53 research outputs found
Dengue viruses and promising envelope protein domain III-based vaccines
Get PDFAbstract
Dengue viruses are emerging mosquito-borne pathogens belonging to Flaviviridae family which are transmitted to humans via the bites of infected mosquitoes Aedes aegypti and Aedes albopictus. Because of the wide distribution of these mosquito vectors, more than 2.5 billion people are approximately at risk of dengue infection. Dengue viruses cause dengue fever and severe life-threatening illnesses as well as dengue hemorrhagic fever and dengue shock syndrome. All four serotypes of dengue virus can cause dengue diseases, but the manifestations are nearly different depending on type of the virus in consequent infections. Infection by any serotype creates life-long immunity against the corresponding serotype and temporary immunity to the others. This transient immunity declines after a while (6 months to 2 years) and is not protective against other serotypes, even may enhance the severity of a secondary heterotypic infection with a different serotype through a phenomenon known as antibody-depended enhancement (ADE). Although, it can be one of the possible explanations for more severe dengue diseases in individuals infected with a different serotype after primary infection. The envelope protein (E protein) of dengue virus is responsible for a wide range of biological activities, including binding to host cell receptors and fusion to and entry into host cells. The E protein, and especially its domain III (EDIII), stimulates host immunity responses by inducing protective and neutralizing antibodies. Therefore, the dengue E protein is an important antigen for vaccine development and diagnostic purposes. Here, we have provided a comprehensive review of dengue disease, vaccine design challenges, and various approaches in dengue vaccine development with emphasizing on newly developed envelope domain III-based dengue vaccine candidates.
Keywords:
Dengue virus Envelope protein Chimeric vaccine Disease Immunogenicit
All-optical generation of antiferromagnetic magnon currents via the magnon circular photogalvanic effect
Get PDFWe introduce the magnon circular photogalvanic effect enabled by two-magnon Raman scattering. This provides an all-optical pathway to the generation of directed magnon currents with circularly polarized light in honeycomb antiferromagnetic insulators. The effect is the leading order contribution to magnon photocurrent generation via optical fields. Control of the magnon current by the polarization and angle of incidence of the laser is demonstrated. Experimental detection by sizable inverse spin Hall voltages in platinum contacts is proposed
Direct optical probe of magnon topology in two-dimensional quantum magnets
Get PDFControlling edge states of topological magnon insulators is a promising route to stable spintronics devices. However, to experimentally ascertain the topology of magnon bands is a challenging task. Here we derive a fundamental relation between the light-matter coupling and the quantum geometry of magnon states. This allows to establish the two-magnon Raman circular dichroism as an optical probe of magnon topology in honeycomb magnets, in particular of the Chern number and the topological gap. Our results pave the way for interfacing light and topological magnons in functional quantum devices
Equilibrium Studies in Adsorption of Hg(II) from Aqueous Solutions using Biocompatible Polymeric Polypyrrole-Chitosan Nanocomposite
Full text linkStacking Ensemble-Based Machine Learning Model for Predicting Deterioration Components of Steel W-Section Beams
No full textThe collapse evaluation of the structural systems under seismic loading necessitates identifying and quantifying deterioration components (DCs). In the case of steel w-section beams (SWSB), three distinct types of DCs have been derived. These deterioration components for steel beams comprise the following: pre-capping plastic rotation (θp), post-capping plastic rotation (θpc), and cumulative rotation capacity (Λ). The primary objective of this research is to employ a machine learning (ML) model for accurate determination of these deterioration components. The stacking model is a powerful combination of meta-learners, which is used for better learning and performance of base learners. The base learners consist of AdaBoost, Random Forest (RF), and XGBoost. Among various machine learning algorithms, the stacking model exhibited superior functioning. The evaluation metrics of the stacking model were as follows: R2 = 0.9 and RMSE = 0.003 for θp, R2 = 0.97 and RMSE = 0.012 for θpc, and R2 = 0.98 and RMSE = 0.09 for Λ. The significance of input variables, specifically the web-depth-over-web-thickness ratio (h/tw) and the flange width-to-thickness ratio (bf/2tf), in determining the deterioration components was assessed using the Shapley Additive Explanations model. These parameters emerged as the most crucial factors in the evaluation
Evaluation of COD removal by biologically GSBR from photocatalytically pre-treated oilfield produced water
Full text linkPreparation, Characterization and Photocatalytic Properties of Visible-Light-Driven CuO/SnO2/TiO2 Photocatalyst
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SEISMIC PERFORMANCE ASSESSMENT OF ISOLATED STEEL MOMENT FRAMES WITH LOSS APPROACH
No full textEarthquakes pose inevitable damage and loss of life in structures. Seismic isolation has proven to be an effective method to reduce the seismic vibration and mitigate seismic losses and damage costs. The isolator drastically reduces the main frequency of the structure and subsequently lowers the acceleration of the floors. While this flexible layer protects the building from destruction,
it undergoes a relatively large displacement demand. Isolated structures as well as fixed structures could suffer from inelastic deformation and serious damage under intense seismic ground motions. Performance-based seismic design (PBSD) is a concept that permits the design of buildings with reliable understanding of the risk of life, occupancy, and economic loss that may occur as a result of future earthquakes. Also, Seismic loss estimation method combines seismic hazard, structural response, damage fragility, and damage consequences of allowing quantification of seismic risk based on seismic performance of a building is expressed as the probable damage and resulting consequences of a building's response to earthquake shaking. Nonlinear 4-story archetypes of conventional special moment resisting frame and isolated intermediate moment resisting frame were compared with each other under Far-Field and Near-Field ground motions. Detailed three-dimensional (3D) numerical models of the structures were developed in OpenSees software and Performance Assessment Calculation Tool (PACT) was used for the loss estimation of archetypes. The decision variables in this study were defined as expected annualized repair cost or financial losses (EAL) and expected annualized fatalities (EAF). The analysis results showed that seismic isolation reduces collapse probability, EAL and EAF in superstructures significantly and can be cost effective in mitigating seismic risk. Seismic isolation reduces EAL by 72\% and 67\% under Far-Field and Near-Field ground motions, respectively. Furthermore the result of this study showing that the effectivity of isolation system decreases in Near-Field compared with Far-Field ground motions. The economic feasibility studies showed that if isolation system is used, pay-back period times are around 14 and 18 years under Far-Field and Near-Field ground motions, respectively. The benefit of loss estimation approach is an improved method to assess the effectiveness of isolation system in terms of loss estimation
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