Multi-subject hierarchical inverse covariance modelling improves estimation of functional brain networks.

PubMed

Colclough, Giles L; Woolrich, Mark W; Harrison, Samuel J; Rojas López, Pedro A; Valdes-Sosa, Pedro A; Smith, Stephen M

2018-05-07

A Bayesian model for sparse, hierarchical, inver-covariance estimation is presented, and applied to multi-subject functional connectivity estimation in the human brain. It enables simultaneous inference of the strength of connectivity between brain regions at both subject and population level, and is applicable to fMRI, MEG and EEG data. Two versions of the model can encourage sparse connectivity, either using continuous priors to suppress irrelevant connections, or using an explicit description of the network structure to estimate the connection probability between each pair of regions. A large evaluation of this model, and thirteen methods that represent the state of the art of inverse covariance modelling, is conducted using both simulated and resting-state functional imaging datasets. Our novel Bayesian approach has similar performance to the best extant alternative, Ng et al.'s Sparse Group Gaussian Graphical Model algorithm, which also is based on a hierarchical structure. Using data from the Human Connectome Project, we show that these hierarchical models are able to reduce the measurement error in MEG beta-band functional networks by 10%, producing concomitant increases in estimates of the genetic influence on functional connectivity. Copyright © 2018. Published by Elsevier Inc.

Fast sparsely synchronized brain rhythms in a scale-free neural network.

PubMed

Kim, Sang-Yoon; Lim, Woochang

2015-08-01

We consider a directed version of the Barabási-Albert scale-free network model with symmetric preferential attachment with the same in- and out-degrees and study the emergence of sparsely synchronized rhythms for a fixed attachment degree in an inhibitory population of fast-spiking Izhikevich interneurons. Fast sparsely synchronized rhythms with stochastic and intermittent neuronal discharges are found to appear for large values of J (synaptic inhibition strength) and D (noise intensity). For an intensive study we fix J at a sufficiently large value and investigate the population states by increasing D. For small D, full synchronization with the same population-rhythm frequency fp and mean firing rate (MFR) fi of individual neurons occurs, while for large D partial synchronization with fp>〈fi〉 (〈fi〉: ensemble-averaged MFR) appears due to intermittent discharge of individual neurons; in particular, the case of fp>4〈fi〉 is referred to as sparse synchronization. For the case of partial and sparse synchronization, MFRs of individual neurons vary depending on their degrees. As D passes a critical value D* (which is determined by employing an order parameter), a transition to unsynchronization occurs due to the destructive role of noise to spoil the pacing between sparse spikes. For D

Sparsely-synchronized brain rhythm in a small-world neural network

NASA Astrophysics Data System (ADS)

Kim, Sang-Yoon; Lim, Woochang

2013-07-01

Sparsely-synchronized cortical rhythms, associated with diverse cognitive functions, have been observed in electric recordings of brain activity. At the population level, cortical rhythms exhibit small-amplitude fast oscillations while at the cellular level, individual neurons show stochastic firings sparsely at a much lower rate than the population rate. We study the effect of network architecture on sparse synchronization in an inhibitory population of subthreshold Morris-Lecar neurons (which cannot fire spontaneously without noise). Previously, sparse synchronization was found to occur for cases of both global coupling ( i.e., regular all-to-all coupling) and random coupling. However, a real neural network is known to be non-regular and non-random. Here, we consider sparse Watts-Strogatz small-world networks which interpolate between a regular lattice and a random graph via rewiring. We start from a regular lattice with only short-range connections and then investigate the emergence of sparse synchronization by increasing the rewiring probability p for the short-range connections. For p = 0, the average synaptic path length between pairs of neurons becomes long; hence, only an unsynchronized population state exists because the global efficiency of information transfer is low. However, as p is increased, long-range connections begin to appear, and global effective communication between distant neurons may be available via shorter synaptic paths. Consequently, as p passes a threshold p th (}~ 0.044), sparsely-synchronized population rhythms emerge. However, with increasing p, longer axon wirings become expensive because of their material and energy costs. At an optimal value p* DE (}~ 0.24) of the rewiring probability, the ratio of the synchrony degree to the wiring cost is found to become maximal. In this way, an optimal sparse synchronization is found to occur at a minimal wiring cost in an economic small-world network through trade-off between synchrony and wiring cost.

Rural America's Stake in the Digital Economy. The Main Street Economist: Commentary on the Rural Economy.

ERIC Educational Resources Information Center

Staihr, Brian

This first article in a series on telecommunications in rural America provides an overview of several key telecommunication issues facing rural regions. High speed data services known as broadband have the potential to make rural areas less isolated and improve the rural quality of life, but physical barriers, sparse population density, and few…

Cities as selective land predators? A lesson on urban growth, deregulated planning and sprawl containment.

PubMed

Colantoni, Andrea; Grigoriadis, Efstathios; Sateriano, Adele; Venanzoni, Giuseppe; Salvati, Luca

2016-03-01

The present study investigates changes in the use of land caused by the expansion of an informal city in the Mediterranean region (Athens, Greece) and it proposes a simplified methodology to assess selective land take at the scale of municipalities. The amount of land take over twenty years (1987-2007) for cropland, sparsely vegetated areas and natural land was compared with the surface area of the respective class at the beginning of the study period (1987). Indicators of selective land take by class were correlated with socioeconomic indicators at the scale of municipalities to verify the influence of the local context and the impact of urban planning on land take processes. Evidence indicates that urban expansion into fringe land consumes primarily cropland and sparse vegetation in the case of the Athens' metropolitan region. Cropland and sparse vegetation were consumed proportionally more than the respective availability in 16 municipalities out of 60. Agricultural land take was positively correlated with population density and growth rate, rate of participation to the job market and road density. Sparse vegetation land take was observed in municipalities with predominance of high density settlements. As a result of second-home expansion in coastal municipalities, natural land was converted to urban use in proportion to the availability in the landscape. Urban planning seems to have a limited impact on selective land take. Copyright © 2015 Elsevier B.V. All rights reserved.

The domestication of Amazonia before European conquest.

PubMed

Clement, Charles R; Denevan, William M; Heckenberger, Michael J; Junqueira, André Braga; Neves, Eduardo G; Teixeira, Wenceslau G; Woods, William I

2015-08-07

During the twentieth century, Amazonia was widely regarded as relatively pristine nature, little impacted by human history. This view remains popular despite mounting evidence of substantial human influence over millennial scales across the region. Here, we review the evidence of an anthropogenic Amazonia in response to claims of sparse populations across broad portions of the region. Amazonia was a major centre of crop domestication, with at least 83 native species containing populations domesticated to some degree. Plant domestication occurs in domesticated landscapes, including highly modified Amazonian dark earths (ADEs) associated with large settled populations and that may cover greater than 0.1% of the region. Populations and food production expanded rapidly within land management systems in the mid-Holocene, and complex societies expanded in resource-rich areas creating domesticated landscapes with profound impacts on local and regional ecology. ADE food production projections support estimates of at least eight million people in 1492. By this time, highly diverse regional systems had developed across Amazonia where subsistence resources were created with plant and landscape domestication, including earthworks. This review argues that the Amazonian anthrome was no less socio-culturally diverse or populous than other tropical forested areas of the world prior to European conquest. © 2015 The Author(s).

Multivariate quadrature for representing cloud condensation nuclei activity of aerosol populations

DOE PAGES

Fierce, Laura; McGraw, Robert L.

2017-07-26

Here, sparse representations of atmospheric aerosols are needed for efficient regional- and global-scale chemical transport models. Here we introduce a new framework for representing aerosol distributions, based on the quadrature method of moments. Given a set of moment constraints, we show how linear programming, combined with an entropy-inspired cost function, can be used to construct optimized quadrature representations of aerosol distributions. The sparse representations derived from this approach accurately reproduce cloud condensation nuclei (CCN) activity for realistically complex distributions simulated by a particleresolved model. Additionally, the linear programming techniques described in this study can be used to bound key aerosolmore » properties, such as the number concentration of CCN. Unlike the commonly used sparse representations, such as modal and sectional schemes, the maximum-entropy approach described here is not constrained to pre-determined size bins or assumed distribution shapes. This study is a first step toward a particle-based aerosol scheme that will track multivariate aerosol distributions with sufficient computational efficiency for large-scale simulations.« less

Multivariate quadrature for representing cloud condensation nuclei activity of aerosol populations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fierce, Laura; McGraw, Robert L.

Here, sparse representations of atmospheric aerosols are needed for efficient regional- and global-scale chemical transport models. Here we introduce a new framework for representing aerosol distributions, based on the quadrature method of moments. Given a set of moment constraints, we show how linear programming, combined with an entropy-inspired cost function, can be used to construct optimized quadrature representations of aerosol distributions. The sparse representations derived from this approach accurately reproduce cloud condensation nuclei (CCN) activity for realistically complex distributions simulated by a particleresolved model. Additionally, the linear programming techniques described in this study can be used to bound key aerosolmore » properties, such as the number concentration of CCN. Unlike the commonly used sparse representations, such as modal and sectional schemes, the maximum-entropy approach described here is not constrained to pre-determined size bins or assumed distribution shapes. This study is a first step toward a particle-based aerosol scheme that will track multivariate aerosol distributions with sufficient computational efficiency for large-scale simulations.« less

Egg fertilisation in a freshwater mussel: effects of distance, flow and male density

Treesearch

Tyler L. Mosley; Wendell R. Haag; James A. Stoeckel

2014-01-01

1. Small or sparse populations can experience Allee effects if egg fertilisation is reduced because of a shortage of sperm. 2. Freshwater mussels are spermcasters that often occur as sparse, patchy populations. Previous studies suggested that sperm shortage limits these populations unless facultative hermaphroditism and selffertilisation occur at low density...

A robust sparse-modeling framework for estimating schizophrenia biomarkers from fMRI.

PubMed

Dillon, Keith; Calhoun, Vince; Wang, Yu-Ping

2017-01-30

Our goal is to identify the brain regions most relevant to mental illness using neuroimaging. State of the art machine learning methods commonly suffer from repeatability difficulties in this application, particularly when using large and heterogeneous populations for samples. We revisit both dimensionality reduction and sparse modeling, and recast them in a common optimization-based framework. This allows us to combine the benefits of both types of methods in an approach which we call unambiguous components. We use this to estimate the image component with a constrained variability, which is best correlated with the unknown disease mechanism. We apply the method to the estimation of neuroimaging biomarkers for schizophrenia, using task fMRI data from a large multi-site study. The proposed approach yields an improvement in both robustness of the estimate and classification accuracy. We find that unambiguous components incorporate roughly two thirds of the same brain regions as sparsity-based methods LASSO and elastic net, while roughly one third of the selected regions differ. Further, unambiguous components achieve superior classification accuracy in differentiating cases from controls. Unambiguous components provide a robust way to estimate important regions of imaging data. Copyright © 2016 Elsevier B.V. All rights reserved.

What Is a Mild Winter? Regional Differences in Within-Species Responses to Climate Change.

PubMed

Vetter, Sebastian G; Ruf, Thomas; Bieber, Claudia; Arnold, Walter

2015-01-01

Climate change is known to affect ecosystems globally, but our knowledge of its impact on large and widespread mammals, and possibly population-specific responses is still sparse. We investigated large-scale and long-term effects of climate change on local population dynamics using the wild boar (Sus scrofa L.) as a model species. Our results show that population increases across Europe are strongly associated with increasingly mild winters, yet with region-specific threshold temperatures for the onset of exponential growth. Additionally, we found that abundant availability of critical food resources, e.g. beech nuts, can outweigh the negative effects of cold winters on population growth of wild boar. Availability of beech nuts is highly variable and highest in years of beech mast which increased in frequency since 1980, according to our data. We conclude that climate change drives population growth of wild boar directly by relaxing the negative effect of cold winters on survival and reproduction, and indirectly by increasing food availability. However, region-specific responses need to be considered in order to fully understand a species' demographic response to climate change.

Midcontinental Native American population dynamics and late Holocene hydroclimate extremes

NASA Astrophysics Data System (ADS)

Bird, Broxton W.; Wilson, Jeremy J.; Gilhooly, William P., III; Steinman, Byron A.; Stamps, Lucas

2017-01-01

Climate’s influence on late Pre-Columbian (pre-1492 CE), maize-dependent Native American populations in the midcontinental United States (US) is poorly understood as regional paleoclimate records are sparse and/or provide conflicting perspectives. Here, we reconstruct regional changes in precipitation source and seasonality and local changes in warm-season duration and rainstorm events related to the Pacific North American pattern (PNA) using a 2100-year-long multi-proxy lake-sediment record from the midcontinental US. Wet midcontinental climate reflecting negative PNA-like conditions occurred during the Medieval Climate Anomaly (950-1250 CE) as Native American populations adopted intensive maize agriculture, facilitating population aggregation and the development of urban centers between 1000-1200 CE. Intensifying midcontinental socio-political instability and warfare between 1250-1350 CE corresponded with drier positive PNA-like conditions, culminating in the staggered abandonment of many major Native American river valley settlements and large urban centers between 1350-1450 CE during an especially severe warm-season drought. We hypothesize that this sustained drought interval rendered it difficult to support dense populations and large urban centers in the midcontinental US by destabilizing regional agricultural systems, thereby contributing to the host of socio-political factors that led to population reorganization and migration in the midcontinent and neighboring regions shortly before European contact.

Midcontinental Native American population dynamics and late Holocene hydroclimate extremes

PubMed Central

Bird, Broxton W.; Wilson, Jeremy J.; Gilhooly III, William P.; Steinman, Byron A.; Stamps, Lucas

2017-01-01

Climate’s influence on late Pre-Columbian (pre-1492 CE), maize-dependent Native American populations in the midcontinental United States (US) is poorly understood as regional paleoclimate records are sparse and/or provide conflicting perspectives. Here, we reconstruct regional changes in precipitation source and seasonality and local changes in warm-season duration and rainstorm events related to the Pacific North American pattern (PNA) using a 2100-year-long multi-proxy lake-sediment record from the midcontinental US. Wet midcontinental climate reflecting negative PNA-like conditions occurred during the Medieval Climate Anomaly (950–1250 CE) as Native American populations adopted intensive maize agriculture, facilitating population aggregation and the development of urban centers between 1000–1200 CE. Intensifying midcontinental socio-political instability and warfare between 1250–1350 CE corresponded with drier positive PNA-like conditions, culminating in the staggered abandonment of many major Native American river valley settlements and large urban centers between 1350–1450 CE during an especially severe warm-season drought. We hypothesize that this sustained drought interval rendered it difficult to support dense populations and large urban centers in the midcontinental US by destabilizing regional agricultural systems, thereby contributing to the host of socio-political factors that led to population reorganization and migration in the midcontinent and neighboring regions shortly before European contact. PMID:28139698

A serotonin transporter gene polymorphism predicts peripartum depressive symptoms in an at-risk psychiatric cohort.

PubMed

Binder, Elisabeth B; Newport, D Jeffrey; Zach, Elizabeth B; Smith, Alicia K; Deveau, Todd C; Altshuler, Lori L; Cohen, Lee S; Stowe, Zachary N; Cubells, Joseph F

2010-07-01

Peripartum major depressive disorder (MDD) is a prevalent psychiatric disorder with potential detrimental consequences for both mother and child. Despite its enormous health care relevance, data regarding genetic predictors of peripartum depression are sparse. The aim of this study was to investigate associations of the serotonin-transporter linked polymorphic region (5-HTTLPR) genotype with peripartum MDD in an at-risk population. Two hundred and seventy four women with a prior history of MDD were genotyped for 5-HTTLPR and serially evaluated in late pregnancy (gestational weeks 31-40), early post-partum (week 1-8) and late post-partum (week 9-24) for diagnosis of a current major depressive episode (MDE) and depressive symptom severity. 5-HTTLPR S-allele carrier status predicted the occurrence of a MDE in the early post-partum period only (OR=5.13, p=0.017). This association persisted despite continued antidepressant treatment. The 5-HTTLPR genotype may be a clinically relevant predictor of early post-partum depression in an at-risk population. Peripartum major depressive disorder is a prevalent psychiatric disorder with potential detrimental consequences for both mother and child. Despite its enormous health care relevance, data regarding genetic predictors of peripartum depression are sparse. The aim of this study was to investigate associations of the serotonin-transporter linked polymorphic region (5-HTTLPR) genotype with peripartum MDD in an at-risk population. Copyright 2009 Elsevier Ltd. All rights reserved.

The Hayward Fault - Is It Due for a Repeat of the Powerful 1868 Earthquake?

USGS Publications Warehouse

Brocher, Thomas M.; Boatwright, Jack; Lienkaemper, James J.; Prentice, Carol S.; Schwartz, David P.; Bundock, Howard

2008-01-01

On October 21, 1868, a magnitude 6.8 earthquake struck the San Francisco Bay region. Although the region was then sparsely populated, this quake on the Hayward Fault was one of the most destructive in California?s history. Recent studies show that such powerful Hayward Fault quakes have repeatedly jolted the region in the past. U.S. Geological Survey (USGS) scientists describe this fault as a tectonic time bomb, due anytime for another magnitude 6.8 to 7.0 earthquake. Because such a quake could cause hundreds of deaths, leave thousands homeless, and devastate the region?s economy, the USGS and other organizations are working together with new urgency to help prepare Bay Area communities for this certain future quake.

Network dynamics underlying the formation of sparse, informative representations in the hippocampus.

PubMed

Karlsson, Mattias P; Frank, Loren M

2008-12-24

During development, activity-dependent processes increase the specificity of neural responses to stimuli, but the role that this type of process plays in adult plasticity is unclear. We examined the dynamics of hippocampal activity as animals learned about new environments to understand how neural selectivity changes with experience. Hippocampal principal neurons fire when the animal is located in a particular subregion of its environment, and in any given environment the hippocampal representation is sparse: less than half of the neurons in areas CA1 and CA3 are active whereas the rest are essentially silent. Here we show that different dynamics govern the evolution of this sparsity in CA1 and upstream area CA3. CA1, but not CA3, produces twice as many spikes in novel compared with familiar environments. This high rate firing continues during sharp wave ripple events in a subsequent rest period. The overall CA1 population rate declines and the number of active cells decreases as the environment becomes familiar and task performance improves, but the decline in rate is not uniform across neurons. Instead, the activity of cells with initial peak spatial rates above approximately 12 Hz is enhanced, whereas the activity of cells with lower initial peak rates is suppressed. The result of these changes is that the active CA1 population comes to consist of a relatively small group of cells with strong spatial tuning. This process is not evident in CA3, indicating that a region-specific and long timescale process operates in CA1 to create a sparse, spatially informative population of neurons.

Accessibility of general practitioners and selected specialist physicians by car and by public transport in a rural region of Germany.

PubMed

Stentzel, Ulrike; Piegsa, Jens; Fredrich, Daniel; Hoffmann, Wolfgang; van den Berg, Neeltje

2016-10-19

The accessibility of medical care facilities in sparsely populated rural regions is relevant especially for elderly people which often represent a large segment of the population in such regions. Elderly people have higher morbidity risks and a higher demand for medical care. Although travelling with private cars is the dominating traffic mode in rural regions, accessibility by public transport is increasingly important especially because of limited mobility of elderly people. The aim of this study was to determine accessibility both by car and public transport to general practitioners (GP) and selected specialist physicians for a whole region and to detect areas with poor to no access in the county Vorpommern-Greifswald, which is a rural and sparsely populated region in the very northeast of Germany. Accessibility of medical care facilities by car was calculated on the basis of a network analysis within a geographic information system (GIS) with routable street data. Accessibility by public transport was calculated using GIS and a network analysis based on the implementation of Dijkstra's algorithm. The travelling time to general practitioners (GP) by car in the study region ranges from 0.1 to 22.9 min. This is a significant difference compared to other physician groups. Traveling times to specialist physicians are 0.4 to 42.9 min. A minority of 80 % of the inhabitants reach the specialist physicians within 20 min. The accessibility of specialist physicians by public transport is poor. The travel time (round trip) to GPs averages 99.3 min, to internists 143.0, to ophthalmologists 129.3 and to urologists 159.9 min. These differences were significant. Assumed was a one hour appointment on a Tuesday at 11 am. 8,973 inhabitants (3.8 %) have no connection to a GP by public transport. 15,455 inhabitants (6.5 %) have no connection to specialist internists. Good accessibility by public transport is not a question of distance but of transport connections. GIS analyses can detect areas with imminent or manifest deficits in the accessibility of health care providers. Accessibility analyses should be established instruments in planning issues.

Assessing Effects of Prenatal Alcohol Exposure Using Group-wise Sparse Representation of FMRI Data

PubMed Central

Lv, Jinglei; Jiang, Xi; Li, Xiang; Zhu, Dajiang; Zhao, Shijie; Zhang, Tuo; Hu, Xintao; Han, Junwei; Guo, Lei; Li, Zhihao; Coles, Claire; Hu, Xiaoping; Liu, Tianming

2015-01-01

Task-based fMRI activation mapping has been widely used in clinical neuroscience in order to assess different functional activity patterns in conditions such as prenatal alcohol exposure (PAE) affected brains and healthy controls. In this paper, we propose a novel, alternative approach of group-wise sparse representation of the fMRI data of multiple groups of subjects (healthy control, exposed non-dysmorphic PAE and exposed dysmorphic PAE) and assess the systematic functional activity differences among these three populations. Specifically, a common time series signal dictionary is learned from the aggregated fMRI signals of all three groups of subjects, and then the weight coefficient matrices (named statistical coefficient map (SCM)) associated with each common dictionary were statistically assessed for each group separately. Through inter-group comparisons based on the correspondence established by the common dictionary, our experimental results have demonstrated that the group-wise sparse coding strategy and the SCM can effectively reveal a collection of brain networks/regions that were affected by different levels of severity of PAE. PMID:26195294

Statistics of single unit responses in the human medial temporal lobe: A sparse and overdispersed code

NASA Astrophysics Data System (ADS)

Magyar, Andrew

The recent discovery of cells that respond to purely conceptual features of the environment (particular people, landmarks, objects, etc) in the human medial temporal lobe (MTL), has raised many questions about the nature of the neural code in humans. The goal of this dissertation is to develop a novel statistical method based upon maximum likelihood regression which will then be applied to these experiments in order to produce a quantitative description of the coding properties of the human MTL. In general, the method is applicable to any experiments in which a sequence of stimuli are presented to an organism while the binary responses of a large number of cells are recorded in parallel. The central concept underlying the approach is the total probability that a neuron responds to a random stimulus, called the neuronal sparsity. The model then estimates the distribution of response probabilities across the population of cells. Applying the method to single-unit recordings from the human medial temporal lobe, estimates of the sparsity distributions are acquired in four regions: the hippocampus, the entorhinal cortex, the amygdala, and the parahippocampal cortex. The resulting distributions are found to be sparse (large fraction of cells with a low response probability) and highly non-uniform, with a large proportion of ultra-sparse neurons that possess a very low response probability, and a smaller population of cells which respond much more frequently. Rammifications of the results are discussed in relation to the sparse coding hypothesis, and comparisons are made between the statistics of the human medial temporal lobe cells and place cells observed in the rodent hippocampus.

Effect of intermodular connection on fast sparse synchronization in clustered small-world neural networks

NASA Astrophysics Data System (ADS)

Kim, Sang-Yoon; Lim, Woochang

2015-11-01

We consider a clustered network with small-world subnetworks of inhibitory fast spiking interneurons and investigate the effect of intermodular connection on the emergence of fast sparsely synchronized rhythms by varying both the intermodular coupling strength Jinter and the average number of intermodular links per interneuron Msyn(inter ). In contrast to the case of nonclustered networks, two kinds of sparsely synchronized states such as modular and global synchronization are found. For the case of modular sparse synchronization, the population behavior reveals the modular structure, because the intramodular dynamics of subnetworks make some mismatching. On the other hand, in the case of global sparse synchronization, the population behavior is globally identical, independently of the cluster structure, because the intramodular dynamics of subnetworks make perfect matching. We introduce a realistic cross-correlation modularity measure, representing the matching degree between the instantaneous subpopulation spike rates of the subnetworks, and examine whether the sparse synchronization is global or modular. Depending on its magnitude, the intermodular coupling strength Jinter seems to play "dual" roles for the pacing between spikes in each subnetwork. For large Jinter, due to strong inhibition it plays a destructive role to "spoil" the pacing between spikes, while for small Jinter it plays a constructive role to "favor" the pacing between spikes. Through competition between the constructive and the destructive roles of Jinter, there exists an intermediate optimal Jinter at which the pacing degree between spikes becomes maximal. In contrast, the average number of intermodular links per interneuron Msyn(inter ) seems to play a role just to favor the pacing between spikes. With increasing Msyn(inter ), the pacing degree between spikes increases monotonically thanks to the increase in the degree of effectiveness of global communication between spikes. Furthermore, we employ the realistic sub- and whole-population order parameters, based on the instantaneous sub- and whole-population spike rates, to determine the threshold values for the synchronization-unsynchronization transition in the sub- and whole populations, and the degrees of global and modular sparse synchronization are also measured in terms of the realistic sub- and whole-population statistical-mechanical spiking measures defined by considering both the occupation and the pacing degrees of spikes. It is expected that our results could have implications for the role of the brain plasticity in some functional behaviors associated with population synchronization.

GALAPAGOS-C: analysis of galaxy morphologies using high-performance computing methods

NASA Astrophysics Data System (ADS)

Hiemer, Andreas; Barden, Marco; Kelvin, Lee S.; Häußler, Boris; Schindler, Sabine

2014-11-01

We present GALAPAGOS-C, a code designed to process a complete set of survey images through automation of source detection (via SEXTRACTOR), postage stamp cutting, object mask preparation, sky background estimation and complex two-dimensional light profile Sérsic modelling (via GALFIT). GALAPAGOS-C is designed around the concept of MPI-parallelization, allowing the processing of large data sets in a quick and efficient manner. Further, GALAPAGOS-C is capable of fitting multiple-Sérsic profiles to each galaxy, each representing distinct galaxy components (e.g. bulge, disc, bar), in addition to the option to fit asymmetric Fourier mode distortions. The modelling reliability of our core single-Sérsic fitting capability is tested thoroughly using image simulations. We apply GALAPAGOS-C to the Space Telescope A901/902 Galaxy Evolution Survey to investigate the evolution of galaxy structure with cosmic time and the dependence on environment. We measure the distribution of Sérsic indices as a function of local object density in the A901/902 cluster sample to provide one of the first measures of the Sérsic index-density relation. We find that the fraction of galaxies with a high Sérsic index (2.5 < n < 7.0) is higher in denser environments (˜35 per cent), halving towards sparsely populated regions (˜15 per cent). The population of low Sérsic index galaxies (0.4 < n< 1.6) is lower in denser environments (˜35 per cent), increasing towards sparsely populated regions (˜60 per cent). The population of intermediate Sérsic index galaxies (1.6 < n < 2.5) approximately follows the trend of the high Sérsic index types.

Population and policy in Finland.

PubMed

Hulkko, J

1989-03-01

Finland, with a population of 4.9 million, currently has an overall fertility rate of 1.6. There is a small population growth, but this is due to a large reproductive age group, return migration of Finns from Sweden, and a decrease in mortality that has increased the proportion of old people in the population. The state has no official population policy. A recommendation of the Finnish Committee on the World Population Year 1974 that the government establish an agency for population policy has not been adopted. The coalition government now in power has a program, however, aimed at influencing population growth. The program includes proposals to reduce work hours for parents with small children, increase the age limit for participation in the child allowance system, and increase the number of municipal day care facilities. Concerning regional policy, the government wants a balanced development of the country's different regions. Subsidiary industries of agriculture and forestry are being encouraged to preserve population levels in sparse areas. Finland also supports a health policy emphasizing preventive and non-institutional aspects of health care, with targets of life expectancy set at 82 years for women and 75 years for men by the year 2000.

Interpolation of scattered temperature data measurements onto a worldwide regular grid using radial basis functions with applications to global warming

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kansa, E.J.; Axelrod, M.C.; Kercher, J.R.

1994-05-01

Our current research into the response of natural ecosystems to a hypothesized climatic change requires that we have estimates of various meteorological variables on a regularly spaced grid of points on the surface of the earth. Unfortunately, the bulk of the world`s meteorological measurement stations is located at airports that tend to be concentrated on the coastlines of the world or near populated areas. We can also see that the spatial density of the station locations is extremely non-uniform with the greatest density in the USA, followed by Western Europe. Furthermore, the density of airports is rather sparse in desertmore » regions such as the Sahara, the Arabian, Gobi, and Australian deserts; likewise the density is quite sparse in cold regions such as Antarctica Northern Canada, and interior northern Russia. The Amazon Basin in Brazil has few airports. The frequency of airports is obviously related to the population centers and the degree of industrial development of the country. We address the following problem here. Given values of meteorological variables, such as maximum monthly temperature, measured at the more than 5,500 airport stations, interpolate these values onto a regular grid of terrestrial points spaced by one degree in both latitude and longitude. This is known as the scattered data problem.« less

Image fusion using sparse overcomplete feature dictionaries

DOEpatents

Brumby, Steven P.; Bettencourt, Luis; Kenyon, Garrett T.; Chartrand, Rick; Wohlberg, Brendt

2015-10-06

Approaches for deciding what individuals in a population of visual system "neurons" are looking for using sparse overcomplete feature dictionaries are provided. A sparse overcomplete feature dictionary may be learned for an image dataset and a local sparse representation of the image dataset may be built using the learned feature dictionary. A local maximum pooling operation may be applied on the local sparse representation to produce a translation-tolerant representation of the image dataset. An object may then be classified and/or clustered within the translation-tolerant representation of the image dataset using a supervised classification algorithm and/or an unsupervised clustering algorithm.

Population coding in sparsely connected networks of noisy neurons.

PubMed

Tripp, Bryan P; Orchard, Jeff

2012-01-01

This study examines the relationship between population coding and spatial connection statistics in networks of noisy neurons. Encoding of sensory information in the neocortex is thought to require coordinated neural populations, because individual cortical neurons respond to a wide range of stimuli, and exhibit highly variable spiking in response to repeated stimuli. Population coding is rooted in network structure, because cortical neurons receive information only from other neurons, and because the information they encode must be decoded by other neurons, if it is to affect behavior. However, population coding theory has often ignored network structure, or assumed discrete, fully connected populations (in contrast with the sparsely connected, continuous sheet of the cortex). In this study, we modeled a sheet of cortical neurons with sparse, primarily local connections, and found that a network with this structure could encode multiple internal state variables with high signal-to-noise ratio. However, we were unable to create high-fidelity networks by instantiating connections at random according to spatial connection probabilities. In our models, high-fidelity networks required additional structure, with higher cluster factors and correlations between the inputs to nearby neurons.

Large-region acoustic source mapping using a movable array and sparse covariance fitting.

PubMed

Zhao, Shengkui; Tuna, Cagdas; Nguyen, Thi Ngoc Tho; Jones, Douglas L

2017-01-01

Large-region acoustic source mapping is important for city-scale noise monitoring. Approaches using a single-position measurement scheme to scan large regions using small arrays cannot provide clean acoustic source maps, while deploying large arrays spanning the entire region of interest is prohibitively expensive. A multiple-position measurement scheme is applied to scan large regions at multiple spatial positions using a movable array of small size. Based on the multiple-position measurement scheme, a sparse-constrained multiple-position vectorized covariance matrix fitting approach is presented. In the proposed approach, the overall sample covariance matrix of the incoherent virtual array is first estimated using the multiple-position array data and then vectorized using the Khatri-Rao (KR) product. A linear model is then constructed for fitting the vectorized covariance matrix and a sparse-constrained reconstruction algorithm is proposed for recovering source powers from the model. The user parameter settings are discussed. The proposed approach is tested on a 30 m × 40 m region and a 60 m × 40 m region using simulated and measured data. Much cleaner acoustic source maps and lower sound pressure level errors are obtained compared to the beamforming approaches and the previous sparse approach [Zhao, Tuna, Nguyen, and Jones, Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP) (2016)].

Pheromone lures to monitor sparse populations of spruce budworm, Choristoneura fumiferana (Lepidoptera: Tortricidae)

Treesearch

David G. Grimble

1988-01-01

Four types of spruce budworm pheromone lures were field-tested in sparse spruce budworm populations in Maine. BioLures® with constant pheromone emission rates less than 1.0, ca. 1.0-1.5, and ca. 15.0 micrograms of pheromone per day were compared to polyvinyl chloride (PVC) lures with rapidly decreasing pheromone emission rates. Mean trap catch was roughly proportional...

Development of Innovative Technology to Expand Precipitation Observations in Satellite Precipitation Validation in Under-developed Data-sparse Regions

NASA Astrophysics Data System (ADS)

Kucera, P. A.; Steinson, M.

2016-12-01

Accurate and reliable real-time monitoring and dissemination of observations of precipitation and surface weather conditions in general is critical for a variety of research studies and applications. Surface precipitation observations provide important reference information for evaluating satellite (e.g., GPM) precipitation estimates. High quality surface observations of precipitation, temperature, moisture, and winds are important for applications such as agriculture, water resource monitoring, health, and hazardous weather early warning systems. In many regions of the World, surface weather station and precipitation gauge networks are sparsely located and/or of poor quality. Existing stations have often been sited incorrectly, not well-maintained, and have limited communications established at the site for real-time monitoring. The University Corporation for Atmospheric Research (UCAR)/National Center for Atmospheric Research (NCAR), with support from USAID, has started an initiative to develop and deploy low-cost weather instrumentation including tipping bucket and weighing-type precipitation gauges in sparsely observed regions of the world. The goal is to improve the number of observations (temporally and spatially) for the evaluation of satellite precipitation estimates in data-sparse regions and to improve the quality of applications for environmental monitoring and early warning alert systems on a regional to global scale. One important aspect of this initiative is to make the data open to the community. The weather station instrumentation have been developed using innovative new technologies such as 3D printers, Raspberry Pi computing systems, and wireless communications. An initial pilot project have been implemented in the country of Zambia. This effort could be expanded to other data sparse regions around the globe. The presentation will provide an overview and demonstration of 3D printed weather station development and initial evaluation of observed precipitation datasets.

Classification of multispectral or hyperspectral satellite imagery using clustering of sparse approximations on sparse representations in learned dictionaries obtained using efficient convolutional sparse coding

DOEpatents

Moody, Daniela; Wohlberg, Brendt

2018-01-02

An approach for land cover classification, seasonal and yearly change detection and monitoring, and identification of changes in man-made features may use a clustering of sparse approximations (CoSA) on sparse representations in learned dictionaries. The learned dictionaries may be derived using efficient convolutional sparse coding to build multispectral or hyperspectral, multiresolution dictionaries that are adapted to regional satellite image data. Sparse image representations of images over the learned dictionaries may be used to perform unsupervised k-means clustering into land cover categories. The clustering process behaves as a classifier in detecting real variability. This approach may combine spectral and spatial textural characteristics to detect geologic, vegetative, hydrologic, and man-made features, as well as changes in these features over time.

Survey views of the Mir space station taken during rendezvous

NASA Image and Video Library

1997-01-16

STS081-709-061 (12-22 Jan. 1997) --- As recorded while Space Shuttle Atlantis was docked with Russia's Mir Space Station, this 70mm camera's frame shows South Africa's wine growing country (immediately right of the solar panel) in a southwest-looking perspective. Most of the population in the Western Cape Province, as it is known, is clustered in the wet extreme south of the country identified here with denser cloud masses. This is the Mediterranean region of the country, experiencing summer drought when the photograph was taken. Cape Town lies immediately right of the solar panel and the Swartland wheat country to the left. The darker green areas are more heavily vegetated regions on the continental escarpment. The large bay in the region is the remote St. Helena Bay (Africa's southernmost point, Cape Agulhas, lies behind the solar panel). The cloud-free parts of the country in the foreground is the sparsely populated semidesert known as the Karroo, a quiet region to which people retire both for its rare dry climate and its beauty.

Automated bone segmentation from dental CBCT images using patch-based sparse representation and convex optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Li; Gao, Yaozong; Shi, Feng

Purpose: Cone-beam computed tomography (CBCT) is an increasingly utilized imaging modality for the diagnosis and treatment planning of the patients with craniomaxillofacial (CMF) deformities. Accurate segmentation of CBCT image is an essential step to generate three-dimensional (3D) models for the diagnosis and treatment planning of the patients with CMF deformities. However, due to the poor image quality, including very low signal-to-noise ratio and the widespread image artifacts such as noise, beam hardening, and inhomogeneity, it is challenging to segment the CBCT images. In this paper, the authors present a new automatic segmentation method to address these problems. Methods: To segmentmore » CBCT images, the authors propose a new method for fully automated CBCT segmentation by using patch-based sparse representation to (1) segment bony structures from the soft tissues and (2) further separate the mandible from the maxilla. Specifically, a region-specific registration strategy is first proposed to warp all the atlases to the current testing subject and then a sparse-based label propagation strategy is employed to estimate a patient-specific atlas from all aligned atlases. Finally, the patient-specific atlas is integrated into amaximum a posteriori probability-based convex segmentation framework for accurate segmentation. Results: The proposed method has been evaluated on a dataset with 15 CBCT images. The effectiveness of the proposed region-specific registration strategy and patient-specific atlas has been validated by comparing with the traditional registration strategy and population-based atlas. The experimental results show that the proposed method achieves the best segmentation accuracy by comparison with other state-of-the-art segmentation methods. Conclusions: The authors have proposed a new CBCT segmentation method by using patch-based sparse representation and convex optimization, which can achieve considerably accurate segmentation results in CBCT segmentation based on 15 patients.« less

Sparse orthogonal population representation of spatial context in the retrosplenial cortex.

PubMed

Mao, Dun; Kandler, Steffen; McNaughton, Bruce L; Bonin, Vincent

2017-08-15

Sparse orthogonal coding is a key feature of hippocampal neural activity, which is believed to increase episodic memory capacity and to assist in navigation. Some retrosplenial cortex (RSC) neurons convey distributed spatial and navigational signals, but place-field representations such as observed in the hippocampus have not been reported. Combining cellular Ca 2+ imaging in RSC of mice with a head-fixed locomotion assay, we identified a population of RSC neurons, located predominantly in superficial layers, whose ensemble activity closely resembles that of hippocampal CA1 place cells during the same task. Like CA1 place cells, these RSC neurons fire in sequences during movement, and show narrowly tuned firing fields that form a sparse, orthogonal code correlated with location. RSC 'place' cell activity is robust to environmental manipulations, showing partial remapping similar to that observed in CA1. This population code for spatial context may assist the RSC in its role in memory and/or navigation.Neurons in the retrosplenial cortex (RSC) encode spatial and navigational signals. Here the authors use calcium imaging to show that, similar to the hippocampus, RSC neurons also encode place cell-like activity in a sparse orthogonal representation, partially anchored to the allocentric cues on the linear track.

Dense encoding of natural odorants by ensembles of sparsely activated neurons in the olfactory bulb

PubMed Central

Gschwend, Olivier; Beroud, Jonathan; Vincis, Roberto; Rodriguez, Ivan; Carleton, Alan

2016-01-01

Sensory information undergoes substantial transformation along sensory pathways, usually encompassing sparsening of activity. In the olfactory bulb, though natural odorants evoke dense glomerular input maps, mitral and tufted (M/T) cells tuning is considered to be sparse because of highly odor-specific firing rate change. However, experiments used to draw this conclusion were either based on recordings performed in anesthetized preparations or used monomolecular odorants presented at arbitrary concentrations. In this study, we evaluated the lifetime and population sparseness evoked by natural odorants by capturing spike temporal patterning of neuronal assemblies instead of individual M/T tonic activity. Using functional imaging and tetrode recordings in awake mice, we show that natural odorants at their native concentrations are encoded by broad assemblies of M/T cells. While reducing odorant concentrations, we observed a reduced number of activated glomeruli representations and consequently a narrowing of M/T tuning curves. We conclude that natural odorants at their native concentrations recruit M/T cells with phasic rather than tonic activity. When encoding odorants in assemblies, M/T cells carry information about a vast number of odorants (lifetime sparseness). In addition, each natural odorant activates a broad M/T cell assembly (population sparseness). PMID:27824096

Preliminary methodology to assess the national and regional impact of U.S. wind energy development on birds and bats

USGS Publications Warehouse

Diffendorfer, James E.; Beston, Julie A.; Merrill, Matthew D.; Stanton, Jessica C.; Corum, Margo D.; Loss, Scott R.; Thogmartin, Wayne E.; Johnson, Douglas H.; Erickson, Richard A.; Heist, Kevin W.

2015-01-01

Components of the methodology are based on simplifying assumptions and require information that, for many species, may be sparse or unreliable. These assumptions are presented in the report and should be carefully considered when using output from the methodology. In addition, this methodology can be used to recommend species for more intensive demographic modeling or highlight those species that may not require any additional protection because effects of wind energy development on their populations are projected to be small.

Olfactory coding: giant inhibitory neuron governs sparse odor codes.

PubMed

Gupta, Nitin; Stopfer, Mark

2011-07-12

Electrophysiological investigations in locusts have revealed that the sparseness of odor representations, in the brain region expected to mediate olfactory learning, is shaped by a unique inhibitory neuron. Copyright © 2011 Elsevier Ltd. All rights reserved.

Climate change and health research in the Eastern Mediterranean Region.

PubMed

Habib, Rima R; Zein, Kareem El; Ghanawi, Joly

2010-06-01

Anthropologically induced climate change, caused by an increased concentration of greenhouse gases in the atmosphere, is an emerging threat to human health. Consequences of climate change may affect the prevalence of various diseases and environmental and social maladies that affect population health. In this article, we reviewed the literature on climate change and health in the Eastern Mediterranean Region. This region already faces numerous humanitarian crises, from conflicts to natural hazards and a high burden of disease. Climate change is likely to aggravate these emergencies, necessitating a strengthening of health systems and capacities in the region. However, the existing literature on climate change from the region is sparse and informational gaps stand in the way of regional preparedness and adaptation. Further research is needed to assess climatic changes and related health impacts in the Eastern Mediterranean Region. Such knowledge will allow countries to identify preparedness vulnerabilities, evaluate capacity to adapt to climate change, and develop adaptation strategies to allay the health impacts of climate change.

Evaluation of Observation-Fused Regional Air Quality Model Results for Population Air Pollution Exposure Estimation

PubMed Central

Chen, Gang; Li, Jingyi; Ying, Qi; Sherman, Seth; Perkins, Neil; Rajeshwari, Sundaram; Mendola, Pauline

2014-01-01

In this study, Community Multiscale Air Quality (CMAQ) model was applied to predict ambient gaseous and particulate concentrations during 2001 to 2010 in 15 hospital referral regions (HRRs) using a 36-km horizontal resolution domain. An inverse distance weighting based method was applied to produce exposure estimates based on observation-fused regional pollutant concentration fields using the differences between observations and predictions at grid cells where air quality monitors were located. Although the raw CMAQ model is capable of producing satisfying results for O3 and PM2.5 based on EPA guidelines, using the observation data fusing technique to correct CMAQ predictions leads to significant improvement of model performance for all gaseous and particulate pollutants. Regional average concentrations were calculated using five different methods: 1) inverse distance weighting of observation data alone, 2) raw CMAQ results, 3) observation-fused CMAQ results, 4) population-averaged raw CMAQ results and 5) population-averaged fused CMAQ results. It shows that while O3 (as well as NOx) monitoring networks in the HRR regions are dense enough to provide consistent regional average exposure estimation based on monitoring data alone, PM2.5 observation sites (as well as monitors for CO, SO2, PM10 and PM2.5 components) are usually sparse and the difference between the average concentrations estimated by the inverse distance interpolated observations, raw CMAQ and fused CMAQ results can be significantly different. Population-weighted average should be used to account spatial variation in pollutant concentration and population density. Using raw CMAQ results or observations alone might lead to significant biases in health outcome analyses. PMID:24747248

Improved mb-Ms Discrimination Using mb(P-coda) and MsU with Application to the Six North Korean Nuclear Tests

NASA Astrophysics Data System (ADS)

Napoli, V.; Yoo, S. H.; Russell, D. R.

2017-12-01

To improve discrimination of small explosions and earthquakes, we developed a new magnitude scale based on the standard Ms:mb discrimination method. In place of 20 second Ms measurements we developed a unified Rayleigh and Love wave magnitude scale (MsU) that is designed to maximize available information from single stations and then combine magnitude estimates into network averages. Additionally, in place of mb(P) measurements we developed an mb(P-Coda) magnitude scale as the properties of the coda make sparse network mb(P-Coda) more robust and less variable than network mb(P) estimates. A previous mb:MsU study conducted in 2013 in the Korean Peninsula shows that the use of MsU in place of standard 20 second Ms, leads to increased population separation and reduced scattering. The goals of a combined mb(P-coda):MsU scale are reducing scatter, ensuring applicability at small magnitudes with sparse networks, and improving the overall distribution for mb:Ms earthquake and explosion populations. To test this method we are calculating mb(P-coda)and MsU for a catalog earthquakes located in and near the Korean Peninsula, for the six North Korean nuclear tests (4.1 < mb < 6.3) and for the 3 aftershocks to date that occurred after the sixth test (2.6 < ML < 4.0). Compared to the previous 2013 study, we expect to see greater separation in the populations and less scattering with the inclusion of mb(P-coda) and with the implementation of additional filters for MsU to improve signal-to-noise levels; this includes S-transform filtering for polarization and off-azimuth signal reduction at regional distances. As we are expanding our database of mb(P-coda):MsU measurements in the Korean Peninsula to determine the earthquake and explosion distribution, this research will address the limitations and potential for discriminating small magnitude events using sparse networks.

Development of a Web-Accessible Population Pharmacokinetic Service—Hemophilia (WAPPS-Hemo): Study Protocol

PubMed Central

Foster, Gary; Navarro-Ruan, Tamara; McEneny-King, Alanna; Edginton, Andrea N; Thabane, Lehana

2016-01-01

Background Individual pharmacokinetic assessment is a critical component of tailored prophylaxis for hemophilia patients. Population pharmacokinetics allows using individual sparse data, thus simplifying individual pharmacokinetic studies. Implementing population pharmacokinetics capacity for the hemophilia community is beyond individual reach and requires a system effort. Objective The Web-Accessible Population Pharmacokinetic Service—Hemophilia (WAPPS-Hemo) project aims to assemble a database of patient pharmacokinetic data for all existing factor concentrates, develop and validate population pharmacokinetics models, and integrate these models within a Web-based calculator for individualized pharmacokinetic estimation in patients at participating treatment centers. Methods Individual pharmacokinetic studies on factor VIII and IX concentrates will be sourced from pharmaceutical companies and independent investigators. All factor concentrate manufacturers, hemophilia treatment centers (HTCs), and independent investigators (identified via a systematic review of the literature) having on file pharmacokinetic data and willing to contribute full or sparse pharmacokinetic data will be eligible for participation. Multicompartmental modeling will be performed using a mixed-model approach for derivation and Bayesian forecasting for estimation of individual sparse data. NONMEM (ICON Development Solutions) will be used as modeling software. Results The WAPPS-Hemo research network has been launched and is currently joined by 30 HTCs from across the world. We have gathered dense individual pharmacokinetic data on 878 subjects, including several replicates, on 21 different molecules from 17 different sources. We have collected sparse individual pharmacokinetic data on 289 subjects from the participating centers through the testing phase of the WAPPS-Hemo Web interface. We have developed prototypal population pharmacokinetics models for 11 molecules. The WAPPS-Hemo website (available at www.wapps-hemo.org, version 2.4), with core functionalities allowing hemophilia treaters to obtain individual pharmacokinetic estimates on sparse data points after 1 or more infusions of a factor concentrate, was launched for use within the research network in July 2015. Conclusions The WAPPS-Hemo project and research network aims to make it easier to perform individual pharmacokinetic assessments on a reduced number of plasma samples by adoption of a population pharmacokinetics approach. The project will also gather data to substantially enhance the current knowledge about factor concentrate pharmacokinetics and sources of its variability in target populations. Trial Registration ClinicalTrials.gov NCT02061072; https://clinicaltrials.gov/ct2/show/NCT02061072 (Archived by WebCite at http://www.webcitation.org/6mRK9bKP6) PMID:27977390

Helicopter-based emergency medical services for a sparsely populated region: A study of 42,500 dispatches.

PubMed

Østerås, Ø; Brattebø, G; Heltne, J-K

2016-05-01

The Helicopter Emergency Medical Service (HEMS) in Norway is operated day and night, despite challenging geography and weather. In Western Norway, three ambulance helicopters, with a rapid response car as an alternative, cover close to 1 million inhabitants in an area of 45,000 km(2) . Our objective was to assess patterns of emergency medical problems and treatments in HEMS in a geographically large, but sparsely populated region. Data from all HEMS dispatches during 2004-2013 were assessed retrospectively. Information was analyzed with respect to patient treatment and characteristics, in addition to variations in services use during the day, week, and seasons. A total of 42,456 dispatches were analyzed. One third of the patients encountered were severely ill or injured, and two thirds of these received advanced treatment. Median activation time and on-scene time in primary helicopter missions were 5 and 11 min, respectively. Most patients (95%) were reached within 45 min by helicopter or rapid response car. Patterns of use did not change. More than one third of all dispatches were declined or aborted, mostly due to no longer medical indication, bad weather conditions, or competing missions. One third of the patients encountered were severely ill or injured, and more than two thirds of these received advanced treatment. HEMS use did not change over the 10-year period, however HEMS use peaked during daytime, weekends, and the summer. More than one third of all dispatches were declined or aborted. © 2015 The Authors. Acta Anaesthesiologica Scandinavica published by John Wiley & Sons Ltd on behalf of Acta Anaesthesiologica Scandinavica Foundation.

A populous intermediate-age open cluster and evidence of an embedded cluster among the FSR globular cluster candidates

NASA Astrophysics Data System (ADS)

Bica, E.; Bonatto, C.

2008-03-01

We study the nature of the globular cluster (GC) candidates FSR 1603 and FSR1755 selected from the catalogue of Froebrich, Scholz & Raftery. Their properties are investigated with Two-Micron All-Sky Survey field-star decontaminated photometry, which is used to build colour-magnitude diagrams (CMDs) and stellar radial density profiles. FSR1603 has the open cluster Ruprecht 101 as optical counterpart, and we show it to be a massive intermediate-age cluster. Relevant parameters of FSR1603 are the age ~1Gyr, distance from the Sun dsolar ~ 2.7kpc, Galactocentric distance RGC ~ 6.4kpc, core radius RC ~ 1.1pc, mass function slope χ ~ 1.8, observed stellar mass (for stars with mass in the range 1.27 <= m <= 2.03Msolar) Mobs ~ 500Msolar and a total (extrapolated to m = 0.08Msolar) stellar mass Mtot ~ 2300Msolar. FSR1755, on the other hand, is not a populous cluster. It may be a sparse young cluster embedded in the HII region Sh2-3, subject to an absorption AV ~ 4.1, located at dsolar ~ 1.3kpc. Important field-star contamination, spatially variable heavy dust obscuration, even in Ks, and gas emission characterize its field. A nearly vertical, sparse blue stellar sequence shows up in the CMDs.

Carpinus tibetana (Betulaceae), a new species from southeast Tibet, China

PubMed Central

Lu, Zhiqiang; Li, Ying; Yang, Xiaoyue; Liu, Jianquan

2018-01-01

Abstract A new species Carpinus tibetana Z. Qiang Lu & J. Quan Liu from southeast Tibet is described and illustrated. The specimens of this new species were previously identified and placed under C. monbeigiana Hand.-Mazz. or C. mollicoma Hu. However, the specimens from southeast Tibet differ from those of C. monbeigiana from other regions with more lateral veins (19–24 vs 14–18) on each side of the midvein and dense pubescence on the abaxial leaf surface, while from those of C. mollicoma from other regions differ by nutlet with dense resinous glands and glabrous or sparsely villous at apex. Principal Component Analyses based on morphometric characters recognise the Tibetan populations as a separate group. Nuclear ribosomal ITS sequence variations show stable and distinct genetic divergences between the Tibetan populations and C. monbeigiana or C. mollicoma by two or three fixed nucleotide mutations. Phylogenetic analysis also identified three respective genetic clusters and the C. mollicoma cluster diverged early. In addition, the Tibetan populations show a disjunct geographic isolation from the other two species. Therefore, C. tibetana, based on the Tibetan populations, is here erected as a new species, distinctly different from C. monbeigiana and C. mollicoma. PMID:29750069

Carpinus tibetana (Betulaceae), a new species from southeast Tibet, China.

PubMed

Lu, Zhiqiang; Li, Ying; Yang, Xiaoyue; Liu, Jianquan

2018-01-01

A new species Carpinus tibetana Z. Qiang Lu & J. Quan Liu from southeast Tibet is described and illustrated. The specimens of this new species were previously identified and placed under C. monbeigiana Hand.-Mazz. or C. mollicoma Hu. However, the specimens from southeast Tibet differ from those of C. monbeigiana from other regions with more lateral veins (19-24 vs 14-18) on each side of the midvein and dense pubescence on the abaxial leaf surface, while from those of C. mollicoma from other regions differ by nutlet with dense resinous glands and glabrous or sparsely villous at apex. Principal Component Analyses based on morphometric characters recognise the Tibetan populations as a separate group. Nuclear ribosomal ITS sequence variations show stable and distinct genetic divergences between the Tibetan populations and C. monbeigiana or C. mollicoma by two or three fixed nucleotide mutations. Phylogenetic analysis also identified three respective genetic clusters and the C. mollicoma cluster diverged early. In addition, the Tibetan populations show a disjunct geographic isolation from the other two species. Therefore, C. tibetana , based on the Tibetan populations, is here erected as a new species, distinctly different from C. monbeigiana and C. mollicoma .

Investments in blood safety improve the availability of blood to underserved areas in a sub-Saharan African country

PubMed Central

Pitman, J. P.; Wilkinson, R.; Basavaraju, S. V.; von Finckenstein, B.; Sibinga, C. Smit; Marfin, A. A.; Postma, M. J.; Mataranyika, M.; Tobias, J.; Lowrance, D. W.

2015-01-01

Background and Objectives Since 2004, several African countries, including Namibia, have received assistance from the U.S. President’s Emergency Plan for AIDS Relief (PEPFAR). Gains have been documented in the safety and number of collected units in these countries, but the distribution of blood has not been described. Materials and Methods Nine years of data on blood requests and issues from Namibia were stratified by region to describe temporal and spatial changes in the number and type of blood components issued to Namibian healthcare facilities nationally. Results Between 2004 and 2007 (early years of PEPFAR support) and 2008–2011 (peak years of PEPFAR support), the average number of red cell units issued annually increased by 23.5% in seven densely populated but less-developed regions in northern Namibia; by 30% in two regions with urban centres; and by 35.1% in four sparsely populated rural regions. Conclusion Investments in blood safety and a policy decision to emphasize distribution of blood to underserved regions improved blood availability in remote rural areas and increased the proportion of units distributed as components. However, disparities persist in the distribution of blood between Namibia’s urban and rural regions. PMID:26478742

A Probabilistic Tsunami Hazard Study of the Auckland Region, Part I: Propagation Modelling and Tsunami Hazard Assessment at the Shoreline

NASA Astrophysics Data System (ADS)

Power, William; Wang, Xiaoming; Lane, Emily; Gillibrand, Philip

2013-09-01

Regional source tsunamis represent a potentially devastating threat to coastal communities in New Zealand, yet are infrequent events for which little historical information is available. It is therefore essential to develop robust methods for quantitatively estimating the hazards posed, so that effective mitigation measures can be implemented. We develop a probabilistic model for the tsunami hazard posed to the Auckland region of New Zealand from the Kermadec Trench and the southern New Hebrides Trench subduction zones. An innovative feature of our model is the systematic analysis of uncertainty regarding the magnitude-frequency distribution of earthquakes in the source regions. The methodology is first used to estimate the tsunami hazard at the coastline, and then used to produce a set of scenarios that can be applied to produce probabilistic maps of tsunami inundation for the study region; the production of these maps is described in part II. We find that the 2,500 year return period regional source tsunami hazard for the densely populated east coast of Auckland is dominated by events originating in the Kermadec Trench, while the equivalent hazard to the sparsely populated west coast is approximately equally due to events on the Kermadec Trench and the southern New Hebrides Trench.

Limited-memory trust-region methods for sparse relaxation

NASA Astrophysics Data System (ADS)

Adhikari, Lasith; DeGuchy, Omar; Erway, Jennifer B.; Lockhart, Shelby; Marcia, Roummel F.

2017-08-01

In this paper, we solve the l2-l1 sparse recovery problem by transforming the objective function of this problem into an unconstrained differentiable function and applying a limited-memory trust-region method. Unlike gradient projection-type methods, which uses only the current gradient, our approach uses gradients from previous iterations to obtain a more accurate Hessian approximation. Numerical experiments show that our proposed approach eliminates spurious solutions more effectively while improving computational time.

Polarization-independent tunable spectral slicing filter in Ti:LiNbO3.

PubMed

Rabelo, Renato C; Eknoyan, Ohannes; Taylor, Henry F

2011-02-01

A two-port polarization-independent tunable spectral slicing filter at the 1530 nm wavelength regime is presented. The design utilizes an asymmetric interferometer with a sparse index grating along its arms. The sparse grating makes it possible to select equally spaced frequency channels from an incident WDM signal and to place nulls between them to coincide with the signal comb frequency. The number of selected channels and nulls between them depends on the number of coupling regions used in the sparse grating. The free spectral range depends on the spacing between the coupling regions. The Z-transform method is used to synthesize the filter and determine the spectral response. The operation of a device with six coupling regions is demonstrated, and good agreement with theoretical predictions is obtained. A 3 dB bandwidth of ∼1 nm and thermal tuning over a range of ∼13 nm are measured.

Redistribution population data across a regular spatial grid according to buildings characteristics

NASA Astrophysics Data System (ADS)

Calka, Beata; Bielecka, Elzbieta; Zdunkiewicz, Katarzyna

2016-12-01

Population data are generally provided by state census organisations at the predefined census enumeration units. However, these datasets very are often required at userdefined spatial units that differ from the census output levels. A number of population estimation techniques have been developed to address these problems. This article is one of those attempts aimed at improving county level population estimates by using spatial disaggregation models with support of buildings characteristic, derived from national topographic database, and average area of a flat. The experimental gridded population surface was created for Opatów county, sparsely populated rural region located in Central Poland. The method relies on geolocation of population counts in buildings, taking into account the building volume and structural building type and then aggregation the people total in 1 km quadrilateral grid. The overall quality of population distribution surface expressed by the mean of RMSE equals 9 persons, and the MAE equals 0.01. We also discovered that nearly 20% of total county area is unpopulated and 80% of people lived on 33% of the county territory.

Multiscale Region-Level VHR Image Change Detection via Sparse Change Descriptor and Robust Discriminative Dictionary Learning

PubMed Central

Xu, Yuan; Ding, Kun; Huo, Chunlei; Zhong, Zisha; Li, Haichang; Pan, Chunhong

2015-01-01

Very high resolution (VHR) image change detection is challenging due to the low discriminative ability of change feature and the difficulty of change decision in utilizing the multilevel contextual information. Most change feature extraction techniques put emphasis on the change degree description (i.e., in what degree the changes have happened), while they ignore the change pattern description (i.e., how the changes changed), which is of equal importance in characterizing the change signatures. Moreover, the simultaneous consideration of the classification robust to the registration noise and the multiscale region-consistent fusion is often neglected in change decision. To overcome such drawbacks, in this paper, a novel VHR image change detection method is proposed based on sparse change descriptor and robust discriminative dictionary learning. Sparse change descriptor combines the change degree component and the change pattern component, which are encoded by the sparse representation error and the morphological profile feature, respectively. Robust change decision is conducted by multiscale region-consistent fusion, which is implemented by the superpixel-level cosparse representation with robust discriminative dictionary and the conditional random field model. Experimental results confirm the effectiveness of the proposed change detection technique. PMID:25918748

Eight luminous early-type galaxies in nearby pairs and sparse groups. I. Stellar populations spatially analysed

NASA Astrophysics Data System (ADS)

Rosa, D. A.; Milone, A. C.; Krabbe, A. C.; Rodrigues, I.

2018-06-01

We present a detailed spatial analysis of stellar populations based on long-slit optical spectra in a sample of eight luminous early-type galaxies selected from nearby sparse groups and pairs, three of them may have interaction with another galaxy of similar mass. We have spatially measured luminosity-weighted averages of age, [M/H], [Fe/H], and [α /Fe] in the sample galaxies to add empirical data relative to the influence of galaxy mass, environment, interaction, and AGN feedback in their formation and evolution. The stellar population of the individual galaxies were determined through the well-established stellar population synthesis code starlight using semi-empirical simple stellar population models. Radial variations of luminosity- weighted means of age, [M/H], [Fe/H], and [α /Fe] were quantified up to half of the effective radius of each galaxy. We found trends between representative values of age, [M/H], [α /Fe], and the nuclear stellar velocity dispersion. There are also relations between the metallicity/age gradients and the velocity dispersion. Contributions of 1-4 Gyr old stellar populations were quantified in IC 5328 and NGC 6758 as well as 4-8 Gyr old ones in NGC 5812. Extended gas is present in IC 5328, NGC 1052, NGC 1209, and NGC 6758, and the presence of a LINER is identified in all these galaxies. The regions up to one effective radius of all galaxies are basically dominated by α -enhanced metal-rich old stellar populations likely due to rapid star formation episodes that induced efficient chemical enrichment. On average, the age and [α /Fe] gradients are null and the [M/H] gradients are negative, although discordant cases were found. We found no correlation between the stellar population properties and the LINER presence as well as between the stellar properties and environment or gravitational interaction, suggesting that the influence of progenitor mass cannot be discarded in the formation and evolution of early-type galaxies.

A sparse differential clustering algorithm for tracing cell type changes via single-cell RNA-sequencing data

PubMed Central

Barron, Martin; Zhang, Siyuan

2018-01-01

Abstract Cell types in cell populations change as the condition changes: some cell types die out, new cell types may emerge and surviving cell types evolve to adapt to the new condition. Using single-cell RNA-sequencing data that measure the gene expression of cells before and after the condition change, we propose an algorithm, SparseDC, which identifies cell types, traces their changes across conditions and identifies genes which are marker genes for these changes. By solving a unified optimization problem, SparseDC completes all three tasks simultaneously. SparseDC is highly computationally efficient and demonstrates its accuracy on both simulated and real data. PMID:29140455

Cerebellar Functional Parcellation Using Sparse Dictionary Learning Clustering.

PubMed

Wang, Changqing; Kipping, Judy; Bao, Chenglong; Ji, Hui; Qiu, Anqi

2016-01-01

The human cerebellum has recently been discovered to contribute to cognition and emotion beyond the planning and execution of movement, suggesting its functional heterogeneity. We aimed to identify the functional parcellation of the cerebellum using information from resting-state functional magnetic resonance imaging (rs-fMRI). For this, we introduced a new data-driven decomposition-based functional parcellation algorithm, called Sparse Dictionary Learning Clustering (SDLC). SDLC integrates dictionary learning, sparse representation of rs-fMRI, and k-means clustering into one optimization problem. The dictionary is comprised of an over-complete set of time course signals, with which a sparse representation of rs-fMRI signals can be constructed. Cerebellar functional regions were then identified using k-means clustering based on the sparse representation of rs-fMRI signals. We solved SDLC using a multi-block hybrid proximal alternating method that guarantees strong convergence. We evaluated the reliability of SDLC and benchmarked its classification accuracy against other clustering techniques using simulated data. We then demonstrated that SDLC can identify biologically reasonable functional regions of the cerebellum as estimated by their cerebello-cortical functional connectivity. We further provided new insights into the cerebello-cortical functional organization in children.

New methods for sampling sparse populations

Treesearch

Anna Ringvall

2007-01-01

To improve surveys of sparse objects, methods that use auxiliary information have been suggested. Guided transect sampling uses prior information, e.g., from aerial photographs, for the layout of survey strips. Instead of being laid out straight, the strips will wind between potentially more interesting areas. 3P sampling (probability proportional to prediction) uses...

Multiple View Zenith Angle Observations of Reflectance From Ponderosa Pine Stands

NASA Technical Reports Server (NTRS)

Johnson, Lee F.; Lawless, James G. (Technical Monitor)

1994-01-01

Reflectance factors (RF(lambda)) from dense and sparse ponderosa pine (Pinus ponderosa) stands, derived from radiance data collected in the solar principal plane by the Advanced Solid-State Array Spectro-radiometer (ASAS), were examined as a function of view zenith angle (theta(sub v)). RF(lambda) was maximized with theta(sub v) nearest the solar retrodirection, and minimized near the specular direction throughout the ASAS spectral region. The dense stand had much higher RF anisotropy (ma)dmurn RF is minimum RF) in the red region than did the sparse stand (relative differences of 5.3 vs. 2.75, respectively), as a function of theta(sub v), due to the shadow component in the canopy. Anisotropy in the near-infrared (NIR) was more similar between the two stands (2.5 in the dense stand and 2.25 in the sparse stand); the dense stand exhibited a greater hotspot effect than 20 the sparse stand in this spectral region. Two common vegetation transforms, the NIR/red ratio and the normalized difference vegetation index (NDVI), both showed a theta(sub v) dependence for the dense stand. Minimum values occurred near the retrodirection and maximum values occurred near the specular direction. Greater relative differences were noted for the NIR/red ratio (2.1) than for the NDVI (1.3). The sparse stand showed no obvious dependence on theta(sub v) for either transform, except for slightly elevated values toward the specular direction.

Direct measurement of magnon temperature: new insight into magnon-phonon coupling in magnetic insulators.

PubMed

Agrawal, M; Vasyuchka, V I; Serga, A A; Karenowska, A D; Melkov, G A; Hillebrands, B

2013-09-06

We present spatially resolved measurements of the magnon temperature in a magnetic insulator subject to a thermal gradient. Our data reveal an unexpectedly close correspondence between the spatial dependencies of the exchange magnon and phonon temperatures. These results indicate that if--as is currently thought--the transverse spin Seebeck effect is caused by a temperature difference between the magnon and phonon baths, it must be the case that the magnon temperature is spectrally nonuniform and that the effect is driven by the sparsely populated dipolar region of the magnon spectrum.

Analog system for computing sparse codes

DOEpatents

Rozell, Christopher John; Johnson, Don Herrick; Baraniuk, Richard Gordon; Olshausen, Bruno A.; Ortman, Robert Lowell

2010-08-24

A parallel dynamical system for computing sparse representations of data, i.e., where the data can be fully represented in terms of a small number of non-zero code elements, and for reconstructing compressively sensed images. The system is based on the principles of thresholding and local competition that solves a family of sparse approximation problems corresponding to various sparsity metrics. The system utilizes Locally Competitive Algorithms (LCAs), nodes in a population continually compete with neighboring units using (usually one-way) lateral inhibition to calculate coefficients representing an input in an over complete dictionary.

Assessing sensory versus optogenetic network activation by combining (o)fMRI with optical Ca2+ recordings.

PubMed

Schmid, Florian; Wachsmuth, Lydia; Schwalm, Miriam; Prouvot, Pierre-Hugues; Jubal, Eduardo Rosales; Fois, Consuelo; Pramanik, Gautam; Zimmer, Claus; Faber, Cornelius; Stroh, Albrecht

2016-11-01

Encoding of sensory inputs in the cortex is characterized by sparse neuronal network activation. Optogenetic stimulation has previously been combined with fMRI (ofMRI) to probe functional networks. However, for a quantitative optogenetic probing of sensory-driven sparse network activation, the level of similarity between sensory and optogenetic network activation needs to be explored. Here, we complement ofMRI with optic fiber-based population Ca 2+ recordings for a region-specific readout of neuronal spiking activity in rat brain. Comparing Ca 2+ responses to the blood oxygenation level-dependent signal upon sensory stimulation with increasing frequencies showed adaptation of Ca 2+ transients contrasted by an increase of blood oxygenation level-dependent responses, indicating that the optical recordings convey complementary information on neuronal network activity to the corresponding hemodynamic response. To study the similarity of optogenetic and sensory activation, we quantified the density of cells expressing channelrhodopsin-2 and modeled light propagation in the tissue. We estimated the effectively illuminated volume and numbers of optogenetically stimulated neurons, being indicative of sparse activation. At the functional level, upon either sensory or optogenetic stimulation we detected single-peak short-latency primary Ca 2+ responses with similar amplitudes and found that blood oxygenation level-dependent responses showed similar time courses. These data suggest that ofMRI can serve as a representative model for functional brain mapping. © The Author(s) 2015.

Development of a Web-Accessible Population Pharmacokinetic Service-Hemophilia (WAPPS-Hemo): Study Protocol.

