bluuebunny/crossref_metadata_2025 huggingface dataset:
Cardioprotection by Citrus grandis (L.) Peel Ethanolic Extract in Alloxan‐Induced Cardiotoxicity in Diabetic Rats
Authors: Najar Imtiyaz Ahmed , Bhat Moomin Hussain , Qadrie Zulfqar Lateif , Amaldoss Maria John Newton , Kushwah Ajay Singh , Singh Thakur Gurjeet , Kabra Atul , Khan Nadeem , Kumar Manish
Published: June 2022

Diabetic cardiomyopathy (DCM) pathogenesis is multifarious, and there are insufficient therapeutic options to treat DCM. The present research explored the effects of Citrus grandis peel ethanolic extract (CGPE) in alloxan‐induced DCM in rats. Diabetes was triggered by intraperitoneal (i.p.) injection of alloxan (150 mg/kg) in Wistar rats (200‐250 g). CGPE (100, 200, and 400 mg/kg) or glibenclamide (Glib, 10 mg/kg) were administered orally for 2 weeks. After the treatment schedule, prooxidants (thiobarbituric acid reactive substances), antioxidants (glutathione, catalase, and superoxide dismutase), and inflammatory markers (tumor necrosis factor‐α) were determined in cardiac tissues. Biomarkers of cell death, viz., lactate dehydrogenase (LDH), creatine kinase MB (CK‐MB) activity, glucose levels, total cholesterol (TC), and high‐density lipoproteins (HDL), were assessed in the blood. Rats administered with alloxan showed a consistent increase in blood glucose level (days 7 and 14) that was lowered considerably (p < 0.001) by CGPE or Glib. Alloxan‐induced increase in LDH, CK‐MB, TC, and decline in HDL was attenuated (p < 0.001) in rats that were treated with CGPE or Glib. Alloxan significantly (p < 0.001) elevated oxidative stress, inflammation, and reduced antioxidants in the cardiac tissue of rats, and these pathogenic abnormalities were ameliorated (p < 0.001) by CGPE. Histopathological studies showed a decrease in morphological disruptions by alloxan in CGPE‐treated rats. CGPE (400 mg/kg) significantly ameliorated biochemical parameters in comparison to the lower doses against alloxan cardiotoxicity. Citrus grandis peel extract can be an alternative in the management of DCM.
Analysis of the Role of Continuous Early Intervention in Improving the Quality of Life of Breast Cancer Patients
Authors: Ding Xiufang , Chen Lijie
Published: June 2022

In order to improve the quality of life of breast cancer patients, this paper will apply continuous early intervention to the nursing of breast cancer patients. The continuous early intervention nursing model can propose countermeasures for the health problems faced by patients with postoperative chemotherapy. In order to analyze the effect of continuous early intervention nursing on negative emotions and quality of life in breast cancer patients, the effect of continuous early intervention in improving the quality of life of breast cancer patients is analyzed by means of experimental research. The control group is given routine nursing, and the observation group is given continuous early intervention nursing intervention. Moreover, this paper obtains data statistics in combination with statistical analysis. Through the comparison of the test results, it can be seen that the implementation of continuous early intervention nursing intervention in breast cancer patients can improve the nursing effect, effectively relieve the negative emotions of patients, and improve the quality of life of patients.
A Two-Step Damage Diagnostic Approach Based on Static Strain Energy and Model-Updating via the Equilibrium Optimizer
Authors: Safa Behrouz , Rasouli Asghar , Nasira Yahya
Published: June 2022

Despite the great achievements accomplished so far in the field of damage detection, the need for a more comprehensive damage detection approach that effectively functions despite several real-world obstacles still exists. Among different methods suggested so far, model-updating holds the most appeal; however, its accuracy and efficiency are seriously challenged when the problem size grows as it fails to solve the problem with an increase in the number of variables. In this paper, a two-step approach is suggested that reduces the problem size in model updating-based damage detection methods by identifying potentially damaged elements using a static strain-based damage identification index over the first step. Therefore, only a few unknown variables will be introduced to the next step, which involves an iterative model-updating process that includes a novel damage-sensitive objective function to determine damage severities in the located elements of the previous step. In this stage, a meta-heuristic optimizer, the Equilibrium Optimizer, is utilized to detect the unknown variables, i.e., damage values. This optimization algorithm is used given that it has not been applied to damage detection problems before. The method is also tested on a number of numerical examples to be validated and the effects of external factors such as measurement noise can be taken into account. Apart from that, a comparative study is also carried out to compare the efficacy of the present work with previous references. Interestingly, the method is capable of detecting damaged elements with great speed and accuracy, and the quality of the results has not been seriously affected in the presence of perturbing factors. Moreover, information from even a limited number of first modes has been enough to solve the problem, which means that the approach does not require all vibration modes. Finally, an experimental verification study is also carried out to demonstrate the capability of the method in detecting damaged elements in real structures. It is shown that the method can detect the damaged element successfully, which is indicative of the practicality of the suggested technique in real-world applications.
Informative SNP Selection Based on a Fuzzy Clustering and Improved Binary Particle Swarm Optimization Algorithm
Authors: Li Zejun , Ang Li , Shi Wei , Xin Ning , Chen Min , Tang Hua
Published: June 2022

