Variability-Aware VLSI Design Automation For Nanoscale Technologies

As technology scaling enters the nanometer regime, design of large scale ICs gets more challenging due to shrinking feature sizes and increasing design complexity. Aggressive scaling causes significant degradation in reliability, increased susceptibility to fabrication and environmental randomness and increased dynamic and leakage power dissipation. In this work, we investigate these scaling issues in large scale integrated systems. This dissertation proposes to develop variability-aware design methodologies by proposing design analysis, design-time optimization, post-silicon tunability and runtime-adaptivity based optimization techniques for handling variability. We discuss our research in the area of variability-aware analysis, specifically focusing on the problem of statistical timing analysis. The first technique presents the concept of error budgeting that achieves significant runtime speedups during statistical timing analysis. The second work presents a general framework for non-linear non-Gaussian statistical timing analysis considering correlations. Further, we present our work on design-time optimization schemes that are applicable during physical synthesis. Firstly, we present a buffer insertion technique that considers wire-length uncertainty and proposes algorithms to perform probabilistic buffer insertion. Secondly, we present a stochastic optimization framework based on Monte-Carlo technique considering fabrication variability. This optimization framework can be applied to problems that can be modeled as linear programs without without imposing any assumptions on the nature of the variability. Subsequently, we present our work on post-silicon tunability based design optimization. This work presents a design management framework that can be used to balance the effort spent on pre-silicon (through gate sizing) and post-silicon optimization (through tunable clock-tree buffers) while maximizing the yield gains. Lastly, we present our work on variability-aware runtime optimization techniques. We look at the problem of runtime supply voltage scaling for dynamic power optimization, and propose a framework to consider the impact of variability on the reliability of such designs. We propose a probabilistic design synthesis technique where reliability of the design is a primary optimization metric

Efficacy of hydro-methanolic extract of Neolamarckia cadamba bark over hematological & biochemical parameters of Wistar albino rats and against microorganisms

263-268Activity of the hydro-methanolic (HM) extract of Neolamarckia cadamba bark was studied over hematological and biochemical parameters of Wistar albino rats as well as its antimicrobial potential was tested against certain bacterial (Gram positive: S. aureus & B. subtilis, Gram negative: E. coli & P. aeruginosa) and fungal strains (A. niger & C. albicans). Efficacy of HM extract of N. cadamba bark over hematological and biochemical parameters was carried out using four groups containing six Wistar albino rats: Gp-I as control (without fed), Gp-II, Gp-III and Gp-IV were orally fed with HM extract of N. cadamba bark with different concentrations of 125 mg/Kg, 250 mg/Kg and 500 mg/Kg bwt, respectively. Study revealed significant increase (p<0.01) in level of red blood cells (RBC), haemoglobin (Hb), total leukocyte count (TLC) and packed cell volume (PCV) of Gp-II, III and IV when compared to control (Gp-I). Dose dependent progression in hematological indices values was observed. TLC values of animals of Gp-IV were found to be more increased in comparison with other hematological values of animals of other groups. Dose dependent significant decrease (p<0.01) in glucose and total cholesterol value of treated groups was found with respect to control. Concentration of two liver enzymes ALT/SGPT (alanine amino transferase), AST/SGOT (aspartate amino transferase) and amount of albumin, urea, creatinine and bilirubin of treated groups was not significantly different from control. Study suggested significant (p<0.01) antimicrobial activity towards C. albicans, A. niger, E. coli, P. aeruginosa, B. subtilis & S. aureus. Study revealed the synergistic efficacy of phytochemicals present in hydro-methanolic extract of N. cadamba bark for health benefits

sCrop: A Novel Device for Sustainable Automatic Disease Prediction, Crop Selection, and Irrigation in Internet-of-Agro-Things for Smart Agriculture

Accepted Manuscript version of an article introducing the innovative idea of the Internet-of-Agro-Things (IoAT) with an explanation of the automatic detection of plant disease for the development of Agriculture Cyber-Physical System (ACPS). An accuracy of 99.24% is achieved by the proposed plant disease prediction framework

Immunosuppressive and anti-cancer potential of aqueous extract of Solanum Xanthocarpum