PubMed

Iorio, Alfonso; Keepanasseril, Arun; Foster, Gary; Navarro-Ruan, Tamara; McEneny-King, Alanna; Edginton, Andrea N; Thabane, Lehana

2016-12-15

Individual pharmacokinetic assessment is a critical component of tailored prophylaxis for hemophilia patients. Population pharmacokinetics allows using individual sparse data, thus simplifying individual pharmacokinetic studies. Implementing population pharmacokinetics capacity for the hemophilia community is beyond individual reach and requires a system effort. The Web-Accessible Population Pharmacokinetic Service-Hemophilia (WAPPS-Hemo) project aims to assemble a database of patient pharmacokinetic data for all existing factor concentrates, develop and validate population pharmacokinetics models, and integrate these models within a Web-based calculator for individualized pharmacokinetic estimation in patients at participating treatment centers. Individual pharmacokinetic studies on factor VIII and IX concentrates will be sourced from pharmaceutical companies and independent investigators. All factor concentrate manufacturers, hemophilia treatment centers (HTCs), and independent investigators (identified via a systematic review of the literature) having on file pharmacokinetic data and willing to contribute full or sparse pharmacokinetic data will be eligible for participation. Multicompartmental modeling will be performed using a mixed-model approach for derivation and Bayesian forecasting for estimation of individual sparse data. NONMEM (ICON Development Solutions) will be used as modeling software. The WAPPS-Hemo research network has been launched and is currently joined by 30 HTCs from across the world. We have gathered dense individual pharmacokinetic data on 878 subjects, including several replicates, on 21 different molecules from 17 different sources. We have collected sparse individual pharmacokinetic data on 289 subjects from the participating centers through the testing phase of the WAPPS-Hemo Web interface. We have developed prototypal population pharmacokinetics models for 11 molecules. The WAPPS-Hemo website (available at www.wapps-hemo.org, version 2.4), with core functionalities allowing hemophilia treaters to obtain individual pharmacokinetic estimates on sparse data points after 1 or more infusions of a factor concentrate, was launched for use within the research network in July 2015. The WAPPS-Hemo project and research network aims to make it easier to perform individual pharmacokinetic assessments on a reduced number of plasma samples by adoption of a population pharmacokinetics approach. The project will also gather data to substantially enhance the current knowledge about factor concentrate pharmacokinetics and sources of its variability in target populations. ClinicalTrials.gov NCT02061072; https://clinicaltrials.gov/ct2/show/NCT02061072 (Archived by WebCite at http://www.webcitation.org/6mRK9bKP6). ©Alfonso Iorio, Arun Keepanasseril, Gary Foster, Tamara Navarro-Ruan, Alanna McEneny-King, Andrea N Edginton, Lehana Thabane. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 15.12.2016.

Automatic segmentation of right ventricle on ultrasound images using sparse matrix transform and level set

NASA Astrophysics Data System (ADS)

Qin, Xulei; Cong, Zhibin; Halig, Luma V.; Fei, Baowei

2013-03-01

An automatic framework is proposed to segment right ventricle on ultrasound images. This method can automatically segment both epicardial and endocardial boundaries from a continuous echocardiography series by combining sparse matrix transform (SMT), a training model, and a localized region based level set. First, the sparse matrix transform extracts main motion regions of myocardium as eigenimages by analyzing statistical information of these images. Second, a training model of right ventricle is registered to the extracted eigenimages in order to automatically detect the main location of the right ventricle and the corresponding transform relationship between the training model and the SMT-extracted results in the series. Third, the training model is then adjusted as an adapted initialization for the segmentation of each image in the series. Finally, based on the adapted initializations, a localized region based level set algorithm is applied to segment both epicardial and endocardial boundaries of the right ventricle from the whole series. Experimental results from real subject data validated the performance of the proposed framework in segmenting right ventricle from echocardiography. The mean Dice scores for both epicardial and endocardial boundaries are 89.1%+/-2.3% and 83.6+/-7.3%, respectively. The automatic segmentation method based on sparse matrix transform and level set can provide a useful tool for quantitative cardiac imaging.

Two-stage sparse coding of region covariance via Log-Euclidean kernels to detect saliency.

PubMed

Zhang, Ying-Ying; Yang, Cai; Zhang, Ping

2017-05-01

In this paper, we present a novel bottom-up saliency detection algorithm from the perspective of covariance matrices on a Riemannian manifold. Each superpixel is described by a region covariance matrix on Riemannian Manifolds. We carry out a two-stage sparse coding scheme via Log-Euclidean kernels to extract salient objects efficiently. In the first stage, given background dictionary on image borders, sparse coding of each region covariance via Log-Euclidean kernels is performed. The reconstruction error on the background dictionary is regarded as the initial saliency of each superpixel. In the second stage, an improvement of the initial result is achieved by calculating reconstruction errors of the superpixels on foreground dictionary, which is extracted from the first stage saliency map. The sparse coding in the second stage is similar to the first stage, but is able to effectively highlight the salient objects uniformly from the background. Finally, three post-processing methods-highlight-inhibition function, context-based saliency weighting, and the graph cut-are adopted to further refine the saliency map. Experiments on four public benchmark datasets show that the proposed algorithm outperforms the state-of-the-art methods in terms of precision, recall and mean absolute error, and demonstrate the robustness and efficiency of the proposed method. Copyright © 2017 Elsevier Ltd. All rights reserved.

Implementation of Ebola case-finding using a village chieftaincy taskforce in a remote outbreak - Liberia, 2014.

PubMed

Hagan, José E; Smith, Wilmot; Pillai, Satish K; Yeoman, Kristin; Gupta, Sundeep; Neatherlin, John; Slutsker, Laurence; Lindblade, Kim A; DeCock, Kevin M; Kateh, Francis; Nyenswah, Tolbert

2015-02-27

On October 16, 2014, a woman aged 48 years traveled from Monrovia, Liberia, to the Kayah region of Rivercess County, a remote, resource-poor, and sparsely populated region of Liberia, and died on October 21 with symptoms compatible with Ebola virus disease (Ebola). She was buried in accordance with local tradition, which included grooming, touching, and kissing the body by family and other community members while it was being prepared for burial. During October 24-November 12, eight persons with probable and 13 with confirmed Ebola epidemiologically linked to the deceased woman had onset of symptoms. Nineteen of the 21 persons lived in five nearby villages in Kayah region; two, both with probable cases, lived in neighboring Grand Bassa County (Figure). Four of the confirmed cases in Kayah were linked by time and location, although the source case could not be determined because the patients had more than one exposure.

Astronomical Site Survey for Mountain Wumingshan Area in Western Sichuan Based on GIS

NASA Astrophysics Data System (ADS)

Wu, N.; Liu, Y.; Zhao, H. M.

2016-11-01

In the Western-China Astronomical Site Survey project, we utilize the Geographic Information System (GIS) for the collection of long-term data, in order to investigate and study the Wumingshan (WMS) mountain and its surrounding areas for their geography, geology, climate, meteorology, social and demographic trends. Data analysis results show that the WMS mountain is located in the eastern fold belt of the Tibet Plateau--the typical region of the Hengduan Mountains, which leads to its large elevation, gently trended ridge, and stable geological structure. The highest altitude above the sea level at the WMS is more than 5000 m, but there are population settlements nearby with the low altitude of only 2000-3000 m, which are important for realizing low-level cost logistics conditions for the future headquarter or logistic base. Earthquake landslides and other geological disasters were rarely recorded. The other facts are such as the dry and clean atmosphere, the sparse vegetation, the semi-dry-state land, the perennial prevailing southwest wind, the rain-less winter, and the relatively short rainy-season summer, the location in the heartland of the large Shangri-La, no records of dust storms and the other inclement weather, low cloud coverage, the stability of wind direction, the small wind speed, the high possibility of clear sky, the far distance away from the developed areas in Sichuan and Yunnan provinces, and Tibet Autonomous Region, the sparsely populated people, the slowly developed economy, the peaceful and stable social environment, etc. Specially, in recent years, with the development of the local tourist resources, the traffic conditions in Daocheng have been significantly improved. With high quality highway maintenance and daily air transport capacity, the transportation of land and aviation is rarely interrupted due to snowing, which often happens in high plateau regions. Therefore, the WMS area possesses the potential conditions to establish the future high altitude observatory, and it is really a very rare astronomical site resource.

The application of low-rank and sparse decomposition method in the field of climatology

NASA Astrophysics Data System (ADS)

Gupta, Nitika; Bhaskaran, Prasad K.

2018-04-01

The present study reports a low-rank and sparse decomposition method that separates the mean and the variability of a climate data field. Until now, the application of this technique was limited only in areas such as image processing, web data ranking, and bioinformatics data analysis. In climate science, this method exactly separates the original data into a set of low-rank and sparse components, wherein the low-rank components depict the linearly correlated dataset (expected or mean behavior), and the sparse component represents the variation or perturbation in the dataset from its mean behavior. The study attempts to verify the efficacy of this proposed technique in the field of climatology with two examples of real world. The first example attempts this technique on the maximum wind-speed (MWS) data for the Indian Ocean (IO) region. The study brings to light a decadal reversal pattern in the MWS for the North Indian Ocean (NIO) during the months of June, July, and August (JJA). The second example deals with the sea surface temperature (SST) data for the Bay of Bengal region that exhibits a distinct pattern in the sparse component. The study highlights the importance of the proposed technique used for interpretation and visualization of climate data.

Segmentation of Hyperacute Cerebral Infarcts Based on Sparse Representation of Diffusion Weighted Imaging.

PubMed

Zhang, Xiaodong; Jing, Shasha; Gao, Peiyi; Xue, Jing; Su, Lu; Li, Weiping; Ren, Lijie; Hu, Qingmao

2016-01-01

Segmentation of infarcts at hyperacute stage is challenging as they exhibit substantial variability which may even be hard for experts to delineate manually. In this paper, a sparse representation based classification method is explored. For each patient, four volumetric data items including three volumes of diffusion weighted imaging and a computed asymmetry map are employed to extract patch features which are then fed to dictionary learning and classification based on sparse representation. Elastic net is adopted to replace the traditional L 0 -norm/ L 1 -norm constraints on sparse representation to stabilize sparse code. To decrease computation cost and to reduce false positives, regions-of-interest are determined to confine candidate infarct voxels. The proposed method has been validated on 98 consecutive patients recruited within 6 hours from onset. It is shown that the proposed method could handle well infarcts with intensity variability and ill-defined edges to yield significantly higher Dice coefficient (0.755 ± 0.118) than the other two methods and their enhanced versions by confining their segmentations within the regions-of-interest (average Dice coefficient less than 0.610). The proposed method could provide a potential tool to quantify infarcts from diffusion weighted imaging at hyperacute stage with accuracy and speed to assist the decision making especially for thrombolytic therapy.

A Participatory Modeling Application of a Distributed Hydrologic Model in Nuevo Leon, Mexico for the 2010 Hurricane Alex Flood Event

NASA Astrophysics Data System (ADS)

Baish, A. S.; Vivoni, E. R.; Payan, J. G.; Robles-Morua, A.; Basile, G. M.

2011-12-01

A distributed hydrologic model can help bring consensus among diverse stakeholders in regional flood planning by producing quantifiable sets of alternative futures. This value is acute in areas with high uncertainties in hydrologic conditions and sparse observations. In this study, we conduct an application of the Triangulated Irregular Network (TIN)-based Real-time Integrated Basin Simulator (tRIBS) in the Santa Catarina basin of Nuevo Leon, Mexico, where Hurricane Alex in July 2010 led to catastrophic flooding of the capital city of Monterrey. Distributed model simulations utilize best-available information on the regional topography, land cover, and soils obtained from Mexican government agencies or analysis of remotely-sensed imagery from MODIS and ASTER. Furthermore, we developed meteorological forcing for the flood event based on multiple data sources, including three local gauge networks, satellite-based estimates from TRMM and PERSIANN, and the North American Land Data Assimilation System (NLDAS). Remotely-sensed data allowed us to quantify rainfall distributions in the upland, rural portions of the Santa Catarina that are sparsely populated and ungauged. Rural areas had significant contributions to the flood event and as a result were considered by stakeholders for flood control measures, including new reservoirs and upland vegetation management. Participatory modeling workshops with the stakeholders revealed a disconnect between urban and rural populations in regard to understanding the hydrologic conditions of the flood event and the effectiveness of existing and potential flood control measures. Despite these challenges, the use of the distributed flood forecasts developed within this participatory framework facilitated building consensus among diverse stakeholders and exploring alternative futures in the basin.

Evolution of opinions on social networks in the presence of competing committed groups.

PubMed

Xie, Jierui; Emenheiser, Jeffrey; Kirby, Matthew; Sreenivasan, Sameet; Szymanski, Boleslaw K; Korniss, Gyorgy

2012-01-01

Public opinion is often affected by the presence of committed groups of individuals dedicated to competing points of view. Using a model of pairwise social influence, we study how the presence of such groups within social networks affects the outcome and the speed of evolution of the overall opinion on the network. Earlier work indicated that a single committed group within a dense social network can cause the entire network to quickly adopt the group's opinion (in times scaling logarithmically with the network size), so long as the committed group constitutes more than about 10% of the population (with the findings being qualitatively similar for sparse networks as well). Here we study the more general case of opinion evolution when two groups committed to distinct, competing opinions A and B, and constituting fractions pA and pB of the total population respectively, are present in the network. We show for stylized social networks (including Erdös-Rényi random graphs and Barabási-Albert scale-free networks) that the phase diagram of this system in parameter space (pA,pB) consists of two regions, one where two stable steady-states coexist, and the remaining where only a single stable steady-state exists. These two regions are separated by two fold-bifurcation (spinodal) lines which meet tangentially and terminate at a cusp (critical point). We provide further insights to the phase diagram and to the nature of the underlying phase transitions by investigating the model on infinite (mean-field limit), finite complete graphs and finite sparse networks. For the latter case, we also derive the scaling exponent associated with the exponential growth of switching times as a function of the distance from the critical point.

Quality of obstetric care in the sparsely populated sub-arctic area of Norway 2009–2011

PubMed Central

2013-01-01

Background It is challenging to obtain high quality obstetric care in a sparsely populated area. In the subarctic region of Norway, significant distances, weather conditions and seasonable darkness have called for a decentralized care model. We aimed to explore the quality of this care. Methods A retrospective study employing data (2009–11) from the Medical Birth Registry of Norway was initiated. Northern Norwegian and Norwegian figures were compared. Midwife administered maternity units, departments at local and regional specialist hospitals were compared. National registry data on post-caesarean wound infection (2009–2010) was added. Quality of care was measured as rate of multiple pregnancies, caesarean section, post-caesarean wound infection, Apgar score <7, birth weight <2.5 kilos, perineal rupture, stillbirth, eclampsia, pregnancy induced diabetes and vacuum or forceps assisted delivery. There were 15,586 births in 15 delivery units. Results Multiple pregnancies were less common in northern Norway (1.3 vs. 1.7%) (P = 0.02). Less use of vacuum (6.6% vs. 8.3%) (P = 0.01) and forceps (0.9% vs 1.7%) (P < 0.01) assisted delivery was observed. There was no difference with regard to pregnancy induced diabetes, caesarean section, stillbirth, Apgar score < 7 and eclampsia. A significant difference in birth weight < 2.5 kilos (4.7% vs. 5.0%) (P < 0.04) and perineal rupture grade 3 and 4 (1.5% vs. 2.3%) (P < 0.02) were revealed. The post-caesarean wound infection rate was higher (10.5% vs. 7.4%) (P < 0.01). Conclusion Northern Norway had an obstetric care of good quality. Birth weight, multiple pregnancies and post-caesarean wound infection rates should be further elucidated. PMID:24034451

Evolution of Opinions on Social Networks in the Presence of Competing Committed Groups

PubMed Central

Xie, Jierui; Emenheiser, Jeffrey; Kirby, Matthew; Sreenivasan, Sameet; Szymanski, Boleslaw K.; Korniss, Gyorgy

2012-01-01

Public opinion is often affected by the presence of committed groups of individuals dedicated to competing points of view. Using a model of pairwise social influence, we study how the presence of such groups within social networks affects the outcome and the speed of evolution of the overall opinion on the network. Earlier work indicated that a single committed group within a dense social network can cause the entire network to quickly adopt the group's opinion (in times scaling logarithmically with the network size), so long as the committed group constitutes more than about of the population (with the findings being qualitatively similar for sparse networks as well). Here we study the more general case of opinion evolution when two groups committed to distinct, competing opinions and , and constituting fractions and of the total population respectively, are present in the network. We show for stylized social networks (including Erdös-Rényi random graphs and Barabási-Albert scale-free networks) that the phase diagram of this system in parameter space consists of two regions, one where two stable steady-states coexist, and the remaining where only a single stable steady-state exists. These two regions are separated by two fold-bifurcation (spinodal) lines which meet tangentially and terminate at a cusp (critical point). We provide further insights to the phase diagram and to the nature of the underlying phase transitions by investigating the model on infinite (mean-field limit), finite complete graphs and finite sparse networks. For the latter case, we also derive the scaling exponent associated with the exponential growth of switching times as a function of the distance from the critical point. PMID:22448238

Substance abuse associated with elder abuse in the United States.

PubMed

Jogerst, Gerald J; Daly, Jeanette M; Galloway, Lara J; Zheng, Shimin; Xu, Yinghui

2012-01-01

Substance abuse by either victim or perpetrator has long been associated with violence and abuse. Sparse research is available regarding elder abuse and its association with substance abuse. The objective of this study was to evaluate the association of state-reported domestic elder abuse with regional levels of substance abuse. Census demographic and elder abuse data were sorted into substate regions to align with the substance use treatment-planning regions for 2269 US counties. From the 2269 US counties there were 229 substate regions in which there were 213,444 investigations of abuse. For the other Ns (reports and substantiations) there were fewer counties and regions. See first sentence of data analyses and first sentence of results. Elder abuse report rates ranged from .03 to .41% (80 regions), investigation rates .001 to .34% (229 regions), and substantiation rates 0 to .22% (184 regions). Elder abuse investigations and substantiations were associated with various forms of substance abuse. Higher investigation rates were significantly associated with a higher rate of any illicit drug use in the past month, a lower median household income, lower proportion of the population graduated high school, and higher population of Hispanics. Higher substantiation rates were significantly associated with higher rate of illicit drug use in the past month and higher population of Hispanics. It may be worthwhile for administrators of violence programs to pay particular attention to substance abuse among their clients and in their community's environment, especially if older persons are involved. Measures of documented elder abuse at the county level are minimal. To be able to associate substance abuse with elder abuse is a significant finding, realizing that the substance abuse can be by the victim or the perpetrator of elder abuse.

Habitat selection by female swift foxes (Vulpes velox) during the pup-rearing season

USGS Publications Warehouse

Sasmal, Indrani; Jenks, Jonathan A.; Grovenburg, Troy W.; Datta, Shubham; Schroeder, Greg M.; Klaver, Robert W.; Honness, Kevin M.

2011-01-01

The swift fox (Vulpes velox) was historically distributed in western South Dakota including the region surrounding Badlands National Park (BNP). The species declined during the mid-1800s, largely due to habitat loss and poisoning targeted at wolves (Canis lupis) and coyotes (C. latrans). Only a small population of swift foxes near Ardmore, South Dakota persisted. In 2003, an introduction program was initiated at BNP with swift foxes translocated from Colorado and Wyoming. We report on habitat use by female swift foxes during the pup-rearing season (May–July) in 2009. Analyses of location data from 13 radiomarked female foxes indicated disproportional use (P Ŷ = 1.01), sparse vegetation (Ŷ = 1.43) and prairie dog towns (Ŷ = 1.18) in proportion to their availability, whereas they were less likely to use woodland (Ŷ = 0.00), shrubland (Ŷ = 0.14), pasture/agricultural-land (Ŷ = 0.25) and development (Ŷ = 0.16) relative to availability. Swift foxes typically are located in habitats that provide greater visibility, such as shortgrass prairie and areas with sparse vegetation; which allow detection of approaching coyotes (e.g., primary predator of swift foxes).

Tensor Sparse Coding for Positive Definite Matrices.

PubMed

Sivalingam, Ravishankar; Boley, Daniel; Morellas, Vassilios; Papanikolopoulos, Nikos

2013-08-02

In recent years, there has been extensive research on sparse representation of vector-valued signals. In the matrix case, the data points are merely vectorized and treated as vectors thereafter (for e.g., image patches). However, this approach cannot be used for all matrices, as it may destroy the inherent structure of the data. Symmetric positive definite (SPD) matrices constitute one such class of signals, where their implicit structure of positive eigenvalues is lost upon vectorization. This paper proposes a novel sparse coding technique for positive definite matrices, which respects the structure of the Riemannian manifold and preserves the positivity of their eigenvalues, without resorting to vectorization. Synthetic and real-world computer vision experiments with region covariance descriptors demonstrate the need for and the applicability of the new sparse coding model. This work serves to bridge the gap between the sparse modeling paradigm and the space of positive definite matrices.

Tensor sparse coding for positive definite matrices.

PubMed

Sivalingam, Ravishankar; Boley, Daniel; Morellas, Vassilios; Papanikolopoulos, Nikolaos

2014-03-01

In recent years, there has been extensive research on sparse representation of vector-valued signals. In the matrix case, the data points are merely vectorized and treated as vectors thereafter (for example, image patches). However, this approach cannot be used for all matrices, as it may destroy the inherent structure of the data. Symmetric positive definite (SPD) matrices constitute one such class of signals, where their implicit structure of positive eigenvalues is lost upon vectorization. This paper proposes a novel sparse coding technique for positive definite matrices, which respects the structure of the Riemannian manifold and preserves the positivity of their eigenvalues, without resorting to vectorization. Synthetic and real-world computer vision experiments with region covariance descriptors demonstrate the need for and the applicability of the new sparse coding model. This work serves to bridge the gap between the sparse modeling paradigm and the space of positive definite matrices.

The opponent channel population code of sound location is an efficient representation of natural binaural sounds.

PubMed

Młynarski, Wiktor

2015-05-01

In mammalian auditory cortex, sound source position is represented by a population of broadly tuned neurons whose firing is modulated by sounds located at all positions surrounding the animal. Peaks of their tuning curves are concentrated at lateral position, while their slopes are steepest at the interaural midline, allowing for the maximum localization accuracy in that area. These experimental observations contradict initial assumptions that the auditory space is represented as a topographic cortical map. It has been suggested that a "panoramic" code has evolved to match specific demands of the sound localization task. This work provides evidence suggesting that properties of spatial auditory neurons identified experimentally follow from a general design principle- learning a sparse, efficient representation of natural stimuli. Natural binaural sounds were recorded and served as input to a hierarchical sparse-coding model. In the first layer, left and right ear sounds were separately encoded by a population of complex-valued basis functions which separated phase and amplitude. Both parameters are known to carry information relevant for spatial hearing. Monaural input converged in the second layer, which learned a joint representation of amplitude and interaural phase difference. Spatial selectivity of each second-layer unit was measured by exposing the model to natural sound sources recorded at different positions. Obtained tuning curves match well tuning characteristics of neurons in the mammalian auditory cortex. This study connects neuronal coding of the auditory space with natural stimulus statistics and generates new experimental predictions. Moreover, results presented here suggest that cortical regions with seemingly different functions may implement the same computational strategy-efficient coding.

Incidence of tonsillar cancer in northern Sweden: Impact of human papilloma virus.

PubMed

Loizou, Christos; Laurell, Göran; Lindquist, David; Öfverman, Charlotte; Stefansson, Kristina; Nylander, Karin; Olofsson, Katarina

2015-12-01

The incidence rate of tonsillar cancer is increasing worldwide. The current study identifies a parallel increase in the incidence of tonsillar cancer, human papilloma virus (HPV) and p16 expression among a population from northern Sweden, a sparsely populated area, confirming the strong association between p16 and HPV infection in tonsillar tissue. Data from the Swedish Cancer Registry was assessed to identify cases of tonsillar cancer in the northern territorial area of Sweden. HPV DNA was extracted from paraffin embedded diagnostic biopsies and detected by polymerase chain reaction using general primers Gp5+/6+ and CpI/IIG. Expression of p16 was identified by immunochemistry. Patients were grouped into urban or rural residence categories. A total of 214 cases were identified, comprising 155 (72.4%) men and 59 (27.6%) women, and 65 of these patients, who presented between 2000 and 2012, were analyzed. The overall median age for the analyzed patients was 58 years; 48 (74%) were males (median age, 57.5 years) and 17 (26%) were females (median age, 65 years). Of the 65 specimens, 59 (91%) were positive for HPV, and 62 (95%) expressed p16. The incidence of tonsillar cancer in the cohort demonstrated a 2-fold increase between 1990 and 2013; specifically, a 2.7-fold increase was observed in men whilst the female group exhibited only a small increase. These findings demonstrate a strong association between p16 expression and HPV infection in tonsillar malignancies. The incidence of HPV-positive tonsillar cancer has increased in recent years, even in sparsely populated regions, as demonstrated in northern Sweden.

Decline in Chinese lake phosphorus concentration accompanied by shift in sources since 2006

NASA Astrophysics Data System (ADS)

Tong, Yindong; Zhang, Wei; Wang, Xuejun; Couture, Raoul-Marie; Larssen, Thorjørn; Zhao, Yue; Li, Jing; Liang, Huijiao; Liu, Xueyan; Bu, Xiaoge; He, Wei; Zhang, Qianggong; Lin, Yan

2017-07-01

Domestic wastewater and agricultural activities are important sources of nutrient pollutants such as phosphorus and nitrogen. Upon reaching freshwater, these nutrients can lead to extensive growth of harmful algae, which results in eutrophication. Many Chinese lakes are subject to such eutrophication, especially in highly polluted areas, and as such, understanding nutrient fluxes to these lakes offers insights into the varying processes governing pollutant fluxes as well as lake water quality. Here we analyse water quality data, recorded between 2006 and 2014 in 862 freshwater lakes in four geographical regions of China, to assess the input of phosphorus from human activity. We find that improvements in sanitation of both rural and urban domestic wastewater have resulted in large-scale declines in lake phosphorus concentrations in the most populated parts of China. In more sparsely populated regions, diffuse sources such as aquaculture and livestock farming offset this decline. Anthropogenic deforestation and soil erosion may also offset decreases in point sources of pollution. In the light of these regional differences, we suggest that a spatially flexible set of policies for water quality control would be beneficial for the future health of Chinese lakes.

Young Stellar Populations in MYStIX Star-forming Regions: Candidate Protostars

NASA Astrophysics Data System (ADS)

Romine, Gregory; Feigelson, Eric D.; Getman, Konstantin V.; Kuhn, Michael A.; Povich, Matthew S.

2016-12-01

The Massive Young Star-Forming Complex in Infrared and X-ray (MYStIX) project provides a new census on stellar members of massive star-forming regions within 4 kpc. Here the MYStIX Infrared Excess catalog and Chandra-based X-ray photometric catalogs are mined to obtain high-quality samples of Class I protostars using criteria designed to reduce extragalactic and Galactic field star contamination. A total of 1109 MYStIX Candidate Protostars (MCPs) are found in 14 star-forming regions. Most are selected from protoplanetary disk infrared excess emission, but 20% are found from their ultrahard X-ray spectra from heavily absorbed magnetospheric flare emission. Two-thirds of the MCP sample is newly reported here. The resulting samples are strongly spatially associated with molecular cores and filaments on Herschel far-infrared maps. This spatial agreement and other evidence indicate that the MCP sample has high reliability with relatively few “false positives” from contaminating populations. But the limited sensitivity and sparse overlap among the infrared and X-ray subsamples indicate that the sample is very incomplete with many “false negatives.” Maps, tables, and source descriptions are provided to guide further study of star formation in these regions. In particular, the nature of ultrahard X-ray protostellar candidates without known infrared counterparts needs to be elucidated.

Global Estimates of Fine Particulate Matter Using a Combined Geophysical-Statistical Method with Information from Satellites, Models, and Monitors

NASA Technical Reports Server (NTRS)

Van Donkelaar, Aaron; Martin, Randall V.; Brauer, Michael; Hsu, N. Christina; Kahn, Ralph A.; Levy, Robert C.; Lyapustin, Alexei; Sayer, Andrew M.; Winker, David M.

2016-01-01

We estimated global fine particulate matter (PM(sub 2.5)) concentrations using information from satellite-, simulation- and monitor-based sources by applying a Geographically Weighted Regression (GWR) to global geophysically-based satellite-derived PM(sub 2.5) estimates. Aerosol optical depth from multiple satellite products (MISR, MODIS Dark Target, MODIS and SeaWiFS Deep Blue, and MODIS MAIAC) was combined with simulation (GEOS-Chem) based upon their relative uncertainties as determined using ground-based sun photometer (AERONET) observations for 1998-2014. The GWR predictors included simulated aerosol composition and land use information. The resultant PM(sub 2.5) estimates were highly consistent (R(sup 2) equals 0.81) with out-of-sample cross-validated PM(sub 2.5) concentrations from monitors. The global population-weighted annual average PM(sub 2.5) concentrations were 3-fold higher than the 10 micrograms per cubic meter WHO guideline, driven by exposures in Asian and African regions. Estimates in regions with high contributions from mineral dust were associated with higher uncertainty, resulting from both sparse ground-based monitoring, and challenging conditions for retrieval and simulation. This approach demonstrates that the addition of even sparse ground-based measurements to more globally continuous PM(sub 2.5) data sources can yield valuable improvements to PM(sub 2.5) characterization on a global scale.

Improved statistical power with a sparse shape model in detecting an aging effect in the hippocampus and amygdala

NASA Astrophysics Data System (ADS)

Chung, Moo K.; Kim, Seung-Goo; Schaefer, Stacey M.; van Reekum, Carien M.; Peschke-Schmitz, Lara; Sutterer, Matthew J.; Davidson, Richard J.

2014-03-01

The sparse regression framework has been widely used in medical image processing and analysis. However, it has been rarely used in anatomical studies. We present a sparse shape modeling framework using the Laplace- Beltrami (LB) eigenfunctions of the underlying shape and show its improvement of statistical power. Tradition- ally, the LB-eigenfunctions are used as a basis for intrinsically representing surface shapes as a form of Fourier descriptors. To reduce high frequency noise, only the first few terms are used in the expansion and higher frequency terms are simply thrown away. However, some lower frequency terms may not necessarily contribute significantly in reconstructing the surfaces. Motivated by this idea, we present a LB-based method to filter out only the significant eigenfunctions by imposing a sparse penalty. For dense anatomical data such as deformation fields on a surface mesh, the sparse regression behaves like a smoothing process, which will reduce the error of incorrectly detecting false negatives. Hence the statistical power improves. The sparse shape model is then applied in investigating the influence of age on amygdala and hippocampus shapes in the normal population. The advantage of the LB sparse framework is demonstrated by showing the increased statistical power.

Arrangement of the myenteric plexus throughout the gastrointestinal tract of the opossum.

PubMed

Christensen, J; Rick, G A; Robison, B A; Stiles, M J; Wix, M A

1983-10-01

Silver impregnation of the myenteric plexus of the opossum gut was used to find differences among various regions. In the esophagus, the plexus was sparse and ganglia were spaced irregularly, many being parafascicular. Ganglia were sparse in the striated-muscle region, but more frequent in the smooth-muscle region. In the stomach, uniformly spaced ganglia were large and intrafascicular; ganglia were larger in the distal stomach than in the proximal stomach. The proximal stomach contained thick fascicles, called shunt fascicles, radiating from the lesser to the greater curvatures and bypassing ganglia. A thick nerve bundle encircled the pylorus. In the small intestine, the regularly spaced ganglia were large and intrafascicular. In the cecum, they were small and intrafascicular. In the colon, they were large and intrafascicular. Shunt fascicles, like those of the proximal stomach, extended from the rectum into the distal colon. In the rectum, the plexus was sparse, and ganglia were small and distributed irregularly. Many ganglia were parafascicular. Unique knots of tangled fascicles were frequent in the rectum; these were called labyrinthine nodes. The least densely innervated regions of the gut are the lower esophageal sphincter and the rectum. Major differences in the anatomy of the plexus characterize the different regions of the gut.

Infrared moving small target detection based on saliency extraction and image sparse representation

NASA Astrophysics Data System (ADS)

Zhang, Xiaomin; Ren, Kan; Gao, Jin; Li, Chaowei; Gu, Guohua; Wan, Minjie

2016-10-01

Moving small target detection in infrared image is a crucial technique of infrared search and tracking system. This paper present a novel small target detection technique based on frequency-domain saliency extraction and image sparse representation. First, we exploit the features of Fourier spectrum image and magnitude spectrum of Fourier transform to make a rough extract of saliency regions and use a threshold segmentation system to classify the regions which look salient from the background, which gives us a binary image as result. Second, a new patch-image model and over-complete dictionary were introduced to the detection system, then the infrared small target detection was converted into a problem solving and optimization process of patch-image information reconstruction based on sparse representation. More specifically, the test image and binary image can be decomposed into some image patches follow certain rules. We select the target potential area according to the binary patch-image which contains salient region information, then exploit the over-complete infrared small target dictionary to reconstruct the test image blocks which may contain targets. The coefficients of target image patch satisfy sparse features. Finally, for image sequence, Euclidean distance was used to reduce false alarm ratio and increase the detection accuracy of moving small targets in infrared images due to the target position correlation between frames.

Reprint of "Two-stage sparse coding of region covariance via Log-Euclidean kernels to detect saliency".

PubMed

Zhang, Ying-Ying; Yang, Cai; Zhang, Ping

2017-08-01

In this paper, we present a novel bottom-up saliency detection algorithm from the perspective of covariance matrices on a Riemannian manifold. Each superpixel is described by a region covariance matrix on Riemannian Manifolds. We carry out a two-stage sparse coding scheme via Log-Euclidean kernels to extract salient objects efficiently. In the first stage, given background dictionary on image borders, sparse coding of each region covariance via Log-Euclidean kernels is performed. The reconstruction error on the background dictionary is regarded as the initial saliency of each superpixel. In the second stage, an improvement of the initial result is achieved by calculating reconstruction errors of the superpixels on foreground dictionary, which is extracted from the first stage saliency map. The sparse coding in the second stage is similar to the first stage, but is able to effectively highlight the salient objects uniformly from the background. Finally, three post-processing methods-highlight-inhibition function, context-based saliency weighting, and the graph cut-are adopted to further refine the saliency map. Experiments on four public benchmark datasets show that the proposed algorithm outperforms the state-of-the-art methods in terms of precision, recall and mean absolute error, and demonstrate the robustness and efficiency of the proposed method. Copyright © 2017 Elsevier Ltd. All rights reserved.

Tensor Dictionary Learning for Positive Definite Matrices.

PubMed

Sivalingam, Ravishankar; Boley, Daniel; Morellas, Vassilios; Papanikolopoulos, Nikolaos

2015-11-01

Sparse models have proven to be extremely successful in image processing and computer vision. However, a majority of the effort has been focused on sparse representation of vectors and low-rank models for general matrices. The success of sparse modeling, along with popularity of region covariances, has inspired the development of sparse coding approaches for these positive definite descriptors. While in earlier work, the dictionary was formed from all, or a random subset of, the training signals, it is clearly advantageous to learn a concise dictionary from the entire training set. In this paper, we propose a novel approach for dictionary learning over positive definite matrices. The dictionary is learned by alternating minimization between sparse coding and dictionary update stages, and different atom update methods are described. A discriminative version of the dictionary learning approach is also proposed, which simultaneously learns dictionaries for different classes in classification or clustering. Experimental results demonstrate the advantage of learning dictionaries from data both from reconstruction and classification viewpoints. Finally, a software library is presented comprising C++ binaries for all the positive definite sparse coding and dictionary learning approaches presented here.

An investigation of emotion dynamics in major depressive disorder patients and healthy persons using sparse longitudinal networks.

PubMed

de Vos, Stijn; Wardenaar, Klaas J; Bos, Elisabeth H; Wit, Ernst C; Bouwmans, Mara E J; de Jonge, Peter

2017-01-01

Differences in within-person emotion dynamics may be an important source of heterogeneity in depression. To investigate these dynamics, researchers have previously combined multilevel regression analyses with network representations. However, sparse network methods, specifically developed for longitudinal network analyses, have not been applied. Therefore, this study used this approach to investigate population-level and individual-level emotion dynamics in healthy and depressed persons and compared this method with the multilevel approach. Time-series data were collected in pair-matched healthy persons and major depressive disorder (MDD) patients (n = 54). Seven positive affect (PA) and seven negative affect (NA) items were administered electronically at 90 times (30 days; thrice per day). The population-level (healthy vs. MDD) and individual-level time series were analyzed using a sparse longitudinal network model based on vector autoregression. The population-level model was also estimated with a multilevel approach. Effects of different preprocessing steps were evaluated as well. The characteristics of the longitudinal networks were investigated to gain insight into the emotion dynamics. In the population-level networks, longitudinal network connectivity was strongest in the healthy group, with nodes showing more and stronger longitudinal associations with each other. Individually estimated networks varied strongly across individuals. Individual variations in network connectivity were unrelated to baseline characteristics (depression status, neuroticism, severity). A multilevel approach applied to the same data showed higher connectivity in the MDD group, which seemed partly related to the preprocessing approach. The sparse network approach can be useful for the estimation of networks with multiple nodes, where overparameterization is an issue, and for individual-level networks. However, its current inability to model random effects makes it less useful as a population-level approach in case of large heterogeneity. Different preprocessing strategies appeared to strongly influence the results, complicating inferences about network density.

WHAT IS NEW IN RURAL EDUCATION--NFIRE.

ERIC Educational Resources Information Center

KRAHMER, EDWARD; STURGES, A.W.

RURAL EDUCATION IS DEFINED AS THAT WHICH PREVAILS IN SPARSELY POPULATED AREAS AND SMALL RURAL COMMUNITIES (LESS THAN 2500 POPULATION). FACTORS USUALLY FOUND WITH SUCH SCHOOL OFFERINGS, INCLUDE SPARSITY OF POPULATION, SMALL SCHOOL ENROLLMENTS, ISOLATION FROM CULTURAL EVENTS, AND REMOTENESS FROM EDUCATIONAL OPPORTUNITIES. SUCH FACTORS AS THESE HELP…

Conservation threats due to human-caused increases in fire frequency in Mediterranean-climate ecosystems.

PubMed

Syphard, Alexandra D; Radeloff, Volker C; Hawbaker, Todd J; Stewart, Susan I

2009-06-01

Periodic wildfire is an important natural process in Mediterranean-climate ecosystems, but increasing fire recurrence threatens the fragile ecology of these regions. Because most fires are human-caused, we investigated how human population patterns affect fire frequency. Prior research in California suggests the relationship between population density and fire frequency is not linear. There are few human ignitions in areas with low population density, so fire frequency is low. As population density increases, human ignitions and fire frequency also increase, but beyond a density threshold, the relationship becomes negative as fuels become sparser and fire suppression resources are concentrated. We tested whether this hypothesis also applies to the other Mediterranean-climate ecosystems of the world. We used global satellite databases of population, fire activity, and land cover to evaluate the spatial relationship between humans and fire in the world's five Mediterranean-climate ecosystems. Both the mean and median population densities were consistently and substantially higher in areas with than without fire, but fire again peaked at intermediate population densities, which suggests that the spatial relationship is complex and nonlinear. Some land-cover types burned more frequently than expected, but no systematic differences were observed across the five regions. The consistent association between higher population densities and fire suggests that regardless of differences between land-cover types, natural fire regimes, or overall population, the presence of people in Mediterranean-climate regions strongly affects the frequency of fires; thus, population growth in areas now sparsely settled presents a conservation concern. Considering the sensitivity of plant species to repeated burning and the global conservation significance of Mediterranean-climate ecosystems, conservation planning needs to consider the human influence on fire frequency. Fine-scale spatial analysis of relationships between people and fire may help identify areas where increases in fire frequency will threaten ecologically valuable areas. ©2009 Society for Conservation Biology.

Interconnection economics of small power systems -- A case study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bloethe, W.G.; Thakar, H.C.; Kim, L.C.

1996-11-01

The advantages of interconnecting large electric power systems has been almost universally accepted in those parts of North America that are not geographically isolated. However, interconnecting power systems can result in significant economic advantages, even in those parts of the world where power systems are small and widely separated. This paper examines two small, isolated power systems on the island of Borneo in Southeast Asia. The Malaysian State of Srawak lies on the north coast of Borneo. With an area of 123,156 square km (47,555 square mi.) and population of 1.7 million, it is the largest, but most sparsely populated,more » state in the Federation of Malaysia. Its neighbor to the south is the Indonesian Province of West Kalimantan. A study examining the feasibility of interconnecting these two power systems was undertaken in 1994 as a part of the Association of Southeast Asian Nations (ASEAN) initiative to interconnect the power systems in the region. The ASEAN region is characterized by rapidly growing economies and rapid load growth.« less

Visual saliency detection based on in-depth analysis of sparse representation

NASA Astrophysics Data System (ADS)

Wang, Xin; Shen, Siqiu; Ning, Chen

2018-03-01

Visual saliency detection has been receiving great attention in recent years since it can facilitate a wide range of applications in computer vision. A variety of saliency models have been proposed based on different assumptions within which saliency detection via sparse representation is one of the newly arisen approaches. However, most existing sparse representation-based saliency detection methods utilize partial characteristics of sparse representation, lacking of in-depth analysis. Thus, they may have limited detection performance. Motivated by this, this paper proposes an algorithm for detecting visual saliency based on in-depth analysis of sparse representation. A number of discriminative dictionaries are first learned with randomly sampled image patches by means of inner product-based dictionary atom classification. Then, the input image is partitioned into many image patches, and these patches are classified into salient and nonsalient ones based on the in-depth analysis of sparse coding coefficients. Afterward, sparse reconstruction errors are calculated for the salient and nonsalient patch sets. By investigating the sparse reconstruction errors, the most salient atoms, which tend to be from the most salient region, are screened out and taken away from the discriminative dictionaries. Finally, an effective method is exploited for saliency map generation with the reduced dictionaries. Comprehensive evaluations on publicly available datasets and comparisons with some state-of-the-art approaches demonstrate the effectiveness of the proposed algorithm.

Exploratory graphical models of functional and structural connectivity patterns for Alzheimer's Disease diagnosis.

PubMed

Ortiz, Andrés; Munilla, Jorge; Álvarez-Illán, Ignacio; Górriz, Juan M; Ramírez, Javier

2015-01-01

Alzheimer's Disease (AD) is the most common neurodegenerative disease in elderly people. Its development has been shown to be closely related to changes in the brain connectivity network and in the brain activation patterns along with structural changes caused by the neurodegenerative process. Methods to infer dependence between brain regions are usually derived from the analysis of covariance between activation levels in the different areas. However, these covariance-based methods are not able to estimate conditional independence between variables to factor out the influence of other regions. Conversely, models based on the inverse covariance, or precision matrix, such as Sparse Gaussian Graphical Models allow revealing conditional independence between regions by estimating the covariance between two variables given the rest as constant. This paper uses Sparse Inverse Covariance Estimation (SICE) methods to learn undirected graphs in order to derive functional and structural connectivity patterns from Fludeoxyglucose (18F-FDG) Position Emission Tomography (PET) data and segmented Magnetic Resonance images (MRI), drawn from the ADNI database, for Control, MCI (Mild Cognitive Impairment Subjects), and AD subjects. Sparse computation fits perfectly here as brain regions usually only interact with a few other areas. The models clearly show different metabolic covariation patters between subject groups, revealing the loss of strong connections in AD and MCI subjects when compared to Controls. Similarly, the variance between GM (Gray Matter) densities of different regions reveals different structural covariation patterns between the different groups. Thus, the different connectivity patterns for controls and AD are used in this paper to select regions of interest in PET and GM images with discriminative power for early AD diagnosis. Finally, functional an structural models are combined to leverage the classification accuracy. The results obtained in this work show the usefulness of the Sparse Gaussian Graphical models to reveal functional and structural connectivity patterns. This information provided by the sparse inverse covariance matrices is not only used in an exploratory way but we also propose a method to use it in a discriminative way. Regression coefficients are used to compute reconstruction errors for the different classes that are then introduced in a SVM for classification. Classification experiments performed using 68 Controls, 70 AD, and 111 MCI images and assessed by cross-validation show the effectiveness of the proposed method.

Multidisciplinary population monitoring when demographic data are sparse: a case study of remote trout populations

PubMed Central

Fraser, Dylan J; Calvert, Anna M; Bernatchez, Louis; Coon, Andrew

2013-01-01

The potential of genetic, genomic, and phenotypic metrics for monitoring population trends may be especially high in isolated regions, where traditional demographic monitoring is logistically difficult and only sporadic sampling is possible. This potential, however, is relatively underexplored empirically. Over eleven years, we assessed several such metrics along with traditional ecological knowledge and catch data in a socioeconomically important trout species occupying a large, remote lake. The data revealed largely stable characteristics in two populations over 2–3 generations, but possible contemporary changes in a third population. These potential shifts were suggested by reduced catch rates, reduced body size, and changes in selection implied at one gene-associated single nucleotide polymorphism. A demographic decline in this population, however, was ambiguously supported, based on the apparent lack of temporal change in effective population size, and corresponding traditional knowledge suggesting little change in catch. We illustrate how the pluralistic approach employed has practicality for setting future monitoring efforts of these populations, by guiding monitoring priorities according to the relative merits of different metrics and availability of resources. Our study also considers some advantages and disadvantages to adopting a pluralistic approach to population monitoring where demographic data are not easily obtained. PMID:24455128

Effect of Climate Change on Vegetation Phenology of Different Land Cover Types on the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Cheng, M.; Jin, J.

2017-12-01

Vegetation phenology is one of the most sensitive bio-indicators of climate change, and it has received increasing interests in the context of global warming. As one of the most sensitive areas to global change, the Tibetan Plateau is a unique region to study the trends in vegetation phenology in response to climate change because of its unique vegetation composition, climate features and low-level human disturbance. Although some studies have aroused wide controversies about the actual plant phenology patterns in the Tibetan Plateau, yet the reasons remain unclear. In particular, the phenology characteristics of sparse herbaceous or sparse shrub and evergreen forest that are mostly located in the northwest and southeast of the Tibetan Plateau remain less studied. In this study, the spatio-temporal patterns of the start (SOS), end (EOS) and length (LOS) of the vegetation growing season for six vegetation types in the Tibetan Plateau, including evergreen broadleaf forests, evergreen coniferous forests, evergreen shrub, meadow, steppe and sparse herbaceous or sparse shrub, were quantified from 1982 to 2014 using NOAA/AVHRR NDVI data set at a spatial resolution of 0.05°×0.05° and 7-day intervals using NDVI relative change rate threshold and sixth order polynomial fit models. Assisted with the monthly precipitation and temperature data, the relative effects of changing climates on the variability of phenology were also examined. Diverse phenological changes were observed for different land cover types, with an advancing start of growing season (SOS), delaying end of growing season (EOS) and increasing length of growing season (LOS) in the eastern Tibetan Plateau where meadow was the dominant vegetation type, but with the opposite changes in the steppe and sparse herbaceous or sparse shrub regions which are mostly located in the northwestern and western edges of the Tibetan Plateau. Correlation analysis indicated that sufficient preseason precipitation may delay the SOS of evergreen forests in the southeastern Plateau and advance the SOS of steppe and sparse herbaceous or sparse shrub in relatively arid areas, while the advance of SOS in meadow areas could be related to higher preseason temperature.

Combined analysis of roadside and off-road breeding bird survey data to assess population change in Alaska

USGS Publications Warehouse

Handel, Colleen M.; Sauer, John

2017-01-01

Management interest in North American birds has increasingly focused on species that breed in Alaska, USA, and Canada, where habitats are changing rapidly in response to climatic and anthropogenic factors. We used a series of hierarchical models to estimate rates of population change in 2 forested Bird Conservation Regions (BCRs) in Alaska based on data from the roadside North American Breeding Bird Survey (BBS) and the Alaska Landbird Monitoring Survey, which samples off-road areas on public resource lands. We estimated long-term (1993–2015) population trends for 84 bird species from the BBS and short-term (2003–2015) trends for 31 species from both surveys. Among the 84 species with long-term estimates, 11 had positive trends and 17 had negative trends in 1 or both BCRs; negative trends were primarily found among aerial insectivores and wetland-associated species, confirming range-wide negative continental trends for many of these birds. Three species with negative trends in the contiguous United States and southern Canada had positive trends in Alaska, suggesting different population dynamics at the northern edges of their ranges. Regional population trends within Alaska differed for several species, particularly those represented by different subspecies in the 2 BCRs, which are separated by rugged, glaciated mountain ranges. Analysis of the roadside and off-road data in a joint hierarchical model with shared parameters resulted in improved precision of trend estimates and suggested a roadside-related difference in underlying population trends for several species, particularly within the Northwestern Interior Forest BCR. The combined analysis highlights the importance of considering population structure, physiographic barriers, and spatial heterogeneity in habitat change when assessing patterns of population change across a landscape as broad as Alaska. Combined analysis of roadside and off-road survey data in a hierarchical framework may be particularly useful for evaluating patterns of population change in relatively undeveloped regions with sparse roadside BBS coverage.

Embedded sparse representation of fMRI data via group-wise dictionary optimization

NASA Astrophysics Data System (ADS)

Zhu, Dajiang; Lin, Binbin; Faskowitz, Joshua; Ye, Jieping; Thompson, Paul M.

2016-03-01

Sparse learning enables dimension reduction and efficient modeling of high dimensional signals and images, but it may need to be tailored to best suit specific applications and datasets. Here we used sparse learning to efficiently represent functional magnetic resonance imaging (fMRI) data from the human brain. We propose a novel embedded sparse representation (ESR), to identify the most consistent dictionary atoms across different brain datasets via an iterative group-wise dictionary optimization procedure. In this framework, we introduced additional criteria to make the learned dictionary atoms more consistent across different subjects. We successfully identified four common dictionary atoms that follow the external task stimuli with very high accuracy. After projecting the corresponding coefficient vectors back into the 3-D brain volume space, the spatial patterns are also consistent with traditional fMRI analysis results. Our framework reveals common features of brain activation in a population, as a new, efficient fMRI analysis method.

Cell Assembly Dynamics of Sparsely-Connected Inhibitory Networks: A Simple Model for the Collective Activity of Striatal Projection Neurons.

PubMed

Angulo-Garcia, David; Berke, Joshua D; Torcini, Alessandro

2016-02-01

Striatal projection neurons form a sparsely-connected inhibitory network, and this arrangement may be essential for the appropriate temporal organization of behavior. Here we show that a simplified, sparse inhibitory network of Leaky-Integrate-and-Fire neurons can reproduce some key features of striatal population activity, as observed in brain slices. In particular we develop a new metric to determine the conditions under which sparse inhibitory networks form anti-correlated cell assemblies with time-varying activity of individual cells. We find that under these conditions the network displays an input-specific sequence of cell assembly switching, that effectively discriminates similar inputs. Our results support the proposal that GABAergic connections between striatal projection neurons allow stimulus-selective, temporally-extended sequential activation of cell assemblies. Furthermore, we help to show how altered intrastriatal GABAergic signaling may produce aberrant network-level information processing in disorders such as Parkinson's and Huntington's diseases.

Kernelized Elastic Net Regularization: Generalization Bounds, and Sparse Recovery.

PubMed

Feng, Yunlong; Lv, Shao-Gao; Hang, Hanyuan; Suykens, Johan A K

2016-03-01

Kernelized elastic net regularization (KENReg) is a kernelization of the well-known elastic net regularization (Zou & Hastie, 2005). The kernel in KENReg is not required to be a Mercer kernel since it learns from a kernelized dictionary in the coefficient space. Feng, Yang, Zhao, Lv, and Suykens (2014) showed that KENReg has some nice properties including stability, sparseness, and generalization. In this letter, we continue our study on KENReg by conducting a refined learning theory analysis. This letter makes the following three main contributions. First, we present refined error analysis on the generalization performance of KENReg. The main difficulty of analyzing the generalization error of KENReg lies in characterizing the population version of its empirical target function. We overcome this by introducing a weighted Banach space associated with the elastic net regularization. We are then able to conduct elaborated learning theory analysis and obtain fast convergence rates under proper complexity and regularity assumptions. Second, we study the sparse recovery problem in KENReg with fixed design and show that the kernelization may improve the sparse recovery ability compared to the classical elastic net regularization. Finally, we discuss the interplay among different properties of KENReg that include sparseness, stability, and generalization. We show that the stability of KENReg leads to generalization, and its sparseness confidence can be derived from generalization. Moreover, KENReg is stable and can be simultaneously sparse, which makes it attractive theoretically and practically.

Reconstructing a spatially heterogeneous epidemic: Characterising the geographic spread of 2009 A/H1N1pdm infection in England

NASA Astrophysics Data System (ADS)

Birrell, Paul J.; Zhang, Xu-Sheng; Pebody, Richard G.; Gay, Nigel J.; de Angelis, Daniela

2016-07-01

Understanding how the geographic distribution of and movements within a population influence the spatial spread of infections is crucial for the design of interventions to curb transmission. Existing knowledge is typically based on results from simulation studies whereas analyses of real data remain sparse. The main difficulty in quantifying the spatial pattern of disease spread is the paucity of available data together with the challenge of incorporating optimally the limited information into models of disease transmission. To address this challenge the role of routine migration on the spatial pattern of infection during the epidemic of 2009 pandemic influenza in England is investigated here through two modelling approaches: parallel-region models, where epidemics in different regions are assumed to occur in isolation with shared characteristics; and meta-region models where inter-region transmission is expressed as a function of the commuter flux between regions. Results highlight that the significantly less computationally demanding parallel-region approach is sufficiently flexible to capture the underlying dynamics. This suggests that inter-region movement is either inaccurately characterized by the available commuting data or insignificant once its initial impact on transmission has subsided.

Seismic data restoration with a fast L1 norm trust region method

NASA Astrophysics Data System (ADS)

Cao, Jingjie; Wang, Yanfei

2014-08-01

Seismic data restoration is a major strategy to provide reliable wavefield when field data dissatisfy the Shannon sampling theorem. Recovery by sparsity-promoting inversion often get sparse solutions of seismic data in a transformed domains, however, most methods for sparsity-promoting inversion are line-searching methods which are efficient but are inclined to obtain local solutions. Using trust region method which can provide globally convergent solutions is a good choice to overcome this shortcoming. A trust region method for sparse inversion has been proposed, however, the efficiency should be improved to suitable for large-scale computation. In this paper, a new L1 norm trust region model is proposed for seismic data restoration and a robust gradient projection method for solving the sub-problem is utilized. Numerical results of synthetic and field data demonstrate that the proposed trust region method can get excellent computation speed and is a viable alternative for large-scale computation.

Sparse genetic tracing reveals regionally specific functional organization of mammalian nociceptors.

PubMed

Olson, William; Abdus-Saboor, Ishmail; Cui, Lian; Burdge, Justin; Raabe, Tobias; Ma, Minghong; Luo, Wenqin

2017-10-12

The human distal limbs have a high spatial acuity for noxious stimuli but a low density of pain-sensing neurites. To elucidate mechanisms underlying regional differences in processing nociception, we sparsely traced non-peptidergic nociceptors across the body using a newly generated Mrgprd CreERT2 mouse line. We found that mouse plantar paw skin is also innervated by a low density of Mrgprd + nociceptors, while individual arbors in different locations are comparable in size. Surprisingly, the central arbors of plantar paw and trunk innervating nociceptors have distinct morphologies in the spinal cord. This regional difference is well correlated with a heightened signal transmission for plantar paw circuits, as revealed by both spinal cord slice recordings and behavior assays. Taken together, our results elucidate a novel somatotopic functional organization of the mammalian pain system and suggest that regional central arbor structure could facilitate the "enlarged representation" of plantar paw regions in the CNS.

The Opponent Channel Population Code of Sound Location Is an Efficient Representation of Natural Binaural Sounds

PubMed Central

Młynarski, Wiktor

2015-01-01

In mammalian auditory cortex, sound source position is represented by a population of broadly tuned neurons whose firing is modulated by sounds located at all positions surrounding the animal. Peaks of their tuning curves are concentrated at lateral position, while their slopes are steepest at the interaural midline, allowing for the maximum localization accuracy in that area. These experimental observations contradict initial assumptions that the auditory space is represented as a topographic cortical map. It has been suggested that a “panoramic” code has evolved to match specific demands of the sound localization task. This work provides evidence suggesting that properties of spatial auditory neurons identified experimentally follow from a general design principle- learning a sparse, efficient representation of natural stimuli. Natural binaural sounds were recorded and served as input to a hierarchical sparse-coding model. In the first layer, left and right ear sounds were separately encoded by a population of complex-valued basis functions which separated phase and amplitude. Both parameters are known to carry information relevant for spatial hearing. Monaural input converged in the second layer, which learned a joint representation of amplitude and interaural phase difference. Spatial selectivity of each second-layer unit was measured by exposing the model to natural sound sources recorded at different positions. Obtained tuning curves match well tuning characteristics of neurons in the mammalian auditory cortex. This study connects neuronal coding of the auditory space with natural stimulus statistics and generates new experimental predictions. Moreover, results presented here suggest that cortical regions with seemingly different functions may implement the same computational strategy-efficient coding. PMID:25996373

San Francisco, San Pablo Bay Area

NASA Image and Video Library

1994-09-30

STS068-244-022 (30 September-11 October 1994) --- (San Francisco, San Pablo Bay Area) Photographed through the Space Shuttle Endeavour's flight deck windows, the heavily populated bay area is featured in this 70mm frame. The relatively low altitude of Endeavour's orbit (115 nautical miles) and the use of a 250mm lens on the Hasselblad camera allowed for capturing detail in features such as the Berkeley Marina (frame center). The region's topography is well depicted with the lowland areas heavily populated and the hills much more sparsely covered. The Oakland Hills in the right lower center appear to be re-vegetated after a devastating fire. The Golden Gate Recreation Area in the upper left also shows heavy vegetation. The three bridges across the main part of the bay and their connecting roads are prominent. Cultural features such as Golden Gate Park and the Presidio contrast with the gray of the city.

Efficient diagonalization of the sparse matrices produced within the framework of the UK R-matrix molecular codes

NASA Astrophysics Data System (ADS)

Galiatsatos, P. G.; Tennyson, J.

2012-11-01

The most time consuming step within the framework of the UK R-matrix molecular codes is that of the diagonalization of the inner region Hamiltonian matrix (IRHM). Here we present the method that we follow to speed up this step. We use shared memory machines (SMM), distributed memory machines (DMM), the OpenMP directive based parallel language, the MPI function based parallel language, the sparse matrix diagonalizers ARPACK and PARPACK, a variation for real symmetric matrices of the official coordinate sparse matrix format and finally a parallel sparse matrix-vector product (PSMV). The efficient application of the previous techniques rely on two important facts: the sparsity of the matrix is large enough (more than 98%) and in order to get back converged results we need a small only part of the matrix spectrum.

Peru 2007 tsunami runup observations and modeling

NASA Astrophysics Data System (ADS)

Fritz, H. M.; Kalligeris, N.; Borrero, J. C.

2008-05-01

On 15 August 2007 an earthquake with moment magnitude (Mw) of 8.0 centered off the coast of central Peru, generated a tsunami with locally focused runup heights of up to 10 m. A reconnaissance team was deployed in the immediate aftermath and investigated the tsunami effects at 51 sites. The largest runup heights were measured in a sparsely populated desert area south of the Paracas Peninsula resulting in only 3 tsunami fatalities. Numerical modeling of the earthquake source and tsunami suggest that a region of high slip near the coastline was primarily responsible for the extreme runup heights. The town of Pisco was spared by the presence of the Paracas Peninsula, which blocked tsunami waves from propagating northward from the high slip region. The coast of Peru has experienced numerous deadly and destructive tsunamis throughout history, which highlights the importance of ongoing tsunami awareness and education efforts in the region. The Peru tsunami is compared against recent mega-disasters such as the 2004 Indian Ocean tsunami and Hurricane Katrina.

Detection of Alzheimer's disease using group lasso SVM-based region selection

NASA Astrophysics Data System (ADS)

Sun, Zhuo; Fan, Yong; Lelieveldt, Boudewijn P. F.; van de Giessen, Martijn

2015-03-01

Alzheimer's disease (AD) is one of the most frequent forms of dementia and an increasing challenging public health problem. In the last two decades, structural magnetic resonance imaging (MRI) has shown potential in distinguishing patients with Alzheimer's disease and elderly controls (CN). To obtain AD-specific biomarkers, previous research used either statistical testing to find statistically significant different regions between the two clinical groups, or l1 sparse learning to select isolated features in the image domain. In this paper, we propose a new framework that uses structural MRI to simultaneously distinguish the two clinical groups and find the bio-markers of AD, using a group lasso support vector machine (SVM). The group lasso term (mixed l1- l2 norm) introduces anatomical information from the image domain into the feature domain, such that the resulting set of selected voxels are more meaningful than the l1 sparse SVM. Because of large inter-structure size variation, we introduce a group specific normalization factor to deal with the structure size bias. Experiments have been performed on a well-designed AD vs. CN dataset1 to validate our method. Comparing to the l1 sparse SVM approach, our method achieved better classification performance and a more meaningful biomarker selection. When we vary the training set, the selected regions by our method were more stable than the l1 sparse SVM. Classification experiments showed that our group normalization lead to higher classification accuracy with fewer selected regions than the non-normalized method. Comparing to the state-of-art AD vs. CN classification methods, our approach not only obtains a high accuracy with the same dataset, but more importantly, we simultaneously find the brain anatomies that are closely related to the disease.

Reconstructing cortical current density by exploring sparseness in the transform domain

NASA Astrophysics Data System (ADS)

Ding, Lei

2009-05-01

In the present study, we have developed a novel electromagnetic source imaging approach to reconstruct extended cortical sources by means of cortical current density (CCD) modeling and a novel EEG imaging algorithm which explores sparseness in cortical source representations through the use of L1-norm in objective functions. The new sparse cortical current density (SCCD) imaging algorithm is unique since it reconstructs cortical sources by attaining sparseness in a transform domain (the variation map of cortical source distributions). While large variations are expected to occur along boundaries (sparseness) between active and inactive cortical regions, cortical sources can be reconstructed and their spatial extents can be estimated by locating these boundaries. We studied the SCCD algorithm using numerous simulations to investigate its capability in reconstructing cortical sources with different extents and in reconstructing multiple cortical sources with different extent contrasts. The SCCD algorithm was compared with two L2-norm solutions, i.e. weighted minimum norm estimate (wMNE) and cortical LORETA. Our simulation data from the comparison study show that the proposed sparse source imaging algorithm is able to accurately and efficiently recover extended cortical sources and is promising to provide high-accuracy estimation of cortical source extents.

Sparse approximation problem: how rapid simulated annealing succeeds and fails

NASA Astrophysics Data System (ADS)

Obuchi, Tomoyuki; Kabashima, Yoshiyuki

2016-03-01

Information processing techniques based on sparseness have been actively studied in several disciplines. Among them, a mathematical framework to approximately express a given dataset by a combination of a small number of basis vectors of an overcomplete basis is termed the sparse approximation. In this paper, we apply simulated annealing, a metaheuristic algorithm for general optimization problems, to sparse approximation in the situation where the given data have a planted sparse representation and noise is present. The result in the noiseless case shows that our simulated annealing works well in a reasonable parameter region: the planted solution is found fairly rapidly. This is true even in the case where a common relaxation of the sparse approximation problem, the G-relaxation, is ineffective. On the other hand, when the dimensionality of the data is close to the number of non-zero components, another metastable state emerges, and our algorithm fails to find the planted solution. This phenomenon is associated with a first-order phase transition. In the case of very strong noise, it is no longer meaningful to search for the planted solution. In this situation, our algorithm determines a solution with close-to-minimum distortion fairly quickly.

Online Hierarchical Sparse Representation of Multifeature for Robust Object Tracking

PubMed Central

Qu, Shiru

2016-01-01

Object tracking based on sparse representation has given promising tracking results in recent years. However, the trackers under the framework of sparse representation always overemphasize the sparse representation and ignore the correlation of visual information. In addition, the sparse coding methods only encode the local region independently and ignore the spatial neighborhood information of the image. In this paper, we propose a robust tracking algorithm. Firstly, multiple complementary features are used to describe the object appearance; the appearance model of the tracked target is modeled by instantaneous and stable appearance features simultaneously. A two-stage sparse-coded method which takes the spatial neighborhood information of the image patch and the computation burden into consideration is used to compute the reconstructed object appearance. Then, the reliability of each tracker is measured by the tracking likelihood function of transient and reconstructed appearance models. Finally, the most reliable tracker is obtained by a well established particle filter framework; the training set and the template library are incrementally updated based on the current tracking results. Experiment results on different challenging video sequences show that the proposed algorithm performs well with superior tracking accuracy and robustness. PMID:27630710

Incoming Population: Where Will the People Live? Coping with Growth.

ERIC Educational Resources Information Center

Siegler, Theodore R.

The guide describes an assessment procedure that can be used by sparsely populated communities located near a potential development to help predict where the incoming population will choose to live and shop. First, a numerical model, the "gravity model," is presented which utilizes community size and the distance from the community to…

Louisiana's Coastal Crisis: Characterizing Household and Community-Level Impacts and Responses

NASA Astrophysics Data System (ADS)

Austin, D. E.

2017-12-01

Rich in natural resources and critical ecosystems, the Mississippi delta also is the site of numerous human communities, from sparsely populated towns to dense urban neighborhoods. People who live and work within the delta face major challenges as they confront land loss, subsidence, and storms. This presentation outlines key household and community-level impacts of these environmental changes and both individual and collective responses to them. Based on two decades of applied ethnographic research in the region, as well as the author's participation as an advisor to federal, state, and local organizations, the presentation considers historical and contemporary processes and practices, social organization, and cultural dynamics to analyze proposed policies for addressing the impacts.

The anatomy of the caudal zona incerta in rodents and primates

PubMed Central

Watson, Charles; Lind, Christopher R P; Thomas, Meghan G

2014-01-01

The caudal zona incerta is the target of a recent modification of established procedures for deep brain stimulation (DBS) for Parkinson's disease and tremor. The caudal zona incerta contains a number of neuronal populations that are distinct in terms of their cytoarchitecture, connections, and pattern of immunomarkers and is located at a position where a number of major tracts converge before turning toward their final destination in the forebrain. However, it is not clear which of the anatomical features of the region are related to its value as a target for DBS. This paper has tried to identify features that distinguish the caudal zona incerta of rodents (mouse and rat) and primates (marmoset, rhesus monkey, and human) from the remainder of the zona incerta. We studied cytoarchitecture, anatomical relationships, the pattern of immunomarkers, and gene expression in both of these areas. We found that the caudal zona incerta has a number of histological and gene expression characteristics that distinguish it from the other subdivisions of the zona incerta. Of particular note are the sparse population of GABA neurons and the small but distinctive population of calbindin neurons. We hope that a clearer appreciation of the anatomy of the region will in the end assist the interpretation of cases in which DBS is used in human patients. PMID:24138151

Environmental impact of geometric earthwork construction in pre-Columbian Amazonia.

PubMed

Carson, John Francis; Whitney, Bronwen S; Mayle, Francis E; Iriarte, José; Prümers, Heiko; Soto, J Daniel; Watling, Jennifer

2014-07-22

There is considerable controversy over whether pre-Columbian (pre-A.D. 1492) Amazonia was largely "pristine" and sparsely populated by slash-and-burn agriculturists, or instead a densely populated, domesticated landscape, heavily altered by extensive deforestation and anthropogenic burning. The discovery of hundreds of large geometric earthworks beneath intact rainforest across southern Amazonia challenges its status as a pristine landscape, and has been assumed to indicate extensive pre-Columbian deforestation by large populations. We tested these assumptions using coupled local- and regional-scale paleoecological records to reconstruct land use on an earthwork site in northeast Bolivia within the context of regional, climate-driven biome changes. This approach revealed evidence for an alternative scenario of Amazonian land use, which did not necessitate labor-intensive rainforest clearance for earthwork construction. Instead, we show that the inhabitants exploited a naturally open savanna landscape that they maintained around their settlement despite the climatically driven rainforest expansion that began ∼2,000 y ago across the region. Earthwork construction and agriculture on terra firme landscapes currently occupied by the seasonal rainforests of southern Amazonia may therefore not have necessitated large-scale deforestation using stone tools. This finding implies far less labor--and potentially lower population density--than previously supposed. Our findings demonstrate that current debates over the magnitude and nature of pre-Columbian Amazonian land use, and its impact on global biogeochemical cycling, are potentially flawed because they do not consider this land use in the context of climate-driven forest-savanna biome shifts through the mid-to-late Holocene.

Environmental impact of geometric earthwork construction in pre-Columbian Amazonia

PubMed Central

Carson, John Francis; Whitney, Bronwen S.; Mayle, Francis E.; Iriarte, José; Prümers, Heiko; Soto, J. Daniel; Watling, Jennifer

2014-01-01

There is considerable controversy over whether pre-Columbian (pre-A.D. 1492) Amazonia was largely “pristine” and sparsely populated by slash-and-burn agriculturists, or instead a densely populated, domesticated landscape, heavily altered by extensive deforestation and anthropogenic burning. The discovery of hundreds of large geometric earthworks beneath intact rainforest across southern Amazonia challenges its status as a pristine landscape, and has been assumed to indicate extensive pre-Columbian deforestation by large populations. We tested these assumptions using coupled local- and regional-scale paleoecological records to reconstruct land use on an earthwork site in northeast Bolivia within the context of regional, climate-driven biome changes. This approach revealed evidence for an alternative scenario of Amazonian land use, which did not necessitate labor-intensive rainforest clearance for earthwork construction. Instead, we show that the inhabitants exploited a naturally open savanna landscape that they maintained around their settlement despite the climatically driven rainforest expansion that began ∼2,000 y ago across the region. Earthwork construction and agriculture on terra firme landscapes currently occupied by the seasonal rainforests of southern Amazonia may therefore not have necessitated large-scale deforestation using stone tools. This finding implies far less labor—and potentially lower population density—than previously supposed. Our findings demonstrate that current debates over the magnitude and nature of pre-Columbian Amazonian land use, and its impact on global biogeochemical cycling, are potentially flawed because they do not consider this land use in the context of climate-driven forest–savanna biome shifts through the mid-to-late Holocene. PMID:25002502

Influence of air mass origin on aerosol properties at a remote Michigan forest site

NASA Astrophysics Data System (ADS)

VanReken, T. M.; Mwaniki, G. R.; Wallace, H. W.; Pressley, S. N.; Erickson, M. H.; Jobson, B. T.; Lamb, B. K.