Single-nucleotide polymorphism (SNP) involves the replacement of a single nucleotide in a deoxyribonucleic acid (DNA) sequence and is often linked to the development of specific diseases. Although current genotyping methods can tag SNP loci within biological samples to provide accurate genetic information for a disease associated, they have limited prediction accuracy. Furthermore, they are complex to perform and may result in the prediction of an excessive number of tag SNP loci, which may not always be associated with the disease. Therefore in this manuscript, we aimed to evaluate the impact of a newly optimized fuzzy clustering and binary particle swarm optimization algorithm (FCBPSO) on the accuracy and running time of informative SNP selection. Fuzzy clustering and FCBPSO were first applied to identify the equivalence relation and the candidate tag SNP set to reduce the redundancy between loci. The FCBPSO algorithm was then optimized and used to obtain the final tag SNP set. The prediction performance and running time of the newly developed model were compared with other traditional methods, including NMC, SPSO, and MCMR. The prediction accuracy of the FCBPSO algorithm was always higher than that of the other algorithms especially as the number of tag SNPs increased. However, when the number of tag SNPs was low, the prediction accuracy of FCBPSO was slightly lower than that of MCMR (add prediction accuracy values for each algorithm). However, the running time of the FCBPSO algorithm was always lower than that of MCMR. FCBPSO not only reduced the size and dimension of the optimization problem but also simplified the training of the prediction model. This improved the prediction accuracy of the model and reduced the running time when compared with other traditional methods.
Research on IoT Forensics System Based on Blockchain Technology
Authors: Liang Guangjun , Xin Jianfang , Wang Qun , Ni Xueli , Guo Xiangmin
Published: June 2022

In recent years, mobile edge computing (MEC) has become a research hotspot in academia. The Internet of Things (IoT) is an excellent way to build the infrastructure required for a MEC environment. Its rich digital tracking repository can provide insights into people's daily activities at home and elsewhere. Meanwhile, due to the open connectivity of the Internet of things devices, they can easily become the target of network attacks and be used by criminals as criminal tools. As a result, civil and criminal cases have increased year by year. This article conducts in-depth research on IoT forensics. By comparing its difference with traditional digital forensics (DF), the definition of IoT forensics is given. We have systematically sorted out the research results since the concept of IoT forensics was proposed in 2013 and proposed a generalized IoT forensics model. By studying blockchain technology and introducing it into the IoT forensics framework, a blockchain-based IoT forensics architecture is further proposed. Further, an alliance chain IoT forensics system is proposed. From the perspective of the data provider and the data visitor, the process of evidence storage and forensics of the IoT system is discussed. Finally, taking Unmanned Aerial Vehicle (UAV) forensics as an example, we give an experiment of IoT forensics analysis.
Test-Retest Reliability, Validity, and Minimal Detectable Change of the Measurement of Lower Limb Muscular Strength with Handheld Dynamometry in Patients Undergoing Hemodialysis
Authors: Perez-Dominguez Borja , Lopez-Brull Aida , Plaza-Carrasco Maria , Casaña-Granell Jose , Garcia-Testal Alicia , Benitez-Martinez Josep
Published: June 2022

Background. Chronic kidney disease is an exponentially growing medical and economic worldwide problem. There are specific elements used to assess patient’s functional capacity loss and overall deterioration in order to determine the patient’s clinical status, and muscle impairment is one of the most common. It is therefore necessary to develop reliable and applicable methods to determine muscle impairment in patients with chronic kidney disease Methods. This is a prospective, nonexperimental, descriptive methodological investigation performed in patients undergoing hemodialysis. This study analyzes the reliability and validity of muscle strength assessments performed with handheld dynamometry in patients with chronic kidney disease undergoing hemodialysis. Results. Results show overall high reliability and validity in the assessment of muscle strength of the lower limbs Conclusion. To our knowledge, this is the first study to assess handheld dynamometry in patients undergoing hemodialysis, presenting promising results with a relatively affordable and easily applicable method.
The Effect of Corneal Refractive Power Area Changes on Myopia Progression during Orthokeratology
Authors: Chen Minfeng , Liu Xinting , Xie Zhu , Wang Pengqi , Zheng Miaoran , Mao Xinjie
Published: June 2022

