Choose-Your-Own Adventure: A Lightweight, High-Performance Approach To Defect And Variation Mitigation In Reconfigurable Logic

For field-programmable gate arrays (FPGAs), fine-grained pre-computed alternative configurations, combined with simple test-based selection, produce limited per-chip specialization to counter yield loss, increased delay, and increased energy costs that come from fabrication defects and variation. This lightweight approach achieves much of the benefit of knowledge-based full specialization while reducing to practical, palatable levels the computational, testing, and load-time costs that obstruct the application of the knowledge-based approach. In practice this may more than double the power-limited computational capabilities of dies fabricated with 22nm technologies. Contributions of this work: • Choose-Your-own-Adventure (CYA), a novel, lightweight, scalable methodology to achieve defect and variation mitigation • Implementation of CYA, including preparatory components (generation of diverse alternative paths) and FPGA load-time components • Detailed performance characterization of CYA – Comparison to conventional loading and dynamic frequency and voltage scaling (DFVS) – Limit studies to characterize the quality of the CYA implementation and identify potential areas for further optimizatio

Travel time moments for sorbing solutes in heterogeneous domains under nonuniform flow conditions

 A methodology for evaluating the unconditional and conditional moments of travel time for a sorbing solute is presented. The approach is applicable for any flow configuration and for a wide range of mass transfer rate‐limited linear processes. The methodology is applicable to the general case of spatially variable hydrological and chemical parameters. The sorption model used to derive the temporal moments is that of a continuous distribution of mass rate coefficients [Haggerty and Gorelick, 1998]. Models such as instantaneous equilibrium, first‐order and two‐site sorption kinetics, among others, can be considered as particular cases of this general model. Using a deterministic approach, the low‐order moments of the breakthrough curves for reactive solutes can be obtained as a function of those for conservative tracers. Using a stochastic approach, the unconditional low‐order statistics of the travel time moments can be obtained. These moments depend on the statistics of two Lagrangian functions, the travel time for a conservative solute, and an integral of the variations of the chemical parameters weighted by the inverse local velocity along the trajectory. Finally, conditional temporal moments are derived. Moments can be conditioned to any type of information, hard or soft, hydraulic or geochemical. Conditioning is found to reduce uncertainty, characterized by a reduction in the variance of the travel time. The general results are particularized for both uniform in the mean and convergent flow conditions and for simple sorption models such as linear instantaneous equilibrium and first‐order kinetics. In all such cases, close‐form results, based on small perturbations expansions, are presented for the travel time moments

Conditional moments of the breakthrough curves of kinetically sorbing solute in heterogeneous porous media using multirate mass transfer models for sorption and desorption

A methodology is presented for evaluating the temporal moments of solutes undergoing linear rate‐limited mass transfer processes based on a Lagrangian approach to solute transport in heterogeneous media. The temporal moments of sorbing solutes are written as a function of those of conservative tracers. The general continuous diffusion rate model that has recently appeared in the hydrologic literature is used to model the rate‐limited mass transfer processes. The methodology is also applied to desorption from an initially uniformly contaminated aquifer, and the concentration expected value and variance are found quasi‐analytically. The conditional temporal moments of sorbing solutes can be written as a function of the conditional moments of conservative tracers. Conditioning results in a reduction of the variance of travel time. The amount of reduction depends on the chemical model selecte

Mapping the Volumetric Soil Water Content of a California Vineyard Using High-Frequency GPR Ground Wave Data

An attempt was made to establish the utility of ground-penetrating radar (GPR) as a quick and noninvasive field tool for shallow soil water content estimates as a function of space and time. Initially, detailed studies of collocated data, with electromagnetic velocity estimates from GPR data compared to gravimetric measurements of water content and to soil testure were carried out. Using the procedures developed during the detailed studies, full grids of GPR data were collected over the entire site several times. Data obtained indicate that incorporation of multiple frequency GPR grids can provide high-resolution estimates of soil water content variations as a function of depth as well as space and time

Field-Scale Estimation of Volumetric Water Content Using Ground-Penetrating Radar Ground Wave Techniques

Ground-penetrating radar (GPR) ground wave techniques were applied to estimate soil water content in the uppermost ∼10 cm of a 3 acre California vineyard several times over 1 year. We collected densely spaced GPR travel time measurements using 900 and 450 MHz antennas and analyzed these data to estimate water content. The spatial distribution of water content across the vineyard did not change significantly with time, although the absolute water content values varied seasonally and with irrigation. The GPR estimates of water content were compared to gravimetric water content, time domain reflectometry, and soil texture measurements. The comparisons of GPR-derived estimates of water content to gravimetric water content measurements showed that the GPR estimates had a root mean square error of volumetric water content of the order of 0.01. The results from this study indicate that GPR ground waves can be used to provide noninvasive, spatially dense estimates of shallow water content over large areas and in a rapid manner

GPR Monitoring of Volumetric Water Content in Soils Applied to Highway Construction and Maintenance

