Hardware/software approaches for reducing the process variation impact on instruction fetches

Cataloged from PDF version of article.As technology moves towards finer process geometries, it is becoming extremely difficult to control critical physical parameters such as channel length, gate oxide thickness, and dopant ion concentration. Variations in these parameters lead to dramatic variations in access latencies in Static Random Access Memory (SRAM) devices. This means that different lines of the same cache may have different access latencies. A simple solution to this problem is to adopt the worst-case latency paradigm. While this egalitarian cache management is simple, it may introduce significant performance overhead during instruction fetches when both address translation (instruction Translation Lookaside Buffer (TLB) access) and instruction cache access take place, making this solution infeasible for future high-performance processors. In this study, we first propose some hardware and software enhancements and then, based on those, investigate several techniques to mitigate the effect of process variation on the instruction fetch pipeline stage in modern processors. For address translation, we study an approach that performs the virtual-to-physical page translation once, then stores it in a special register, reusing it as long as the execution remains on the same instruction page. To handle varying access latencies across different instruction cache lines, we annotate the cache access latency of instructions within themselves to give the circuitry a hint about how long to wait for the next instruction to become available

Bayesian inference of accurate population sizes and FRET efficiencies from single diffusing biomolecules.

It is of significant biophysical interest to obtain accurate intramolecular distance information and population sizes from single-molecule Förster resonance energy transfer (smFRET) data obtained from biomolecules in solution. Experimental methods of increasing cost and complexity are being developed to improve the accuracy and precision of data collection. However, the analysis of smFRET data sets currently relies on simplistic, and often arbitrary methods, for the selection and denoising of fluorescent bursts. Although these methods are satisfactory for the analysis of simple, low-noise systems with intermediate FRET efficiencies, they display systematic inaccuracies when applied to more complex systems. We have developed an inference method for the analysis of smFRET data from solution studies based on rigorous model-based Bayesian techniques. We implement a Monte Carlo Markov chain (MCMC) based algorithm that simultaneously estimates population sizes and intramolecular distance information directly from a raw smFRET data set, with no intermediate event selection and denoising steps. Here, we present both our parametric model of the smFRET process and the algorithm developed for data analysis. We test the algorithm using a combination of simulated data sets and data from dual-labeled DNA molecules. We demonstrate that our model-based method systematically outperforms threshold-based techniques in accurately inferring both population sizes and intramolecular distances.This is the final published version. It's also available from ACS in Analytical Chemistry: http://pubs.acs.org/doi/pdf/10.1021/ac501188r

The tetraspanin CD9 controls migration and proliferation of parietal epithelial cells and glomerular disease progression

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Prevalence of alcohol use in Istanbul

The current research assessed the prevalence of alcohol use in istanbul, Turkey along with characteristics and severity of related problems. The data were collected from structured interviews including the CAGE Questionnaire to eliminate the severity of alcohol-related problems of 1,550 residents (743 women, 807 men) of Istanbul, ages 12 to 65 years. Current alcohol use was 25.6% (397 persons, 118 women wand 279 men), including 15.9% of the women and 34.5% of the men. 67% reported never having used alcohol. The rate of alcohol use was highest in the 40- to 49-yr. age group; the onset of use was reported as most common for the 16- to 19-yr.-olds. Prevalence of risky drinking was 6.8% (106 persons). Men were more likely to have an earlier initiation to alcohol use, to consume more [5.2 standard drinks (SD 3.4) vs 3.6 standard drinks (SD=2.5)] and be problem drinkers (31.5% vs 15.2%) than women. Prevalence of alcohol use seems to be relatively low in Istanbul. Data on characteristics of alcohol use are important in estimating groups at risk for problems and in planning prevention strategies

Estrone specific molecularly imprinted polymeric nanospheres: Synthesis, characterization and applications for electrochemical sensor development

The aim of this study is (i) to prepare estrone-imprinted nanospheres (nano-EST-MIPs) and (ii) to integrate them into the electrochemical sensor as a recognition layer. N-methacryloyl-(l)-phenylalanine (MAPA) was chosen as the complexing monomer. Firstly, estrone (EST) was complexed with MAPA and the EST-imprinted poly(2-hyroxyethylmethacrylate-co-N-methacryloyl-(l)- phenylalanine) [EST-imprinted poly(HEMA-MAPA)] nanospheres were synthesized by surfactant-free emulsion polymerization method. The specific surface area of the EST-imprinted poly(HEMA-MAPA) nanospheres was found to be 1275 m2/g with a size of 163.2 nm in diameter. According to the elemental analysis results, the nanospheres contained 95.3 mmole MAPA/g nanosphere. The application of EST specific MIP nanospheres for the development of an electrochemical biosensor was introduced for the first time in our study by using electrochemical impedance spectroscopy (EIS) technique. This nano-MIP based sensor presented a great specificity and selectivity for EST. © 2013 Bentham Science Publishers