feature information. Finally, the lower feature information in the prediction layer increases. The experimental results show that CBSSD has a significantly higher recognition rate and a lower false detection rate than conventional algorithms, and it still maintains a good detection effect under low illumination. This is of great significance to small object detection using images taken by UAVs in traffic scenes. Furthermore, a method to improve the SSD algorithm is proposed.
In Vivo Anti-Inflammatory, Analgesic, Sedative, Muscle Relaxant Activities and Molecular Docking Analysis of Phytochemicals from Euphorbia pulcherrima
Authors: Aljohani Abdullah S. M. , Alhumaydhi Fahad A. , Rauf Abdur , Hamad Essam M. , Rashid Umer
Published: April 2022

Euphorbia pulcherrima is an important medicinal plant that is used in a traditional system for its curative properties such as analgesic potency, antipyretic, anti-inflammatory, sedation potential, and antidepressant and cure of diseases such as skin diseases. This study deals with the isolation of two flavonoids namely spinacetin (1) and patuletin (2) from chloroform fraction of Euphorbia pulcherrima. The isolated compound spinacetin (1) and patuletin (2) were screened for in vivo anti-inflammatory, analgesic, sedative, and muscle relaxant effects. Compounds 1 and 2 were assessed against hot plate-induced noxious stimuli at various doses which showed excellent (

p
<
0.05

) analgesic effect in a dose-dependent manner. The muscle relaxant activity was determined by traction and inclined screening model, both compounds showed significant muscle relaxant activity with time. The sedative potential of isolated compounds 1 and 2 was determined by the open field model, both compounds showed good sedation (

p
<
0.05

) at 20 mg/kg. The anti-inflammatory potential of compound 1 was recorded by histamine-induced paw edema and carrageen paw edema model, and in both models, compounds 1 and 2 showed strong effect at 20 mg/kg. Binding orientations, binding energy values, and computed inhibition constants (Ki) values revealed that the studied compounds have a good to excellent inhibition potential against μ-opioid receptors and COX-2.
Optimization of Solar Hybrid Power Generation Using Conductance-Fuzzy Dual-Mode Control Method
Authors: Ramesh S. , Seetha J. , Ramkumar G. , Sahoo Satyajeet , Amirthalakshmi T. M. , Ranjith A. , Seikh Asiful H. , Khan Mohammed Sohail M. A. , Subbiah Ram
Published: April 2022

The functioning of a solar hybrid power system is investigated in this research using a unique fuzzy control method. Turbines, solar photovoltaics, diesel engines, fuel cells, aqua-electrolyzes, and other autonomous generation products are used in the hybrid renewable energy system. Further energy storage components of the system include the batteries, turbine, and ultracapacitor. This research incorporates a supercapacitor hybrid energy storage system (HESS) into a solar hybrid power generating system, allowing the consumption and energy storage space and power output to be significantly increased. This study’s approach incorporates a decentralized power generation system with a HESS while increasing electrical output in phases utilizing a dynamic reactive power compensation scheme and a conductance-fuzzy dual-mode control strategy. Due to a nonlinear behavior of photovoltaic (PV) devices’ power output, maximum power point tracking (MPPT) methods must be used to create the greatest power. Infrequently developing atmospheric circumstances, traditional MPPT algorithms do not work adequately. Modeling is used to determine the microgrid’s power output to the photovoltaic hybrid power generating organization, as well as the optimization method for each device in the network. The dynamic power factor correction scheme and also the conductance-fuzzy dual-mode control approach are primarily used in this study to optimize the solar hybrid renewable energy system.
The Overexpression of TOB1 Induces Autophagy in Gastric Cancer Cells by Secreting Exosomes
Authors: Wang Yanhong , Song Ying , Zhou Lijie , Wang Mengxi , Wang Dong , Bai Jing , Fu Songbin , Yu Jingcui
Published: April 2022

We previously confirmed that transducer of ERBB2, 1 (TOB1) gene, can induce autophagy in gastric cancer cells. Studies have shown the biogenesis of exosomes overlaps with different autophagy processes, which helps to maintain the self-renewal and homeostasis of body cells. This study is aimed at verifying whether overexpressing TOB1 induces autophagy by secreting exosomes in gastric cancer cells and its underlying mechanisms. Differential ultracentrifugation was used to extracted the exosomes from the culture medium of gastric cancer cell line AGS-TOB1 ectopically overexpressing TOB1 (exo-AGS-TOB1, experimental group) and AGS-empty-vector cell line with low expression of endogenous TOB1 (exo-AGS-Vector, control group). Exosomal markers CD9 and TSG101 were determined in both the cell supernatants of exo-AGS-TOB1 and exo-AGS-Vector by Western blot. Under the transmission electron microscope (TEM), the exosomes were round and saucer-like vesicles with double-layer membrane structure, and the vesicles showed different translucency due to different contents. The peak size of exosomes detected by nanoparticle tracking analysis (NTA) was about 100 nm. When the exosomes of exo-AGS-TOB1 and exo-AGS-Vector were cocultured with TOB1 knockdown gastric cancer cell line HGC-27-TOB1-6E12 for 48 hours, the conversion of autophagy-related protein LC3-I to LC3-II in HGC-27-TOB1-6E12 gastric cancer cells cocultured with exo-AGS-TOB1 was significantly higher than that in the control group, and the ratio of LC3-II/LC3-I was statistically different (

