Mohit Kumar

Abstract Individual cells in a tumour can be distributed among Epithelial (E) and Mesenchymal (M) cell-states, as characterised by the levels of canonical E and M markers.

Audio Presented by Credibility Happy Learning ✨✨ Cache memory serves as a vital component within a computer system, acting as a secure repository for recent instructions and data.

Tamil culture, with its rich tapestry of traditions, rituals, and deep-rooted beliefs, holds the cow in high esteem as a sacred and integral part of its heritage. From religious ceremonies…

To stay afloat in this highly volatile market, exploration and productions (E&P) companies rely on high cash flow by reducing their Capex (capital expenditures) and Opex (operational expenditures), which directly strains oilfield services and equipment (OFSE) companies. The reduction is significant in drilling new wells, aggravating the oil market's volatility by reducing the oil supply and decreasing hydrocarbon availability. However, because OFSE and E&P companies both depend on the technical expertise of OFSEs for their project success, they must work toward creating value, not claiming the values. E&P and OFSE must understand the entire value chain and develop modified commercial models that are win-win for both.

Abstract Elucidating the emergent dynamics of complex regulatory networks enabling cellular differentiation is crucial to understand embryonic

Abstract Aim: To assess the functional relevance of a putative Major Facilitator Superfamily (MFS) protein (PF3D7_0210300; PfMFS_DT) as a

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In today's rapidly evolving world, every industry is constantly seeking innovative ways to improve performance and drive efficiency. The oil and gas industry is following the same path. Due to the extremely volatile nature of oil prices, sustainable performance is the need of the hour. In the era of data, the oil and gas sector has been presented with a groundbreaking opportunity to revolutionize its operations.

Epigenetic alterations that lead to differential expression of microRNAs (miRNAs/miR) are known to regulate tumour cell states, epithelial–mesenchymal transition (EMT) and the progression to metastasis in breast cancer. This study explores the key contribution of miRNA-18a in mediating a hybrid E/M cell state that is pivotal to the malignant transformation and tumour progression in the aggressive ER-negative subtype of breast cancer. The expression status and associated effects of miR-18a were evaluated in patient-derived breast tumour samples in combination with gene expression data from public datasets, and further validated in in vitro and in vivo breast cancer model systems. The clinical relevance of the study findings was corroborated against human breast tumour specimens (n = 446 patients). The down-regulated expression of miR-18a observed in ER-negative tumours was found to drive the enrichment of hybrid epithelial/mesenchymal (E/M) cells with luminal attributes, enhanced traits of migration, stemness, drug-resistance and immunosuppression. Further analysis of the miR-18a targets highlighted possible hypoxia-inducible factor 1-alpha (HIF-1α)-mediated signalling in these tumours. This is a foremost report that validates the dual role of miR-18a in breast cancer that is subtype-specific based on hormone receptor expression. The study also features a novel association of low miR-18a levels and subsequent enrichment of hybrid E/M cells, increased migration and stemness in a subgroup of ER-negative tumours that may be attributed to HIF-1α mediated signalling. The results highlight the possibility of stratifying the ER-negative disease into clinically relevant groups by analysing miRNA signatures.

The need for intelligence in today’s era has tremendously increased the demand for Internet of Things (IoT) devices implanted to collect and process diverse data. Cloud computing offers a plethora of services to computationally constrained internet of things devices, but latency degrades the performance of real-time applications. A few other computing paradigms have been developed through the years to overcome this limitation of IoT devices. Fog computing, one of these paradigms, comes into picture as a backbone and offers services to applications which are required to be processed within a deadline. However, addressing challenges such as heterogeneity, offloading mechanisms, resource allocation, and complexity is crucial. This paper presents a framework for intelligent offloading mechanisms and an efficient resource allocation that results in improving the quality of service (QoS) parameters in an integrated cloud-fog-IoT environment. The proposed Fuzzy based Harris Hawks -Genetic Algorithm (HHGA) applies fuzzy-based logic to offload tasks to respective paradigms (cloud or fog), where the upcoming IoT request will be executed. In addition, the Fuzzy-based HHGA algorithm is developed by combining conventional Harris Hawks Optimization (HHO) and Genetic Algorithm (GA) to improve the exploration and exploitation. The proposed algorithm is eventually integrated with the present framework to search for the optimal resources for upcoming requests and reduce the service cost, time, and energy consumption. The experiments are conducted and consecutively the performance of the proposed framework is evaluated. The results demonstrate that the proposed algorithm outperforms Harris Hawks Optimization by 16.95%, Genetic Algorithm by 38.23% and Particle Swarm Optimization (PSO) by 23.09%.