2015-04-01

The northern Great Lakes region of North America is a large, relatively pristine area. To date, there has only been limited study of the atmospheric aerosol in this region. During summer 2009, a detailed characterization of the atmospheric aerosol was conducted at the University of Michigan Biological Station (UMBS) as part of the Community Atmosphere-Biosphere Interactions Experiment (CABINEX). Measurements included particle size distribution, water-soluble composition, and CCN activity. Aerosol properties were strongly dependent on the origin of the air masses reaching the site. For ∼60% of the study period, air was transported from sparsely populated regions to the northwest. During these times aerosol loadings were low, with mean number and volume concentrations of 1630 cm-3 and 1.91 μm3 cm-3, respectively. The aerosol during clean periods was dominated by organics, and exhibited low hygroscopicities (mean κ = 0.18 at s = 0.3%). When air was from more populated regions to the east and south (∼29% of the time), aerosol properties reflected a stronger anthropogenic influence, with 85% greater particle number concentrations, 2.5 times greater aerosol volume, six times more sulfate mass, and increased hygroscopicity (mean к = 0.24 at s = 0.3%). These trends are have the potential to influence forest-atmosphere interactions and should be targeted for future study.

Influence of air mass origin on aerosol properties at a remote Michigan forest site

DOE PAGES

VanReken, T. M.; Mwaniki, G. R.; Wallace, H. W.; ...

2015-02-10

The northern Great Lakes region of North America is a large, relatively pristine area. To date, there has only been limited study of the atmospheric aerosol in this region. During summer 2009, a detailed characterization of the atmospheric aerosol was conducted at the University of Michigan Biological Station (UMBS) as part of the Community Atmosphere–Biosphere Interactions Experiment (CABINEX). Measurements included particle size distribution, water-soluble composition, and CCN activity. Aerosol properties were strongly dependent on the origin of the air masses reaching the site. For ~60% of the study period, air was transported from sparsely populated regions to the northwest. Duringmore » these times aerosol loadings were low, with mean number and volume concentrations of 1630 cm -3 and 1.91 μm 3 cm -3, respectively. The aerosol during clean periods was dominated by organics, and exhibited low hygroscopicities (mean κ = 0.18 at s = 0.3%). When air was from more populated regions to the east and south (~29% of the time), aerosol properties reflected a stronger anthropogenic influence, with 85% greater particle number concentrations, 2.5 times greater aerosol volume, six times more sulfate mass, and increased hygroscopicity (mean к = 0.24 at s = 0.3%). Furthermore, these trends are have the potential to influence forest–atmosphere interactions and should be targeted for future study.« less

YOUNG STELLAR POPULATIONS IN MYStIX STAR-FORMING REGIONS: CANDIDATE PROTOSTARS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Romine, Gregory; Feigelson, Eric D.; Getman, Konstantin V.

The Massive Young Star-Forming Complex in Infrared and X-ray (MYStIX) project provides a new census on stellar members of massive star-forming regions within 4 kpc. Here the MYStIX Infrared Excess catalog and Chandra -based X-ray photometric catalogs are mined to obtain high-quality samples of Class I protostars using criteria designed to reduce extragalactic and Galactic field star contamination. A total of 1109 MYStIX Candidate Protostars (MCPs) are found in 14 star-forming regions. Most are selected from protoplanetary disk infrared excess emission, but 20% are found from their ultrahard X-ray spectra from heavily absorbed magnetospheric flare emission. Two-thirds of the MCP sample ismore » newly reported here. The resulting samples are strongly spatially associated with molecular cores and filaments on Herschel far-infrared maps. This spatial agreement and other evidence indicate that the MCP sample has high reliability with relatively few “false positives” from contaminating populations. But the limited sensitivity and sparse overlap among the infrared and X-ray subsamples indicate that the sample is very incomplete with many “false negatives.” Maps, tables, and source descriptions are provided to guide further study of star formation in these regions. In particular, the nature of ultrahard X-ray protostellar candidates without known infrared counterparts needs to be elucidated.« less

The 15 August 2007 Peru tsunami runup observations and modeling

NASA Astrophysics Data System (ADS)

Fritz, Hermann M.; Kalligeris, Nikos; Borrero, Jose C.; Broncano, Pablo; Ortega, Erick

2008-05-01

On 15 August 2007 an earthquake with moment magnitude (Mw) of 8.0 centered off the coast of central Peru, generated a tsunami with locally focused runup heights of up to10 m. A reconnaissance team was deployed two weeks after the event and investigated the tsunami effects at 51 sites. Three tsunami fatalities were reported south of the Paracas Peninsula in a sparsely populated desert area where the largest tsunami runup heights were measured. Numerical modeling of the earthquake source and tsunami suggest that a region of high slip near the coastline was primarily responsible for the extreme runup heights. The town of Pisco was spared by the Paracas Peninsula, which blocked tsunami waves from propagating northward from the high slip region. The coast of Peru has experienced numerous deadly and destructive tsunamis throughout history, which highlights the importance of ongoing tsunami awareness and education efforts to ensure successful self-evacuation.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xiao, Kai; Ma, Ying -Zhong; Simpson, Mary Jane

Charge carrier trapping degrades the performance of organometallic halide perovskite solar cells. To characterize the locations of electronic trap states in a heterogeneous photoactive layer, a spatially resolved approach is essential. Here, we report a comparative study on methylammonium lead tri-iodide perovskite thin films subject to different thermal annealing times using a combined photoluminescence (PL) and femtosecond transient absorption microscopy (TAM) approach to spatially map trap states. This approach coregisters the initially populated electronic excited states with the regions that recombine radiatively. Although the TAM images are relatively homogeneous for both samples, the corresponding PL images are highly structured. Themore » remarkable variation in the PL intensities as compared to transient absorption signal amplitude suggests spatially dependent PL quantum efficiency, indicative of trapping events. Furthermore, detailed analysis enables identification of two trapping regimes: a densely packed trapping region and a sparse trapping area that appear as unique spatial features in scaled PL maps.« less

Can seed removal through soil erosion explain the scarcity of vegetation in the Chinese Loess Plateau?

NASA Astrophysics Data System (ADS)

Jiao, Juying; Han, Luyan; Jia, Yanfeng; Wang, Ning; Lei, Dong; Li, Linyu

2011-09-01

Seed removal by water erosion may explain the sparse vegetation cover in systems like the Chinese Loess Plateau, which is characterized by severe soil erosion. The seeds from 16 species found on the plateau were examined in relation to the likelihood of their removal by erosion, as tested by rainfall simulation experiments. The experiments were performed over 1-m 2 plots with slopes of 10°, 15°, 20° and 25° for 60 min at intensities of 50 mm h -1, 100 mm h -1 and 150 mm h -1, respectively. Seed loss occurred at simulated rainfall intensities of 100 mm h -1 and 150 mm h -1, with total seed loss rates of 26-33% and 59-67%, respectively. Most seeds were displaced, even at 50 mm h -1. The degrees of seed loss and displacement varied among species. These data, in combination with data from our former research on propagule, seedling and population development in these species, indicate that the species with high seed loss rates either compensate by having a soil seed bank that produces seedlings during the growing season or reproduce by vegetative propagation; the species with no seed loss are still sparsely distributed. Seed germination and seedling survival seem to be more important than seed loss in determining establishment in these regions of the Loess Plateau. Seed translocation by water erosion, however, contributes to the observed distribution of vegetation in this geographic region.

Thermal infrared remote sensing of water temperature in riverine landscapes

USGS Publications Warehouse

Handcock, Rebecca N.; Torgersen, Christian E.; Cherkauer, Keith A.; Gillespie, Alan R.; Klement, Tockner; Faux, Russell N.; Tan, Jing; Carbonneau, Patrice E.; Piégay, Hervé

2012-01-01

Water temperature in riverine landscapes is an important regional indicator of water quality that is influenced by both ground- and surface-water inputs, and indirectly by land use in the surrounding watershed (Brown and Krygier, 1970; Beschta et al., 1987; Chen et al., 1998; Poole and Berman, 2001).Coldwater fishes such as salmon and trout are sensitive to elevated water temperature; therefore, water temperature must meet management guidelines and quality standards, which aim to create a healthy environment for endangered populations (McCullough et al., 2009). For example, in the USA, the Environmental Protection Agency (EPA) has established water quality standards to identify specific temperature criteria to protect coldwater fishes (Environmental Protection Agency, 2003). Trout and salmon can survive in cool-water refugia even when temperatures at other measurement locations are at or above the recommended maximums (Ebersole et al., 2001; Baird and Krueger, 2003; High et al., 2006). Spatially extensive measurements of water temperature are necessary to locate these refugia, to identify the location of ground- and surface-water inputs to the river channel, and to identify thermal pollution sources. Regional assessment of water temperature in streams and rivers has been limited by sparse sampling in both space and time. Water temperature has typically been measured using a network of widely distributed instream gages, which record the temporal change of the bulk, or kinetic, temperature of the water (Tk) at specific locations. For example, the State of Washington (USA) recorded water quality conditions at 76 stations within the Puget Lowlands eco region, which contains 12,721 km of streams and rivers (Washington Department of Ecology, 1998). Such gages are sparsely distributed, are typically located only in larger streams and rivers, and give limited information about the spatial distribution of water temperature.

Thermal infrared remote sensing of water temperature in riverine landscapes: Chapter 5

USGS Publications Warehouse

Carbonneau, Rebecca N.; Piégay, Hervé; Handcock, R.N; Torgersen, Christian E.; Cherkauer, K.A; Gillespie, A.R; Tockner, K; Faux, R. N.; Tan, Jing

2012-01-01

Water temperature in riverine landscapes is an important regional indicator of water quality that is influenced by both ground- and surface-water inputs, and indirectly by land use in the surrounding watershed (Brown and Krygier, 1970; Beschta et al., 1987; Chen et al., 1998; Poole and Berman, 2001). Coldwater fishes such as salmon and trout are sensitive to elevated water temperature; therefore, water temperature must meet management guidelines and quality standards, which aim to create a healthy environment for endangered populations (McCullough et al., 2009). For example, in the USA, the Environmental Protection Agency (EPA) has established water quality standards to identify specific temperature criteria to protect coldwater fishes (Environmental Protection Agency, 2003). Trout and salmon can survive in cool-water refugia even when temperatures at other measurement locations are at or above the recommended maximums (Ebersole et al., 2001; Baird and Krueger, 2003; High et al., 2006). Spatially extensive measurements of water temperature are necessary to locate these refugia, to identify the location of ground- and surface-water inputs to the river channel, and to identify thermal pollution sources. Regional assessment of water temperature in streams and rivers has been limited by sparse sampling in both space and time. Water temperature has typically been measured using a network of widely distributed instream gages, which record the temporal change of the bulk, or kinetic, temperature of the water (Tk) at specific locations. For example, the State of Washington (USA) recorded water quality conditions at 76 stations within the Puget Lowlands eco region, which contains 12,721 km of streams and rivers (Washington Department of Ecology, 1998). Such gages are sparsely distributed, are typically located only in larger streams and rivers, and give limited information about the spatial distribution of water temperature (Cherkauer et al., 2005).

Sparse Bayesian Learning for Identifying Imaging Biomarkers in AD Prediction

PubMed Central

Shen, Li; Qi, Yuan; Kim, Sungeun; Nho, Kwangsik; Wan, Jing; Risacher, Shannon L.; Saykin, Andrew J.

2010-01-01

We apply sparse Bayesian learning methods, automatic relevance determination (ARD) and predictive ARD (PARD), to Alzheimer’s disease (AD) classification to make accurate prediction and identify critical imaging markers relevant to AD at the same time. ARD is one of the most successful Bayesian feature selection methods. PARD is a powerful Bayesian feature selection method, and provides sparse models that is easy to interpret. PARD selects the model with the best estimate of the predictive performance instead of choosing the one with the largest marginal model likelihood. Comparative study with support vector machine (SVM) shows that ARD/PARD in general outperform SVM in terms of prediction accuracy. Additional comparison with surface-based general linear model (GLM) analysis shows that regions with strongest signals are identified by both GLM and ARD/PARD. While GLM P-map returns significant regions all over the cortex, ARD/PARD provide a small number of relevant and meaningful imaging markers with predictive power, including both cortical and subcortical measures. PMID:20879451

Change detection and classification of land cover in multispectral satellite imagery using clustering of sparse approximations (CoSA) over learned feature dictionaries

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moody, Daniela I.; Brumby, Steven P.; Rowland, Joel C.

Neuromimetic machine vision and pattern recognition algorithms are of great interest for landscape characterization and change detection in satellite imagery in support of global climate change science and modeling. We present results from an ongoing effort to extend machine vision methods to the environmental sciences, using adaptive sparse signal processing combined with machine learning. A Hebbian learning rule is used to build multispectral, multiresolution dictionaries from regional satellite normalized band difference index data. Land cover labels are automatically generated via our CoSA algorithm: Clustering of Sparse Approximations, using a clustering distance metric that combines spectral and spatial textural characteristics tomore » help separate geologic, vegetative, and hydrologie features. We demonstrate our method on example Worldview-2 satellite images of an Arctic region, and use CoSA labels to detect seasonal surface changes. In conclusion, our results suggest that neuroscience-based models are a promising approach to practical pattern recognition and change detection problems in remote sensing.« less

Change detection and classification of land cover in multispectral satellite imagery using clustering of sparse approximations (CoSA) over learned feature dictionaries

DOE PAGES

Moody, Daniela I.; Brumby, Steven P.; Rowland, Joel C.; ...

2014-10-01

Neuromimetic machine vision and pattern recognition algorithms are of great interest for landscape characterization and change detection in satellite imagery in support of global climate change science and modeling. We present results from an ongoing effort to extend machine vision methods to the environmental sciences, using adaptive sparse signal processing combined with machine learning. A Hebbian learning rule is used to build multispectral, multiresolution dictionaries from regional satellite normalized band difference index data. Land cover labels are automatically generated via our CoSA algorithm: Clustering of Sparse Approximations, using a clustering distance metric that combines spectral and spatial textural characteristics tomore » help separate geologic, vegetative, and hydrologie features. We demonstrate our method on example Worldview-2 satellite images of an Arctic region, and use CoSA labels to detect seasonal surface changes. In conclusion, our results suggest that neuroscience-based models are a promising approach to practical pattern recognition and change detection problems in remote sensing.« less

The application of sparse arrays in high frequency transcranial focused ultrasound therapy: A simulation study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pajek, Daniel, E-mail: dpajek@sri.utoronto.ca; Hynynen, Kullervo

2013-12-15

Purpose: Transcranial focused ultrasound is an emerging therapeutic modality that can be used to perform noninvasive neurosurgical procedures. The current clinical transcranial phased array operates at 650 kHz, however the development of a higher frequency array would enable more precision, while reducing the risk of standing waves. However, the smaller wavelength and the skull's increased distortion at this frequency are problematic. It would require an order of magnitude more elements to create such an array. Random sparse arrays enable steering of a therapeutic array with fewer elements. However, the tradeoffs inherent in the use of sparsity in a transcranial phasedmore » array have not been systematically investigated and so the objective of this simulation study is to investigate the effect of sparsity on transcranial arrays at a frequency of 1.5 MHz that provides small focal spots for precise exposure control. Methods: Transcranial sonication simulations were conducted using a multilayer Rayleigh-Sommerfeld propagation model. Element size and element population were varied and the phased array's ability to steer was assessed. Results: The focal pressures decreased proportionally as elements were removed. However, off-focus hotspots were generated if a high degree of steering was attempted with very sparse arrays. A phased array consisting of 1588 elements 3 mm in size, a 10% population, was appropriate for steering up to 4 cm in all directions. However, a higher element population would be required if near-skull sonication is desired. Conclusions: This study demonstrated that the development of a sparse, hemispherical array at 1.5 MHz could enable more precision in therapies that utilize lower intensity sonications.« less

Errors in Representing Regional Acid Deposition with Spatially Sparse Monitoring: Case Studies of the Eastern US Using Model Predictions

EPA Science Inventory

The current study uses case studies of model-estimated regional precipitation and wet ion deposition to estimate errors in corresponding regional values derived from the means of site-specific values within regions of interest located in the eastern US. The mean of model-estimate...

DISTRIBUTIONAL CHANGES AND POPULATION STATUS FOR AMPHIBIANS IN THE EASTERN MOJAVE DESERT

EPA Science Inventory

A number of amphibian species historically inhabited sparsely distributed wetlands in the Mojave Desert of western North America, habitats that have been dramatically altered or eliminated as a result of human activities. The population status and distributional changes for amphi...

Variation in developmental time affects mating success and Allee effects

Treesearch

Christelle Robinet; Andrew Liebhold; David Gray

2007-01-01

A fundamental question in biological conservation and invasion biology is why do some populations go extinct? Allee effects, notably those caused by mate location failure, are potentially key factors leading to the extinction of sparse populations. Several previous studies have focused on the inability of males and females to locate each other in space when populations...

Energy Efficient Sparse Connectivity from Imbalanced Synaptic Plasticity Rules

PubMed Central

Sacramento, João; Wichert, Andreas; van Rossum, Mark C. W.

2015-01-01

It is believed that energy efficiency is an important constraint in brain evolution. As synaptic transmission dominates energy consumption, energy can be saved by ensuring that only a few synapses are active. It is therefore likely that the formation of sparse codes and sparse connectivity are fundamental objectives of synaptic plasticity. In this work we study how sparse connectivity can result from a synaptic learning rule of excitatory synapses. Information is maximised when potentiation and depression are balanced according to the mean presynaptic activity level and the resulting fraction of zero-weight synapses is around 50%. However, an imbalance towards depression increases the fraction of zero-weight synapses without significantly affecting performance. We show that imbalanced plasticity corresponds to imposing a regularising constraint on the L 1-norm of the synaptic weight vector, a procedure that is well-known to induce sparseness. Imbalanced plasticity is biophysically plausible and leads to more efficient synaptic configurations than a previously suggested approach that prunes synapses after learning. Our framework gives a novel interpretation to the high fraction of silent synapses found in brain regions like the cerebellum. PMID:26046817

Spatial information outflow from the hippocampal circuit: distributed spatial coding and phase precession in the subiculum.

PubMed

Kim, Steve M; Ganguli, Surya; Frank, Loren M

2012-08-22

Hippocampal place cells convey spatial information through a combination of spatially selective firing and theta phase precession. The way in which this information influences regions like the subiculum that receive input from the hippocampus remains unclear. The subiculum receives direct inputs from area CA1 of the hippocampus and sends divergent output projections to many other parts of the brain, so we examined the firing patterns of rat subicular neurons. We found a substantial transformation in the subicular code for space from sparse to dense firing rate representations along a proximal-distal anatomical gradient: neurons in the proximal subiculum are more similar to canonical, sparsely firing hippocampal place cells, whereas neurons in the distal subiculum have higher firing rates and more distributed spatial firing patterns. Using information theory, we found that the more distributed spatial representation in the subiculum carries, on average, more information about spatial location and context than the sparse spatial representation in CA1. Remarkably, despite the disparate firing rate properties of subicular neurons, we found that neurons at all proximal-distal locations exhibit robust theta phase precession, with similar spiking oscillation frequencies as neurons in area CA1. Our findings suggest that the subiculum is specialized to compress sparse hippocampal spatial codes into highly informative distributed codes suitable for efficient communication to other brain regions. Moreover, despite this substantial compression, the subiculum maintains finer scale temporal properties that may allow it to participate in oscillatory phase coding and spike timing-dependent plasticity in coordination with other regions of the hippocampal circuit.

Sparse brain network using penalized linear regression

NASA Astrophysics Data System (ADS)

Lee, Hyekyoung; Lee, Dong Soo; Kang, Hyejin; Kim, Boong-Nyun; Chung, Moo K.

2011-03-01

Sparse partial correlation is a useful connectivity measure for brain networks when it is difficult to compute the exact partial correlation in the small-n large-p setting. In this paper, we formulate the problem of estimating partial correlation as a sparse linear regression with a l1-norm penalty. The method is applied to brain network consisting of parcellated regions of interest (ROIs), which are obtained from FDG-PET images of the autism spectrum disorder (ASD) children and the pediatric control (PedCon) subjects. To validate the results, we check their reproducibilities of the obtained brain networks by the leave-one-out cross validation and compare the clustered structures derived from the brain networks of ASD and PedCon.

Sparse PCA with Oracle Property.

PubMed

Gu, Quanquan; Wang, Zhaoran; Liu, Han

In this paper, we study the estimation of the k -dimensional sparse principal subspace of covariance matrix Σ in the high-dimensional setting. We aim to recover the oracle principal subspace solution, i.e., the principal subspace estimator obtained assuming the true support is known a priori. To this end, we propose a family of estimators based on the semidefinite relaxation of sparse PCA with novel regularizations. In particular, under a weak assumption on the magnitude of the population projection matrix, one estimator within this family exactly recovers the true support with high probability, has exact rank- k , and attains a [Formula: see text] statistical rate of convergence with s being the subspace sparsity level and n the sample size. Compared to existing support recovery results for sparse PCA, our approach does not hinge on the spiked covariance model or the limited correlation condition. As a complement to the first estimator that enjoys the oracle property, we prove that, another estimator within the family achieves a sharper statistical rate of convergence than the standard semidefinite relaxation of sparse PCA, even when the previous assumption on the magnitude of the projection matrix is violated. We validate the theoretical results by numerical experiments on synthetic datasets.

Sparse PCA with Oracle Property

PubMed Central

Gu, Quanquan; Wang, Zhaoran; Liu, Han

2014-01-01

In this paper, we study the estimation of the k-dimensional sparse principal subspace of covariance matrix Σ in the high-dimensional setting. We aim to recover the oracle principal subspace solution, i.e., the principal subspace estimator obtained assuming the true support is known a priori. To this end, we propose a family of estimators based on the semidefinite relaxation of sparse PCA with novel regularizations. In particular, under a weak assumption on the magnitude of the population projection matrix, one estimator within this family exactly recovers the true support with high probability, has exact rank-k, and attains a s/n statistical rate of convergence with s being the subspace sparsity level and n the sample size. Compared to existing support recovery results for sparse PCA, our approach does not hinge on the spiked covariance model or the limited correlation condition. As a complement to the first estimator that enjoys the oracle property, we prove that, another estimator within the family achieves a sharper statistical rate of convergence than the standard semidefinite relaxation of sparse PCA, even when the previous assumption on the magnitude of the projection matrix is violated. We validate the theoretical results by numerical experiments on synthetic datasets. PMID:25684971

Optimal sparse approximation with integrate and fire neurons.

PubMed

Shapero, Samuel; Zhu, Mengchen; Hasler, Jennifer; Rozell, Christopher

2014-08-01

Sparse approximation is a hypothesized coding strategy where a population of sensory neurons (e.g. V1) encodes a stimulus using as few active neurons as possible. We present the Spiking LCA (locally competitive algorithm), a rate encoded Spiking Neural Network (SNN) of integrate and fire neurons that calculate sparse approximations. The Spiking LCA is designed to be equivalent to the nonspiking LCA, an analog dynamical system that converges on a ℓ(1)-norm sparse approximations exponentially. We show that the firing rate of the Spiking LCA converges on the same solution as the analog LCA, with an error inversely proportional to the sampling time. We simulate in NEURON a network of 128 neuron pairs that encode 8 × 8 pixel image patches, demonstrating that the network converges to nearly optimal encodings within 20 ms of biological time. We also show that when using more biophysically realistic parameters in the neurons, the gain function encourages additional ℓ(0)-norm sparsity in the encoding, relative both to ideal neurons and digital solvers.

Geographic patterns and dynamics of Alaskan climate interpolated from a sparse station record

USGS Publications Warehouse

Fleming, Michael D.; Chapin, F. Stuart; Cramer, W.; Hufford, Gary L.; Serreze, Mark C.

2000-01-01

Data from a sparse network of climate stations in Alaska were interpolated to provide 1-km resolution maps of mean monthly temperature and precipitation-variables that are required at high spatial resolution for input into regional models of ecological processes and resource management. The interpolation model is based on thin-plate smoothing splines, which uses the spatial data along with a digital elevation model to incorporate local topography. The model provides maps that are consistent with regional climatology and with patterns recognized by experienced weather forecasters. The broad patterns of Alaskan climate are well represented and include latitudinal and altitudinal trends in temperature and precipitation and gradients in continentality. Variations within these broad patterns reflect both the weakening and reduction in frequency of low-pressure centres in their eastward movement across southern Alaska during the summer, and the shift of the storm tracks into central and northern Alaska in late summer. Not surprisingly, apparent artifacts of the interpolated climate occur primarily in regions with few or no stations. The interpolation model did not accurately represent low-level winter temperature inversions that occur within large valleys and basins. Along with well-recognized climate patterns, the model captures local topographic effects that would not be depicted using standard interpolation techniques. This suggests that similar procedures could be used to generate high-resolution maps for other high-latitude regions with a sparse density of data.

Natural image sequences constrain dynamic receptive fields and imply a sparse code.

PubMed

Häusler, Chris; Susemihl, Alex; Nawrot, Martin P

2013-11-06

In their natural environment, animals experience a complex and dynamic visual scenery. Under such natural stimulus conditions, neurons in the visual cortex employ a spatially and temporally sparse code. For the input scenario of natural still images, previous work demonstrated that unsupervised feature learning combined with the constraint of sparse coding can predict physiologically measured receptive fields of simple cells in the primary visual cortex. This convincingly indicated that the mammalian visual system is adapted to the natural spatial input statistics. Here, we extend this approach to the time domain in order to predict dynamic receptive fields that can account for both spatial and temporal sparse activation in biological neurons. We rely on temporal restricted Boltzmann machines and suggest a novel temporal autoencoding training procedure. When tested on a dynamic multi-variate benchmark dataset this method outperformed existing models of this class. Learning features on a large dataset of natural movies allowed us to model spatio-temporal receptive fields for single neurons. They resemble temporally smooth transformations of previously obtained static receptive fields and are thus consistent with existing theories. A neuronal spike response model demonstrates how the dynamic receptive field facilitates temporal and population sparseness. We discuss the potential mechanisms and benefits of a spatially and temporally sparse representation of natural visual input. Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.

Interpretation of the Precision Matrix and Its Application in Estimating Sparse Brain Connectivity during Sleep Spindles from Human Electrocorticography Recordings

PubMed Central

Das, Anup; Sampson, Aaron L.; Lainscsek, Claudia; Muller, Lyle; Lin, Wutu; Doyle, John C.; Cash, Sydney S.; Halgren, Eric; Sejnowski, Terrence J.

2017-01-01

The correlation method from brain imaging has been used to estimate functional connectivity in the human brain. However, brain regions might show very high correlation even when the two regions are not directly connected due to the strong interaction of the two regions with common input from a third region. One previously proposed solution to this problem is to use a sparse regularized inverse covariance matrix or precision matrix (SRPM) assuming that the connectivity structure is sparse. This method yields partial correlations to measure strong direct interactions between pairs of regions while simultaneously removing the influence of the rest of the regions, thus identifying regions that are conditionally independent. To test our methods, we first demonstrated conditions under which the SRPM method could indeed find the true physical connection between a pair of nodes for a spring-mass example and an RC circuit example. The recovery of the connectivity structure using the SRPM method can be explained by energy models using the Boltzmann distribution. We then demonstrated the application of the SRPM method for estimating brain connectivity during stage 2 sleep spindles from human electrocorticography (ECoG) recordings using an 8 × 8 electrode array. The ECoG recordings that we analyzed were from a 32-year-old male patient with long-standing pharmaco-resistant left temporal lobe complex partial epilepsy. Sleep spindles were automatically detected using delay differential analysis and then analyzed with SRPM and the Louvain method for community detection. We found spatially localized brain networks within and between neighboring cortical areas during spindles, in contrast to the case when sleep spindles were not present. PMID:28095202

Population estimation with sparse data: The role of estimators versus indices revisited

Treesearch

Kevin S. McKelvey; Dean E. Pearson

2001-01-01

The use of indices to evaluate small-mammal populations has been heavily criticized, yet a review of small-mammal studies published from 1996 through 2000 indicated that indices are still the primary methods employed for measuring populations. The literature review also found that 98% of the samples collected in these studies were too small for reliable...

Density of large snags and logs in northern Arizona mixed-conifer and ponderosa pine forests

Treesearch

Joseph L. Ganey; Benjamin J. Bird; L. Scott Baggett; Jeffrey S. Jenness

2015-01-01

Large snags and logs provide important biological legacies and resources for native wildlife, yet data on populations of large snags and logs and factors influencing those populations are sparse. We monitored populations of large snags and logs in mixed-conifer and ponderosa pine (Pinus ponderosa) forests in northern Arizona from 1997 through 2012. We modeled density...

Working with the Suicidal Client Who Also Abuses Substances

ERIC Educational Resources Information Center

Esposito-Smythers, Christianne; Walsh, Adam; Spirito, Anthony; Rizzo, Christie; Goldston, David B.; Kaminer, Yifrah

2012-01-01

Substance use disorders and suicidal thoughts and behaviors commonly co-occur in adolescent and adult psychiatric populations and are often functionally interrelated. Although the evidence base for treatment of this population is sparse, integrated cognitive behavioral treatment (CBT) protocols, or those that rely heavily on CBT techniques, hold…

Auditory Processing and Early Literacy Skills in a Preschool and Kindergarten Population

ERIC Educational Resources Information Center

Corriveau, Kathleen H.; Goswami, Usha; Thomson, Jennifer M.

2010-01-01

Although the relationship between auditory processing and reading-related skills has been investigated in school-age populations and in prospective studies of infants, understanding of the relationship between these variables in the period immediately preceding formal reading instruction is sparse. In this cross-sectional study, auditory…

ℓ0 -based sparse hyperspectral unmixing using spectral information and a multi-objectives formulation

NASA Astrophysics Data System (ADS)

Xu, Xia; Shi, Zhenwei; Pan, Bin

2018-07-01

Sparse unmixing aims at recovering pure materials from hyperpspectral images and estimating their abundance fractions. Sparse unmixing is actually ℓ0 problem which is NP-h ard, and a relaxation is often used. In this paper, we attempt to deal with ℓ0 problem directly via a multi-objective based method, which is a non-convex manner. The characteristics of hyperspectral images are integrated into the proposed method, which leads to a new spectra and multi-objective based sparse unmixing method (SMoSU). In order to solve the ℓ0 norm optimization problem, the spectral library is encoded in a binary vector, and a bit-wise flipping strategy is used to generate new individuals in the evolution process. However, a multi-objective method usually produces a number of non-dominated solutions, while sparse unmixing requires a single solution. How to make the final decision for sparse unmixing is challenging. To handle this problem, we integrate the spectral characteristic of hyperspectral images into SMoSU. By considering the spectral correlation in hyperspectral data, we improve the Tchebycheff decomposition function in SMoSU via a new regularization item. This regularization item is able to enforce the individual divergence in the evolution process of SMoSU. In this way, the diversity and convergence of population is further balanced, which is beneficial to the concentration of individuals. In the experiments part, three synthetic datasets and one real-world data are used to analyse the effectiveness of SMoSU, and several state-of-art sparse unmixing algorithms are compared.

Cancer epidemiology in the pacific islands - past, present and future.

PubMed

Moore, Malcolm A; Baumann, Francine; Foliaki, Sunia; Goodman, Marc T; Haddock, Robert; Maraka, Roger; Koroivueta, Josefa; Roder, David; Vinit, Thomas; Whippy, Helen J D; Sobue, Tomotaka

2010-01-01

The Pacific Ocean contains approximately 25,000 islands, stretching from Papua New Guinea to Easter Island, populated by mixtures of Melanesians, Micronesians and Polynesians, as well as migrant groups from Asia and Europe. The region encompasses a third of the surface of the earth although it is sparsely populated at a total of around 9 million. With the exception of some of the more populated islands, such as New Zealand and Hawaii, few surveys of chronic diseases have been conducted, but it is increasingly recognized that obesity, diabetes and associated conditions are emerging public health problems and clearly there is a need for cooperation to optimize control. Here we focus on cancer registry and epidemiological findings for Papua New Guinea, the Solomons, Vanuatu, Samoa, New Caledonia, Fiji, Polynesia, French Polynesia, Maori in New Zealand, Native Hawaiians, Micronesia, including Guam, and Aboriginal populations in Australia as assessed by PubMed searches and perusal of the International Agency for Cancer Research descriptive epidemiology database. Overall, the major cancers in males are oral and liver in Papua New Guinea and the Solomon Islands, and lung and prostate elsewhere (Fiji being exceptional in demonstrating a predominance of esophageal cancer), whereas in females it is breast and either cervix or lung, depending largely on whether cervical cancer screening program is active. In certain locations thyroid cancer is also very prevalent in females. The similarities and variation point to advantages for collaborative research to provide the evidence-base for effective cancer control programs in the region.

Cancer Epidemiology in the Pacific Islands - Past, Present and Future

PubMed Central

Moore, Malcolm A; Baumann, Francine; Foliaki, Sunia; Goodman, Marc T; Haddock, Robert; Maraka, Roger; Koroivueta, Josefa; Roder, David; Vinit, Thomas; Whippy, Helen JD; Sobue, Tomotaka

2015-01-01

The Pacific Ocean contains approximately 25,000 islands, stretching from Papua New Guinea to Easter Island, populated by mixtures of Melanesians, Micronesians and Polynesians, as well as migrant groups from Asia and Europe. The region encompasses a third of the surface of the earth although it is sparsely populated at a total of around 9 million. With the exception of some of the more populated islands, such as New Zealand and Hawaii, few surveys of chronic diseases have been conducted, but it is increasingly recognized that obesity, diabetes and associated conditions are emerging public health problems and clearly there is a need for cooperation to optimize control. Here we focus on cancer registry and epidemiological findings for Papua New Guinea, the Solomons, Vanuatu, Samoa, New Caledonia, Fiji, Polynesia, French Polynesia, Maori in New Zealand, Native Hawaiians, Micronesia, including Guam, and Aboriginal populations in Australia as assessed by PubMed searches and perusal of the International Agency for Cancer Research descriptive epidemiology database. Overall, the major cancers in males are oral and liver in Papua New Guinea and the Solomon Islands, and lung and prostate elsewhere (Fiji being exceptional in demonstrating a predominance of esophageal cancer), whereas in females it is breast and either cervix or lung, depending largely on whether cervical cancer screening program is active. In certain locations thyroid cancer is also very prevalent in females. The similarities and variation point to advantages for collaborative research to provide the evidence-base for effective cancer control programs in the region. PMID:20553071

Finite difference method accelerated with sparse solvers for structural analysis of the metal-organic complexes

NASA Astrophysics Data System (ADS)

Guda, A. A.; Guda, S. A.; Soldatov, M. A.; Lomachenko, K. A.; Bugaev, A. L.; Lamberti, C.; Gawelda, W.; Bressler, C.; Smolentsev, G.; Soldatov, A. V.; Joly, Y.

2016-05-01

Finite difference method (FDM) implemented in the FDMNES software [Phys. Rev. B, 2001, 63, 125120] was revised. Thorough analysis shows, that the calculated diagonal in the FDM matrix consists of about 96% zero elements. Thus a sparse solver would be more suitable for the problem instead of traditional Gaussian elimination for the diagonal neighbourhood. We have tried several iterative sparse solvers and the direct one MUMPS solver with METIS ordering turned out to be the best. Compared to the Gaussian solver present method is up to 40 times faster and allows XANES simulations for complex systems already on personal computers. We show applicability of the software for metal-organic [Fe(bpy)3]2+ complex both for low spin and high spin states populated after laser excitation.

Genetic Diversity and Population Structure of the Pelagic Thresher Shark (Alopias pelagicus) in the Pacific Ocean: Evidence for Two Evolutionarily Significant Units

PubMed Central

Cardeñosa, Diego; Hyde, John; Caballero, Susana

2014-01-01

There has been an increasing concern about shark overexploitation in the last decade, especially for open ocean shark species, where there is a paucity of data about their life histories and population dynamics. Little is known regarding the population structure of the pelagic thresher shark, Alopias pelagicus. Though an earlier study using mtDNA control region data, showed evidence for differences between eastern and western Pacific populations, the study was hampered by low sample size and sparse geographic coverage, particularly a lack of samples from the central Pacific. Here, we present the population structure of Alopias pelagicus analyzing 351 samples from six different locations across the Pacific Ocean. Using data from mitochondrial DNA COI sequences and seven microsatellite loci we found evidence of strong population differentiation between western and eastern Pacific populations and evidence for reciprocally monophyly for organelle haplotypes and significant divergence of allele frequencies at nuclear loci, suggesting the existence of two Evolutionarily Significant Units (ESU) in the Pacific Ocean. Interestingly, the population in Hawaii appears to be composed of both ESUs in what seems to be clear sympatry with reproductive isolation. These results may indicate the existence of a new cryptic species in the Pacific Ocean. The presence of these distinct ESUs highlights the need for revised management plans for this highly exploited shark throughout its range. PMID:25337814

Genetic diversity and population structure of the pelagic thresher shark (Alopias pelagicus) in the Pacific Ocean: evidence for two evolutionarily significant units.

PubMed

Cardeñosa, Diego; Hyde, John; Caballero, Susana

2014-01-01

There has been an increasing concern about shark overexploitation in the last decade, especially for open ocean shark species, where there is a paucity of data about their life histories and population dynamics. Little is known regarding the population structure of the pelagic thresher shark, Alopias pelagicus. Though an earlier study using mtDNA control region data, showed evidence for differences between eastern and western Pacific populations, the study was hampered by low sample size and sparse geographic coverage, particularly a lack of samples from the central Pacific. Here, we present the population structure of Alopias pelagicus analyzing 351 samples from six different locations across the Pacific Ocean. Using data from mitochondrial DNA COI sequences and seven microsatellite loci we found evidence of strong population differentiation between western and eastern Pacific populations and evidence for reciprocally monophyly for organelle haplotypes and significant divergence of allele frequencies at nuclear loci, suggesting the existence of two Evolutionarily Significant Units (ESU) in the Pacific Ocean. Interestingly, the population in Hawaii appears to be composed of both ESUs in what seems to be clear sympatry with reproductive isolation. These results may indicate the existence of a new cryptic species in the Pacific Ocean. The presence of these distinct ESUs highlights the need for revised management plans for this highly exploited shark throughout its range.

Kriging and local polynomial methods for blending satellite-derived and gauge precipitation estimates to support hydrologic early warning systems

USGS Publications Warehouse

Verdin, Andrew; Funk, Christopher C.; Rajagopalan, Balaji; Kleiber, William

2016-01-01

Robust estimates of precipitation in space and time are important for efficient natural resource management and for mitigating natural hazards. This is particularly true in regions with developing infrastructure and regions that are frequently exposed to extreme events. Gauge observations of rainfall are sparse but capture the precipitation process with high fidelity. Due to its high resolution and complete spatial coverage, satellite-derived rainfall data are an attractive alternative in data-sparse regions and are often used to support hydrometeorological early warning systems. Satellite-derived precipitation data, however, tend to underrepresent extreme precipitation events. Thus, it is often desirable to blend spatially extensive satellite-derived rainfall estimates with high-fidelity rain gauge observations to obtain more accurate precipitation estimates. In this research, we use two different methods, namely, ordinary kriging and κ-nearest neighbor local polynomials, to blend rain gauge observations with the Climate Hazards Group Infrared Precipitation satellite-derived precipitation estimates in data-sparse Central America and Colombia. The utility of these methods in producing blended precipitation estimates at pentadal (five-day) and monthly time scales is demonstrated. We find that these blending methods significantly improve the satellite-derived estimates and are competitive in their ability to capture extreme precipitation.

The genetic architecture of growth and fillet traits in farmed Atlantic salmon (Salmo salar).

PubMed

Tsai, Hsin Yuan; Hamilton, Alastair; Guy, Derrick R; Tinch, Alan E; Bishop, Stephen C; Houston, Ross D

2015-05-19

Performance and quality traits such as harvest weight, fillet weight and flesh color are of economic importance to the Atlantic salmon aquaculture industry. The genetic factors underlying these traits are of scientific and commercial interest. However, such traits are typically polygenic in nature, with the number and size of QTL likely to vary between studies and populations. The aim of this study was to investigate the genetic basis of several growth and fillet traits measured at harvest in a large farmed salmon population by using SNP markers. Due to the marked heterochiasmy in salmonids, an efficient two-stage mapping approach was applied whereby QTL were detected using a sire-based linkage analysis, a sparse SNP marker map and exploiting low rates of recombination, while a subsequent dam-based analysis focused on the significant chromosomes with a denser map to confirm QTL and estimate their position. The harvest traits all showed significant heritability, ranging from 0.05 for fillet yield up to 0.53 for the weight traits. In the sire-based analysis, 1695 offspring with trait records and their 20 sires were successfully genotyped for the SNPs on the sparse map. Chromosomes 13, 18, 19 and 20 were shown to harbor genome-wide significant QTL affecting several growth-related traits. The QTL on chr. 13, 18 and 20 were detected in the dam-based analysis using 512 offspring from 10 dams and explained approximately 6-7 % of the within-family variation in these traits. We have detected several QTL affecting economically important complex traits in a commercial salmon population. Overall, the results suggest that the traits are relatively polygenic and that QTL tend to be pleiotropic (affecting the weight of several components of the harvested fish). Comparison of QTL regions across studies suggests that harvest trait QTL tend to be relatively population-specific. Therefore, the application of marker or genomic selection for improvement in these traits is likely to be most effective when the discovery population is closely related to the selection candidates (e.g. within-family genomic selection).

Structured Sparse Principal Components Analysis With the TV-Elastic Net Penalty.

PubMed

de Pierrefeu, Amicie; Lofstedt, Tommy; Hadj-Selem, Fouad; Dubois, Mathieu; Jardri, Renaud; Fovet, Thomas; Ciuciu, Philippe; Frouin, Vincent; Duchesnay, Edouard

2018-02-01

Principal component analysis (PCA) is an exploratory tool widely used in data analysis to uncover the dominant patterns of variability within a population. Despite its ability to represent a data set in a low-dimensional space, PCA's interpretability remains limited. Indeed, the components produced by PCA are often noisy or exhibit no visually meaningful patterns. Furthermore, the fact that the components are usually non-sparse may also impede interpretation, unless arbitrary thresholding is applied. However, in neuroimaging, it is essential to uncover clinically interpretable phenotypic markers that would account for the main variability in the brain images of a population. Recently, some alternatives to the standard PCA approach, such as sparse PCA (SPCA), have been proposed, their aim being to limit the density of the components. Nonetheless, sparsity alone does not entirely solve the interpretability problem in neuroimaging, since it may yield scattered and unstable components. We hypothesized that the incorporation of prior information regarding the structure of the data may lead to improved relevance and interpretability of brain patterns. We therefore present a simple extension of the popular PCA framework that adds structured sparsity penalties on the loading vectors in order to identify the few stable regions in the brain images that capture most of the variability. Such structured sparsity can be obtained by combining, e.g., and total variation (TV) penalties, where the TV regularization encodes information on the underlying structure of the data. This paper presents the structured SPCA (denoted SPCA-TV) optimization framework and its resolution. We demonstrate SPCA-TV's effectiveness and versatility on three different data sets. It can be applied to any kind of structured data, such as, e.g., -dimensional array images or meshes of cortical surfaces. The gains of SPCA-TV over unstructured approaches (such as SPCA and ElasticNet PCA) or structured approach (such as GraphNet PCA) are significant, since SPCA-TV reveals the variability within a data set in the form of intelligible brain patterns that are easier to interpret and more stable across different samples.

Extracting Vegetation Coverage in Dry-hot Valley Regions Based on Alternating Angle Minimum Algorithm

NASA Astrophysics Data System (ADS)

Y Yang, M.; Wang, J.; Zhang, Q.

2017-07-01

Vegetation coverage is one of the most important indicators for ecological environment change, and is also an effective index for the assessment of land degradation and desertification. The dry-hot valley regions have sparse surface vegetation, and the spectral information about the vegetation in such regions usually has a weak representation in remote sensing, so there are considerable limitations for applying the commonly-used vegetation index method to calculate the vegetation coverage in the dry-hot valley regions. Therefore, in this paper, Alternating Angle Minimum (AAM) algorithm of deterministic model is adopted for selective endmember for pixel unmixing of MODIS image in order to extract the vegetation coverage, and accuracy test is carried out by the use of the Landsat TM image over the same period. As shown by the results, in the dry-hot valley regions with sparse vegetation, AAM model has a high unmixing accuracy, and the extracted vegetation coverage is close to the actual situation, so it is promising to apply the AAM model to the extraction of vegetation coverage in the dry-hot valley regions.

Accurate sparse-projection image reconstruction via nonlocal TV regularization.

PubMed

Zhang, Yi; Zhang, Weihua; Zhou, Jiliu

2014-01-01

Sparse-projection image reconstruction is a useful approach to lower the radiation dose; however, the incompleteness of projection data will cause degeneration of imaging quality. As a typical compressive sensing method, total variation has obtained great attention on this problem. Suffering from the theoretical imperfection, total variation will produce blocky effect on smooth regions and blur edges. To overcome this problem, in this paper, we introduce the nonlocal total variation into sparse-projection image reconstruction and formulate the minimization problem with new nonlocal total variation norm. The qualitative and quantitative analyses of numerical as well as clinical results demonstrate the validity of the proposed method. Comparing to other existing methods, our method more efficiently suppresses artifacts caused by low-rank reconstruction and reserves structure information better.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Desai, Mihir I., E-mail: mdesai@swri.edu; Department of Physics & Astronomy, University of Texas at San Antonio, TX 782, USA.; Dayeh, Maher A.

Observations over the last decade have shown that suprathermal ions with energies above that of the core or bulk solar wind protons (i.e., ~1-2 keV/nucleon) are an important constituent of the overall seed population that is accelerated in solar and interplanetary events. Despite the recent recognition of their importance, the origin of these populations and the method of their acceleration remains poorly understood. This is partly due to the fact that these particles exist in the so-called tail regions of the corresponding solar wind distributions where high temporal and sensitivity measurements are sparse. Moreover, observations comprising long-term averages (between hoursmore » to more than a day) show conflicting results. For instance, below ~40 keV/nucleon the ion differential intensities in the solar wind frame appear to exhibit a near-constant power-law spectral slope of ~1.5, perhaps indicating a universal acceleration mechanism. In contrast, at energies greater than ~40 keV/nucleon, the ion composition changes with solar activity, and the energy spectra are significantly steeper, perhaps indicating that the suprathermal pool of material also comprises lower-energy particle populations accelerated in corotating interaction regions, interplanetary shocks, and solar energetic particle events. This paper discusses key observations of suprathermal ions and electrons in terms of state-of-the-art theories and models that have been put forward to account for their origin and acceleration.« less

A combinatorial model for dentate gyrus sparse coding

DOE PAGES

Severa, William; Parekh, Ojas; James, Conrad D.; ...

2016-12-29

The dentate gyrus forms a critical link between the entorhinal cortex and CA3 by providing a sparse version of the signal. Concurrent with this increase in sparsity, a widely accepted theory suggests the dentate gyrus performs pattern separation—similar inputs yield decorrelated outputs. Although an active region of study and theory, few logically rigorous arguments detail the dentate gyrus’s (DG) coding. We suggest a theoretically tractable, combinatorial model for this action. The model provides formal methods for a highly redundant, arbitrarily sparse, and decorrelated output signal.To explore the value of this model framework, we assess how suitable it is for twomore » notable aspects of DG coding: how it can handle the highly structured grid cell representation in the input entorhinal cortex region and the presence of adult neurogenesis, which has been proposed to produce a heterogeneous code in the DG. We find tailoring the model to grid cell input yields expansion parameters consistent with the literature. In addition, the heterogeneous coding reflects activity gradation observed experimentally. Lastly, we connect this approach with more conventional binary threshold neural circuit models via a formal embedding.« less

Automatic segmentation of right ventricular ultrasound images using sparse matrix transform and a level set

NASA Astrophysics Data System (ADS)

Qin, Xulei; Cong, Zhibin; Fei, Baowei

2013-11-01

An automatic segmentation framework is proposed to segment the right ventricle (RV) in echocardiographic images. The method can automatically segment both epicardial and endocardial boundaries from a continuous echocardiography series by combining sparse matrix transform, a training model, and a localized region-based level set. First, the sparse matrix transform extracts main motion regions of the myocardium as eigen-images by analyzing the statistical information of the images. Second, an RV training model is registered to the eigen-images in order to locate the position of the RV. Third, the training model is adjusted and then serves as an optimized initialization for the segmentation of each image. Finally, based on the initializations, a localized, region-based level set algorithm is applied to segment both epicardial and endocardial boundaries in each echocardiograph. Three evaluation methods were used to validate the performance of the segmentation framework. The Dice coefficient measures the overall agreement between the manual and automatic segmentation. The absolute distance and the Hausdorff distance between the boundaries from manual and automatic segmentation were used to measure the accuracy of the segmentation. Ultrasound images of human subjects were used for validation. For the epicardial and endocardial boundaries, the Dice coefficients were 90.8 ± 1.7% and 87.3 ± 1.9%, the absolute distances were 2.0 ± 0.42 mm and 1.79 ± 0.45 mm, and the Hausdorff distances were 6.86 ± 1.71 mm and 7.02 ± 1.17 mm, respectively. The automatic segmentation method based on a sparse matrix transform and level set can provide a useful tool for quantitative cardiac imaging.

Galaxy redshift surveys with sparse sampling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chiang, Chi-Ting; Wullstein, Philipp; Komatsu, Eiichiro

2013-12-01

Survey observations of the three-dimensional locations of galaxies are a powerful approach to measure the distribution of matter in the universe, which can be used to learn about the nature of dark energy, physics of inflation, neutrino masses, etc. A competitive survey, however, requires a large volume (e.g., V{sub survey} ∼ 10Gpc{sup 3}) to be covered, and thus tends to be expensive. A ''sparse sampling'' method offers a more affordable solution to this problem: within a survey footprint covering a given survey volume, V{sub survey}, we observe only a fraction of the volume. The distribution of observed regions should bemore » chosen such that their separation is smaller than the length scale corresponding to the wavenumber of interest. Then one can recover the power spectrum of galaxies with precision expected for a survey covering a volume of V{sub survey} (rather than the volume of the sum of observed regions) with the number density of galaxies given by the total number of observed galaxies divided by V{sub survey} (rather than the number density of galaxies within an observed region). We find that regularly-spaced sampling yields an unbiased power spectrum with no window function effect, and deviations from regularly-spaced sampling, which are unavoidable in realistic surveys, introduce calculable window function effects and increase the uncertainties of the recovered power spectrum. On the other hand, we show that the two-point correlation function (pair counting) is not affected by sparse sampling. While we discuss the sparse sampling method within the context of the forthcoming Hobby-Eberly Telescope Dark Energy Experiment, the method is general and can be applied to other galaxy surveys.« less

Sparse short-distance connections enhance calcium wave propagation in a 3D model of astrocyte networks

PubMed Central

Lallouette, Jules; De Pittà, Maurizio; Ben-Jacob, Eshel; Berry, Hugues

2014-01-01

Traditionally, astrocytes have been considered to couple via gap-junctions into a syncytium with only rudimentary spatial organization. However, this view is challenged by growing experimental evidence that astrocytes organize as a proper gap-junction mediated network with more complex region-dependent properties. On the other hand, the propagation range of intercellular calcium waves (ICW) within astrocyte populations is as well highly variable, depending on the brain region considered. This suggests that the variability of the topology of gap-junction couplings could play a role in the variability of the ICW propagation range. Since this hypothesis is very difficult to investigate with current experimental approaches, we explore it here using a biophysically realistic model of three-dimensional astrocyte networks in which we varied the topology of the astrocyte network, while keeping intracellular properties and spatial cell distribution and density constant. Computer simulations of the model suggest that changing the topology of the network is indeed sufficient to reproduce the distinct ranges of ICW propagation reported experimentally. Unexpectedly, our simulations also predict that sparse connectivity and restriction of gap-junction couplings to short distances should favor propagation while long–distance or dense connectivity should impair it. Altogether, our results provide support to recent experimental findings that point toward a significant functional role of the organization of gap-junction couplings into proper astroglial networks. Dynamic control of this topology by neurons and signaling molecules could thus constitute a new type of regulation of neuron-glia and glia-glia interactions. PMID:24795613

[Population in the northern border area. Urban dynamism and binational interrelation].

PubMed

Ham Chande, R

1988-01-01

The 3300 km border between Mexico and the US constitutes the geopolitical separation between an underdeveloped country on the 1 hand and 1 of the most technologically and economically powerful countries in the world on the other. The border region is characterized by the contrasts on either side of the border and by the strong interrelation between both sides. Vast streams of persons, merchandise, money, services, communications, and cultural influences flow from 1 side to the other. The border region as a seat of population has a recent history. The border was defined in near current form only in the mid-19th century, when the expansionist tendencies of the US encountered a vast area of very sparse population. In 1900, the principal localities of the border zone had only about 39,000 inhabitants, of whom fewer than 5000 lived west of Ciudad Juarez. Between 1910-20, the population of the border region increased from 53,000 to 96,000 as a result of migrants fleeing the ravages of the revolution. The population of the border region was estimated at 3.826 million in 1988, resulting from rates of growth above Mexico's national average. Settlement in the area has depended on events and conditions in Mexico and on such US occurrences as Prohibition, the Great Depression, the 2nd World War, the Bracero program, and the Program of Border Industrialization. 82% of the border population lives in urban zones, partly because of lack of water. 80% of the urban population is concentrated in 6 cities, Juarez, Tijuana, Mexicali, Nuevo Laredo, Reynosa, and Matamoros. Much of the population of the 6 cities is composed of persons born elsewhere. The border area also has a large floating population of undocumented migrants in transit to or from the US. The high rates of urbanization and of binational interaction are reflected in demographic dynamics. In 1979, 71% of women in union in the border area vs 54% in the rest of Mexico had used contraception, and the infant mortality rate was 10% below the national average. In the 20-29 cohort there were 88 men per 100 women, reflecting male emigration and female inmigration. The rate of economic participation was higher than the national average, per capita production was greater, and unemployment rates were lower.

Microstructure Images Restoration of Metallic Materials Based upon KSVD and Smoothing Penalty Sparse Representation Approach.

PubMed

Li, Qing; Liang, Steven Y

2018-04-20

Microstructure images of metallic materials play a significant role in industrial applications. To address image degradation problem of metallic materials, a novel image restoration technique based on K-means singular value decomposition (KSVD) and smoothing penalty sparse representation (SPSR) algorithm is proposed in this work, the microstructure images of aluminum alloy 7075 (AA7075) material are used as examples. To begin with, to reflect the detail structure characteristics of the damaged image, the KSVD dictionary is introduced to substitute the traditional sparse transform basis (TSTB) for sparse representation. Then, due to the image restoration, modeling belongs to a highly underdetermined equation, and traditional sparse reconstruction methods may cause instability and obvious artifacts in the reconstructed images, especially reconstructed image with many smooth regions and the noise level is strong, thus the SPSR (here, q = 0.5) algorithm is designed to reconstruct the damaged image. The results of simulation and two practical cases demonstrate that the proposed method has superior performance compared with some state-of-the-art methods in terms of restoration performance factors and visual quality. Meanwhile, the grain size parameters and grain boundaries of microstructure image are discussed before and after they are restored by proposed method.

Probabilistic Air Segmentation and Sparse Regression Estimated Pseudo CT for PET/MR Attenuation Correction

PubMed Central

Chen, Yasheng; Juttukonda, Meher; Su, Yi; Benzinger, Tammie; Rubin, Brian G.; Lee, Yueh Z.; Lin, Weili; Shen, Dinggang; Lalush, David

2015-01-01

Purpose To develop a positron emission tomography (PET) attenuation correction method for brain PET/magnetic resonance (MR) imaging by estimating pseudo computed tomographic (CT) images from T1-weighted MR and atlas CT images. Materials and Methods In this institutional review board–approved and HIPAA-compliant study, PET/MR/CT images were acquired in 20 subjects after obtaining written consent. A probabilistic air segmentation and sparse regression (PASSR) method was developed for pseudo CT estimation. Air segmentation was performed with assistance from a probabilistic air map. For nonair regions, the pseudo CT numbers were estimated via sparse regression by using atlas MR patches. The mean absolute percentage error (MAPE) on PET images was computed as the normalized mean absolute difference in PET signal intensity between a method and the reference standard continuous CT attenuation correction method. Friedman analysis of variance and Wilcoxon matched-pairs tests were performed for statistical comparison of MAPE between the PASSR method and Dixon segmentation, CT segmentation, and population averaged CT atlas (mean atlas) methods. Results The PASSR method yielded a mean MAPE ± standard deviation of 2.42% ± 1.0, 3.28% ± 0.93, and 2.16% ± 1.75, respectively, in the whole brain, gray matter, and white matter, which were significantly lower than the Dixon, CT segmentation, and mean atlas values (P < .01). Moreover, 68.0% ± 16.5, 85.8% ± 12.9, and 96.0% ± 2.5 of whole-brain volume had within ±2%, ±5%, and ±10% percentage error by using PASSR, respectively, which was significantly higher than other methods (P < .01). Conclusion PASSR outperformed the Dixon, CT segmentation, and mean atlas methods by reducing PET error owing to attenuation correction. © RSNA, 2014 PMID:25521778

Development of Innovative Technology to Provide Low-Cost Surface Atmospheric Observations in Data Sparse Regions

NASA Astrophysics Data System (ADS)

Kucera, Paul; Steinson, Martin

2017-04-01

Accurate and reliable real-time monitoring and dissemination of observations of surface weather conditions is critical for a variety of societal applications. Applications that provide local and regional information about temperature, precipitation, moisture, and winds, for example, are important for agriculture, water resource monitoring, health, and monitoring of hazard weather conditions. In many regions of the World, surface weather stations are sparsely located and/or of poor quality. Existing stations have often been sited incorrectly, not well-maintained, and have limited communications established at the site for real-time monitoring. The University Corporation for Atmospheric Research (UCAR)/National Center for Atmospheric Research (NCAR), with support from USAID, has started an initiative to develop and deploy low-cost weather instrumentation in sparsely observed regions of the world. The project is focused on improving weather observations for environmental monitoring and early warning alert systems on a regional to global scale. Instrumentation that has been developed use innovative new technologies such as 3D printers, Raspberry Pi computing systems, and wireless communications. The goal of the project is to make the weather station designs, software, and processing tools an open community resource. The weather stations can be built locally by agencies, through educational institutions, and residential communities as a citizen effort to augment existing networks to improve detection of natural hazards for disaster risk reduction. The presentation will provide an overview of the open source weather station technology and evaluation of sensor observations for the initial networks that have been deployed in Africa.

Improvement of Disease Prediction and Modeling through the Use of Meteorological Ensembles: Human Plague in Uganda

PubMed Central

Moore, Sean M.; Monaghan, Andrew; Griffith, Kevin S.; Apangu, Titus; Mead, Paul S.; Eisen, Rebecca J.

2012-01-01

Climate and weather influence the occurrence, distribution, and incidence of infectious diseases, particularly those caused by vector-borne or zoonotic pathogens. Thus, models based on meteorological data have helped predict when and where human cases are most likely to occur. Such knowledge aids in targeting limited prevention and control resources and may ultimately reduce the burden of diseases. Paradoxically, localities where such models could yield the greatest benefits, such as tropical regions where morbidity and mortality caused by vector-borne diseases is greatest, often lack high-quality in situ local meteorological data. Satellite- and model-based gridded climate datasets can be used to approximate local meteorological conditions in data-sparse regions, however their accuracy varies. Here we investigate how the selection of a particular dataset can influence the outcomes of disease forecasting models. Our model system focuses on plague (Yersinia pestis infection) in the West Nile region of Uganda. The majority of recent human cases have been reported from East Africa and Madagascar, where meteorological observations are sparse and topography yields complex weather patterns. Using an ensemble of meteorological datasets and model-averaging techniques we find that the number of suspected cases in the West Nile region was negatively associated with dry season rainfall (December-February) and positively with rainfall prior to the plague season. We demonstrate that ensembles of available meteorological datasets can be used to quantify climatic uncertainty and minimize its impacts on infectious disease models. These methods are particularly valuable in regions with sparse observational networks and high morbidity and mortality from vector-borne diseases. PMID:23024750

Glutamic Acid - Amino Acid, Neurotransmitter, and Drug - Is Responsible for Protein Synthesis Rhythm in Hepatocyte Populations in vitro and in vivo.

PubMed

Brodsky, V Y; Malchenko, L A; Konchenko, D S; Zvezdina, N D; Dubovaya, T K

2016-08-01

Primary cultures of rat hepatocytes were studied in serum-free media. Ultradian protein synthesis rhythm was used as a marker of cell synchronization in the population. Addition of glutamic acid (0.2 mg/ml) to the medium of nonsynchronous sparse cultures resulted in detection of a common protein synthesis rhythm, hence in synchronization of the cells. The antagonist of glutamic acid metabotropic receptors MCPG (0.01 mg/ml) added together with glutamic acid abolished the synchronization effect; in sparse cultures, no rhythm was detected. Feeding rats with glutamic acid (30 mg with food) resulted in protein synthesis rhythm in sparse cultures obtained from the rats. After feeding without glutamic acid, linear kinetics of protein synthesis was revealed. Thus, glutamic acid, a component of blood as a non-neural transmitter, can synchronize the activity of hepatocytes and can form common rhythm of protein synthesis in vitro and in vivo. This effect is realized via receptors. Mechanisms of cell-cell communication are discussed on analyzing effects of non-neural functions of neurotransmitters. Glutamic acid is used clinically in humans. Hence, a previously unknown function of this drug is revealed.

Finger vein verification system based on sparse representation.

PubMed

Xin, Yang; Liu, Zhi; Zhang, Haixia; Zhang, Hong

2012-09-01

Finger vein verification is a promising biometric pattern for personal identification in terms of security and convenience. The recognition performance of this technology heavily relies on the quality of finger vein images and on the recognition algorithm. To achieve efficient recognition performance, a special finger vein imaging device is developed, and a finger vein recognition method based on sparse representation is proposed. The motivation for the proposed method is that finger vein images exhibit a sparse property. In the proposed system, the regions of interest (ROIs) in the finger vein images are segmented and enhanced. Sparse representation and sparsity preserving projection on ROIs are performed to obtain the features. Finally, the features are measured for recognition. An equal error rate of 0.017% was achieved based on the finger vein image database, which contains images that were captured by using the near-IR imaging device that was developed in this study. The experimental results demonstrate that the proposed method is faster and more robust than previous methods.

Functional brain networks reconstruction using group sparsity-regularized learning.

PubMed

Zhao, Qinghua; Li, Will X Y; Jiang, Xi; Lv, Jinglei; Lu, Jianfeng; Liu, Tianming

2018-06-01

Investigating functional brain networks and patterns using sparse representation of fMRI data has received significant interests in the neuroimaging community. It has been reported that sparse representation is effective in reconstructing concurrent and interactive functional brain networks. To date, most of data-driven network reconstruction approaches rarely take consideration of anatomical structures, which are the substrate of brain function. Furthermore, it has been rarely explored whether structured sparse representation with anatomical guidance could facilitate functional networks reconstruction. To address this problem, in this paper, we propose to reconstruct brain networks utilizing the structure guided group sparse regression (S2GSR) in which 116 anatomical regions from the AAL template, as prior knowledge, are employed to guide the network reconstruction when performing sparse representation of whole-brain fMRI data. Specifically, we extract fMRI signals from standard space aligned with the AAL template. Then by learning a global over-complete dictionary, with the learned dictionary as a set of features (regressors), the group structured regression employs anatomical structures as group information to regress whole brain signals. Finally, the decomposition coefficients matrix is mapped back to the brain volume to represent functional brain networks and patterns. We use the publicly available Human Connectome Project (HCP) Q1 dataset as the test bed, and the experimental results indicate that the proposed anatomically guided structure sparse representation is effective in reconstructing concurrent functional brain networks.

The disease complex of the gypsy moth. 1. Major components

Treesearch

R.W. Campbell; J.D. Podgwaite

1971-01-01

A study was undertaken to elucidate the impact of the various components of disease on natural populations of the gypsy moth, Porthetria dispar. Diseased larvae from both sparse and dense populations were examined and categorized on the basis of etiologic and nonetiologic mortality factors. Results indicated a significantly higher incidence of...

Planning for Computer-Based Distance Education: A Review of Administrative Issues.

ERIC Educational Resources Information Center

Lever-Duffy, Judy C.

The Homestead Campus of Miami-Dade Community College, in Florida, serves a sparsely populated area with a culturally diverse population including migrant farm workers, prison inmates, and U.S. Air Force personnel. To increase access to college services, the campus focused on implementing a computer-based distance education program as its primary…

Kinetic Simulations of Type II Radio Burst Emission Processes

NASA Astrophysics Data System (ADS)

Ganse, U.; Spanier, F. A.; Vainio, R. O.

2011-12-01

The fundamental emission process of Type II Radio Bursts has been under discussion for many decades. While analytic deliberations point to three wave interaction as the source for fundamental and harmonic radio emissions, sparse in-situ observational data and high computational demands for kinetic simulations have not allowed for a definite conclusion to be reached. A popular model puts the radio emission into the foreshock region of a coronal mass ejection's shock front, where shock drift acceleration can create eletrcon beam populations in the otherwise quiescent foreshock plasma. Beam-driven instabilities are then assumed to create waves, forming the starting point of three wave interaction processes. Using our kinetic particle-in-cell code, we have studied a number of emission scenarios based on electron beam populations in a CME foreshock, with focus on wave-interaction microphysics on kinetic scales. The self-consistent, fully kinetic simulations with completely physical mass-ratio show fundamental and harmonic emission of transverse electromagnetic waves and allow for detailled statistical analysis of all contributing wavemodes and their couplings.

Temporally-Constrained Group Sparse Learning for Longitudinal Data Analysis in Alzheimer’s Disease

PubMed Central

Jie, Biao; Liu, Mingxia; Liu, Jun

2016-01-01

Sparse learning has been widely investigated for analysis of brain images to assist the diagnosis of Alzheimer’s disease (AD) and its prodromal stage, i.e., mild cognitive impairment (MCI). However, most existing sparse learning-based studies only adopt cross-sectional analysis methods, where the sparse model is learned using data from a single time-point. Actually, multiple time-points of data are often available in brain imaging applications, which can be used in some longitudinal analysis methods to better uncover the disease progression patterns. Accordingly, in this paper we propose a novel temporally-constrained group sparse learning method aiming for longitudinal analysis with multiple time-points of data. Specifically, we learn a sparse linear regression model by using the imaging data from multiple time-points, where a group regularization term is first employed to group the weights for the same brain region across different time-points together. Furthermore, to reflect the smooth changes between data derived from adjacent time-points, we incorporate two smoothness regularization terms into the objective function, i.e., one fused smoothness term which requires that the differences between two successive weight vectors from adjacent time-points should be small, and another output smoothness term which requires the differences between outputs of two successive models from adjacent time-points should also be small. We develop an efficient optimization algorithm to solve the proposed objective function. Experimental results on ADNI database demonstrate that, compared with conventional sparse learning-based methods, our proposed method can achieve improved regression performance and also help in discovering disease-related biomarkers. PMID:27093313

A sparse representation-based approach for copy-move image forgery detection in smooth regions

NASA Astrophysics Data System (ADS)

Abdessamad, Jalila; ElAdel, Asma; Zaied, Mourad

2017-03-01

Copy-move image forgery is the act of cloning a restricted region in the image and pasting it once or multiple times within that same image. This procedure intends to cover a certain feature, probably a person or an object, in the processed image or emphasize it through duplication. Consequences of this malicious operation can be unexpectedly harmful. Hence, the present paper proposes a new approach that automatically detects Copy-move Forgery (CMF). In particular, this work broaches a widely common open issue in CMF research literature that is detecting CMF within smooth areas. Indeed, the proposed approach represents the image blocks as a sparse linear combination of pre-learned bases (a mixture of texture and color-wise small patches) which allows a robust description of smooth patches. The reported experimental results demonstrate the effectiveness of the proposed approach in identifying the forged regions in CM attacks.

The effects of missing data on global ozone estimates

NASA Technical Reports Server (NTRS)

Drewry, J. W.; Robbins, J. L.

1981-01-01

The effects of missing data and model truncation on estimates of the global mean, zonal distribution, and global distribution of ozone are considered. It is shown that missing data can introduce biased estimates with errors that are not accounted for in the accuracy calculations of empirical modeling techniques. Data-fill techniques are introduced and used for evaluating error bounds and constraining the estimate in areas of sparse and missing data. It is found that the accuracy of the global mean estimate is more dependent on data distribution than model size. Zonal features can be accurately described by 7th order models over regions of adequate data distribution. Data variance accounted for by higher order models appears to represent climatological features of columnar ozone rather than pure error. Data-fill techniques can prevent artificial feature generation in regions of sparse or missing data without degrading high order estimates over dense data regions.

Estimation of white matter fiber parameters from compressed multiresolution diffusion MRI using sparse Bayesian learning.