Purpose. To investigate the effect of corneal refractive power area changes on myopia progression during orthokeratology. Methods. One hundred and sixteen children who met the inclusion criteria and insisted on wearing orthokeratology lenses for two years were retrospectively assessed. Seventy-two children with the orthokeratology lens decentration distance more than 0.5 mm but less than 1.5 mm were in the decentered group, and forty-four children with the orthokeratology lens decentration distance less than 0.5 mm were in the centric group. The orthokeratology decentration via tangential difference topography was analyzed. This study calculated the different power areas in the central 4 mm pupillary area by axial-difference corneal topography, compared the differences of the different power areas between these two groups, and evaluated the relationships between corneal positive-power area, orthokeratology decentration, and AL changes. Results. The axial length changes of the centric group presented a statistical difference with the decentered group (0.52 ± 0.37 mm vs. 0.38 ± 0.26 mm; t = 2.403,p=0.018). For all children, both the AL changes (0.43 ± 0.31 mm) and decentration distance (0.64 ± 0.33 mm) showed a significant correlation with the positive-power area (r = −0.366,p<0.001and r = 0.624,p<0.001); AL changes also presented a statistical correlation with decentration distance (r = −0.343,p<0.001), baseline age (r = −0.329,p<0.001), and baseline spherical equivalent refractive power (r = 0.335,p<0.001). In the centric group and decentered group, the AL changes (centric group: r = −0.319,p=0.035; decentered group: r = −0.332,p=0.04) and decentration distance (centric group: r = 0.462,p=0.002; decentered group: r = 0.524,p<0.001) had a significant correlation with the positive-power area yet. In the multiple regression analysis, AL changes were increased with less baseline age (beta, 0.015;p<0.001), positive-power area (beta, 0.021;p=0.002), and larger SER (beta, 0.025;p=0.018). Conclusions. The corneal positive-power area had a positive impact on affirming AL changes during orthokeratology. This area might be formed by lens decentration to provide an additional myopia-defocusing influence on the retina to achieve better myopia control.
Availability and Accessibility of Islamic Religious Education Elementary School Students in Non-Muslim Base Areas, North Minahasa, Indonesia
Authors: Idris Muh. , Bin Tahir Saidna Zulfiqar , Wilya Evra , Yusriadi Yusriadi , Sarabani Leeda
Published: June 2022

This study aims to (1) describe the position of Islamic Religious Education in the Indonesian National Education System, (2) reveal the condition of Islamic Religious Education (IRE) in North Minahasa, and (3) analyze the accessibility of IRE for Islamic students in non-Muslim elementary schools. A qualitative-descriptive method was used for this analysis, with primary data being obtained and identified through informants. Meanwhile, books, scientific journals, and other pieces of relevant literature were used as secondary data and analyzed inductively. The results showed that elementary schools did not pragmatically have Islamic Religious Education services although the rights of the Muslim students in obtaining them had been guaranteed by the Indonesian Government through the National Education System (NES) Law Number 20 of 2003. This led to the inaccessibility of the educational services, with the main factor being the insufficient number of Islamic students, as required by the NES. Despite the unfulfilled quota to obtain these services, government control as policymakers was still needed. This indicated that the ministry and the education office at the central and regional levels should have alternative solutions, respectively, without being negligent in resolving the problematic condition. Based on these results, the patterns by which the state failed in the equal availability and accessibility of religious education to Indonesian students were observed at all levels of state elementary schools under its regulation. These subsequently strengthened inequalities in this educational field while practicing religious discrimination based on accessibility. Additionally, the results suggest that the central and regional Indonesian governments, as well as other related agencies, need to be more proactive in providing religious education services to all institutional students. This leads to the availability of equality in obtaining education for all citizens, as mandated by law.
An Automatic Error Correction Method for English Composition Grammar Based on Multilayer Perceptron
Authors: Wang Juan , Gu Feng
Published: June 2022

In order to improve the timeliness of English grammar error correction and the recall rate of English grammar error correction, this paper proposes an automatic error correction method for English composition grammar based on a multilayer perceptron. On the basis of preprocessing the English composition corpus data, this paper extracts the grammatical features in the English composition corpus and constructs a grammatical feature set. We take the feature set as the input information of the multilayer perceptron and realize feature classification through network learning and training. The grammatical error items in the English composition are detected according to the similarity, and the error correction is completed by setting the penalty parameter and reducing the deviation parameter. The experimental results show that the syntax error detection time of this method is less than 6 minutes, the recall rate is higher than 90%, and the detection error rate is lower than 6%. The method improves the timeliness of grammatical error correction and improves the efficiency of error correction.
The Impact of Digital Economy of Resource-Based City on Carbon Emissions Trading by Blockchain Technology
Authors: Zhang Jiahao , Li Jingyi , Ye Duoduo , Sun Chuanqing
Published: June 2022

To reduce the carbon emission intensity of resource-based cities and strengthen the sustainable development of these cities, firstly, blockchain technology is analyzed. Secondly, the development of the digital economy is discussed in digital resource-based cities. Finally, according to blockchain technology, a model of carbon emissions trading in the digital economy is designed, and the specific impact of the digital economy on carbon emissions trading is studied according to the model. The research results show that the mean value of the development index of the digital economy (digital) is −0.0168, the maximum value is 4.2560, the minimum value is −1.3429, and the standard deviation is 0.9572, indicating that the quality of digital economy development varies greatly among different regions. And according to the results of the digital model, it is found that the regression coefficient of the variable digital is significantly negative at the 1% level, showing that the digital economy will obviously suppress the carbon emission intensity of cities. After replacing the explained variables, the coefficient of the digital economy is still significantly negative. It indicates that the development of the digital economy can effectively suppress the carbon emission intensity of urban. Therefore, the designed model of carbon emissions trading under the blockchain technology can not only provide a secure platform for carbon emissions trading but also provide more comprehensive trading reference information for carbon emissions trading. It provides technical support for reducing the carbon emission intensity of resource-based cities and also contributes to the development of resource-based cities.
Energy-Based Aerodynamic Analysis on the Blended-Wing-Body Aircraft with Boundary Layer Ingestion
Authors: Zhao Wenyuan , Zhang Yanlai , Wu Jianghao
Published: June 2022

