EFFECTS OF VERTICAL-LAYER STRUCTURE AND BOUNDARY CONDITIONS ON CMAQ-V4.5 AND V4.6 MODELS

EPA Science Inventory

This work is aimed at determining whether the increased vertical layers in CMAQ provides substantially improved model performance and assess whether using the spatially and temporally varying boundary conditions from GEOS-CHEM offer improved model performance as compared to the d...

The Construct of the Multisensory Temporal Binding Window and its Dysregulation in Developmental Disabilities

PubMed Central

Wallace, Mark T.; Stevenson, Ryan A.

2014-01-01

Behavior, perception and cognition are strongly shaped by the synthesis of information across the different sensory modalities. Such multisensory integration often results in performance and perceptual benefits that reflect the additional information conferred by having cues from multiple senses providing redundant or complementary information. The spatial and temporal relationships of these cues provide powerful statistical information about how these cues should be integrated or “bound” in order to create a unified perceptual representation. Much recent work has examined the temporal factors that are integral in multisensory processing, with many focused on the construct of the multisensory temporal binding window – the epoch of time within which stimuli from different modalities is likely to be integrated and perceptually bound. Emerging evidence suggests that this temporal window is altered in a series of neurodevelopmental disorders, including autism, dyslexia and schizophrenia. In addition to their role in sensory processing, these deficits in multisensory temporal function may play an important role in the perceptual and cognitive weaknesses that characterize these clinical disorders. Within this context, focus on improving the acuity of multisensory temporal function may have important implications for the amelioration of the “higher-order” deficits that serve as the defining features of these disorders. PMID:25128432

Neocortical Temporal Lobe Epilepsy

PubMed Central

Bercovici, Eduard; Kumar, Balagobal Santosh; Mirsattari, Seyed M.

2012-01-01

Complex partial seizures (CPSs) can present with various semiologies, while mesial temporal lobe epilepsy (mTLE) is a well-recognized cause of CPS, neocortical temporal lobe epilepsy (nTLE) albeit being less common is increasingly recognized as separate disease entity. Differentiating the two remains a challenge for epileptologists as many symptoms overlap due to reciprocal connections between the neocortical and the mesial temporal regions. Various studies have attempted to correctly localize the seizure focus in nTLE as patients with this disorder may benefit from surgery. While earlier work predicted poor outcomes in this population, recent work challenges those ideas yielding good outcomes in part due to better localization using improved anatomical and functional techniques. This paper provides a comprehensive review of the diagnostic workup, particularly the application of recent advances in electroencephalography and functional brain imaging, in neocortical temporal lobe epilepsy. PMID:22953057

Temporal resolution improvement using PICCS in MDCT cardiac imaging

PubMed Central

Chen, Guang-Hong; Tang, Jie; Hsieh, Jiang

2009-01-01

The current paradigm for temporal resolution improvement is to add more source-detector units and∕or increase the gantry rotation speed. The purpose of this article is to present an innovative alternative method to potentially improve temporal resolution by approximately a factor of 2 for all MDCT scanners without requiring hardware modification. The central enabling technology is a most recently developed image reconstruction method: Prior image constrained compressed sensing (PICCS). Using the method, cardiac CT images can be accurately reconstructed using the projection data acquired in an angular range of about 120°, which is roughly 50% of the standard short-scan angular range (∼240° for an MDCT scanner). As a result, the temporal resolution of MDCT cardiac imaging can be universally improved by approximately a factor of 2. In order to validate the proposed method, two in vivo animal experiments were conducted using a state-of-the-art 64-slice CT scanner (GE Healthcare, Waukesha, WI) at different gantry rotation times and different heart rates. One animal was scanned at heart rate of 83 beats per minute (bpm) using 400 ms gantry rotation time and the second animal was scanned at 94 bpm using 350 ms gantry rotation time, respectively. Cardiac coronary CT imaging can be successfully performed at high heart rates using a single-source MDCT scanner and projection data from a single heart beat with gantry rotation times of 400 and 350 ms. Using the proposed PICCS method, the temporal resolution of cardiac CT imaging can be effectively improved by approximately a factor of 2 without modifying any scanner hardware. This potentially provides a new method for single-source MDCT scanners to achieve reliable coronary CT imaging for patients at higher heart rates than the current heart rate limit of 70 bpm without using the well-known multisegment FBP reconstruction algorithm. This method also enables dual-source MDCT scanner to achieve higher temporal resolution without further hardware modifications. PMID:19610302

Temporal resolution improvement using PICCS in MDCT cardiac imaging.

