GeantV: Results from the prototype of concurrent vector particle transport simulation in HEP

Full detector simulation was among the largest CPU consumer in all CERN experiment software stacks for the first two runs of the Large Hadron Collider (LHC). In the early 2010's, the projections were that simulation demands would scale linearly with luminosity increase, compensated only partially by an increase of computing resources. The extension of fast simulation approaches to more use cases, covering a larger fraction of the simulation budget, is only part of the solution due to intrinsic precision limitations. The remainder corresponds to speeding-up the simulation software by several factors, which is out of reach using simple optimizations on the current code base. In this context, the GeantV R&D project was launched, aiming to redesign the legacy particle transport codes in order to make them benefit from fine-grained parallelism features such as vectorization, but also from increased code and data locality. This paper presents extensively the results and achievements of this R&D, as well as the conclusions and lessons learnt from the beta prototype.Comment: 34 pages, 26 figures, 24 table

Micro-algal lethality potentials of marine organisms collected from the Indian littoral

Microalgal lethality bioassay was developed to detect the toxic profile of organic extract of marine organisms and their possible significance in the context of antifouling activities. Organic extracts of seaweeds, Ulva fasciata and Hypnea musciformis, sponges, Dendrilla nigra, Axinella donnai and Clathria gorgonoides and a holothurian Holothuria scabra were used for the detection of microalgal lethality potential. The microalgae such as Isochrysis galbana, Chlorella salina and Nanochloropsis sp. were used for the assay. The findings revealed that H. scabra contained toxic secondary metabolites, which might have the reason for its potent antifouling activity. Invariably all extracts inhibited the growth of microalgae at various concentrations except H. musciformis and A. donnani, which induce the growth of microalgae to certain extent. Based on the present findings, it could be inferred that the ‘microalgal lethality bioassay’ could be used as a primary screening assay system for the detection of biotoxic and antifouling agents from marine organisms

Targeting tumorigenesis: development and use of mTOR inhibitors in cancer therapy

The mammalian target of rapamycin (mTOR) is an intracellular serine/threonine protein kinase positioned at a central point in a variety of cellular signaling cascades. The established involvement of mTOR activity in the cellular processes that contribute to the development and progression of cancer has identified mTOR as a major link in tumorigenesis. Consequently, inhibitors of mTOR, including temsirolimus, everolimus, and ridaforolimus (formerly deforolimus) have been developed and assessed for their safety and efficacy in patients with cancer. Temsirolimus is an intravenously administered agent approved by the US Food and Drug Administration (FDA) and the European Medicines Agency (EMEA) for the treatment of advanced renal cell carcinoma (RCC). Everolimus is an oral agent that has recently obtained US FDA and EMEA approval for the treatment of advanced RCC after failure of treatment with sunitinib or sorafenib. Ridaforolimus is not yet approved for any indication. The use of mTOR inhibitors, either alone or in combination with other anticancer agents, has the potential to provide anticancer activity in numerous tumor types. Cancer types in which these agents are under evaluation include neuroendocrine tumors, breast cancer, leukemia, lymphoma, hepatocellular carcinoma, gastric cancer, pancreatic cancer, sarcoma, endometrial cancer, and non-small-cell lung cancer. The results of ongoing clinical trials with mTOR inhibitors, as single agents and in combination regimens, will better define their activity in cancer

Challenges in developing a voice input voice output communication aid for people with severe dysarthria

This paper describes the development of a voice-input voice-output communication aid (VIVOCA) for people with disordered or unintelligible speech, initially concentrating on people with severe dysarthria. The VIVOCA is intended to recognize and interpret an individual’s disordered speech and speak out an equivalent message in clear synthesized speech. User consultation suggests that such a device would be acceptable and would be useful in communication situations where speed and intelligibility are crucial. Speech recognition techniques build on previously successful development of speech-based home control interfaces, and various methods for speech ‘translation’ have been evaluated

CF-GeNe: Fuzzy Framework for Robust Gene Regulatory Network Inference

Most Gene Regulatory Network (GRN) studies ignore the impact of the noisy nature of gene expression data despite its significant influence upon inferred results. This paper presents an innovative Collateral-Fuzzy Gene Regulatory Network Reconstruction (CF-GeNe) framework for Gene Regulatory Network (GRN) inference. The approach uses the Collateral Missing Value Estimation (CMVE) algorithm as its core to estimate missing values in microarray gene expression data. CF-GeNe also mimics the inherent fuzzy nature of gene co-regulation by applying fuzzy clustering principles using the well-established fuzzy cmeans algorithm, with the model adapting to the data distribution by automatically determining key parameters, like the number of clusters. Empirical results confirm that the CMVE-based CF-GeNe paradigm infers the majority of co-regulated links even in the presence of large numbers of missing values, compared to other data imputation methods including: Least Square Impute (LSImpute), K-Nearest Neighbour Impute (KNN), Bayesian Principal Component Analysis Impute (BPCA) and ZeroImpute. The statistical significance of this improved performance has been underscored by gene selection and also by applying the Wilcoxon Ranksum Significance Test, with results corroborating the ability of CF-GeNe to successfully infer GRN interactions in noisy gene expression data

Transcriptional Gene Regulatory Network Reconstruction through Cross Platform Gene Network Fusion

Microarray gene expression data is used to model differential activity in Gene Regulatory Networks (GRN) to elucidate complex cellular processes, though network modeling is susceptible to errors due to both noisy nature of gene expression data and platform bias. This intuitively provided the motivation for the development of an innovative technique, which effectively integrates GRN using cross-platform data to minimize the two aforementioned effects. This paper presents a GRN integration (GeNi) framework that fuses cross-platform GRN to remove platform and experimental bias using the Dempster Shafer Theory of Evidence. The proposed model estimates gene co-regulation strength by using mutual information and removes spurious co-regulations through data processing inequality. The method automatically adapts to the data distribution using Belief theory, which does not require a preset threshold to accept co-regulated links. GeNi is applied to identify common cancer-related regulatory links in ten different datasets generated by different microarray platforms including cDNA and Affymetrix arrays. Experimental results demonstrate that GeNi can be effectively applied for GRN reconstruction and cross-platform gene network fusion for any gene expression data

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Not AvailableSponges are closely associated with microorganisms that occur either intracellularly and extracellularly. Sponges are soft-bodied sessile organisms appear to be defenseless in facing predation. Microbial symbionts supposed to have a functional role in the host defense against pathogens, predation and microfouling processes. Recently, the ubiquitous defense enzyme, phospholipase A2 (PLA2) detected in the sponge associated bacterium envisaged the possible functional role in the ecological succession of host sponge against predatory / fouling pressure in the habitat. In present review, we highlighted the possible functional interactions between associated microbes and host sponges and its potentials in bioprospecting approaches.Not Availabl

Sponge-microbial interactions: Ecological implications and bioprospecting avenues

Sponges are closely associated with microorganisms that occur either intracellularly and extracellularly. Sponges are soft-bodied sessile organisms appear to be defenseless in facing predation. Microbial symbionts supposed to have a functional role in the host defense against pathogens, predation and microfouling processes. Recently, the ubiquitous defense enzyme, phospholipase A2 (PLA2) detected in the sponge associated bacterium envisaged the possible functional role in the ecological succession of host sponge against predatory / fouling pressure in the habitat. In present review, we highlighted the possible functional interactions between associated microbes and host sponges and its potentials in bioprospecting approaches