This study is aimed at evaluating the energy saving benefit and its limitation of the boundary layer ingestion (BLI) applied to a transonic blended-wing-body (BWB) aircraft. The power balance method is adopted in the aerodynamic performance analysis of the aircraft. We further improve the one-dimensional analysis framework by adding the pressure volumetric work term in the power balance equation for the application in compressible flow with shock wave regions. A determining expression for the power-saving coefficient (PSC) of the BLI effect is also deduced, which is related to a BLI fraction, the airframe dissipation component ratios, and the specific thrust of the propulsor. This expression provides a way for the preliminary evaluation and comparison of BLI benefits applied in different aircraft configurations. The flow quantities of three different configurations are obtained by 3D Reynolds-averaged Navier–Stokes (RANS) numerical simulations for the calculation of aerodynamic dissipation components. The grid refinement and domain size study shows that the calculated force coefficients and total dissipation coefficient have a good convergence characteristic with the mesh refinement and are insensitive to the variation in domain size. The evaluated PSC of the BWB aircraft with a BLI propulsor is 5% using the previously developed determining expression. The maximum of PSC is 18.8%. The following comparison of dissipation components for the power-on and power-off cases shows that the benefit of BLI is slightly underestimated by the determining expression of PSC. The reason is that the variation in the boundary layer velocity profile at the trailing edge of the center body part is neglected, which is due to the installation of the propulsor. Furthermore, when the BLI propulsor is applied to a BWB aircraft, the variation in trailing edge vortex dissipation and volumetric pressure work term should be studied in detail.
Size-Dependent Behaviour of Representative Volume Element for Granular Material under Gravity-Induced Stress Gradient
Authors: Li Ruilin , Ji Yukun , Chen Jun , Chen Daqing , Cai Shangyue
Published: June 2022

Gravity is the primary load source in geotechnical engineering, and its effect becomes extremely important in these cases such as lunar research station construction and in situ resource utilization. However, at the current stage, the study on the effect of gravity-induced stress gradients on the behavior of geomaterials is seriously lacking. In this work, the size-dependent behaviour of representative volume element (RVE) of granular matter under the gravity-induced stress gradient is studied. A homogenization theory is proposed firstly, which homogenizes the granular matter into stress gradient continuum through RVE. Then, numerical triaxial loading for RVEs with various heights and particle sizes is carried out under 0∼10 g gravity. The results show that the size effect and its origination appear to have no obvious influence on isotropic compression. However, the macroscopic shear strength, elastic modulus, and volumetric deformation all show size effect dependence, and the gravity-induced stress gradient leads to significant differences between different originations of size effect. The valence, orientation, and elongation degree of microscopic void cells are further analyzed, which suggests that applying of stress gradient results in the evolution of void cells demonstrates a dependence on both the size effect and its origination. The results indicate that the gravity-induced stress gradient and corresponding size effect should be paid sufficient attention to granular mechanics of terrestrial and off-earth engineering.
The Prognostic Implication of the BRAF V600E Mutation in Papillary Thyroid Cancer in a Chinese Population
Authors: Ye Ziheng , Xia Xiaotian , Xu Peipei , Liu Wenfei , Wang Shoufei , Fan Youben , Guo Minggao
Published: June 2022

Background. The BRAF V600E mutation is an important genetic event in papillary thyroid cancer (PTC). This study aimed to provide additional information regarding the association of the BRAF V600E mutation with PTC prognosis. Methods. A retrospective single-center study based on a Chinese population was performed to analyze the association of the BRAF V600E mutation with several clinicopathological features. Kaplan–Meier survival curves and Cox proportional hazards regression analysis were applied to implement the survival analysis. Results. The BRAF V600E mutation was present in 1102 (87.7%) of the 1257 patients and was significantly associated with older age, conventional subtype, multifocality, advanced TNM stage, and a reduced prevalence of Hashimoto’s thyroiditis. The Kaplan–Meier survival curves demonstrated that the difference between the BRAF V600E-positive and BRAF V600E-negative groups was significant with a log-rank P-value of 0.048. The Cox proportional hazards regression analysis adjusted HR was 3.731 (95% CI, 1.457 to 9.554). We further demonstrated that larger tumor size (>1 cm), extrathyroidal extension (ETE), and lateral lymph node metastasis (LNM) were associated with a higher probability of PTC recurrence in patients harboring the BRAF V600E mutation. Conclusions. The BRAF V600E mutation remains an independent risk factor for PTC recurrence and may be useful for clinical decisions when it combines with some pathological factors.
Toward Privacy-Preserving Blockchain-Based Electricity Auction for V2G Networks in the Smart Grid
Authors: Zhang Weijian , Yang Wen , Chen Cen , Li Nuannuan , Bao Zijian , Luo Min
Published: June 2022