PubMed

Chen, Guang-Hong; Tang, Jie; Hsieh, Jiang

2009-06-01

The current paradigm for temporal resolution improvement is to add more source-detector units and/or increase the gantry rotation speed. The purpose of this article is to present an innovative alternative method to potentially improve temporal resolution by approximately a factor of 2 for all MDCT scanners without requiring hardware modification. The central enabling technology is a most recently developed image reconstruction method: Prior image constrained compressed sensing (PICCS). Using the method, cardiac CT images can be accurately reconstructed using the projection data acquired in an angular range of about 120 degrees, which is roughly 50% of the standard short-scan angular range (approximately 240 degrees for an MDCT scanner). As a result, the temporal resolution of MDCT cardiac imaging can be universally improved by approximately a factor of 2. In order to validate the proposed method, two in vivo animal experiments were conducted using a state-of-the-art 64-slice CT scanner (GE Healthcare, Waukesha, WI) at different gantry rotation times and different heart rates. One animal was scanned at heart rate of 83 beats per minute (bpm) using 400 ms gantry rotation time and the second animal was scanned at 94 bpm using 350 ms gantry rotation time, respectively. Cardiac coronary CT imaging can be successfully performed at high heart rates using a single-source MDCT scanner and projection data from a single heart beat with gantry rotation times of 400 and 350 ms. Using the proposed PICCS method, the temporal resolution of cardiac CT imaging can be effectively improved by approximately a factor of 2 without modifying any scanner hardware. This potentially provides a new method for single-source MDCT scanners to achieve reliable coronary CT imaging for patients at higher heart rates than the current heart rate limit of 70 bpm without using the well-known multisegment FBP reconstruction algorithm. This method also enables dual-source MDCT scanner to achieve higher temporal resolution without further hardware modifications.

The use of quantile regression to forecast higher than expected respiratory deaths in a daily time series: a study of New York City data 1987-2000.

PubMed

Soyiri, Ireneous N; Reidpath, Daniel D

2013-01-01

Forecasting higher than expected numbers of health events provides potentially valuable insights in its own right, and may contribute to health services management and syndromic surveillance. This study investigates the use of quantile regression to predict higher than expected respiratory deaths. Data taken from 70,830 deaths occurring in New York were used. Temporal, weather and air quality measures were fitted using quantile regression at the 90th-percentile with half the data (in-sample). Four QR models were fitted: an unconditional model predicting the 90th-percentile of deaths (Model 1), a seasonal/temporal (Model 2), a seasonal, temporal plus lags of weather and air quality (Model 3), and a seasonal, temporal model with 7-day moving averages of weather and air quality. Models were cross-validated with the out of sample data. Performance was measured as proportionate reduction in weighted sum of absolute deviations by a conditional, over unconditional models; i.e., the coefficient of determination (R1). The coefficient of determination showed an improvement over the unconditional model between 0.16 and 0.19. The greatest improvement in predictive and forecasting accuracy of daily mortality was associated with the inclusion of seasonal and temporal predictors (Model 2). No gains were made in the predictive models with the addition of weather and air quality predictors (Models 3 and 4). However, forecasting models that included weather and air quality predictors performed slightly better than the seasonal and temporal model alone (i.e., Model 3 > Model 4 > Model 2) This study provided a new approach to predict higher than expected numbers of respiratory related-deaths. The approach, while promising, has limitations and should be treated at this stage as a proof of concept.

The Use of Quantile Regression to Forecast Higher Than Expected Respiratory Deaths in a Daily Time Series: A Study of New York City Data 1987-2000

PubMed Central

Soyiri, Ireneous N.; Reidpath, Daniel D.

2013-01-01

Forecasting higher than expected numbers of health events provides potentially valuable insights in its own right, and may contribute to health services management and syndromic surveillance. This study investigates the use of quantile regression to predict higher than expected respiratory deaths. Data taken from 70,830 deaths occurring in New York were used. Temporal, weather and air quality measures were fitted using quantile regression at the 90th-percentile with half the data (in-sample). Four QR models were fitted: an unconditional model predicting the 90th-percentile of deaths (Model 1), a seasonal / temporal (Model 2), a seasonal, temporal plus lags of weather and air quality (Model 3), and a seasonal, temporal model with 7-day moving averages of weather and air quality. Models were cross-validated with the out of sample data. Performance was measured as proportionate reduction in weighted sum of absolute deviations by a conditional, over unconditional models; i.e., the coefficient of determination (R1). The coefficient of determination showed an improvement over the unconditional model between 0.16 and 0.19. The greatest improvement in predictive and forecasting accuracy of daily mortality was associated with the inclusion of seasonal and temporal predictors (Model 2). No gains were made in the predictive models with the addition of weather and air quality predictors (Models 3 and 4). However, forecasting models that included weather and air quality predictors performed slightly better than the seasonal and temporal model alone (i.e., Model 3 > Model 4 > Model 2) This study provided a new approach to predict higher than expected numbers of respiratory related-deaths. The approach, while promising, has limitations and should be treated at this stage as a proof of concept. PMID:24147122

Graph regularized nonnegative matrix factorization for temporal link prediction in dynamic networks

NASA Astrophysics Data System (ADS)

Ma, Xiaoke; Sun, Penggang; Wang, Yu

2018-04-01

Many networks derived from society and nature are temporal and incomplete. The temporal link prediction problem in networks is to predict links at time T + 1 based on a given temporal network from time 1 to T, which is essential to important applications. The current algorithms either predict the temporal links by collapsing the dynamic networks or collapsing features derived from each network, which are criticized for ignoring the connection among slices. to overcome the issue, we propose a novel graph regularized nonnegative matrix factorization algorithm (GrNMF) for the temporal link prediction problem without collapsing the dynamic networks. To obtain the feature for each network from 1 to t, GrNMF factorizes the matrix associated with networks by setting the rest networks as regularization, which provides a better way to characterize the topological information of temporal links. Then, the GrNMF algorithm collapses the feature matrices to predict temporal links. Compared with state-of-the-art methods, the proposed algorithm exhibits significantly improved accuracy by avoiding the collapse of temporal networks. Experimental results of a number of artificial and real temporal networks illustrate that the proposed method is not only more accurate but also more robust than state-of-the-art approaches.

