An SMP Soft Classification Algorithm for Remote Sensing

This work introduces a symmetric multiprocessing (SMP) version of the continuous iterative guided spectral class rejection (CIGSCR) algorithm, a semiautomated classification algorithm for remote sensing (multispectral) images. The algorithm uses soft data clusters to produce a soft classification containing inherently more information than a comparable hard classification at an increased computational cost. Previous work suggests that similar algorithms achieve good parallel scalability, motivating the parallel algorithm development work here. Experimental results of applying parallel CIGSCR to an image with approximately 10^8 pixels and six bands demonstrate superlinear speedup. A soft two class classification is generated in just over four minutes using 32 processors

Parallel Deterministic and Stochastic Global Minimization of Functions with Very Many Minima

The optimization of three problems with high dimensionality and many local minima are investigated under five different optimization algorithms: DIRECT, simulated annealing, Spall’s SPSA algorithm, the KNITRO package, and QNSTOP, a new algorithm developed at Indiana University

Power Saving Experiments for Large Scale Global Optimization

Green computing, an emerging field of research that seeks to reduce excess power consumption in high performance computing (HPC), is gaining popularity among researchers. Research in this field often relies on simulation or only uses a small cluster, typically 8 or 16 nodes, because of the lack of hardware support. In contrast, System G at Virginia Tech is a 2592 processor supercomputer equipped with power aware components suitable for large scale green computing research. DIRECT is a deterministic global optimization algorithm, implemented in the mathematical software package VTDIRECT95. This paper explores the potential energy savings for the parallel implementation of DIRECT, called pVTdirect, when used with a large scale computational biology application, parameter estimation for a budding yeast cell cycle model, on System G. Two power aware approaches for pVTdirect are developed and compared against the CPUSPEED power saving system tool. The results show that knowledge of the parallel workload of the underlying application is beneficial for power management

Social stress-enhanced severity of Citrobacter rodentium-induced colitis is CCL2-dependent and attenuated by probiotic Lactobacillus reuteri

Psychological stressors are known to affect colonic diseases but the mechanisms by which this occurs, and whether probiotics can prevent stressor effects, are not understood. Because inflammatory monocytes that traffic into the colon can exacerbate colitis, we tested whether CCL2, a chemokine involved in monocyte recruitment, was necessary for stressor-induced exacerbation of infectious colitis. Mice were exposed to a social disruption stressor that entails repeated social defeat. During stressor exposure, mice were orally challenged with Citrobacter rodentium to induce a colonic inflammatory response. Exposure to the stressor during challenge resulted in significantly higher colonic pathogen levels, translocation to the spleen, increases in colonic macrophages, and increases in inflammatory cytokines and chemokines. The stressor-enhanced severity of C. rodentium-induced colitis was not evident in CCL2[superscript −/−] mice, indicating the effects of the stressor are CCL2-dependent. In addition, we tested whether probiotic intervention could attenuate stressor-enhanced infectious colitis by reducing monocyte/macrophage accumulation. Treating mice with probiotic Lactobacillus reuteri reduced CCL2 mRNA levels in the colon and attenuated stressor-enhanced infectious colitis. These data demonstrate that probiotic L. reuteri can prevent the exacerbating effects of stressor exposure on pathogen-induced colitis, and suggest that one mechanism by which this occurs is through downregulation of the chemokine CCL2.National Cancer Institute (U.S.) (Grants AT006552-01A1, P30-CA016058, and T32-DE014320

An introduction to Trends in Extreme Weather and Climate Events: Observations, Socioeconomic Impacts, Terrestrial Ecological Impacts, and Model Projections

Weather and climatic extremes can have serious and damaging effects on human society and infrastructure as well as on ecosystems and wildlife. Thus, they are usually the main focus of attention of the news media in reports on climate. There are some indications from observations concerning how climatic extremes may have changed in the past. Climate models show how they could change in the future either due to natural climate fluctuations or under conditions of greenhouse gas-induced warming. These observed and modeled changes relate directly to the understanding of socioeconomic and ecological impacts related to extremes.Integrative Biolog

Chapter 15: Potential Surprises: Compound Extremes and Tipping Elements

The Earth system is made up of many components that interact in complex ways across a broad range of temporal and spatial scales. As a result of these interactions the behavior of the system cannot be predicted by looking at individual components in isolation. Negative feedbacks, or self-stabilizing cycles, within and between components of the Earth system can dampen changes (Ch. 2: Physical Drivers of Climate Change). However, their stabilizing effects render such feedbacks of less concern from a risk perspective than positive feedbacks, or self-reinforcing cycles. Positive feedbacks magnify both natural and anthropogenic changes. Some Earth system components, such as arctic sea ice and the polar ice sheets, may exhibit thresholds beyond which these self-reinforcing cycles can drive the component, or the entire system, into a radically different state. Although the probabilities of these state shifts may be difficult to assess, their consequences could be high, potentially exceeding anything anticipated by climate model projections for the coming century

