23 research outputs found
Halo orbit design around Lagrangian points using gradient and non gradient based optimization techniques
No full textIMAGE DENOISING USING OPTIMALLY WEIGHTED BILATERAL FILTERS: A SURE AND FAST APPROACH
No full textThe bilateral filter is known to be quite effective in denoising images corrupted with small dosages of additive Gaussian noise. The denoising performance of the filter, however, is known to degrade quickly with the increase in noise level. Several adaptations of the filter have been proposed in the literature to address this shortcoming, but often at a substantial computational overhead. In this paper, we report a simple pre-processing step that can substantially improve the denoising performance of the bilateral filter, at almost no additional cost. The modified filter is designed to be robust at large noise levels, and often tends to perform poorly below a certain noise threshold. To get the best of the original and the modified filter, we propose to combine them in a weighted fashion, where the weights are chosen to minimize (a surrogate of) the oracle mean-squared-error (MSE). The optimally-weighted filter is thus guaranteed to perform better than either of the component filters in terms of the MSE, at all noise levels. We also provide a fast algorithm for the weighted filtering. Visual and quantitative denoising results on standard test images are reported which demonstrate that the improvement over the original filter is significant both visually and in terms of PSNR. Moreover, the denoising performance of the optimally-weighted bilateral filter is competitive with the computation-intensive non-local means filter
Image denoising using optimally weighted bilateral filters: A sure and fast approach
No full textThe bilateral filter is known to be quite effective in denoising images corrupted with small dosages of additive Gaussian noise. The denoising performance of the filter, however, is known to degrade quickly with the increase in noise level. Several adaptations of the filter have been proposed in the literature to address this shortcoming, but often at a substantial computational overhead. In this paper, we report a simple pre-processing step that can substantially improve the denoising performance of the bilateral filter, at almost no additional cost. The modified filter is designed to be robust at large noise levels, and often tends to perform poorly below a certain noise threshold. To get the best of the original and the modified filter, we propose to combine them in a weighted fashion, where the weights are chosen to minimize (a surrogate of) the oracle mean-squared-error (MSE). The optimally-weighted filter is thus guaranteed to perform better than either of the component filters in terms of the MSE, at all noise levels. We also provide a fast algorithm for the weighted filtering. Visual and quantitative denoising results on standard test images are reported which demonstrate that the improvement over the original filter is significant both visually and in terms of PSNR. Moreover, the denoising performance of the optimally-weighted bilateral filter is competitive with the computation-intensive non-local means filter
Biased signalling in platelet G-protein‐coupled receptors.
No full textPlatelets are small megakaryocyte-derived, anucleate, disk-like structures that play an outsized role in human health and disease. Both a decrease in the number of platelets and a variety of platelet function disorders result in petechiae or bleeding that can be life threatening. Conversely, the inappropriate activation of platelets, within diseased blood vessels, remains the leading cause of death and morbidity by affecting heart attacks and stroke. The fine balance of the platelet state in healthy individuals is controlled by a number of receptor-mediated signaling pathways that allow the platelet to rapidly respond and maintain haemostasis. G-protein coupled receptors (GPCRs) are particularly important regulators of platelet function. Here we focus on the major platelet-expressed GPCRs and discuss the roles of downstream signaling pathways (e.g., different G-protein subtypes or β-arrestin) in regulating the different phases of the platelet activation. Further, we consider the potential for selectively targeting signaling pathways that may contribute to platelet responses in disease through development of biased agonists. Such selective targeting of GPCR-mediated signaling pathways by drugs, often referred to as biased signaling, holds promise in delivering therapeutic interventions that do not present significant side effects, especially in finely balanced physiological systems such as platelet activation in haemostasis.The presentation of the authors' names and (or) special characters in the title of the pdf file of the accepted manuscript may differ slightly from what is displayed on the item page. The information in the pdf file of the accepted manuscript reflects the original submission by the author
Time Series Prediction for Traffic Flow Forecasting Using CNN
No full textTraffic problems are very common nowadays throughout the world. In India also heavy traffic also occurred in many populated cities. For this reason, the public loses their time and life, and this pollution impacts human health. So, traffic research is necessary for this situation. We concentrate on the traffic network to find a better solution or model to predict future traffic. Our proposed model uses a time series for traffic forecasting. It deals with time series analysis for traffic congestion, traffic control, and traffic prediction. This paper focuses on appropriate datasets with different vehicles in various time series. A novel time series forecasting model was used for this research, and it also predicted a 99% accuracy rate. A comparative study is also presented in this research