Temporally coherent 4D video segmentation for teleconferencing

NASA Astrophysics Data System (ADS)

Ehmann, Jana; Guleryuz, Onur G.

2013-09-01

We develop an algorithm for 4-D (RGB+Depth) video segmentation targeting immersive teleconferencing ap- plications on emerging mobile devices. Our algorithm extracts users from their environments and places them onto virtual backgrounds similar to green-screening. The virtual backgrounds increase immersion and interac- tivity, relieving the users of the system from distractions caused by disparate environments. Commodity depth sensors, while providing useful information for segmentation, result in noisy depth maps with a large number of missing depth values. By combining depth and RGB information, our work signi¯cantly improves the other- wise very coarse segmentation. Further imposing temporal coherence yields compositions where the foregrounds seamlessly blend with the virtual backgrounds with minimal °icker and other artifacts. We achieve said improve- ments by correcting the missing information in depth maps before fast RGB-based segmentation, which operates in conjunction with temporal coherence. Simulation results indicate the e±cacy of the proposed system in video conferencing scenarios.

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

Yuan, Chris, E-mail: cyuan@uwm.edu; Wang, Endong; Zhai, Qiang

Temporal homogeneity of inventory data is one of the major problems in life cycle assessment (LCA). Addressing temporal homogeneity of life cycle inventory data is important in reducing the uncertainties and improving the reliability of LCA results. This paper attempts to present a critical review and discussion on the fundamental issues of temporal homogeneity in conventional LCA and propose a theoretical framework for temporal discounting in LCA. Theoretical perspectives for temporal discounting in life cycle inventory analysis are discussed first based on the key elements of a scientific mechanism for temporal discounting. Then generic procedures for performing temporal discounting inmore » LCA is derived and proposed based on the nature of the LCA method and the identified key elements of a scientific temporal discounting method. A five-step framework is proposed and reported in details based on the technical methods and procedures needed to perform a temporal discounting in life cycle inventory analysis. Challenges and possible solutions are also identified and discussed for the technical procedure and scientific accomplishment of each step within the framework. - Highlights: • A critical review for temporal homogeneity problem of life cycle inventory data • A theoretical framework for performing temporal discounting on inventory data • Methods provided to accomplish each step of the temporal discounting framework.« less

An Improved STARFM with Help of an Unmixing-Based Method to Generate High Spatial and Temporal Resolution Remote Sensing Data in Complex Heterogeneous Regions.

PubMed

Xie, Dengfeng; Zhang, Jinshui; Zhu, Xiufang; Pan, Yaozhong; Liu, Hongli; Yuan, Zhoumiqi; Yun, Ya

2016-02-05

Remote sensing technology plays an important role in monitoring rapid changes of the Earth's surface. However, sensors that can simultaneously provide satellite images with both high temporal and spatial resolution haven't been designed yet. This paper proposes an improved spatial and temporal adaptive reflectance fusion model (STARFM) with the help of an Unmixing-based method (USTARFM) to generate the high spatial and temporal data needed for the study of heterogeneous areas. The results showed that the USTARFM had higher accuracy than STARFM methods in two aspects of analysis: individual bands and of heterogeneity analysis. Taking the predicted NIR band as an example, the correlation coefficients (r) for the USTARFM, STARFM and unmixing methods were 0.96, 0.95, 0.90, respectively (p-value < 0.001); Root Mean Square Error (RMSE) values were 0.0245, 0.0300, 0.0401, respectively; and ERGAS values were 0.5416, 0.6507, 0.8737, respectively. The USTARM showed consistently higher performance than STARM when the degree of heterogeneity ranged from 2 to 10, highlighting that the use of this method provides the capacity to solve the data fusion problems faced when using STARFM. Additionally, the USTARFM method could help researchers achieve better performance than STARFM at a smaller window size from its heterogeneous land surface quantitative representation.

A spatial-temporal system for dynamic cadastral management.

PubMed

Nan, Liu; Renyi, Liu; Guangliang, Zhu; Jiong, Xie

2006-03-01

A practical spatio-temporal database (STDB) technique for dynamic urban land management is presented. One of the STDB models, the expanded model of Base State with Amendments (BSA), is selected as the basis for developing the dynamic cadastral management technique. Two approaches, the Section Fast Indexing (SFI) and the Storage Factors of Variable Granularity (SFVG), are used to improve the efficiency of the BSA model. Both spatial graphic data and attribute data, through a succinct engine, are stored in standard relational database management systems (RDBMS) for the actual implementation of the BSA model. The spatio-temporal database is divided into three interdependent sub-databases: present DB, history DB and the procedures-tracing DB. The efficiency of database operation is improved by the database connection in the bottom layer of the Microsoft SQL Server. The spatio-temporal system can be provided at a low-cost while satisfying the basic needs of urban land management in China. The approaches presented in this paper may also be of significance to countries where land patterns change frequently or to agencies where financial resources are limited.