PubMed

Pisharady, Pramod Kumar; Sotiropoulos, Stamatios N; Duarte-Carvajalino, Julio M; Sapiro, Guillermo; Lenglet, Christophe

2018-02-15

We present a sparse Bayesian unmixing algorithm BusineX: Bayesian Unmixing for Sparse Inference-based Estimation of Fiber Crossings (X), for estimation of white matter fiber parameters from compressed (under-sampled) diffusion MRI (dMRI) data. BusineX combines compressive sensing with linear unmixing and introduces sparsity to the previously proposed multiresolution data fusion algorithm RubiX, resulting in a method for improved reconstruction, especially from data with lower number of diffusion gradients. We formulate the estimation of fiber parameters as a sparse signal recovery problem and propose a linear unmixing framework with sparse Bayesian learning for the recovery of sparse signals, the fiber orientations and volume fractions. The data is modeled using a parametric spherical deconvolution approach and represented using a dictionary created with the exponential decay components along different possible diffusion directions. Volume fractions of fibers along these directions define the dictionary weights. The proposed sparse inference, which is based on the dictionary representation, considers the sparsity of fiber populations and exploits the spatial redundancy in data representation, thereby facilitating inference from under-sampled q-space. The algorithm improves parameter estimation from dMRI through data-dependent local learning of hyperparameters, at each voxel and for each possible fiber orientation, that moderate the strength of priors governing the parameter variances. Experimental results on synthetic and in-vivo data show improved accuracy with a lower uncertainty in fiber parameter estimates. BusineX resolves a higher number of second and third fiber crossings. For under-sampled data, the algorithm is also shown to produce more reliable estimates. Copyright © 2017 Elsevier Inc. All rights reserved.

Multi-objective based spectral unmixing for hyperspectral images

NASA Astrophysics Data System (ADS)

Xu, Xia; Shi, Zhenwei

2017-02-01

Sparse hyperspectral unmixing assumes that each observed pixel can be expressed by a linear combination of several pure spectra in a priori library. Sparse unmixing is challenging, since it is usually transformed to a NP-hard l0 norm based optimization problem. Existing methods usually utilize a relaxation to the original l0 norm. However, the relaxation may bring in sensitive weighted parameters and additional calculation error. In this paper, we propose a novel multi-objective based algorithm to solve the sparse unmixing problem without any relaxation. We transform sparse unmixing to a multi-objective optimization problem, which contains two correlative objectives: minimizing the reconstruction error and controlling the endmember sparsity. To improve the efficiency of multi-objective optimization, a population-based randomly flipping strategy is designed. Moreover, we theoretically prove that the proposed method is able to recover a guaranteed approximate solution from the spectral library within limited iterations. The proposed method can directly deal with l0 norm via binary coding for the spectral signatures in the library. Experiments on both synthetic and real hyperspectral datasets demonstrate the effectiveness of the proposed method.

Sparse reconstruction for quantitative bioluminescence tomography based on the incomplete variables truncated conjugate gradient method.

PubMed

He, Xiaowei; Liang, Jimin; Wang, Xiaorui; Yu, Jingjing; Qu, Xiaochao; Wang, Xiaodong; Hou, Yanbin; Chen, Duofang; Liu, Fang; Tian, Jie

2010-11-22

In this paper, we present an incomplete variables truncated conjugate gradient (IVTCG) method for bioluminescence tomography (BLT). Considering the sparse characteristic of the light source and insufficient surface measurement in the BLT scenarios, we combine a sparseness-inducing (ℓ1 norm) regularization term with a quadratic error term in the IVTCG-based framework for solving the inverse problem. By limiting the number of variables updated at each iterative and combining a variable splitting strategy to find the search direction more efficiently, it obtains fast and stable source reconstruction, even without a priori information of the permissible source region and multispectral measurements. Numerical experiments on a mouse atlas validate the effectiveness of the method. In vivo mouse experimental results further indicate its potential for a practical BLT system.

Change detection and change monitoring of natural and man-made features in multispectral and hyperspectral satellite imagery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moody, Daniela Irina

An approach for land cover classification, seasonal and yearly change detection and monitoring, and identification of changes in man-made features may use a clustering of sparse approximations (CoSA) on sparse representations in learned dictionaries. A Hebbian learning rule may be used to build multispectral or hyperspectral, multiresolution dictionaries that are adapted to regional satellite image data. Sparse image representations of pixel patches over the learned dictionaries may be used to perform unsupervised k-means clustering into land cover categories. The clustering process behaves as a classifier in detecting real variability. This approach may combine spectral and spatial textural characteristics to detectmore » geologic, vegetative, hydrologic, and man-made features, as well as changes in these features over time.« less

Automatic segmentation of brain MRI in high-dimensional local and non-local feature space based on sparse representation.

PubMed

Khalilzadeh, Mohammad Mahdi; Fatemizadeh, Emad; Behnam, Hamid

2013-06-01

Automatic extraction of the varying regions of magnetic resonance images is required as a prior step in a diagnostic intelligent system. The sparsest representation and high-dimensional feature are provided based on learned dictionary. The classification is done by employing the technique that computes the reconstruction error locally and non-locally of each pixel. The acquired results from the real and simulated images are superior to the best MRI segmentation method with regard to the stability advantages. In addition, it is segmented exactly through a formula taken from the distance and sparse factors. Also, it is done automatically taking sparse factor in unsupervised clustering methods whose results have been improved. Copyright © 2013 Elsevier Inc. All rights reserved.

Amino acid Alphabet Size in Protein Evolution Experiments: Better to Search a Small library Thoroughly or a Large Library Sparsely?

PubMed Central

Muñoz, Enrique

2015-01-01

We compare the results obtained from searching a smaller library thoroughly versus searching a more diverse, larger library sparsely. We study protein evolution with reduced amino acid alphabets, by simulating directed evolution experiments at three different alphabet sizes: 20, 5 and 2. We employ a physical model for evolution, the generalized NK model, that has proved successful in modeling protein evolution, antibody evolution, and T cell selection. We find that antibodies with higher affinity are found by searching a library with a larger alphabet sparsely than by searching a smaller library thoroughly, even with well-designed reduced libraries. We find ranked amino acid usage frequencies in agreement with observations of the CDR-H3 variable region of human antibodies. PMID:18375453

Collaborative Medical Engagement and Needs Assessment in the Democratic Republic of the Congo: A Preliminary Report from Muanda

PubMed Central

Lesho, Emil; Okito, Edmond Amisi; Mann, Kelly; McCullough, Michael; Hesse, Elisabeth

2014-01-01

The Democratic Republic of the Congo is the second largest and fourth most populous country in Africa. More than two decades of ongoing conflicts have degraded its healthcare system. A broad range of tropical diseases, along with opportunities for collaborative medical engagements (CMEs), are prevalent. However, reports from such events in this country are sparse. In June 2013, a CME was conducted in the western town of Muanda. Twenty-two hours of didactic sessions were collaboratively presented, and 158 patients were collaboratively evaluated. Durable dental and respiratory equipment, infrastructure improvements, and training opportunities were the top needs identified by the providers. Whether the regional referral hospital received sustainable benefit remains under investigation. However, the approach and needs assessment described herein provide a framework for future engagements or assistance. This CME established a precedence of medical partnership in the region because it led to the largest multidisciplinary joint collaboration in the history of the Democratic Republic of the Congo. PMID:24534813

Collaborative medical engagement and needs assessment in the Democratic Republic of the Congo: a preliminary report from Muanda.

PubMed

Lesho, Emil; Okito, Edmond Amisi; Mann, Kelly; McCullough, Michael; Hesse, Elisabeth

2014-04-01

The Democratic Republic of the Congo is the second largest and fourth most populous country in Africa. More than two decades of ongoing conflicts have degraded its healthcare system. A broad range of tropical diseases, along with opportunities for collaborative medical engagements (CMEs), are prevalent. However, reports from such events in this country are sparse. In June 2013, a CME was conducted in the western town of Muanda. Twenty-two hours of didactic sessions were collaboratively presented, and 158 patients were collaboratively evaluated. Durable dental and respiratory equipment, infrastructure improvements, and training opportunities were the top needs identified by the providers. Whether the regional referral hospital received sustainable benefit remains under investigation. However, the approach and needs assessment described herein provide a framework for future engagements or assistance. This CME established a precedence of medical partnership in the region because it led to the largest multidisciplinary joint collaboration in the history of the Democratic Republic of the Congo.

Deserts : geology and resources

USGS Publications Warehouse

Walker, Alta S.

1996-01-01

Approximately one-third of the Earth's land surface is desert, arid land with meager rainfall that supports only sparse vegetation and a limited population of people and animals. Deserts stark, sometimes mysterious worlds have been portrayed as fascinating environments of adventure and exploration from narratives such as that of Lawrence of Arabia to movies such as "Dune." These arid regions are called deserts because they are dry. They may be hot, they may be cold. They may be regions of sand or vast areas of rocks and gravel peppered with occasional plants. But deserts are always dry. Deserts are natural laboratories in which to study the interactions of wind and sometimes water on the arid surfaces of planets. They contain valuable mineral deposits that were formed in the arid environment or that were exposed by erosion. Because deserts are dry, they are ideal places for human artifacts and fossils to be preserved. Deserts are also fragile environments. The misuse of these lands is a serious and growing problem in parts of our world.

Imaging electronic trap states in perovskite thin films with combined fluorescence and femtosecond transient absorption microscopy

DOE PAGES

Xiao, Kai; Ma, Ying -Zhong; Simpson, Mary Jane; ...

2016-04-22

Charge carrier trapping degrades the performance of organometallic halide perovskite solar cells. To characterize the locations of electronic trap states in a heterogeneous photoactive layer, a spatially resolved approach is essential. Here, we report a comparative study on methylammonium lead tri-iodide perovskite thin films subject to different thermal annealing times using a combined photoluminescence (PL) and femtosecond transient absorption microscopy (TAM) approach to spatially map trap states. This approach coregisters the initially populated electronic excited states with the regions that recombine radiatively. Although the TAM images are relatively homogeneous for both samples, the corresponding PL images are highly structured. Themore » remarkable variation in the PL intensities as compared to transient absorption signal amplitude suggests spatially dependent PL quantum efficiency, indicative of trapping events. Furthermore, detailed analysis enables identification of two trapping regimes: a densely packed trapping region and a sparse trapping area that appear as unique spatial features in scaled PL maps.« less

Chemical exchange in biomacromolecules: Past, present, and future

PubMed Central

Palmer, Arthur G.

2014-01-01

The perspective reviews quantitative investigations of chemical exchange phenomena in proteins and other biological macromolecules using NMR spectroscopy, particularly relaxation dispersion methods. The emphasis is on techniques and applications that quantify the populations, interconversion kinetics, and structural features of sparsely populated conformational states in equilibrium with a highly populated ground state. Applications to folding, mol ecular recognition, catalysis, and allostery by proteins and nucleic acids are highlighted. PMID:24656076

NMR paves the way for atomic level descriptions of sparsely populated, transiently formed biomolecular conformers.

PubMed

Sekhar, Ashok; Kay, Lewis E

2013-08-06

The importance of dynamics to biomolecular function is becoming increasingly clear. A description of the structure-function relationship must, therefore, include the role of motion, requiring a shift in paradigm from focus on a single static 3D picture to one where a given biomolecule is considered in terms of an ensemble of interconverting conformers, each with potentially diverse activities. In this Perspective, we describe how recent developments in solution NMR spectroscopy facilitate atomic resolution studies of sparsely populated, transiently formed biomolecular conformations that exchange with the native state. Examples of how this methodology is applied to protein folding and misfolding, ligand binding, and molecular recognition are provided as a means of illustrating both the power of the new techniques and the significant roles that conformationally excited protein states play in biology.

Local sparse bump hunting reveals molecular heterogeneity of colon tumors‡

PubMed Central

Dazard, Jean-Eudes; Rao, J. Sunil; Markowitz, Sanford

2013-01-01

The question of molecular heterogeneity and of tumoral phenotype in cancer remains unresolved. To understand the underlying molecular basis of this phenomenon, we analyzed genome-wide expression data of colon cancer metastasis samples, as these tumors are the most advanced and hence would be anticipated to be the most likely heterogeneous group of tumors, potentially exhibiting the maximum amount of genetic heterogeneity. Casting a statistical net around such a complex problem proves difficult because of the high dimensionality and multi-collinearity of the gene expression space, combined with the fact that genes act in concert with one another and that not all genes surveyed might be involved. We devise a strategy to identify distinct subgroups of samples and determine the genetic/molecular signature that defines them. This involves use of the local sparse bump hunting algorithm, which provides a much more optimal and biologically faithful transformed space within which to search for bumps. In addition, thanks to the variable selection feature of the algorithm, we derived a novel sparse gene expression signature, which appears to divide all colon cancer patients into two populations: a population whose expression pattern can be molecularly encompassed within the bump and an outlier population that cannot be. Although all patients within any given stage of the disease, including the metastatic group, appear clinically homogeneous, our procedure revealed two subgroups in each stage with distinct genetic/molecular profiles. We also discuss implications of such a finding in terms of early detection, diagnosis and prognosis. PMID:22052459

Statistical power calculations for mixed pharmacokinetic study designs using a population approach.

PubMed

Kloprogge, Frank; Simpson, Julie A; Day, Nicholas P J; White, Nicholas J; Tarning, Joel

2014-09-01

Simultaneous modelling of dense and sparse pharmacokinetic data is possible with a population approach. To determine the number of individuals required to detect the effect of a covariate, simulation-based power calculation methodologies can be employed. The Monte Carlo Mapped Power method (a simulation-based power calculation methodology using the likelihood ratio test) was extended in the current study to perform sample size calculations for mixed pharmacokinetic studies (i.e. both sparse and dense data collection). A workflow guiding an easy and straightforward pharmacokinetic study design, considering also the cost-effectiveness of alternative study designs, was used in this analysis. Initially, data were simulated for a hypothetical drug and then for the anti-malarial drug, dihydroartemisinin. Two datasets (sampling design A: dense; sampling design B: sparse) were simulated using a pharmacokinetic model that included a binary covariate effect and subsequently re-estimated using (1) the same model and (2) a model not including the covariate effect in NONMEM 7.2. Power calculations were performed for varying numbers of patients with sampling designs A and B. Study designs with statistical power >80% were selected and further evaluated for cost-effectiveness. The simulation studies of the hypothetical drug and the anti-malarial drug dihydroartemisinin demonstrated that the simulation-based power calculation methodology, based on the Monte Carlo Mapped Power method, can be utilised to evaluate and determine the sample size of mixed (part sparsely and part densely sampled) study designs. The developed method can contribute to the design of robust and efficient pharmacokinetic studies.

Educational Provision in Sparsely Populated Areas of Western Australia. Studies in Rural Education No. 1.

ERIC Educational Resources Information Center

Brown, Sandra; Williams, Michael

This study of educational provisions in Western Australia, an area of 2.5 million square kilometers with a mere 1.2 million inhabitants, provides a broad picture of the complex, difficult, and expensive undertaking of providing education to a small, widely-spread population which differs in demographic, economic, and cultural characteristics. The…

Indiana: The State and Its Educational System.

ERIC Educational Resources Information Center

Hodgkinson, Harold L.

Much of Indiana is sparsely populated and is concerned with agricultural activity; 70 percent of the state's population lives in its 13 metro areas. Partly because residents have done well without high levels of education, a small proportion of adults possess college degrees. Currently, many new jobs in Indiana are at the low end of services that…

Geographical and Geodemographic Connections between Different Types of Small Area as the Origins and Destinations of Migrants to Mid-Wales

ERIC Educational Resources Information Center

Walford, Nigel

2007-01-01

Exchanges of population between supposedly "urban" and "rural" spaces have occurred throughout history as people migrate between areas with relatively, densely and sparsely settled populations. However, comparatively little is known about whether the same small areas persistently contribute to the flow and what types of…

Study of Experiences and Needs of Rural Education Achievement Program Grantees

ERIC Educational Resources Information Center

Schmidt, Rebecca Anne; Caspary, Kyra; Jonas, Deborah

2016-01-01

Nationally, 28 percent of all public elementary and secondary schools were in rural locations in 2013-14, serving 18 percent of all K-12 students (U.S. Department of Education, National Center for Education Statistics 2015). Rural schools serve students in sparsely populated areas and have smaller overall populations than schools in other…

New Maps of California to Improve Tsunami Preparedness

NASA Astrophysics Data System (ADS)

Barberopoulou, Aggeliki; Borrero, Jose C.; Uslu, Burak; Kalligeris, Nikos; Goltz, James D.; Wilson, Rick I.; Synolakis, Costas E.

2009-04-01

On 25 April 1992, an M 7.1 earthquake shook the coast of Cape Mendocino near Petrolia, Calif., followed by two large aftershocks (both M ˜ 6.6) the next day. Although no lives were lost in these temblors, 98 people were injured. These earthquakes heavily damaged older structures within this sparsely populated, mountainous region, causing more than US$66 million in losses. Approximately 20 minutes after the first earthquake, tide gauge stations in nearby Crescent City reported a surge—a tsunami with maximum wave heights (from trough to crest) of 1.1 meters. The tsunami hit Crescent City and Eureka at low tide. Fortunately, no damages occurred to city or harbor facilities—had this happened during high tide, it may have been a different story [McCarthy et al., 1993].

HIV, HCV, HBV, and syphilis among transgender women from Brazil: Assessing different methods to adjust infection rates of a hard-to-reach, sparse population.

PubMed

Bastos, Francisco I; Bastos, Leonardo Soares; Coutinho, Carolina; Toledo, Lidiane; Mota, Jurema Corrêa; Velasco-de-Castro, Carlos Augusto; Sperandei, Sandro; Brignol, Sandra; Travassos, Tamiris Severino; Dos Santos, Camila Mattos; Malta, Monica Siqueira

2018-05-01

Different sampling strategies, analytic alternatives, and estimators have been proposed to better assess the characteristics of different hard-to-reach populations and their respective infection rates (as well as their sociodemographic characteristics, associated harms, and needs) in the context of studies based on respondent-driven sampling (RDS). Despite several methodological advances and hundreds of empirical studies implemented worldwide, some inchoate findings and methodological challenges remain. The in-depth assessment of the local structure of networks and the performance of the available estimators are particularly relevant when the target populations are sparse and highly stigmatized. In such populations, bottlenecks as well as other sources of biases (for instance, due to homophily and/or too sparse or fragmented groups of individuals) may be frequent, affecting the estimates.In the present study, data were derived from a cross-sectional, multicity RDS study, carried out in 12 Brazilian cities with transgender women (TGW). Overall, infection rates for HIV and syphilis were very high, with some variation between different cities. Notwithstanding, findings are of great concern, considering the fact that female TGW are not only very hard-to-reach but also face deeply-entrenched prejudice and have been out of the reach of most therapeutic and preventive programs and projects.We cross-compared findings adjusted using 2 estimators (the classic estimator usually known as estimator II, originally proposed by Volz and Heckathorn) and a brand new strategy to adjust data generated by RDS, partially based on Bayesian statistics, called for the sake of this paper, the RDS-B estimator. Adjusted prevalence was cross-compared with estimates generated by non-weighted analyses, using what has been called by us a naïve estimator or rough estimates.

Brain Region-Specific Activity Patterns after Recent or Remote Memory Retrieval of Auditory Conditioned Fear

ERIC Educational Resources Information Center

Kwon, Jeong-Tae; Jhang, Jinho; Kim, Hyung-Su; Lee, Sujin; Han, Jin-Hee

2012-01-01

Memory is thought to be sparsely encoded throughout multiple brain regions forming unique memory trace. Although evidence has established that the amygdala is a key brain site for memory storage and retrieval of auditory conditioned fear memory, it remains elusive whether the auditory brain regions may be involved in fear memory storage or…

Microstructure Images Restoration of Metallic Materials Based upon KSVD and Smoothing Penalty Sparse Representation Approach

PubMed Central

Liang, Steven Y.

2018-01-01

Microstructure images of metallic materials play a significant role in industrial applications. To address image degradation problem of metallic materials, a novel image restoration technique based on K-means singular value decomposition (KSVD) and smoothing penalty sparse representation (SPSR) algorithm is proposed in this work, the microstructure images of aluminum alloy 7075 (AA7075) material are used as examples. To begin with, to reflect the detail structure characteristics of the damaged image, the KSVD dictionary is introduced to substitute the traditional sparse transform basis (TSTB) for sparse representation. Then, due to the image restoration, modeling belongs to a highly underdetermined equation, and traditional sparse reconstruction methods may cause instability and obvious artifacts in the reconstructed images, especially reconstructed image with many smooth regions and the noise level is strong, thus the SPSR (here, q = 0.5) algorithm is designed to reconstruct the damaged image. The results of simulation and two practical cases demonstrate that the proposed method has superior performance compared with some state-of-the-art methods in terms of restoration performance factors and visual quality. Meanwhile, the grain size parameters and grain boundaries of microstructure image are discussed before and after they are restored by proposed method. PMID:29677163

Sensorimotor Representations in Cerebellar Granule Cells in Larval Zebrafish Are Dense, Spatially Organized, and Non-temporally Patterned.

PubMed

Knogler, Laura D; Markov, Daniil A; Dragomir, Elena I; Štih, Vilim; Portugues, Ruben

2017-05-08

A fundamental question in neurobiology is how animals integrate external sensory information from their environment with self-generated motor and sensory signals in order to guide motor behavior and adaptation. The cerebellum is a vertebrate hindbrain region where all of these signals converge and that has been implicated in the acquisition, coordination, and calibration of motor activity. Theories of cerebellar function postulate that granule cells encode a variety of sensorimotor signals in the cerebellar input layer. These models suggest that representations should be high-dimensional, sparse, and temporally patterned. However, in vivo physiological recordings addressing these points have been limited and in particular have been unable to measure the spatiotemporal dynamics of population-wide activity. In this study, we use both calcium imaging and electrophysiology in the awake larval zebrafish to investigate how cerebellar granule cells encode three types of sensory stimuli as well as stimulus-evoked motor behaviors. We find that a large fraction of all granule cells are active in response to these stimuli, such that representations are not sparse at the population level. We find instead that most responses belong to only one of a small number of distinct activity profiles, which are temporally homogeneous and anatomically clustered. We furthermore identify granule cells that are active during swimming behaviors and others that are multimodal for sensory and motor variables. When we pharmacologically change the threshold of a stimulus-evoked behavior, we observe correlated changes in these representations. Finally, electrophysiological data show no evidence for temporal patterning in the coding of different stimulus durations. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

A high-capacity model for one shot association learning in the brain

PubMed Central

Einarsson, Hafsteinn; Lengler, Johannes; Steger, Angelika

2014-01-01

We present a high-capacity model for one-shot association learning (hetero-associative memory) in sparse networks. We assume that basic patterns are pre-learned in networks and associations between two patterns are presented only once and have to be learned immediately. The model is a combination of an Amit-Fusi like network sparsely connected to a Willshaw type network. The learning procedure is palimpsest and comes from earlier work on one-shot pattern learning. However, in our setup we can enhance the capacity of the network by iterative retrieval. This yields a model for sparse brain-like networks in which populations of a few thousand neurons are capable of learning hundreds of associations even if they are presented only once. The analysis of the model is based on a novel result by Janson et al. on bootstrap percolation in random graphs. PMID:25426060

Correlated activity supports efficient cortical processing

PubMed Central

Hung, Chou P.; Cui, Ding; Chen, Yueh-peng; Lin, Chia-pei; Levine, Matthew R.

2015-01-01

Visual recognition is a computational challenge that is thought to occur via efficient coding. An important concept is sparseness, a measure of coding efficiency. The prevailing view is that sparseness supports efficiency by minimizing redundancy and correlations in spiking populations. Yet, we recently reported that “choristers”, neurons that behave more similarly (have correlated stimulus preferences and spontaneous coincident spiking), carry more generalizable object information than uncorrelated neurons (“soloists”) in macaque inferior temporal (IT) cortex. The rarity of choristers (as low as 6% of IT neurons) indicates that they were likely missed in previous studies. Here, we report that correlation strength is distinct from sparseness (choristers are not simply broadly tuned neurons), that choristers are located in non-granular output layers, and that correlated activity predicts human visual search efficiency. These counterintuitive results suggest that a redundant correlational structure supports efficient processing and behavior. PMID:25610392

A high-capacity model for one shot association learning in the brain.

PubMed

Einarsson, Hafsteinn; Lengler, Johannes; Steger, Angelika

2014-01-01

We present a high-capacity model for one-shot association learning (hetero-associative memory) in sparse networks. We assume that basic patterns are pre-learned in networks and associations between two patterns are presented only once and have to be learned immediately. The model is a combination of an Amit-Fusi like network sparsely connected to a Willshaw type network. The learning procedure is palimpsest and comes from earlier work on one-shot pattern learning. However, in our setup we can enhance the capacity of the network by iterative retrieval. This yields a model for sparse brain-like networks in which populations of a few thousand neurons are capable of learning hundreds of associations even if they are presented only once. The analysis of the model is based on a novel result by Janson et al. on bootstrap percolation in random graphs.

Phylogeography of the Qinghai-Tibetan Plateau endemic Juniperus przewalskii (Cupressaceae) inferred from chloroplast DNA sequence variation.

PubMed

Zhang, Q; Chiang, T Y; George, M; Liu, J Q; Abbott, R J

2005-10-01

The vegetation of the northeast Qinghai-Tibetan Plateau is dominated by alpine meadow and desert-steppe with sparse forests scattered within it. To obtain a better understanding of the phylogeography of one constituent species of the forests in this region, we examined chloroplast trnT-trnF and trnS-trnG sequence variation within Juniperus przewalskii, a key endemic tree species. Sequence data were obtained from 392 trees in 20 populations covering the entire distribution range of the species. Six cpDNA haplotypes were identified. Significant population subdivision was detected (G(ST) = 0.772, N(ST) = 0.834), suggesting low levels of recurrent gene flow among populations and significant phylogeographic structure (N(ST) > G(ST), P < 0.05). Eight of the nine disjunct populations surveyed on the high-elevation northeast plateau were fixed for a single haplotype (A), while the remaining, more westerly population, contained the same haplotype at high frequency together with two low frequency haplotypes (C and F). In contrast, most populations that occurred at lower altitudes at the plateau edge were fixed or nearly fixed for one of two haplotypes, A or E. However, two plateau edge populations had haplotype compositions different from the rest. In one, four haplotypes (A, B, D and E) were present at approximately equivalent frequencies, which might reflect a larger refugium in the area of this population during the last glacial period. Phylogenetic analysis indicated that the most widely distributed haplotype A is not ancestral to other haplotypes. The contrasting phylogeographic structures of the haplotype-rich plateau edge area and the almost haplotype-uniform plateau platform region indicate that the plateau platform was recolonized by J. przewalskii during the most recent postglacial period. This is supported by the findings of a nested clade analysis, which inferred that postglacial range expansion from the plateau edge followed by recent fragmentation is largely responsible for the present-day spatial distribution of cpDNA haplotypes within the species.

Segmentation of High Angular Resolution Diffusion MRI using Sparse Riemannian Manifold Clustering

PubMed Central

Wright, Margaret J.; Thompson, Paul M.; Vidal, René

2015-01-01

We address the problem of segmenting high angular resolution diffusion imaging (HARDI) data into multiple regions (or fiber tracts) with distinct diffusion properties. We use the orientation distribution function (ODF) to represent HARDI data and cast the problem as a clustering problem in the space of ODFs. Our approach integrates tools from sparse representation theory and Riemannian geometry into a graph theoretic segmentation framework. By exploiting the Riemannian properties of the space of ODFs, we learn a sparse representation for each ODF and infer the segmentation by applying spectral clustering to a similarity matrix built from these representations. In cases where regions with similar (resp. distinct) diffusion properties belong to different (resp. same) fiber tracts, we obtain the segmentation by incorporating spatial and user-specified pairwise relationships into the formulation. Experiments on synthetic data evaluate the sensitivity of our method to image noise and the presence of complex fiber configurations, and show its superior performance compared to alternative segmentation methods. Experiments on phantom and real data demonstrate the accuracy of the proposed method in segmenting simulated fibers, as well as white matter fiber tracts of clinical importance in the human brain. PMID:24108748

Assessing the effects of cocaine dependence and pathological gambling using group-wise sparse representation of natural stimulus FMRI data.

PubMed

Ren, Yudan; Fang, Jun; Lv, Jinglei; Hu, Xintao; Guo, Cong Christine; Guo, Lei; Xu, Jiansong; Potenza, Marc N; Liu, Tianming

2017-08-01

Assessing functional brain activation patterns in neuropsychiatric disorders such as cocaine dependence (CD) or pathological gambling (PG) under naturalistic stimuli has received rising interest in recent years. In this paper, we propose and apply a novel group-wise sparse representation framework to assess differences in neural responses to naturalistic stimuli across multiple groups of participants (healthy control, cocaine dependence, pathological gambling). Specifically, natural stimulus fMRI (N-fMRI) signals from all three groups of subjects are aggregated into a big data matrix, which is then decomposed into a common signal basis dictionary and associated weight coefficient matrices via an effective online dictionary learning and sparse coding method. The coefficient matrices associated with each common dictionary atom are statistically assessed for each group separately. With the inter-group comparisons based on the group-wise correspondence established by the common dictionary, our experimental results demonstrated that the group-wise sparse coding and representation strategy can effectively and specifically detect brain networks/regions affected by different pathological conditions of the brain under naturalistic stimuli.

A GALEX-BASED SEARCH FOR THE SPARSE YOUNG STELLAR POPULATION IN THE TAURUS-AURIGAE STAR FORMING REGION

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gómez de Castro, Ana I.; Lopez-Santiago, Javier; López-Martínez, Fatima

2015-02-01

In this work, we identify 63 bona fide new candidates to T Tauri stars (TTSs) in the Taurus-Auriga region, using its ultraviolet excess as our baseline. The initial data set was defined from the GALEX all sky survey (AIS). The GALEX satellite obtained images in the near-ultraviolet (NUV) and far-ultraviolet (FUV) bands where TTSs show a prominent excess compared with main-sequence or giants stars. GALEX AIS surveyed the Taurus-Auriga molecular complex, as well as a fraction of the California Nebula and the Perseus complex; bright sources and dark clouds were avoided. The properties of TTSs in the ultraviolet (GALEX), opticalmore » (UCAC4), and infrared (2MASS) have been defined using the TTSs observed with the International Ultraviolet Explorer reference sample. The candidates were identified by means of a mixed ultraviolet-optical-infrared excess set of colors; we found that the FUV-NUV versus J–K color-color diagram is ideally suited for this purpose. From an initial sample of 163,313 bona fide NUV sources, a final list of 63 new candidates to TTSs in the region was produced. The search procedure has been validated by its ability to detect all known TTSs in the area surveyed: 31 TTSs. Also, we show that the weak-lined TTSs are located in a well-defined stripe in the FUV-NUV versus J–K diagram. Moreover, in this work, we provide a list of TTSs photometric standards for future GALEX-based studies of the young stellar population in star forming regions.« less

Uncovering the Anthropogenic Sea Level Change using an Improved Sea Level Reconstruction for the Indian Ocean

NASA Astrophysics Data System (ADS)

Kumar, P.; Hamlington, B.; Thompson, P. R.; Han, W.

2016-12-01

Despite having some of the world's most densely populated and vulnerable coastal regions, sea level (SL) variability in the Indian Ocean (IO) has received considerably less attention than the Pacific Ocean. Differentiating the internal variability from the long-term trend in global mean sea level (GMSL) at decadal time-scales is vital for planning and mitigation efforts in the IO region. Understanding the dynamics of internal and anthropogenic SL change is essential for understanding the dynamic pathways that link the IO basin to terrestrial climates world-wide. With a sparse pre-satellite observational record of the IO, the Indo-Pacific internal climate variability is difficult to represent accurately. However, an improved representation of pre-satellite SL variability can be achieved by using a multivariate reconstruction technique. By using cyclostationary empirical orthogonal functions (CSEOFs) that can capture time-varying spatial patterns, gaps in the historical record when observations are sparse are filled using spatial relationships from time periods when the observational network is dense. This reconstruction method combines SL data and sea surface temperature (SST) to create a SL reconstruction that spans a period from 1900 to present, long enough to study climate signals over interannual to decadal time scales. This study aims at estimating the component of SL rise that relates to anthropogenic forcing by identifying and removing the fraction related to internal variability. An improved understanding of how the internal climate variability can affect the IO SL trend and variability, will provide an insight into the future SL changes. It is also important to study links between SL and climate variability in the past to understand how SL will respond to similar climatic events in the future and if this response will be influenced by the changing climate.

Using Geostatistical Data Fusion Techniques and MODIS Data to Upscale Simulated Wheat Yield

NASA Astrophysics Data System (ADS)

Castrignano, A.; Buttafuoco, G.; Matese, A.; Toscano, P.

2014-12-01

Population growth increases food request. Assessing food demand and predicting the actual supply for a given location are critical components of strategic food security planning at regional scale. Crop yield can be simulated using crop models because is site-specific and determined by weather, management, length of growing season and soil properties. Crop models require reliable location-specific data that are not generally available. Obtaining these data at a large number of locations is time-consuming, costly and sometimes simply not feasible. An upscaling method to extend coverage of sparse estimates of crop yield to an appropriate extrapolation domain is required. This work is aimed to investigate the applicability of a geostatistical data fusion approach for merging remote sensing data with the predictions of a simulation model of wheat growth and production using ground-based data. The study area is Capitanata plain (4000 km2) located in Apulia Region, mostly cropped with durum wheat. The MODIS EVI/NDVI data products for Capitanata plain were downloaded from the Land Processes Distributed Active Archive Center (LPDAAC) remote for the whole crop cycle of durum wheat. Phenological development, biomass growth and grain quantity of durum wheat were simulated by the Delphi system, based on a crop simulation model linked to a database including soil properties, agronomical and meteorological data. Multicollocated cokriging was used to integrate secondary exhaustive information (multi-spectral MODIS data) with primary variable (sparsely distributed biomass/yield model predictions of durum wheat). The model estimates looked strongly spatially correlated with the radiance data (red and NIR bands) and the fusion data approach proved to be quite suitable and flexible to integrate data of different type and support.

Screening of Infants at Eight Months for Atypical Development in Primary Health Care in Southern Sweden

ERIC Educational Resources Information Center

Sivberg, Bengt; Lundqvist, Pia; Johanson, Ingmarie; Nordström, Berit; Persson, Bengt A.

2016-01-01

Screening studies of a population in primary health care are sparsely reported. The aim was to describe observed atypical behaviours that may be associated with autism spectrum conditions, in a population (n?=?4,329) of infants at eight months. Observations were performed by paediatric nurses. An observational instrument, named SEEK developed for…

A circular model for song motor control in Serinus canaria

PubMed Central

Alonso, Rodrigo G.; Trevisan, Marcos A.; Amador, Ana; Goller, Franz; Mindlin, Gabriel B.

2015-01-01

Song production in songbirds is controlled by a network of nuclei distributed across several brain regions, which drives respiratory and vocal motor systems to generate sound. We built a model for birdsong production, whose variables are the average activities of different neural populations within these nuclei of the song system. We focus on the predictions of respiratory patterns of song, because these can be easily measured and therefore provide a validation for the model. We test the hypothesis that it is possible to construct a model in which (1) the activity of an expiratory related (ER) neural population fits the observed pressure patterns used by canaries during singing, and (2) a higher forebrain neural population, HVC, is sparsely active, simultaneously with significant motor instances of the pressure patterns. We show that in order to achieve these two requirements, the ER neural population needs to receive two inputs: a direct one, and its copy after being processed by other areas of the song system. The model is capable of reproducing the measured respiratory patterns and makes specific predictions on the timing of HVC activity during their production. These results suggest that vocal production is controlled by a circular network rather than by a simple top-down architecture. PMID:25904860

Simulated effect of pig-population density on epidemic size and choice of control strategy for classical swine fever epidemics in The Netherlands.

PubMed

Mangen, M-J J; Nielen, M; Burrell, A M

2002-12-18

We examined the importance of pig-population density in the area of an outbreak of classical swine fever (CSF) for the spread of the infection and the choice of control measures. A spatial, stochastic, dynamic epidemiological simulation model linked to a sector-level market-and-trade model for The Netherlands were used. Outbreaks in sparsely and densely populated areas were compared under four different control strategies and with two alternative trade assumptions. The obligatory control strategy required by current EU legislation was predicted to be enough to eradicate an epidemic starting in an area with sparse pig population. By contrast, additional control measures would be necessary if the outbreak began in an area with high pig density. The economic consequences of using preventive slaughter rather than emergency vaccination as an additional control measure depended strongly on the reactions of trading partners. Reducing the number of animal movements significantly reduced the size and length of epidemics in areas with high pig density. The phenomenon of carrier piglets was included in the model with realistic probabilities of infection by this route, but it made a negligible contribution to the spread of the infection.

Towards the low-dose characterization of beam sensitive nanostructures via implementation of sparse image acquisition in scanning transmission electron microscopy

NASA Astrophysics Data System (ADS)

Hwang, Sunghwan; Han, Chang Wan; Venkatakrishnan, Singanallur V.; Bouman, Charles A.; Ortalan, Volkan

2017-04-01

Scanning transmission electron microscopy (STEM) has been successfully utilized to investigate atomic structure and chemistry of materials with atomic resolution. However, STEM’s focused electron probe with a high current density causes the electron beam damages including radiolysis and knock-on damage when the focused probe is exposed onto the electron-beam sensitive materials. Therefore, it is highly desirable to decrease the electron dose used in STEM for the investigation of biological/organic molecules, soft materials and nanomaterials in general. With the recent emergence of novel sparse signal processing theories, such as compressive sensing and model-based iterative reconstruction, possibilities of operating STEM under a sparse acquisition scheme to reduce the electron dose have been opened up. In this paper, we report our recent approach to implement a sparse acquisition in STEM mode executed by a random sparse-scan and a signal processing algorithm called model-based iterative reconstruction (MBIR). In this method, a small portion, such as 5% of randomly chosen unit sampling areas (i.e. electron probe positions), which corresponds to pixels of a STEM image, within the region of interest (ROI) of the specimen are scanned with an electron probe to obtain a sparse image. Sparse images are then reconstructed using the MBIR inpainting algorithm to produce an image of the specimen at the original resolution that is consistent with an image obtained using conventional scanning methods. Experimental results for down to 5% sampling show consistency with the full STEM image acquired by the conventional scanning method. Although, practical limitations of the conventional STEM instruments, such as internal delays of the STEM control electronics and the continuous electron gun emission, currently hinder to achieve the full potential of the sparse acquisition STEM in realizing the low dose imaging condition required for the investigation of beam-sensitive materials, the results obtained in our experiments demonstrate the sparse acquisition STEM imaging is potentially capable of reducing the electron dose by at least 20 times expanding the frontiers of our characterization capabilities for investigation of biological/organic molecules, polymers, soft materials and nanostructures in general.

Close Binaries in the Orion Nebula Cluster: On the Universality of Stellar Multiplicity and the Origin of Field Stars

NASA Astrophysics Data System (ADS)

Duchene, Gaspard; Lacour, Sylvestre; Moraux, Estelle; Bouvier, Jerome; Goodwin, Simon

2018-01-01

While stellar multiplicity is an ubiquitous outcome of star formation, there is a clear dichotomy between the multiplicity properties of young (~1 Myr-old) stellar clusters, like the ONC, which host a mostly field-like population of visual binaries, and those of equally young sparse populations, like the Taurus-Auriga region, which host twice as many stellar companions. Two distinct scenarios can account for this observation: one in which different star-forming regions form different number of stars, and one in which multiplicity properties are universal at birth but where internal cluster dynamics destroy many wide binaries. To solve this ambiguity, one must probe binaries that are sufficiently close so as not to be destroyed through interactions with other cluster members. To this end, we have conducted a survey for 10-100 au binaries in the ONC using the aperture masking technique with the VLT adaptive optics system. Among our sample of the 42 ONC members, we discovered 13 companions in this range of projected separations. This is consistent with the companion frequency observed in the Taurus population and twice as high as that observed among field stars. This survey thus strongly supports the idea that stellar multiplicity is characterized by near-universal initial properties that can later be dynamically altered. On the other hand, this exacerbates the question of the origin of field stars, since only clusters much denser than the ONC can effectively destroyed binaries closer than 100 au.

Recent Progress in Understanding the Origin and Acceleration of Suprathermal Ions and Electrons

NASA Astrophysics Data System (ADS)

Desai, Mihir; Dayeh, Maher

2017-04-01

Ions and electrons with energies that lie above (i.e., ˜2 keV) that of the core or bulk solar wind protons and electrons are known as suprathermal particles. Observations over the last decade have shown that such suprathermal particles are an important constituent of the overall seed population that is accelerated in solar and interplanetary events. Despite their increased level of importance, where these populations originate from and how they are accelerated remains highly controversial. This is partly due to the fact that these particles exist in the so-called tail regions of the corresponding solar wind distributions where high temporal and sensitivity measurements are sparse. Moreover, observations comprising long-term averages (between ˜hours to more than a day) have shown conflicting results. For instance, below ˜40 keV/nucleon the ion differential intensities in the solar wind frame appear to exhibit a near-constant power-law spectral slope of ˜1.5, perhaps indicating a universal acceleration mechanism. In contrast, at energies greater than ˜40 keV/nucleon, the ion composition changes with solar activity and the energy spectra are significantly steeper, perhaps indicating that the suprathermal pool of material also comprises lower-energy particle populations accelerated in corotating interaction regions, interplanetary shocks, and solar energetic particle events. This talk discusses recent observations of suprathermal ions and electrons in terms of state-of-the-art theories and models that have been put forward to account for their origins and acceleration.

Mapping transiently formed and sparsely populated conformations on a complex energy landscape.

PubMed

Wang, Yong; Papaleo, Elena; Lindorff-Larsen, Kresten

2016-08-23

Determining the structures, kinetics, thermodynamics and mechanisms that underlie conformational exchange processes in proteins remains extremely difficult. Only in favourable cases is it possible to provide atomic-level descriptions of sparsely populated and transiently formed alternative conformations. Here we benchmark the ability of enhanced-sampling molecular dynamics simulations to determine the free energy landscape of the L99A cavity mutant of T4 lysozyme. We find that the simulations capture key properties previously measured by NMR relaxation dispersion methods including the structure of a minor conformation, the kinetics and thermodynamics of conformational exchange, and the effect of mutations. We discover a new tunnel that involves the transient exposure towards the solvent of an internal cavity, and show it to be relevant for ligand escape. Together, our results provide a comprehensive view of the structural landscape of a protein, and point forward to studies of conformational exchange in systems that are less characterized experimentally.

Cataract surgical coverage and outcome in the Tibet Autonomous Region of China

PubMed Central

Bassett, K L; Noertjojo, K; Liu, L; Wang, F S; Tenzing, C; Wilkie, A; Santangelo, M; Courtright, P

2005-01-01

Background: A recently published, population based survey of the Tibet Autonomous Region (TAR) of China reported on low vision, blindness, and blinding conditions. This paper presents detailed findings from that survey regarding cataract, including prevalence, cataract surgical coverage, surgical outcome, and barriers to use of services. Methods: The Tibet Eye Care Assessment (TECA) was a prevalence survey of people from randomly selected households from three of the seven provinces of the TAR (Lhoka, Nakchu, and Lingzhr), representing its three main environmental regions. The survey, conducted in 1999 and 2000, assessed visual acuity, cause of vision loss, and eye care services. Results: Among the 15 900 people enumerated, 12 644 were examined (79.6%). Cataract prevalence was 5.2% and 13.8%, for the total population, and those over age 50, respectively. Cataract surgical coverage (vision <6/60) for people age 50 and older (85–90% of cataract blind) was 56% overall, 70% for men and 47% for women. The most common barriers to use of cataract surgical services were distance and cost. In the 216 eyes with cataract surgery, 60% were aphakic and 40% were pseudophakic. Pseudophakic surgery left 19% of eyes blind (<6/60) and an additional 20% of eyes with poor vision (6/24–6/60). Aphakic surgery left 24% of eyes blind and an additional 21% of eyes with poor vision. Even though more women remained blind than men, 28% versus 18% respectively, the different was not statistically significant (p = 0.25). Conclusions: Cataract surgical coverage was remarkably high despite the difficulty of providing services to such an isolated and sparse population. Cataract surgical outcome was poor for both aphakic and pseudophakic surgery. Two main priorities are improving cataract surgical quality and cataract surgical coverage, particularly for women. PMID:15615736

Assessing intra- and inter-regional climate effects on Douglas-fir biomass dynamics in Oregon and Washington, USA

Treesearch

David M. Bell; Andrew N. Gray

2016-01-01

While ecological succession shapes contemporary forest structure and dynamics, other factors like forest structure (dense vs. sparse canopies) and climate may alter structural trajectories. To assess potential sources of variation in structural trajectories, we examined proportional biomass change for a regionally dominant tree species, Douglas-fir (...

The shared and unique values of optical, fluorescence, thermal and microwave satellite data for estimating large-scale crop yields

USDA-ARS?s Scientific Manuscript database

Large-scale crop monitoring and yield estimation are important for both scientific research and practical applications. Satellite remote sensing provides an effective means for regional and global cropland monitoring, particularly in data-sparse regions that lack reliable ground observations and rep...

Deterministic matrices matching the compressed sensing phase transitions of Gaussian random matrices

PubMed Central

Monajemi, Hatef; Jafarpour, Sina; Gavish, Matan; Donoho, David L.; Ambikasaran, Sivaram; Bacallado, Sergio; Bharadia, Dinesh; Chen, Yuxin; Choi, Young; Chowdhury, Mainak; Chowdhury, Soham; Damle, Anil; Fithian, Will; Goetz, Georges; Grosenick, Logan; Gross, Sam; Hills, Gage; Hornstein, Michael; Lakkam, Milinda; Lee, Jason; Li, Jian; Liu, Linxi; Sing-Long, Carlos; Marx, Mike; Mittal, Akshay; Monajemi, Hatef; No, Albert; Omrani, Reza; Pekelis, Leonid; Qin, Junjie; Raines, Kevin; Ryu, Ernest; Saxe, Andrew; Shi, Dai; Siilats, Keith; Strauss, David; Tang, Gary; Wang, Chaojun; Zhou, Zoey; Zhu, Zhen

2013-01-01

In compressed sensing, one takes samples of an N-dimensional vector using an matrix A, obtaining undersampled measurements . For random matrices with independent standard Gaussian entries, it is known that, when is k-sparse, there is a precisely determined phase transition: for a certain region in the (,)-phase diagram, convex optimization typically finds the sparsest solution, whereas outside that region, it typically fails. It has been shown empirically that the same property—with the same phase transition location—holds for a wide range of non-Gaussian random matrix ensembles. We report extensive experiments showing that the Gaussian phase transition also describes numerous deterministic matrices, including Spikes and Sines, Spikes and Noiselets, Paley Frames, Delsarte-Goethals Frames, Chirp Sensing Matrices, and Grassmannian Frames. Namely, for each of these deterministic matrices in turn, for a typical k-sparse object, we observe that convex optimization is successful over a region of the phase diagram that coincides with the region known for Gaussian random matrices. Our experiments considered coefficients constrained to for four different sets , and the results establish our finding for each of the four associated phase transitions. PMID:23277588

SPLASH: structural pattern localization analysis by sequential histograms.

PubMed

Califano, A

2000-04-01

The discovery of sparse amino acid patterns that match repeatedly in a set of protein sequences is an important problem in computational biology. Statistically significant patterns, that is patterns that occur more frequently than expected, may identify regions that have been preserved by evolution and which may therefore play a key functional or structural role. Sparseness can be important because a handful of non-contiguous residues may play a key role, while others, in between, may be changed without significant loss of function or structure. Similar arguments may be applied to conserved DNA patterns. Available sparse pattern discovery algorithms are either inefficient or impose limitations on the type of patterns that can be discovered. This paper introduces a deterministic pattern discovery algorithm, called Splash, which can find sparse amino or nucleic acid patterns matching identically or similarly in a set of protein or DNA sequences. Sparse patterns of any length, up to the size of the input sequence, can be discovered without significant loss in performances. Splash is extremely efficient and embarrassingly parallel by nature. Large databases, such as a complete genome or the non-redundant SWISS-PROT database can be processed in a few hours on a typical workstation. Alternatively, a protein family or superfamily, with low overall homology, can be analyzed to discover common functional or structural signatures. Some examples of biologically interesting motifs discovered by Splash are reported for the histone I and for the G-Protein Coupled Receptor families. Due to its efficiency, Splash can be used to systematically and exhaustively identify conserved regions in protein family sets. These can then be used to build accurate and sensitive PSSM or HMM models for sequence analysis. Splash is available to non-commercial research centers upon request, conditional on the signing of a test field agreement. acal@us.ibm.com, Splash main page http://www.research.ibm.com/splash

Estimation for sparse vegetation information in desertification region based on Tiangong-1 hyperspectral image.

PubMed

Wu, Jun-Jun; Gao, Zhi-Hai; Li, Zeng-Yuan; Wang, Hong-Yan; Pang, Yong; Sun, Bin; Li, Chang-Long; Li, Xu-Zhi; Zhang, Jiu-Xing

2014-03-01

In order to estimate the sparse vegetation information accurately in desertification region, taking southeast of Sunite Right Banner, Inner Mongolia, as the test site and Tiangong-1 hyperspectral image as the main data, sparse vegetation coverage and biomass were retrieved based on normalized difference vegetation index (NDVI) and soil adjusted vegetation index (SAVI), combined with the field investigation data. Then the advantages and disadvantages between them were compared. Firstly, the correlation between vegetation indexes and vegetation coverage under different bands combination was analyzed, as well as the biomass. Secondly, the best bands combination was determined when the maximum correlation coefficient turned up between vegetation indexes (VI) and vegetation parameters. It showed that the maximum correlation coefficient between vegetation parameters and NDVI could reach as high as 0.7, while that of SAVI could nearly reach 0.8. The center wavelength of red band in the best bands combination for NDVI was 630nm, and that of the near infrared (NIR) band was 910 nm. Whereas, when the center wavelength was 620 and 920 nm respectively, they were the best combination for SAVI. Finally, the linear regression models were established to retrieve vegetation coverage and biomass based on Tiangong-1 VIs. R2 of all models was more than 0.5, while that of the model based on SAVI was higher than that based on NDVI, especially, the R2 of vegetation coverage retrieve model based on SAVI was as high as 0.59. By intersection validation, the standard errors RMSE based on SAVI models were lower than that of the model based on NDVI. The results showed that the abundant spectral information of Tiangong-1 hyperspectral image can reflect the actual vegetaion condition effectively, and SAVI can estimate the sparse vegetation information more accurately than NDVI in desertification region.

Hippocampal Remapping Is Constrained by Sparseness rather than Capacity

PubMed Central

Kammerer, Axel; Leibold, Christian

2014-01-01

Grid cells in the medial entorhinal cortex encode space with firing fields that are arranged on the nodes of spatial hexagonal lattices. Potential candidates to read out the space information of this grid code and to combine it with other sensory cues are hippocampal place cells. In this paper, we investigate a population of grid cells providing feed-forward input to place cells. The capacity of the underlying synaptic transformation is determined by both spatial acuity and the number of different spatial environments that can be represented. The codes for different environments arise from phase shifts of the periodical entorhinal cortex patterns that induce a global remapping of hippocampal place fields, i.e., a new random assignment of place fields for each environment. If only a single environment is encoded, the grid code can be read out at high acuity with only few place cells. A surplus in place cells can be used to store a space code for more environments via remapping. The number of stored environments can be increased even more efficiently by stronger recurrent inhibition and by partitioning the place cell population such that learning affects only a small fraction of them in each environment. We find that the spatial decoding acuity is much more resilient to multiple remappings than the sparseness of the place code. Since the hippocampal place code is sparse, we thus conclude that the projection from grid cells to the place cells is not using its full capacity to transfer space information. Both populations may encode different aspects of space. PMID:25474570

Assessing population exposure for landslide risk analysis using dasymetric cartography

NASA Astrophysics Data System (ADS)

Garcia, Ricardo A. C.; Oliveira, Sergio C.; Zezere, Jose L.

2015-04-01

Exposed Population is a major topic that needs to be taken into account in a full landslide risk analysis. Usually, risk analysis is based on an accounting of inhabitants number or inhabitants density, applied over statistical or administrative terrain units, such as NUTS or parishes. However, this kind of approach may skew the obtained results underestimating the importance of population, mainly in territorial units with predominance of rural occupation. Furthermore, the landslide susceptibility scores calculated for each terrain unit are frequently more detailed and accurate than the location of the exposed population inside each territorial unit based on Census data. These drawbacks are not the ideal setting when landslide risk analysis is performed for urban management and emergency planning. Dasymetric cartography, which uses a parameter or set of parameters to restrict the spatial distribution of a particular phenomenon, is a methodology that may help to enhance the resolution of Census data and therefore to give a more realistic representation of the population distribution. Therefore, this work aims to map and to compare the population distribution based on a traditional approach (population per administrative terrain units) and based on dasymetric cartography (population by building). The study is developed in the Region North of Lisbon using 2011 population data and following three main steps: i) the landslide susceptibility assessment based on statistical models independently validated; ii) the evaluation of population distribution (absolute and density) for different administrative territorial units (Parishes and BGRI - the basic statistical unit in the Portuguese Census); and iii) the dasymetric population's cartography based on building areal weighting. Preliminary results show that in sparsely populated administrative units, population density differs more than two times depending on the application of the traditional approach or the dasymetric cartography. This work was supported by the FCT - Portuguese Foundation for Science and Technology.

Population clustering and clonal structure evidence the relict state of Ulmus minor Mill. in the Balearic Islands

PubMed Central

Fuentes-Utrilla, P; Valbuena-Carabaña, M; Ennos, R; Gil, L

2014-01-01

Field elm (Ulmus minor) is a riparian tree that grows in rare, small populations scattered along temporary watercourses in the Balearic Islands, nowadays mostly covered with Mediterranean vegetation. Agriculture and farming on the fertile land along the periodically flooded plains have reduced the elm populations to sparse tree lines along the creek beds. The presence of field elm in this very anthropic landscape has led some authors to consider it as an introduced species in the Balearics. However, pollen data suggest these elms may be the remains of larger populations experiencing continuous population shrinkage during the Holocene, and hence be native to the isles. In this paper, we apply genetic markers to assess whether field elm is or is not indigenous to the Balearic Islands. We compare the genetic variation in nine nuclear microsatellites of six Balearic populations (three in each of the largest islands, Majorca and Minorca) with that of three natural Iberian populations located in two regions, one geologically (Baetic mountains, SE Iberia) and another historically (Catalonia, NE Iberia) related to the islands. Principal coordinates analysis and Bayesian clustering methods reveal a strong genetic differentiation of the Balearic populations from the Iberian ones, and even among islands, which support their native origin. Genotypic variation in the islands is very low and clonal reproduction is very high compared with the mainland, as it is frequently observed in populations of clonal species where sexual reproduction is limited. We discuss the practical implications of these findings for the conservation of elm genetic resources of these findings. PMID:24619184

Sparse Multivariate Autoregressive Modeling for Mild Cognitive Impairment Classification

PubMed Central

Li, Yang; Wee, Chong-Yaw; Jie, Biao; Peng, Ziwen

2014-01-01

Brain connectivity network derived from functional magnetic resonance imaging (fMRI) is becoming increasingly prevalent in the researches related to cognitive and perceptual processes. The capability to detect causal or effective connectivity is highly desirable for understanding the cooperative nature of brain network, particularly when the ultimate goal is to obtain good performance of control-patient classification with biological meaningful interpretations. Understanding directed functional interactions between brain regions via brain connectivity network is a challenging task. Since many genetic and biomedical networks are intrinsically sparse, incorporating sparsity property into connectivity modeling can make the derived models more biologically plausible. Accordingly, we propose an effective connectivity modeling of resting-state fMRI data based on the multivariate autoregressive (MAR) modeling technique, which is widely used to characterize temporal information of dynamic systems. This MAR modeling technique allows for the identification of effective connectivity using the Granger causality concept and reducing the spurious causality connectivity in assessment of directed functional interaction from fMRI data. A forward orthogonal least squares (OLS) regression algorithm is further used to construct a sparse MAR model. By applying the proposed modeling to mild cognitive impairment (MCI) classification, we identify several most discriminative regions, including middle cingulate gyrus, posterior cingulate gyrus, lingual gyrus and caudate regions, in line with results reported in previous findings. A relatively high classification accuracy of 91.89 % is also achieved, with an increment of 5.4 % compared to the fully-connected, non-directional Pearson-correlation-based functional connectivity approach. PMID:24595922

[Mediterranean diet in cancer patients and cancer free adult Arabs in Israel--a case-control study].

PubMed

Idilbi, Nasra Muhammad; Barchana, Micha; Milman, Uzi; Carel, Rafael S

2013-07-01

Although several studies have investigated the association of the Mediterranean diet (MD) with overall risk of specific cancers, data on overall cancer risk are sparse, especially in Arab populations. To compare between the score of MD in cancer patients and cancer-free adult Israeli Arabs in order to identify risk factors amenable to intervention. A case control study was conducted in northern Israel, involving 200 Arab subscribers of a regional Health Maintenance Organization (HMO). An inverse association was found (p = 0.000) between Mediterranean diet score and cancer, with OR = 0.4, 95% CI = 0.260-0.612. Greater adherence to Mediterranean diet is associated with lower prevalence of cancer. The adoption of this dietary pattern also seems to moderate the prevalence of obesity and risks of chronic diseases.

Societal Influences on Children's Psychology: The Schools in Iceland and Singapore Promote Prosocial Values, Positive Self-Concepts, and Achievement in Young Adolescents

ERIC Educational Resources Information Center

Stiles, Deborah A.

2005-01-01

In most ways the island nations of Iceland and Singapore could not be more different from each other: Iceland is sparsely populated, located near the Arctic Circle, and a very free and individualistic democratic society; Singapore is densely populated, located near the equator, and a very regulated and collectivist meritocracy. But both nations…

Training as a Tool for Community Development: 25 Years of Experience in Sparsely Populated Rural Areas in Cuenca, Spain

ERIC Educational Resources Information Center

Diaz-Puente, Jose M.; Moreno, Francisco Jose Gallego; Zamorano, Ramon

2012-01-01

Training is a key tool for community development processes in rural areas. This training is made difficult by the characteristics of the rural areas and their population. Furthermore, the methods used by traditional training bodies are not adapted to the peculiarities of these areas. This article analyses the training methodology used by the…

Forest resources in Northwest Florida

Treesearch

I.F. Eldredge

1938-01-01

Northwest Florida is the long arm of the State that extends along the Gulf Coast south of Georgia and Alabama and includes the 16 counties west of the Aucilla River (see map, fig. 1). It is a rather sparsely settled area in which only 26 percent of the total population of 254,000 (1930 Census) live in cities of 2,500 population or larger; most of the inhabitants live...

Differences in Mental Health for Sexual Minority Students at Faith-Based Colleges/Universities and in the General College/University Population

ERIC Educational Resources Information Center

Cunningham, Jamal R.

2017-01-01

The present study is an examination of mental health between lesbian, gay, bisexual, queer, and questioning students at faith based colleges/universities (FBCU) and the general college/university population (GCUP), which includes mostly non-faith based colleges/universities (NFBCU) as well as some FBCU. Current literature on this topic is sparse.…

The application of nonlinear programming and collocation to optimal aeroassisted orbital transfers

NASA Astrophysics Data System (ADS)

Shi, Y. Y.; Nelson, R. L.; Young, D. H.; Gill, P. E.; Murray, W.; Saunders, M. A.

1992-01-01

Sequential quadratic programming (SQP) and collocation of the differential equations of motion were applied to optimal aeroassisted orbital transfers. The Optimal Trajectory by Implicit Simulation (OTIS) computer program codes with updated nonlinear programming code (NZSOL) were used as a testbed for the SQP nonlinear programming (NLP) algorithms. The state-of-the-art sparse SQP method is considered to be effective for solving large problems with a sparse matrix. Sparse optimizers are characterized in terms of memory requirements and computational efficiency. For the OTIS problems, less than 10 percent of the Jacobian matrix elements are nonzero. The SQP method encompasses two phases: finding an initial feasible point by minimizing the sum of infeasibilities and minimizing the quadratic objective function within the feasible region. The orbital transfer problem under consideration involves the transfer from a high energy orbit to a low energy orbit.

Synthesis and Characterization of Novel Anchorlipids for Tethered Bilayer Lipid Membranes.

PubMed

Andersson, Jakob; Knobloch, Jacqueline J; Perkins, Michael V; Holt, Stephen A; Köper, Ingo

2017-05-09

Tethered bilayer lipid membranes are versatile solid-supported model membrane systems. Core to these systems is an anchorlipid that covalently links a lipid bilayer to a support. The molecular structure of these lipids can have a significant impact on the properties of the resulting bilayer. Here, the synthesis of anchorlipids containing ester groups in the tethering part is described. The lipids are used to form bilayer membranes, and the resulting structures are compared with membranes formed using conventional anchorlipids or sparsely tethered membranes. All membranes showed good electrical sealing properties; the disulphide-terminated anchorlipids could be used in a sparsely tethered system without significantly reducing the sealing properties of the lipid bilayers. The sparsely tethered systems also allowed for higher ion transport across the membrane, which is in good correlation with higher hydration of the spacer region as seen by neutron scattering.

Role of resting cysts in Chilean Alexandrium catenella dinoflagellate blooms revisited.

PubMed

Mardones, Jorge I; Bolch, Chris; Guzmán, Leonardo; Paredes, Javier; Varela, Daniel; Hallegraeff, Gustaaf M

2016-05-01

The detection of sparse Alexandrium catenella-resting cysts in sediments of southern Chilean fjords has cast doubts on their importance in the recurrence of massive toxic dinoflagellate blooms in the region. The role of resting cysts and the existence of different regional Chilean populations was studied by culturing and genetic approaches to define: (1) cyst production; (2) dormancy period; (3) excystment success; (4) offspring viability and (5) strain mating compatibility. This study newly revealed a short cyst dormancy (minimum 69 days), the role of key abiotic factors (in decreasing order salinity, irradiance, temperature and nutrients) controlling cyst germination (max. 60%) and germling growth rates (up to 0.36-0.52div.day -1 ). Amplified fragment length polymorphism (AFLP) characterization showed significant differences in genetic distances (GD) among A. catenella populations that were primarily determined by the geographical origin of isolates and most likely driven by oceanographic dispersal barriers. A complex heterothallic mating system pointed to variable reproductive compatibility (RCs) among Chilean strains that was high among northern (Los Lagos/North Aysén) and southern populations (Magallanes), but limited among the genetically differentiated central (South Aysén) populations. Field cyst surveys after a massive 2009 bloom event revealed the existence of exceptional high cyst densities in particular areas of the fjords (max. 14.627cystscm -3 ), which contrast with low cyst concentrations (<221.3cystscm -3 ) detected by previous oceanographic campaigns. In conclusion, the present study suggests that A. catenella resting cysts play a more important role in the success of this species in Chilean fjords than previously thought. Results from in vitro experiments suggest that pelagic-benthic processes can maintain year-round low vegetative cell concentrations in the water column, but also can explain the detection of high cysts aggregations after the 2009-bloom event. Regional drivers that lead to massive outbreaks, however, are still unknown but potential scenarios are discussed. Copyright © 2016 Elsevier B.V. All rights reserved.

Sparse evidence for equine or avian influenza virus infections among Mongolian adults with animal exposures.

PubMed

Khurelbaatar, Nyamdavaa; Krueger, Whitney S; Heil, Gary L; Darmaa, Badarchiin; Ulziimaa, Daramragchaa; Tserennorov, Damdindorj; Baterdene, Ariungerel; Anderson, Benjamin D; Gray, Gregory C

2013-11-01

In recent years, Mongolia has experienced recurrent epizootics of equine influenza virus (EIV) among its 2·1 million horses and multiple incursions of highly pathogenic avian influenza (HPAI) virus via migrating birds. No human EIV or HPAI infections have been reported. In 2009, 439 adults in Mongolia were enrolled in a population-based study of zoonotic influenza transmission. Enrollment sera were examined for serological evidence of infection with nine avian, three human, and one equine influenza virus strains. Seroreactivity was sparse among participants suggesting little human risk of zoonotic influenza infection. © 2013 John Wiley & Sons Ltd.

Manitoba

Atmospheric Science Data Center

2013-04-17

... black spruce, jack pine, tamarack, willow, and birch. Human population density is sparse, averaging about 1 person per 10 square ... Big Sand Lake, above image center, was reported to be under control on June 20, whereas the plume at lower left, to the west of Gold Sand ...

Amphibian Population Sensitivity to Environmental and Anthropogenic Impacts on Larval Development and Survival

EPA Science Inventory

Anticipating chronic effects of contaminant exposure on amphibian species is complicated both by toxicological and ecological uncertainty. Data for both chemical exposures and amphibian vital rates, including altered growth, are sparse. Developmental plasticity in amphibians fu...

Evaluating the use of transfers for improving demand responsive systems adopting zoning strategies.

DOT National Transportation Integrated Search

2011-08-01

Due to widely dispersed population density over large and sparsely suburban/rural areas, : conventional fixed route transit services hardly satisfy the travel needs of their residents. As an : alternative, demand responsive transit (DRT) systems have...

Phylogeography of Japanese horse chestnut (Aesculus turbinata) in the Japanese Archipelago based on chloroplast DNA haplotypes.

PubMed

Sugahara, Kanako; Kaneko, Yuko; Ito, Satoshi; Yamanaka, Keisuke; Sakio, Hitoshi; Hoshizaki, Kazuhiko; Suzuki, Wajiro; Yamanaka, Norikazu; Setoguchi, Hiroaki

2011-01-01

Japanese horse chestnut (Aesculus turbinata: Hippocastanaceae) is one of the typical woody plants that grow in temperate riparian forests in the Japanese Archipelago. To analyze the phylogeography of this plant in the Japanese Archipelago, we determined cpDNA haplotypes for 337 samples from 55 populations covering the entire distribution range. Based on 1,313 bp of two spacers, we determined ten haplotypes that are distinguished from adjacent haplotypes by one or two steps. Most of the populations had a single haplotype, suggesting low diversity. Spatial analysis of molecular variance suggested three obvious phylogeographic structures in western Japan, where Japanese horse chestnut is scattered and isolated in mountainous areas. Conversely, no clear phylogeographic structure was observed from the northern to the southern limit of this species, including eastern Japan, where this plant is more common. Rare and private haplotypes were also found in southwestern Japan, where Japanese horse chestnuts are distributed sparsely. These findings imply that western Japan might have maintained a relatively large habitat for A. turbinata during the Quaternary climatic oscillations, while northerly regions could not.

Exploitation of Wireless Technology in Remote Care Processes

NASA Astrophysics Data System (ADS)

Hämäläinen, Matti; Taparugssanagorn, Attaphongse; Iinatti, Jari; Kohno, Ryuji

The average age of population is predicted to be raised universally but the number of nursing staff is not increasing at the same rate. This leads us to the situation where, e.g., we have too many patients for one nurse. On the other hand, sparse population in some regions, such as Northern or Eastern Finland, causes a severe problem that doctors are far away from patient. In this paper, we summarize the possibilities and applications that utilize wireless technologies in healthcare sector and which can be useful in nursing activities. The use of new innovations is one way to solve the problems that are based on the expected lack of professional staff in the future. Despite of the very natural hospital link, the developed technical solutions have applications outside hospital. Remote care of aging people and other special groups need to be done daily and almost real-time. Keeping people home instead of hospital is one way to decrease the entire care costs. In addition to the obvious human context, we derive some other applications where we can benefit wireless nursing and remote sensing techniques.

Predicting Deforestation Patterns in Loreto, Peru from 2000-2010 Using a Nested GLM Approach

NASA Astrophysics Data System (ADS)

Vijay, V.; Jenkins, C.; Finer, M.; Pimm, S.

2013-12-01

Loreto is the largest province in Peru, covering about 370,000 km2. Because of its remote location in the Amazonian rainforest, it is also one of the most sparsely populated. Though a majority of the region remains covered by forest, deforestation is being driven by human encroachment through industrial activities and the spread of colonization and agriculture. The importance of accurate predictive modeling of deforestation has spawned an extensive body of literature on the topic. We present a nested GLM approach based on predictions of deforestation from 2000-2010 and using variables representing the expected drivers of deforestation. Models were constructed using 2000 to 2005 changes and tested against data for 2005 to 2010. The most complex model, which included transportation variables (roads and navigable rivers), spatial contagion processes, population centers and industrial activities, performed better in predicting the 2005 to 2010 changes (75.8% accurate) than did a simpler model using only transportation variables (69.2% accurate). Finally we contrast the GLM approach with a more complex spatially articulated model.

76 FR 47142 - Submission for OMB Review; Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2011-08-04

... species placement within a predator/prey chain or food web can serve as an ecological indicator. Similarly... Sound region are sparse; yet, they are critical to the development of sound ecosystem health targets...

Sparse estimation of model-based diffuse thermal dust emission

NASA Astrophysics Data System (ADS)

Irfan, Melis O.; Bobin, Jérôme

2018-03-01

Component separation for the Planck High Frequency Instrument (HFI) data is primarily concerned with the estimation of thermal dust emission, which requires the separation of thermal dust from the cosmic infrared background (CIB). For that purpose, current estimation methods rely on filtering techniques to decouple thermal dust emission from CIB anisotropies, which tend to yield a smooth, low-resolution, estimation of the dust emission. In this paper, we present a new parameter estimation method, premise: Parameter Recovery Exploiting Model Informed Sparse Estimates. This method exploits the sparse nature of thermal dust emission to calculate all-sky maps of thermal dust temperature, spectral index, and optical depth at 353 GHz. premise is evaluated and validated on full-sky simulated data. We find the percentage difference between the premise results and the true values to be 2.8, 5.7, and 7.2 per cent at the 1σ level across the full sky for thermal dust temperature, spectral index, and optical depth at 353 GHz, respectively. A comparison between premise and a GNILC-like method over selected regions of our sky simulation reveals that both methods perform comparably within high signal-to-noise regions. However, outside of the Galactic plane, premise is seen to outperform the GNILC-like method with increasing success as the signal-to-noise ratio worsens.