With the development of electric vehicle (EV) technology, EV has become a key component in the future smart grid. Due to the sheer large number of EVs on the road, the emerging vehicle-to-grid (V2G) technology, which allows for two-way electrical flows between EVs and the power grid, is gaining traction. However, establishing a fair and private electricity exchange scheme has gradually become a critical challenge. The emergence of blockchain technology offers a novel approach for resolving this issue. In this study, we overview the opportunities and challenges of blockchain in the smart grid. Then, we provide a privacy-preserving blockchain-based electricity auction scheme for V2G networks in smart grid. In particular, we exploit PS group signatures to keep the privacy of EVs or charging stations and leverage blockchain to provide automated auction execution. With our mechanism, the identity of EV/charging station is conditionally protected. In case of an emergency, the trusted authority (i.e., the group manager) can open the identity. Meanwhile, we present the security analysis to prove our scheme’s security. Finally, we implement the experiment to evaluate efficiency. The experimental results show that our proposal is efficient and suitable for V2G networks.
Factors Influencing Piezoelectric Response of Horizontally and Vertically Embedded PZT Patch in Confined Granular Fills
Authors: Kumari Nisha , Trivedi Ashutosh
Published: June 2022

The energy harvesting from ambient vibrations in the confined granular fill along the expressways and highways is a prospective power source for varied engineering applications. This paper presents the study of charge density, voltage output, and power from the PZT (lead zirconate titanate) patches embedded in dynamically loaded confined granular fill. The effect of the alignment of PZT patches, thickness ratio, material properties of the confined granular fill, and retaining structure on the voltage output is investigated. It provides the scope for the evaluation of voltage output directly from the stress-strain response, position of the PZT patch, and the engineering properties of the confined granular fill. The alignment of PZT patches in the horizontal and vertical directions has been examined analytically to optimize voltage outputs. The results indicate that the modulus ratio of the material, alignment of PZT patches, and gradation of infill material significantly affect the voltage generation. A relationship for voltage and power output has been proposed for a set of engineering applications. The observed voltage output is found appropriate for wide-ranging implements classified as low- (LRA), medium- (MRA), and high- (HRA) resistance applications. It is proposed to be up-scaled using multiple patches embedded throughout the confined granular fill and pavements subjected to continuous dynamic loads.
A Design Model of English Auxiliary Teaching System Using Artificial Neural Networks
Authors: Zhao Beidou
Published: June 2022

At present, the development of artificial intelligence has entered a new stage. In the next few years, human life will be greatly covered by artificial intelligence. Artificial intelligence (AI) is an intelligent technology that simulates the human brain for thinking operation. English is very difficult for Chinese students to learn. Moreover, at present, there are still many areas that need to be improved or improved in the design of English assistant instruction system (EAIS) in China. This study aims to study an EAIS based on AI. This study presents an algorithm combined with neural network. This study designs a system that can enable students’ autonomous learning system, English teacher assisted teaching, AI expert intelligent diagnosis, and system administrator to manage and analyze data. And this study tests the actual effect of the system. By comparing the academic performance of two classes in the school, the results show that although the average score of students’ monthly test fluctuates after using the AI EAIS, it tends to rise as a whole. Moreover, its initial score of 81.5 was 1.1 lower than that of the class without the teaching system and finally increased to 90.11. It is 6.89 points higher than the class that does not use the teaching system. This shows that the auxiliary system designed in this study has a certain effect on the improvement of students’ English performance.
Deep Learning-Based Image Reconstruction for Different Medical Imaging Modalities
Authors: Yaqub Muhammad , Jinchao Feng , Arshid Kaleem , Ahmed Shahzad , Zhang Wenqian , Nawaz Muhammad Zubair , Mahmood Tariq
Published: June 2022

Image reconstruction in magnetic resonance imaging (MRI) and computed tomography (CT) is a mathematical process that generates images at many different angles around the patient. Image reconstruction has a fundamental impact on image quality. In recent years, the literature has focused on deep learning and its applications in medical imaging, particularly image reconstruction. Due to the performance of deep learning models in a wide variety of vision applications, a considerable amount of work has recently been carried out using image reconstruction in medical images. MRI and CT appear as the ultimate scientifically appropriate imaging mode for identifying and diagnosing different diseases in this ascension age of technology. This study demonstrates a number of deep learning image reconstruction approaches and a comprehensive review of the most widely used different databases. We also give the challenges and promising future directions for medical image reconstruction.
Volleyball Video Moving Target Tracking and Detection Algorithm Based on Multisensor Information Fusion
Authors: Wang Cong , Dong Kongmei
Published: June 2022

With the improvement of the level of sports competition technology, pure sports game broadcasting can no longer meet the requirements of various users. Users urgently need new technologies to meet the needs of quickly obtaining game information. The 5G Internet of Things is rapidly rising; volleyball is also gradually into people’s life. To solve the above problems, the research on the volleyball video moving target tracking and detection algorithm based on 5G Internet of Things communication and artificial intelligence becomes very important. This article is aimed at comparing the tracking and detection algorithms of volleyball video moving targets through 5G Internet of Things communication and artificial intelligence. In the process of detecting moving targets, several commonly used background detection methods are comprehensively compared and analyzed, and a method based on adaptive background difference is proposed. The algorithm uses Gaussian mixture model for background modeling, uses the OTSU threshold algorithm to determine the segmentation threshold

