5 resultados para Crack pattern

em Duke University


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Timing-related defects are major contributors to test escapes and in-field reliability problems for very-deep submicrometer integrated circuits. Small delay variations induced by crosstalk, process variations, power-supply noise, as well as resistive opens and shorts can potentially cause timing failures in a design, thereby leading to quality and reliability concerns. We present a test-grading technique that uses the method of output deviations for screening small-delay defects (SDDs). A new gate-delay defect probability measure is defined to model delay variations for nanometer technologies. The proposed technique intelligently selects the best set of patterns for SDD detection from an n-detect pattern set generated using timing-unaware automatic test-pattern generation (ATPG). It offers significantly lower computational complexity and excites a larger number of long paths compared to a current generation commercial timing-aware ATPG tool. Our results also show that, for the same pattern count, the selected patterns provide more effective coverage ramp-up than timing-aware ATPG and a recent pattern-selection method for random SDDs potentially caused by resistive shorts, resistive opens, and process variations. © 2010 IEEE.

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While genome-wide gene expression data are generated at an increasing rate, the repertoire of approaches for pattern discovery in these data is still limited. Identifying subtle patterns of interest in large amounts of data (tens of thousands of profiles) associated with a certain level of noise remains a challenge. A microarray time series was recently generated to study the transcriptional program of the mouse segmentation clock, a biological oscillator associated with the periodic formation of the segments of the body axis. A method related to Fourier analysis, the Lomb-Scargle periodogram, was used to detect periodic profiles in the dataset, leading to the identification of a novel set of cyclic genes associated with the segmentation clock. Here, we applied to the same microarray time series dataset four distinct mathematical methods to identify significant patterns in gene expression profiles. These methods are called: Phase consistency, Address reduction, Cyclohedron test and Stable persistence, and are based on different conceptual frameworks that are either hypothesis- or data-driven. Some of the methods, unlike Fourier transforms, are not dependent on the assumption of periodicity of the pattern of interest. Remarkably, these methods identified blindly the expression profiles of known cyclic genes as the most significant patterns in the dataset. Many candidate genes predicted by more than one approach appeared to be true positive cyclic genes and will be of particular interest for future research. In addition, these methods predicted novel candidate cyclic genes that were consistent with previous biological knowledge and experimental validation in mouse embryos. Our results demonstrate the utility of these novel pattern detection strategies, notably for detection of periodic profiles, and suggest that combining several distinct mathematical approaches to analyze microarray datasets is a valuable strategy for identifying genes that exhibit novel, interesting transcriptional patterns.

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Regular landscape patterning arises from spatially-dependent feedbacks, and can undergo catastrophic loss in response to changing landscape drivers. The central Everglades (Florida, USA) historically exhibited regular, linear, flow-parallel orientation of high-elevation sawgrass ridges and low-elevation sloughs that has degraded due to hydrologic modification. In this study, we use a meta-ecosystem approach to model a mechanism for the establishment, persistence, and loss of this landscape. The discharge competence (or self-organizing canal) hypothesis assumes non-linear relationships between peat accretion and water depth, and describes flow-dependent feedbacks of microtopography on water depth. Closed-form model solutions demonstrate that 1) this mechanism can produce spontaneous divergence of local elevation; 2) divergent and homogenous states can exhibit global bi-stability; and 3) feedbacks that produce divergence act anisotropically. Thus, discharge competence and non-linear peat accretion dynamics may explain the establishment, persistence, and loss of landscape pattern, even in the absence of other spatial feedbacks. Our model provides specific, testable predictions that may allow discrimination between the self-organizing canal hypotheses and competing explanations. The potential for global bi-stability suggested by our model suggests that hydrologic restoration may not re-initiate spontaneous pattern establishment, particularly where distinct soil elevation modes have been lost. As a result, we recommend that management efforts should prioritize maintenance of historic hydroperiods in areas of conserved pattern over restoration of hydrologic regimes in degraded regions. This study illustrates the value of simple meta-ecosystem models for investigation of spatial processes.

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The Dietary Approaches to Stop Hypertension (DASH) trial showed that a diet rich in fruits, vegetables, low-fat dairy products with reduced total and saturated fat, cholesterol, and sugar-sweetened products effectively lowers blood pressure in individuals with prehypertension and stage I hypertension. Limited evidence is available on the safety and efficacy of the DASH eating pattern in special patient populations that were excluded from the trial. Caution should be exercised before initiating the DASH diet in patients with chronic kidney disease, chronic liver disease, and those who are prescribed renin-angiotensin-aldosterone system antagonist, but these conditions are not strict contraindications to DASH. Modifications to the DASH diet may be necessary to facilitate its use in patients with chronic heart failure, uncontrolled diabetes mellitus type II, lactose intolerance, and celiac disease. In general, the DASH diet can be adopted by most patient populations and initiated simultaneously with medication therapy and other lifestyle interventions.

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A juvenile cranium of Homunculus patagonicus Ameghino, 1891a from the late Early Miocene of Santa Cruz Province (Argentina) provides the first evidence of developing cranial anatomy for any fossil platyrrhine. The specimen preserves the rostral part of the cranium with deciduous and permanent alveoli and teeth. The dental eruption sequence in the new specimen and a reassessment of eruption patterns in living and fossil platyrrhines suggest that the ancestral platyrrhine pattern of tooth replacement was for the permanent incisors to erupt before M(1), not an accelerated molar eruption (before the incisors) as recently proposed. Two genera and species of Santacrucian monkeys are now generally recognized: H. patagonicus Ameghino, 1891a and Killikaike blakei Tejedor et al., 2006. Taxonomic allocation of Santacrucian monkeys to these species encounters two obstacles: 1) the (now lost) holotype and a recently proposed neotype of H. patagonicus are mandibles from different localities and different geologic members of the Santa Cruz Formation, separated by approximately 0.7 million years, whereas the holotype of K. blakei is a rostral part of a cranium without a mandible; 2) no Santacrucian monkey with associated cranium and mandible has ever been found. Bearing in mind these uncertainties, our examination of the new specimen as well as other cranial specimens of Santacrucian monkeys establishes the overall dental and cranial similarity between the holotype of Killikaike blakei, adult cranial material previously referred to H. patagonicus, and the new juvenile specimen. This leads us to conclude that Killikaike blakei is a junior subjective synonym of H. patagonicus.