Magnetotelluric data, Taos Plateau Volcanic Field, New Mexico

USGS Publications Warehouse

Ailes, Chad E.; Rodriguez, Brian D.

2010-01-01

The population of the San Luis Basin region of northern New Mexico is growing. Water shortfalls could have serious consequences. Future growth and land management in the region depend on accurate assessment and protection of the region's groundwater resources. An important issue in managing the groundwater resources is a better understanding of the hydrogeology of the Santa Fe Group and the nature of the sedimentary deposits that fill the Rio Grande rift, which contain the principal groundwater aquifers. The shallow unconfined aquifer and the deeper confined Santa Fe Group aquifer in the San Luis Basin are the main sources of municipal water for the region. The U.S. Geological Survey (USGS) is conducting a series of multidisciplinary studies of the San Luis Basin. Detailed geologic mapping, high-resolution airborne magnetic surveys, gravity surveys, an electromagnetic survey called magnetotellurics (MT), and hydrologic and lithologic data are being used to better understand the aquifers. This report describes a regional east-west MT sounding profile acquired in late July 2009 across the Taos Plateau Volcanic Field where drillhole data are sparse. Resistivity modeling of the MT data can be used to help map changes in electrical resistivity with depths that are related to differences in rock types. These various rock types help control the properties of aquifers. The purpose of this report is to release the MT sounding data collected along the east-west profile. No interpretation of the data is included.

Height changes along selected lines through the Death Valley region, California and Nevada, 1905-1984

USGS Publications Warehouse

Castle, Robert O.; Gilmore, Thomas D.; Walker, James P.; Castle, Susan A.

2005-01-01

Comparisons among repeated levelings along selected lines through the Death Valley region of California and adjacent parts of Nevada have disclosed surprisingly large vertical displacements. The vertical control data in this lightly populated area is sparse; moreover, as much as a third of the recovered data is so thoroughly contaminated by systematic error and survey blunders that no attempt was made to correct these data and they were simply discarded. In spite of these limitations, generally episodic, commonly large vertical displacements are disclosed along a number of lines. Displacements in excess of 0.4 m, with respect to our selected control point at Beatty, Nevada, and differential displacements of about 0.7 m apparently occurred during the earlier years of the 20th century and continued episodically through at least 1943. While this area contains abundant evidence of continuing tectonic activity through latest Quaternary time, it is virtually devoid of historic seismicity. We have detected no clear connection between the described vertical displacements and fault zones reportedly active during Holocene time, although we sense some association with several more broadly defined tectonic features.

Transition from grant funding to a self-supporting burn telemedicine program in the western United States.

PubMed

Russell, Katie W; Saffle, Jeffrey R; Theurer, Louanna; Cochran, Amalia L

2015-12-01

Many Americans have limited access to specialty burn care, and telemedicine has been proposed as a means to address this disparity. However, many telemedicine programs have been founded on grant support and then fail once the grant support expires. Our objective was to demonstrate that a burn telemedicine program can be financially viable. This retrospective review from 2005 to 2014 evaluated burn telemedicine visits and financial reimbursement during and after a Technology Opportunities Program grant to a regional burn center. In 2005, we had 12 telemedicine visits, which increased to 458 in 2014. In terms of how this compares to in-person clinic visits, we saw a consistent increase in telemedicine visits as a percentage of total clinic visits from .26% in 2005 to 14% in 2014. Median telemedicine reimbursement has been equivalent to in-person visits. Specialty telemedicine programs can successfully transition from grant-funded enterprises to self-sustaining. The availability of telemedicine services allows access to specialty expertise in a large and sparsely populated region without imposing an undue financial burden. Copyright © 2015 Elsevier Inc. All rights reserved.

The red edge in arid region vegetation: 340-1060 nm spectra

NASA Technical Reports Server (NTRS)

Ray, Terrill W.; Murray, Bruce C.; Chehbouni, A.; Njoku, Eni

1993-01-01

The remote sensing study of vegetated regions of the world has typically been focused on the use of broad-band vegetation indices such as NDVI. Various modifications of these indices have been developed in attempts to minimize the effect of soil background, e.g., SAVI, or to reduce the effect of the atmosphere, e.g., ARVI. Most of these indices depend on the so-called 'red edge,' the sharp transition between the strong absorption of chlorophyll pigment in visible wavelengths and the strong scattering in the near-infrared from the cellular structure of leaves. These broadband indices tend to become highly inaccurate as the green canopy cover becomes sparse. The advent of high spectral resolution remote sensing instrument such as the Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) has allowed the detection of narrow spectral features in vegetation and there are reports of detection of the red edge even for pixels with very low levels of green vegetation cover by Vane et al. and Elvidge et al., and to characterize algal biomass in coastal areas. Spectral mixing approaches similar to those of Smith et al. can be extended into the high spectral resolution domain allowing for the analysis of more endmembers, and potentially, discrimination between material with narrow spectral differences. Vegetation in arid regions tends to be sparse, often with small leaves such as the creosote bush. Many types of arid region vegetation spend much of the year with their leaves in a senescent state, i.e., yellow, with lowered chlorophyll pigmentation. The sparseness of the leaves of many arid region plants has the dual effect of lowering the green leaf area which can be observed and of allowing more of the sub-shrub soil to be visible which further complicates the spectrum of a region covered with arid region vegetation. Elvidge examined the spectral characteristics of dry plant materials showing significant differences in the region of the red edge and the diagnostic ligno-cellulose absorptions at 2090 nm and 2300 nm. Ray et al. detected absorption at 2100 nm in AVIRIS spectra of an abandoned field known to be covered by a great deal of dead plant litter. In order to better study arid region vegetation remote sensing data, it is necessary to better characterize the reflectance spectra of in situ, living, arid region plants.

AMPHIBIAN DECLINES AND ENVIRONMENTAL CHANGE IN THE EASTERN "MOJAVE DESERT"

EPA Science Inventory

A number of amphibian species historically inhabited sparsely distributed wetlands in the Mojave Desert, USA, habitats that have been dramatically altered or eliminated as a result of human activities. The population status and distribution of amphibians were investigated in a 20...

State-wide Conservation Forum to Facilitate Cooperative Conservation

DTIC Science & Technology

2007-03-01

leaf pine ecosystem that is home to the red-cockaded woodpecker (RCW), an endangered species. After significant train- ing restrictions were imposed...ranking). Caroline and Essex counties were rural, sparsely populated areas, dominated by forestland and small farms. Both counties are experiencing

Distributed Bandpass Filtering and Signal Demodulation in Cortical Network Models

NASA Astrophysics Data System (ADS)

McDonnell, Mark D.

Experimental recordings of cortical activity often exhibit narrowband oscillations, at various center frequencies ranging in the order of 1-200 Hz. Many neuronal mechanisms are known to give rise to oscillations, but here we focus on a population effect known as sparsely synchronised oscillations. In this effect, individual neurons in a cortical network fire irregularly at slow average spike rates (1-10 Hz), but the population spike rate oscillates at gamma frequencies (greater than 40 Hz) in response to spike bombardment from the thalamus. These cortical networks form recurrent (feedback) synapses. Here we describe a model of sparsely synchronized population oscillations using the language of feedback control engineering, where we treat spiking as noisy feedback. We show, using a biologically realistic model of synaptic current that includes a delayed response to inputs, that the collective behavior of the neurons in the network is like a distributed bandpass filter acting on the network inputs. Consequently, the population response has the character of narrowband random noise, and therefore has an envelope and instantaneous frequency with lowpass characteristics. Given that there exist biologically plausible neuronal mechanisms for demodulating the envelope and instantaneous frequency, we suggest there is potential for similar effects to be exploited in nanoscale electronics implementations of engineered communications receivers.

Deformable segmentation via sparse representation and dictionary learning.

PubMed

Zhang, Shaoting; Zhan, Yiqiang; Metaxas, Dimitris N

2012-10-01

"Shape" and "appearance", the two pillars of a deformable model, complement each other in object segmentation. In many medical imaging applications, while the low-level appearance information is weak or mis-leading, shape priors play a more important role to guide a correct segmentation, thanks to the strong shape characteristics of biological structures. Recently a novel shape prior modeling method has been proposed based on sparse learning theory. Instead of learning a generative shape model, shape priors are incorporated on-the-fly through the sparse shape composition (SSC). SSC is robust to non-Gaussian errors and still preserves individual shape characteristics even when such characteristics is not statistically significant. Although it seems straightforward to incorporate SSC into a deformable segmentation framework as shape priors, the large-scale sparse optimization of SSC has low runtime efficiency, which cannot satisfy clinical requirements. In this paper, we design two strategies to decrease the computational complexity of SSC, making a robust, accurate and efficient deformable segmentation system. (1) When the shape repository contains a large number of instances, which is often the case in 2D problems, K-SVD is used to learn a more compact but still informative shape dictionary. (2) If the derived shape instance has a large number of vertices, which often appears in 3D problems, an affinity propagation method is used to partition the surface into small sub-regions, on which the sparse shape composition is performed locally. Both strategies dramatically decrease the scale of the sparse optimization problem and hence speed up the algorithm. Our method is applied on a diverse set of biomedical image analysis problems. Compared to the original SSC, these two newly-proposed modules not only significant reduce the computational complexity, but also improve the overall accuracy. Copyright © 2012 Elsevier B.V. All rights reserved.

Repeating Marmara Sea earthquakes: indication for fault creep

NASA Astrophysics Data System (ADS)

Bohnhoff, Marco; Wollin, Christopher; Domigall, Dorina; Küperkoch, Ludger; Martínez-Garzón, Patricia; Kwiatek, Grzegorz; Dresen, Georg; Malin, Peter E.

2017-07-01

Discriminating between a creeping and a locked status of active faults is of central relevance to characterize potential rupture scenarios of future earthquakes and the associated seismic hazard for nearby population centres. In this respect, highly similar earthquakes that repeatedly activate the same patch of an active fault portion are an important diagnostic tool to identify and possibly even quantify the amount of fault creep. Here, we present a refined hypocentre catalogue for the Marmara region in northwestern Turkey, where a magnitude M up to 7.4 earthquake is expected in the near future. Based on waveform cross-correlation for selected spatial seismicity clusters, we identify two magnitude M ∼ 2.8 repeater pairs. These repeaters were identified as being indicative of fault creep based on the selection criteria applied to the waveforms. They are located below the western part of the Marmara section of the North Anatolian Fault Zone and are the largest reported repeaters for the larger Marmara region. While the eastern portion of the Marmara seismic gap has been identified to be locked, only sparse information on the deformation status has been reported for its western part. Our findings indicate that the western Marmara section deforms aseismically to a substantial extent, which reduces the probability for this region to host a nucleation point for the pending Marmara earthquake. This is of relevance, since a nucleation of the Marmara event in the west and subsequent eastward rupture propagation towards the Istanbul metropolitan region would result in a substantially higher seismic hazard and resulting risk than if the earthquake would nucleate in the east and thus propagate westward away from the population centre Istanbul.

Sparse EEG/MEG source estimation via a group lasso

PubMed Central

Lim, Michael; Ales, Justin M.; Cottereau, Benoit R.; Hastie, Trevor

2017-01-01

Non-invasive recordings of human brain activity through electroencephalography (EEG) or magnetoencelphalography (MEG) are of value for both basic science and clinical applications in sensory, cognitive, and affective neuroscience. Here we introduce a new approach to estimating the intra-cranial sources of EEG/MEG activity measured from extra-cranial sensors. The approach is based on the group lasso, a sparse-prior inverse that has been adapted to take advantage of functionally-defined regions of interest for the definition of physiologically meaningful groups within a functionally-based common space. Detailed simulations using realistic source-geometries and data from a human Visual Evoked Potential experiment demonstrate that the group-lasso method has improved performance over traditional ℓ2 minimum-norm methods. In addition, we show that pooling source estimates across subjects over functionally defined regions of interest results in improvements in the accuracy of source estimates for both the group-lasso and minimum-norm approaches. PMID:28604790

Sparse Reconstruction of Regional Gravity Signal Based on Stabilized Orthogonal Matching Pursuit (SOMP)

NASA Astrophysics Data System (ADS)

Saadat, S. A.; Safari, A.; Needell, D.

2016-06-01

The main role of gravity field recovery is the study of dynamic processes in the interior of the Earth especially in exploration geophysics. In this paper, the Stabilized Orthogonal Matching Pursuit (SOMP) algorithm is introduced for sparse reconstruction of regional gravity signals of the Earth. In practical applications, ill-posed problems may be encountered regarding unknown parameters that are sensitive to the data perturbations. Therefore, an appropriate regularization method needs to be applied to find a stabilized solution. The SOMP algorithm aims to regularize the norm of the solution vector, while also minimizing the norm of the corresponding residual vector. In this procedure, a convergence point of the algorithm that specifies optimal sparsity-level of the problem is determined. The results show that the SOMP algorithm finds the stabilized solution for the ill-posed problem at the optimal sparsity-level, improving upon existing sparsity based approaches.

A multi-objective framework to predict flows of ungauged rivers within regions of sparse hydrometeorologic observation

NASA Astrophysics Data System (ADS)

Alipour, M.; Kibler, K. M.

2017-12-01

Despite advances in flow prediction, managers of ungauged rivers located within broad regions of sparse hydrometeorologic observation still lack prescriptive methods robust to the data challenges of such regions. We propose a multi-objective streamflow prediction framework for regions of minimum observation to select models that balance runoff efficiency with choice of accurate parameter values. We supplement sparse observed data with uncertain or low-resolution information incorporated as `soft' a priori parameter estimates. The performance of the proposed framework is tested against traditional single-objective and constrained single-objective calibrations in two catchments in a remote area of southwestern China. We find that the multi-objective approach performs well with respect to runoff efficiency in both catchments (NSE = 0.74 and 0.72), within the range of efficiencies returned by other models (NSE = 0.67 - 0.78). However, soil moisture capacity estimated by the multi-objective model resonates with a priori estimates (parameter residuals of 61 cm versus 289 and 518 cm for maximum soil moisture capacity in one catchment, and 20 cm versus 246 and 475 cm in the other; parameter residuals of 0.48 versus 0.65 and 0.7 for soil moisture distribution shape factor in one catchment, and 0.91 versus 0.79 and 1.24 in the other). Thus, optimization to a multi-criteria objective function led to very different representations of soil moisture capacity as compared to models selected by single-objective calibration, without compromising runoff efficiency. These different soil moisture representations may translate into considerably different hydrological behaviors. The proposed approach thus offers a preliminary step towards greater process understanding in regions of severe data limitations. For instance, the multi-objective framework may be an adept tool to discern between models of similar efficiency to select models that provide the "right answers for the right reasons". Managers may feel more confident to utilize such models to predict flows in fully ungauged areas.

Uncertainty in regional temperatures inferred from sparse global observations: Application to a probabilistic classification of El Niño

NASA Astrophysics Data System (ADS)

Ilyas, Maryam; Brierley, Christopher M.; Guillas, Serge

2017-09-01

Instrumental records showing increases in surface temperature are some of the robust and iconic evidence of climate change. But how much should we trust regional temperature estimates interpolated from sparse observations? Here we quantify the uncertainty in the instrumental record by applying multiresolution lattice kriging, a recently developed interpolation technique that leverages the multiple spatial scales of temperature anomalies. The probability of monthly anomalies across the globe is represented by an ensemble, based on HadCRUT4 and accounting for observational and coverage uncertainties. To demonstrate the potential of these new data, we investigate the area-averaged temperature anomalies over the Niño 3.4 region in the equatorial Pacific. Having developed a definition of the El Niño-Southern Oscillation (ENSO) able to cope with probability distribution functions, we classify the ENSO state for each year since 1851. We find that for many years it is ambiguous as to whether there was an El Niño or not from the Niño 3.4 region alone. These years are mainly before 1920, but also just after World War II.

Sparse reconstruction of breast MRI using homotopic L0 minimization in a regional sparsified domain.

PubMed

Wong, Alexander; Mishra, Akshaya; Fieguth, Paul; Clausi, David A

2013-03-01

The use of MRI for early breast examination and screening of asymptomatic women has become increasing popular, given its ability to provide detailed tissue characteristics that cannot be obtained using other imaging modalities such as mammography and ultrasound. Recent application-oriented developments in compressed sensing theory have shown that certain types of magnetic resonance images are inherently sparse in particular transform domains, and as such can be reconstructed with a high level of accuracy from highly undersampled k-space data below Nyquist sampling rates using homotopic L0 minimization schemes, which holds great potential for significantly reducing acquisition time. An important consideration in the use of such homotopic L0 minimization schemes is the choice of sparsifying transform. In this paper, a regional differential sparsifying transform is investigated for use within a homotopic L0 minimization framework for reconstructing breast MRI. By taking local regional characteristics into account, the regional differential sparsifying transform can better account for signal variations and fine details that are characteristic of breast MRI than the popular finite differential transform, while still maintaining strong structure fidelity. Experimental results show that good breast MRI reconstruction accuracy can be achieved compared to existing methods.

Mitochondrial DNA haplotype distribution patterns in Pinus ponderosa (Pinaceae): range-wide evolutionary history and implications for conservation.

PubMed

Potter, Kevin M; Hipkins, Valerie D; Mahalovich, Mary F; Means, Robert E

2013-08-01

Ponderosa pine (Pinus ponderosa Douglas ex P. Lawson & C. Lawson) exhibits complicated patterns of morphological and genetic variation across its range in western North America. This study aims to clarify P. ponderosa evolutionary history and phylogeography using a highly polymorphic mitochondrial DNA marker, with results offering insights into how geographical and climatological processes drove the modern evolutionary structure of tree species in the region. We amplified the mtDNA nad1 second intron minisatellite region for 3,100 trees representing 104 populations, and sequenced all length variants. We estimated population-level haplotypic diversity and determined diversity partitioning among varieties, races and populations. After aligning sequences of minisatellite repeat motifs, we evaluated evolutionary relationships among haplotypes. The geographical structuring of the 10 haplotypes corresponded with division between Pacific and Rocky Mountain varieties. Pacific haplotypes clustered with high bootstrap support, and appear to have descended from Rocky Mountain haplotypes. A greater proportion of diversity was partitioned between Rocky Mountain races than between Pacific races. Areas of highest haplotypic diversity were the southern Sierra Nevada mountain range in California, northwestern California, and southern Nevada. Pinus ponderosa haplotype distribution patterns suggest a complex phylogeographic history not revealed by other genetic and morphological data, or by the sparse paleoecological record. The results appear consistent with long-term divergence between the Pacific and Rocky Mountain varieties, along with more recent divergences not well-associated with race. Pleistocene refugia may have existed in areas of high haplotypic diversity, as well as the Great Basin, Southwestern United States/northern Mexico, and the High Plains.

Risk of congenital anomalies in the vicinity of municipal solid waste incinerators

PubMed Central

Cordier, S; Chevrier, C; Robert-Gnansia, E; Lorente, C; Brula, P; Hours, M

2004-01-01

Background: Although municipal solid waste incineration (MSWI) has contributed to increase the overall environmental load of particulate matter containing dioxins and metals, evidence of health consequences to populations is sparse. Aims: To assess at a regional level (in southeast France) the impact of these emissions on birth defect rates. Methods: Communities with fewer than 50 000 inhabitants surrounding the 70 incinerators that operated at least one year from 1988 to 1997 were studied. Each exposed community (n = 194) was assigned an exposure index estimated from a Gaussian plume model. Poisson models and a reference population of the 2678 unexposed communities in the region were used to calculate relative risks for congenital malformations, adjusted for year of birth, maternal age, department of birth, population density, average family income, and when available, local road traffic. Results: The rate of congenital anomalies was not significantly higher in exposed compared with unexposed communities. Some subgroups of major anomalies, specifically facial clefts and renal dysplasia, were more frequent in the exposed communities. Among exposed communities, a dose-response trend of risk with increasing exposure was observed for obstructive uropathies. Risks of cardiac anomalies, obstructive uropathies, and skin anomalies increased linearly with road traffic density. Conclusions: Although both incinerator emissions and road traffic may plausibly explain some of the excess risks observed, several alternative explanations, including exposure misclassification, ascertainment bias, and residual confounding cannot be excluded. Some of the effects observed, if real, might be attributable to old-technology MSWIs and the persistent pollution they have generated. PMID:14691267

Management of land use conflicts in the United States Rocky Mountains

USGS Publications Warehouse

Baron, Jill S.; Theobald, D.M.; Fagre, D.B.

2000-01-01

People have long been attracted to the beauty and grandeur of the Rocky Mountains. Until very recently, however, the Rocky Mountain region was sparsely populated and its use mostly extractive. Commodities removed in massive quantities included first beaver, then precious metals, timber, energy, and finally water. There has been a fundamental change in migration patterns since the 1980s. Populations are expanding not only in urban areas; many rural areas are also growing faster. In an affluent and mobile society, Americans are moving to the West for aesthetic reasons, often based on perceptions that have little to do with regional roots, family ties, or economic opportunities.Wallace Stegner described the West into the 1980s as a colony for the rest of the nation. “It seems to be almost like a continuous repetitive act of God that the western resources should be mined …, that populations should rush in and have to rush out again, or trickle out again…. Get in, get rich, get out….Every boom and bust leaves the West physically a little poorer, a little worse damaged” (Stegner 1996).In an article about actor and director Robert Redford, writer Richard Raynor talks about unexpected side effects Redford's movies have had on American behavior. “A River Runs Through It" dangerously swelled the banks of American rivers with novice fishermen. It seems likely that Redford's loving rendition of ranch life in The Horse Whisperer … will have a similar effect on western Montana, filling it with even more people in a nostalgic search for American rapture and simplicity” (1998).

Example-Based Image Colorization Using Locality Consistent Sparse Representation.

PubMed

Bo Li; Fuchen Zhao; Zhuo Su; Xiangguo Liang; Yu-Kun Lai; Rosin, Paul L

2017-11-01

Image colorization aims to produce a natural looking color image from a given gray-scale image, which remains a challenging problem. In this paper, we propose a novel example-based image colorization method exploiting a new locality consistent sparse representation. Given a single reference color image, our method automatically colorizes the target gray-scale image by sparse pursuit. For efficiency and robustness, our method operates at the superpixel level. We extract low-level intensity features, mid-level texture features, and high-level semantic features for each superpixel, which are then concatenated to form its descriptor. The collection of feature vectors for all the superpixels from the reference image composes the dictionary. We formulate colorization of target superpixels as a dictionary-based sparse reconstruction problem. Inspired by the observation that superpixels with similar spatial location and/or feature representation are likely to match spatially close regions from the reference image, we further introduce a locality promoting regularization term into the energy formulation, which substantially improves the matching consistency and subsequent colorization results. Target superpixels are colorized based on the chrominance information from the dominant reference superpixels. Finally, to further improve coherence while preserving sharpness, we develop a new edge-preserving filter for chrominance channels with the guidance from the target gray-scale image. To the best of our knowledge, this is the first work on sparse pursuit image colorization from single reference images. Experimental results demonstrate that our colorization method outperforms the state-of-the-art methods, both visually and quantitatively using a user study.

Population pressure and human carrying capacity in selected locations of Machakos and Kitui districts.

PubMed

Bernard, F E; Thom, D J

1981-04-01

The nature and magnitude of population pressure in Machakos and Kitui Districts of Kenya were investigated. Specific study objectives were: 1) to examine the roots and evolution of the problem; 2) to compute carrying capacity for a sample of locations and ecozones in the 2 districts; and 3) to consider agricultural and demographic implications of the findings. Carrying capacity is defined as the number of people and the level of their activities which a region is able to sustain in perpetuity at an acceptable quality of life and without land deterioration. A methodology for calculating human carrying capacity utilizing crude soil, ecological, crop yield, and land use data for 41 locations in Machakos and Kitui Districts is demonstrated. Analysis and a comparison of population carrying capacities within the study area reveals that Machakos has reached a critical level of population pressure. To the north in Mbere and eastward in Kitui there are areas that are not currently experiencing population pressure, but it is likely that as the pressure in western Machakos becomes more acute, movement into these adjacent lands of relatively sparse settlement will increase. Signs of environmental stress resulting from overpopulation are evident throughout Machakos. The methodology used for estimating population pressure provided reasonably accurate carrying capacity estimates, but the methodology could be refined. Vigorous efforts to rejuvenate the land through soil and water conservation have been undertaken, but these have been insufficient and must be increased. Such efforts will fail unless the basic problem of population pressure in the marginal lands is resolved.

Bullying among Middle School Children Raised by Grandparents

ERIC Educational Resources Information Center

Edwards, Oliver W.

2016-01-01

Empirical research investigating the growing population of children raised by grandparents remains sparse. Much of the research examines the grandparents' functioning and suggests that they experience heightened psychosocial distress. Although the children are reported to manifest psychosocial and behavioral difficulty, a dearth of empirical…

Got Game

ERIC Educational Resources Information Center

Lum, Lydia

2007-01-01

Around the country, disabled sports are often treated like second-class siblings to their able-bodied counterparts, largely because the latter bring in prestigious tournaments and bowl games, lucrative TV contracts and national exposure for top athletes and coaches. Because disabled people are so sparsely distributed in the general population, it…

The disease complex of the gypsy moth. II. Aerobic bacterial pathogens

Treesearch

J.D. Podgwaite; R.W. Campbell

1972-01-01

Eighty-six pathogenic aerobic bacterial isolates from diseased gypsy moth larvae collected in both sparse and dense populations were characterized and identified as members of the families Bacillaceae, Enterobacteriaceae, Lactobacillaceae, Pseudomonadaceae, and Achromobacteraceae. The commonest pathogens were Streptococcus faecalis, Bacillus cereus, Bacillus...

Mapping transiently formed and sparsely populated conformations on a complex energy landscape

PubMed Central

Wang, Yong; Papaleo, Elena; Lindorff-Larsen, Kresten

2016-01-01

Determining the structures, kinetics, thermodynamics and mechanisms that underlie conformational exchange processes in proteins remains extremely difficult. Only in favourable cases is it possible to provide atomic-level descriptions of sparsely populated and transiently formed alternative conformations. Here we benchmark the ability of enhanced-sampling molecular dynamics simulations to determine the free energy landscape of the L99A cavity mutant of T4 lysozyme. We find that the simulations capture key properties previously measured by NMR relaxation dispersion methods including the structure of a minor conformation, the kinetics and thermodynamics of conformational exchange, and the effect of mutations. We discover a new tunnel that involves the transient exposure towards the solvent of an internal cavity, and show it to be relevant for ligand escape. Together, our results provide a comprehensive view of the structural landscape of a protein, and point forward to studies of conformational exchange in systems that are less characterized experimentally. DOI: http://dx.doi.org/10.7554/eLife.17505.001 PMID:27552057

Remote monitoring of sub ppb levels of vinyl chloride, dichloroethylene and trichloroethylene via modem operated automated GC

DOE Office of Scientific and Technical Information (OSTI.GOV)

Linenberg, A.; Lander, N.J.

1994-12-31

The need for remote monitoring of certain compounds in a sparsely populated area with limited user assistance led to the development and manufacture of a self contained, portable gas chromatography with the appropriate software. Part per billion levels of vinyl chloride, cis 1,2 dichloroethylene and trichloroethylene were detected in air using a trap for preconcentration of the compounds. The units were continuously calibrated with certified standards from Scott Specialty Gases, which in one case was 1 part per billion of the aforementioned compounds. The entire operation of the units, including monitoring instrument responses, changing operating parameters, data transfer, data reviewmore » and data reporting was done entirely on a remote basis from approximately 600 miles away using a remote computer with a modem and remote operating software. The entire system concept promises the availability of highly sensitive remote monitoring in sparsely populated areas for long periods of time.« less

Radium-226-contaminated drinking water: hypothesis on an exposure pathway in a population with elevated childhood leukemia.

PubMed

Hoffmann, W; Kranefeld, A; Schmitz-Feuerhake, I

1993-10-01

A recent epidemiological survey on childhood malignant disease in the region of Ellweiler, Rheinland-Pfalz, Germany, revealed a significantly increased incidence of childhood leukemia, but observed incidences of lymphoma and solid tumors were normal. Established risk factors such as individual exposure to chemicals as well as hereditary genetic disorders were ruled out in interviews with the patients or their families. The general population in the region, however, is subjected to considerable doses of ionizing radiation due to high levels of external gamma radiation and high activities of indoor radon. Radiation-specific chromosome aberrations were found in one of two healthy siblings and one father of leukemia patients as well as in any of three probands living in houses with high indoor radon activities. Radon and natural gamma radiation, however, cannot explain the geographical pattern of the cases. Four out of seven cases were observed in two particular villages near a uranium processing plant. The drinking water of these villages partly came from a small river that was contaminated with radium-226 washed out from the dumps of the uranium plant. Only sparse measurements of 226Ra are available, but derived red bone marrow doses for children in the two villages obtained from a simple radio-ecological model show the significance of the drinking water pathway. Prenatal 226Ra exposure of fetuses due to placental transfer and accumulation may have led to significant doses and may explain the excess cases of childhood leukemia in the region even in quantitative terms.

The morphological and chemical characteristics of striatal neurons immunoreactive for the alpha1-subunit of the GABA(A) receptor in the rat.

PubMed

Waldvogel, H J; Kubota, Y; Trevallyan, S C; Kawaguchi, Y; Fritschy, J M; Mohler, H; Faull, R L

1997-10-01

The distribution, morphology and chemical characteristics of neurons immunoreactive for the alpha1-subunit of the GABA(A) receptor in the striatum of the basal ganglia in the rat brain were investigated at the light, confocal and electron microscope levels using single, double and triple immunohistochemical labelling techniques. The results showed that alpha1-subunit immunoreactive neurons were sparsely distributed throughout the rat striatum. Double and triple labelling results showed that all the alpha1-subunit-immunoreactive neurons were positive for glutamate decarboxylase and immunoreactive for the beta2,3 and gamma2 subunits of the GABA(A) receptor. Three types of alpha1-subunit-immunoreactive neurons were identified in the striatum on the basis of cellular morphology and chemical characteristics. The most numerous alpha1-subunit-immunoreactive neurons were medium-sized, aspiny neurons with a widely branching dendritic tree. They were parvalbumin-negative and were located mainly in the dorsolateral regions of the striatum. Electron microscopy showed that these neurons had an indented nuclear membrane, typical of striatal interneurons, and were surrounded by small numbers of axon terminals which established alpha1-subunit-immunoreactive synaptic contacts with the soma and dendrites. These cells were classified as type 1 alpha1-subunit-immunoreactive neurons and comprised 75% of the total population of alpha1-subunit-immunoreactive neurons in the striatum. The remaining alpha1-subunit-immunoreactive neurons comprised of a heterogeneous population of large-sized neurons localized in the ventral and medial regions of the striatum. The most numerous large-sized cells were parvalbumin-negative, had two to three relatively short branching dendrites and were designated type 2 alpha1-subunit-immunoreactive neurons. Electron microscopy showed that the type 2 neurons were characterized by a highly convoluted nuclear membrane and were sparsely covered with small axon terminals. The type 2 neurons comprised 20% of the total population of alpha1-subunit-immunoreactive neurons. The remaining large-sized alpha1-immunoreactive cells were designated type 3 cells; they were positive for parvalbumin and were distinguished by long branching dendrites extending dorsally for 600-800 microm into the striatum. These neurons comprised 5% of the total population of alpha1-subunit-immunoreactive neurons and were surrounded by enkephalin-immunoreactive terminals. Electron microscopy showed that the alpha1-subunit type 3 neurons had an indented nuclear membrane and were densely covered with small axon terminals which established alpha1-subunit-immunoreactive symmetrical synaptic contacts with the soma and dendrites. These results provide a detailed characterization of the distribution, morphology and chemical characteristics of the alpha1-subunit-immunoreactive neurons in the rat striatum and suggest that the type 1 and type 2 neurons comprise of separate populations of striatal interneurons while the type 3 neurons may represent the large striatonigral projection neurons described by Bolam et al. [Bolam J. P., Somogyi P., Totterdell S. and Smith A. D. (1981) Neuroscience 6, 2141-2157.].

Recovering fine details from under-resolved electron tomography data using higher order total variation ℓ 1 regularization

DOE PAGES

Sanders, Toby; Gelb, Anne; Platte, Rodrigo B.; ...

2017-01-03

Over the last decade or so, reconstruction methods using ℓ 1 regularization, often categorized as compressed sensing (CS) algorithms, have significantly improved the capabilities of high fidelity imaging in electron tomography. The most popular ℓ 1 regularization approach within electron tomography has been total variation (TV) regularization. In addition to reducing unwanted noise, TV regularization encourages a piecewise constant solution with sparse boundary regions. In this paper we propose an alternative ℓ 1 regularization approach for electron tomography based on higher order total variation (HOTV). Like TV, the HOTV approach promotes solutions with sparse boundary regions. In smooth regions however,more » the solution is not limited to piecewise constant behavior. We demonstrate that this allows for more accurate reconstruction of a broader class of images – even those for which TV was designed for – particularly when dealing with pragmatic tomographic sampling patterns and very fine image features. In conclusion, we develop results for an electron tomography data set as well as a phantom example, and we also make comparisons with discrete tomography approaches.« less

SparCLeS: dynamic l₁ sparse classifiers with level sets for robust beard/moustache detection and segmentation.

PubMed

Le, T Hoang Ngan; Luu, Khoa; Savvides, Marios

2013-08-01

Robust facial hair detection and segmentation is a highly valued soft biometric attribute for carrying out forensic facial analysis. In this paper, we propose a novel and fully automatic system, called SparCLeS, for beard/moustache detection and segmentation in challenging facial images. SparCLeS uses the multiscale self-quotient (MSQ) algorithm to preprocess facial images and deal with illumination variation. Histogram of oriented gradients (HOG) features are extracted from the preprocessed images and a dynamic sparse classifier is built using these features to classify a facial region as either containing skin or facial hair. A level set based approach, which makes use of the advantages of both global and local information, is then used to segment the regions of a face containing facial hair. Experimental results demonstrate the effectiveness of our proposed system in detecting and segmenting facial hair regions in images drawn from three databases, i.e., the NIST Multiple Biometric Grand Challenge (MBGC) still face database, the NIST Color Facial Recognition Technology FERET database, and the Labeled Faces in the Wild (LFW) database.

Detection and characterization of nonspecific, sparsely-populated binding modes in the early stages of complexation

PubMed Central

Cardone, A.; Bornstein, A.; Pant, H. C.; Brady, M.; Sriram, R.; Hassan, S. A.

2015-01-01

A method is proposed to study protein-ligand binding in a system governed by specific and non-specific interactions. Strong associations lead to narrow distributions in the proteins configuration space; weak and ultra-weak associations lead instead to broader distributions, a manifestation of non-specific, sparsely-populated binding modes with multiple interfaces. The method is based on the notion that a discrete set of preferential first-encounter modes are metastable states from which stable (pre-relaxation) complexes at equilibrium evolve. The method can be used to explore alternative pathways of complexation with statistical significance and can be integrated into a general algorithm to study protein interaction networks. The method is applied to a peptide-protein complex. The peptide adopts several low-population conformers and binds in a variety of modes with a broad range of affinities. The system is thus well suited to analyze general features of binding, including conformational selection, multiplicity of binding modes, and nonspecific interactions, and to illustrate how the method can be applied to study these problems systematically. The equilibrium distributions can be used to generate biasing functions for simulations of multiprotein systems from which bulk thermodynamic quantities can be calculated. PMID:25782918

Large Scale Variability Survey of Orion II: mapping the young, low-mass stellar populations

NASA Astrophysics Data System (ADS)

Briceño, C.; Calvet, N.; Hartmann, L. W.; Vivas, A. K.

2000-12-01

We present further results of our ongoing large scale variability survey of the Orion OB1 Association, carried out with the 8k x 8k CCD Mosaic Camera on the 1m Schmidt telescope at the Venezuela National Observatory. In an area of over 60 square degrees we have unveiled new populations of low-mass young stars over a range of environments, from the dense molecular clouds of the Orion belt region, Ori OB 1b, to areas devoid of gas in Orion OB 1a. These new young stars span ages from 1-2 Myr in Ori OB 1b to roughly 10 Myr in Ori OB 1a, a likely scenario of sequential star formation triggered by the first generation of massive stars. Proxy indicators like Hα emission and near-IR excesses show that accretion from circumstellar disks in the 10 Myr stars of Ori OB 1a has mostly stopped. This population is a numerous analog of groups like TW Hya, making it an excellent laboratory to look for debris disks and study the epoch of planet formation in sparse, non-clustered environments. Research reported herein funded by NSF grant No. 9987367, and by CONICIT and Ministerio de Ciencia y Tecnología, Venezuela.

Post-Sonoman conodont biofacies of the Triassic of northwestern Nevada

NASA Astrophysics Data System (ADS)

Carey, S. P.

Biofacies interpretation of Star Peak and partly equivalent basinal conodonts is based upon sedimentologically and paleontologically determined lithofacies relationships as well as a regional shelf oceanic basin terranes model. Late Spathian transgression initiated Star Peak sedimentation. Deep shelf (basinal) conditions represented by the lower member of the Prida Formation supported an abundant neospathodid fauna (Neospathodus homeri and N. triangularis) succeeded by a neogondolellid fauna (Neogondolella jubata and N. timorensis). At the same time, restricted shallow marine waters to the east were sparsely populated by neogondolellids. During the Anisian, deep shelf (basinal) conditions characterized all of Star Peak deposition (Fossil Hill Member). Ladinian progradation of a carbonate platform across the shelf resulted in a diversification of environments. None was hospitable to conodonts. The platform slope lithology (upper Prida) is apparently barren. Rare neogondellids occur in restricted shallow marine deposits of the Home Station Member (Augusta Mountain Formation) but are absent from the supratidal Panther Canyon Member.

The genetic prehistory of the Baltic Sea region.

PubMed

Mittnik, Alissa; Wang, Chuan-Chao; Pfrengle, Saskia; Daubaras, Mantas; Zariņa, Gunita; Hallgren, Fredrik; Allmäe, Raili; Khartanovich, Valery; Moiseyev, Vyacheslav; Tõrv, Mari; Furtwängler, Anja; Andrades Valtueña, Aida; Feldman, Michal; Economou, Christos; Oinonen, Markku; Vasks, Andrejs; Balanovska, Elena; Reich, David; Jankauskas, Rimantas; Haak, Wolfgang; Schiffels, Stephan; Krause, Johannes

2018-01-30

While the series of events that shaped the transition between foraging societies and food producers are well described for Central and Southern Europe, genetic evidence from Northern Europe surrounding the Baltic Sea is still sparse. Here, we report genome-wide DNA data from 38 ancient North Europeans ranging from ~9500 to 2200 years before present. Our analysis provides genetic evidence that hunter-gatherers settled Scandinavia via two routes. We reveal that the first Scandinavian farmers derive their ancestry from Anatolia 1000 years earlier than previously demonstrated. The range of Mesolithic Western hunter-gatherers extended to the east of the Baltic Sea, where these populations persisted without gene-flow from Central European farmers during the Early and Middle Neolithic. The arrival of steppe pastoralists in the Late Neolithic introduced a major shift in economy and mediated the spread of a new ancestry associated with the Corded Ware Complex in Northern Europe.

The investigation of identifying method on grass fire by FY-3 VIRR images

NASA Astrophysics Data System (ADS)

Jiang, Youyan; Han, Tao; Wang, Dawei

2018-03-01

Grassland fire has the characteristics of fierce fire and rapid spreading, and many fires occur in sparsely populated places. Satellite remote sensing has the characteristics of fast imaging period and wide coverage, and plays an important role in the rapid monitoring and evaluation of grassland fire. FY-3 satellite has been widely used since its launch in September 2008, and this paper uses the fire information of Gansu grassland from 2011 to 2016, based on the more mature MODIS and NOAA-AVHRR fire identification method. The results show that the accuracy of FY-3/VIRR satellite data fire detection are higher than that of NOAA-AVHRR satellite, and the accuracy of FY-3/VIRR satellite data is described. There is a greater improvement, the ability to identify slightly worse than the MODIS satellite, the region is relatively large fire detection accuracy is higher.

An approach to predict water quality in data-sparse catchments using hydrological catchment similarity

NASA Astrophysics Data System (ADS)

Pohle, Ina; Glendell, Miriam; Stutter, Marc I.; Helliwell, Rachel C.

2017-04-01

An understanding of catchment response to climate and land use change at a regional scale is necessary for the assessment of mitigation and adaptation options addressing diffuse nutrient pollution. It is well documented that the physicochemical properties of a river ecosystem respond to change in a non-linear fashion. This is particularly important when threshold water concentrations, relevant to national and EU legislation, are exceeded. Large scale (regional) model assessments required for regulatory purposes must represent the key processes and mechanisms that are more readily understood in catchments with water quantity and water quality data monitored at high spatial and temporal resolution. While daily discharge data are available for most catchments in Scotland, nitrate and phosphorus are mostly available on a monthly basis only, as typified by regulatory monitoring. However, high resolution (hourly to daily) water quantity and water quality data exist for a limited number of research catchments. To successfully implement adaptation measures across Scotland, an upscaling from data-rich to data-sparse catchments is required. In addition, the widespread availability of spatial datasets affecting hydrological and biogeochemical responses (e.g. soils, topography/geomorphology, land use, vegetation etc.) provide an opportunity to transfer predictions between data-rich and data-sparse areas by linking processes and responses to catchment attributes. Here, we develop a framework of catchment typologies as a prerequisite for transferring information from data-rich to data-sparse catchments by focusing on how hydrological catchment similarity can be used as an indicator of grouped behaviours in water quality response. As indicators of hydrological catchment similarity we use flow indices derived from observed discharge data across Scotland as well as hydrological model parameters. For the latter, we calibrated the lumped rainfall-runoff model TUWModel using multiple objective functions. The relationships between indicators of hydrological catchment similarity, physical catchment characteristics and nitrate and phosphorus concentrations in rivers are then investigated using multivariate statistics. This understanding of the relationship between catchment characteristics, hydrological processes and water quality will allow us to implement more efficient regulatory water quality monitoring strategies, to improve existing water quality models and to model mitigation and adaptation scenarios to global change in data-sparse catchments.

Role of tumbling in bacterial swarming

NASA Astrophysics Data System (ADS)

Sidortsov, Marina; Morgenstern, Yakov; Be'er, Avraham

2017-08-01

Typical wild-type bacteria swimming in sparse suspensions exhibit a movement pattern called "run and tumble," characterized by straight trajectories (runs) interspersed by shorter, random reorientation (tumbles). This is achieved by rotating their flagella counterclockwise, or clockwise, respectively. The chemotaxis signaling network operates in controlling the frequency of tumbles, enabling navigation toward or away from desired regions in the medium. In contrast, while in dense populations, flagellated bacteria exhibit collective motion and form large dynamic clusters, whirls, and jets, with intricate dynamics that is fundamentally different than trajectories of sparsely swimming cells. Although collectively swarming cells do change direction at the level of the individual cell, often exhibiting reversals, it has been suggested that chemotaxis does not play a role in multicellular colony expansion, but the change in direction stems from clockwise flagellar rotation. In this paper, the effects of cell rotor switching (i.e., the ability to tumble) and chemotaxis on the collective statistics of swarming bacteria are studied experimentally in wild-type Bacillus subtilis and two mutants—one that does not tumble and one that tumbles independently of the chemotaxis system. We show that while several of the parameters examined are similar between the strains, other collective and individual characteristics are significantly different. The results demonstrate that tumbling and/or flagellar directional rotor switching has an important role on the dynamics of swarming, and imply that swarming models of self-propelled rods that do not take tumbling and/or rotor switching into account may be oversimplified.

Modeling hydrologic and geomorphic hazards across post-fire landscapes using a self-organizing map approach

USGS Publications Warehouse

Friedel, Michael J.

2011-01-01

Few studies attempt to model the range of possible post-fire hydrologic and geomorphic hazards because of the sparseness of data and the coupled, nonlinear, spatial, and temporal relationships among landscape variables. In this study, a type of unsupervised artificial neural network, called a self-organized map (SOM), is trained using data from 540 burned basins in the western United States. The sparsely populated data set includes variables from independent numerical landscape categories (climate, land surface form, geologic texture, and post-fire condition), independent landscape classes (bedrock geology and state), and dependent initiation processes (runoff, landslide, and runoff and landslide combination) and responses (debris flows, floods, and no events). Pattern analysis of the SOM-based component planes is used to identify and interpret relations among the variables. Application of the Davies-Bouldin criteria following k-means clustering of the SOM neurons identified eight conceptual regional models for focusing future research and empirical model development. A split-sample validation on 60 independent basins (not included in the training) indicates that simultaneous predictions of initiation process and response types are at least 78% accurate. As climate shifts from wet to dry conditions, forecasts across the burned landscape reveal a decreasing trend in the total number of debris flow, flood, and runoff events with considerable variability among individual basins. These findings suggest the SOM may be useful in forecasting real-time post-fire hazards, and long-term post-recovery processes and effects of climate change scenarios.

Sparse and Specific Coding during Information Transmission between Co-cultured Dentate Gyrus and CA3 Hippocampal Networks

PubMed Central

Poli, Daniele; Thiagarajan, Srikanth; DeMarse, Thomas B.; Wheeler, Bruce C.; Brewer, Gregory J.

2017-01-01

To better understand encoding and decoding of stimulus information in two specific hippocampal sub-regions, we isolated and co-cultured rat primary dentate gyrus (DG) and CA3 neurons within a two-chamber device with axonal connectivity via micro-tunnels. We tested the hypothesis that, in these engineered networks, decoding performance of stimulus site information would be more accurate when stimuli and information flow occur in anatomically correct feed-forward DG to CA3 vs. CA3 back to DG. In particular, we characterized the neural code of these sub-regions by measuring sparseness and uniqueness of the responses evoked by specific paired-pulse stimuli. We used the evoked responses in CA3 to decode the stimulation sites in DG (and vice-versa) by means of learning algorithms for classification (support vector machine, SVM). The device was placed over an 8 × 8 grid of extracellular electrodes (micro-electrode array, MEA) in order to provide a platform for monitoring development, self-organization, and improved access to stimulation and recording at multiple sites. The micro-tunnels were designed with dimensions 3 × 10 × 400 μm allowing axonal growth but not migration of cell bodies and long enough to exclude traversal by dendrites. Paired-pulse stimulation (inter-pulse interval 50 ms) was applied at 22 different sites and repeated 25 times in each chamber for each sub-region to evoke time-locked activity. DG-DG and CA3-CA3 networks were used as controls. Stimulation in DG drove signals through the axons in the tunnels to activate a relatively small set of specific electrodes in CA3 (sparse code). CA3-CA3 and DG-DG controls were less sparse in coding than CA3 in DG-CA3 networks. Using all target electrodes with the three highest spike rates (14%), the evoked responses in CA3 specified each stimulation site in DG with optimum uniqueness of 64%. Finally, by SVM learning, these evoked responses in CA3 correctly decoded the stimulation sites in DG for 43% of the trials, significantly higher than the reverse, i.e., how well-recording in DG could predict the stimulation site in CA3. In conclusion, our co-cultured model for the in vivo DG-CA3 hippocampal network showed sparse and specific responses in CA3, selectively evoked by each stimulation site in DG. PMID:28321182

Childcare Providers: Work Stress and Personal Well-Being

ERIC Educational Resources Information Center

Faulkner, Monica; Gerstenblatt, Paula; Lee, Ahyoung; Vallejo, Viana; Travis, Dnika

2016-01-01

Childcare providers face multiple work-related stressors. Small studies of childcare providers have suggested that providers have high levels of depression compared to the general population. However, unlike other caregiving professions, the research examining childcare providers is sparse, and there is little information to inform practices and…

Modeling Alzheimer's disease cognitive scores using multi-task sparse group lasso.

PubMed

Liu, Xiaoli; Goncalves, André R; Cao, Peng; Zhao, Dazhe; Banerjee, Arindam

2018-06-01

Alzheimer's disease (AD) is a severe neurodegenerative disorder characterized by loss of memory and reduction in cognitive functions due to progressive degeneration of neurons and their connections, eventually leading to death. In this paper, we consider the problem of simultaneously predicting several different cognitive scores associated with categorizing subjects as normal, mild cognitive impairment (MCI), or Alzheimer's disease (AD) in a multi-task learning framework using features extracted from brain images obtained from ADNI (Alzheimer's Disease Neuroimaging Initiative). To solve the problem, we present a multi-task sparse group lasso (MT-SGL) framework, which estimates sparse features coupled across tasks, and can work with loss functions associated with any Generalized Linear Models. Through comparisons with a variety of baseline models using multiple evaluation metrics, we illustrate the promising predictive performance of MT-SGL on ADNI along with its ability to identify brain regions more likely to help the characterization Alzheimer's disease progression. Copyright © 2017 Elsevier Ltd. All rights reserved.

Advantage of population pharmacokinetic method for evaluating the bioequivalence and accuracy of parameter estimation of pidotimod.

PubMed

Huang, Jihan; Li, Mengying; Lv, Yinghua; Yang, Juan; Xu, Ling; Wang, Jingjing; Chen, Junchao; Wang, Kun; He, Yingchun; Zheng, Qingshan

2016-09-01

This study was aimed at exploring the accuracy of population pharmacokinetic method in evaluating the bioequivalence of pidotimod with sparse data profiles and whether this method is suitable for bioequivalence evaluation in special populations such as children with fewer samplings. Methods In this single-dose, two-period crossover study, 20 healthy male Chinese volunteers were randomized 1 : 1 to receive either the test or reference formulation, with a 1-week washout before receiving the alternative formulation. Noncompartmental and population compartmental pharmacokinetic analyses were conducted. Simulated data were analyzed to graphically evaluate the model and the pharmacokinetic characteristics of the two pidotimod formulations. Various sparse sampling scenarios were generated from the real bioequivalence clinical trial data and evaluated by population pharmacokinetic method. The 90% confidence intervals (CIs) for AUC0-12h, AUC0-∞, and Cmax were 97.3 - 118.7%, 96.9 - 118.7%, and 95.1 - 109.8%, respectively, within the 80 - 125% range for bioequivalence using noncompartmental analysis. The population compartmental pharmacokinetics of pidotimod were described using a one-compartment model with first-order absorption and lag time. In the comparison of estimations in different dataset, the estimation of random three- and< fixed four-point sampling strategies can provide results similar to those obtained through rich sampling. The nonlinear mixed-effects model requires fewer data points. Moreover, compared with the noncompartmental analysis method, the pharmacokinetic parameters can be more accurately estimated using nonlinear mixed-effects model. The population pharmacokinetic modeling method was used to assess the bioequivalence of two pidotimod formulations with relatively few sampling points and further validated the bioequivalence of the two formulations. This method may provide useful information for regulating bioequivalence evaluation in special populations.

The Effectiveness of Using Limited Gauge Measurements for Bias Adjustment of Satellite-Based Precipitation Estimation over Saudi Arabia

NASA Astrophysics Data System (ADS)

Alharbi, Raied; Hsu, Kuolin; Sorooshian, Soroosh; Braithwaite, Dan

2018-01-01

Precipitation is a key input variable for hydrological and climate studies. Rain gauges are capable of providing reliable precipitation measurements at point scale. However, the uncertainty of rain measurements increases when the rain gauge network is sparse. Satellite -based precipitation estimations appear to be an alternative source of precipitation measurements, but they are influenced by systematic bias. In this study, a method for removing the bias from the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS) over a region where the rain gauge is sparse is investigated. The method consists of monthly empirical quantile mapping, climate classification, and inverse-weighted distance method. Daily PERSIANN-CCS is selected to test the capability of the method for removing the bias over Saudi Arabia during the period of 2010 to 2016. The first six years (2010 - 2015) are calibrated years and 2016 is used for validation. The results show that the yearly correlation coefficient was enhanced by 12%, the yearly mean bias was reduced by 93% during validated year. Root mean square error was reduced by 73% during validated year. The correlation coefficient, the mean bias, and the root mean square error show that the proposed method removes the bias on PERSIANN-CCS effectively that the method can be applied to other regions where the rain gauge network is sparse.

Turning a blind eye: the mobilization of radiology services in resource-poor regions

PubMed Central

2010-01-01

While primary care, obstetrical, and surgical services have started to expand in the world's poorest regions, there is only sparse literature on the essential support systems that are required to make these operations function. Diagnostic imaging is critical to effective rural healthcare delivery, yet it has been severely neglected by the academic, public, and private sectors. Currently, a large portion of the world's population lacks access to any form of diagnostic imaging. In this paper we argue that two primary imaging modalities--diagnostic ultrasound and X-Ray--are ideal for rural healthcare services and should be scaled-up in a rapid and standardized manner. Such machines, if designed for resource-poor settings, should a) be robust in harsh environmental conditions, b) function reliably in environments with unstable electricity, c) minimize radiation dangers to staff and patients, d) be operable by non-specialist providers, and e) produce high-quality images required for accurate diagnosis. Few manufacturers are producing ultrasound and X-Ray machines that meet the specifications needed for rural healthcare delivery in resource-poor regions. A coordinated effort is required to create demand sufficient for manufacturers to produce the desired machines and to ensure that the programs operating them are safe, effective, and financially feasible. PMID:20946643

Turning a blind eye: the mobilization of radiology services in resource-poor regions.

PubMed

Maru, Duncan Smith-Rohrberg; Schwarz, Ryan; Jason, Andrews; Basu, Sanjay; Sharma, Aditya; Moore, Christopher

2010-10-14

While primary care, obstetrical, and surgical services have started to expand in the world's poorest regions, there is only sparse literature on the essential support systems that are required to make these operations function. Diagnostic imaging is critical to effective rural healthcare delivery, yet it has been severely neglected by the academic, public, and private sectors. Currently, a large portion of the world's population lacks access to any form of diagnostic imaging. In this paper we argue that two primary imaging modalities--diagnostic ultrasound and X-Ray--are ideal for rural healthcare services and should be scaled-up in a rapid and standardized manner. Such machines, if designed for resource-poor settings, should a) be robust in harsh environmental conditions, b) function reliably in environments with unstable electricity, c) minimize radiation dangers to staff and patients, d) be operable by non-specialist providers, and e) produce high-quality images required for accurate diagnosis. Few manufacturers are producing ultrasound and X-Ray machines that meet the specifications needed for rural healthcare delivery in resource-poor regions. A coordinated effort is required to create demand sufficient for manufacturers to produce the desired machines and to ensure that the programs operating them are safe, effective, and financially feasible.

Dispersal capacity and genetic relatedness in Acropora cervicornis on the Florida Reef Tract

NASA Astrophysics Data System (ADS)

Drury, Crawford; Paris, Claire B.; Kourafalou, Vassiliki H.; Lirman, Diego

2018-06-01

Sexual reproduction in scleractinian corals is a critical component of species recovery, fostering population connectivity and enhancing genetic diveristy. The relative contribution of sexual reproduction to both connectivity and diversity in Acropora cervicornis may be variable due to this species' capacity to reproduce effectively by fragmentation. Using a biophysical model and genomic data in this threatened species, we construct potential connectivity pathways on the Florida Reef Tract (FRT) and compare them to inferred migration rates derived from next-generation sequencing, using a link and node-based approach. Larval connectivity on the FRT can be divided into two zones: the northern region, where most transport is unidirectional to the north with the Florida Current, and the southern region that is more dynamic and exhibits complex spatial patterns. These biophysical linkages are poorly correlated with genetic connectivity patterns, which resolve many reciprocal connections and suggest a less sparse network. These results are difficult to reconcile with genetic data which indicate that individual reefs are diverse, suggesting important contributions of sexual reproduction and recruitment. Larval connectivity models highlight potential resources for recovery, such as areas with high larval export like the Lower Keys, or areas that are well connected to most other regions on the FRT, such as the Dry Tortugas.

Odyssey personal communications satellite system

NASA Technical Reports Server (NTRS)

Spitzer, Christopher J.

1993-01-01

The spectacular growth of cellular telephone networks has proved the demand for personal communications. Large regions of the world are too sparsely populated to be economically served by terrestrial cellular communications. Since satellites are well suited to this application, TRW filed with the FCC on May 31, 1993 for the Odyssey construction permit. Odyssey will provide high quality wireless communication services worldwide from satellites. These services will include: voice, data, paging, and messaging. Odyssey will be an economical approach to providing communications. A constellation of 12 satellites will be orbited in three, 55 deg. inclined planes at an altitude of 10,354 km to provide continuous coverage of designated regions. Two satellites will be visible anywhere in the world at all times. This dual visibility leads to high line-of-sight elevation angles, minimizing obstructions by terrain, trees and buildings. Each satellite generates a multibeam antenna pattern that divides its coverage area into a set of contiguous cells. The communications system employs spread spectrum CDMA on both the uplinks and downlinks. This signaling method permits band sharing with other systems and applications. Signal processing is accomplished on the ground at the satellite's 'Gateway' stations. The 'bent pipe' transponders accommodates different regional standards, as well as signaling changes over time. The low power Odyssey handset will be cellular compatible. Multipath fade protection is provided in the handset.

Approximation and spatial regionalization of rainfall erosivity based on sparse data in a mountainous catchment of the Yangtze River in Central China.

PubMed

Schönbrodt-Stitt, Sarah; Bosch, Anna; Behrens, Thorsten; Hartmann, Heike; Shi, Xuezheng; Scholten, Thomas

2013-10-01

In densely populated countries like China, clean water is one of the most challenging issues of prospective politics and environmental planning. Water pollution and eutrophication by excessive input of nitrogen and phosphorous from nonpoint sources is mostly linked to soil erosion from agricultural land. In order to prevent such water pollution by diffuse matter fluxes, knowledge about the extent of soil loss and the spatial distribution of hot spots of soil erosion is essential. In remote areas such as the mountainous regions of the upper and middle reaches of the Yangtze River, rainfall data are scarce. Since rainfall erosivity is one of the key factors in soil erosion modeling, e.g., expressed as R factor in the Revised Universal Soil Loss Equation model, a methodology is needed to spatially determine rainfall erosivity. Our study aims at the approximation and spatial regionalization of rainfall erosivity from sparse data in the large (3,200 km(2)) and strongly mountainous catchment of the Xiangxi River, a first order tributary to the Yangtze River close to the Three Gorges Dam. As data on rainfall were only obtainable in daily records for one climate station in the central part of the catchment and five stations in its surrounding area, we approximated rainfall erosivity as R factors using regression analysis combined with elevation bands derived from a digital elevation model. The mean annual R factor (R a) amounts for approximately 5,222 MJ mm ha(-1) h(-1) a(-1). With increasing altitudes, R a rises up to maximum 7,547 MJ mm ha(-1) h(-1) a(-1) at an altitude of 3,078 m a.s.l. At the outlet of the Xiangxi catchment erosivity is at minimum with approximate R a=1,986 MJ mm ha(-1) h(-1) a(-1). The comparison of our results with R factors from high-resolution measurements at comparable study sites close to the Xiangxi catchment shows good consistance and allows us to calculate grid-based R a as input for a spatially high-resolution and area-specific assessment of soil erosion risk.

Populations of Bactrocera oleae (Diptera: Tephritidae) and Its Parasitoids in Himalayan Asia

USDA-ARS?s Scientific Manuscript database

For a biological control program against olive fruit fly, Bactrocera oleae Rossi, olives were collected in the Himalayan foothills (China, Nepal, India, and Pakistan) to discover new natural enemies. Wild olives, Olea europaea ssp. cuspidata (Wall ex. G. Don), were sparsely distributed and fly-infes...

Populations of Bactrocera oleae (Diptera: Tephritidae) and Its Parasitoids in Himalayan Asia

USDA-ARS?s Scientific Manuscript database

For a biological control program against olive fruit fly, Bactrocera oleae Rossi, olives were collected in the Himalayan foothills (China, Nepal, India, and Pakistan) to discover new natural enemies. Wild olives, Olea europaea ssp. cuspidata (Wall ex. G. Don), were sparsely distributed and fly-infe...

14 CFR 91.305 - Flight test areas.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 14 Aeronautics and Space 2 2012-01-01 2012-01-01 false Flight test areas. 91.305 Section 91.305... AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT RULES Special Flight Operations § 91.305 Flight test areas. No person may flight test an aircraft except over open water, or sparsely populated...

14 CFR 91.305 - Flight test areas.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 14 Aeronautics and Space 2 2013-01-01 2013-01-01 false Flight test areas. 91.305 Section 91.305... AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT RULES Special Flight Operations § 91.305 Flight test areas. No person may flight test an aircraft except over open water, or sparsely populated...

14 CFR 91.305 - Flight test areas.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 14 Aeronautics and Space 2 2010-01-01 2010-01-01 false Flight test areas. 91.305 Section 91.305... AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT RULES Special Flight Operations § 91.305 Flight test areas. No person may flight test an aircraft except over open water, or sparsely populated...

Rural Inservice Education: Staples Teacher Center Style.

ERIC Educational Resources Information Center

Krueger, Rick

In its two-year existence, the federally funded Staples Teacher Center (STC) in Minnesota has had a significant impact on improving classroom instruction and staff development activities in a rural setting, proving that teacher centers are a most effective delivery system for inservice education in sparsely populated areas. Services are rendered…

Poverty and Rural Schools. Research Brief

ERIC Educational Resources Information Center

Johnston, Howard

2009-01-01

Impoverished populations and schools in rural areas face special challenges that are different from other settings. Among these are the distances from social services, the sparse availability of assistance programs, and the shortage of resources to support educational programs and student learning. Rural schools, do, however, have assets that can…

Parent Education in a Rural State.

ERIC Educational Resources Information Center

Good, Linda

In order to develop baseline information from which strengths and weaknesses of present parent education services could be identified, this study examined parent education in a sparsely populated rural state. The participants, 358 professionals in education and social service, were asked to respond to a mail survey within 2 weeks. No follow-up…

When Rural Reality Goes Virtual.

ERIC Educational Resources Information Center

Husain, Dilshad D.

1998-01-01

In rural towns where sparse population and few business are barriers, virtual reality may be the only way to bring work-based learning to students. A partnership between a small-town high school, the Ohio Supercomputer Center, and a high-tech business will enable students to explore the workplace using virtual reality. (JOW)

Imputation of missing genotypes from sparse to high density using long-range phasing

USDA-ARS?s Scientific Manuscript database

Related individuals share potentially long chromosome segments that trace to a common ancestor. A phasing algorithm (ChromoPhase) that utilizes this characteristic of finite populations was developed to phase large sections of a chromosome. In addition to phasing, ChromoPhase imputes missing genotyp...

Industrialization in the Rural Southeast: The Role of Education.

ERIC Educational Resources Information Center

Fratoe, Frank A.

Focusing on contributions of educational resources to the growth of nonfarm enterprises in small towns and sparsely populated areas of the Southeast, this paper discusses four major problems which are at least partly amenable to educational solutions and examines various educational means for overcoming those problems. Research and development…

PROGRAMS FOR THOSE RURAL SCHOOLS WHICH ARE NECESSARILY EXISTENT.

ERIC Educational Resources Information Center

BOHRSON, RALPH G.; GANN, ELBIE L.

NECESSARILY EXISTENT RURAL SCHOOLS ARE DEFINED AS THOSE WHOSE STUDENT BODY IS LIMITED DUE TO EXTREMES OF DISTANCE, TERRAIN, CLIMATE, OR SPARSE POPULATION. DOCUMENTED REPORTS OF PROJECTS COMPLETED AND IN PROGRESS POINT OUT THE FOLLOWING PROMISING PRACTICES--NONGRADED INSTRUCTION, TEAM TEACHING, UTILIZATION OF TEACHER AIDES, MULTIPLE CLASS TEACHING,…

Distance Learning and Libraries in the Cyberspace Age.

ERIC Educational Resources Information Center

Erazo, Edward; Derlin, Roberta L.

The growth of telecommunications technology for distance learning in the Cyberspace Age has opened many options for studying off-campus from home or office from remote and sparsely populated communities. Higher education is exploring this modern version of correspondence courses with the goal of increasing their student enrollment as well as…

Small Modifications to Network Topology Can Induce Stochastic Bistable Spiking Dynamics in a Balanced Cortical Model

PubMed Central

McDonnell, Mark D.; Ward, Lawrence M.

2014-01-01

Abstract Directed random graph models frequently are used successfully in modeling the population dynamics of networks of cortical neurons connected by chemical synapses. Experimental results consistently reveal that neuronal network topology is complex, however, in the sense that it differs statistically from a random network, and differs for classes of neurons that are physiologically different. This suggests that complex network models whose subnetworks have distinct topological structure may be a useful, and more biologically realistic, alternative to random networks. Here we demonstrate that the balanced excitation and inhibition frequently observed in small cortical regions can transiently disappear in otherwise standard neuronal-scale models of fluctuation-driven dynamics, solely because the random network topology was replaced by a complex clustered one, whilst not changing the in-degree of any neurons. In this network, a small subset of cells whose inhibition comes only from outside their local cluster are the cause of bistable population dynamics, where different clusters of these cells irregularly switch back and forth from a sparsely firing state to a highly active state. Transitions to the highly active state occur when a cluster of these cells spikes sufficiently often to cause strong unbalanced positive feedback to each other. Transitions back to the sparsely firing state rely on occasional large fluctuations in the amount of non-local inhibition received. Neurons in the model are homogeneous in their intrinsic dynamics and in-degrees, but differ in the abundance of various directed feedback motifs in which they participate. Our findings suggest that (i) models and simulations should take into account complex structure that varies for neuron and synapse classes; (ii) differences in the dynamics of neurons with similar intrinsic properties may be caused by their membership in distinctive local networks; (iii) it is important to identify neurons that share physiological properties and location, but differ in their connectivity. PMID:24743633

Determinants of mobile phone output power in a multinational study: implications for exposure assessment.

PubMed

Vrijheid, M; Mann, S; Vecchia, P; Wiart, J; Taki, M; Ardoino, L; Armstrong, B K; Auvinen, A; Bédard, D; Berg-Beckhoff, G; Brown, J; Chetrit, A; Collatz-Christensen, H; Combalot, E; Cook, A; Deltour, I; Feychting, M; Giles, G G; Hepworth, S J; Hours, M; Iavarone, I; Johansen, C; Krewski, D; Kurttio, P; Lagorio, S; Lönn, S; McBride, M; Montestrucq, L; Parslow, R C; Sadetzki, S; Schüz, J; Tynes, T; Woodward, A; Cardis, E

2009-10-01

The output power of a mobile phone is directly related to its radiofrequency (RF) electromagnetic field strength, and may theoretically vary substantially in different networks and phone use circumstances due to power control technologies. To improve indices of RF exposure for epidemiological studies, we assessed determinants of mobile phone output power in a multinational study. More than 500 volunteers in 12 countries used Global System for Mobile communications software-modified phones (GSM SMPs) for approximately 1 month each. The SMPs recorded date, time, and duration of each call, and the frequency band and output power at fixed sampling intervals throughout each call. Questionnaires provided information on the typical circumstances of an individual's phone use. Linear regression models were used to analyse the influence of possible explanatory variables on the average output power and the percentage call time at maximum power for each call. Measurements of over 60,000 phone calls showed that the average output power was approximately 50% of the maximum, and that output power varied by a factor of up to 2 to 3 between study centres and network operators. Maximum power was used during a considerable proportion of call time (39% on average). Output power decreased with increasing call duration, but showed little variation in relation to reported frequency of use while in a moving vehicle or inside buildings. Higher output powers for rural compared with urban use of the SMP were observed principally in Sweden where the study covered very sparsely populated areas. Average power levels are substantially higher than the minimum levels theoretically achievable in GSM networks. Exposure indices could be improved by accounting for average power levels of different telecommunications systems. There appears to be little value in gathering information on circumstances of phone use other than use in very sparsely populated regions.

Body-wide hierarchical fuzzy modeling, recognition, and delineation of anatomy in medical images.