Spatio-temporal water quality mapping from satellite images using geographically and temporally weighted regression

NASA Astrophysics Data System (ADS)

Chu, Hone-Jay; Kong, Shish-Jeng; Chang, Chih-Hua

2018-03-01

The turbidity (TB) of a water body varies with time and space. Water quality is traditionally estimated via linear regression based on satellite images. However, estimating and mapping water quality require a spatio-temporal nonstationary model, while TB mapping necessitates the use of geographically and temporally weighted regression (GTWR) and geographically weighted regression (GWR) models, both of which are more precise than linear regression. Given the temporal nonstationary models for mapping water quality, GTWR offers the best option for estimating regional water quality. Compared with GWR, GTWR provides highly reliable information for water quality mapping, boasts a relatively high goodness of fit, improves the explanation of variance from 44% to 87%, and shows a sufficient space-time explanatory power. The seasonal patterns of TB and the main spatial patterns of TB variability can be identified using the estimated TB maps from GTWR and by conducting an empirical orthogonal function (EOF) analysis.

Modeling emissions for three-dimensional atmospheric chemistry transport models.

PubMed

Matthias, Volker; Arndt, Jan A; Aulinger, Armin; Bieser, Johannes; Denier Van Der Gon, Hugo; Kranenburg, Richard; Kuenen, Jeroen; Neumann, Daniel; Pouliot, George; Quante, Markus

2018-01-24

Poor air quality is still a threat for human health in many parts of the world. In order to assess measures for emission reductions and improved air quality, three-dimensional atmospheric chemistry transport modeling systems are used in numerous research institutions and public authorities. These models need accurate emission data in appropriate spatial and temporal resolution as input. This paper reviews the most widely used emission inventories on global and regional scale and looks into the methods used to make the inventory data model ready. Shortcomings of using standard temporal profiles for each emission sector are discussed and new methods to improve the spatio-temporal distribution of the emissions are presented. These methods are often neither top-down nor bottom-up approaches but can be seen as hybrid methods that use detailed information about the emission process to derive spatially varying temporal emission profiles. These profiles are subsequently used to distribute bulk emissions like national totals on appropriate grids. The wide area of natural emissions is also summarized and the calculation methods are described. Almost all types of natural emissions depend on meteorological information, which is why they are highly variable in time and space and frequently calculated within the chemistry transport models themselves. The paper closes with an outlook for new ways to improve model ready emission data, for example by using external databases about road traffic flow or satellite data to determine actual land use or leaf area. In a world where emission patterns change rapidly, it seems appropriate to use new types of statistical and observational data to create detailed emission data sets and keep emission inventories up-to-date. Emission data is probably the most important input for chemistry transport model (CTM) systems. It needs to be provided in high temporal and spatial resolution and on a grid that is in agreement with the CTM grid. Simple methods to distribute the emissions in time and space need to be replaced by sophisticated emission models in order to improve the CTM results. New methods, e.g. for ammonia emissions, provide grid cell dependent temporal profiles. In the future, large data fields from traffic observations or satellite observations could be used for more detailed emission data.

"Transformation Tuesday": Temporal context and post valence influence the provision of social support on social media.

PubMed

Vogel, Erin A; Rose, Jason P; Crane, Chantal

2018-01-01

Social network sites (SNSs) such as Facebook have become integral in the development and maintenance of interpersonal relationships. Users of SNSs seek social support and validation, often using posts that illustrate how they have changed over time. The purpose of the present research is to examine how the valence and temporal context of an SNS post affect the likelihood of other users providing social support. Participants viewed hypothetical SNS posts and reported their intentions to provide social support to the users. Results revealed that participants were more likely to provide social support for posts that were positive and included temporal context (i.e., depicted improvement over time; Study 1). Furthermore, this research suggests that visual representations of change over time are needed to elicit social support (Study 2). Results are discussed in terms of their practical implications for SNS users and theoretical implications for the literature on social support and social media.

An implicit spatial and high-order temporal finite difference scheme for 2D acoustic modelling

NASA Astrophysics Data System (ADS)

Wang, Enjiang; Liu, Yang

2018-01-01

The finite difference (FD) method exhibits great superiority over other numerical methods due to its easy implementation and small computational requirement. We propose an effective FD method, characterised by implicit spatial and high-order temporal schemes, to reduce both the temporal and spatial dispersions simultaneously. For the temporal derivative, apart from the conventional second-order FD approximation, a special rhombus FD scheme is included to reach high-order accuracy in time. Compared with the Lax-Wendroff FD scheme, this scheme can achieve nearly the same temporal accuracy but requires less floating-point operation times and thus less computational cost when the same operator length is adopted. For the spatial derivatives, we adopt the implicit FD scheme to improve the spatial accuracy. Apart from the existing Taylor series expansion-based FD coefficients, we derive the least square optimisation based implicit spatial FD coefficients. Dispersion analysis and modelling examples demonstrate that, our proposed method can effectively decrease both the temporal and spatial dispersions, thus can provide more accurate wavefields.

Spatial-Temporal Data Collection with Compressive Sensing in Mobile Sensor Networks

PubMed Central

Li, Jiayin; Guo, Wenzhong; Chen, Zhonghui; Xiong, Neal

2017-01-01

Compressive sensing (CS) provides an energy-efficient paradigm for data gathering in wireless sensor networks (WSNs). However, the existing work on spatial-temporal data gathering using compressive sensing only considers either multi-hop relaying based or multiple random walks based approaches. In this paper, we exploit the mobility pattern for spatial-temporal data collection and propose a novel mobile data gathering scheme by employing the Metropolis-Hastings algorithm with delayed acceptance, an improved random walk algorithm for a mobile collector to collect data from a sensing field. The proposed scheme exploits Kronecker compressive sensing (KCS) for spatial-temporal correlation of sensory data by allowing the mobile collector to gather temporal compressive measurements from a small subset of randomly selected nodes along a random routing path. More importantly, from the theoretical perspective we prove that the equivalent sensing matrix constructed from the proposed scheme for spatial-temporal compressible signal can satisfy the property of KCS models. The simulation results demonstrate that the proposed scheme can not only significantly reduce communication cost but also improve recovery accuracy for mobile data gathering compared to the other existing schemes. In particular, we also show that the proposed scheme is robust in unreliable wireless environment under various packet losses. All this indicates that the proposed scheme can be an efficient alternative for data gathering application in WSNs. PMID:29117152

Spatial-Temporal Data Collection with Compressive Sensing in Mobile Sensor Networks.