451-457In this study whole plant aqueous extract of Solanum Xanthocarpum (HAESX) was investigated to assess its effect on humoral immune response along with interleukin-2 (IL-2) production and its expression in Wistar albino rats splenocytes culture. Anticancer potential of HAESX was investigated using rat lever hepatoma (N1S1 cancerous cell line). The effect of HAESX over humoral immune response was studied using four groups of five animals each (Group-I as control, Group -II orally fed with 125 mg/kg body weight, Group -III orally fed with 250 mg/kg body weight and Group -IV orally fed with 500 mg/kg body weight of HAESX). Quantification of IL-2 was done by sandwich ELISA and its expression was detected by the real time PCR. SRB assay (Sulforhodamine B) was done for detecting the effect of HAESX on N1S1 cell line. Dose dependent decrease in antibody titer was observed and production of IL-2 was also decreased significantly. Suppression of IL-2 production at 250 µg/mL and 500 µg/mL dose was also confirmed by the Real time PCR. Relative fold change in the expression of IL-2 gene was 592.22 and 10.77 at 250, 500 μg/mL HAESX concentrations respectively with respect to control. Dose dependent suppression of percent growth of N1S1 cells with increasing concentrations (10, 20, 40 and 80 µg/mL) of HAESX was found. It was concluded that S. xanthocarpum have the immunosuppressive, and anti cancer activity that can be further explore in treatment of various inflammatory and autoimmune disease

Immunosuppressive and anti-cancer potential of aqueous extract of Solanum Xanthocarpum

In this study whole plant aqueous extract of Solanum Xanthocarpum (HAESX) was investigated to assess its effect on humoral immune response along with interleukin-2 (IL-2) production and its expression in Wistar albino rats splenocytes culture. Anticancer potential of HAESX was investigated using rat lever hepatoma (N1S1 cancerous cell line). The effect of HAESX over humoral immune response was studied using four groups of five animals each (Group-I as control, Group -II orally fed with 125 mg/kg body weight, Group -III orally fed with 250 mg/kg body weight and Group -IV orally fed with 500 mg/kg body weight of HAESX). Quantification of IL-2 was done by sandwich ELISA and its expression was detected by the real time PCR. SRB assay (Sulforhodamine B) was done for detecting the effect of HAESX on N1S1 cell line. Dose dependent decrease in antibody titer was observed and production of IL-2 was also decreased significantly. Suppression of IL-2 production at 250 µg/mL and 500 µg/mL dose was also confirmed by the Real time PCR. Relative fold change in the expression of IL-2 gene was 592.22 and 10.77 at 250, 500 μg/mL HAESX concentrations respectively with respect to control. Dose dependent suppression of percent growth of N1S1 cells with increasing concentrations (10, 20, 40 and 80 µg/mL) of HAESX was found. It was concluded that S. xanthocarpum have the immunosuppressive, and anti cancer activity that can be further explore in treatment of various inflammatory and autoimmune disease

Yield estimation of a memristive sensor array

This paper proposes a method to calculate the yield of a memristor based sensor array considered as the probability that the chip provides acceptable sensing results when the array is affected by manufacturing defects. The modeling is based on a Markov Chain approach, in which each state represents an operating chip configuration and the state transitions take into account manufacturing defects. The proposed method is applicable to evaluate the yield with different fault models to achieve the comparative yield obtained by several redundancy allocations

Detection of anti-Mycobacterium avium subspecies paratuberculosis antibodies in thyroid and type-1 diabetes patients

49-52Mycobacterium avium subspecies paratuberculosis (MAP) causes granulomatous intestinal disease in animals (Johne’s diseases). MAP has also been associated with several autoimmune disorders. In this study, we screened serum samples from confirmed patients of thyroid and type 1 diabetes for the presence of antibody against MAP. We used newly developed 'cocktail ELISA' (based on recombinant secretary proteins) and extensively validated 'indigenous ELISA' (based on whole cell protoplasmic antigen) and both the tests were also compared for their diagnostic potential. A total of 90 serums samples were included of which anti-MAP antibodies was detected in 28.8% and 26.6% of samples by indigenous ELISA (iELISA) and cocktail ELISA (cELISA), respectively. There was almost perfect agreement between the two tests in detecting the anti-MAP antibodies. Study raises concern on high detection of anti-MAP antibodies in human, thus warranting necessary control measure to minimize MAP exposure in human beings

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages