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In image processing applications, image denoising is an emerging area that recovers the original image from noisy image, which is essential in the applications like pattern analysis. The main aim of this study is to propose an effective filtering technique with peer groups for effective image restoration processes. Existing bilateral filter has lower performance in smoothing the high curvature and high gradient regions due to nearby input signals are outliers that miss the filter window. In this research paper, a new approach is proposed that includes fuzzy-based approach and similarity function for filtering the mixed noise. In a peer group, the similarity function was adaptive to edge information and local noise level, which was utilised for detecting the similarity among pixels. In addition, a new filtering method modified trilateral filter (MTF) with improved generalised fuzzy peer group (IGFPG) is proposed to remove mixed impulse and adaptive white Gaussian noise from colour images. The modified trilateral filter includes Kikuchi algorithm and loopy belief propagation to solve the inference issues on the basis of passing local message. In this research work, the images were collected from KODAK dataset and a few real time multimedia images like Lena were also used for testing the effectiveness of the proposed methodology. The collected colour images were contaminated with adaptive white Gaussian noise (AWGN) of standard deviation σε[05,20] and impulse noise of probability pε[0.05, 0.20]. The proposed MTF-IGFPG method has the advantages of consider image photometric and geometric similarities. The local structural similarity and narrow spatial window is applied for smoothing the images to effectively preserve the images. From the simulation, the proposed MTF-IGFPG approach attained better performance related to the existing approaches in light of normalised colour difference (NCD), peak signal-to-noise ratio (PSNR), and mean absolute error (MAE). Hence, the proposed approach almost achieved PSNR of 36 dB, which shows 0.2 dB to 2 dB improvement than the existing methods.

The main intent of this paper is to implement the stability-aware energy-efficient clustering protocol in WSN. This paper plans to derive a multi-objective function with the constraints like energy, distance, delay, stability period, and intents to attain the objective by developing a new well-performing meta-heuristic algorithm called Opposition-based Elephant Herding Optimisation (O-EHO). The objective function diminishes the energy consumption of sensor nodes by optimum selection of cluster heads that leads to maintain the energy balance between the normal nodes. In this way, there is a remarkable enhancement in the performance parameters such as throughput, stability period, and network lifetime. It is proved that the network lifetime is enhanced by the stability period and thus it is considered as the most significant parameter. The experimental analysis proves the competitive performance of the proposed model over other heuristic methods.

From early history, builders, manufacturers, and engineers continued to develop composites of wide assortments of materials. Furthermore, chemical upheaval changed the composite development of plastics such as polyvinyl, polystyrene, etc., and reinforcement was reinforced essential to provide strength and rigidity. At present composites finds many applications in every aspects of day to day life. The utilization of raw materials like coal, baggase and agricultural wastes are used in large scales in industries for power generation and food production. The utilization of these fuels causing huge environmental pollution liberating in the form of ashes. These ashes can be utilized in effective way for manufacturing and structural applications with their incorporation in polymer matrix composites. To enhance the mechanical properties and in reducing the manufacturing cost, these industrial wastes plays a major role. The present research work mainly focuses on the influence of Coal Fly Ash (CFA), Silicon Carbide (SiC) and a mixture of CFA & SiC as filler materials on the mechanical behavior of Epoxy Glass fiber composite. Various types of composites are fabricated by manual hand lay-up process with varying weight percentages of the filler materials and epoxy resin as matrix material. The filler materials weight proportions are taken as 5%, 10% and 15%. The prepared composites are cut into tests specimen as per the ASTM standards of mechanical characterization. The mechanical properties of the composites (like Tensile strength (ASTM D3039/D3039M: 2017), Flexural strength (ASTM D790: 2015), Impact strength (ASTM D 229 el: 2019), Interlaminar shear strength (ASTM D2240: 2015), Hardness (ASTM D2240: 2015)) are determined by using corresponding testing machines and it is observed that the properties exhibited by the composites are enhanced with the incorporation of CFA, SiC & mixture of CFA and SiC when compared with the unfilled composites. So, these composites are considered a multifunctional composite material where the individual fillers are used in some applications and the combined proportions are used in different applications. They replace the existing materials that are very high in cost and cause more pollution at the time of manufacturing. These composites give the ability to improve and increase the efficiency, autonomy, and life expectancy of a structure.

Background:Myelodysplastic syndrome (MDS) is a clinically heterogenous disease of hematopoietic stem cells (HSC) characterized by ineffective hematopoiesis, uni/multi-lineage dysplasia and a high tendency to transform into acute myeloid leukemia. Aberrant chromosomal and genetic lesions contribute to MDS pathogenesis which has been associated with chronic activation of the innate immune response and a hyperinflammatory microenvironment (Barryero L, et al.Blood, 2018). Dysfunction of Toll like receptors (TLR) and downstream effectors has been associated with the loss of progenitor function and differentiation of bone marrow (BM) cells in MDS patients. Azacitidine (AZA), a hypomethylating agent (HMA), is the mainstay of therapy for patients with higher-risk MDS (Silverman LR, The Myelodysplastic Syndrome in Cancer Medicine, Editors: R.J. Bast, et al. 2017) and carries an overall response rate (ORR) of 50% in patients with significant effects on hematopoiesis, ranging from improvement in a single lineage to complete restoration of blood counts and transfusion independence with survival benefits (Silverman LR, et al., Leukemia, 1993). The response to AZA is not durable and all patients relapse with worsening bone marrow failure.