Performance analysis of IRS-assisted terahertz communication system
No full textIntelligent reflecting surfaces (IRS), a new paradigm for controlling the wireless propagation environment, is an excellent cost-effective technology for terahertz (THz) systems. In this paper, the performance of an IRS-assisted THz system, with N reflective elements, is systematically analyzed over the deterministic IRS channel gain, the THz path loss model, and the sum of independent and non-identically distributed (i.ni.d.) cascaded a-µ fading channels. The probability density function (PDF) and the cumulative distribution function (CDF) of the proposed system are statistically characterized in terms of programmable multi-variate Fox's H function. Using derived statistical results, the closed-form solution for outage probability of THz-IRS system is reported along with its simple asymptotic expansions. The analytical results are validated using Monte-Carlo simulations. Results show that, sufficient signal-to-noise ratio (SNR) can be achieved with enough number of IRS antenna elements, making THz communication feasible.Info-communications Media Development Authority (IMDA)Ministry of Education (MOE)National Research Foundation (NRF)This research is supported by the Ministry of Education, Singapore, under its Academic Research Fund Tier 1, National Research Foundation, Singapore, under its Competitive Research Programme, and the National Research Foundation, Singapore and Infocomm Media Development Authority under its Future Communications Research & Development Programme
Related Data for: Performance Analysis of IRS-assisted Terahertz Communication System
No full textIn this paper, the performance of an IRS-assisted THz system, with N reflective elements, is systematically analyzed over the deterministic IRS channel gain, the THz path loss model, and the sum of independent and non-identically distributed (i.ni.d.) cascaded α−µ fading channels. The probability density function (PDF) and the cumulative distribution function (CDF) of the proposed system are statistically characterized in terms of programmable multi-variate Fox’s H function. Using derived statistical results, the closed-form solution for outage probability of THz-IRS system is reported along with its simple asymptotic expansions. The analytical results are validated using Monte-Carlo simulations. Results show that, sufficient signal-to-noise ratio (SNR) can be achieved with enough number of IRS antenna elements, making THz communication feasible
Human osteoarthritis knee joint synovial fluids cleave and activate Proteinase-Activated Receptor (PAR) mediated signaling
No full textOsteoarthritis (OA) is the most prevalent joint disorder with increasing worldwide incidence. Mechanistic insights into OA pathophysiology are evolving and there are currently no disease-modifying OA drugs. An increase in protease activity is linked to progressive degradation of the cartilage in OA. Proteases also trigger inflammation through a family of G protein-coupled receptors (GPCRs) called the Proteinase-Activated Receptors (PARs). PAR signaling can trigger pro-inflammatory responses and targeting PARs is proposed as a therapeutic approach in OA. Several enzymes can cleave the PAR N-terminus, but the endogenous protease activators of PARs in OA remain unclear. Here we characterized PAR activating enzymes in knee joint synovial fluids from OA patients and healthy donors using genetically encoded PAR biosensor expressing cells. Calcium signaling assays were performed to examine receptor activation. The class and type of enzymes cleaving the PARs was further characterized using protease inhibitors and fluorogenic substrates. We find that PAR1, PAR2 and PAR4 activating enzymes are present in knee joint synovial fluids from healthy controls and OA patients. Compared to healthy controls, PAR1 activating enzymes are elevated in OA synovial fluids while PAR4 activating enzyme levels are decreased. Using enzyme class and type selective inhibitors and fluorogenic substrates we find that multiple PAR activating enzymes are present in OA joint fluids and identify serine proteinases (thrombin and trypsin-like) and matrix metalloproteinases as the major classes of PAR activating enzymes in the OA synovial fluids. Synovial fluid driven increase in calcium signaling was significantly reduced in cells treated with PAR1 and PAR2 antagonists, but not in PAR4 antagonist treated cells. OA associated elevation of PAR1 cleavage suggests that targeting this receptor may be beneficial in the treatment of OA
Structure, function and pathophysiology of protease activated receptors
No full textDiscovered in the 1990s, protease activated receptors(1) (PARs) are membrane-spanning cell surface proteins that belong to the G protein coupled receptor (GPCR) family. A defining feature of these receptors is their irreversible activation by proteases; mainly serine. Proteolytic agonists remove the PAR extracellular amino terminal pro-domain to expose a new amino terminus, or tethered ligand, that binds intramolecularly to induce intracellular signal transduction via a number of molecular pathways that regulate a variety of cellular responses. By these mechanisms PARs function as cell surface sensors of extracellular and cell surface associated proteases, contributing extensively to regulation of homeostasis, as well as to dysfunctional responses required for progression of a number of diseases. This review examines common and distinguishing structural features of PARS, mechanisms of receptor activation, trafficking and signal termination, and discusses the physiological and pathological roles of these receptors and emerging approaches for modulating PAR-mediated signaling in disease. (C) 2011 Elsevier Inc. All rights reserved
