57 resultados para Goloboff, Gerardo Mario


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Embedded many-core architectures contain dozens to hundreds of CPU cores that are connected via a highly scalable NoC interconnect. Our Multiprocessor-System-on-Chip CoreVAMPSoC combines the advantages of tightly coupled bus-based communication with the scalability of NoC approaches by adding a CPU cluster as an additional level of hierarchy. In this work, we analyze different cluster interconnect implementations with 8 to 32 CPUs and compare them in terms of resource requirements and performance to hierarchical NoCs approaches. Using 28nm FD-SOI technology the area requirement for 32 CPUs and AXI crossbar is 5.59mm2 including 23.61% for the interconnect at a clock frequency of 830 MHz. In comparison, a hierarchical MPSoC with 4 CPU cluster and 8 CPUs in each cluster requires only 4.83mm2 including 11.61% for the interconnect. To evaluate the performance, we use a compiler for streaming applications to map programs to the different MPSoC configurations. We use this approach for a design-space exploration to find the most efficient architecture and partitioning for an application.

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Fusing data from multiple sensing modalities, e.g. laser and radar, is a promising approach to achieve resilient perception in challenging environmental conditions. However, this may lead to \emph{catastrophic fusion} in the presence of inconsistent data, i.e. when the sensors do not detect the same target due to distinct attenuation properties. It is often difficult to discriminate consistent from inconsistent data across sensing modalities using local spatial information alone. In this paper we present a novel consistency test based on the log marginal likelihood of a Gaussian process model that evaluates data from range sensors in a relative manner. A new data point is deemed to be consistent if the model statistically improves as a result of its fusion. This approach avoids the need for absolute spatial distance threshold parameters as required by previous work. We report results from object reconstruction with both synthetic and experimental data that demonstrate an improvement in reconstruction quality, particularly in cases where data points are inconsistent yet spatially proximal.

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Introduction The epidemic of nutrition related non-communicable diseases such as type 2 diabetes mellitus and obesity has reached to epidemic portion in the Sri Lanka. However, to date, detailed data on food consumption in the Sri Lankan population is limited. The aim of this study is to identify energy and major nutrient intake among Sri Lankan adults. Methods A nationally-representative sample of adults was selected using a multi-stage random cluster sampling technique. Results Data from 463 participants (166 Males, 297 Females) were analyzed. Total energy intake was significantly higher in males (1913 ± 567 kcal/d) than females (1514 ± 458 kcal/d). However, there was no significant gender differences in the percentage of energy from carbohydrate (Male: 72.8 ± 6.4%, Female: 73.9 ± 6.7%), fat (Male: 19.9 ± 6.1%, Female: 18.5 ± 5.7%) and proteins (Male: 10.6 ± 2.1%, Female: 10.9 ± 5.6%). Conclusion The present study provides the first national estimates of energy and nutrient intake of the Sri Lankan adult population.

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Purpose To investigate if the accuracy of intraocular pressure (IOP) measurements using rebound tonometry over disposable hydrogel (etafilcon A) contact lenses (CL) is affected by the positive power of the CLs. Methods The experimental group comprised 26 subjects, (8 male, 18 female). IOP measurements were undertaken on the subjects’ right eyes in random order using a Rebound Tonometer (ICare). The CLs had powers of +2.00D and +6.00D. Measurements were taken over each contact lens and also before and after the CLs had been worn. Results The IOP measure obtained with both CLs was significantly lower compared to the value without CLs (t test; p<0.001) but no significant difference was found between the two powers of CLs. Conclusions Rebound tonometry over positive hydrogel CLs leads to a certain degree of IOP underestimation. This result didn’t change for the two positive lenses used in the experiment, despite their large difference in power and therefore in lens thickness. Optometrists should bear this in mind when measuring IOP with the rebound tonometer over plus power contact lenses.

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Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P < 5 × 10−8), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for ~2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.

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Waist-hip ratio (WHR) is a measure of body fat distribution and a predictor of metabolic consequences independent of overall adiposity. WHR is heritable, but few genetic variants influencing this trait have been identified. We conducted a meta-analysis of 32 genome-wide association studies for WHR adjusted for body mass index (comprising up to 77,167 participants), following up 16 loci in an additional 29 studies (comprising up to 113,636 subjects). We identified 13 new loci in or near RSPO3, VEGFA, TBX15-WARS2, NFE2L3, GRB14, DNM3-PIGC, ITPR2-SSPN, LY86, HOXC13, ADAMTS9, ZNRF3-KREMEN1, NISCH-STAB1 and CPEB4 (P = 1.9 × 10−9 to P = 1.8 × 10−40) and the known signal at LYPLAL1. Seven of these loci exhibited marked sexual dimorphism, all with a stronger effect on WHR in women than men (P for sex difference = 1.9 × 10−3 to P = 1.2 × 10−13). These findings provide evidence for multiple loci that modulate body fat distribution independent of overall adiposity and reveal strong gene-by-sex interactions.