PubMed

Udupa, Jayaram K; Odhner, Dewey; Zhao, Liming; Tong, Yubing; Matsumoto, Monica M S; Ciesielski, Krzysztof C; Falcao, Alexandre X; Vaideeswaran, Pavithra; Ciesielski, Victoria; Saboury, Babak; Mohammadianrasanani, Syedmehrdad; Sin, Sanghun; Arens, Raanan; Torigian, Drew A

2014-07-01

To make Quantitative Radiology (QR) a reality in radiological practice, computerized body-wide Automatic Anatomy Recognition (AAR) becomes essential. With the goal of building a general AAR system that is not tied to any specific organ system, body region, or image modality, this paper presents an AAR methodology for localizing and delineating all major organs in different body regions based on fuzzy modeling ideas and a tight integration of fuzzy models with an Iterative Relative Fuzzy Connectedness (IRFC) delineation algorithm. The methodology consists of five main steps: (a) gathering image data for both building models and testing the AAR algorithms from patient image sets existing in our health system; (b) formulating precise definitions of each body region and organ and delineating them following these definitions; (c) building hierarchical fuzzy anatomy models of organs for each body region; (d) recognizing and locating organs in given images by employing the hierarchical models; and (e) delineating the organs following the hierarchy. In Step (c), we explicitly encode object size and positional relationships into the hierarchy and subsequently exploit this information in object recognition in Step (d) and delineation in Step (e). Modality-independent and dependent aspects are carefully separated in model encoding. At the model building stage, a learning process is carried out for rehearsing an optimal threshold-based object recognition method. The recognition process in Step (d) starts from large, well-defined objects and proceeds down the hierarchy in a global to local manner. A fuzzy model-based version of the IRFC algorithm is created by naturally integrating the fuzzy model constraints into the delineation algorithm. The AAR system is tested on three body regions - thorax (on CT), abdomen (on CT and MRI), and neck (on MRI and CT) - involving a total of over 35 organs and 130 data sets (the total used for model building and testing). The training and testing data sets are divided into equal size in all cases except for the neck. Overall the AAR method achieves a mean accuracy of about 2 voxels in localizing non-sparse blob-like objects and most sparse tubular objects. The delineation accuracy in terms of mean false positive and negative volume fractions is 2% and 8%, respectively, for non-sparse objects, and 5% and 15%, respectively, for sparse objects. The two object groups achieve mean boundary distance relative to ground truth of 0.9 and 1.5 voxels, respectively. Some sparse objects - venous system (in the thorax on CT), inferior vena cava (in the abdomen on CT), and mandible and naso-pharynx (in neck on MRI, but not on CT) - pose challenges at all levels, leading to poor recognition and/or delineation results. The AAR method fares quite favorably when compared with methods from the recent literature for liver, kidneys, and spleen on CT images. We conclude that separation of modality-independent from dependent aspects, organization of objects in a hierarchy, encoding of object relationship information explicitly into the hierarchy, optimal threshold-based recognition learning, and fuzzy model-based IRFC are effective concepts which allowed us to demonstrate the feasibility of a general AAR system that works in different body regions on a variety of organs and on different modalities. Copyright © 2014 Elsevier B.V. All rights reserved.

Interest focuses on exploratory areas

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stremel, K.

1984-10-01

Speculative geophysical programs are underway in sparsely drilled areas throughout the southern Rocky Mountain region. Responding to significant operator interest generated by new production in Nevada, a few contractors are designing programs to establish optimum recording parameters. Geophysical exploration activities in Colorado and Utah are discussed.

Effect of the Large Scale Environment on the Internal Dynamics of Early-Type Galaxies

NASA Astrophysics Data System (ADS)

Maubon, G.; Prugniel, Ph.

We have studied the population-density relation in very sparse environments, from poor clusters to isolated galaxies, and we find that early-type galaxies with a young stellar population are preferably found in the lowest density environments. We show a marginal indication that this effect is due to an enhancement of the stellar formation independent of the morphological segregation, but we failed to find any effect from the internal dynamics.

Water resources of the St. Louis River watershed, northeastern Minnesota

USGS Publications Warehouse

Lindholm, Gerald F.; Ericson, D.W.; Broussard, W.L.; Hult, M.F.

1979-01-01

The watershed is sparsely settled except for its northern and south-eastern parts. About 80 percent of the urban population lives on the Iron Range. Most of the suburban and rural residents alro live on or near the range or in the southeastern part of the watershed. Total population (1970), exclusive of those in the city of Duluth, which is included in the Lake Superior watershed (Olcott and others, 1976), was about 117,000.

Evolution of Optical Binary Fraction in Sparse Stellar Systems

NASA Astrophysics Data System (ADS)

Li, Zhongmu; Mao, Caiyan

2018-05-01

This work studies the evolution of the fraction of optical binary stars (OBF; not including components such as neutron stars and black holes), which is caused by stellar evolution, and the contributions of various binaries to OBF via the stellar population synthesis technique. It is shown that OBF decreases from 1 to about 0.81 for stellar populations with the Salpeter initial mass function (IMF), and to about 0.85 for the case of the Kroupa IMF, on a timescale of 15 Gyr. This result depends on metallicity, slightly. The contributions of binaries varying with mass ratio, orbital period, separation, spectral types of primary and secondary, contact degree, and pair type to OBF are calculated for stellar populations with different ages and metallicities. The contribution of different kinds of binaries to OBF depends on age and metallicity. The results can be used for estimating the global OBF of star clusters or galaxies from the fraction of a kind of binary. It is also helpful for estimating the primordial and future binary fractions of sparse stellar systems from the present observations. Our results are suitable for studying field stars, open clusters, and the outer part of globular clusters, because the OBF of such objects is affected by dynamical processes, relatively slightly, but they can also be used for giving some limits for other populations.

N-mixture models for estimating population size from spatially replicated counts

USGS Publications Warehouse

Royle, J. Andrew

2004-01-01

Spatial replication is a common theme in count surveys of animals. Such surveys often generate sparse count data from which it is difficult to estimate population size while formally accounting for detection probability. In this article, i describe a class of models (n-mixture models) which allow for estimation of population size from such data. The key idea is to view site-specific population sizes, n, as independent random variables distributed according to some mixing distribution (e.g., Poisson). Prior parameters are estimated from the marginal likelihood of the data, having integrated over the prior distribution for n. Carroll and lombard (1985, journal of american statistical association 80, 423-426) proposed a class of estimators based on mixing over a prior distribution for detection probability. Their estimator can be applied in limited settings, but is sensitive to prior parameter values that are fixed a priori. Spatial replication provides additional information regarding the parameters of the prior distribution on n that is exploited by the n-mixture models and which leads to reasonable estimates of abundance from sparse data. A simulation study demonstrates superior operating characteristics (bias, confidence interval coverage) of the n-mixture estimator compared to the caroll and lombard estimator. Both estimators are applied to point count data on six species of birds illustrating the sensitivity to choice of prior on p and substantially different estimates of abundance as a consequence.

Structured networks support sparse traveling waves in rodent somatosensory cortex.

PubMed

Moldakarimov, Samat; Bazhenov, Maxim; Feldman, Daniel E; Sejnowski, Terrence J

2018-05-15

Neurons responding to different whiskers are spatially intermixed in the superficial layer 2/3 (L2/3) of the rodent barrel cortex, where a single whisker deflection activates a sparse, distributed neuronal population that spans multiple cortical columns. How the superficial layer of the rodent barrel cortex is organized to support such distributed sensory representations is not clear. In a computer model, we tested the hypothesis that sensory representations in L2/3 of the rodent barrel cortex are formed by activity propagation horizontally within L2/3 from a site of initial activation. The model explained the observed properties of L2/3 neurons, including the low average response probability in the majority of responding L2/3 neurons, and the existence of a small subset of reliably responding L2/3 neurons. Sparsely propagating traveling waves similar to those observed in L2/3 of the rodent barrel cortex occurred in the model only when a subnetwork of strongly connected neurons was immersed in a much larger network of weakly connected neurons.

Efficient Computation of Anharmonic Force Constants via q-space, with Application to Graphene

NASA Astrophysics Data System (ADS)

Kornbluth, Mordechai; Marianetti, Chris

We present a new approach for extracting anharmonic force constants from a sparse sampling of the anharmonic dynamical tensor. We calculate the derivative of the energy with respect to q-space displacements (phonons) and strain, which guarantees the absence of supercell image errors. Central finite differences provide a well-converged quadratic error tail for each derivative, separating the contribution of each anharmonic order. These derivatives populate the anharmonic dynamical tensor in a sparse mesh that bounds the Brillouin Zone, which ensures comprehensive sampling of q-space while exploiting small-cell calculations for efficient, high-throughput computation. This produces a well-converged and precisely-defined dataset, suitable for big-data approaches. We transform this sparsely-sampled anharmonic dynamical tensor to real-space anharmonic force constants that obey full space-group symmetries by construction. Machine-learning techniques identify the range of real-space interactions. We show the entire process executed for graphene, up to and including the fifth-order anharmonic force constants. This method successfully calculates strain-based phonon renormalization in graphene, even under large strains, which solves a major shortcoming of previous potentials.

Applications of monsoon research: Opportunities to inform decisionmaking and reduce regional vulnerability

NASA Astrophysics Data System (ADS)

Ray, A. J.; Garfin, G. M.; Wilder, M.; Lenart, M.; Vásquez-León, M.; Comrie, A. C.

2007-05-01

This presentation will describe ongoing efforts to understand interactions between the North American Monsoon and society, in order to develop applications for monsoon research in a highly complex, multicultural and binational region. The North American Monsoon is an annual precipitation regime that begins in early June in Mexico and progresses northward to the southwestern United States. The region includes stakeholders in large urban complexes, productive agricultural areas, and sparsely populated arid and semi-arid ecosystems. The political, cultural, and socioeconomic divisions between the U.S. and Mexico create a broad range of sensitivities to climate variability as well as capacities to use forecasts and other information to cope with climate. We will highlight methodologies to link climate science with society and analyze opportunities for monsoon science to benefit society in four sectors: natural hazards management, agriculture, public health, and water management. We present a synthesized list of stakeholder needs and a calendar of decisions to help scientists link user needs to potential forecasts and products. To ensure usability of forecasts and other research products, we recommend iterative scientist-stakeholder interactions, through integrated assessments. These knowledge- exchange interactions can improve the capacity for stakeholders to use forecasts thoughtfully and inform the development of research, and for the research community to obtain feedback on climate-related products and receive insights to guide research direction. We expect that integrated assessments can capitalize on the opportunities for monsoon science to inform decisionmaking, in the best instances, reduce regional climate vulnerabilities and enhance regional sustainability

A New Population Estimate for the Florida Scrub Jay on Merritt Island National Wildlife Refuge

NASA Technical Reports Server (NTRS)

Breininger, David R.

1989-01-01

The variable circular plot method was used to sample avifauna within different vegetation types determined from aerial imagery. The Florida Scrub Jay (Aphelocoma coerulescens coerulescens) population was estimated to range between 1,415 and 3,603 birds. Approximately half of the scrub and slash pine habitat appeared to be unused by Florida Scrub Jay, probably because the slash pine cover was too dense or the oak cover was too sparse. Results from the study suggest that the entire state population may be much lower than believed because the size of two of the three largest populations may have been overestimated.

Effect of distribution of striated laser hardening tracks on dry sliding wear resistance of biomimetic surface

NASA Astrophysics Data System (ADS)

Su, Wei; Zhou, Ti; Zhang, Peng; Zhou, Hong; Li, Hui

2018-01-01

Some biological surfaces were proved to have excellent anti-wear performance. Being inspired, Nd:YAG pulsed laser was used to create striated biomimetic laser hardening tracks on medium carbon steel samples. Dry sliding wear tests biomimetic samples were performed to investigate specific influence of distribution of laser hardening tracks on sliding wear resistance of biomimetic samples. After comparing wear weight loss of biomimetic samples, quenched sample and untreated sample, it can be suggested that the sample covered with dense laser tracks (3.5 mm spacing) has lower wear weight loss than the one covered with sparse laser tracks (4.5 mm spacing); samples distributed with only dense laser tracks or sparse laser tracks (even distribution) were proved to have better wear resistance than samples distributed with both dense and sparse tracks (uneven distribution). Wear mechanisms indicate that laser track and exposed substrate of biomimetic sample can be regarded as hard zone and soft zone respectively. Inconsecutive striated hard regions, on the one hand, can disperse load into small branches, on the other hand, will hinder sliding abrasives during wear. Soft regions with small range are beneficial in consuming mechanical energy and storing lubricative oxides, however, soft zone with large width (>0.5 mm) will be harmful to abrasion resistance of biomimetic sample because damages and material loss are more obvious on surface of soft phase. As for the reason why samples with even distributed bionic laser tracks have better wear resistance, it can be explained by the fact that even distributed laser hardening tracks can inhibit severe worn of local regions, thus sliding process can be more stable and wear extent can be alleviated as well.

Continuously amplified warming in the Alaskan Arctic: Implications for estimating global warming hiatus: SPATIAL COVERAGE AND BIAS IN TREND

DOE PAGES

Wang, Kang; Zhang, Tingjun; Zhang, Xiangdong; ...

2017-09-13

Historically, in-situ measurements have been notoriously sparse over the Arctic. As a consequence, the existing gridded data of Surface Air Temperature (SAT) may have large biases in estimating the warming trend in this region. Using data from an expanded monitoring network with 31 stations in the Alaskan Arctic, we demonstrate that the SAT has increased by 2.19 °C in this region, or at a rate of 0.23 °C/decade during 1921-2015. Mean- while, we found that the SAT warmed at 0.71 °C/decade over 1998-2015, which is two to three times faster than the rate established from the gridded datasets. Focusing onmore » the "hiatus" period 1998-2012 as identied by the Intergovernmental Panel on Climate Change (IPCC) report, the SAT has increased at 0.45 °C/decade, which captures more than 90% of the regional trend for 1951- 2012. We suggest that sparse in-situ measurements are responsible for underestimation of the SAT change in the gridded datasets. It is likely that enhanced climate warming may also have happened in the other regions of the Arctic since the late 1990s but left undetected because of incomplete observational coverage.« less

Continuously amplified warming in the Alaskan Arctic: Implications for estimating global warming hiatus: SPATIAL COVERAGE AND BIAS IN TREND

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Kang; Zhang, Tingjun; Zhang, Xiangdong

Historically, in-situ measurements have been notoriously sparse over the Arctic. As a consequence, the existing gridded data of Surface Air Temperature (SAT) may have large biases in estimating the warming trend in this region. Using data from an expanded monitoring network with 31 stations in the Alaskan Arctic, we demonstrate that the SAT has increased by 2.19 °C in this region, or at a rate of 0.23 °C/decade during 1921-2015. Mean- while, we found that the SAT warmed at 0.71 °C/decade over 1998-2015, which is two to three times faster than the rate established from the gridded datasets. Focusing onmore » the "hiatus" period 1998-2012 as identied by the Intergovernmental Panel on Climate Change (IPCC) report, the SAT has increased at 0.45 °C/decade, which captures more than 90% of the regional trend for 1951- 2012. We suggest that sparse in-situ measurements are responsible for underestimation of the SAT change in the gridded datasets. It is likely that enhanced climate warming may also have happened in the other regions of the Arctic since the late 1990s but left undetected because of incomplete observational coverage.« less

Continuously amplified warming in the Alaskan Arctic: Implications for estimating global warming hiatus

USGS Publications Warehouse

Wang, Kang; Zhang, Tingjun; Zhang, Xiangdong; Clow, Gary D.; Jafarov, Elchin E.; Overeem, Irina; Romanovsky, Vladimir; Peng, Xiaoqing; Cao, Bin

2017-01-01

Historically, in situ measurements have been notoriously sparse over the Arctic. As a consequence, the existing gridded data of surface air temperature (SAT) may have large biases in estimating the warming trend in this region. Using data from an expanded monitoring network with 31 stations in the Alaskan Arctic, we demonstrate that the SAT has increased by 2.19°C in this region, or at a rate of 0.23°C/decade during 1921–2015. Meanwhile, we found that the SAT warmed at 0.71°C/decade over 1998–2015, which is 2 to 3 times faster than the rate established from the gridded data sets. Focusing on the “hiatus” period 1998–2012 as identified by the Intergovernmental Panel on Climate Change (IPCC) report, the SAT has increased at 0.45°C/decade, which captures more than 90% of the regional trend for 1951–2012. We suggest that sparse in situ measurements are responsible for underestimation of the SAT change in the gridded data sets. It is likely that enhanced climate warming may also have happened in the other regions of the Arctic since the late 1990s but left undetected because of incomplete observational coverage.

Improved Detection of Local Earthquakes in the Vienna Basin (Austria), using Subspace Detectors

NASA Astrophysics Data System (ADS)

Apoloner, Maria-Theresia; Caffagni, Enrico; Bokelmann, Götz

2016-04-01

The Vienna Basin in Eastern Austria is densely populated and highly-developed; it is also a region of low to moderate seismicity, yet the seismological network coverage is relatively sparse. This demands improving our capability of earthquake detection by testing new methods, enlarging the existing local earthquake catalogue. This contributes to imaging tectonic fault zones for better understanding seismic hazard, also through improved earthquake statistics (b-value, magnitude of completeness). Detection of low-magnitude earthquakes or events for which the highest amplitudes slightly exceed the signal-to-noise-ratio (SNR), may be possible by using standard methods like the short-term over long-term average (STA/LTA). However, due to sparse network coverage and high background noise, such a technique may not detect all potentially recoverable events. Yet, earthquakes originating from the same source region and relatively close to each other, should be characterized by similarity in seismic waveforms, at a given station. Therefore, waveform similarity can be exploited by using specific techniques such as correlation-template based (also known as matched filtering) or subspace detection methods (based on the subspace theory). Matching techniques basically require a reference or template event, usually characterized by high waveform coherence in the array receivers, and high SNR, which is cross-correlated with the continuous data. Instead, subspace detection methods overcome in principle the necessity of defining template events as single events, but use a subspace extracted from multiple events. This approach theoretically should be more robust in detecting signals that exhibit a strong variability (e.g. because of source or magnitude). In this study we scan the continuous data recorded in the Vienna Basin with a subspace detector to identify additional events. This will allow us to estimate the increase of the seismicity rate in the local earthquake catalogue, therefore providing an evaluation of network performance and efficiency of the method.

Disrupted Small-World Networks in Schizophrenia

ERIC Educational Resources Information Center

Liu, Yong; Liang, Meng; Zhou, Yuan; He, Yong; Hao, Yihui; Song, Ming; Yu, Chunshui; Liu, Haihong; Liu, Zhening; Jiang, Tianzi

2008-01-01

The human brain has been described as a large, sparse, complex network characterized by efficient small-world properties, which assure that the brain generates and integrates information with high efficiency. Many previous neuroimaging studies have provided consistent evidence of "dysfunctional connectivity" among the brain regions in…

Canny edge-based deformable image registration

NASA Astrophysics Data System (ADS)

Kearney, Vasant; Huang, Yihui; Mao, Weihua; Yuan, Baohong; Tang, Liping

2017-02-01

This work focuses on developing a 2D Canny edge-based deformable image registration (Canny DIR) algorithm to register in vivo white light images taken at various time points. This method uses a sparse interpolation deformation algorithm to sparsely register regions of the image with strong edge information. A stability criterion is enforced which removes regions of edges that do not deform in a smooth uniform manner. Using a synthetic mouse surface ground truth model, the accuracy of the Canny DIR algorithm was evaluated under axial rotation in the presence of deformation. The accuracy was also tested using fluorescent dye injections, which were then used for gamma analysis to establish a second ground truth. The results indicate that the Canny DIR algorithm performs better than rigid registration, intensity corrected Demons, and distinctive features for all evaluation matrices and ground truth scenarios. In conclusion Canny DIR performs well in the presence of the unique lighting and shading variations associated with white-light-based image registration.

A sparse representation of the pathologist's interaction with whole slide images to improve the assigned relevance of regions of interest

NASA Astrophysics Data System (ADS)

Santiago, Daniel; Corredor, Germán.; Romero, Eduardo

2017-11-01

During a diagnosis task, a Pathologist looks over a Whole Slide Image (WSI), aiming to find out relevant pathological patterns. Nonetheless, a virtual microscope captures these structures, but also other cellular patterns with different or none diagnostic meaning. Annotation of these images depends on manual delineation, which in practice becomes a hard task. This article contributes a new method for detecting relevant regions in WSI using the routine navigations in a virtual microscope. This method constructs a sparse representation or dictionary of each navigation path and determines the hidden relevance by maximizing the incoherence between several paths. The resulting dictionaries are then projected onto each other and relevant information is set to the dictionary atoms whose similarity is higher than a custom threshold. Evaluation was performed with 6 pathological images segmented from a skin biopsy already diagnosed with basal cell carcinoma (BCC). Results show that our proposal outperforms the baseline by more than 20%.

Pumping Iron in Australia: Prevalence, Trends and Sociodemographic Correlates of Muscle Strengthening Activity Participation from a National Sample of 195,926 Adults.

PubMed

Bennie, Jason A; Pedisic, Zeljko; van Uffelen, Jannique G Z; Charity, Melanie J; Harvey, Jack T; Banting, Lauren K; Vergeer, Ineke; Biddle, Stuart J H; Eime, Rochelle M

2016-01-01

The current Australian Physical Activity Guidelines recommend that adults engage in regular muscle-strengthening activity (e.g. strength or resistance training). However, public health surveillance studies describing the patterns and trends of population-level muscle-strengthening activity participation are sparse. The aim of this study is to examine the prevalence, trends and sociodemographic correlates of muscle-strengthening activity participation in a national-representative sample of Australians aged 15 years and over. Between 2001 and 2010, quarterly cross-sectional national telephone surveys were conducted as part of the Australian Sports Commission's 'Exercise, Recreation and Sport Survey'. Pooled population-weighted proportions were calculated for reporting: [i] no muscle-strengthening activity; [ii] insufficient muscle-strengthening activity, and [iii] sufficient muscle-strengthening activity. Associations with sociodemographic variables were assessed using multiple logistic regression analyses. Out of 195,926 participants, aged 15-98 years, only 10.4% (95% CI: 10.1-10.7) and 9.3% (95% CI: 9.1-9.5) met the muscle-strengthening activity recommendations in the past two weeks and in the past year, respectively. Older adults (50+ years), and those living in socioeconomically disadvantaged, outer regional/remote areas and with lower education were less likely to report sufficient muscle-strengthening activity (p<0.001). Over the 10-year monitoring period, there was a significant increase in the prevalence of sufficient muscle-strengthening activity (6.4% to 12.0%, p-value for linear trend <0.001). A vast majority of Australian adults did not engage in sufficient muscle-strengthening activity. There is a need for public health strategies to support participation in muscle-strengthening activity in this population. Such strategies should target older and lower educated adults, and those living in socioeconomically disadvantaged, outer regional/remote and areas.

SD-MSAEs: Promoter recognition in human genome based on deep feature extraction.

PubMed

Xu, Wenxuan; Zhang, Li; Lu, Yaping

2016-06-01

The prediction and recognition of promoter in human genome play an important role in DNA sequence analysis. Entropy, in Shannon sense, of information theory is a multiple utility in bioinformatic details analysis. The relative entropy estimator methods based on statistical divergence (SD) are used to extract meaningful features to distinguish different regions of DNA sequences. In this paper, we choose context feature and use a set of methods of SD to select the most effective n-mers distinguishing promoter regions from other DNA regions in human genome. Extracted from the total possible combinations of n-mers, we can get four sparse distributions based on promoter and non-promoters training samples. The informative n-mers are selected by optimizing the differentiating extents of these distributions. Specially, we combine the advantage of statistical divergence and multiple sparse auto-encoders (MSAEs) in deep learning to extract deep feature for promoter recognition. And then we apply multiple SVMs and a decision model to construct a human promoter recognition method called SD-MSAEs. Framework is flexible that it can integrate new feature extraction or new classification models freely. Experimental results show that our method has high sensitivity and specificity. Copyright © 2016 Elsevier Inc. All rights reserved.

Air ambulance and hospital services for critically ill and injured in Greenland, Iceland and the Faroe Islands: how can we improve?

PubMed Central

Gunnarsson, Björn; Jensen, Niels S Kieler; Garði, Tummas i; Harðardóttir, Helga; Stefánsdóttir, Lilja; Heimisdóttir, María

2015-01-01

The Nordic Atlantic Cooperation (NORA) is an intergovernmental organization under the auspices of the Nordic Council of Ministers. The NORA region comprises Greenland, Iceland, Faroe Islands and western coastal areas of Norway. Historical, cultural and institutional links bind these nations together in multiple ways, and regional co-operation has in recent years become a focus of interest. This commentary addresses air medical services (AMSs) and available advanced hospital services in the 3 smallest NORA countries challenged sparse populations, hereafter referred to as the region. It seems likely that strengthened regional co-operation can help these countries to address common challenges within health care by exchanging know-how and best practices, pooling resources and improving the efficiency of care delivery. The 4 largest hospitals in the region, Dronning Ingrids Hospital in Nuuk (Greenland), Landspítali in Reykjavík and Sjúkrahúsið á Akureyri, (both in Iceland) and Landssjúkrahúsið Tórshavn on the Faroe Islands, have therefore undertaken the project Network for patient transport in the North-West Atlantic (in Danish: Netværk for patienttransport i Vest-Norden). The goal of the project, and of this article, is to exchange information and provide an overview of current AMSs and access to acute hospital care for severely ill or injured patients in the 3 participating countries. Of equal importance is the intention to highlight the need for increased regional co-operation to optimize use of limited resources in the provision of health care services. PMID:26066019

Problems of Ecological Environment in Western China

ERIC Educational Resources Information Center

Wenjuan, Zhang; Jixi, Gao

2004-01-01

Western China is vast, expansive, sparsely populated, and economically underdeveloped, but it plays an important role in economic and social development in China. While the west is a crucial base of power resources, it is also rich in fauna and flora resources and the major habitat for China's many rare wildlife species. Therefore, protecting its…

Pre-School Education for Children Living in Sparsely Populated Areas.

ERIC Educational Resources Information Center

Council for Cultural Cooperation, Strasbourg (France). Committee for General and Technical Education.

This report describes the proceedings of a symposium on rural preschool education, one of four conferences in a Council of Europe preschool project relating to equal educational opportunity. Delegates from 19 European countries participated. Included in this report are summaries of a paper on the ecology of childhood (discussing the background of…

Imputation of Missing Genotypes From Sparse to High Density Using Long-Range Phasing

USDA-ARS?s Scientific Manuscript database

Related individuals in a population share long chromosome segments which trace to a common ancestor. We describe a long-range phasing algorithm that makes use of this property to phase whole chromosomes and simultaneously impute a large number of missing markers. We test our method by imputing marke...

A Neglected Population: Drug-Using Women and Women's Methods of HIV/STI Prevention

ERIC Educational Resources Information Center

Gollub, Erica L.

2008-01-01

Women drug users are at extremely high risk of HIV and sexually transmitted infections (STIs) from sexual transmission, but remain seriously neglected in intervention research promoting women-initiated methods of HIV/STI prevention. Sparse available data indicate a high interest and enthusiasm for women-initiated methods among these women.…

Environmental Education in Sparsely Populated Areas: Conflicting Attitudes in Student's Conception of Environmental Issues.

ERIC Educational Resources Information Center

Chaib, Mohamed

1988-01-01

Two studies in southeastern Sweden examined rural children's conflicting attitudes toward environmental change in the local community. Following a yearlong curriculum in environmental studies, 14 fifth and sixth graders in Ramkvilla were presented with an imaginary scenario involving the construction of a new factory. Their small, somewhat idyllic…

General Christopher C. Andrews: Leading the Minnesota Forestry Revolution

ERIC Educational Resources Information Center

Rice, Anna M.

2002-01-01

In the nineteenth century, America's burgeoning population certainly did grab all the timber it could. Vast pine forests stretched from Maine to Dakota, and the lumber industry voraciously consumed them from east to west. In 1800, the Minnesota territory was sparsely sprinkled with fur traders and American Indians. By 1850, its bounteous forests…

Reversing Patterns of Control in Australia: Can Schools Be Self-Governing?

ERIC Educational Resources Information Center

Smart, Don

Historically, in sharp contrast with the United States, the Australian state systems of public education have always been extremely centralized and hierarchical in structure. While these highly centralized systems served the sparsely populated Australian states well during the early years of this century in providing universal free education and…

Family Involvement in Creative Teaching Practices for All in Small Rural Schools

ERIC Educational Resources Information Center

Vigo Arrazola, Begoña; Soriano Bozalongo, Juana

2015-01-01

Parental involvement is interpreted as a key form of support that can contribute to the establishment of inclusive practices in schools, but this can be difficult in sparsely populated areas. Using ethnographic methods of participant observation, informal conversations and document analysis, this article therefore focuses on family involvement…

Widening Access through Partnerships with Working Life

ERIC Educational Resources Information Center

Casson, Andrew

2006-01-01

Dalarna University has doubled its student numbers during the past five years, and now has the highest proportion of students from non-academic backgrounds of Swedish universities (37%). The province of Dalarna combines steel and paper industry in a number of relatively small towns with large areas of sparsely populated countryside. By tradition,…

Center for Support of Mental Health Services in Isolated Rural Areas. Final Report.

ERIC Educational Resources Information Center

Ciarlo, James A.

In 1994, the University of Denver received a grant to develop and operate the Frontier Mental Health Services Resource Network (FMHSRN). FMHSRN's principal aim was to improve delivery of mental health services in sparsely populated "frontier" areas by providing technical assistance to frontier and rural audiences. Traditional…

Rural Schools: Off the Beaten Path

ERIC Educational Resources Information Center

Gordon, Dan

2011-01-01

This article is the second of a two-part series on how schools in different types of communities meet the challenge of implementing technology. The emergence of technology as a critical component of education has presented rural districts with an invaluable tool for overcoming the problems created by sparse and remote populations. But rural…

Insights into the latent multinomial model through mark-resight data on female grizzly bears with cubs-of-the-year

USGS Publications Warehouse

Higgs, Megan D.; Link, William; White, Gary C.; Haroldson, Mark A.; Bjornlie, Daniel D.

2013-01-01

Mark-resight designs for estimation of population abundance are common and attractive to researchers. However, inference from such designs is very limited when faced with sparse data, either from a low number of marked animals, a low probability of detection, or both. In the Greater Yellowstone Ecosystem, yearly mark-resight data are collected for female grizzly bears with cubs-of-the-year (FCOY), and inference suffers from both limitations. To overcome difficulties due to sparseness, we assume homogeneity in sighting probabilities over 16 years of bi-annual aerial surveys. We model counts of marked and unmarked animals as multinomial random variables, using the capture frequencies of marked animals for inference about the latent multinomial frequencies for unmarked animals. We discuss undesirable behavior of the commonly used discrete uniform prior distribution on the population size parameter and provide OpenBUGS code for fitting such models. The application provides valuable insights into subtleties of implementing Bayesian inference for latent multinomial models. We tie the discussion to our application, though the insights are broadly useful for applications of the latent multinomial model.

Avian demographic responses to drought and fire: a community-level perspective.

PubMed

Saracco, James F; Fettig, Stephen M; San Miguel, George L; Mehlman, David W; Albert, Steven K

2018-05-22

Drought stress is an important consideration for wildlife in arid and semiarid regions under climate change. Drought can impact plant and animal populations directly, through effects on their physiology, as well as indirectly through effects on vegetation productivity and resource availability, and by creating conditions conducive to secondary disturbance, such as wildfire. We implemented a novel approach to understanding community-level demographic responses of birds and their habitats to these stressors in the context of climate change at 14 study sites in the Four Corners region of the southwestern United States. A large wildfire affecting three of the sites provided a natural experiment for also examining fire effects on vegetation and the bird community. We assessed (1) trends in drought and end-of-century (2071-2100) predicted average drought conditions under mid-range and high greenhouse gas concentration trajectory scenarios; (2) effects of drought and fire on habitat (vegetation greenness); and (3) effects of drought and fire on community-level avian productivity and adult apparent survival rates. Drought has increased and is expected to increase further at our study sites under climate change. Under spring drought conditions, vegetation greenness and avian productivity declined, while summer drought appeared to negatively affect adult apparent survival rates. Response to fire was mixed; in the year of the fire, avian productivity declined, but was higher than normal for several years post-fire. Our results highlight important links between environmental stressors and avian vital rates that will likely affect population trajectories in this region under climate change. We suggest that the use and continued development of community-level demographic models will provide useful tool for leveraging sparse species-level data to provide multi-species inferences and inform conservation. © 2018 by the Ecological Society of America.

A Newly Defined Area of the Mouse Anterior Hypothalamus Involved in Septohypothalamic Circuit: Perifornical Area of the Anterior Hypothalamus, PeFAH.

PubMed

Horii-Hayashi, Noriko; Nishi, Mayumi

2018-02-27

Although the hypothalamus is classified into more than 10 compartments, it still contains uncharacterized areas. In this study, we identified a new triangular-shaped area between the paraventricular hypothalamic nucleus (PVN) and the fornix area in the mouse anterior hypothalamus, which is enriched in chondroitin sulfate proteoglycans (CSPGs). We designated this region as the perifornical area of the anterior hypothalamus (PeFAH) based on its anatomical location. As evidenced by Nissl staining, the PeFAH was distinguishable as an area of relatively low density. Immunohistochemical and DNA microarray analyses indicated that PeFAH contains sparsely distributed calretinin-positive neurons and densely clustered enkephalin-positive neurons. Furthermore, the PeFAH was shown to have bidirectional neural connections with the lateral septum. Indeed, we confirmed enkephalinergic projections from PeFAH neurons to the lateral septum, and inversely, calbindin-positive lateral septum neurons as afferents to the PeFAH. Finally, c-Fos expression analysis revealed that the activity of certain PeFAH neuronal populations tended to be increased by psychological stressors, but not that of enkephalinergic neurons. We proposed PeFAH as a new region in the AH.

Using Passive Sampling to Asses Ozone Formation in Sparsely Monitored Areas

NASA Astrophysics Data System (ADS)

Crosby, C. M.; Mainord, J.; George, L. A.

2016-12-01

Tropospheric ozone (O3), a secondary pollutant, is detrimental to both human health and the environment. O3 is formed from nitrogen oxides (NOx) and volatile organic compounds, (VOC's) in the presence of sunlight. Hermiston is a low population rural city in Oregon (17,707), where O3 levels are expected to be minimal. However, Hermiston has recently experienced elevated O3 concentrations, approaching EPA levels of non-attainment. These levels were not predicted by airshed modeling of the region, suggesting that precursor emissions are not adequately represented in the model. Due to the limited monitoring in the area, there are no measurements of precursors in the region. In this study, passive Ogawa samplers were used to measure NOx and O3 levels at twenty sites in the area. The concentrations were then mapped in conjunction with wind trajectories derived from HYSPLIT and compared to NOx point sources attained from the National Emissions Inventory (NEI). The measurement campaign revealed areas of elevated NOx concentrations that were not accounted for in the airshed model. Further exploration is needed to identify these sources. This study lays groundwork for the use of passive sampling to ground-truth airshed models in the absence of monitoring networks.

Advances in variable selection methods II: Effect of variable selection method on classification of hydrologically similar watersheds in three Mid-Atlantic ecoregions

EPA Science Inventory

Hydrological flow predictions in ungauged and sparsely gauged watersheds use regionalization or classification of hydrologically similar watersheds to develop empirical relationships between hydrologic, climatic, and watershed variables. The watershed classifications may be based...

Mapping impervious surfaces using object-oriented classification in a semiarid urban region

USDA-ARS?s Scientific Manuscript database

Mapping the expansion of impervious surfaces in urbanizing areas is important for monitoring and understanding the hydrologic impacts of land development. The most common approach using spectral vegetation indices, however, is difficult in arid and semiarid environments where vegetation is sparse an...

Reliable positioning in a sparse GPS network, eastern Ontario

NASA Astrophysics Data System (ADS)

Samadi Alinia, H.; Tiampo, K.; Atkinson, G. M.

2013-12-01

Canada hosts two regions that are prone to large earthquakes: western British Columbia, and the St. Lawrence River region in eastern Canada. Although eastern Ontario is not as seismically active as other areas of eastern Canada, such as the Charlevoix/Ottawa Valley seismic zone, it experiences ongoing moderate seismicity. In historic times, potentially damaging events have occurred in New York State (Attica, 1929, M=5.7; Plattsburg, 2002, M=5.0), north-central Ontario (Temiskaming, 1935, M=6.2; North Bay, 2000, M=5.0), eastern Ontario (Cornwall, 1944, M=5.8), Georgian Bay (2005, MN=4.3), and western Quebec (Val-Des-Bois,2010, M=5.0, MN=5.8). In eastern Canada, the analysis of detailed, high-precision measurements of surface deformation is a key component in our efforts to better characterize the associated seismic hazard. The data from precise, continuous GPS stations is necessary to adequately characterize surface velocities from which patterns and rates of stress accumulation on faults can be estimated (Mazzotti and Adams, 2005; Mazzotti et al., 2005). Monitoring of these displacements requires employing high accuracy GPS positioning techniques. Detailed strain measurements can determine whether the regional strain everywhere is commensurate with a large event occurring every few hundred years anywhere within this general area or whether large earthquakes are limited to specific areas (Adams and Halchuck, 2003; Mazzotti and Adams, 2005). In many parts of southeastern Ontario and western Québec, GPS stations are distributed quite sparsely, with spacings of approximately 100 km or more. The challenge is to provide accurate solutions for these sparse networks with an approach that is capable of achieving high-accuracy positioning. Here, various reduction techniques are applied to a sparse network installed with the Southern Ontario Seismic Network in eastern Ontario. Recent developments include the implementation of precise point positioning processing on acquired GPS raw data. These are based on precise GPS orbit and clock data products with centimeter accuracy computed beforehand. Here, the analysis of 1Hz GPS data is conducted in order to find the most reliable regional network from eight stations (STCO, TYNO, ACTO, INUQ, IVKQ, KLBO, MATQ and ALGO) that cover the study area in eastern Ontario. In this way, the estimated parameters are the total number of ambiguities and resolved ambiguities, posteriori rms of each baseline and the coordinates for each station and their differences with the known coordinates. The positioning accuracy, the corrections and the accuracy of interpolated corrections, and the initialization time required for precise positioning are presented for the various applications.

A probabilistic method for streamflow projection and associated uncertainty analysis in a data sparse alpine region

NASA Astrophysics Data System (ADS)

Ren, Weiwei; Yang, Tao; Shi, Pengfei; Xu, Chong-yu; Zhang, Ke; Zhou, Xudong; Shao, Quanxi; Ciais, Philippe

2018-06-01

Climate change imposes profound influence on regional hydrological cycle and water security in many alpine regions worldwide. Investigating regional climate impacts using watershed scale hydrological models requires a large number of input data such as topography, meteorological and hydrological data. However, data scarcity in alpine regions seriously restricts evaluation of climate change impacts on water cycle using conventional approaches based on global or regional climate models, statistical downscaling methods and hydrological models. Therefore, this study is dedicated to development of a probabilistic model to replace the conventional approaches for streamflow projection. The probabilistic model was built upon an advanced Bayesian Neural Network (BNN) approach directly fed by the large-scale climate predictor variables and tested in a typical data sparse alpine region, the Kaidu River basin in Central Asia. Results show that BNN model performs better than the general methods across a number of statistical measures. The BNN method with flexible model structures by active indicator functions, which reduce the dependence on the initial specification for the input variables and the number of hidden units, can work well in a data limited region. Moreover, it can provide more reliable streamflow projections with a robust generalization ability. Forced by the latest bias-corrected GCM scenarios, streamflow projections for the 21st century under three RCP emission pathways were constructed and analyzed. Briefly, the proposed probabilistic projection approach could improve runoff predictive ability over conventional methods and provide better support to water resources planning and management under data limited conditions as well as enable a facilitated climate change impact analysis on runoff and water resources in alpine regions worldwide.

A robust holographic autofocusing criterion based on edge sparsity: comparison of Gini index and Tamura coefficient for holographic autofocusing based on the edge sparsity of the complex optical wavefront

NASA Astrophysics Data System (ADS)

Tamamitsu, Miu; Zhang, Yibo; Wang, Hongda; Wu, Yichen; Ozcan, Aydogan

2018-02-01

The Sparsity of the Gradient (SoG) is a robust autofocusing criterion for holography, where the gradient modulus of the complex refocused hologram is calculated, on which a sparsity metric is applied. Here, we compare two different choices of sparsity metrics used in SoG, specifically, the Gini index (GI) and the Tamura coefficient (TC), for holographic autofocusing on dense/connected or sparse samples. We provide a theoretical analysis predicting that for uniformly distributed image data, TC and GI exhibit similar behavior, while for naturally sparse images containing few high-valued signal entries and many low-valued noisy background pixels, TC is more sensitive to distribution changes in the signal and more resistive to background noise. These predictions are also confirmed by experimental results using SoG-based holographic autofocusing on dense and connected samples (such as stained breast tissue sections) as well as highly sparse samples (such as isolated Giardia lamblia cysts). Through these experiments, we found that ToG and GoG offer almost identical autofocusing performance on dense and connected samples, whereas for naturally sparse samples, GoG should be calculated on a relatively small region of interest (ROI) closely surrounding the object, while ToG offers more flexibility in choosing a larger ROI containing more background pixels.

Hybrid Geometric Calibration Method for Multi-Platform Spaceborne SAR Image with Sparse Gcps

NASA Astrophysics Data System (ADS)

Lv, G.; Tang, X.; Ai, B.; Li, T.; Chen, Q.

2018-04-01

Geometric calibration is able to provide high-accuracy geometric coordinates of spaceborne SAR image through accurate geometric parameters in the Range-Doppler model by ground control points (GCPs). However, it is very difficult to obtain GCPs that covering large-scale areas, especially in the mountainous regions. In addition, the traditional calibration method is only used for single platform SAR images and can't support the hybrid geometric calibration for multi-platform images. To solve the above problems, a hybrid geometric calibration method for multi-platform spaceborne SAR images with sparse GCPs is proposed in this paper. First, we calibrate the master image that contains GCPs. Secondly, the point tracking algorithm is used to obtain the tie points (TPs) between the master and slave images. Finally, we calibrate the slave images using TPs as the GCPs. We take the Beijing-Tianjin- Hebei region as an example to study SAR image hybrid geometric calibration method using 3 TerraSAR-X images, 3 TanDEM-X images and 5 GF-3 images covering more than 235 kilometers in the north-south direction. Geometric calibration of all images is completed using only 5 GCPs. The GPS data extracted from GNSS receiver are used to assess the plane accuracy after calibration. The results after geometric calibration with sparse GCPs show that the geometric positioning accuracy is 3 m for TSX/TDX images and 7.5 m for GF-3 images.

Decadal Changes in Ozone and Emissions in Central California and Current Issues

NASA Astrophysics Data System (ADS)

Tanrikulu, S.; Beaver, S.; Soong, S.; Tran, C.; Cordova, J.; Palazoglu, A.

2011-12-01

The relationships among ozone, emissions, and meteorology are very complex in central California, and must be well studied and understood in order to facilitate better air quality planning. Factors significantly impacting changes in emissions such as economic and population growth, and adopted emission controls make the matter even more complex. Here we review the history of ozone pollution in central California since the 1970s to plan for the future. Since the 1970s, changes in emissions have been accompanied by likewise dramatic changes in region-to-region differences in air quality. We focus on the coastal San Francisco Bay Area (SFBA) and the inland San Joaquin Valley (SJV). In the 1970s, the SFBA population was approaching 5 million people while the considerably larger and more rural SJV population remained below 2 million. The SFBA population was mostly confined to coastal locations. Peak ozone levels occurred mostly around the population centers and especially over the Bay itself. Hourly average ozone levels routinely approached 160 ppb. These high ozone levels promoted regulations under which SFBA emissions were continuously reduced through the present. By the 1990s, SFBA emissions had been reduced considerably despite the region's population growing to around 6 million. Relative to the 1970s, in 1990s the SFBA had lower peak ozone levels that were shifted to inland locations where much of the population growth was occurring. The SFBA still exceeded the federal 1-hour standard. A rapidly changing economic landscape in the 1970s promoted vast changes in the central California population distribution. In the SJV, the OPEC oil crisis promoted significant development of petroleum resources. Meanwhile, family farms were quickly being replaced with commercial-scale farming operations. The SJV population rapidly expanded to around 3 million people by the early 1990s. During this time, SJV emissions increased considerably, largely from increases in mobile source activities. The previously sparsely populated SJV had quickly developed an even more severe ozone problem than previous years. From 1990 to 2010, the SFBA population expanded to inland locations and then even further into the sheltered SJV. SFBA emissions for ROG and NOx were decreased around 40% and 15%, respectively during this period. High ozone levels became rather infrequent for coastal SFBA locations. During the same period, the SJV population continued to expand rapidly while emissions decreased, especially for ROG. Peak ozone levels remained around 100 ppb and shifted to locations downwind of Fresno and Bakersfield. Central California has experienced perhaps the most dramatic population growth and shifts in the United States during the contemporary economic era. These changes in population have led to some of the most difficult air quality management problems faced by regulators in the United States. Lessons learned from central California highlight the potential benefits of acting early and also the necessity for a long-term, flexible approach using sustained regulations to accompany population changes.

Compressive sensing for single-shot two-dimensional coherent spectroscopy

NASA Astrophysics Data System (ADS)

Harel, E.; Spencer, A.; Spokoyny, B.

2017-02-01

In this work, we explore the use of compressive sensing for the rapid acquisition of two-dimensional optical spectra that encodes the electronic structure and ultrafast dynamics of condensed-phase molecular species. Specifically, we have developed a means to combine multiplexed single-element detection and single-shot and phase-resolved two-dimensional coherent spectroscopy. The method described, which we call Single Point Array Reconstruction by Spatial Encoding (SPARSE) eliminates the need for costly array detectors while speeding up acquisition by several orders of magnitude compared to scanning methods. Physical implementation of SPARSE is facilitated by combining spatiotemporal encoding of the nonlinear optical response and signal modulation by a high-speed digital micromirror device. We demonstrate the approach by investigating a well-characterized cyanine molecule and a photosynthetic pigment-protein complex. Hadamard and compressive sensing algorithms are demonstrated, with the latter achieving compression factors as high as ten. Both show good agreement with directly detected spectra. We envision a myriad of applications in nonlinear spectroscopy using SPARSE with broadband femtosecond light sources in so-far unexplored regions of the electromagnetic spectrum.

A case for archaeological reconnaissance of the Cabo Catoche-Porvenir region of the northeastern Yucatan Peninsula

NASA Technical Reports Server (NTRS)

Duller, Charles E.

1990-01-01

Satellite remote sensing technology is a tool with which archaeologists can, with relative ease, survey a region that is otherwise inaccessible. The northeast corner of the Yucatan Peninsula is such an area: it is isolated and sparsely inhabited, with dense forest and extensive swamps. From Cabo Catoche inland to Cancun, this remote corner of the ancient Maya world is virtually unexplored. Recent satellite images disclose evidence of past human activity in this unexplored region and offer a compelling argument for an archaeological reconnaissance.

Walrus areas of use in the Chukchi Sea during sparse sea ice cover

USGS Publications Warehouse

Jay, Chadwick V.; Fischbach, Anthony S.; Kochnev, Anatoly A.

2012-01-01

The Pacific walrus Odobenus rosmarus divergens feeds on benthic invertebrates on the continental shelf of the Chukchi and Bering Seas and rests on sea ice between foraging trips. With climate warming, ice-free periods in the Chukchi Sea have increased and are projected to increase further in frequency and duration. We radio-tracked walruses to estimate areas of walrus foraging and occupancy in the Chukchi Sea from June to November of 2008 to 2011, years when sea ice was sparse over the continental shelf in comparison to historical records. The earlier and more extensive sea ice retreat in June to September, and delayed freeze-up of sea ice in October to November, created conditions for walruses to arrive earlier and stay later in the Chukchi Sea than in the past. The lack of sea ice over the continental shelf from September to October caused walruses to forage in nearshore areas instead of offshore areas as in the past. Walruses did not frequent the deep waters of the Arctic Basin when sea ice retreated off the shelf. Walruses foraged in most areas they occupied, and areas of concentrated foraging generally corresponded to regions of high benthic biomass, such as in the northeastern (Hanna Shoal) and southwestern Chukchi Sea. A notable exception was the occurrence of concentrated foraging in a nearshore area of northwestern Alaska that is apparently depauperate in walrus prey. With increasing sea ice loss, it is likely that walruses will increase their use of coastal haul-outs and nearshore foraging areas, with consequences to the population that are yet to be understood.

Development of a population pharmacokinetic model for carbamazepine based on sparse therapeutic monitoring data from pediatric patients with epilepsy.

PubMed

Carlsson, Kristin Cecilie; Hoem, Nils Ove; Glauser, Tracy; Vinks, Alexander A

2005-05-01

Population models can be important extensions of therapeutic drug monitoring (TDM), as they allow estimation of individual pharmacokinetic parameters based on a small number of measured drug concentrations. This study used a Bayesian approach to explore the utility of routinely collected and sparse TDM data (1 sample per patient) for carbamazepine (CBZ) monotherapy in developing a population pharmacokinetic (PPK) model for CBZ in pediatric patients that would allow prediction of CBZ concentrations for both immediate- and controlled-release formulations. Patient and TDM data were obtained from a pediatric neurology outpatient database. Data were analyzed using an iterative 2-stage Bayesian algorithm and a nonparametric adaptive grid algorithm. Models were compared by final log likelihood, mean error (ME) as a measure of bias, and root mean squared error (RMSE) as a measure of precision. Fifty-seven entries with data on CBZ monotherapy were identified from the database and used in the analysis (36 from males, 21 from females; mean [SD] age, 9.1 [4.4] years [range, 2-21 years]). Preliminary models estimating clearance (Cl) or the elimination rate constant (K(el)) gave good prediction of serum concentrations compared with measured serum concentrations, but estimates of Cl and K(el) were highly correlated with estimates of volume of distribution (V(d)). Different covariate models were then tested. The selected model had zero-order input and had age and body weight as covariates. Cl (L/h) was calculated as K(el) . V(d), where K(el) = [K(i) - (K(s) . age)] and V(d) = [V(i) + (V(s) . body weight)]. Median parameter estimates were V(i) (intercept) = 11.5 L (fixed); V(s) (slope) = 0.3957 L/kg (range, 0.01200-1.5730); K(i) (intercept) = 0.173 h(-1) (fixed); and K(s) (slope) = 0.004487 h(-1) . y(-1) (range, 0.0001800-0.02969). The fit was good for estimates of steady-state serum concentrations based on prior values (population median estimates) (R = 0.468; R(2) = 0.219) but was even better for predictions based on individual Bayesian posterior values (R(2) = 0.991), with little bias (ME = -0.079) and good precision (RMSE = 0.055). Based on the findings of this study, sparse TDM data can be used for PPK modeling of CBZ clearance in children with epilepsy, and these models can be used to predict Cl at steady state in pediatric patients. However, to estimate additional pharmacokinetic model parameters (eg, the absorption rate constant and V(d)), it would be necessary to combine sparse TDM data with additional well-timed samples. This would allow development of more informative PPK models that could be used as part of Bayesian dose-individualization strategies.

The Joker: A custom Monte Carlo sampler for binary-star and exoplanet radial velocity data

NASA Astrophysics Data System (ADS)

Price-Whelan, Adrian M.; Hogg, David W.; Foreman-Mackey, Daniel; Rix, Hans-Walter

2017-01-01

Given sparse or low-quality radial-velocity measurements of a star, there are often many qualitatively different stellar or exoplanet companion orbit models that are consistent with the data. The consequent multimodality of the likelihood function leads to extremely challenging search, optimization, and MCMC posterior sampling over the orbital parameters. The Joker is a custom-built Monte Carlo sampler that can produce a posterior sampling for orbital parameters given sparse or noisy radial-velocity measurements, even when the likelihood function is poorly behaved. The method produces correct samplings in orbital parameters for data that include as few as three epochs. The Joker can therefore be used to produce proper samplings of multimodal pdfs, which are still highly informative and can be used in hierarchical (population) modeling.

Should we expect population thresholds for wildlife disease?

USGS Publications Warehouse

Lloyd-Smith, James O.; Cross, P.C.; Briggs, C.J.; Daugherty, M.; Getz, W.M.; Latto, J.; Sanchez, M.; Smith, A.; Swei, A.

2005-01-01

Host population thresholds for invasion or persistence of infectious disease are core concepts of disease ecology, and underlie on-going and controversial disease control policies based on culling and vaccination. Empirical evidence for these thresholds in wildlife populations has been sparse, however, though recent studies have narrowed this gap. Here we review the theoretical bases for population thresholds for disease, revealing why they are difficult to measure and sometimes are not even expected, and identifying important facets of wildlife ecology left out of current theories. We discuss strengths and weaknesses of selected empirical studies that have reported disease thresholds for wildlife, identify recurring obstacles, and discuss implications of our imperfect understanding of wildlife thresholds for disease control policy.

Measuring Change in Leadership Identity and Problem Framing

ERIC Educational Resources Information Center

Young, Michelle D.; O'Doherty, Ann; Gooden, Mark A.; Goodnow, Elisabeth

2011-01-01

In recent years, significant attention has been directed to the need for more and better-prepared educational leaders (Young, Crow, Murphy & Ogawa, 2009). While many organizations prepare school principals, evidence of program impact is sparse (Orr & Pounder, 2008; Southern Regional Education Board, 2008). The study described in this…

Introduction to Biological Soil Crusts

Science.gov Websites

Introduction to Biological Soil Crusts In more arid regions, vegetative cover is generally sparse. Open spaces are usually covered by biological soil crusts, a highly specialized community of cyanobacteria, mosses , and lichens (Figure 1). Biological soil crusts are commonly found in semiarid and arid environments

HEALTH EFFECTS AND CHARACTERIZATION OF URBAN AND RURAL COARSE PARTICULATEMATTER IN NORTHEASTERN COLORADO

EPA Science Inventory

The proposed research will contribute to our understanding of the health outcomes associated with CP and other air pollutants in a region of the country with relatively sparse monitoring data and few prior health effects studies. The work will allow comparison of responses in ...

Efficient transformation of an auditory population code in a small sensory system.

PubMed

Clemens, Jan; Kutzki, Olaf; Ronacher, Bernhard; Schreiber, Susanne; Wohlgemuth, Sandra

2011-08-16

Optimal coding principles are implemented in many large sensory systems. They include the systematic transformation of external stimuli into a sparse and decorrelated neuronal representation, enabling a flexible readout of stimulus properties. Are these principles also applicable to size-constrained systems, which have to rely on a limited number of neurons and may only have to fulfill specific and restricted tasks? We studied this question in an insect system--the early auditory pathway of grasshoppers. Grasshoppers use genetically fixed songs to recognize mates. The first steps of neural processing of songs take place in a small three-layer feed-forward network comprising only a few dozen neurons. We analyzed the transformation of the neural code within this network. Indeed, grasshoppers create a decorrelated and sparse representation, in accordance with optimal coding theory. Whereas the neuronal input layer is best read out as a summed population, a labeled-line population code for temporal features of the song is established after only two processing steps. At this stage, information about song identity is maximal for a population decoder that preserves neuronal identity. We conclude that optimal coding principles do apply to the early auditory system of the grasshopper, despite its size constraints. The inputs, however, are not encoded in a systematic, map-like fashion as in many larger sensory systems. Already at its periphery, part of the grasshopper auditory system seems to focus on behaviorally relevant features, and is in this property more reminiscent of higher sensory areas in vertebrates.

A Tool for Creating Regionally Calibrated High-Resolution Land Cover Data Sets for the West African Sahel: Using Machine Learning to Scale Up Hand-Classified Maps in a Data-Sparse Environment

NASA Astrophysics Data System (ADS)

Van Gordon, M.; Van Gordon, S.; Min, A.; Sullivan, J.; Weiner, Z.; Tappan, G. G.

2017-12-01

Using support vector machine (SVM) learning and high-accuracy hand-classified maps, we have developed a publicly available land cover classification tool for the West African Sahel. Our classifier produces high-resolution and regionally calibrated land cover maps for the Sahel, representing a significant contribution to the data available for this region. Global land cover products are unreliable for the Sahel, and accurate land cover data for the region are sparse. To address this gap, the U.S. Geological Survey and the Regional Center for Agriculture, Hydrology and Meteorology (AGRHYMET) in Niger produced high-quality land cover maps for the region via hand-classification of Landsat images. This method produces highly accurate maps, but the time and labor required constrain the spatial and temporal resolution of the data products. By using these hand-classified maps alongside SVM techniques, we successfully increase the resolution of the land cover maps by 1-2 orders of magnitude, from 2km-decadal resolution to 30m-annual resolution. These high-resolution regionally calibrated land cover datasets, along with the classifier we developed to produce them, lay the foundation for major advances in studies of land surface processes in the region. These datasets will provide more accurate inputs for food security modeling, hydrologic modeling, analyses of land cover change and climate change adaptation efforts. The land cover classification tool we have developed will be publicly available for use in creating additional West Africa land cover datasets with future remote sensing data and can be adapted for use in other parts of the world.

Disease Mapping for Stomach Cancer in Libya Based on Besag– York– Mollié (BYM) Model

PubMed

Alhdiri, Maryam Ahmed Salem; Samat, Nor Azah; Mohamed, Zulkifley

2017-06-25

Globally, Cancer is the ever-increasing health problem and most common cause of medical deaths. In Libya, it is an important health concern, especially in the setting of an aging population and limited healthcare facilities. Therefore, the goal of this research is to map of the county’ cancer incidence rate using the Bayesian method and identify the high-risk regions (for the first time in a decade). In the field of disease mapping, very little has been done to address the issue of analyzing sparse cancer diseases in Libya. Standardized Morbidity Ratio or SMR is known as a traditional approach to measure the relative risk of the disease, which is the ratio of observed and expected number of accounts in a region that has the greatest uncertainty if the disease is rare or small geographical region. Therefore, to solve some of SMR’s problems, we used statistical smoothing or Bayesian models to estimate the relative risk for stomach cancer incidence in Libya in 2007 based on the BYM model. This research begins with a short offer of the SMR and Bayesian model with BYM model, which we applied to stomach cancer incidence in Libya. We compared all of the results using maps and tables. We found that BYM model is potentially beneficial, because it gives better relative risk estimates compared to SMR method. As well as, it has can overcome the classical method problem when there is no observed stomach cancer in a region. Creative Commons Attribution License

Discrete Molecular Dynamics Can Predict Helical Prestructured Motifs in Disordered Proteins

PubMed Central

Han, Kyou-Hoon; Dokholyan, Nikolay V.; Tompa, Péter; Kalmár, Lajos; Hegedűs, Tamás

2014-01-01

Intrinsically disordered proteins (IDPs) lack a stable tertiary structure, but their short binding regions termed Pre-Structured Motifs (PreSMo) can form transient secondary structure elements in solution. Although disordered proteins are crucial in many biological processes and designing strategies to modulate their function is highly important, both experimental and computational tools to describe their conformational ensembles and the initial steps of folding are sparse. Here we report that discrete molecular dynamics (DMD) simulations combined with replica exchange (RX) method efficiently samples the conformational space and detects regions populating α-helical conformational states in disordered protein regions. While the available computational methods predict secondary structural propensities in IDPs based on the observation of protein-protein interactions, our ab initio method rests on physical principles of protein folding and dynamics. We show that RX-DMD predicts α-PreSMos with high confidence confirmed by comparison to experimental NMR data. Moreover, the method also can dissect α-PreSMos in close vicinity to each other and indicate helix stability. Importantly, simulations with disordered regions forming helices in X-ray structures of complexes indicate that a preformed helix is frequently the binding element itself, while in other cases it may have a role in initiating the binding process. Our results indicate that RX-DMD provides a breakthrough in the structural and dynamical characterization of disordered proteins by generating the structural ensembles of IDPs even when experimental data are not available. PMID:24763499

Generation of dense statistical connectomes from sparse morphological data

PubMed Central

Egger, Robert; Dercksen, Vincent J.; Udvary, Daniel; Hege, Hans-Christian; Oberlaender, Marcel

2014-01-01

Sensory-evoked signal flow, at cellular and network levels, is primarily determined by the synaptic wiring of the underlying neuronal circuitry. Measurements of synaptic innervation, connection probabilities and subcellular organization of synaptic inputs are thus among the most active fields of research in contemporary neuroscience. Methods to measure these quantities range from electrophysiological recordings over reconstructions of dendrite-axon overlap at light-microscopic levels to dense circuit reconstructions of small volumes at electron-microscopic resolution. However, quantitative and complete measurements at subcellular resolution and mesoscopic scales to obtain all local and long-range synaptic in/outputs for any neuron within an entire brain region are beyond present methodological limits. Here, we present a novel concept, implemented within an interactive software environment called NeuroNet, which allows (i) integration of sparsely sampled (sub)cellular morphological data into an accurate anatomical reference frame of the brain region(s) of interest, (ii) up-scaling to generate an average dense model of the neuronal circuitry within the respective brain region(s) and (iii) statistical measurements of synaptic innervation between all neurons within the model. We illustrate our approach by generating a dense average model of the entire rat vibrissal cortex, providing the required anatomical data, and illustrate how to measure synaptic innervation statistically. Comparing our results with data from paired recordings in vitro and in vivo, as well as with reconstructions of synaptic contact sites at light- and electron-microscopic levels, we find that our in silico measurements are in line with previous results. PMID:25426033

The Broadband Quandary for Rural America. The Main Street Economist: Commentary on the Rural Economy.

ERIC Educational Resources Information Center

Staihr, Brian

High speed data services known as broadband have the potential to make rural areas less isolated and improve the rural quality of life, but physical barriers, sparse population density, and few markets present significant obstacles to their deployment in rural areas. Broadband applications such as e-commerce, distance education, and telemedicine…

Intelligence and Family Size: Another Look. Discussion Papers No. 467-77.

ERIC Educational Resources Information Center

Olneck, Michael R.; Wolfe, Barbara L.

Periodically, fears are voiced that the intelligence level of the United States population is falling. Historically, this fear has been linked to the belief that fertility is inversely related to intelligence. Evidence for that belief is sparse and may be an artifact of the failure of researchers to consider completed families. An inverse…

Typicality Mediates Performance during Category Verification in Both Ad-Hoc and Well-Defined Categories

ERIC Educational Resources Information Center

Sandberg, Chaleece; Sebastian, Rajani; Kiran, Swathi

2012-01-01

Background: The typicality effect is present in neurologically intact populations for natural, ad-hoc, and well-defined categories. Although sparse, there is evidence of typicality effects in persons with chronic stroke aphasia for natural and ad-hoc categories. However, it is unknown exactly what influences the typicality effect in this…

Skin-Color Prejudice and Within-Group Racial Discrimination: Historical and Current Impact on Latino/a Populations

ERIC Educational Resources Information Center

Chavez-Dueñas, Nayeli Y.; Adames, Hector Y.; Organista, Kurt C.

2014-01-01

The psychological literature on colorism, a form of within-group racial discrimination, is sparse. In an effort to contribute to this understudied area and highlight its significance, a concise and selective review of the history of colorism in Latin America is provided. Specifically, three historical eras (i.e., conquest, colonization, and…

The Landscape Documentary: Unveiling the Face of "Wasteland."

ERIC Educational Resources Information Center

Denton, Craig L.

This paper outlines the process of a photographic landscape documentary project which set out to unveil the face of Utah's West Desert (a 42,000 square-mile, sparsely-populated, broad, rugged land of salt bed "playas" and high mountain ranges) comprising one-third of the state and which hoped to make the West Desert, recently under…

Distance Education: Is It Art or Is It Science?

ERIC Educational Resources Information Center

Munsch, Ted

2008-01-01

Distance education is becoming a more common method of curriculum delivery across grade levels in Australia, the United States and throughout the world. Especially in remote rural areas with sparse student populations, distance delivery of course work is often the only available means for students to learn and for teachers to teach. The days of…

A Population-Based Survival Assessment of Categorizing Level III and IV Rural Hospitals as Trauma Centers

ERIC Educational Resources Information Center

Arthur, Melanie; Newgard, Craig D.; Mullins, Richard J.; Diggs, Brian S.; Stone, Judith V.; Adams, Annette L.; Hedges, Jerris R.

2009-01-01

Context: Patients injured in rural areas are hypothesized to have improved outcomes if statewide trauma systems categorize rural hospitals as Level III and IV trauma centers, though evidence to support this belief is sparse. Purpose: To determine if there is improved survival among injured patients hospitalized in states that categorize rural…

Solo but Not Separate: Preparing 21st-Century School Library Professionals Who Can "Go It Alone"

ERIC Educational Resources Information Center

Pasco, Becky

2011-01-01

Preparing school librarians for a diverse array of 21st-century educational environments is a daunting task. Faculty in school library preparation programs send candidates out into sparsely populated rural areas, dense urban settings, and everything in between. Some candidates will provide services and resources in updated, modern facilities,…

Health status and epidemiological capacity and prospects: WHO Western Pacific Region.

PubMed

Blakely, Tony; Pega, Frank; Nakamura, Yosikazu; Beaglehole, Robert; Lee, Liming; Tukuitonga, Colin Fonotau

2011-08-01

This article on the state of epidemiology in the WHO Western Pacific Region (WPR) is the first in a series of eight articles commissioned by the International Epidemiological Association (IEA) to identify global opportunities to promote the development of epidemiology. Global mortality and disease data were used to summarize the burden of mortality, disease, risk factor and patterns of inequalities in the region. Medline bibliometrics were used to estimate epidemiological publication output by country. Key informant surveys, Internet and literature searches and author knowledge and networks were used to elicit perspectives on epidemiological training, research, funding and workforce. Findings The WPR has the lowest age-standardized disability-adjusted life-years (DALY) rate per 1000 of the six WHO regions, with non-communicable disease making the largest percentage contributions in both low- and middle-income countries (LMICs, 68%) and high-income countries (HICs, 84%) in the WPR. The number of Medline-indexed epidemiological research publications per year was greatest for Japan, Australia and China. However, the rate per head of population was greatest for Micronesia and New Zealand. The substantive focus of research roughly equated with burden of disease patterns. Research capacity (staff, funding, infrastructure) varies hugely between countries. Epidemiology training embedded within academic Masters of Public Health programmes is the dominant vehicle for training in most countries. Field epidemiology and in-service training are also common. The Pacific Island countries and territories, because of sparse populations over large distances and chronic workforce and funding capacity problems, rely on outside agencies (e.g. WHO, universities) for provision of training. Cross-national networks and collaborations are increasing. Communicable disease surveillance and research need consolidation (especially in eastern Asian WPR countries), and non-communicable disease epidemiological capacity requires strengthening to match disease trends. Capacity and sustainability of both training and research within LMICs in WPR are ongoing priorities. China in particular is advancing quickly. One role for the IEA in building capacity is facilitating collaborative networks within WPR.

Socioeconomic implications of tobacco use in Ghana.

PubMed

John, Rijo M; Mamudu, Hadii M; Liber, Alex C

2012-10-01

Country-level evidence from Africa on the prevalence of tobacco use and the role played by both demographic and socioeconomic factors, as influences on the use of tobacco products, is sparse. This paper analyzes the determinants of tobacco use in Ghana and explores the association between tobacco use and poverty in the country. Data from the 2008 Ghana Demographic and Health Survey, a nationally representative survey of households (n = 12,323), were used to generate descriptive statistics and characterize tobacco use in the country. A logistic regression model was used to evaluate the relationships between tobacco use and age, place of residence, region, education status, wealth, marital status, alcohol use, and whether the person has children. Unadjusted and adjusted odds ratios were calculated for tobacco users and nonusers on the likelihood of their purchase of selected commodities indicative of living standards. Tobacco use was significantly higher among those living in poverty stricken regions, those with less education, lower levels of wealth, parents, and alcohol users. Tobacco use was significantly higher among men (7%) than women (0.4%), and it increased to a peak age of 41.4 years before it declined. Using tobacco was also associated with a lower likelihood of purchasing health insurance. Tobacco use is inextricably related to poverty in Ghana. Policies should be formulated to target populations and regions with higher tobacco prevalence to combat both poverty and tobacco use simultaneously.

Investigation of the geology and hydrology of the Coconino Plateau of northern Arizona: a project of the Arizona Rural Watershed Initiative

USGS Publications Warehouse

Flynn, Marilyn E.; Bills, Donald J.

2002-01-01

The water resources of the Coconino Plateau in northern Arizona are under increasing demand as a result of development. The population of this arid region continues to grow, and the number of visitors to the many national and state parks and monuments in the region has increased annually. The sustainability, protection, and maintenance of springs and seeps and associated riparian habitat on the Coconino Plateau are major issues that have broad public and governmental support. Regional stakeholders agree that an improved understanding of the regional hydrogeologic system is needed to address the concerns of water supply and ground-water sustainability. The base of information required to adequately describe the hydrogeology of the Coconino Plateau currently does not exist. Hydrogeologic data is most abundant for large population centers like Flagstaff and Sedona, but is sparse for less populated areas like Williams, Tusayan, Valle, and Cameron. There are still large parts of the Coconino Plateau for which there is no basic geologic or hydrologic information available. In order to develop a hydrogeologic framework for the Coconino Plateau, a comprehensive effort is needs to compile existent data and collect additional data to fill in data gaps and reinforce limited information. In 1999, the U.S. Geological Survey (USGS) began an assessment of the hydrogeology of the Coconino Plateau in cooperation with the Arizona Department of Water Resources (ADWR) as part of the Rural Watershed Initiative, a program established by the State of Arizona and managed by the ADWR. Assessments also are underway in the upper-middle Verde River watershed (Woodhouse and others, 2002) to the south and in the Mogollon Highlands to the southeast (Parker and Flynn, 2000). Each study has as its objectives: (1) the collection, compilation, and evaluation of all existing geologic, hydrologic, and related data pertaining to the study area and the creation of a database that is readily accessible to the public and (2) the development of an understanding of the hydrogeologic framework, which is the relation between hydrologic and geologic properties, that can be used for water-resources management purposes and that will support the development of conceptual and interpretive models that can be used to evaluate the effects of climate and water use on regional water resources.

Distribution and sediment production of large benthic foraminifers on reef flats of the Majuro Atoll, Marshall Islands

NASA Astrophysics Data System (ADS)

Fujita, K.; Osawa, Y.; Kayanne, H.; Ide, Y.; Yamano, H.