Invasion speeds for structured populations in fluctuating environments

We live in a time where climate models predict future increases in environmental variability and biological invasions are becoming increasingly frequent. A key to developing effective responses to biological invasions in increasingly variable environments will be estimates of their rates of spatial spread and the associated uncertainty of these estimates. Using stochastic, stage-structured, integro-difference equation models, we show analytically that invasion speeds are asymptotically normally distributed with a variance that decreases in time. We apply our methods to a simple juvenile-adult model with stochastic variation in reproduction and an illustrative example with published data for the perennial herb, \emph{Calathea ovandensis}. These examples buttressed by additional analysis reveal that increased variability in vital rates simultaneously slow down invasions yet generate greater uncertainty about rates of spatial spread. Moreover, while temporal autocorrelations in vital rates inflate variability in invasion speeds, the effect of these autocorrelations on the average invasion speed can be positive or negative depending on life history traits and how well vital rates ``remember'' the past

Our Globally Changing Climate

Since the Third U.S. National Climate Assessment (NCA3) was published in May 2014, new observations along multiple lines of evidence have strengthened the conclusion that Earth's climate is changing at a pace and in a pattern not explainable by natural influences. While this report focuses especially on observed and projected future changes for the United States, it is important to understand those changes in the global context (this chapter). The world has warmed over the last 150 years, especially over the last six decades, and that warming has triggered many other changes to Earth's climate. Evidence for a changing climate abounds, from the top of the atmosphere to the depths of the oceans. Thousands of studies conducted by tens of thousands of scientists around the world have documented changes in surface, atmospheric, and oceanic temperatures; melting glaciers; disappearing snow cover; shrinking sea ice; rising sea level; and an increase in atmospheric water vapor. Rainfall patterns and storms are changing, and the occurrence of droughts is shifting

Changes in the Seasonality of Precipitation over the Contiguous USA

Consequences of possible changes in annual total precipitation are dictated, in part, by the timing of precipitation events and changes therein. Herein, we investigated historical changes in precipitation seasonality over the US using observed station precipitation records to compute a standard seasonality index (SI) and the day of year on which certain percentiles of the annual total precipitation were achieved (percentile day of year). The mean SI from the majority of stations exhibited no difference in 1971–2000 relative to 30-year periods earlier in the century. However, analysis of the day of year on which certain percentiles of annual total precipitation were achieved indicated spatially coherent patterns of change. In some regions, the mean day of the year on which the 50th percentile of annual precipitation was achieved differed by 20–30 days between 1971–2000 and both 1911–1940 and 1941–1970. Output from the 10-Atmosphere-Ocean General Circulation Models (AOGCM) simulations of 1971–2000, 2046–2065, and 2081–2100 was used to determine whether AOGCMs are capable of representing the seasonal distribution of precipitation and to examine possible future changes. Many of the AOGCMs qualitatively captured spatial patterns of seasonality during 1971–2000, but there was considerable divergence between AOGCMs in terms of future changes. In both the west and southeast, 7 of 10 AOGCMs indicated later attainment of the 50th percentile accumulation in 2047–2065, implying a possible reversal of the twentieth-century tendency toward relative increases in precipitation receipt during winter and early spring over the southeast. However, this is also a region characterized by considerable interannual variability in the percentile day of year during the historical period

Exploring factors that influence the spread and sustainability of a dysphagia innovation: an instrumental case study

Background: Swallowing difficulties challenge patient safety due to the increased risk of malnutrition, dehydration and aspiration pneumonia. A theoretically driven study was undertaken to examine the spread and sustainability of a locally developed innovation that involved using the Inter-Professional Dysphagia Framework to structure education for the workforce. A conceptual framework with 3 spread strategies (hierarchical control, participatory adaptation and facilitated evolution) was blended with a processual approach to sustaining organisational change. The aim was to understand the processes, mechanism and outcomes associated with the spread and sustainability of this safety initiative. Methods: An instrumental case study, prospectively tracked a dysphagia innovation for 34 months (April 2011 to January 2014) in a large health care organisation in England. A train-the-trainer intervention (as participatory adaptation) was deployed on care pathways for stroke and fractured neck of femur. Data were collected at the organisational and clinical level through interviews (n = 30) and document review. The coding frame combined the processual approach with the spread mechanisms. Pre-determined outcomes included the number of staff trained about dysphagia and impact related to changes in practice. Results: The features and processes associated with hierarchical control and participatory adaptation were identified. Leadership, critical junctures, temporality and making the innovation routine were aspects of hierarchical control. Participatory adaptation was evident on the care pathways through stakeholder responses, workload and resource pressures. Six of the 25 ward based trainers cascaded the dysphagia training. The expected outcomes were achieved when the top-down mandate (hierarchical control) was supplemented by local engagement and support (participatory adaptation). Conclusions: Frameworks for spread and sustainability were combined to create a ‘small theory’ that described the interventions, the processes and desired outcomes a priori. This novel methodological approach confirmed what is known about spread and sustainability, highlighted the particularity of change and offered new insights into the factors associated with hierarchical control and participatory adaptation. The findings illustrate the dualities of organisational change as universal and context specific; as particular and amendable to theoretical generalisation. Appreciating these dualities may contribute to understanding why many innovations fail to become routine