An overview is given on two experiments, a controlled pit study and a transportation application in subasphalt soils. Both experiments show that common-offset ground-penetrating radar (GPR) reflection data can be used to estimate θv to a high degree of accuracy. The methodology developed in these two experiments provides a technique for obtaining quick, noninvasive, accurate, and high-resolution estimates of θv

Characterization of Soil Water Content Variability and Soil Texture Using GPR Groundwave Techniques

Accurate characterization of near-surface soil water content is vital for guiding agricultural management decisions and for reducing the potential negative environmental impacts of agriculture. Characterizing the near-surface soil water content can be difficult, as this parameter is often both spatially and temporally variable, and obtaining sufficient measurements to describe the heterogeneity can be prohibitively expensive. Understanding the spatial correlation of near-surface soil water content can help optimize data acquisition and improve understanding of the processes controlling soil water content at the field scale. In this study, ground penetrating radar (GPR) methods were used to characterize the spatial correlation of water content in a three acre field as a function of sampling depth, season, vegetation, and soil texture. GPR data were acquired with 450 MHz and 900 MHz antennas, and measurements of the GPR groundwave were used to estimate soil water content at four different times. Additional water content estimates were obtained using time domain reflectometry measurements, and soil texture measurements were also acquired. Variograms were calculated for each set of measurements, and comparison of these variograms showed that the horizontal spatial correlation was greater for deeper water content measurements than for shallower measurements. Precipitation and irrigation were both shown to increase the spatial variability of water content, while shallowly-rooted vegetation decreased the variability. Comparison of the variograms of water content and soil texture showed that soil texture generally had greater small-scale spatial correlation than water content, and that the variability of water content in deeper soil layers was more closely correlated to soil texture than were shallower water content measurements. Lastly, cross-variograms of soil texture and water content were calculated, and co-kriging of water content estimates and soil texture measurements showed that geophysically-derived estimates of soil water content could be used to improve spatial estimation of soil texture

Using a Mathematical Model to Analyze the Role of Probiotics and Inflammation in Necrotizing Enterocolitis

Background: Necrotizing enterocolitis (NEC) is a severe disease of the gastrointestinal tract of pre-term babies and is thought to be related to the physiological immaturity of the intestine and altered levels of normal flora in the gut. Understanding the factors that contribute to the pathology of NEC may lead to the development of treatment strategies aimed at re-establishing the integrity of the epithelial wall and preventing the propagation of inflammation in NEC. Several studies have shown a reduced incidence and severity of NEC in neonates treated with probiotics (beneficial bacteria species). Methodology/Principal Findings: The objective of this study is to use a mathematical model to predict the conditions under which probiotics may be successful in promoting the health of infants suffering from NEC. An ordinary differential equation model is developed that tracks the populations of pathogenic and probiotic bacteria in the intestinal lumen and in the blood/tissue region. The permeability of the intestinal epithelial layer is treated as a variable, and the role of the inflammatory response is included. The model predicts that in the presence of probiotics health is restored in many cases that would have been otherwise pathogenic. The timing of probiotic administration is also shown to determine whether or not health is restored. Finally, the model predicts that probiotics may be harmful to the NEC patient under very specific conditions, perhaps explaining the detrimental effects of probiotics observed in some clinical studies. Conclusions/Significance: The reduced, experimentally motivated mathematical model that we have developed suggests how a certain general set of characteristics of probiotics can lead to beneficial or detrimental outcomes for infants suffering from NEC, depending on the influences of probiotics on defined features of the inflammatory response. © 2010 Arciero et al

Modeling the interactions of bacteria and Toll-like receptor-mediated inflammation in necrotizing enterocolitis

Necrotizing enterocolitis (NEC) is a severe disease of the gastrointestinal tract in premature infants, characterized by a disrupted intestinal epithelium and an exaggerated pro-inflammatory response. Since the activation of Toll-like receptor-4 (TLR4) blocks cell migration and proliferation and contributes to an uncontrolled inflammatory response within the intestine, this receptor has been identified as a key contributor to the development of NEC. Toll-like receptor-9 (TLR9) has been shown to sense bacterial genome components (CpG DNA) and to play an anti-inflammatory role in NEC. We present in vitro results demonstrating direct inhibition of TLR4 activation by CpG DNA, and we develop a mathematical model of bacteria-immune interactions within the intestine to investigate how such inhibition of TLR4 signaling might alter inflammation, associated bacterial invasion of tissue, and resulting outcomes. The model predicts that TLR9 can inhibit both the beneficial and detrimental effects of TLR4, and thus a proper balance of action by these two receptors is needed to promote intestinal health. The model results are also used to explore three interventions that could potentially prevent the development of NEC: reducing bacteria in the mucus layer, administering probiotic treatment, and blocking TLR4 activation. While the model shows that these interventions would be successful in most cases, the model is also used to identify situations in which the proposed treatments might be harmful