KAPow: A System Identification Approach to Online Per-Module Power Estimation in FPGA Designs

In a modern FPGA system-on-chip design, it is often insufficient to simply assess the total power consumption of the entire circuit by design-time estimation or runtime power rail measurement. Instead, to make better runtime decisions, it is desirable to understand the power consumed by each individual module in the system. In this work, we combine boardlevel power measurements with register-level activity counting to build an online model that produces a breakdown of power consumption within the design. Online model refinement avoids the need for a time-consuming characterisation stage and also allows the model to track long-term changes to operating conditions. Our flow is named KAPow, a (loose) acronym for ‘K’ounting Activity for Power estimation, which we show to be accurate, with per-module power estimates as close to ±5mW of true measurements, and to have low overheads. We also demonstrate an application example in which a permodule power breakdown can be used to determine an efficient mapping of tasks to modules and reduce system-wide power consumption by over 8%

Necrotizing meningoencephalitis in atypical dog breeds: a case series and literature review.

BackgroundCanine necrotizing meningoencephalitis (NME) is a fatal, noninfectious inflammatory disease of unknown etiology. NME has been reported only in a small number of dog breeds, which has led to the presumption that it is a breed-restricted disorder.Hypothesis/objectivesOur objective was to describe histopathologically confirmed NME in dog breeds in which the condition has not been reported previously and to provide preliminary evidence that NME affects a wider spectrum of dog breeds than previously reported.AnimalsFour dogs with NME.MethodsArchives from 3 institutions and from 1 author's (BS) collection were reviewed to identify histopathologically confirmed cases of NME in breeds in which the disease has not been reported previously. Age, sex, breed, survival from onset of clinical signs, and histopathologic findings were evaluated.ResultsNecrotizing meningoencephalitis was identified in 4 small dog breeds (Papillon, Shih Tzu, Coton de Tulear, and Brussels Griffon). Median age at clinical evaluation was 2.5 years. Histopathologic abnormalities included 2 or more of the following: lymphoplasmacytic or histiocytic meningoencephalitis or encephalitis, moderate-to-severe cerebrocortical necrosis, variable involvement of other anatomic locations within the brain (cerebellum, brainstem), and absence of detectable infectious agents.Conclusions and clinical importanceUntil now, NME has only been described in 5 small dog breeds. We document an additional 4 small breeds previously not shown to develop NME. Our cases further illustrate that NME is not a breed-restricted disorder and should be considered in the differential diagnosis for dogs with signalment and clinical signs consistent with inflammatory brain disease

KAPow: high-accuracy, low-overhead online per-module power estimation for FPGA designs

In an FPGA system-on-chip design, it is often insufficient to merely assess the power consumption of the entire circuit by compile-time estimation or runtime power measurement. Instead, to make better decisions, one must understand the power consumed by each module in the system. In this work, we combine measurements of register-level switching activity and system-level power to build an adaptive online model that produces live breakdowns of power consumption within the design. Online model refinement avoids time-consuming characterisation while also allowing the model to track long-term operating condition changes. Central to our method is an automated flow that selects signals predicted to be indicative of high power consumption, instrumenting them for monitoring. We named this technique KAPow, for 'K'ounting Activity for Power estimation, which we show to be accurate and to have low overheads across a range of representative benchmarks. We also propose a strategy allowing for the identification and subsequent elimination of counters found to be of low significance at runtime, reducing algorithmic complexity without sacrificing significant accuracy. Finally, we demonstrate an application example in which a module-level power breakdown can be used to determine an efficient mapping of tasks to modules and reduce system-wide power consumption by up to 7%

Young people and political action: who is taking responsibility for positive social change?

A human rights perspective suggests that we are all responsible for ensuring the human rights of others, which in turn ensures that our own human rights are respected and protected. A convenience sample of 108 young people (41 males and 67 females) aged between 16 and 25 completed a questionnaire which asked about (a) levels of involvement in political activity and (b) sense of personal responsibility for ensuring that the human rights of marginalised groups (e.g. ethnic minorities, immigrants, lesbians and gay men) are protected. Findings showed that most respondents supported (in principle) the notion of human rights for all, but tended to engage in low key political activity (e.g. signing petitions; donating money or goods to charity) rather than actively working towards positive social change. Qualitative data collected in the questionnaire suggested three main barriers to respondents viewing themselves as agents of positive social change: (1) "It’s not my problem", (2) "It’s not my responsibility", and (3) a sense of helplessness. Suggestions for how political action might best be mobilised among young people are also discussed.</p

Soluble fms-Like Tyrosine Kinase 1 (sFlt1), Endoglin and Placental Growth Factor (PlGF) in Preeclampsia among High Risk Pregnancies