PubMed

Zheng, Haifeng; Li, Jiayin; Feng, Xinxin; Guo, Wenzhong; Chen, Zhonghui; Xiong, Neal

2017-11-08

Compressive sensing (CS) provides an energy-efficient paradigm for data gathering in wireless sensor networks (WSNs). However, the existing work on spatial-temporal data gathering using compressive sensing only considers either multi-hop relaying based or multiple random walks based approaches. In this paper, we exploit the mobility pattern for spatial-temporal data collection and propose a novel mobile data gathering scheme by employing the Metropolis-Hastings algorithm with delayed acceptance, an improved random walk algorithm for a mobile collector to collect data from a sensing field. The proposed scheme exploits Kronecker compressive sensing (KCS) for spatial-temporal correlation of sensory data by allowing the mobile collector to gather temporal compressive measurements from a small subset of randomly selected nodes along a random routing path. More importantly, from the theoretical perspective we prove that the equivalent sensing matrix constructed from the proposed scheme for spatial-temporal compressible signal can satisfy the property of KCS models. The simulation results demonstrate that the proposed scheme can not only significantly reduce communication cost but also improve recovery accuracy for mobile data gathering compared to the other existing schemes. In particular, we also show that the proposed scheme is robust in unreliable wireless environment under various packet losses. All this indicates that the proposed scheme can be an efficient alternative for data gathering application in WSNs .

Water Quality Sensing and Spatio-Temporal Monitoring Structure with Autocorrelation Kernel Methods.

PubMed

Vizcaíno, Iván P; Carrera, Enrique V; Muñoz-Romero, Sergio; Cumbal, Luis H; Rojo-Álvarez, José Luis

2017-10-16

Pollution on water resources is usually analyzed with monitoring campaigns, which consist of programmed sampling, measurement, and recording of the most representative water quality parameters. These campaign measurements yields a non-uniform spatio-temporal sampled data structure to characterize complex dynamics phenomena. In this work, we propose an enhanced statistical interpolation method to provide water quality managers with statistically interpolated representations of spatial-temporal dynamics. Specifically, our proposal makes efficient use of the a priori available information of the quality parameter measurements through Support Vector Regression (SVR) based on Mercer's kernels. The methods are benchmarked against previously proposed methods in three segments of the Machángara River and one segment of the San Pedro River in Ecuador, and their different dynamics are shown by statistically interpolated spatial-temporal maps. The best interpolation performance in terms of mean absolute error was the SVR with Mercer's kernel given by either the Mahalanobis spatial-temporal covariance matrix or by the bivariate estimated autocorrelation function. In particular, the autocorrelation kernel provides with significant improvement of the estimation quality, consistently for all the six water quality variables, which points out the relevance of including a priori knowledge of the problem.

Water Quality Sensing and Spatio-Temporal Monitoring Structure with Autocorrelation Kernel Methods

PubMed Central

Vizcaíno, Iván P.; Muñoz-Romero, Sergio; Cumbal, Luis H.

2017-01-01

Pollution on water resources is usually analyzed with monitoring campaigns, which consist of programmed sampling, measurement, and recording of the most representative water quality parameters. These campaign measurements yields a non-uniform spatio-temporal sampled data structure to characterize complex dynamics phenomena. In this work, we propose an enhanced statistical interpolation method to provide water quality managers with statistically interpolated representations of spatial-temporal dynamics. Specifically, our proposal makes efficient use of the a priori available information of the quality parameter measurements through Support Vector Regression (SVR) based on Mercer’s kernels. The methods are benchmarked against previously proposed methods in three segments of the Machángara River and one segment of the San Pedro River in Ecuador, and their different dynamics are shown by statistically interpolated spatial-temporal maps. The best interpolation performance in terms of mean absolute error was the SVR with Mercer’s kernel given by either the Mahalanobis spatial-temporal covariance matrix or by the bivariate estimated autocorrelation function. In particular, the autocorrelation kernel provides with significant improvement of the estimation quality, consistently for all the six water quality variables, which points out the relevance of including a priori knowledge of the problem. PMID:29035333

The Improvement of Spatial-Temporal PM2.5 Resolution in Taiwan by Using Data Assimilation Method

NASA Astrophysics Data System (ADS)