T

, and proposes a background update method that combines the expected full statistics and the

L

-close window to accelerate the background update speed, so that a more accurate sports prospect target. Experimental results show that the algorithm can detect and track moving targets in volleyball videos well in a fixed scene or when moving targets are not blocked, with a detection accuracy of more than 92%.
Optimization Design and Performance Analysis of Improved IEEE802.11p MAC Mechanism Based on High Mobility of Vehicle
Authors: Peng Jiankui , Li Suoping , Dou Zufang , Yang Sa
Published: June 2022

The high-speed movement of vehicles is the core factor affecting the rapid development of vehicular ad hoc network (VANET), especially the impact of vehicle mobility on data access and transmission performance. However, the classic IEEE802.11p data access and transmission protocol are still used in the multi-hop VANET under the highway system, which is adopted in the low-speed environment. Therefore, the impact of vehicle movement on the performance of the existing network is analyzed theoretically, and it is found that the network performance will be greatly reduced with the increase of vehicle speed. In order to improve the network performance in high-speed environment, an improved network access transmission protocol is proposed. Through Markov modeling, the analytic expressions of system delay, throughput, and packet loss rate are obtained. Finally, the effectiveness of the improved mechanism is verified by comparing the simulation results of two mechanisms.
An Experimental Study on the Inhibition of Wear Particle‐Induced Osteolysis by Lycium barbarum Polysaccharide In Vivo
Authors: Liu Zige , Feng Lin , Yeow Sai Kiang , Chen Desheng
Published: June 2022

Objective. To investigate the effect of Lycium barbarum polysaccharide (LBP) in a mouse calvarial osteolysis model and to explore the potential mechanisms involved. Methods. Eighty C57BL/6J mice were randomly assigned to four groups: Sham control (PBS treatment), Vehicle (titanium/PBS treatment), Low‐LBP (titanium/50 mg kg-1 day-1 LBP), and High‐LBP (titanium/100 mg kg-1 day-1 LBP). After 2 weeks, mouse calvariae were collected for microcomputed tomography (micro‐CT) and histomorphometry analysis. The levels of tumor necrosis factor‐α (TNF‐α), interleukin‐1β (IL‐1β), and IL‐6 were measured by enzyme‐linked immunosorbent assay (ELISA). Results. LBP significantly reduced titanium‐particle‐induced osteolysis compared with the Vehicle group as confirmed by micro‐CT and histomorphometry data. Additionally, high osteoprotegerin (OPG) and low receptor activator of nuclear factor kappa‐Β ligand (RANKL), TNF‐α, IL‐1β and IL‐6 were noted in LBP treatment groups. Conclusion. LBP inhibited wear particle‐induced osteolysis in mice and suppressed the expression of inflammation‐related factors; this inhibitory effect of LBP may be achieved with the regulation of OPG/RANKL pathway and inhibition of inflammatory factor production.
TADW: Traceable and Anti-detection Dynamic Watermarking of Deep Neural Networks
Authors: Dong Jinwei , Wang He , He Zhipeng , Niu Jun , Zhu Xiaoyan , Wu Gaofei
Published: June 2022

Deep neural networks (DNN) with incomparably advanced performance have been extensively applied in diverse fields (e.g., image recognition, natural language processing, and speech recognition). Training a high-performance DNN model requires a lot of training data and intellectual and computing resources, which bring a high cost to the model owners. Therefore, illegal model abuse (model theft, derivation, resale or redistribution, etc.) seriously infringes model owners’ legitimate rights and interests. Watermarking is considered the main topic of DNN ownership protection. However, almost all existing watermarking works apply solely to image data. They do not trace the unique infringing model, and the adversary easily detects these ownership verification samples (trigger set) simultaneously. This paper introduces TADW, a dynamic watermarking scheme with tracking and antidetection abilities in the deep learning (DL) textual domain. Specifically, we propose a new approach to construct trigger set samples for antidetection and innovatively design a mapping algorithm that assigns a unique serial number (SN) to every watermarked model. Furthermore, we implement and detailedly evaluate TADW on 2 benchmark datasets and 3 popular DNNs. Experiment results show that TADW can successfully verify the ownership of the target model at a less than 0.5% accuracy cost and identify unique infringing models. In addition, TADW is excellently robust against different model modifications and can serve numerous users.
A Comparative Thermal Performance Assessment of Various Solar Collectors for Domestic Water Heating
Authors: Kalair Ali Raza , Seyedmahmoudian Mehdi , Saleem Muhammad Shoaib , Abas Naeem , Rauf Shoaib , Stojcevski Alex
Published: June 2022

Growing population, depleting fossil fuels, economic expansions, and energy intensive life style demand are resulting in higher energy prices. We use energy as of heat and electricity, which can directly be obtained from sun using thermal collectors and solar cells. Solar thermal systems are gaining attention for water and space heating applications due to green aspects of solar energy. A solar thermal collector is a vital part of solar thermal energy system to absorb radiant energy from the sun. In this study, a solar water heating (SWH) system has been designed and simulated in the TRNSYS ® software using thermal and chemical properties of heat transfer fluids using REFPROP for dwellings located on ±31° latitudes (+31 Lahore in Pakistan and -31° Perth in Australia). We present an efficiency parametric optimization-based model for water and space heating. Simulation results for four types of solar thermal collectors are presented, and performance is analyzed on the basis of output temperature (