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Since the late 1990s, the International Contact Lens Prescribing Survey Consortium has prospectively gathered information about 285,000 contact lens fits from more than 50 countries. This article presents our 14th annual summary of current trends published in Contact Lens Spectrum. With only minor differences in the distribution of our surveys among markets, we have continued to adopt the same approach throughout the past 18 years. Through national coordinators, we approach contact lens prescribers in each country and ask them to record information about the first 10 patients whom they fit with contact lenses after receipt of our survey form. The information collected is generic, and respondents are weighted to reflect the volume of contact lens fits undertaken by each. For this 2014 report, we present information about 25,179 contact lens fits from 32 countries...

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We have been collecting data on worldwide contact lens prescribing habits for almost 20 years. Over this time period, we have amassed prospective information about 315,000 contact lens fits in 59 countries. This article marks our 15th report in Contact Lens Spectrum and features a breakdown of more than 23,000 contact lens fits in 34 markets. As in previous years, our international network of coordinators distributed survey forms to eyecare practitioners in their market who then recorded generic information about the first 10 patients fit with contact lenses after receipt. Information is gathered about patient age and gender; whether the contact lenses are prescribed as a new fit or a refit; contact lens material, design, and replacement frequency; number of intended days per week of use; wearing modality; and care system. Contact lens fits are weighted to reflect the number of fits undertaken by each eyecare practitioner. The study data were entered and processed at the University of Manchester and at the University of Waterloo.

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With the development of wearable and mobile computing technology, more and more people start using sleep-tracking tools to collect personal sleep data on a daily basis aiming at understanding and improving their sleep. While sleep quality is influenced by many factors in a person’s lifestyle context, such as exercise, diet and steps walked, existing tools simply visualize sleep data per se on a dashboard rather than analyse those data in combination with contextual factors. Hence many people find it difficult to make sense of their sleep data. In this paper, we present a cloud-based intelligent computing system named SleepExplorer that incorporates sleep domain knowledge and association rule mining for automated analysis on personal sleep data in light of contextual factors. Experiments show that the same contextual factors can play a distinct role in sleep of different people, and SleepExplorer could help users discover factors that are most relevant to their personal sleep.

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Homozygosity has long been associated with rare, often devastating, Mendelian disorders1, and Darwin was one of the first to recognize that inbreeding reduces evolutionary fitness2. However, the effect of the more distant parental relatedness that is common in modern human populations is less well understood. Genomic data now allow us to investigate the effects of homozygosity on traits of public health importance by observing contiguous homozygous segments (runs of homozygosity), which are inferred to be homozygous along their complete length. Given the low levels of genome-wide homozygosity prevalent in most human populations, information is required on very large numbers of people to provide sufficient power3, 4. Here we use runs of homozygosity to study 16 health-related quantitative traits in 354,224 individuals from 102 cohorts, and find statistically significant associations between summed runs of homozygosity and four complex traits: height, forced expiratory lung volume in one second, general cognitive ability and educational attainment (P < 1 × 10−300, 2.1 × 10−6, 2.5 × 10−10 and 1.8 × 10−10, respectively). In each case, increased homozygosity was associated with decreased trait value, equivalent to the offspring of first cousins being 1.2 cm shorter and having 10 months’ less education. Similar effect sizes were found across four continental groups and populations with different degrees of genome-wide homozygosity, providing evidence that homozygosity, rather than confounding, directly contributes to phenotypic variance. Contrary to earlier reports in substantially smaller samples5, 6, no evidence was seen of an influence of genome-wide homozygosity on blood pressure and low density lipoprotein cholesterol, or ten other cardio-metabolic traits. Since directional dominance is predicted for traits under directional evolutionary selection7, this study provides evidence that increased stature and cognitive function have been positively selected in human evolution, whereas many important risk factors for late-onset complex diseases may not have been.

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Network Interfaces (NIs) are used in Multiprocessor System-on-Chips (MPSoCs) to connect CPUs to a packet switched Network-on-Chip. In this work we introduce a new NI architecture for our hierarchical CoreVA-MPSoC. The CoreVA-MPSoC targets streaming applications in embedded systems. The main contribution of this paper is a system-level analysis of different NI configurations, considering both software and hardware costs for NoC communication. Different configurations of the NI are compared using a benchmark suite of 10 streaming applications. The best performing NI configuration shows an average speedup of 20 for a CoreVA-MPSoC with 32 CPUs compared to a single CPU. Furthermore, we present physical implementation results using a 28 nm FD-SOI standard cell technology. A hierarchical MPSoC with 8 CPU clusters and 4 CPUs in each cluster running at 800MHz requires an area of 4.56mm2.

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Parallel programming and effective partitioning of applications for embedded many-core architectures requires optimization algorithms. However, these algorithms have to quickly evaluate thousands of different partitions. We present a fast performance estimator embedded in a parallelizing compiler for streaming applications. The estimator combines a single execution-based simulation and an analytic approach. Experimental results demonstrate that the estimator has a mean error of 2.6% and computes its estimation 2848 times faster compared to a cycle accurate simulator.