Lin, Yong-Qing; Lin, Yuan-Chien

2017-04-01

Forecasting air pollution concentration, e.g., the concentration of PM2.5, is of great significance to protect human health and the environment. Accurate prediction of PM2.5 concentrations is limited in number and the data quality of air quality monitoring stations. The spatial and temporal variations of PM2.5 concentrations are measured by 76 National Air Quality Monitoring Stations (built by the TW-EPA) in Taiwan. The National Air Quality Monitoring Stations are costly and scarce because of the highly precise instrument and their size. Therefore, many places still out of the range of National Air Quality Monitoring Stations. Recently, there are an enormous number of portable air quality sensors called "AirBox" developed jointly by the Taiwan government and a private company. By virtue of its price and portative, the AirBox can provide higher resolution of space-time PM2.5 measurement. However, the spatiotemporal distribution and data quality are different between AirBox and National Air Quality Monitoring Stations. To integrate the heterogeneous PM2.5 data, the data assimilation method should be performed before further analysis. In this study, we propose a data assimilation method based on Ensemble Kalman Filter (EnKF), which is a variant of classic Kalman Filter, can be used to combine additional heterogeneous data from different source while modeling to improve the estimation of spatial-temporal PM2.5 concentration. The assimilation procedure uses the advantages of the two kinds of heterogeneous data and merges them to produce the final estimation. The results have shown that by combining AirBox PM2.5 data as additional information in our model based EnKF can bring the better estimation of spatial-temporal PM2.5 concentration and improve the it's space-time resolution. Under the approach proposed in this study, higher spatial-temporal resoultion could provide a very useful information for a better spatial-temporal data analysis and further environmental management, such as air pollution source localization and micro-scale air pollution analysis. Keywords: PM2.5, Data Assimilation, Ensemble Kalman Filter, Air Quality

Lossless Video Sequence Compression Using Adaptive Prediction

NASA Technical Reports Server (NTRS)

Li, Ying; Sayood, Khalid

2007-01-01

We present an adaptive lossless video compression algorithm based on predictive coding. The proposed algorithm exploits temporal, spatial, and spectral redundancies in a backward adaptive fashion with extremely low side information. The computational complexity is further reduced by using a caching strategy. We also study the relationship between the operational domain for the coder (wavelet or spatial) and the amount of temporal and spatial redundancy in the sequence being encoded. Experimental results show that the proposed scheme provides significant improvements in compression efficiencies.

The auditory basis of language impairments: temporal processing versus processing efficiency hypotheses.

PubMed

Hartley, Douglas E H; Hill, Penny R; Moore, David R

2003-12-01

Claims have been made that language-impaired children have deficits processing rapidly presented or brief sensory information. These claims, known as the 'temporal processing hypothesis', are supported by demonstrations that language-impaired children have excess backward masking (BM). One explanation for these results is that BM is developmentally delayed in these children. However, little was known about how BM normally develops. Recently, we assessed BM in normally developing 6- and 8-year-old children and adults. Results showed that BM thresholds continue to improve over a comparatively protracted period (>10 years old). We also analysed reported deficits in BM in language-impaired and younger children, in terms of a model of temporal resolution. This analysis suggests that poor processing efficiency, rather than deficits in temporal resolution, can account for these results. This 'processing efficiency hypothesis' was recently tested in our laboratory. This experiment measured BM as a function of delays between the tone and the noise in children and adults. Results supported the processing efficiency hypothesis, and suggested that reduced processing efficiency alone could account for differences between adults and children. These findings provide a new perspective on the mechanisms underlying communication disorders, and imply that remediation strategies should be directed towards improving processing efficiency, not temporal resolution.

Learning of Temporal and Spatial Movement Aspects: A Comparison of Four Types of Haptic Control and Concurrent Visual Feedback.

PubMed

Rauter, Georg; Sigrist, Roland; Riener, Robert; Wolf, Peter

2015-01-01

In literature, the effectiveness of haptics for motor learning is controversially discussed. Haptics is believed to be effective for motor learning in general; however, different types of haptic control enhance different movement aspects. Thus, in dependence on the movement aspects of interest, one type of haptic control may be effective whereas another one is not. Therefore, in the current work, it was investigated if and how different types of haptic controllers affect learning of spatial and temporal movement aspects. In particular, haptic controllers that enforce active participation of the participants were expected to improve spatial aspects. Only haptic controllers that provide feedback about the task's velocity profile were expected to improve temporal aspects. In a study on learning a complex trunk-arm rowing task, the effect of training with four different types of haptic control was investigated: position control, path control, adaptive path control, and reactive path control. A fifth group (control) trained with visual concurrent augmented feedback. As hypothesized, the position controller was most effective for learning of temporal movement aspects, while the path controller was most effective in teaching spatial movement aspects of the rowing task. Visual feedback was also effective for learning temporal and spatial movement aspects.

A generalized spatiotemporal covariance model for stationary background in analysis of MEG data.

PubMed

Plis, S M; Schmidt, D M; Jun, S C; Ranken, D M

2006-01-01

Using a noise covariance model based on a single Kronecker product of spatial and temporal covariance in the spatiotemporal analysis of MEG data was demonstrated to provide improvement in the results over that of the commonly used diagonal noise covariance model. In this paper we present a model that is a generalization of all of the above models. It describes models based on a single Kronecker product of spatial and temporal covariance as well as more complicated multi-pair models together with any intermediate form expressed as a sum of Kronecker products of spatial component matrices of reduced rank and their corresponding temporal covariance matrices. The model provides a framework for controlling the tradeoff between the described complexity of the background and computational demand for the analysis using this model. Ways to estimate the value of the parameter controlling this tradeoff are also discussed.

Ultrafast and versatile spectroscopy by temporal Fourier transform

NASA Astrophysics Data System (ADS)

Zhang, Chi; Wei, Xiaoming; Marhic, Michel E.; Wong, Kenneth K. Y.