T

out

), solar fraction (

f

), and collector efficiency (

η

). This study evaluates the comparative performance of evacuated tube collector (ETC), flat-plate collector (FPC), compound parabolic concentrator (CPC), and thermosiphon-driven systems. Our findings conclude the evacuated glass tube collector achieves the highest solar fraction, i.e., 50% of demand coverage during August in Pakistan and February in Australia, with an overall average of 43% annually.
Design and Performance Analysis of a Dynamic Magnetic Resonance Imaging-Compatible Device for Triangular Fibrocartilage Complex Injury Diagnosis
Authors: Fu Jiayu , Zhang Hui , Wei Kaiqi , Shi Chao , Zong Wei
Published: June 2022

Pain and injury of the triangular fibrocartilage complex (TFCC) due to overuse or trauma are commonly diagnosed through static MRI scanning, while TFCC is always involved in radial and ulnar deviation of the wrist. To the best of our knowledge, a dynamic MRI diagnostic method and auxiliary tool have not been applied or fully developed in the literature. As such, this study presents the design and evaluation of a dynamic magnetic resonance imaging (MRI) auxiliary tool for TFCC injury diagnosis. First, 3D scanning and Python are used to measure and fit the radial and ulnar deviation trajectories of healthy participants and patients. 3D printing is then used to manufacture the auxiliary tool for dynamic MRI, and dynamic MRI diagnosis is then conducted to explore the clinical effect. The radial and ulnar deviation trajectory is presented as an asymmetric curve without an obvious circular centre, and the results indicate that the designed auxiliary device meets the requirements of the ulnar and radial movements of the human wrist. According to the MRI contrast test results, the image quality score of patients wearing the auxiliary device is higher than for those without. Such devices could assist clinicians in the diagnosis of TFCC damage, and our method could not only serve as the reference standard for clinical noninvasive diagnosis but also help in understanding the disease and improving the accuracy of TFCC diagnosis.
Photodynamic Therapy–Induced Cell Surface Expression and Release of Heat Shock Proteins: Relevance for Tumor Response
Authors: Korbelik Mladen , Sun Jinghai , Cecic Ivana
Published: June 2022

Almost instantaneously after the treatment of mouse SCCVII tumor cells with Photofrin-based photodynamic therapy (PDT), a fraction (15-25%) of total cellular heat shock protein 70 (HSP70) became exposed at the cell surface. The level of this surface-expressed HSP70 then remained unchanged for the next 6 hours and persisted at lower levels even at 18 hours after PDT. A similar induction of surface HSP70 expression was found with PDT-treated human umbilical vein endothelial cells. The same analysis for several other HSPs revealed the induced surface expression of HSP60 and GRP94, but not GRP78, on PDT-treated SCCVII cells. A fraction of total HSP70 existing in SCCVII cells at the time of PDT treatment was promptly (within 1 hour) released from cells after high treatment doses, whereas even lower PDT doses induced a substantial HSP70 release at later time intervals. Macrophages coincubated with PDT-treated SCCVII cells displayed elevated levels of both HSP70 and GRP94 on their surface and were stimulated to produce tumor necrosis factor α, whose production was inhibited by the presence of antibodies against either HSP70, Toll-like receptors 2 and 4, or specific NF-κB inhibitor in the coincubation medium. The induction of cell surface expression and release of HSPs by PDT may represent an important event in the response of tumors to this treatment modality with a critical role in the induced inflammatory and immune responses that contribute to the therapeutic outcome.
Down-regulation of RAB6KIFL/KIF20A, a Kinesin Involved with Membrane Trafficking of Discs Large Homologue 5, Can Attenuate Growth of Pancreatic Cancer Cell
Authors: Taniuchi Keisuke , Nakagawa Hidewaki , Nakamura Toru , Eguchi Hidetoshi , Ohigashi Hiroaki , Ishikawa Osamu , Katagiri Toyomasa , Nakamura Yusuke
Published: June 2022

To identify novel molecular targets for treatment of pancreatic ductal adenocarcinoma (PDAC), we generated precise gene expression profiles of PDACs on a genome-wide cDNA microarray after populations of tumor cells were purified by laser microdissection. Through functional analysis of genes that were transactivated in PDACs, we identified RAB6KIFL as a candidate for development of drugs to treat PDACs at the molecular level. Knockdown of endogenous RAB6KIFL expression in PDAC cell lines by small interfering RNA drastically attenuated growth of those cells, suggesting an essential role for the gene product in maintaining viability of PDAC cells. RAB6KIFL belongs to the kinesin superfamily of motor proteins, which have critical functions in trafficking of molecules and organelles. Proteomics analyses using a polyclonal anti-RAB6KIFL antibody identified one of the cargoes transported by RAB6KIFL as discs, large homologue 5 (DLG5), a scaffolding protein that may link the vinexin-β-catenin complex at sites of cell-cell contact. Like RAB6KIFL, DLG5 was overexpressed in PDACs, and knockdown of endogenous DLG5 by small interfering RNA significantly suppressed the growth of PDAC cells as well. Decreased levels of endogenous RAB6KIFL in PDAC cells altered the subcellular localization of DLG5 from cytoplasmic membranes to cytoplasm. Our results imply that collaboration of RAB6KIFL and DLG5 is likely to be involved in pancreatic carcinogenesis. These molecules should be promising targets for development of new therapeutic strategies for PDACs.
Decreased Fidelity in Replicating CpG Methylation Patterns in Cancer Cells
Authors: Ushijima Toshikazu , Watanabe Naoko , Shimizu Kimiko , Miyamoto Kazuaki , Sugimura Takashi , Kaneda Atsushi
Published: June 2022