P
<
0.05

). More autophagosomes in HGC-27-TOB1-6E12 cells cocultured with exo-AGS-TOB1 for 48 hours were observed under TEM, while fewer autophagosomes were found in the control group. Lastly, miRNAs were differentially expressed by cell supernatant-exosomal whole transcriptome sequencing. Thus, our results provide new insights into TOB1-induced autophagy in gastric cancer.
Optical Investigation of p-GaAs/i-GaN0.38yAs1-1.38ySby/n-GaAs Quantum Wells Emitters
Authors: Guizani I. , Bilel C. , Alrowaili Malak , Rebey A.
Published: April 2022

We have studied the 1.55 μm optical properties of p-GaAs/i-GaN0.38yAs1-1.38ySby/n-GaAs quantum wells using a self-consistent calculation combined with the anticrossing model. We have found that the increase of injected carriers’ density induces the increase of optical gain and radiative current density. The rise of doping density causes a blue shift of the fundamental transition energy accompanied with significant increase of optical gain. The quantum-conﬁned Stark effect on radiative current density is also studied. The variation of radiative current as function of well width and Sb composition is also examined. In order to operate the emission wavelength at the optical fiber telecommunication domain, we have adjusted the well parameters of p-GaAs/i-GaN0.38yAs1-1.38ySby/n-GaAs.
Medicinal Uses, Phytochemistry, Pharmacology, and Toxicology of Mentha spicata
Authors: El Menyiy Naoual , Mrabti Hanae Naceiri , El Omari Nasreddine , Bakili Afaf EI , Bakrim Saad , Mekkaoui Mouna , Balahbib Abdelaali , Amiri-Ardekani Ehsan , Ullah Riaz , Alqahtani Ali S. , Shahat Abdelaaty A. , Bouyahya Abdelhakim
Published: April 2022

Mentha spicata, also called Mentha viridis, is a medicinal plant of the Lamiaceae family characterized by its potency to synthesize and secret secondary metabolites, essentially essential oils. Different populations use the aerial parts of this plant for tea preparation, and this tisane has shown several effects, according to ethnopharmacological surveys carried out in different areas around the world. These effects are attributed to different compounds of M. spicata, in which their biological effects were recently proved experimentally. Pharmacological properties of M. spicata extracts and essential oils were investigated for different health benefits such as antioxidant, anticancer, antiparasitic, antimicrobial, and antidiabetic effects. In vitro and in vivo studies showed positives effects that could be certainly related to different bioactive compounds identified in M. spicata. Indeed, volatile compounds seem to be efficient in inhibiting different microbial agents such as bacteria, fungi, and parasites through several mechanisms. Moreover, M. spicata exhibited, according to some studies, promising antioxidant, antidiabetic, anti-inflammatory, and anticancer effects, which show its potential to be used as a source for identifying natural drugs against cellular oxidative stress and its related diseases. Importantly, toxicological investigations of M. spicata show the safety of this species at different doses and several periods of use which justify its use in traditional medicines as tisane with tea. Here, we report, explore, and highlight the data published on M. spicata concerning its botanical description and geographical distribution, its phytochemical compounds, its pharmacological properties, and its toxicological investigations of M. spicata.
A Hybrid Indoor Positioning Model for Critical Situations Based on Localization Technologies
Authors: Mahdi Alaa A. , Chalechale Abdolah , AbdelRaouf Ashraf
Published: April 2022

The domains of positioning and tracking have undergone substantial evolution and advancements recently, especially within the concept of the Internet of Things (IoT) and in health care. Unfortunately, neither the current satellite positioning systems nor the standalone cellular systems remain useful for successfully localizing and tracking inside buildings. This paper proposes a new model that could improve the accuracy of localization in indoor environments. In addition, a broad review is conducted to discover the state-of-the-art indoor localization technologies appropriate for disasters and rescue situations. After a comprehensive study, three important technologies that need to be deeply reviewed are identified, which are wireless local area network (WLAN), dead reckoning (DR), and hybrid approaches. Based on these, a novel architecture is introduced that is more convenient to meet the operation of rescuing injured or older people in critical situations, where other technologies might be unavailable or require some extra infrastructures. The proposed model has two modes and selects one of these modes automatically. The first mode assumes the existence of both WLAN signals and smartphone sensors to be used for identifying the position of the object; otherwise, only smartphone sensors will be employed to achieve positioning. Significantly, the designated components and the flow control depicted provide a proper and suitable horizon for the next researchers who desire to develop a new indoor positioning system in this discipline with a low positioning root-mean-squared error on the centimeter scale that can later be incorporated in numerous applications relating to the IoT, health care, and evacuation plans.