2014-06-01

One of the most remarkable and useful properties of a spatially converging lens system is its inherent ability to perform the Fourier transform; the same applies for the time-lens system. At the back focal plane of the time-lens, the spectral information can be instantaneously obtained in the time axis. By implementing temporal Fourier transform for spectroscopy applications, this time-lens-based architecture can provide orders of magnitude improvement over the state-of-art spatial-dispersion-based spectroscopy in terms of the frame rate. On the other hand, in addition to the single-lens structure, the multi-lens structures (e.g. telescope or wide-angle scope) will provide very versatile operating conditions. Leveraging the merit of instantaneous response, as well as the flexible lens structure, here we present a 100-MHz frame rate spectroscopy system - the parametric spectro-temporal analyzer (PASTA), which achieves 17 times zoom in/out ratio for different observation ranges.

Characterization of dynamic changes of current source localization based on spatiotemporal fMRI constrained EEG source imaging

NASA Astrophysics Data System (ADS)

Nguyen, Thinh; Potter, Thomas; Grossman, Robert; Zhang, Yingchun

2018-06-01

Objective. Neuroimaging has been employed as a promising approach to advance our understanding of brain networks in both basic and clinical neuroscience. Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) represent two neuroimaging modalities with complementary features; EEG has high temporal resolution and low spatial resolution while fMRI has high spatial resolution and low temporal resolution. Multimodal EEG inverse methods have attempted to capitalize on these properties but have been subjected to localization error. The dynamic brain transition network (DBTN) approach, a spatiotemporal fMRI constrained EEG source imaging method, has recently been developed to address these issues by solving the EEG inverse problem in a Bayesian framework, utilizing fMRI priors in a spatial and temporal variant manner. This paper presents a computer simulation study to provide a detailed characterization of the spatial and temporal accuracy of the DBTN method. Approach. Synthetic EEG data were generated in a series of computer simulations, designed to represent realistic and complex brain activity at superficial and deep sources with highly dynamical activity time-courses. The source reconstruction performance of the DBTN method was tested against the fMRI-constrained minimum norm estimates algorithm (fMRIMNE). The performances of the two inverse methods were evaluated both in terms of spatial and temporal accuracy. Main results. In comparison with the commonly used fMRIMNE method, results showed that the DBTN method produces results with increased spatial and temporal accuracy. The DBTN method also demonstrated the capability to reduce crosstalk in the reconstructed cortical time-course(s) induced by neighboring regions, mitigate depth bias and improve overall localization accuracy. Significance. The improved spatiotemporal accuracy of the reconstruction allows for an improved characterization of complex neural activity. This improvement can be extended to any subsequent brain connectivity analyses used to construct the associated dynamic brain networks.

Improving image-quality of interference fringes of out-of-plane vibration using temporal speckle pattern interferometry and standard deviation for piezoelectric plates.

PubMed

Chien-Ching Ma; Ching-Yuan Chang

2013-07-01

Interferometry provides a high degree of accuracy in the measurement of sub-micrometer deformations; however, the noise associated with experimental measurement undermines the integrity of interference fringes. This study proposes the use of standard deviation in the temporal domain to improve the image quality of patterns obtained from temporal speckle pattern interferometry. The proposed method combines the advantages of both mean and subtractive methods to remove background noise and ambient disturbance simultaneously, resulting in high-resolution images of excellent quality. The out-of-plane vibration of a thin piezoelectric plate is the main focus of this study, providing information useful to the development of energy harvesters. First, ten resonant states were measured using the proposed method, and both mode shape and resonant frequency were investigated. We then rebuilt the phase distribution of the first resonant mode based on the clear interference patterns obtained using the proposed method. This revealed instantaneous deformations in the dynamic characteristics of the resonant state. The proposed method also provides a frequency-sweeping function, facilitating its practical application in the precise measurement of resonant frequency. In addition, the mode shapes and resonant frequencies obtained using the proposed method were recorded and compared with results obtained using finite element method and laser Doppler vibrometery, which demonstrated close agreement.

Temporal and spatial control of gene expression in horticultural crops

PubMed Central

Dutt, Manjul; Dhekney, Sadanand A; Soriano, Leonardo; Kandel, Raju; Grosser, Jude W

2014-01-01

Biotechnology provides plant breeders an additional tool to improve various traits desired by growers and consumers of horticultural crops. It also provides genetic solutions to major problems affecting horticultural crops and can be a means for rapid improvement of a cultivar. With the availability of a number of horticultural genome sequences, it has become relatively easier to utilize these resources to identify DNA sequences for both basic and applied research. Promoters play a key role in plant gene expression and the regulation of gene expression. In recent years, rapid progress has been made on the isolation and evaluation of plant-derived promoters and their use in horticultural crops, as more and more species become amenable to genetic transformation. Our understanding of the tools and techniques of horticultural plant biotechnology has now evolved from a discovery phase to an implementation phase. The availability of a large number of promoters derived from horticultural plants opens up the field for utilization of native sequences and improving crops using precision breeding. In this review, we look at the temporal and spatial control of gene expression in horticultural crops and the usage of a variety of promoters either isolated from horticultural crops or used in horticultural crop improvement. PMID:26504550

A Spatio-Temporally Explicit Random Encounter Model for Large-Scale Population Surveys