The unmethylated or methylated status of individual CpG sites is faithfully copied into daughter cells. Here, we analyzed the fidelity in replicating their methylation statuses in cancer cells. A single cell was clonally expanded, and methylation statuses of individual CpG sites were determined for an average of 12.5 DNA molecules obtained from the expanded population. By counting the deviation from the original methylation patterns inferred, the number of errors was measured. The analysis was done in four gastric cancer cell lines for five CpG islands (CGI), and repeated six times (total 1,495 clones sequenced). HSC39 and HSC57 showed error rates <1.0 × 10−3 errors per site per generation (99.90-100% fidelity) for all the five CGIs. In contrast, AGS showed significantly elevated error rates, mainly due to increased de novo methylation, in three CGIs (1.6- to 3.2-fold), and KATOIII showed a significantly elevated error rate in one CGI (2.2-fold). By selective amplification of fully methylated DNA molecules by methylation-specific PCR, those were stochastically detected in KATOIII and AGS but never in HSC39 and HSC57. When methylation of entire CGIs was examined for eight additional CGIs, KATOIII and AGS had frequent methylation, whereas HSC39 and HSC57 had few. KATOIII and AGS had four and eight times, respectively, as high expression levels of DNMT3B as HSC39. These data showed that some cancer cells have decreased fidelity in replicating methylation patterns in some CGIs, and that the decrease could lead to methylation of the entire CGIs.
Thymosin β10 Inhibits Angiogenesis and Tumor Growth by Interfering with Ras Function
Authors: Lee Seung-Hoon , Son Myung Jin , Oh Sun-Hee , Rho Seung-Bae , Park Kyungsook , Kim Yung-Jin , Park Mi-Sun , Lee Je-Ho
Published: June 2022

Thymosin β10 is a monomeric actin sequestering protein that regulates actin dynamics. Previously, we and others have shown that thymosin β10 acts as an actin-mediated tumor suppressor. In this study, we show that thymosin β10 is not only a cytoskeletal regulator, but that it also acts as a potent inhibitor of angiogenesis and tumor growth by its interaction with Ras. We found that overexpressed thymosin β10 significantly inhibited vascular endothelial growth factor–induced endothelial cell proliferation, migration, invasion, and tube formation in vitro. Vessel sprouting was also inhibited ex vivo. We further show that thymosin β10 directly interacted with Ras. This interaction resulted in inhibition of the Ras downstream mitogen-activated protein kinase/extracellular signal-regulated kinase kinase signaling pathway, leading to decreased vascular endothelial growth factor production. Thymosin β10 injected into a xenograft model of human ovarian cancer in nude mice markedly inhibited tumor growth and reduced tumor vascularity. In contrast, a related thymosin family member, thymosin β4, did not bind to Ras and showed positive effects on angiogenesis. These findings show that the inhibition of Ras signal transduction by thymosin β10 results in antiangiogenic and antitumor effects, suggesting that thymosin β10 may be valuable in anticancer therapy.
Wavelet Transformations of Tumor Expression Profiles Reveals a Pervasive Genome-Wide Imprinting of Aneuploidy on the Cancer Transcriptome
Authors: Aggarwal Amit , Leong Siew Hong , Lee Cheryl , Kon Oi Lian , Tan Patrick
Published: June 2022

Aneuploidy is frequently observed in many human cancers, but its global effects on the cancer transcriptome are controversial. We did a systematic and unbiased genome-wide survey to determine the extent a tumor's abnormal karyotype (chromosomal amplifications and deletions) is detectably “imprinted” onto that tumor's gene expression profile. By using a novel methodology employing wavelet transform signal-processing algorithms to identify genomic regions of coordinated gene expression (wavelet variance scanning), we analyzed a series of gastric cancer cell lines and identified >100 genomic regions exhibiting distinct patterns of subtle but significant coordinated transcription, ranging from tens to hundreds of genes. A large majority (80%) of these regions could be specifically localized to a site of detectable genomic amplification or deletion; reciprocally, up to 47% of the total aneuploidy in each of the individual cell lines could be directly inferred from the gene expression data. Genome-wide portraits of tumor aneuploidy can thus be successfully reconstructed solely from gene expression data, implying that the effects of aneuploidy must be pervasively and globally imprinted within the cancer transcriptome. Aneuploidy may contribute to tumor behavior not just by affecting the expression of a few key oncogenes and tumor suppressor genes but also by subtly altering the expression levels of hundreds of genes in the oncogenome.