2009-03-01

The distributions and population densities of large benthic foraminifers (LBFs) were investigated on reef flats of the Majuro Atoll, Marshall Islands. Annual sediment production by foraminifers was estimated based on population density data. Predominant LBFs were Calcarina and Amphistegina, and the population densities of these foraminifers varied with location and substratum type on reef flats. Both foraminifers primarily attached to macrophytes, particularly turf-forming algae, and were most abundant on an ocean reef flat (ORF) and in an inter-island channel near windward, sparsely populated islands. Calcarina density was higher on windward compared to leeward sides of ORFs, whereas Amphistegina density was similar on both sides of ORFs. These foraminifers were more common on the ocean side relative to the lagoon side of reef flats around a windward reef island, and both were rare or absent in nearshore zones around reef islands and on an ORF near windward, densely populated islands. Foraminiferal production rates varied with the degree to which habitats were subject to water motion and human influences. Highly productive sites (>103 g CaCO3 m-2 year-1) included an ORF and an inter-island channel near windward, sparsely populated islands, and a seaward area of a reef flat with no reef islands. Low-productivity sites (<10 g CaCO3 m-2 year-1) included generally nearshore zones of lagoonal reef flats, leeward ORFs, and a windward ORF near densely populated islands. These results suggest that the distribution and production of LBFs were largely influenced by a combination of natural environmental factors, including water motion, water depth, elevation relative to the lowest tidal level at spring tide, and the distribution of suitable substratum. The presence of reef islands may limit the distribution and production of foraminifers by altering water circulation in nearshore environments. Furthermore, increased anthropogenic factors (population and activities) may adversely affect foraminiferal distribution and production.

Galaxy evolution in extreme environments: Molecular gas content star formation and AGN in isolated void galaxies

NASA Astrophysics Data System (ADS)

Das, Mousumi; Iono, Daisuke; Saito, Toshiki; Subramanian, Smitha

Since the early redshift surveys of the large scale structure of our universe, it has become clear that galaxies cluster along walls, sheet and filaments leaving large, empty regions called voids between them. Although voids represent the most under dense parts of our universe, they do contain a sparse but significant population of isolated galaxies that are generally low luminosity, late type disk galaxies. Recent studies show that most void galaxies have ongoing star formation and are in an early stage of evolution. We present radio, optical studies of the molecular gas content and star formation in a sample of void galaxies. Using SDSS data, we find that AGN are rare in these systems and are found only in the Bootes void; their black hole masses and radio properties are similar to bright spirals galaxies. Our studies suggest that close galaxy interactions and gas accretion are the main drivers of galaxy evolution in these systems despite their location in the underdense environment of the voids.

First Gridded Spatial Field Reconstructions of Snow from Tree Rings

NASA Astrophysics Data System (ADS)

Coulthard, B. L.; Anchukaitis, K. J.; Pederson, G. T.; Alder, J. R.; Hostetler, S. W.; Gray, S. T.

2017-12-01

Western North America's mountain snowpacks provide critical water resources for human populations and ecosystems. Warmer temperatures and changing precipitation patterns will increasingly alter the quantity, extent, and persistence of snow in coming decades. A comprehensive understanding of the causes and range of long-term variability in this system is required for forecasting future anomalies, but snowpack observations are limited and sparse. While individual tree ring-based annual snowpack reconstructions have been developed for specific regions and mountain ranges, we present here the first collection of spatially-explicit gridded field reconstructions of seasonal snowpack within the American Rocky Mountains. Capitalizing on a new western North American snow-sensitive network of over 700 tree-ring chronologies, as well as recent advances in PRISM-based snow modeling, our gridded reconstructions offer a full space-time characterization of snow and associated water resource fluctuations over several centuries. The quality of reconstructions is evaluated against existing observations, proxy-records, and an independently-developed first-order monthly snow model.

Hubble Uncovers a Galaxy Pair Coming in from the Wilderness

NASA Image and Video Library

2017-12-08

NASA’s Hubble Space Telescope uncovered two tiny dwarf galaxies that have wandered from a vast cosmic wilderness into a nearby “big city” packed with galaxies. After being idle for billions of years, they are ready to party by starting a firestorm of star birth. Hubble captured the glow of new stars in these small, ancient galaxies, called Pisces A and Pisces B. Observations suggests the galaxies are late bloomers because they have spent most of their existence in the Local Void, a region of the universe sparsely populated with galaxies. The Local Void is roughly 150 million light-years across. Credits: NASA, ESA, and E. Tollerud (STScI) NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

A multiscale Markov random field model in wavelet domain for image segmentation

NASA Astrophysics Data System (ADS)

Dai, Peng; Cheng, Yu; Wang, Shengchun; Du, Xinyu; Wu, Dan

2017-07-01

The human vision system has abilities for feature detection, learning and selective attention with some properties of hierarchy and bidirectional connection in the form of neural population. In this paper, a multiscale Markov random field model in the wavelet domain is proposed by mimicking some image processing functions of vision system. For an input scene, our model provides its sparse representations using wavelet transforms and extracts its topological organization using MRF. In addition, the hierarchy property of vision system is simulated using a pyramid framework in our model. There are two information flows in our model, i.e., a bottom-up procedure to extract input features and a top-down procedure to provide feedback controls. The two procedures are controlled simply by two pyramidal parameters, and some Gestalt laws are also integrated implicitly. Equipped with such biological inspired properties, our model can be used to accomplish different image segmentation tasks, such as edge detection and region segmentation.

Earth Observations

NASA Image and Video Library

2010-09-20

ISS024-E-015121 (20 Sept. 2010) --- Twitchell Canyon Fire in central Utah is featured in this image photographed by an Expedition 24 crew member on the International Space Station (ISS). The Twitchell Canyon Fire near central Utah?s Fishlake National Forest is reported to have an area of approximately 13,383 hectares (approximately 134 square kilometers, or 33,071 acres). This detailed image shows smoke plumes generated by several fire spots close to the southwestern edge of the burned area. The fire was started by a lightning strike on July 20, 2010. Whereas many of the space station images of Earth are looking straight down (nadir), this photograph was exposed at an angle. The space station was located over a point approximately 509 kilometers (316 miles) to the northeast, near the Colorado/Wyoming border, at the time the image was taken on Sept. 20. Southwesterly winds were continuing to extend smoke plumes from the fire to the northeast. While the Twitchell Canyon region is sparsely populated, Interstate Highway 15 is visible at upper left.

Climate Change Amplifications of Climate-Fire Teleconnections in the Southern Hemisphere

NASA Astrophysics Data System (ADS)

Mariani, Michela; Holz, Andrés.; Veblen, Thomas T.; Williamson, Grant; Fletcher, Michael-Shawn; Bowman, David M. J. S.

2018-05-01

Recent changes in trend and variability of the main Southern Hemisphere climate modes are driven by a variety of factors, including increasing atmospheric greenhouse gases, changes in tropical sea surface temperature, and stratospheric ozone depletion and recovery. One of the most important implications for climatic change is its effect via climate teleconnections on natural ecosystems, water security, and fire variability in proximity to populated areas, thus threatening human lives and properties. Only sparse and fragmentary knowledge of relationships between teleconnections, lightning strikes, and fire is available during the observed record within the Southern Hemisphere. This constitutes a major knowledge gap for undertaking suitable management and conservation plans. Our analysis of documentary fire records from Mediterranean and temperate regions across the Southern Hemisphere reveals a critical increased strength of climate-fire teleconnections during the onset of the 21st century including a tight coupling between lightning-ignited fire occurrences, the upward trend in the Southern Annular Mode, and rising temperatures across the Southern Hemisphere.

An Accurate Mass Determination for Kepler-1655b, a Moderately Irradiated World with a Significant Volatile Envelope

NASA Astrophysics Data System (ADS)

Haywood, Raphaëlle D.; Vanderburg, Andrew; Mortier, Annelies; Giles, Helen A. C.; López-Morales, Mercedes; Lopez, Eric D.; Malavolta, Luca; Charbonneau, David; Collier Cameron, Andrew; Coughlin, Jeffrey L.; Dressing, Courtney D.; Nava, Chantanelle; Latham, David W.; Dumusque, Xavier; Lovis, Christophe; Molinari, Emilio; Pepe, Francesco; Sozzetti, Alessandro; Udry, Stéphane; Bouchy, François; Johnson, John A.; Mayor, Michel; Micela, Giusi; Phillips, David; Piotto, Giampaolo; Rice, Ken; Sasselov, Dimitar; Ségransan, Damien; Watson, Chris; Affer, Laura; Bonomo, Aldo S.; Buchhave, Lars A.; Ciardi, David R.; Fiorenzano, Aldo F.; Harutyunyan, Avet

2018-05-01

We present the confirmation of a small, moderately irradiated (F = 155 ± 7 F ⊕) Neptune with a substantial gas envelope in a P = 11.8728787 ± 0.0000085 day orbit about a quiet, Sun-like G0V star Kepler-1655. Based on our analysis of the Kepler light curve, we determined Kepler-1655b’s radius to be 2.213 ± 0.082 R ⊕. We acquired 95 high-resolution spectra with Telescopio Nazionale Galileo/HARPS-N, enabling us to characterize the host star and determine an accurate mass for Kepler-1655b of 5.0{+/- }2.83.1 {M}\\oplus via Gaussian-process regression. Our mass determination excludes an Earth-like composition with 98% confidence. Kepler-1655b falls on the upper edge of the evaporation valley, in the relatively sparsely occupied transition region between rocky and gas-rich planets. It is therefore part of a population of planets that we should actively seek to characterize further.

How can hydrological modeling help to understand process dynamics in sparsely gauged tropical regions - case study Mata Âtlantica, Brazil

NASA Astrophysics Data System (ADS)

Künne, Annika; Penedo, Santiago; Schuler, Azeneth; Bardy Prado, Rachel; Kralisch, Sven; Flügel, Wolfgang-Albert

2015-04-01

To ensure long-term water security for domestic, agricultural and industrial use in the emerging country of Brazil with fast-growing markets and technologies, understanding of catchment hydrology is essential. Yet, hydrological analysis, high resolution temporal and spatial monitoring and reliable meteo-hydrological data are insufficient to fully understand hydrological processes in the region and to predict future trends. Physically based hydrological modeling can help to expose uncertainties of measured data, predict future trends and contribute to physical understanding about the watershed. The Brazilian Atlantic rainforest (Mata Atlântica) is one of the world's biodiversity hotspots. After the Portuguese colonization, its original expansion of 1.5 million km² was reduced to only 7% of the former area. Due to forest fragmentation, overexploitation and soil degradation, pressure on water resources in the region has significantly increased. Climatically, the region possesses distinctive wet and dry periods. While extreme precipitation events in the rainy season cause floods and landslides, dry periods can lead to water shortages, especially in the agricultural and domestic supply sectors. To ensure both, the protection of the remnants of Atlantic rainforest biome as well as water supply, a hydrological understanding of this sparsely gauged region is essential. We will present hydrological models of two meso- to large-scale catchments (Rio Macacu and Rio Dois Rios) within the Mata Âtlantica in the state of Rio de Janeiro. The results show how physically based models can contribute to hydrological system understanding within the region and answer what-if scenarios, supporting regional planners and decision makers in integrated water resources management.

Simulated soil organic carbon response to tillage, yield, and climate change in the southeastern Coastal Plains

USDA-ARS?s Scientific Manuscript database

Intensive tillage, low-residue crops, and a warm, humid climate have contributed to soil organic carbon (SOC) loss in the southeastern Coastal Plains region. Conservation (CnT) tillage and winter cover cropping are current management practices to rebuild SOC; however, there is sparse long-term field...

Monthly flooded area classification using low resolution SAR imagery in the Sudd wetland from 2007-2011

USDA-ARS?s Scientific Manuscript database

The annual flood cycle of the Sudd wetland in South Sudan plays an important role in the Nile River Basin water balance. The wetland, however, is extensive and sparsely instrumented, which has inhibited credible understanding of regional flooding across space and time. Here we explore the potential ...

Replicating receptive fields of simple and complex cells in primary visual cortex in a neuronal network model with temporal and population sparseness and reliability.

PubMed

Tanaka, Takuma; Aoyagi, Toshio; Kaneko, Takeshi

2012-10-01

We propose a new principle for replicating receptive field properties of neurons in the primary visual cortex. We derive a learning rule for a feedforward network, which maintains a low firing rate for the output neurons (resulting in temporal sparseness) and allows only a small subset of the neurons in the network to fire at any given time (resulting in population sparseness). Our learning rule also sets the firing rates of the output neurons at each time step to near-maximum or near-minimum levels, resulting in neuronal reliability. The learning rule is simple enough to be written in spatially and temporally local forms. After the learning stage is performed using input image patches of natural scenes, output neurons in the model network are found to exhibit simple-cell-like receptive field properties. When the output of these simple-cell-like neurons are input to another model layer using the same learning rule, the second-layer output neurons after learning become less sensitive to the phase of gratings than the simple-cell-like input neurons. In particular, some of the second-layer output neurons become completely phase invariant, owing to the convergence of the connections from first-layer neurons with similar orientation selectivity to second-layer neurons in the model network. We examine the parameter dependencies of the receptive field properties of the model neurons after learning and discuss their biological implications. We also show that the localized learning rule is consistent with experimental results concerning neuronal plasticity and can replicate the receptive fields of simple and complex cells.

Home ranges of lions in the Kalahari, Botswana exhibit vast sizes and high temporal variability.

PubMed

Zehnder, André; Henley, Stephen; Weibel, Robert

2018-06-01

The central Kalahari region in Botswana is one of the few remaining ecosystems with a stable lion population. Yet, relatively little is known about the ecology of the lions there. As an entry point, home range estimations provide information about the space utilization of the studied animals. The home ranges of eight lions in this region were determined to investigate their spatial overlaps and spatiotemporal variations. We found that, except for MCP, all home range estimators yielded comparable results regarding size and shape. The home ranges of all individuals were located predominantly inside the protected reserves. Their areas were among the largest known for lions with 1131 - 4314km 2 (95%), with no significant differences between males and females. Numerous overlaps between lions of different sexes were detected, although these originate from different groups. A distance chart confirmed that most of these lions directly encountered each other once or several times. Strong temporal variations of the home ranges were observed that did not match a seasonal pattern. The exceptionally large home ranges are likely to be caused by the sparse and dynamic prey populations. Since the ungulates in the study area move in an opportunistic way, too, strong spatiotemporal home range variations emerge. This can lead to misleading home ranges. We therefore recommend clarifying the stability of the home ranges by applying several levels of temporal aggregation. The lack of strict territoriality is likely an adaptation to the variable prey base and the high energetic costs associated with defending a large area. Copyright © 2018 Elsevier GmbH. All rights reserved.

Observations of fibropapillomatosis in green turtles (Chelonia mydas) in Indonesia.

PubMed

Adnyana, W; Ladds, P W; Blair, D

1997-10-01

To determine the prevalence and manifestations of fibropapillomatosis in green turtles in Indonesia, to identify any relationship between fibropapillomatosis and concurrent parasitic infection, to ascertain the effect of fibropapillomatosis on health, and to examine whether environment might have an effect on the prevalence of fibropapillomatosis. 4407 green turtles (Chelonia mydas) and 401 hawksbill turtles (Eretmochelys imbricata) were examined. The occurrence of fibropapillomatosis was correlated with sex, maturity, curved carapace length, body weight/curved carapace length ratio, the number and distribution of tumours on the skin, parasite burdens, some haematological variables and the region of capture. Fibropapillomatosis was seen only in green turtles, and the overall prevalence in these was 21.5%. This prevalence increased with the curved carapace length up to 85 cm. The average number of tumours per affected turtle was 5 +/- SD 4.1 (range, 1 to 29), and was negatively correlated with the body weight/curved carapace length ratio (rs = -0.8; P = 0.001). The red blood cell count in turtles with fibropapilloma was lower than in non-fibropapilloma turtles captured and examined at the same time (P = 0.001). The prevalence of fibropapilloma in turtles captured near densely populated, industrial regions (26.3%) was greater than in turtles from sparsely populated areas (17.7%). Fibropapillomatosis in green sea turtles in Indonesia is of moderate occurrence: young mature turtles (curved carapace length = 85 cm) are most frequently affected. Fibropapilloma adversely affects health of turtles. Fluke infestation seems not to be a causal factor, but viral infection, perhaps with concurrent stress of environmental origin, seems likely.

Forest response to 1,000 years of drought variability in the Southwestern United States

NASA Astrophysics Data System (ADS)

Williams, A. P.; Meko, D. M.; Woodhouse, C. A.; Cook, E.; Swetnam, T. W.; Macalady, A. K.; Allen, C. D.; Rauscher, S. A.; Jiang, X.; Grissino-Mayer, H.; McDowell, N. G.; Cai, M.

2011-12-01

Droughts in the early 1950s and early 2000s significantly accelerated tree mortality rates in the Southwestern United States. During the early 2000s, forest inventory data indicate that the proportion of dead piñon pine, ponderosa pine, and Douglas-fir trees doubled in the Southwest. The 2000s drought peaked in 2002 and was the most severe drought in at least 100 years. In 2011, precipitation, dew-point, and wind data indicate the intensity of the 2002 drought has been surpassed in a number of ways. Measurements of water potential in piñon pine trees in northern New Mexico indicate that, at present, trees have less access to soil moisture than in 2002 when widespread mortality occurred. How do these recent droughts compare to those of the last 1000 years? We used records of annual tree-ring widths from 309 populations of piñon pine, ponderosa pine, and Douglas-fir throughout the Southwestern United States to reconstruct a single record of regional drought stress from 1000-2005 AD. This record indicates that the last Southwestern drought similar in intensity to one in the early 2000s occurred in the late 1600s. Both of these droughts, however, paled in comparison to a mega-drought that occurred from 1575-1595. The emergence from this mega-drought, around 1600 AD, appears to mark a transition period from a time when droughts similar the early 2000s drought were much more common. Tree-age studies indicate a scarcity of Southwestern trees with rings extending back beyond the mega-drought of the late 1500s. This suggests that (1) the late-1500s mega-drought triggered a massive die-off of forests and/or (2) the higher frequency of drought events prior to the mega-drought sustained a much more sparse forest population than the one that has thrived from the 1600s through present. Given this apparent plasticity of Southwestern forests, a change in the forest population should be underway if higher temperatures contribute to forest drought stress. The Southwestern tree-ring record indicates that this is the case. During the 20th century, tree-ring widths correlated very positively with total winter precipitation and very negatively with spring-summer maximum temperature. This indicates that Southwestern forest growth is significantly impacted by both the amount of water delivered before the growing season and temperature during the growing season. We conclude that in the absence of a significant increase in winter precipitation, continued warming should lead to a more sparsely populated Southwestern forest population, similar to the one that appears to have existed during 1000-1600 AD.

Treating Mental Health Disorders for Children in Child Welfare Care: Evaluating the Outcome Literature

ERIC Educational Resources Information Center

Stewart, Shannon L.; Leschied, Alan; den Dunnen, Wendy; Zalmanowitz, Sharla; Baiden, Philip

2013-01-01

Background: Children involved in the child welfare system (CWS) have a greater need for mental health treatment relative to children in the general population. However, the research on mental health treatment for children in the CWS is sparse with only one known previous review of mental health services with children in the CWS. Objective: This…

Needs for Rural Research in the Northern Finland Context

ERIC Educational Resources Information Center

Muilu, Toivo

2010-01-01

The aim of this paper is to discuss the needs and demands which rural research faces at the interface between research and development. The case study area is northern Finland, which constitutes the most remote and sparsely populated areas of the European Union. This paper is based on the tradition of rural research since the 1980s in connection…

Conserving biodiversity on Mongolian Rangelands: Implications for protected area development and pastoral uses

Treesearch

Richard P. Reading; Donald J. Bedunah; Sukhiin Amgalanbaatar

2006-01-01

Mongolia is a sparsely populated country with over 80 percent of its land used by pastoralists for extensive livestock grazing. Mongolia’s wildlife and pastoralists have faced dramatic challenges with the recent rapid socioeconomic changes. Livestock numbers increased dramatically in the 1990s following the transition from communism to democracy and capitalism. Yet,...

The Four-Day School Week. Revised.

ERIC Educational Resources Information Center

Colorado State Dept. of Education, Denver.

This paper provides an overview of the 4-day school week being utilized by 36 school districts in Colorado. These districts, which tend to be rural and sparsely populated, schedule 7.5 hours per day for 144 days of school instead of the normal 6 hours for 180 days. Colorado law requires school districts to schedule 1,080 hours per year of…

The Emergence of Probabilistic Reasoning in Very Young Infants: Evidence from 4.5- and 6-Month-Olds

ERIC Educational Resources Information Center

Denison, Stephanie; Reed, Christie; Xu, Fei

2013-01-01

How do people make rich inferences from such sparse data? Recent research has explored this inferential ability by investigating probabilistic reasoning in infancy. For example, 8- and 11-month-old infants can make inferences from samples to populations and vice versa (Denison & Xu, 2010a; Xu & Denison, 2009; Xu & Garcia, 2008a). The…

Evaluating nature and wilderness in Iceland

Treesearch

Thora Ellen Thorhallsdottir

2002-01-01

Iceland is sparsely populated with towns and farms mostly restricted to coastal lowlands. The country’s ca 50,000 km2 (19,000 mi2) interior is an uninhabited highland with isolated mountains and large glaciers. At present, only a small part of Iceland’s rich geothermal and hydroelectric resources have been harnessed, but if political commitments to largescale...

As Aussie as Vegemite: Building the Capacity of Sustainability Educators in Australia

ERIC Educational Resources Information Center

Smith, Phil; Collier, Grahame; Storey, Hazel

2011-01-01

Vegemite, a thick, rich and salty product made from yeast extract, is a paste commonly spread on bread or toast in Australian households. This iconic product mirrors some of the unique aspects of this country. For example, Vegemite thinly spread is best. The population of this country is sparse across the wide lands, and the Australian environment…

Data-assisted reduced-order modeling of extreme events in complex dynamical systems

PubMed Central

Koumoutsakos, Petros

2018-01-01

The prediction of extreme events, from avalanches and droughts to tsunamis and epidemics, depends on the formulation and analysis of relevant, complex dynamical systems. Such dynamical systems are characterized by high intrinsic dimensionality with extreme events having the form of rare transitions that are several standard deviations away from the mean. Such systems are not amenable to classical order-reduction methods through projection of the governing equations due to the large intrinsic dimensionality of the underlying attractor as well as the complexity of the transient events. Alternatively, data-driven techniques aim to quantify the dynamics of specific, critical modes by utilizing data-streams and by expanding the dimensionality of the reduced-order model using delayed coordinates. In turn, these methods have major limitations in regions of the phase space with sparse data, which is the case for extreme events. In this work, we develop a novel hybrid framework that complements an imperfect reduced order model, with data-streams that are integrated though a recurrent neural network (RNN) architecture. The reduced order model has the form of projected equations into a low-dimensional subspace that still contains important dynamical information about the system and it is expanded by a long short-term memory (LSTM) regularization. The LSTM-RNN is trained by analyzing the mismatch between the imperfect model and the data-streams, projected to the reduced-order space. The data-driven model assists the imperfect model in regions where data is available, while for locations where data is sparse the imperfect model still provides a baseline for the prediction of the system state. We assess the developed framework on two challenging prototype systems exhibiting extreme events. We show that the blended approach has improved performance compared with methods that use either data streams or the imperfect model alone. Notably the improvement is more significant in regions associated with extreme events, where data is sparse. PMID:29795631

Data-assisted reduced-order modeling of extreme events in complex dynamical systems.

PubMed

Wan, Zhong Yi; Vlachas, Pantelis; Koumoutsakos, Petros; Sapsis, Themistoklis

2018-01-01

The prediction of extreme events, from avalanches and droughts to tsunamis and epidemics, depends on the formulation and analysis of relevant, complex dynamical systems. Such dynamical systems are characterized by high intrinsic dimensionality with extreme events having the form of rare transitions that are several standard deviations away from the mean. Such systems are not amenable to classical order-reduction methods through projection of the governing equations due to the large intrinsic dimensionality of the underlying attractor as well as the complexity of the transient events. Alternatively, data-driven techniques aim to quantify the dynamics of specific, critical modes by utilizing data-streams and by expanding the dimensionality of the reduced-order model using delayed coordinates. In turn, these methods have major limitations in regions of the phase space with sparse data, which is the case for extreme events. In this work, we develop a novel hybrid framework that complements an imperfect reduced order model, with data-streams that are integrated though a recurrent neural network (RNN) architecture. The reduced order model has the form of projected equations into a low-dimensional subspace that still contains important dynamical information about the system and it is expanded by a long short-term memory (LSTM) regularization. The LSTM-RNN is trained by analyzing the mismatch between the imperfect model and the data-streams, projected to the reduced-order space. The data-driven model assists the imperfect model in regions where data is available, while for locations where data is sparse the imperfect model still provides a baseline for the prediction of the system state. We assess the developed framework on two challenging prototype systems exhibiting extreme events. We show that the blended approach has improved performance compared with methods that use either data streams or the imperfect model alone. Notably the improvement is more significant in regions associated with extreme events, where data is sparse.

The Joker: A Custom Monte Carlo Sampler for Binary-star and Exoplanet Radial Velocity Data

NASA Astrophysics Data System (ADS)

Price-Whelan, Adrian M.; Hogg, David W.; Foreman-Mackey, Daniel; Rix, Hans-Walter

2017-03-01

Given sparse or low-quality radial velocity measurements of a star, there are often many qualitatively different stellar or exoplanet companion orbit models that are consistent with the data. The consequent multimodality of the likelihood function leads to extremely challenging search, optimization, and Markov chain Monte Carlo (MCMC) posterior sampling over the orbital parameters. Here we create a custom Monte Carlo sampler for sparse or noisy radial velocity measurements of two-body systems that can produce posterior samples for orbital parameters even when the likelihood function is poorly behaved. The six standard orbital parameters for a binary system can be split into four nonlinear parameters (period, eccentricity, argument of pericenter, phase) and two linear parameters (velocity amplitude, barycenter velocity). We capitalize on this by building a sampling method in which we densely sample the prior probability density function (pdf) in the nonlinear parameters and perform rejection sampling using a likelihood function marginalized over the linear parameters. With sparse or uninformative data, the sampling obtained by this rejection sampling is generally multimodal and dense. With informative data, the sampling becomes effectively unimodal but too sparse: in these cases we follow the rejection sampling with standard MCMC. The method produces correct samplings in orbital parameters for data that include as few as three epochs. The Joker can therefore be used to produce proper samplings of multimodal pdfs, which are still informative and can be used in hierarchical (population) modeling. We give some examples that show how the posterior pdf depends sensitively on the number and time coverage of the observations and their uncertainties.

Noniterative MAP reconstruction using sparse matrix representations.

PubMed

Cao, Guangzhi; Bouman, Charles A; Webb, Kevin J

2009-09-01

We present a method for noniterative maximum a posteriori (MAP) tomographic reconstruction which is based on the use of sparse matrix representations. Our approach is to precompute and store the inverse matrix required for MAP reconstruction. This approach has generally not been used in the past because the inverse matrix is typically large and fully populated (i.e., not sparse). In order to overcome this problem, we introduce two new ideas. The first idea is a novel theory for the lossy source coding of matrix transformations which we refer to as matrix source coding. This theory is based on a distortion metric that reflects the distortions produced in the final matrix-vector product, rather than the distortions in the coded matrix itself. The resulting algorithms are shown to require orthonormal transformations of both the measurement data and the matrix rows and columns before quantization and coding. The second idea is a method for efficiently storing and computing the required orthonormal transformations, which we call a sparse-matrix transform (SMT). The SMT is a generalization of the classical FFT in that it uses butterflies to compute an orthonormal transform; but unlike an FFT, the SMT uses the butterflies in an irregular pattern, and is numerically designed to best approximate the desired transforms. We demonstrate the potential of the noniterative MAP reconstruction with examples from optical tomography. The method requires offline computation to encode the inverse transform. However, once these offline computations are completed, the noniterative MAP algorithm is shown to reduce both storage and computation by well over two orders of magnitude, as compared to a linear iterative reconstruction methods.

A multiple hold-out framework for Sparse Partial Least Squares.

PubMed

Monteiro, João M; Rao, Anil; Shawe-Taylor, John; Mourão-Miranda, Janaina

2016-09-15

Supervised classification machine learning algorithms may have limitations when studying brain diseases with heterogeneous populations, as the labels might be unreliable. More exploratory approaches, such as Sparse Partial Least Squares (SPLS), may provide insights into the brain's mechanisms by finding relationships between neuroimaging and clinical/demographic data. The identification of these relationships has the potential to improve the current understanding of disease mechanisms, refine clinical assessment tools, and stratify patients. SPLS finds multivariate associative effects in the data by computing pairs of sparse weight vectors, where each pair is used to remove its corresponding associative effect from the data by matrix deflation, before computing additional pairs. We propose a novel SPLS framework which selects the adequate number of voxels and clinical variables to describe each associative effect, and tests their reliability by fitting the model to different splits of the data. As a proof of concept, the approach was applied to find associations between grey matter probability maps and individual items of the Mini-Mental State Examination (MMSE) in a clinical sample with various degrees of dementia. The framework found two statistically significant associative effects between subsets of brain voxels and subsets of the questions/tasks. SPLS was compared with its non-sparse version (PLS). The use of projection deflation versus a classical PLS deflation was also tested in both PLS and SPLS. SPLS outperformed PLS, finding statistically significant effects and providing higher correlation values in hold-out data. Moreover, projection deflation provided better results. Copyright © 2016 The Author(s). Published by Elsevier B.V. All rights reserved.

Rapid Field Response to the 3 September 2016 M5.8 Earthquake Near Pawnee, Oklahoma: Summary of Structural Damage and Liquefaction Observations

NASA Astrophysics Data System (ADS)

Bennett, S. E. K.; Streig, A. R.; Chang, J. C.; Hornsby, K. T.; Woelfel, I. E.; Andrews, R. D.; Briggs, R. W.; McNamara, D. E.; Williams, R. A.; Wald, D. J.

2016-12-01

The Mw5.8 Pawnee, Oklahoma earthquake occurred on 03 September 2016 (07:02:44 local time; depth 5.6 km) in a rural, sparsely populated area. The USGS, Mw-phase moment tensor indicated slip occurred on a sub-vertical fault plane, striking WNW or NNE. Relocations of this mainshock and a dozen aftershocks (Mw 2.5-3.6) in the day following the event were broadly aligned along a WNW trend. These data, along with USGS `Did You Feel It?' and ShakeMap products, helped guide our field response. Our team arrived to the epicentral region 10 hours after the mainshock and spent the next 1.5 days examining 60 km of paved and dirt roads across a 40 km2 area for evidence of surface deformation, liquefaction, and structural damage. We completed a 2 km-long, NNE transect on foot centered on the epicenter, perpendicular to the suspected WNW-striking source fault. No surface rupture was observed during our reconnaissance surveys. We interviewed 10 residents within a 1-6 km radius of the epicenter, who reported up to 30 seconds of shaking. Structural damage was common and ranged from minor to moderate. Failure and collapse of masonry chimneys and exterior house facades made of stone or brick was common near the epicenter, yet a few were undamaged. At several locations, damage patterns suggest an E-W shaking direction; for example, only the western wall of a century-old unreinforced brick storage building failed, elevated fuel tanks shook E-W, and most metal straps securing a trailer home to its cinder-block foundation were sheared in an E-W direction. One earthquake-related injury was caused by chimney bricks that struck a man on the head. Strong ground motion cracked foundations and interior walls at many homes near the epicenter. Minor ground settlement and ground cracking was observed in artificial fill surrounding houses and along the crests of small earthen dams. A large barn fire was attributed to the earthquake. Landowners reported sand blows in farm fields underlain by sandy floodplain deposits 5-10 km from the epicenter. Subsequent site visits and examination of post-event WorldView-1 satellite imagery confirmed reports of fresh liquefaction, but we were unable to identify additional liquefaction features. The sparse population in the epicentral region appears to have averted widespread damage from this earthquake.

A Bayesian random effects discrete-choice model for resource selection: Population-level selection inference

USGS Publications Warehouse

Thomas, D.L.; Johnson, D.; Griffith, B.

2006-01-01

Modeling the probability of use of land units characterized by discrete and continuous measures, we present a Bayesian random-effects model to assess resource selection. This model provides simultaneous estimation of both individual- and population-level selection. Deviance information criterion (DIC), a Bayesian alternative to AIC that is sample-size specific, is used for model selection. Aerial radiolocation data from 76 adult female caribou (Rangifer tarandus) and calf pairs during 1 year on an Arctic coastal plain calving ground were used to illustrate models and assess population-level selection of landscape attributes, as well as individual heterogeneity of selection. Landscape attributes included elevation, NDVI (a measure of forage greenness), and land cover-type classification. Results from the first of a 2-stage model-selection procedure indicated that there is substantial heterogeneity among cow-calf pairs with respect to selection of the landscape attributes. In the second stage, selection of models with heterogeneity included indicated that at the population-level, NDVI and land cover class were significant attributes for selection of different landscapes by pairs on the calving ground. Population-level selection coefficients indicate that the pairs generally select landscapes with higher levels of NDVI, but the relationship is quadratic. The highest rate of selection occurs at values of NDVI less than the maximum observed. Results for land cover-class selections coefficients indicate that wet sedge, moist sedge, herbaceous tussock tundra, and shrub tussock tundra are selected at approximately the same rate, while alpine and sparsely vegetated landscapes are selected at a lower rate. Furthermore, the variability in selection by individual caribou for moist sedge and sparsely vegetated landscapes is large relative to the variability in selection of other land cover types. The example analysis illustrates that, while sometimes computationally intense, a Bayesian hierarchical discrete-choice model for resource selection can provide managers with 2 components of population-level inference: average population selection and variability of selection. Both components are necessary to make sound management decisions based on animal selection.

Health needs of the Roma population in the Czech and Slovak Republics.

PubMed

Koupilová, I; Epstein, H; Holcík, J; Hajioff, S; McKee, M

2001-11-01

In the growing literature on the human rights of Roma people in Central Europe, their relatively poor health status is often mentioned. However, little concrete information exists about the contemporary health status of the Roma in this region. We sought information on the health of the Roma in two of countries with significant Roma minorities, the Czech and Slovak Republics, by means of systematic searches for literature on the health of Roma people published in Czech or Slovak or by authors from the two countries. Published research on health of the Roma population is sparse. The topics that have received attention suggest a focus on concepts of contagion or social Darwinism, indicating a greater concern with the health needs of the majority populations with which they live. What limited evidence exists indicates that the health needs of the Roma population are considerable. With very few exceptions, the health status of Roma is worse than that of non-Roma population in both countries. The burden of communicable disease among Roma is high and diseases associated with poor hygiene seem to be particularly important. Evidence on health care suggests poor communication between Roma and health workers and low uptake of preventative care. The health needs of Roma lack visibility, not only because of the absence of research but also the absence of advocacy on their behalf. Since 1989, Czech and Slovak researchers have largely turned away from health research on particular ethnic groups. This probably reflects a growing sensitivity about stigmatising Roma, but it also makes it difficult to know how their circumstances might be improved. There is a need for further research into the health of Roma people with particular emphasis on non-communicable disease and for interventions that would improve their health.

Evaluation of a method using survey counts and tag data to estimate the number of Pacific walruses (Odobenus rosmarus divergens) using a coastal haulout in northwestern Alaska

USGS Publications Warehouse

Battaile, Brian; Jay, Chadwick V.; Udevitz, Mark S.; Fischbach, Anthony S.

2017-01-01

Increased periods of sparse sea ice over the continental shelf of the Chukchi Sea in late summer have reduced offshore haulout habitat for Pacific walruses (Odobenus rosmarus divergens) and increased opportunities for human activities in the region. Knowing how many walruses could be affected by human activities would be useful to conservation decisions. Currently, there are no adequate estimates of walrus abundance in the northeastern Chukchi Sea during summer–early autumn. Estimating abundance in autumn might be possible from coastal surveys of hauled out walruses during periods when offshore sea ice is unavailable to walruses. We evaluated methods to estimate the size of the walrus population that was using a haulout on the coast of northwestern Alaska in autumn by using aerial photography to count the number of hauled out walruses (herd size) and data from 37 tagged walruses to estimate availability (proportion of population hauled out). We used two methods to estimate availability, direct proportions of hauled out tagged walruses and smoothed proportions using local polynomial regression. Point estimates of herd size (4200–38,000 walruses) and total population size (76,000–287,000 walruses) ranged widely among days and between the two methods of estimating availability. Estimates of population size were influenced most by variation in estimates of availability. Coastal surveys might be improved most by counting walruses when the greatest numbers are hauled out, thereby reducing the influence of availability on population size estimates. The chance of collecting data during peak haulout periods would be improved by conducting multiple surveys.

Validation of spatiodemographic estimates produced through data fusion of small area census records and household microdata

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rose, Amy N.; Nagle, Nicholas N.

Techniques such as Iterative Proportional Fitting have been previously suggested as a means to generate new data with the demographic granularity of individual surveys and the spatial granularity of small area tabulations of censuses and surveys. This article explores internal and external validation approaches for synthetic, small area, household- and individual-level microdata using a case study for Bangladesh. Using data from the Bangladesh Census 2011 and the Demographic and Health Survey, we produce estimates of infant mortality rate and other household attributes for small areas using a variation of an iterative proportional fitting method called P-MEDM. We conduct an internalmore » validation to determine: whether the model accurately recreates the spatial variation of the input data, how each of the variables performed overall, and how the estimates compare to the published population totals. We conduct an external validation by comparing the estimates with indicators from the 2009 Multiple Indicator Cluster Survey (MICS) for Bangladesh to benchmark how well the estimates compared to a known dataset which was not used in the original model. The results indicate that the estimation process is viable for regions that are better represented in the microdata sample, but also revealed the possibility of strong overfitting in sparsely sampled sub-populations.« less

1H-detected MAS solid-state NMR experiments enable the simultaneous mapping of rigid and dynamic domains of membrane proteins

NASA Astrophysics Data System (ADS)

Gopinath, T.; Nelson, Sarah E. D.; Veglia, Gianluigi

2017-12-01

Magic angle spinning (MAS) solid-state NMR (ssNMR) spectroscopy is emerging as a unique method for the atomic resolution structure determination of native membrane proteins in lipid bilayers. Although 13C-detected ssNMR experiments continue to play a major role, recent technological developments have made it possible to carry out 1H-detected experiments, boosting both sensitivity and resolution. Here, we describe a new set of 1H-detected hybrid pulse sequences that combine through-bond and through-space correlation elements into single experiments, enabling the simultaneous detection of rigid and dynamic domains of membrane proteins. As proof-of-principle, we applied these new pulse sequences to the membrane protein phospholamban (PLN) reconstituted in lipid bilayers under moderate MAS conditions. The cross-polarization (CP) based elements enabled the detection of the relatively immobile residues of PLN in the transmembrane domain using through-space correlations; whereas the most dynamic region, which is in equilibrium between folded and unfolded states, was mapped by through-bond INEPT-based elements. These new 1H-detected experiments will enable one to detect not only the most populated (ground) states of biomacromolecules, but also sparsely populated high-energy (excited) states for a complete characterization of protein free energy landscapes.

Validation of spatiodemographic estimates produced through data fusion of small area census records and household microdata

DOE PAGES

Rose, Amy N.; Nagle, Nicholas N.

2016-08-01

Techniques such as Iterative Proportional Fitting have been previously suggested as a means to generate new data with the demographic granularity of individual surveys and the spatial granularity of small area tabulations of censuses and surveys. This article explores internal and external validation approaches for synthetic, small area, household- and individual-level microdata using a case study for Bangladesh. Using data from the Bangladesh Census 2011 and the Demographic and Health Survey, we produce estimates of infant mortality rate and other household attributes for small areas using a variation of an iterative proportional fitting method called P-MEDM. We conduct an internalmore » validation to determine: whether the model accurately recreates the spatial variation of the input data, how each of the variables performed overall, and how the estimates compare to the published population totals. We conduct an external validation by comparing the estimates with indicators from the 2009 Multiple Indicator Cluster Survey (MICS) for Bangladesh to benchmark how well the estimates compared to a known dataset which was not used in the original model. The results indicate that the estimation process is viable for regions that are better represented in the microdata sample, but also revealed the possibility of strong overfitting in sparsely sampled sub-populations.« less

Superluminous Spiral Galaxies

NASA Astrophysics Data System (ADS)

Ogle, Patrick M.; Lanz, Lauranne; Nader, Cyril; Helou, George

2016-02-01

We report the discovery of spiral galaxies that are as optically luminous as elliptical brightest cluster galaxies, with r-band monochromatic luminosity Lr = 8-14L* (4.3-7.5 × 1044 erg s-1). These super spiral galaxies are also giant and massive, with diameter D = 57-134 kpc and stellar mass Mstars = 0.3-3.4 × 1011M⊙. We find 53 super spirals out of a complete sample of 1616 SDSS galaxies with redshift z < 0.3 and Lr > 8L*. The closest example is found at z = 0.089. We use existing photometry to estimate their stellar masses and star formation rates (SFRs). The SDSS and Wide-field Infrared Survey Explorer colors are consistent with normal star-forming spirals on the blue sequence. However, the extreme masses and rapid SFRs of 5-65 M⊙ yr-1 place super spirals in a sparsely populated region of parameter space, above the star-forming main sequence of disk galaxies. Super spirals occupy a diverse range of environments, from isolation to cluster centers. We find four super spiral galaxy systems that are late-stage major mergers—a possible clue to their formation. We suggest that super spirals are a remnant population of unquenched, massive disk galaxies. They may eventually become massive lenticular galaxies after they are cut off from their gas supply and their disks fade.

Mapping populations at risk: improving spatial demographic data for infectious disease modeling and metric derivation

PubMed Central

2012-01-01

The use of Global Positioning Systems (GPS) and Geographical Information Systems (GIS) in disease surveys and reporting is becoming increasingly routine, enabling a better understanding of spatial epidemiology and the improvement of surveillance and control strategies. In turn, the greater availability of spatially referenced epidemiological data is driving the rapid expansion of disease mapping and spatial modeling methods, which are becoming increasingly detailed and sophisticated, with rigorous handling of uncertainties. This expansion has, however, not been matched by advancements in the development of spatial datasets of human population distribution that accompany disease maps or spatial models. Where risks are heterogeneous across population groups or space or dependent on transmission between individuals, spatial data on human population distributions and demographic structures are required to estimate infectious disease risks, burdens, and dynamics. The disease impact in terms of morbidity, mortality, and speed of spread varies substantially with demographic profiles, so that identifying the most exposed or affected populations becomes a key aspect of planning and targeting interventions. Subnational breakdowns of population counts by age and sex are routinely collected during national censuses and maintained in finer detail within microcensus data. Moreover, demographic and health surveys continue to collect representative and contemporary samples from clusters of communities in low-income countries where census data may be less detailed and not collected regularly. Together, these freely available datasets form a rich resource for quantifying and understanding the spatial variations in the sizes and distributions of those most at risk of disease in low income regions, yet at present, they remain unconnected data scattered across national statistical offices and websites. In this paper we discuss the deficiencies of existing spatial population datasets and their limitations on epidemiological analyses. We review sources of detailed, contemporary, freely available and relevant spatial demographic data focusing on low income regions where such data are often sparse and highlight the value of incorporating these through a set of examples of their application in disease studies. Moreover, the importance of acknowledging, measuring, and accounting for uncertainty in spatial demographic datasets is outlined. Finally, a strategy for building an open-access database of spatial demographic data that is tailored to epidemiological applications is put forward. PMID:22591595

Hybrid sparse blind deconvolution: an implementation of SOOT algorithm to real data

NASA Astrophysics Data System (ADS)

Pakmanesh, Parvaneh; Goudarzi, Alireza; Kourki, Meisam

2018-06-01

Getting information of seismic data depends on deconvolution as an important processing step; it provides the reflectivity series by signal compression. This compression can be obtained by removing the wavelet effects on the traces. The recently blind deconvolution has provided reliable performance for sparse signal recovery. In this study, two deconvolution methods have been implemented to the seismic data; the convolution of these methods provides a robust spiking deconvolution approach. This hybrid deconvolution is applied using the sparse deconvolution (MM algorithm) and the Smoothed-One-Over-Two algorithm (SOOT) in a chain. The MM algorithm is based on the minimization of the cost function defined by standards l1 and l2. After applying the two algorithms to the seismic data, the SOOT algorithm provided well-compressed data with a higher resolution than the MM algorithm. The SOOT algorithm requires initial values to be applied for real data, such as the wavelet coefficients and reflectivity series that can be achieved through the MM algorithm. The computational cost of the hybrid method is high, and it is necessary to be implemented on post-stack or pre-stack seismic data of complex structure regions.

Change detection in Arctic satellite imagery using clustering of sparse approximations (CoSA) over learned feature dictionaries

NASA Astrophysics Data System (ADS)

Moody, Daniela I.; Wilson, Cathy J.; Rowland, Joel C.; Altmann, Garrett L.

2015-06-01

Advanced pattern recognition and computer vision algorithms are of great interest for landscape characterization, change detection, and change monitoring in satellite imagery, in support of global climate change science and modeling. We present results from an ongoing effort to extend neuroscience-inspired models for feature extraction to the environmental sciences, and we demonstrate our work using Worldview-2 multispectral satellite imagery. We use a Hebbian learning rule to derive multispectral, multiresolution dictionaries directly from regional satellite normalized band difference index data. These feature dictionaries are used to build sparse scene representations, from which we automatically generate land cover labels via our CoSA algorithm: Clustering of Sparse Approximations. These data adaptive feature dictionaries use joint spectral and spatial textural characteristics to help separate geologic, vegetative, and hydrologic features. Land cover labels are estimated in example Worldview-2 satellite images of Barrow, Alaska, taken at two different times, and are used to detect and discuss seasonal surface changes. Our results suggest that an approach that learns from both spectral and spatial features is promising for practical pattern recognition problems in high resolution satellite imagery.

Computational efficiency improvements for image colorization

NASA Astrophysics Data System (ADS)

Yu, Chao; Sharma, Gaurav; Aly, Hussein

2013-03-01

We propose an efficient algorithm for colorization of greyscale images. As in prior work, colorization is posed as an optimization problem: a user specifies the color for a few scribbles drawn on the greyscale image and the color image is obtained by propagating color information from the scribbles to surrounding regions, while maximizing the local smoothness of colors. In this formulation, colorization is obtained by solving a large sparse linear system, which normally requires substantial computation and memory resources. Our algorithm improves the computational performance through three innovations over prior colorization implementations. First, the linear system is solved iteratively without explicitly constructing the sparse matrix, which significantly reduces the required memory. Second, we formulate each iteration in terms of integral images obtained by dynamic programming, reducing repetitive computation. Third, we use a coarseto- fine framework, where a lower resolution subsampled image is first colorized and this low resolution color image is upsampled to initialize the colorization process for the fine level. The improvements we develop provide significant speedup and memory savings compared to the conventional approach of solving the linear system directly using off-the-shelf sparse solvers, and allow us to colorize images with typical sizes encountered in realistic applications on typical commodity computing platforms.

Optogenetic stimulation of a hippocampal engram activates fear memory recall.

PubMed

Liu, Xu; Ramirez, Steve; Pang, Petti T; Puryear, Corey B; Govindarajan, Arvind; Deisseroth, Karl; Tonegawa, Susumu

2012-03-22

A specific memory is thought to be encoded by a sparse population of neurons. These neurons can be tagged during learning for subsequent identification and manipulation. Moreover, their ablation or inactivation results in reduced memory expression, suggesting their necessity in mnemonic processes. However, the question of sufficiency remains: it is unclear whether it is possible to elicit the behavioural output of a specific memory by directly activating a population of neurons that was active during learning. Here we show in mice that optogenetic reactivation of hippocampal neurons activated during fear conditioning is sufficient to induce freezing behaviour. We labelled a population of hippocampal dentate gyrus neurons activated during fear learning with channelrhodopsin-2 (ChR2) and later optically reactivated these neurons in a different context. The mice showed increased freezing only upon light stimulation, indicating light-induced fear memory recall. This freezing was not detected in non-fear-conditioned mice expressing ChR2 in a similar proportion of cells, nor in fear-conditioned mice with cells labelled by enhanced yellow fluorescent protein instead of ChR2. Finally, activation of cells labelled in a context not associated with fear did not evoke freezing in mice that were previously fear conditioned in a different context, suggesting that light-induced fear memory recall is context specific. Together, our findings indicate that activating a sparse but specific ensemble of hippocampal neurons that contribute to a memory engram is sufficient for the recall of that memory. Moreover, our experimental approach offers a general method of mapping cellular populations bearing memory engrams.

Optogenetic stimulation of a hippocampal engram activates fear memory recall

PubMed Central

Liu, Xu; Ramirez, Steve; Pang, Petti T.; Puryear, Corey B.; Govindarajan, Arvind; Deisseroth, Karl; Tonegawa, Susumu

2012-01-01

A specific memory is thought to be encoded by a sparse population of neurons1,2. These neurons can be tagged during learning for subsequent identification3 and manipulation4,5,6. Moreover, their ablation or inactivation results in reduced memory expression, suggesting their necessity in mnemonic processes. However, a critical question of sufficiency remains: can one elicit the behavioral output of a specific memory by directly activating a population of neurons that was active during learning? Here we show that optogenetic reactivation of hippocampal neurons activated during fear conditioning is sufficient to induce freezing behavior. We labeled a population of hippocampal dentate gyrus neurons activated during fear learning with channelrhodopsin-2 (ChR2)7,8 and later optically reactivated these neurons in a different context. The mice showed increased freezing only upon light stimulation, indicating light-induced fear memory recall. This freezing was not detected in non-fear conditioned mice expressing ChR2 in a similar proportion of cells, nor in fear conditioned mice with cells labeled by EYFP instead of ChR2. Finally, activation of cells labeled in a context not associated with fear did not evoke freezing in mice that were previously fear conditioned in a different context, suggesting that light-induced fear memory recall is context-specific. Together, our findings indicate that activating a sparse but specific ensemble of hippocampal neurons that contribute to a memory engram is sufficient for the recall of that memory. Moreover, our experimental approach offers a general method of mapping cellular populations bearing memory engrams. PMID:22441246

Vegetation dynamics and responses to climate change and human activities in Central Asia.

PubMed

Jiang, Liangliang; Guli Jiapaer; Bao, Anming; Guo, Hao; Ndayisaba, Felix

2017-12-01

Knowledge of the current changes and dynamics of different types of vegetation in relation to climatic changes and anthropogenic activities is critical for developing adaptation strategies to address the challenges posed by climate change and human activities for ecosystems. Based on a regression analysis and the Hurst exponent index method, this research investigated the spatial and temporal characteristics and relationships between vegetation greenness and climatic factors in Central Asia using the Normalized Difference Vegetation Index (NDVI) and gridded high-resolution station (land) data for the period 1984-2013. Further analysis distinguished between the effects of climatic change and those of human activities on vegetation dynamics by means of a residual analysis trend method. The results show that vegetation pixels significantly decreased for shrubs and sparse vegetation compared with those for the other vegetation types and that the degradation of sparse vegetation was more serious in the Karakum and Kyzylkum Deserts, the Ustyurt Plateau and the wetland delta of the Large Aral Sea than in other regions. The Hurst exponent results indicated that forests are more sustainable than grasslands, shrubs and sparse vegetation. Precipitation is the main factor affecting vegetation growth in the Kazakhskiy Melkosopochnik. Moreover, temperature is a controlling factor that influences the seasonal variation of vegetation greenness in the mountains and the Aral Sea basin. Drought is the main factor affecting vegetation degradation as a result of both increased temperature and decreased precipitation in the Kyzylkum Desert and the northern Ustyurt Plateau. The residual analysis highlighted that sparse vegetation and the degradation of some shrubs in the southern part of the Karakum Desert, the southern Ustyurt Plateau and the wetland delta of the Large Aral Sea were mainly triggered by human activities: the excessive exploitation of water resources in the upstream areas of the Amu Darya basin and oil and natural gas extraction in the southern part of the Karakum Desert and the southern Ustyurt Plateau. The results also indicated that after the collapse of the Soviet Union, abandoned pastures gave rise to increased vegetation in eastern Kazakhstan, Kyrgyzstan and Tajikistan, and abandoned croplands reverted to grasslands in northern Kazakhstan, leading to a decrease in cropland greenness. Shrubs and sparse vegetation were extremely sensitive to short-term climatic variations, and our results demonstrated that these vegetation types were the most seriously degraded by human activities. Therefore, regional governments should strive to restore vegetation to sustain this fragile arid ecological environment. Copyright © 2017 Elsevier B.V. All rights reserved.

Microseismic Monitoring Using Sparse Surface Network of Broadband Instruments: Western Canada Shale Play Case Study

NASA Astrophysics Data System (ADS)

Yenier, E.; Baturan, D.; Karimi, S.

2016-12-01

Monitoring of seismicity related to oil and gas operations is routinely performed nowadays using a number of different surface and downhole seismic array configurations and technologies. Here, we provide a hydraulic fracture (HF) monitoring case study that compares the data set generated by a sparse local surface network of broadband seismometers to a data set generated by a single downhole geophone string. Our data was collected during a 5-day single-well HF operation, by a temporary surface network consisting of 10 stations deployed within 5 km of the production well. The downhole data was recorded by a 20 geophone string deployed in an observation well located 15 m from the production well. Surface network data processing included standard STA/LTA event triggering enhanced by template-matching subspace detection, grid search locations which was improved using the double-differencing re-location technique, as well as Richter (ML) and moment (Mw) magnitude computations for all detected events. In addition, moment tensors were computed from first motion polarities and amplitudes for the subset of highest SNR events. The resulting surface event catalog shows a very weak spatio-temporal correlation to HF operations with only 43% of recorded seismicity occurring during HF stages times. This along with source mechanisms shows that the surface-recorded seismicity delineates the activation of several pre-existing structures striking NNE-SSW and consistent with regional stress conditions as indicated by the orientation of SHmax. Comparison of the sparse-surface and single downhole string datasets allows us to perform a cost-benefit analysis of the two monitoring methods. Our findings show that although the downhole array recorded ten times as many events, the surface network provides a more coherent delineation of the underlying structure and more accurate magnitudes for larger magnitude events. We attribute this to the enhanced focal coverage provided by the surface network and the use of broadband instrumentation. The results indicate that sparse surface networks of high quality instruments can provide rich and reliable datasets for evaluation of the impact and effectiveness of hydraulic fracture operations in regions with favorable surface noise, local stress and attenuation characteristics.

Design of Environmental Flows Below Diversion Hydropower Dams: Is There Benefit to Advanced Streamflow Prediction in Sparse Data Landscapes?

NASA Astrophysics Data System (ADS)

Kibler, K. M.; Alipour, M.

2017-12-01

Diversion hydropower has been shown to significantly alter river flow regimes by dewatering diversion bypass reaches. Data scarcity is one of the foremost challenges to establishing environmental flow regimes below diversion hydropower dams, especially in regions of sparse hydro-meteorological observation. Herein, we test two prediction strategies for generating daily flows in rivers developed with diversion hydropower: a catchment similarity model, and a rainfall-runoff model selected by multi-objective optimization based on soft data. While both methods are designed for ungauged rivers embedded within large regions of sparse hydrologic observation, one is more complex and computationally-intensive. The objective of this study is to assess the benefit of using complex modeling tools in data-sparse landscapes to support design of environmental flow regimes. Models were tested in gauged catchments and then used to simulate a 28-year record of daily flows in 32 ungauged rivers. After perturbing flows with the hydropower diversion, we detect alteration using Indicators of Hydrologic Alteration (IHA) metrics and compare outcomes of the two modeling approaches. The catchment similarity model simulates low flows well (Nash-Sutcliff efficiency (NSE) = 0.91), but poorly represents moderate to high flows (overall NSE = 0.25). The multi-objective rainfall-runoff model performs well overall (NSE = 0.72). Both models agree that flow magnitudes and variability consistently decrease following diversion as temporally-dynamic flows are replaced by static minimal flows. Mean duration of events sustained below the pre-diversion Q75 and mean hydrograph rise and fall rates increase. While we see broad areas of agreement, significant effects and thresholds vary between models, particularly in the representation of moderate flows. Thus, use of simplified streamflow models may bias detected alterations or inadequately characterize pre-regulation flow regimes, providing inaccurate information as a basis for flow regime design. As an alternative, the multi-objective framework can be applied globally, and is robust to common challenges of flow prediction in ungauged rivers, such as equifinality and hydrologic dissimilarity of reference catchments.

Suicide by people in a community justice pathway: population-based nested case–control study

PubMed Central

King, Carlene; Senior, Jane; Webb, Roger T.; Millar, Tim; Piper, Mary; Pearsall, Alison; Humber, Naomi; Appleby, Louis; Shaw, Jenny

2015-01-01

The elevated risk of suicide in prison and after release is a well-recognised and serious problem. Despite this, evidence concerning community-based offenders' suicide risk is sparse. We conducted a population-based nested case–control study of all people in a community justice pathway in England and Wales. Our data show 13% of general population suicides were in community justice pathways before death. Suicide risks were highest among individuals receiving police cautions, and those having recent, or impending prosecution for sexual offences. Findings have implications for the training and practice of clinicians identifying and assessing suicidality, and offering support to those at elevated risk. PMID:26159602

Tackling Contentious Invasive Plant Species: A Case Study of Buffel Grass in Australia

NASA Astrophysics Data System (ADS)

Grice, Anthony C.; Friedel, Margaret H.; Marshall, Nadine A.; van Klinken, Rieks D.

2012-02-01

Introduced plants that have both production values and negative impacts can be contentious. Generally they are either treated as weeds and their use prohibited; or unfettered exploitation is permitted and land managers must individually contend with any negative effects. Buffel grass ( Cenchrus ciliaris) is contentious in Australia and there has been no attempt to broadly and systematically address the issues surrounding it. However, recent research indicates that there is some mutual acceptance by proponents and opponents of each others' perspectives and we contend that this provides the basis for a national approach. It would require thorough and on-going consultation with stakeholders and development of realistic goals that are applicable across a range of scales and responsive to regional differences in costs, benefits and socio-economic and biophysical circumstances. It would be necessary to clearly allocate responsibilities and ascertain the most appropriate balance between legislative and non-legislative mechanisms. A national approach could involve avoiding the introduction of additional genetic material, countering proliferation in regions where the species is sparse, preventing incursion into conservation reserves where it is absent, containing strategically located populations and managing communities to prevent or reduce dominance by buffel grass. This approach could be applied to other contentious plant species.

Genome-Wide Methylome Analyses Reveal Novel Epigenetic Regulation Patterns in Schizophrenia and Bipolar Disorder

PubMed Central

Li, Yongsheng; Camarillo, Cynthia; Xu, Juan; Arana, Tania Bedard; Xiao, Yun; Zhao, Zheng; Chen, Hong; Ramirez, Mercedes; Zavala, Juan; Escamilla, Michael A.; Armas, Regina; Mendoza, Ricardo; Ontiveros, Alfonso; Nicolini, Humberto; Jerez Magaña, Alvaro Antonio; Rubin, Lewis P.; Li, Xia; Xu, Chun

2015-01-01

Schizophrenia (SZ) and bipolar disorder (BP) are complex genetic disorders. Their appearance is also likely informed by as yet only partially described epigenetic contributions. Using a sequencing-based method for genome-wide analysis, we quantitatively compared the blood DNA methylation landscapes in SZ and BP subjects to control, both in an understudied population, Hispanics along the US-Mexico border. Remarkably, we identified thousands of differentially methylated regions for SZ and BP preferentially located in promoters 3′-UTRs and 5′-UTRs of genes. Distinct patterns of aberrant methylation of promoter sequences were located surrounding transcription start sites. In these instances, aberrant methylation occurred in CpG islands (CGIs) as well as in flanking regions as well as in CGI sparse promoters. Pathway analysis of genes displaying these distinct aberrant promoter methylation patterns showed enhancement of epigenetic changes in numerous genes previously related to psychiatric disorders and neurodevelopment. Integration of gene expression data further suggests that in SZ aberrant promoter methylation is significantly associated with altered gene transcription. In particular, we found significant associations between (1) promoter CGIs hypermethylation with gene repression and (2) CGI 3′-shore hypomethylation with increased gene expression. Finally, we constructed a specific methylation analysis platform that facilitates viewing and comparing aberrant genome methylation in human neuropsychiatric disorders. PMID:25734057

Snow as a habitat for microorganisms

NASA Technical Reports Server (NTRS)

Hoham, Ronald W.

1989-01-01

There are three major habitats involving ice and snow, and the microorganisms studied from these habitats are most eukaryotic. Sea ice is inhabited by algae called diatoms, glacial ice has sparse populations of green algai cal desmids, and the temporary and permanent snows in mountainous regions and high latitudes are inhabited mostly by green algal flagellates. The life cycle of green algal flagellates is summarized by discussing the effects of light, temperature, nutrients, and snow melts. Specific examples of optimal conditions and environmental effects for various snow algae are given. It is not likely that the eukaryotic snow algae presented are candidated for life on the planet Mars. Evolutionally, eukaryotic cells as know on Earth may not have had the opportunity to develop on Mars (if life evolved at all on Mars) since eukaryotes did not appear on Earth until almost two billion years after the first prokaryotic organisms. However, the snow/ice ecosystems on Earth present themselves as extreme habitats were there is evidence of prokaryotic life (eubacteria and cyanbacteria) of which literally nothing is known. Any future surveillances of extant and/or extinct life on Mars should include probes (if not landing sites) to investigate sites of concentrations of ice water. The possibility of signs of life in Martian polar regions should not be overlooked.

First evidence of bryophyte diaspores in the plumage of transequatorial migrant birds

PubMed Central

Behling, Emily; Gousse, Hannah; Qian, Emily; Elphick, Chris S.; Lamarre, Jean-François; Bêty, Joël; Liebezeit, Joe; Rozzi, Ricardo; Goffinet, Bernard

2014-01-01

Correlations between transequatorial migratory bird routes and bipolar biogeographic disjunctions in bryophytes suggest that disjunctions between northern and southern high latitude regions may result from bird-mediated dispersal; supporting evidence is, however, exclusively circumstantial. Birds disperse plant units (diaspores) internally via ingestion (endozoochory) or externally by the attachment of diaspores to the body (ectozoochory). Endozoochory is known to be the primary means of bird-mediated dispersal for seeds and invertebrates at local, regional, and continental scales. Data supporting the role of bird-mediated endozoochory or ectozoochory in the long distance dispersal of bryophytes remain sparse, however, despite the large number of bryophytes displaying bipolar disjunctions. To determine if transequatorial migrant shorebirds may play a role in the ectozoochory of bryophyte diaspores, we developed a method for screening feathers of wild birds. We provide the first evidence of microscopic bryophyte diaspores, as well as those from non-bryophyte lineages, embedded in the plumage of long distance transequatorial migrant birds captured in their arctic breeding grounds. The number of diaspores recovered suggests that entire migratory populations may be departing their northern breeding grounds laden with potentially viable plant parts and that they could thereby play significant roles in bipolar range expansions of lineages previously ignored in the migrant bird dispersal literature. PMID:24949241

The health status of street children and youth in low- and middle-income countries: a systematic review of the literature.

PubMed

Woan, Jessica; Lin, Jessica; Auerswald, Colette

2013-09-01

The health of the tens of millions of street children globally is understudied. We undertook a systematic review of the existing quantitative literature regarding the health status of street children and youth in low- and middle-income countries to summarize available knowledge, identify underexplored areas of research, and inform the future research agenda regarding the health of this population. A total of 108 articles met our inclusion criteria. Demographic data and structural factors associated with street life are summarized. Although data in specific regions or diseases are sparse, the literature review illustrates that youth's survival behaviors and the exposures associated with poor shelter have resulted in disproportionate morbidity in the areas of infectious illness, psychiatric disease, reproductive health, and perhaps to a lesser extent, growth. Vast areas of health that may disproportionately affect street children in childhood or later on as adults have not been investigated, including chronic diseases and cognitive deficits. Studies of specific diseases or conditions vary considerably by region. Strengths and limitations of the literature are discussed and principles for future research in this area are proposed. Copyright © 2013 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Hurricane frequency and landfall distribution for coastal wetlands of the Gulf coast, USA

USGS Publications Warehouse

Doyle, T.W.

2009-01-01

The regularity and severity of tropical storms are major determinants controlling ecosystem structure and succession for coastal ecosystems. Hurricane landfall rates vary greatly with high and low frequency for given coastal stretches of the southeastern United States. Site-specific meteorological data of hurricane wind speeds and direction, however, are only available for select populated cities of relatively sparse distribution and inland from the coast. A spatial simulation model of hurricane circulation, HURASIM, was applied to reconstruct chronologies of hurricane wind speeds and vectors for northern Gulf coast locations derived from historical tracking data of North Atlantic tropical storms dating back to 1851. Contrasts of storm frequencies showed that tropical storm incidence is nearly double for Florida coastal ecosystems than the westernmost stretches of Texas coastline. Finer-scale spatial simulations for the north-central Gulf coast exhibited sub-regional differences in storm strength and frequency with coastal position and latitude. The overall pattern of storm incidence in the Gulf basin indicates that the disturbance regime of coastal areas varies greatly along the coast, inland from the coast, and temporally over the period of record. Field and modeling studies of coastal ecosystems will benefit from this retrospective analysis of hurricane incidence and intensity both on a local or regional basis. ?? 2009 The Society of Wetland Scientists.

Behemoth Black Hole Found in an Unlikely Place

NASA Image and Video Library

2016-04-06

This computer-simulated image shows a supermassive black hole at the core of a galaxy. The black region in the center represents the black hole’s event horizon, where no light can escape the massive object’s gravitational grip. The black hole’s powerful gravity distorts space around it like a funhouse mirror. Light from background stars is stretched and smeared as the stars skim by the black hole. Credits: NASA, ESA, and D. Coe, J. Anderson, and R. van der Marel (STScI) More info: Astronomers have uncovered a near-record breaking supermassive black hole, weighing 17 billion suns, in an unlikely place: in the center of a galaxy in a sparsely populated area of the universe. The observations, made by NASA’s Hubble Space Telescope and the Gemini Telescope in Hawaii, may indicate that these monster objects may be more common than once thought. Until now, the biggest supermassive black holes – those roughly 10 billion times the mass of our sun – have been found at the cores of very large galaxies in regions of the universe packed with other large galaxies. In fact, the current record holder tips the scale at 21 billion suns and resides in the crowded Coma galaxy cluster that consists of over 1,000 galaxies.

Longitudinal Prediction of Divorce in Russia: The Role of Individual and Couple Drinking Patterns

PubMed Central

Keenan, Katherine; Kenward, Michael G.; Grundy, Emily; Leon, David A.

2013-01-01

Aims: The aim of the study was to explore associations between dimensions of alcohol use in married couples and subsequent divorce in Russia using longitudinal data. Methods: Follow-up data on 7157 married couples were extracted from 14 consecutive annual rounds (1994–2010) of the Russian Longitudinal Monitoring Survey, a national population-based panel study. Discrete-time hazard models were fitted to estimate the probability of divorce among married couples by drinking patterns reported in the previous survey wave. Results: In adjusted models, increased odds of divorce were associated with greater frequency of husband and wife drinking (test for trend P = 0.005, and P = 0.05, respectively), wife's binge drinking (P = 0.05) and husband's heavy vodka drinking (P = 0.005). Couples in whom the wife drank more frequently than the husband were more likely to divorce (OR 2.86, 95% CI 1.52–5.36), compared with other combinations of drinking. The association between drinking and divorce was stronger in regions outside Moscow or St. Petersburg. Conclusion: This study adds to the sparse literature on the topic and suggests that in Russia heavy and frequent drinking of both husbands and wives put couples at greater risk of future divorce, with some variation by region and aspect of alcohol use. PMID:23851365

Longitudinal prediction of divorce in Russia: the role of individual and couple drinking patterns.

PubMed

Keenan, Katherine; Kenward, Michael G; Grundy, Emily; Leon, David A

2013-01-01

The aim of the study was to explore associations between dimensions of alcohol use in married couples and subsequent divorce in Russia using longitudinal data. Follow-up data on 7157 married couples were extracted from 14 consecutive annual rounds (1994-2010) of the Russian Longitudinal Monitoring Survey, a national population-based panel study. Discrete-time hazard models were fitted to estimate the probability of divorce among married couples by drinking patterns reported in the previous survey wave. In adjusted models, increased odds of divorce were associated with greater frequency of husband and wife drinking (test for trend P = 0.005, and P = 0.05, respectively), wife's binge drinking (P = 0.05) and husband's heavy vodka drinking (P = 0.005). Couples in whom the wife drank more frequently than the husband were more likely to divorce (OR 2.86, 95% CI 1.52-5.36), compared with other combinations of drinking. The association between drinking and divorce was stronger in regions outside Moscow or St. Petersburg. This study adds to the sparse literature on the topic and suggests that in Russia heavy and frequent drinking of both husbands and wives put couples at greater risk of future divorce, with some variation by region and aspect of alcohol use.

Epiphytic macrolichen indication of air quality and climate in interior forested mountains of the Pacific Northwest, USA

Treesearch

Heather T. Root; Linda H. Geiser; Sarah Jovan; Peter Neitlich

2015-01-01

Biomonitoring can provide cost-effective and practical information about the distribution of nitrogen(N) deposition, particularly in regions with complex topography and sparse instrumented monitoring sites. Because of their unique biology, lichens are very sensitive bioindicators of air quality. Lichens lack acuticle to control absorption or leaching of nutrients and...

Regional Differences as Barriers to Body Mass Index Screening Described by Ohio School Nurses

ERIC Educational Resources Information Center

Stalter, Ann M.; Chaudry, Rosemary V.; Polivka, Barbara J.

2011-01-01

Background: Body mass index (BMI) screening is advocated by the National Association of School Nurses (NASN). Research identifying barriers to BMI screening in public elementary school settings has been sparse. The purpose of the study was to identify barriers and facilitating factors of BMI screening practices among Ohio school nurses working in…

The magic of fairy circles: Built or created?

