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African swine fever (ASF) is a highly infectious viral disease with high mortality. The most recent ASF outbreak in Vietnam began in 2019, posing a threat to spread to the neighbouring Asian countries. Without a commercial vaccine or efficient chemotherapeutics, rapid diagnosis and necessary biosecurity procedures are required to control the disease. While the diagnostic method of ASF recommended by the World Organization of Animal Health is real-time PCR, the ideal diagnosis procedure including master mix setup, template extraction and a high-cost qPCR equipment for many samples being tested simultaneously is not portable. In this study, a colorimetric loop-mediated isothermal amplification (LAMP) assay was modified and evaluated for ASF virus detection using crude serum samples co... |
Plant-leaf diseases have become a significant threat to food security due to reducing the quantity and quality of agricultural products. Plant disease detection methods are commonly based on experience through manual observations of leaves. Developing fast, accurate, and automated techniques for identifying of crop diseases using computer vision and artificial intelligence (AI) can help overcome human shortcomings. In the current study, the EfficientNet architectures with pre-trained Noisy-Student weights were implemented using the transfer learning approach to classify leaf image-based healthy and diseased plant groups. The deep learning models were performed on the extended and enhanced PlantVillage datasets, consisting of leaf images of 14 different plant species, with background... |
Intramuscular delivery of human adenovirus (HAdV)-based vaccines leads to rapid recruitment of neutrophils, which then release antimicrobial peptides/proteins (AMPs). How these AMPs influence vaccine efficacy over the subsequent 24 h is poorly understood. In this study, we asked if human neutrophil protein 1 (HNP-1), an α-defensin that influences direct and indirect innate immune responses to a range of pathogens, impacts the response of human phagocytes to three HAdV species/types (HAdV-C5, -D26, -B35). We show that HNP-1 binds to the capsids and redirects HAdV-C5, -D26, and -B35 to Toll-like receptor 4 (TLR4), which leads to internalization, an NLRP3-mediated inflammasome response, and interleukin 1 beta (IL-1β) release. Surprisingly, IL-1β release was not associated with notable ... |
Cancer is the leading cause of morbidity and mortality worldwide. Early detection and treatment are crucial for the prevention and control of cancer burden. In recent years, silver nanoparticles (AgNPs) have attracted considerable interest worldwide to develop a new-generation diagnostic and treatment tool for cancer. AgNPs can kill cancer cells, and they have also been hybridized with other materials to enhance the signal for different biosensing platforms. This review highlights recent advances of AgNPs in cancer diagnosis and treatment through up-to-date publications; Cancer is the leading cause of morbidity and mortality worldwide. Early detection and treatment are crucial for the prevention and control of cancer burden. In recent years, silver nanoparticles (AgNPs) have attract... |
Using bio-based fuels in diesel engines is an effective solution to reduce the generation of toxic components in the exhaust gas. One of them, alcohol, is the potential fuel to reduce emissions and dependence on fossil fuels. So, this study is aimed to investigate the effects of ethanol port injection timing and delivery rate on the combustion characteristic of a heavy-duty V-12 diesel engine when ethanol substitution percentage is 30% to reach the original diesel quantity at full load. The combustion characteristic analysis indicates that the variation in cylinder gas pressure and temperature decreases when retarded ethanol injection timing and decreased ethanol delivery rate, the engine works more smoothly due to the maximum rate of pressure rise decreases. However, the changes ar... |
In this paper, we consider a distributed joint sensing and communication (DJSC) system in which each radar sensor as a JSC node is equipped with a sensing function and a communication function. Deploying multiple JSC nodes may require a large amount of bandwidth. Therefore, we investigate the bandwidth allocation problem for the DJSC system. In particular, we aim to optimize the bandwidth allocation to the sensing function and the communication function of the JSC nodes. To improve the allocation efficiency while benefiting the spatial diversity advantage of the DJSC systems, the objective is to maximize the sum of sensing performances, i.e., estimation rates, communication performances, i.e., communication data rates, and fairness of all the users. The optimization problem is non-c... |
The threats of drug resistance and new emerging pathogens have led to an urgent need to develop alternative treatment therapies. Recently, considerable research efforts have focused on membrane-active peptides (MAPs), a category of peptides in drug discovery with antimicrobial, anticancer, and cell penetration activities that have demonstrated their potential to be multifunctional agents. Nonetheless, natural MAPs have encountered various disadvantages, which mainly include poor bioavailability, the lack of a secondary structure in short peptides, and high production costs for long peptide sequences. Hence, an “all-hydrocarbon stapling system” has been applied to these peptides and proven to effectively stabilize the helical conformations, improving proteolytic resistance and increa... |
Since parallel robots are the multibody systems with closed-loop structures, their movement equations usually are in the complex form of redundant coordinates and their dynamics parameters are usually uncertain. The aim of this paper is to improve the control quality for the parallel robot by applying RBF neutron network. Firstly, the movement equations of Rostock Delta robot are established as differential–algebraic systems of equations with redundant generalized coordinates. Then, the stableness of the control method based on sliding mode control law using neural network is proved. Finally, the error in tracking control of a specific Rostock Delta robot is simulated by using this method. |
This work develops a Neural Network (NN) model for the prediction of the tensile modulus of carbon nanotube (CN)/polymer nanocomposites, based on experimental database. A data set composed of 282 configurations is collected from available resources. Considered input variables of the dataset are such as mechanical properties of separated phases, density of polymer matrix, processing method, geometry of CN, modification method at the CN surface, etc. while the problem output is the tensile modulus of nanocomposite. Parametric studies have been performed in finding optimum architecture of the proposed NN model. |