Background: Differences in circulating concentrations of antiangiogenic factors sFlt1 and soluble endoglin (sEng) and the pro-angiogenic growth factor PlGF are reported to precede the onset of preeclampsia weeks to months in low-risk pregnant women. The objective of this study was to investigate whether similar changes can be detected in pregnant women at high-risk to develop the syndrome. Methods: This study is a secondary analysis of the NICHD MFMU trial of aspirin to prevent preeclampsia in high-risk pregnancies. Serum samples were available from 194 women with pre-existing diabetes, 313 with chronic hypertension, 234 with multifetal gestation, and 252 with a history of preeclampsia in a previous pregnancy. Samples collected across pregnancy were analyzed in a blinded fashion for sFlt1, sEng and PlGF. Results: The odds of developing preeclampsia were significantly increased among women with multiple fetuses for each 2- fold elevation in sFlt1, sEng and the ratio of angiogenic factors (e.g. OR 2.18, 95% CI 1.46-3.32), and significantly decreased for each 2-fold elevation in circulating PlGF (OR 0.50, 95% CI 0.30-0.82) between 7 and 26 weeks' gestation. Cross-sectional analysis of the angiogenic factors across gestation showed significant differences during the third trimester in women who develop preeclampsia compared with appropriate controls in all high-risk groups. However, when data were examined in relation to the gestational week when preeclampsia was diagnosed only sFlt1 was significantly higher 2 to 5 weeks before the clinical onset of preeclampsia and only in women with previous preeclampsia. Conclusions: The pattern of elevated concentrations of sFlt1 and sEng, and low PlGF in high-risk pregnant subjects who develop preeclampsia is similar to that reported in low-risk pregnant women. However, differences in these factors among high-risk women who do and do not develop preeclampsia are modest, and do not appear to be clinically useful predictors in these high-risk pregnant women

Voltage, throughput, power, reliability, and multicore scaling

This article studies the interplay between the performance, energy, and reliability (PER) of parallel-computing systems. It describes methods supporting the meaningful cross-platform analysis of this interplay. These methods lead to the PER software tool, which helps designers analyze, compare, and explore these properties

Regulatory control and the costs and benefits of biochemical noise

Experiments in recent years have vividly demonstrated that gene expression can be highly stochastic. How protein concentration fluctuations affect the growth rate of a population of cells, is, however, a wide open question. We present a mathematical model that makes it possible to quantify the effect of protein concentration fluctuations on the growth rate of a population of genetically identical cells. The model predicts that the population's growth rate depends on how the growth rate of a single cell varies with protein concentration, the variance of the protein concentration fluctuations, and the correlation time of these fluctuations. The model also predicts that when the average concentration of a protein is close to the value that maximizes the growth rate, fluctuations in its concentration always reduce the growth rate. However, when the average protein concentration deviates sufficiently from the optimal level, fluctuations can enhance the growth rate of the population, even when the growth rate of a cell depends linearly on the protein concentration. The model also shows that the ensemble or population average of a quantity, such as the average protein expression level or its variance, is in general not equal to its time average as obtained from tracing a single cell and its descendants. We apply our model to perform a cost-benefit analysis of gene regulatory control. Our analysis predicts that the optimal expression level of a gene regulatory protein is determined by the trade-off between the cost of synthesizing the regulatory protein and the benefit of minimizing the fluctuations in the expression of its target gene. We discuss possible experiments that could test our predictions.Comment: Revised manuscript;35 pages, 4 figures, REVTeX4; to appear in PLoS Computational Biolog

Soil Moisture and Fungi Affect Seed Survival in California Grassland Annual Plants

Survival of seeds in the seed bank is important for the population dynamics of many plant species, yet the environmental factors that control seed survival at a landscape level remain poorly understood. These factors may include soil moisture, vegetation cover, soil type, and soil pathogens. Because many soil fungi respond to moisture and host species, fungi may mediate environmental drivers of seed survival. Here, I measure patterns of seed survival in California annual grassland plants across 15 species in three experiments. First, I surveyed seed survival for eight species at 18 grasslands and coastal sage scrub sites ranging across coastal and inland Santa Barbara County, California. Species differed in seed survival, and soil moisture and geographic location had the strongest influence on survival. Grasslands had higher survival than coastal sage scrub sites for some species. Second, I used a fungicide addition and exotic grass thatch removal experiment in the field to tease apart the relative impact of fungi, thatch, and their interaction in an invaded grassland. Seed survival was lower in the winter (wet season) than in the summer (dry season), but fungicide improved winter survival. Seed survival varied between species but did not depend on thatch. Third, I manipulated water and fungicide in the laboratory to directly examine the relationship between water, fungi, and survival. Seed survival declined from dry to single watered to continuously watered treatments. Fungicide slightly improved seed survival when seeds were watered once but not continually. Together, these experiments demonstrate an important role of soil moisture, potentially mediated by fungal pathogens, in driving seed survival

Bystander responses to a violent incident in an immersive virtual environment

Under what conditions will a bystander intervene to try to stop a violent attack by one person on another? It is generally believed that the greater the size of the crowd of bystanders, the less the chance that any of them will intervene. A complementary model is that social identity is critical as an explanatory variable. For example, when the bystander shares common social identity with the victim the probability of intervention is enhanced, other things being equal. However, it is generally not possible to study such hypotheses experimentally for practical and ethical reasons. Here we show that an experiment that depicts a violent incident at life-size in immersive virtual reality lends support to the social identity explanation. 40 male supporters of Arsenal Football Club in England were recruited for a two-factor between-groups experiment: the victim was either an Arsenal supporter or not (in-group/out-group), and looked towards the participant for help or not during the confrontation. The response variables were the numbers of verbal and physical interventions by the participant during the violent argument. The number of physical interventions had a significantly greater mean in the ingroup condition compared to the out-group. The more that participants perceived that the Victim was looking to them for help the greater the number of interventions in the in-group but not in the out-group. These results are supported by standard statistical analysis of variance, with more detailed findings obtained by a symbolic regression procedure based on genetic programming. Verbal interventions made during their experience, and analysis of post-experiment interview data suggest that in-group members were more prone to confrontational intervention compared to the out-group who were more prone to make statements to try to diffuse the situation