NASA Astrophysics Data System (ADS)

Sahagian, Dork

2017-05-01

Fairy circles are rings of relatively dense grass in arid regions with sparse vegetation. The most famous examples are found in the Namib Desert. There has been an ongoing debate regarding the origin of these features, and a recent paper by Ravi et al. (2017, doi:10.1002/2016JG003604) sheds some light on this situation.

Bridging the gap between strategic and management forest inventories

Treesearch

Ronald E. McRoberts

2009-01-01

Strategic forest inventory programs collect information for a large number of variables on a relatively sparse array of field plots. Data from these inventories are used to produce estimates for large areas such as states and provinces, regions, or countries. The purpose of management forest inventories is to guide management decisions for small areas such as stands....

Social insects dominate eastern US temperate hardwood forest macroinvertebrate communiteis in warmer regions

Treesearch

Joshua R. King; Robert J. Warren; Mark A. Bradford

2013-01-01

Earthworms, termites, and ants are common macroinvertebrates in terrestrial environments, although for most ecosystems data on their abundance and biomass is sparse. Quantifying their areal abundance is a critical first step in understanding their functional importance. We intensively sampled dead wood, litter, and soil in eastern US temperate hardwood forests at four...

Racial and geographic issues in gastroesophageal reflux disease.

PubMed

Sharma, Prateek; Wani, Sachin; Romero, Yvonne; Johnson, David; Hamilton, Frank

2008-11-01

Gastroesophageal reflux disease (GERD) is a common chronic disorder that is associated with a huge economic burden in the western countries and significantly decreased quality of life. This review focuses on the various multicultural issues in the epidemiology, pathophysiology, diagnosis, and treatment of GERD. The prevalence of GERD appears to be highest in North America and Europe, whereas epidemiologic data from the Indian subcontinent, Africa, South America, and the Middle East are sparse. A limited number of studies have elucidated ethnic differences in GERD in multiracial populations. African Americans and Asians appear to be at a lower risk for the development of complicated GERD including Barrett's esophagus (BE). Whether the pathophysiology of GERD differs among different populations remains to be answered satisfactorily. It appears that most of the factors involved in the pathogenesis of GERD, as described in western populations, are present in Asians but at a lower scale. The current recommendations for the management of GERD by the American College of Gastroenterology may not meet the need for different ethnic groups or for different geographic regions. Recognition of language barriers in understanding the common terms used to describe reflux symptoms should be borne in mind while treating GERD patients with different ethnic backgrounds. In addition, a universally accepted definition for treatment success in GERD patients is lacking. Given the negative impact on health-related quality of life, significant cost ramifications, and increased risk for BE and esophageal adenocarcinoma, the study of multicultural issues in GERD should be considered.

Regional trend analysis of surface ozone observations from monitoring networks in eastern North America, Europe and East Asia

NASA Astrophysics Data System (ADS)

Chang, K. L.; Petropavlovskikh, I. V.; Cooper, O. R.; Schultz, M.; Wang, T.

2017-12-01

Surface ozone is a greenhouse gas and pollutant detrimental to human health and crop and ecosystem productivity. The Tropospheric Ozone Assessment Report (TOAR) is designed to provide the research community with an up-to-date observation-based overview of tropospheric ozone's global distribution and trends. The TOAR Surface Ozone Database contains ozone metrics at thousands of monitoring sites around the world, densely clustered across mid-latitude North America, western Europe and East Asia. Calculating regional ozone trends across these locations is challenging due to the uneven spacing of the monitoring sites across urban and rural areas. To meet this challenge we conducted a spatial and temporal trend analysis of several TOAR ozone metrics across these three regions for summertime (April-September) 2000-2014, using the generalized additive mixed model (GAMM). Our analysis indicates that East Asia has the greatest human and plant exposure to ozone pollution among investigating regions, with increasing ozone levels through 2014. The results also show that ozone mixing ratios continue to decline significantly over eastern North America and Europe, however, there is less evidence for decreases of daytime average ozone at urban sites. The present-day spatial coverage of ozone monitors in East Asia (South Korea and Japan) and eastern North America is adequate for estimating regional trends by simply taking the average of the individual trends at each site. However the European network is more sparsely populated across its northern and eastern regions and therefore a simple average of the individual trends at each site does not yield an accurate regional trend. This analysis demonstrates that the GAMM technique can be used to assess the regional representativeness of existing monitoring networks, indicating those networks for which a regional trend can be obtained by simply averaging the trends of all individual sites and those networks that require a more sophisticated statistical approach.

Source Characterization of Underground Explosions from Combined Regional Moment Tensor and First-Motion Analysis

DOE PAGES

Chiang, Andrea; Dreger, Douglas S.; Ford, Sean R.; ...

2014-07-08

Here in this study, we investigate the 14 September 1988 U.S.–Soviet Joint Verification Experiment nuclear test at the Semipalatinsk test site in eastern Kazakhstan and two nuclear explosions conducted less than 10 years later at the Chinese Lop Nor test site. These events were very sparsely recorded by stations located within 1600 km, and in each case only three or four stations were available in the regional distance range. We have utilized a regional distance seismic waveform method fitting long-period, complete, three-component waveforms jointly with first-motion observations from regional stations and teleseismic arrays. The combination of long-period waveforms and first-motionmore » observations provides a unique discrimination of these sparsely recorded events in the context of the Hudson et al. (1989) source-type diagram. We demonstrate through a series of jackknife tests and sensitivity analyses that the source type of the explosions is well constrained. One event, a 1996 Lop Nor shaft explosion, displays large Love waves and possibly reversed Rayleigh waves at one station, indicative of a large F-factor. We show the combination of long-period waveforms and P-wave first motions are able to discriminate this event as explosion-like and distinct from earthquakes and collapses. We further demonstrate the behavior of network sensitivity solutions for models of tectonic release and spall-based tensile damage over a range of F-factors and K-factors.« less

Source Characterization of Underground Explosions from Combined Regional Moment Tensor and First-Motion Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chiang, Andrea; Dreger, Douglas S.; Ford, Sean R.

Here in this study, we investigate the 14 September 1988 U.S.–Soviet Joint Verification Experiment nuclear test at the Semipalatinsk test site in eastern Kazakhstan and two nuclear explosions conducted less than 10 years later at the Chinese Lop Nor test site. These events were very sparsely recorded by stations located within 1600 km, and in each case only three or four stations were available in the regional distance range. We have utilized a regional distance seismic waveform method fitting long-period, complete, three-component waveforms jointly with first-motion observations from regional stations and teleseismic arrays. The combination of long-period waveforms and first-motionmore » observations provides a unique discrimination of these sparsely recorded events in the context of the Hudson et al. (1989) source-type diagram. We demonstrate through a series of jackknife tests and sensitivity analyses that the source type of the explosions is well constrained. One event, a 1996 Lop Nor shaft explosion, displays large Love waves and possibly reversed Rayleigh waves at one station, indicative of a large F-factor. We show the combination of long-period waveforms and P-wave first motions are able to discriminate this event as explosion-like and distinct from earthquakes and collapses. We further demonstrate the behavior of network sensitivity solutions for models of tectonic release and spall-based tensile damage over a range of F-factors and K-factors.« less

Alzheimer's disease detection via automatic 3D caudate nucleus segmentation using coupled dictionary learning with level set formulation.

PubMed

Al-Shaikhli, Saif Dawood Salman; Yang, Michael Ying; Rosenhahn, Bodo

2016-12-01

This paper presents a novel method for Alzheimer's disease classification via an automatic 3D caudate nucleus segmentation. The proposed method consists of segmentation and classification steps. In the segmentation step, we propose a novel level set cost function. The proposed cost function is constrained by a sparse representation of local image features using a dictionary learning method. We present coupled dictionaries: a feature dictionary of a grayscale brain image and a label dictionary of a caudate nucleus label image. Using online dictionary learning, the coupled dictionaries are learned from the training data. The learned coupled dictionaries are embedded into a level set function. In the classification step, a region-based feature dictionary is built. The region-based feature dictionary is learned from shape features of the caudate nucleus in the training data. The classification is based on the measure of the similarity between the sparse representation of region-based shape features of the segmented caudate in the test image and the region-based feature dictionary. The experimental results demonstrate the superiority of our method over the state-of-the-art methods by achieving a high segmentation (91.5%) and classification (92.5%) accuracy. In this paper, we find that the study of the caudate nucleus atrophy gives an advantage over the study of whole brain structure atrophy to detect Alzheimer's disease. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Seasonal variation of carbon fluxes in a sparse savanna in semi arid Sudan.

PubMed

Ardö, Jonas; Mölder, Meelis; El-Tahir, Bashir Awad; Elkhidir, Hatim Abdalla Mohammed

2008-12-01

Large spatial, seasonal and annual variability of major drivers of the carbon cycle (precipitation, temperature, fire regime and nutrient availability) are common in the Sahel region. This causes large variability in net ecosystem exchange and in vegetation productivity, the subsistence basis for a major part of the rural population in Sahel. This study compares the 2005 dry and wet season fluxes of CO2 for a grass land/sparse savanna site in semi arid Sudan and relates these fluxes to water availability and incoming photosynthetic photon flux density (PPFD). Data from this site could complement the current sparse observation network in Africa, a continent where climatic change could significantly impact the future and which constitute a weak link in our understanding of the global carbon cycle. The dry season (represented by Julian day 35-46, February 2005) was characterized by low soil moisture availability, low evapotranspiration and a high vapor pressure deficit. The mean daily NEE (net ecosystem exchange, Eq. 1) was -14.7 mmol d-1 for the 12 day period (negative numbers denote sinks, i.e. flux from the atmosphere to the biosphere). The water use efficiency (WUE) was 1.6 mmol CO2 mol H2O-1 and the light use efficiency (LUE) was 0.95 mmol CO2 mol PPFD-1. Photosynthesis is a weak, but linear function of PPFD. The wet season (represented by Julian day 266-273, September 2005) was, compared to the dry season, characterized by slightly higher soil moisture availability, higher evapotranspiration and a slightly lower vapor pressure deficit. The mean daily NEE was -152 mmol d-1 for the 8 day period. The WUE was lower, 0.97 mmol CO2 mol H2O-1 and the LUE was higher, 7.2 mumol CO2 mmol PPFD-1 during the wet season compared to the dry season. During the wet season photosynthesis increases with PPFD to about 1600 mumol m-2s-1 and then levels off. Based on data collected during two short periods, the studied ecosystem was a sink of carbon both during the dry and wet season 2005. The small sink during the dry season is surprising and similar dry season sinks have not to our knowledge been reported from other similar savanna ecosystems and could have potential management implications for agroforestry. A strong response of NEE versus small changes in plant available soil water content was found. Collection and analysis of flux data for several consecutive years including variations in precipitation, available soil moisture and labile soil carbon are needed for understanding the year to year variation of the carbon budget of this grass land/sparse savanna site in semi arid Sudan.

Quantifying Groundwater Availability in Fractured Rock Aquifers of Northern Ugandan Refugee Settlements

NASA Astrophysics Data System (ADS)

Frederiks, R.; Lowry, C.; Mutiibwa, R.; Moisy, S.; Thapa, L.; Oriba, J.

2017-12-01

In the past two years, Uganda has witnessed an influx of nearly one million refugees who have settled in the sparsely populated northwestern region of the country. This rapid population growth has created high demand for clean water resources. Water supply has been unable to keep pace with demand because the fractured rock aquifers underlying the region often produce low yielding wells. To facilitate management of groundwater resources, it is necessary to quantify the spatial distribution of groundwater. In fractured rock aquifers, there is significant spatial variability in water storage because fractures must be both connected and abundant for water to be extracted in usable quantities. Two conceptual models were evaluated to determine the groundwater storage mechanism in the fractured crystalline bedrock aquifers of northwestern Uganda where by permeability is controlled by faulting, which opens up fractures in the bedrock, or weathering, which occurs when water dissolves components of rock. In order to test these two conceptual models, geologic well logs and available hydrologic data were collected and evaluated using geostatistical and numerical groundwater models. The geostatistical analysis focused on identifying spatially distributed patterns of high and low water yield. The conceptual models were evaluated numerically using four inverse groundwater MODFLOW models based on head and estimated flux targets. The models were based on: (1) the mapped bedrock units using an equivalent porous media approach (2) bedrock units with the addition of known fault zones (3) bedrock units with predicted units of deep weathering based on surface slopes, and (4) bedrock units with discrete faults and simulated weathered zones. Predicting permeable zones is vital for water well drilling in much of East Africa and South America where there is an abundance of both fractured rock and tectonic activity. Given that the population of these developing regions is growing, the demand for sufficient clean water is likely to increase significantly in the next few decades. Thus, it is necessary to improve our ability to predict locations of permeable zones in fractured rock aquifers.

Decoding the encoding of functional brain networks: An fMRI classification comparison of non-negative matrix factorization (NMF), independent component analysis (ICA), and sparse coding algorithms.

PubMed

Xie, Jianwen; Douglas, Pamela K; Wu, Ying Nian; Brody, Arthur L; Anderson, Ariana E

2017-04-15

Brain networks in fMRI are typically identified using spatial independent component analysis (ICA), yet other mathematical constraints provide alternate biologically-plausible frameworks for generating brain networks. Non-negative matrix factorization (NMF) would suppress negative BOLD signal by enforcing positivity. Spatial sparse coding algorithms (L1 Regularized Learning and K-SVD) would impose local specialization and a discouragement of multitasking, where the total observed activity in a single voxel originates from a restricted number of possible brain networks. The assumptions of independence, positivity, and sparsity to encode task-related brain networks are compared; the resulting brain networks within scan for different constraints are used as basis functions to encode observed functional activity. These encodings are then decoded using machine learning, by using the time series weights to predict within scan whether a subject is viewing a video, listening to an audio cue, or at rest, in 304 fMRI scans from 51 subjects. The sparse coding algorithm of L1 Regularized Learning outperformed 4 variations of ICA (p<0.001) for predicting the task being performed within each scan using artifact-cleaned components. The NMF algorithms, which suppressed negative BOLD signal, had the poorest accuracy compared to the ICA and sparse coding algorithms. Holding constant the effect of the extraction algorithm, encodings using sparser spatial networks (containing more zero-valued voxels) had higher classification accuracy (p<0.001). Lower classification accuracy occurred when the extracted spatial maps contained more CSF regions (p<0.001). The success of sparse coding algorithms suggests that algorithms which enforce sparsity, discourage multitasking, and promote local specialization may capture better the underlying source processes than those which allow inexhaustible local processes such as ICA. Negative BOLD signal may capture task-related activations. Copyright © 2017 Elsevier B.V. All rights reserved.

An ultra-sparse code underliesthe generation of neural sequences in a songbird

NASA Astrophysics Data System (ADS)

Hahnloser, Richard H. R.; Kozhevnikov, Alexay A.; Fee, Michale S.

2002-09-01

Sequences of motor activity are encoded in many vertebrate brains by complex spatio-temporal patterns of neural activity; however, the neural circuit mechanisms underlying the generation of these pre-motor patterns are poorly understood. In songbirds, one prominent site of pre-motor activity is the forebrain robust nucleus of the archistriatum (RA), which generates stereotyped sequences of spike bursts during song and recapitulates these sequences during sleep. We show that the stereotyped sequences in RA are driven from nucleus HVC (high vocal centre), the principal pre-motor input to RA. Recordings of identified HVC neurons in sleeping and singing birds show that individual HVC neurons projecting onto RA neurons produce bursts sparsely, at a single, precise time during the RA sequence. These HVC neurons burst sequentially with respect to one another. We suggest that at each time in the RA sequence, the ensemble of active RA neurons is driven by a subpopulation of RA-projecting HVC neurons that is active only at that time. As a population, these HVC neurons may form an explicit representation of time in the sequence. Such a sparse representation, a temporal analogue of the `grandmother cell' concept for object recognition, eliminates the problem of temporal interference during sequence generation and learning attributed to more distributed representations.

Access to Educational Opportunity in Rural Communities: Alternative Patterns of Delivering Vocational Education in Sparsely Populated Areas. Volume 4: The Interdistrict Cooperative Center: A Centralized Center.

ERIC Educational Resources Information Center

Peterson, Roland L.; And Others

The centralized secondary center pattern of inter-school district cooperation is examined in this third of four case studies addressing access of rural students to vocational education. The report identifies essential features of this form of cooperation, details factors facilitating/impeding the operation/maintenance of the cooperative…

Access to Educational Opportunity in Rural Communities: Alternative Patterns of Delivering Vocational Education in Sparsely Populated Areas. Volume 3: The Northwest Multi-District: A Mobile Facilities Center.

ERIC Educational Resources Information Center

Peterson, Roland L.; And Others

Representing the mobile facilities pattern of inter-district cooperation, the Northwest Multi-District case is one of four studies addressing access of rural students to vocational education through inter-school district cooperation. The report identifies essential features of this form of cooperation, details factors facilitating/impeding the…

President Obama Wants Change--How Educators Can Help to Form a Real Global Society

ERIC Educational Resources Information Center

Gentry, Ruben

2009-01-01

"Do nothing and all things will be done," or "Wait, time heals all wounds" may have been sound advice of the past for some distant, sparsely populated island. But failing to address economic issues and not providing health care for the sick were putting America on the verge of financial collapse and making it a land where people had to choose…

Partners in Lifelong Learning: How Creeds Elementary School and the Pungo-Blackwater Public Library Combine Forces for the Benefit of Their Community

ERIC Educational Resources Information Center

Lighthart, Matthew; Spreder, Creedence

2014-01-01

Matthew Lighthart and Creedence Spreder, librarians, describe a partnership that proved successful for the school and library in their community of Pungo, nestled in Virginia Beach's vast but sparsely populated agricultural center. This community was facing a dual challenge: their only elementary school (Creeds) was in dire need of renovation and…

Microwave scattering models and basic experiments

NASA Technical Reports Server (NTRS)

Fung, Adrian K.

1989-01-01

Progress is summarized which has been made in four areas of study: (1) scattering model development for sparsely populated media, such as a forested area; (2) scattering model development for dense media, such as a sea ice medium or a snow covered terrain; (3) model development for randomly rough surfaces; and (4) design and conduct of basic scattering and attenuation experiments suitable for the verification of theoretical models.

Pilot Inventory of FIA plots traditionally called `nonforest'

Treesearch

Rachel Riemann

2003-01-01

Forest-inventory data were collected on plots defined as ?nonforest? by the USDA Forest Service?s Forest Inventory and Analysis (FIA) unit. Nonforest plots may have trees on them, but they do not fit FIA?s definition of forest because the area covered by trees is too small, too sparsely populated by trees, too narrow (e.g., trees between fields or in the middle of a...

Colstrip, Montana: The Fiscal Effects of Recent Coal Development and an Evaluation of the Community's Ability to Handle Further Expansion.

ERIC Educational Resources Information Center

Johnson, Maxine C.; White, Randle V.

Much of the coal development in eastern Montana has occured in or is proposed for sparsely settled Rosebud County, which includes the Colstrip elementary and high school districts. Between fiscal 1966 and 1975, the population growth resulting from coal activities has brought about a 68% real increase in Rosebud County expenditures. Increase in…

Stigmatizing Attitudes towards People Living with HIV/AIDS among College Students in China: Implications for HIV/AIDS Education and Prevention

ERIC Educational Resources Information Center

Zhang, Liying; Li, Xiaoming; Mao, Rong; Stanton, Bonita; Zhao, Qun; Wang, Bo; Mathur, Ambika

2008-01-01

Purpose: The purpose of this paper is to show that HIV/AIDS-related stigma has persisted world-wide for decades. However, studies on the linkage between stigmatizing attitudes towards people living with HIV/AIDS (PLWHA) and misconceptions about HIV transmission routes in the general population, especially among youth in China, are sparse--a gap…

Enhancing Pediatric Palliative Care for Latino Children and Their Families: A Review of the Literature and Recommendations for Research and Practice in the United States

PubMed Central

Raisanen, Jessica C.; Donohue, Pamela K.; Boss, Renee D.

2017-01-01

As the demand for pediatric palliative care (PC) increases, data suggest that Latino children are less likely to receive services than non-Latino children. Evidence on how to best provide PC to Latino children is sparse. We conducted a narrative review of literature related to PC for Latino children and their families in the United States. In the United States, Latinos face multiple barriers that affect their receipt of PC, including poverty, lack of access to health insurance, language barriers, discrimination, and cultural differences. Pediatric PC research and clinical initiatives that target the needs of Latino families are sparse, underfunded, but essential. Education of providers on Latino cultural values is necessary. Additionally, advocacy efforts with a focus on equitable care and policy reform are essential to improving the health of this vulnerable population. PMID:29271924

Image statistics underlying natural texture selectivity of neurons in macaque V4

PubMed Central

Okazawa, Gouki; Tajima, Satohiro; Komatsu, Hidehiko

2015-01-01

Our daily visual experiences are inevitably linked to recognizing the rich variety of textures. However, how the brain encodes and differentiates a plethora of natural textures remains poorly understood. Here, we show that many neurons in macaque V4 selectively encode sparse combinations of higher-order image statistics to represent natural textures. We systematically explored neural selectivity in a high-dimensional texture space by combining texture synthesis and efficient-sampling techniques. This yielded parameterized models for individual texture-selective neurons. The models provided parsimonious but powerful predictors for each neuron’s preferred textures using a sparse combination of image statistics. As a whole population, the neuronal tuning was distributed in a way suitable for categorizing textures and quantitatively predicts human ability to discriminate textures. Together, we suggest that the collective representation of visual image statistics in V4 plays a key role in organizing the natural texture perception. PMID:25535362

Mesoscopic in vivo 3-D tracking of sparse cell populations using angular multiplexed optical projection tomography

PubMed Central

Chen, Lingling; Alexandrov, Yuriy; Kumar, Sunil; Andrews, Natalie; Dallman, Margaret J.; French, Paul M. W.; McGinty, James

2015-01-01

We describe an angular multiplexed imaging technique for 3-D in vivo cell tracking of sparse cell distributions and optical projection tomography (OPT) with superior time-lapse resolution and a significantly reduced light dose compared to volumetric time-lapse techniques. We demonstrate that using dual axis OPT, where two images are acquired simultaneously at different projection angles, can enable localization and tracking of features in 3-D with a time resolution equal to the camera frame rate. This is achieved with a 200x reduction in light dose compared to an equivalent volumetric time-lapse single camera OPT acquisition with 200 projection angles. We demonstrate the application of this technique to mapping the 3-D neutrophil migration pattern observed over ~25.5 minutes in a live 2 day post-fertilisation transgenic LysC:GFP zebrafish embryo following a tail wound. PMID:25909009

Bayes plus Brass: Estimating Total Fertility for Many Small Areas from Sparse Census Data

PubMed Central

Schmertmann, Carl P.; Cavenaghi, Suzana M.; Assunção, Renato M.; Potter, Joseph E.

2013-01-01

Small-area fertility estimates are valuable for analysing demographic change, and important for local planning and population projection. In countries lacking complete vital registration, however, small-area estimates are possible only from sparse survey or census data that are potentially unreliable. Such estimation requires new methods for old problems: procedures must be automated if thousands of estimates are required, they must deal with extreme sampling variability in many areas, and they should also incorporate corrections for possible data errors. We present a two-step algorithm for estimating total fertility in such circumstances, and we illustrate by applying the method to 2000 Brazilian Census data for over five thousand municipalities. Our proposed algorithm first smoothes local age-specific rates using Empirical Bayes methods, and then applies a new variant of Brass’s P/F parity correction procedure that is robust under conditions of rapid fertility decline. PMID:24143946

Mesoscopic in vivo 3-D tracking of sparse cell populations using angular multiplexed optical projection tomography.

PubMed

Chen, Lingling; Alexandrov, Yuriy; Kumar, Sunil; Andrews, Natalie; Dallman, Margaret J; French, Paul M W; McGinty, James

2015-04-01

We describe an angular multiplexed imaging technique for 3-D in vivo cell tracking of sparse cell distributions and optical projection tomography (OPT) with superior time-lapse resolution and a significantly reduced light dose compared to volumetric time-lapse techniques. We demonstrate that using dual axis OPT, where two images are acquired simultaneously at different projection angles, can enable localization and tracking of features in 3-D with a time resolution equal to the camera frame rate. This is achieved with a 200x reduction in light dose compared to an equivalent volumetric time-lapse single camera OPT acquisition with 200 projection angles. We demonstrate the application of this technique to mapping the 3-D neutrophil migration pattern observed over ~25.5 minutes in a live 2 day post-fertilisation transgenic LysC:GFP zebrafish embryo following a tail wound.

The burden of road traffic injuries in Nigeria: results of a population-based survey.

PubMed

Labinjo, M; Juillard, C; Kobusingye, O C; Hyder, A A

2009-06-01

Mortality from road traffic injuries in sub-Saharan Africa is among the highest in the world, yet data from the region are sparse. To date, no multi-site population-based survey on road traffic injuries has been reported from Nigeria, the most populated country in Africa. To explore the epidemiology of road traffic injury in Nigeria and provide data on the populations affected and risk factors for road traffic injury. Data from a population-based survey using two-stage stratified cluster sampling. SUBJECTS/ SETTING: Road traffic injury status and demographic information were collected on 3082 respondents living in 553 households in seven of Nigeria's 37 states. Incidence rates were estimated with confidence intervals based on a Poisson distribution; Poisson regression analysis was used to calculate relative risks for associated factors. The overall road traffic injury rate was 41 per 1000 population (95% CI 34 to 49), and mortality from road traffic injuries was 1.6 per 1000 population (95% CI 0.5 to 3.8). Motorcycle crashes accounted for 54% of all road traffic injuries. The road traffic injury rates found for rural and urban respondents were not significantly different. Increased risk of injury was associated with male gender among those aged 18-44 years, with a relative risk of 2.96 when compared with women in the same age range (95% CI 1.72 to 5.09, p<0.001). The road traffic injury rates found in this survey highlight a neglected public health problem in Nigeria. Simple extrapolations from this survey suggest that over 4 million people may be injured and as many as 200 000 potentially killed as the result of road traffic crashes annually in Nigeria. Appropriate interventions in both the health and transport sectors are needed to address this significant cause of morbidity and mortality in Nigeria.

Prediction of siRNA potency using sparse logistic regression.

PubMed

Hu, Wei; Hu, John

2014-06-01

RNA interference (RNAi) can modulate gene expression at post-transcriptional as well as transcriptional levels. Short interfering RNA (siRNA) serves as a trigger for the RNAi gene inhibition mechanism, and therefore is a crucial intermediate step in RNAi. There have been extensive studies to identify the sequence characteristics of potent siRNAs. One such study built a linear model using LASSO (Least Absolute Shrinkage and Selection Operator) to measure the contribution of each siRNA sequence feature. This model is simple and interpretable, but it requires a large number of nonzero weights. We have introduced a novel technique, sparse logistic regression, to build a linear model using single-position specific nucleotide compositions which has the same prediction accuracy of the linear model based on LASSO. The weights in our new model share the same general trend as those in the previous model, but have only 25 nonzero weights out of a total 84 weights, a 54% reduction compared to the previous model. Contrary to the linear model based on LASSO, our model suggests that only a few positions are influential on the efficacy of the siRNA, which are the 5' and 3' ends and the seed region of siRNA sequences. We also employed sparse logistic regression to build a linear model using dual-position specific nucleotide compositions, a task LASSO is not able to accomplish well due to its high dimensional nature. Our results demonstrate the superiority of sparse logistic regression as a technique for both feature selection and regression over LASSO in the context of siRNA design.

A sparse reconstruction method for the estimation of multiresolution emission fields via atmospheric inversion

DOE PAGES

Ray, J.; Lee, J.; Yadav, V.; ...

2014-08-20

We present a sparse reconstruction scheme that can also be used to ensure non-negativity when fitting wavelet-based random field models to limited observations in non-rectangular geometries. The method is relevant when multiresolution fields are estimated using linear inverse problems. Examples include the estimation of emission fields for many anthropogenic pollutants using atmospheric inversion or hydraulic conductivity in aquifers from flow measurements. The scheme is based on three new developments. Firstly, we extend an existing sparse reconstruction method, Stagewise Orthogonal Matching Pursuit (StOMP), to incorporate prior information on the target field. Secondly, we develop an iterative method that uses StOMP tomore » impose non-negativity on the estimated field. Finally, we devise a method, based on compressive sensing, to limit the estimated field within an irregularly shaped domain. We demonstrate the method on the estimation of fossil-fuel CO 2 (ffCO 2) emissions in the lower 48 states of the US. The application uses a recently developed multiresolution random field model and synthetic observations of ffCO 2 concentrations from a limited set of measurement sites. We find that our method for limiting the estimated field within an irregularly shaped region is about a factor of 10 faster than conventional approaches. It also reduces the overall computational cost by a factor of two. Further, the sparse reconstruction scheme imposes non-negativity without introducing strong nonlinearities, such as those introduced by employing log-transformed fields, and thus reaps the benefits of simplicity and computational speed that are characteristic of linear inverse problems.« less

Urbanization and prevalence of type 2 diabetes in Southern Asia: A systematic analysis

PubMed Central

Cheema, Arsalan; Adeloye, Davies; Sidhu, Simrita; Sridhar, Devi; Chan, Kit Yee

2014-01-01

Background Diabetes mellitus is one of the diseases considered to be the main constituents of the global non–communicable disease (NCD) pandemic. Despite the large impact that NCDs are predicted to have, particularly in developing countries, estimates of disease burden are sparse and inconsistent. This systematic review transparently estimates prevalence of type 2 diabetes mellitus in Southern Asia, its association with urbanization and provides insight into the policy challenges facing the region. Methods The databases Medline and PubMed were searched for population–based studies providing estimates of diabetes prevalence in the Southern Asia region. Studies using WHO diagnostic criteria of fasting plasma glucose (FPG) ≥7.0mmol/L and/or 2h–plasma glucose (2hPG) ≥11.1mmol/L were included. Data from eligible studies was extracted into bubble graphs, and trend lines were applied to UNPD figures to estimate age–specific prevalence in the regional population. Estimates specific to sex, area of residency, and diagnostic method were compared and trends analysed. Results A total of 151 age–specific prevalence estimates were extracted from 39 studies. Diabetes prevalence was estimated to be 7.47% for 2005 and 7.60% for 2010. Prevalence was strongly associated with increased age, male gender and urban residency (P < 0.001). Conclusion Diabetes prevalence in Southern Asia is high and predicted to increase in the future as life expectancy rises and the region continues to urbanise. Countries in this region need to improve NCD surveillance and monitoring so policies can be informed with the best evidence. Programs for prevention need to be put in place, and health system capacity and access needs to be assessed and increased to deal with the predicted rise in NCD prevalence. PMID:24976963

Model simulations of fungal spore distribution over the Indian region

NASA Astrophysics Data System (ADS)

Ansari, Tabish U.; Valsan, Aswathy E.; Ojha, N.; Ravikrishna, R.; Narasimhan, Balaji; Gunthe, Sachin S.

2015-12-01

Fungal spores play important role in the health of humans, animals, and plants by constituting a class of the primary biological aerosol particles (PBAPs). Additionally, these could mediate the hydrological cycle by acting as nuclei for ice and cloud formation (IN and CCN respectively). Various processes in the biosphere and the variations in the meteorological conditions control the releasing mechanism of spores through active wet and dry discharge. In the present paper, we simulate the concentration of fungal spores over the Indian region during three distinct meteorological seasons by combining a numerical model (WRF-Chem) with the fungal spore emissions based on land-use type. Maiden high-resolution regional simulations revealed large spatial gradient and strong seasonal dependence in the concentration of fungal spores over the Indian region. The fungal spore concentrations are found to be the highest during winter (0-70 μg m-3 in December), moderately higher during summer (0-35 μg m-3 in May) and lowest during the monsoon (0-25 μg m-3 in July). The elevated concentrations during winter are attributed to the shallower boundary layer trapping the emitted fungal spores in smaller volume. In contrast, the deeper boundary layer mixing in May and stronger monsoonal-convection in July distribute the fungal spores throughout the lower troposphere (∼5 km). We suggest that the higher fungal spore concentrations during winter could have potential health impacts. While, stronger vertical mixing could enable fungal spores to influence the cloud formation during summer and monsoon. Our study provides the first information about the distribution and seasonal variation of fungal spores over the densely populated and observationally sparse Indian region.

A Dictionary Learning Method with Total Generalized Variation for MRI Reconstruction

PubMed Central

Lu, Hongyang; Wei, Jingbo; Wang, Yuhao; Deng, Xiaohua

2016-01-01

Reconstructing images from their noisy and incomplete measurements is always a challenge especially for medical MR image with important details and features. This work proposes a novel dictionary learning model that integrates two sparse regularization methods: the total generalized variation (TGV) approach and adaptive dictionary learning (DL). In the proposed method, the TGV selectively regularizes different image regions at different levels to avoid oil painting artifacts largely. At the same time, the dictionary learning adaptively represents the image features sparsely and effectively recovers details of images. The proposed model is solved by variable splitting technique and the alternating direction method of multiplier. Extensive simulation experimental results demonstrate that the proposed method consistently recovers MR images efficiently and outperforms the current state-of-the-art approaches in terms of higher PSNR and lower HFEN values. PMID:27110235

A Dictionary Learning Method with Total Generalized Variation for MRI Reconstruction.

PubMed

Lu, Hongyang; Wei, Jingbo; Liu, Qiegen; Wang, Yuhao; Deng, Xiaohua

2016-01-01

Reconstructing images from their noisy and incomplete measurements is always a challenge especially for medical MR image with important details and features. This work proposes a novel dictionary learning model that integrates two sparse regularization methods: the total generalized variation (TGV) approach and adaptive dictionary learning (DL). In the proposed method, the TGV selectively regularizes different image regions at different levels to avoid oil painting artifacts largely. At the same time, the dictionary learning adaptively represents the image features sparsely and effectively recovers details of images. The proposed model is solved by variable splitting technique and the alternating direction method of multiplier. Extensive simulation experimental results demonstrate that the proposed method consistently recovers MR images efficiently and outperforms the current state-of-the-art approaches in terms of higher PSNR and lower HFEN values.

Water Vapor Winds and Their Application to Climate Change Studies

NASA Technical Reports Server (NTRS)

Jedlovec, Gary J.; Lerner, Jeffrey A.

2000-01-01

The retrieval of satellite-derived winds and moisture from geostationary water vapor imagery has matured to the point where it may be applied to better understanding longer term climate changes that were previously not possible using conventional measurements or model analysis in data-sparse regions. In this paper, upper-tropospheric circulation features and moisture transport covering ENSO periods are presented and discussed. Precursors and other detectable interannual climate change signals are analyzed and compared to model diagnosed features. Estimates of winds and humidity over data-rich regions are used to show the robustness of the data and its value over regions that have previously eluded measurement.

Statistical Analysis of Terrestrial Water Storage Change Over Southwestern United States

NASA Astrophysics Data System (ADS)

Eibedingil, I. G.; Mubako, S. T.; Hargrove, W. L.; Espino, A. C.

2017-12-01

A warming trend over recent decades has aggravated water resource challenges in the arid southwestern region of the United States (U.S.). An increase in temperature, coupled with decreasing snowpack and rainfall have impacted the region's cities, ecosystems, and agriculture. The region is the largest contributor of agricultural products to the U.S. market resulting from irrigation. Water use through irrigation is stressing already limited terrestrial water resources. Population growth in recent decades has also led to increased water demand. This study utilizes products of the Gravity Recovery and Climate Experiment (GRACE) twin satellites experiment in MATLAB and ArcGIS to examine terrestrial water storage changes in the southwestern region of the U.S., comprised of the eight states of Texas, California, Nevada, Utah, Arizona, Colorado, New Mexico, and Oklahoma. Linear trend analysis was applied to the equivalent water-height data of terrestrial water storage changes (TWSC), precipitation, and air temperature. Correlation analysis was performed on couplings of TWSC - precipitation and TWSC - air temperature to examine the impact of temperature and precipitation on the region's water resources. Our preliminary results show a decreasing trend of TWSC from April 2002 to July 2016 in almost all parts of the region. Precipitation shows a decreasing trend from March 2000 to March 2017 for most of the region, except for sparse areas of increased precipitation near the northwestern coast of California, and a belt running from Oklahoma through the middle of Texas to the El Paso/New Mexico border. From April 2002 to December 2014, air temperature exhibited a negative trend for most of the region, except a larger part of California and a small location in central Texas. Correlation between TWSC and precipitation was mostly positive, but a negative trend was observed when TWSC and air temperature were correlated. The study contributes to the understanding of terrestrial water storage trends and their relationship with climatic variables, crucial for implementing appropriate adaptation and mitigation policies and strategies, and managing water demand.

Fire responses to postglacial climate change and human impact in northern Patagonia (41-43°S).

PubMed

Iglesias, Virginia; Whitlock, Cathy

2014-12-23

Forest/steppe boundaries are among the most dynamic ecosystems on Earth and are highly vulnerable to changes in climate and land use. In this study we examine the postglacial history of the Patagonian forest/steppe ecotone (41-43°S) to better understand its sensitivity to past variations in climate, disturbance, and human activity before European colonization. We present regional trends in vegetation and biomass burning, as detected by generalized additive models fitted to seven pollen and charcoal records, and compare the results with other paleoenvironmental data, as well as archeological and ecological information to (i) estimate postglacial fire trends at regional scales, (ii) assess the evolution of climate-vegetation-fire linkages over the last 18,000 calibrated (cal) years B.P., and (iii) evaluate the role of humans in altering pre-European landscapes and fire regimes. Pollen and charcoal data indicate that biomass burning was relatively low during warm/dry steppe-dominated landscapes in the late glacial/Early Holocene transition and increased as more humid conditions favored forest development after ca. 10,000 cal years B.P. Postglacial fire activity was thus limited by fuel availability associated with sparse vegetation cover rather than by suitable climate conditions. In contrast to extensive burning by European settlers, variations in indigenous population densities were not associated with fluctuations in regional or watershed-scale fire occurrence, suggesting that climate-vegetation-fire linkages in northern Patagonia evolved with minimal or very localized human influences before European settlement.

Fire responses to postglacial climate change and human impact in northern Patagonia (41–43°S)

PubMed Central

Iglesias, Virginia; Whitlock, Cathy

2014-01-01

Forest/steppe boundaries are among the most dynamic ecosystems on Earth and are highly vulnerable to changes in climate and land use. In this study we examine the postglacial history of the Patagonian forest/steppe ecotone (41–43°S) to better understand its sensitivity to past variations in climate, disturbance, and human activity before European colonization. We present regional trends in vegetation and biomass burning, as detected by generalized additive models fitted to seven pollen and charcoal records, and compare the results with other paleoenvironmental data, as well as archeological and ecological information to (i) estimate postglacial fire trends at regional scales, (ii) assess the evolution of climate–vegetation–fire linkages over the last 18,000 calibrated (cal) years B.P., and (iii) evaluate the role of humans in altering pre-European landscapes and fire regimes. Pollen and charcoal data indicate that biomass burning was relatively low during warm/dry steppe-dominated landscapes in the late glacial/Early Holocene transition and increased as more humid conditions favored forest development after ca. 10,000 cal years B.P. Postglacial fire activity was thus limited by fuel availability associated with sparse vegetation cover rather than by suitable climate conditions. In contrast to extensive burning by European settlers, variations in indigenous population densities were not associated with fluctuations in regional or watershed-scale fire occurrence, suggesting that climate–vegetation–fire linkages in northern Patagonia evolved with minimal or very localized human influences before European settlement. PMID:25489077

An epidemiologic study of Lyme disease in southern Sweden.

PubMed

Berglund, J; Eitrem, R; Ornstein, K; Lindberg, A; Ringér, A; Elmrud, H; Carlsson, M; Runehagen, A; Svanborg, C; Norrby, R

1995-11-16

Lyme disease is the most common vector-borne infection in some temperate regions of the Northern Hemisphere. However, for most areas of endemic disease reliable epidemiologic data are sparse. Over a one-year period, we conducted a prospective, population-based survey of cases of Lyme disease in southern Sweden. The diagnosis was made on the basis of the presence of erythema migrans at least 5 cm in diameter or characteristic clinical manifestations such as arthritis, neuroborreliosis, and carditis. We identified 1471 patients with Lyme disease, for an overall annual incidence of 69 cases per 100,000 inhabitants. The incidence varied markedly according to geographic region, and there were several areas where disease was widely prevalent. The incidence varied according to age, with the highest rates among people 5 to 9 and 60 to 74 years of age, but not according to sex. The most frequent clinical manifestation was erythema migrans (seen in 77 percent of all cases), followed by neuroborreliosis (16 percent) and arthritis (7 percent). Carditis was rare. A preceding tick bite was reported by 79 percent of the patients. Bites in the head and neck region were more common among children than among adults and were associated with an increased risk of neuroborreliosis. Lyme disease is very common in southern Sweden, with a relatively high frequency of neurologic complications and arthritis. With the exception of the low incidence of carditis, the pattern of disease we found in Sweden was similar to that reported in the United States.

Genomewide Linkage Scan for Diabetic Renal Failure and Albuminuria: The FIND Study

PubMed Central

Igo, Robert P.; Iyengar, Sudha K.; Nicholas, Susanne B.; Goddard, Katrina A.B.; Langefeld, Carl D.; Hanson, Robert L.; Duggirala, Ravindranath; Divers, Jasmin; Abboud, Hanna; Adler, Sharon G.; Arar, Nedal H.; Horvath, Amanda; Elston, Robert C.; Bowden, Donald W.; Guo, Xiuqing; Ipp, Eli; Kao, W.H. Linda; Kimmel, Paul L.; Knowler, William C.; Meoni, Lucy A.; Molineros, Julio; Nelson, Robert G.; Pahl, Madeline V.; Parekh, Rulan S.; Rasooly, Rebekah S.; Schelling, Jeffrey R.; Shah, Vallabh O.; Smith, Michael W.; Winkler, Cheryl A.; Zager, Philip G.; Sedor, John R.; Freedman, Barry I.

2011-01-01

Background Diabetic nephropathy (DN) is a leading cause of mortality and morbidity in patients with type 1 and type 2 diabetes. The multicenter FIND consortium aims to identify genes for DN and its associated quantitative traits, e.g. the urine albumin:creatinine ratio (ACR). Herein, the results of whole-genome linkage analysis and a sparse association scan for ACR and a dichotomous DN phenotype are reported in diabetic individuals. Methods A genomewide scan comprising more than 5,500 autosomal single nucleotide polymorphism markers (average spacing of 0.6 cM) was performed on 1,235 nuclear and extended pedigrees (3,972 diabetic participants) ascertained for DN from African-American (AA), American-Indian (AI), European-American (EA) and Mexican-American (MA) populations. Results Strong evidence for linkage to DN was detected on chromosome 6p (p = 8.0 × 10−5, LOD = 3.09) in EA families as well as suggestive evidence for linkage to chromosome 7p in AI families. Regions on chromosomes 3p in AA, 7q in EA, 16q in AA and 22q in MA displayed suggestive evidence of linkage for urine ACR. The linkage peak on chromosome 22q overlaps the MYH9/APOL1 gene region, previously implicated in AA diabetic and nondiabetic nephropathies. Conclusion These results strengthen the evidence for previously identified genomic regions and implicate several novel loci potentially involved in the pathogenesis of DN. PMID:21454968

A prospective study of mandibular trabecular bone to predict fracture incidence in women: a low-cost screening tool in the dental clinic.

PubMed

Jonasson, Grethe; Sundh, Valter; Ahlqwist, Margareta; Hakeberg, Magnus; Björkelund, Cecilia; Lissner, Lauren

2011-10-01

Bone structure is the key to the understanding of fracture risk. The hypothesis tested in this prospective study is that dense mandibular trabeculation predicts low fracture risk, whereas sparse trabeculation is predictive of high fracture risk. Out of 731 women from the Prospective Population Study of Women in Gothenburg with dental examinations at baseline 1968, 222 had their first fracture in the follow-up period until 2006. Mandibular trabeculation was defined as dense, mixed dense plus sparse, and sparse based on panoramic radiographs from 1968 and/or 1980. Time to fracture was ascertained and used as the dependent variable in three Cox proportional hazards regression analyses. The first analysis covered 12 years of follow-up with self-reported endpoints; the second covered 26 years of follow-up with hospital verified endpoints; and the third combined the two follow-up periods, totaling 38 years. Mandibular trabeculation was the main independent variable predicting incident fractures, with age, physical activity, alcohol consumption and body mass index as covariates. The Kaplan-Meier curve indicated a graded association between trabecular density and fracture risk. During the whole period covered, the hazard ratio of future fracture for sparse trabeculation compared to mixed trabeculation was 2.9 (95% CI: 2.2-3.8, p<0.0001), and for dense versus mixed trabeculation was 0.21 (95% CI: 0.1-0.4, p<0.0001). The trabecular pattern was a highly significant predictor of future fracture risk. Our findings imply that dentists, using ordinary dental radiographs, can identify women at high risk for future fractures at 38-54 years of age, often long before the first fracture occurs. Copyright © 2011 Elsevier Inc. All rights reserved.

Low-rank Atlas Image Analyses in the Presence of Pathologies

PubMed Central

Liu, Xiaoxiao; Niethammer, Marc; Kwitt, Roland; Singh, Nikhil; McCormick, Matt; Aylward, Stephen

2015-01-01

We present a common framework, for registering images to an atlas and for forming an unbiased atlas, that tolerates the presence of pathologies such as tumors and traumatic brain injury lesions. This common framework is particularly useful when a sufficient number of protocol-matched scans from healthy subjects cannot be easily acquired for atlas formation and when the pathologies in a patient cause large appearance changes. Our framework combines a low-rank-plus-sparse image decomposition technique with an iterative, diffeomorphic, group-wise image registration method. At each iteration of image registration, the decomposition technique estimates a “healthy” version of each image as its low-rank component and estimates the pathologies in each image as its sparse component. The healthy version of each image is used for the next iteration of image registration. The low-rank and sparse estimates are refined as the image registrations iteratively improve. When that framework is applied to image-to-atlas registration, the low-rank image is registered to a pre-defined atlas, to establish correspondence that is independent of the pathologies in the sparse component of each image. Ultimately, image-to-atlas registrations can be used to define spatial priors for tissue segmentation and to map information across subjects. When that framework is applied to unbiased atlas formation, at each iteration, the average of the low-rank images from the patients is used as the atlas image for the next iteration, until convergence. Since each iteration’s atlas is comprised of low-rank components, it provides a population-consistent, pathology-free appearance. Evaluations of the proposed methodology are presented using synthetic data as well as simulated and clinical tumor MRI images from the brain tumor segmentation (BRATS) challenge from MICCAI 2012. PMID:26111390

Technical note: Avoiding the direct inversion of the numerator relationship matrix for genotyped animals in single-step genomic best linear unbiased prediction solved with the preconditioned conjugate gradient.

PubMed

Masuda, Y; Misztal, I; Legarra, A; Tsuruta, S; Lourenco, D A L; Fragomeni, B O; Aguilar, I

2017-01-01

This paper evaluates an efficient implementation to multiply the inverse of a numerator relationship matrix for genotyped animals () by a vector (). The computation is required for solving mixed model equations in single-step genomic BLUP (ssGBLUP) with the preconditioned conjugate gradient (PCG). The inverse can be decomposed into sparse matrices that are blocks of the sparse inverse of a numerator relationship matrix () including genotyped animals and their ancestors. The elements of were rapidly calculated with the Henderson's rule and stored as sparse matrices in memory. Implementation of was by a series of sparse matrix-vector multiplications. Diagonal elements of , which were required as preconditioners in PCG, were approximated with a Monte Carlo method using 1,000 samples. The efficient implementation of was compared with explicit inversion of with 3 data sets including about 15,000, 81,000, and 570,000 genotyped animals selected from populations with 213,000, 8.2 million, and 10.7 million pedigree animals, respectively. The explicit inversion required 1.8 GB, 49 GB, and 2,415 GB (estimated) of memory, respectively, and 42 s, 56 min, and 13.5 d (estimated), respectively, for the computations. The efficient implementation required <1 MB, 2.9 GB, and 2.3 GB of memory, respectively, and <1 sec, 3 min, and 5 min, respectively, for setting up. Only <1 sec was required for the multiplication in each PCG iteration for any data sets. When the equations in ssGBLUP are solved with the PCG algorithm, is no longer a limiting factor in the computations.

Pumping Iron in Australia: Prevalence, Trends and Sociodemographic Correlates of Muscle Strengthening Activity Participation from a National Sample of 195,926 Adults

PubMed Central

Pedisic, Zeljko; van Uffelen, Jannique G. Z.; Charity, Melanie J.; Harvey, Jack T.; Banting, Lauren K.; Vergeer, Ineke; Biddle, Stuart J. H.; Eime, Rochelle M.

2016-01-01

Objective The current Australian Physical Activity Guidelines recommend that adults engage in regular muscle-strengthening activity (e.g. strength or resistance training). However, public health surveillance studies describing the patterns and trends of population-level muscle-strengthening activity participation are sparse. The aim of this study is to examine the prevalence, trends and sociodemographic correlates of muscle-strengthening activity participation in a national-representative sample of Australians aged 15 years and over. Methods Between 2001 and 2010, quarterly cross-sectional national telephone surveys were conducted as part of the Australian Sports Commission's 'Exercise, Recreation and Sport Survey'. Pooled population-weighted proportions were calculated for reporting: [i] no muscle-strengthening activity; [ii] insufficient muscle-strengthening activity, and [iii] sufficient muscle-strengthening activity. Associations with sociodemographic variables were assessed using multiple logistic regression analyses. Results Out of 195,926 participants, aged 15–98 years, only 10.4% (95% CI: 10.1–10.7) and 9.3% (95% CI: 9.1–9.5) met the muscle-strengthening activity recommendations in the past two weeks and in the past year, respectively. Older adults (50+ years), and those living in socioeconomically disadvantaged, outer regional/remote areas and with lower education were less likely to report sufficient muscle-strengthening activity (p<0.001). Over the 10-year monitoring period, there was a significant increase in the prevalence of sufficient muscle-strengthening activity (6.4% to 12.0%, p-value for linear trend <0.001). Conclusions A vast majority of Australian adults did not engage in sufficient muscle-strengthening activity. There is a need for public health strategies to support participation in muscle-strengthening activity in this population. Such strategies should target older and lower educated adults, and those living in socioeconomically disadvantaged, outer regional/remote and areas. PMID:27119145

Lower limb estimation from sparse landmarks using an articulated shape model.

PubMed

Zhang, Ju; Fernandez, Justin; Hislop-Jambrich, Jacqui; Besier, Thor F

2016-12-08

Rapid generation of lower limb musculoskeletal models is essential for clinically applicable patient-specific gait modeling. Estimation of muscle and joint contact forces requires accurate representation of bone geometry and pose, as well as their muscle attachment sites, which define muscle moment arms. Motion-capture is a routine part of gait assessment but contains relatively sparse geometric information. Standard methods for creating customized models from motion-capture data scale a reference model without considering natural shape variations. We present an articulated statistical shape model of the left lower limb with embedded anatomical landmarks and muscle attachment regions. This model is used in an automatic workflow, implemented in an easy-to-use software application, that robustly and accurately estimates realistic lower limb bone geometry, pose, and muscle attachment regions from seven commonly used motion-capture landmarks. Estimated bone models were validated on noise-free marker positions to have a lower (p=0.001) surface-to-surface root-mean-squared error of 4.28mm, compared to 5.22mm using standard isotropic scaling. Errors at a variety of anatomical landmarks were also lower (8.6mm versus 10.8mm, p=0.001). We improve upon standard lower limb model scaling methods with shape model-constrained realistic bone geometries, regional muscle attachment sites, and higher accuracy. Copyright © 2016 Elsevier Ltd. All rights reserved.

Groupwise registration of MR brain images with tumors.

PubMed

Tang, Zhenyu; Wu, Yihong; Fan, Yong

2017-08-04

A novel groupwise image registration framework is developed for registering MR brain images with tumors. Our method iteratively estimates a normal-appearance counterpart for each tumor image to be registered and constructs a directed graph (digraph) of normal-appearance images to guide the groupwise image registration. Particularly, our method maps each tumor image to its normal appearance counterpart by identifying and inpainting brain tumor regions with intensity information estimated using a low-rank plus sparse matrix decomposition based image representation technique. The estimated normal-appearance images are groupwisely registered to a group center image guided by a digraph of images so that the total length of 'image registration paths' to be the minimum, and then the original tumor images are warped to the group center image using the resulting deformation fields. We have evaluated our method based on both simulated and real MR brain tumor images. The registration results were evaluated with overlap measures of corresponding brain regions and average entropy of image intensity information, and Wilcoxon signed rank tests were adopted to compare different methods with respect to their regional overlap measures. Compared with a groupwise image registration method that is applied to normal-appearance images estimated using the traditional low-rank plus sparse matrix decomposition based image inpainting, our method achieved higher image registration accuracy with statistical significance (p  =  7.02  ×  10 -9 ).

Energetics in a model of prebiotic evolution

NASA Astrophysics Data System (ADS)

Intoy, B. F.; Halley, J. W.

2017-12-01

Previously we reported [A. Wynveen et al., Phys. Rev. E 89, 022725 (2014), 10.1103/PhysRevE.89.022725] that requiring that the systems regarded as lifelike be out of chemical equilibrium in a model of abstracted polymers undergoing ligation and scission first introduced by Kauffman [S. A. Kauffman, The Origins of Order (Oxford University Press, New York, 1993), Chap. 7] implied that lifelike systems were most probable when the reaction network was sparse. The model was entirely statistical and took no account of the bond energies or other energetic constraints. Here we report results of an extension of the model to include effects of a finite bonding energy in the model. We studied two conditions: (1) A food set is continuously replenished and the total polymer population is constrained but the system is otherwise isolated and (2) in addition to the constraints in (1) the system is in contact with a finite-temperature heat bath. In each case, detailed balance in the dynamics is guaranteed during the computations by continuous recomputation of a temperature [in case (1)] and of the chemical potential (in both cases) toward which the system is driven by the dynamics. In the isolated case, the probability of reaching a metastable nonequilibrium state in this model depends significantly on the composition of the food set, and the nonequilibrium states satisfying lifelike condition turn out to be at energies and particle numbers consistent with an equilibrium state at high negative temperature. As a function of the sparseness of the reaction network, the lifelike probability is nonmonotonic, as in our previous model, but the maximum probability occurs when the network is less sparse. In the case of contact with a thermal bath at a positive ambient temperature, we identify two types of metastable nonequilibrium states, termed locally and thermally alive, and locally dead and thermally alive, and evaluate their likelihood of appearance, finding maxima at an optimal temperature and an optimal degree of sparseness in the network. We use a Euclidean metric in the space of polymer populations to distinguish these states from one another and from fully equilibrated states. The metric can be used to characterize the degree and type of chemical equilibrium in observed systems, as we illustrate for the proteome of the ribosome.

The USDA Feed the Future Initiative for genetic improvement of African goats: an update on genomic resources and genetic characterization of indigenous breeds

USDA-ARS?s Scientific Manuscript database

Food production systems in Africa depend heavily on the use of locally adapted animals such as goats which are critical to small-scale farmers as they are easier to acquire, maintain, and act as scavengers in sparse pasture and marginal crop regions. Indigenous goat ecotypes have undergone generatio...

Thermal state of permafrost in North America: a contribution to the international polar year

Treesearch

S.L. Smith; V.E. Romanovsky; A.G. Lewkowicz; C.R. Burn; M. Allard; G.D. Clow; K. Yoshikawa; J. Throop

2010-01-01

A snapshot of the thermal state of permafrost in northern North America during the International Polar Year (IPY) was developed using ground temperature data collected from 350 boreholes. More than half these were established during IPY to enhance the network in sparsely monitored regions. The measurement sites span a diverse range of ecoclimatic and geological...

Regularized two-step brain activity reconstruction from spatiotemporal EEG data

NASA Astrophysics Data System (ADS)

Alecu, Teodor I.; Voloshynovskiy, Sviatoslav; Pun, Thierry

2004-10-01

We are aiming at using EEG source localization in the framework of a Brain Computer Interface project. We propose here a new reconstruction procedure, targeting source (or equivalently mental task) differentiation. EEG data can be thought of as a collection of time continuous streams from sparse locations. The measured electric potential on one electrode is the result of the superposition of synchronized synaptic activity from sources in all the brain volume. Consequently, the EEG inverse problem is a highly underdetermined (and ill-posed) problem. Moreover, each source contribution is linear with respect to its amplitude but non-linear with respect to its localization and orientation. In order to overcome these drawbacks we propose a novel two-step inversion procedure. The solution is based on a double scale division of the solution space. The first step uses a coarse discretization and has the sole purpose of globally identifying the active regions, via a sparse approximation algorithm. The second step is applied only on the retained regions and makes use of a fine discretization of the space, aiming at detailing the brain activity. The local configuration of sources is recovered using an iterative stochastic estimator with adaptive joint minimum energy and directional consistency constraints.

Multimodal sparse reconstruction in guided wave imaging of defects in plates

NASA Astrophysics Data System (ADS)

Golato, Andrew; Santhanam, Sridhar; Ahmad, Fauzia; Amin, Moeness G.

2016-07-01

A multimodal sparse reconstruction approach is proposed for localizing defects in thin plates in Lamb wave-based structural health monitoring. The proposed approach exploits both the sparsity of the defects and the multimodal nature of Lamb wave propagation in plates. It takes into account the variation of the defects' aspect angles across the various transducer pairs. At low operating frequencies, only the fundamental symmetric and antisymmetric Lamb modes emanate from a transmitting transducer. Asymmetric defects scatter these modes and spawn additional converted fundamental modes. Propagation models are developed for each of these scattered and spawned modes arriving at the various receiving transducers. This enables the construction of modal dictionary matrices spanning a two-dimensional array of pixels representing potential defect locations in the region of interest. Reconstruction of the region of interest is achieved by inverting the resulting linear model using the group sparsity constraint, where the groups extend across the various transducer pairs and the different modes. The effectiveness of the proposed approach is established with finite-element scattering simulations of the fundamental Lamb wave modes by crack-like defects in a plate. The approach is subsequently validated with experimental results obtained from an aluminum plate with asymmetric defects.

Data Sparsity Considerations in Climate Impact Analysis for the Water Sector (Invited)

NASA Astrophysics Data System (ADS)

Asante, K. O.; Khimsara, P.; Chan, A.

2013-12-01

Scientists and planners are helping governments and communities around the world to prepare for climate change by performing local impact studies and developing adaptation plans. Most studies begin by analyzing global climate models outputs to estimate the magnitude of projected change, assessing vulnerabilities and proposing adaptation measures. In these studies, climate projections from the Intergovernmental Panel on Climate Change (IPCC) Data Distribution Centre (DDC) are either used directly or downscaled using regional models. Since climate projections cover the entire global, climate change analysis can be performed for any location. However, selection of climate projections for use in historically data sparse regions presents special challenges. Key questions arise about the impact of historical data sparsity on quality of climate projections, spatial consistency of results and suitability for applications such as water resource planning. In this paper, a water-sector climate study conducted in a data-rich setting in California is compared to a similar study conducted a data-sparse setting in Mozambique. The challenges of selecting projections, performing analysis and interpreting the results for climate adaption planning are compared to illustrate the decision process and challenges encountered in these two very different settings.

Sparse Matrices in MATLAB: Design and Implementation

NASA Technical Reports Server (NTRS)

Gilbert, John R.; Moler, Cleve; Schreiber, Robert

1992-01-01

The matrix computation language and environment MATLAB is extended to include sparse matrix storage and operations. The only change to the outward appearance of the MATLAB language is a pair of commands to create full or sparse matrices. Nearly all the operations of MATLAB now apply equally to full or sparse matrices, without any explicit action by the user. The sparse data structure represents a matrix in space proportional to the number of nonzero entries, and most of the operations compute sparse results in time proportional to the number of arithmetic operations on nonzeros.

Development and application of a novel method for regional assessment of groundwater contamination risk in the Songhua River Basin.

PubMed

Nixdorf, Erik; Sun, Yuanyuan; Lin, Mao; Kolditz, Olaf

2017-12-15

The main objective of this study is to quantify the groundwater contamination risk of Songhua River Basin by applying a novel approach of integrating public datasets, web services and numerical modelling techniques. To our knowledge, this study is the first to establish groundwater risk maps for the entire Songhua River Basin, one of the largest and most contamination-endangered river basins in China. Index-based groundwater risk maps were created with GIS tools at a spatial resolution of 30arc sec by combining the results of groundwater vulnerability and hazard assessment. Groundwater vulnerability was evaluated using the DRASTIC index method based on public datasets at the highest available resolution in combination with numerical groundwater modelling. As a novel approach to overcome data scarcity at large scales, a web mapping service based data query was applied to obtain an inventory for potential hazardous sites within the basin. The groundwater risk assessment demonstrated that <1% of Songhua River Basin is at high or very high contamination risk. These areas were mainly located in the vast plain areas with hotspots particularly in the Changchun metropolitan area. Moreover, groundwater levels and pollution point sources were found to play a significantly larger impact in assessing these areas than originally assumed by the index scheme. Moderate contamination risk was assigned to 27% of the aquifers, predominantly associated with less densely populated agricultural areas. However, the majority of aquifer area in the sparsely populated mountain ranges displayed low groundwater contamination risk. Sensitivity analysis demonstrated that this novel method is valid for regional assessments of groundwater contamination risk. Despite limitations in resolution and input data consistency, the obtained groundwater contamination risk maps will be beneficial for regional and local decision-making processes with regard to groundwater protection measures, particularly if other data availability is limited. Copyright © 2017 Elsevier B.V. All rights reserved.

Storage of sparse files using parallel log-structured file system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bent, John M.; Faibish, Sorin; Grider, Gary

A sparse file is stored without holes by storing a data portion of the sparse file using a parallel log-structured file system; and generating an index entry for the data portion, the index entry comprising a logical offset, physical offset and length of the data portion. The holes can be restored to the sparse file upon a reading of the sparse file. The data portion can be stored at a logical end of the sparse file. Additional storage efficiency can optionally be achieved by (i) detecting a write pattern for a plurality of the data portions and generating a singlemore » patterned index entry for the plurality of the patterned data portions; and/or (ii) storing the patterned index entries for a plurality of the sparse files in a single directory, wherein each entry in the single directory comprises an identifier of a corresponding sparse file.« less

Organization of Educational Programs in Sparsely Settled Areas of the World.

ERIC Educational Resources Information Center

Edington, Everett D.

Only one-third of the world's population presently lives in countries where as much as a complete primary education is provided for children in rural areas. While the number of one-teacher schools in the United States has decreased from 148,711 in 1930 to 15,018 in 1961, a similar trend is not taking place as rapidly in other areas of the world,…

Defining Doctrine for Transitions, a Case Study in Post-MCO Security

DTIC Science & Technology

2005-04-28

22 Ibid, 10. 11 to huge numbers of unemployed men throughout the nation. Local military governments used available funds to pay them for... psychic exhaustion and despair.31 Some die-hard Japanese resisters who occupied sparsely populated areas in the mountains of Japan were not captured...demise. The subsequent addition of several million unemployed men to the populace created even greater economic stress on an already stressed

International Conference on Education in Sparsely Populated Rural Areas (7th, Golspie High School, County of Sutherland, Scotland, July 9-17, 1974). Interskola Golspie '74 Report.

ERIC Educational Resources Information Center

Aberdeen Coll. of Education (Scotland).

Papers from a conference series initiated in the Aberdeen College of Education in 1968 and recently held in Golspie, Scotland (July 1974), address policy oriented recommendations relative to rural education. This conference report is intended to serve as a useful source of ideas; as background information on international rural educational…

Measuring and Meeting the Needs of Children and Families in the Community: Survey of Parents on a Housing Estate in Dublin, Ireland

ERIC Educational Resources Information Center

Axford, Nick; Whear, Rebecca

2008-01-01

The methodological and empirical literature on measuring the need of child populations is sparse. What does exist is more orientated towards children in receipt of non-universal or specialist services, overlooking those children with similar needs who are not in contact with such services. Further, there is a tendency often for need analyses not…

Learning Sparse Feature Representations using Probabilistic Quadtrees and Deep Belief Nets

DTIC Science & Technology

2015-04-24

Feature Representations usingProbabilistic Quadtrees and Deep Belief Nets Learning sparse feature representations is a useful instru- ment for solving an...novel framework for the classifi cation of handwritten digits that learns sparse representations using probabilistic quadtrees and Deep Belief Nets... Learning Sparse Feature Representations usingProbabilistic Quadtrees and Deep Belief Nets Report Title Learning sparse feature representations is a useful

Mechanical stretch triggers rapid epithelial cell division through Piezo1.

PubMed

Gudipaty, S A; Lindblom, J; Loftus, P D; Redd, M J; Edes, K; Davey, C F; Krishnegowda, V; Rosenblatt, J

2017-03-02

Despite acting as a barrier for the organs they encase, epithelial cells turn over at some of the fastest rates in the body. However, epithelial cell division must be tightly linked to cell death to preserve barrier function and prevent tumour formation. How does the number of dying cells match those dividing to maintain constant numbers? When epithelial cells become too crowded, they activate the stretch-activated channel Piezo1 to trigger extrusion of cells that later die. However, it is unclear how epithelial cell division is controlled to balance cell death at the steady state. Here we show that mammalian epithelial cell division occurs in regions of low cell density where cells are stretched. By experimentally stretching epithelia, we find that mechanical stretch itself rapidly stimulates cell division through activation of the Piezo1 channel. To stimulate cell division, stretch triggers cells that are paused in early G2 phase to activate calcium-dependent phosphorylation of ERK1/2, thereby activating the cyclin B transcription that is necessary to drive cells into mitosis. Although both epithelial cell division and cell extrusion require Piezo1 at the steady state, the type of mechanical force controls the outcome: stretch induces cell division, whereas crowding induces extrusion. How Piezo1-dependent calcium transients activate two opposing processes may depend on where and how Piezo1 is activated, as it accumulates in different subcellular sites with increasing cell density. In sparse epithelial regions in which cells divide, Piezo1 localizes to the plasma membrane and cytoplasm, whereas in dense regions in which cells extrude, it forms large cytoplasmic aggregates. Because Piezo1 senses both mechanical crowding and stretch, it may act as a homeostatic sensor to control epithelial cell numbers, triggering extrusion and apoptosis in crowded regions and cell division in sparse regions.

A framework for streamflow prediction in the world's most severely data-limited regions: Test of applicability and performance in a poorly-gauged region of China

NASA Astrophysics Data System (ADS)

Alipour, M. H.; Kibler, Kelly M.

2018-02-01

A framework methodology is proposed for streamflow prediction in poorly-gauged rivers located within large-scale regions of sparse hydrometeorologic observation. A multi-criteria model evaluation is developed to select models that balance runoff efficiency with selection of accurate parameter values. Sparse observed data are supplemented by uncertain or low-resolution information, incorporated as 'soft' data, to estimate parameter values a priori. Model performance is tested in two catchments within a data-poor region of southwestern China, and results are compared to models selected using alternative calibration methods. While all models perform consistently with respect to runoff efficiency (NSE range of 0.67-0.78), models selected using the proposed multi-objective method may incorporate more representative parameter values than those selected by traditional calibration. Notably, parameter values estimated by the proposed method resonate with direct estimates of catchment subsurface storage capacity (parameter residuals of 20 and 61 mm for maximum soil moisture capacity (Cmax), and 0.91 and 0.48 for soil moisture distribution shape factor (B); where a parameter residual is equal to the centroid of a soft parameter value minus the calibrated parameter value). A model more traditionally calibrated to observed data only (single-objective model) estimates a much lower soil moisture capacity (residuals of Cmax = 475 and 518 mm and B = 1.24 and 0.7). A constrained single-objective model also underestimates maximum soil moisture capacity relative to a priori estimates (residuals of Cmax = 246 and 289 mm). The proposed method may allow managers to more confidently transfer calibrated models to ungauged catchments for streamflow predictions, even in the world's most data-limited regions.

An innovative approach to address homelessness in regional Australia: Participant evaluation of a co-payment model.

PubMed

Jacups, S; Rogerson, B; Kinchin, I

2018-03-01

Homelessness is not only about lack of secure housing, it is sometimes caused by simple reasons such as lack of money to travel home. The purpose of this study was to investigate whether the participant co-funded assistance program ('Return to Country' [R2C]), when offered to low socio-economic individuals experiencing homelessness, represented an effective use of scarce resources. In northern Australia, a remote and sparsely populated area, Indigenous persons who travel to regional centres cannot always afford airfares home; they therefore become stranded away from their 'country' leading to rapidly deteriorating health, isolation and separation from family and kin. The R2C program was designed to facilitate travel for persons who were temporarily stranded and were voluntarily seeking to return home. The program provided operational support and funding (participants co-funded AU$99) to participants to return home. Using a descriptive, case series research design, university researchers independently evaluated the R2C program using semi-structured interviews with 37 participants. An investment of AU$970 per participant in the program with partial co-payment was associated with high participant acceptability and satisfaction in-line with harms reduction around substance and criminal abuse, which is suggestive of long-term success for the model. Findings from this study can contribute to the development of best practice guidelines and policies that specifically address the needs of this unique population of stranded persons, who are seeking to return home. The acceptance of the co-payment model can be adopted by policy makers involved in homelessness prevention in other locations in Australia or internationally as an add-on service provision to mainstream housing support. Copyright © 2017 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.