PubMed Central

Jousimo, Jussi; Ovaskainen, Otso

2016-01-01

Random encounter models can be used to estimate population abundance from indirect data collected by non-invasive sampling methods, such as track counts or camera-trap data. The classical Formozov–Malyshev–Pereleshin (FMP) estimator converts track counts into an estimate of mean population density, assuming that data on the daily movement distances of the animals are available. We utilize generalized linear models with spatio-temporal error structures to extend the FMP estimator into a flexible Bayesian modelling approach that estimates not only total population size, but also spatio-temporal variation in population density. We also introduce a weighting scheme to estimate density on habitats that are not covered by survey transects, assuming that movement data on a subset of individuals is available. We test the performance of spatio-temporal and temporal approaches by a simulation study mimicking the Finnish winter track count survey. The results illustrate how the spatio-temporal modelling approach is able to borrow information from observations made on neighboring locations and times when estimating population density, and that spatio-temporal and temporal smoothing models can provide improved estimates of total population size compared to the FMP method. PMID:27611683

Deep Temporal Nerve Transfer for Facial Reanimation: Anatomic Dissections and Surgical Case Report.

PubMed

Mahan, Mark A; Sivakumar, Walavan; Weingarten, David; Brown, Justin M

2017-09-08

Facial nerve palsy is a disabling condition that may arise from a variety of injuries or insults and may occur at any point along the nerve or its intracerebral origin. To examine the use of the deep temporal branches of the motor division of the trigeminal nerve for neural reconstruction of the temporal branches of the facial nerve for restoration of active blink and periorbital facial expression. Formalin-fixed human cadaver hemifaces were dissected to identify landmarks for the deep temporal branches and the tension-free coaptation lengths. This technique was then utilized in 1 patient with a history of facial palsy due to a brainstem cavernoma. Sixteen hemifaces were dissected. The middle deep temporal nerve could be consistently identified on the deep side of the temporalis, within 9 to 12 mm posterior to the jugal point of the zygoma. From a lateral approach through the temporalis, the middle deep temporal nerve could be directly coapted to facial temporal branches in all specimens. Our patient has recovered active and independent upper facial muscle contraction, providing the first case report of a distinct distal nerve transfer for upper facial function. The middle deep temporal branches can be readily identified and utilized for facial reanimation. This technique provided a successful reanimation of upper facial muscles with independent activation. Utilizing multiple sources for neurotization of the facial muscles, different potions of the face can be selectively reanimated to reduce the risk of synkinesis and improved control. Copyright © 2017 by the Congress of Neurological Surgeons

The Application of Timing in Therapy of Children and Adults with Language Disorders

PubMed Central

Szelag, Elzbieta; Dacewicz, Anna; Szymaszek, Aneta; Wolak, Tomasz; Senderski, Andrzej; Domitrz, Izabela; Oron, Anna

2015-01-01

A number of evidence revealed a link between temporal information processing (TIP) and language. Both literature data and results of our studies indicated an overlapping of deficient TIP and disordered language, pointing to the existence of an association between these two functions. On this background the new approach is to apply such knowledge in therapy of patients suffering from language disorders. In two studies we asked the following questions: (1) can the temporal training reduce language deficits in aphasic patients (Study 1) or in children with specific language impairment (SLI, Study 2)? (2) can such training ameliorate also the other cognitive functions? Each of these studies employed pre-training assessment, training application, post-training and follow-up assessment. In Study 1 we tested 28 patients suffering from post-stroke aphasia. They were assigned either to the temporal training (Group A, n = 15) in milliseconds range, or to the non-temporal training (Group B, n = 13). Following the training we found only in Group A improved TIP, accompanied by a transfer of improvement to language and working memory functions. In Study 2 we tested 32 children aged from 5 to 8 years, affected by SLI who were classified into the temporal training (Group A, n = 17) or non-temporal training (Group B, n = 15). Group A underwent the multileveled audio-visual computer training Dr. Neuronowski®, recently developed in our laboratory. Group B performed the computer speech therapy exercises extended by playing computer games. Similarly as in Study 1, in Group A we found significant improvements of TIP, auditory comprehension and working memory. These results indicated benefits of temporal training for amelioration of language and other cognitive functions in both aphasic patients and children with SLI. The novel powerful therapy tools provide evidence for future promising clinical applications. PMID:26617547

Plastic brain mechanisms for attaining auditory temporal order judgment proficiency.

PubMed

Bernasconi, Fosco; Grivel, Jeremy; Murray, Micah M; Spierer, Lucas

2010-04-15

Accurate perception of the order of occurrence of sensory information is critical for the building up of coherent representations of the external world from ongoing flows of sensory inputs. While some psychophysical evidence reports that performance on temporal perception can improve, the underlying neural mechanisms remain unresolved. Using electrical neuroimaging analyses of auditory evoked potentials (AEPs), we identified the brain dynamics and mechanism supporting improvements in auditory temporal order judgment (TOJ) during the course of the first vs. latter half of the experiment. Training-induced changes in brain activity were first evident 43-76 ms post stimulus onset and followed from topographic, rather than pure strength, AEP modulations. Improvements in auditory TOJ accuracy thus followed from changes in the configuration of the underlying brain networks during the initial stages of sensory processing. Source estimations revealed an increase in the lateralization of initially bilateral posterior sylvian region (PSR) responses at the beginning of the experiment to left-hemisphere dominance at its end. Further supporting the critical role of left and right PSR in auditory TOJ proficiency, as the experiment progressed, responses in the left and right PSR went from being correlated to un-correlated. These collective findings provide insights on the neurophysiologic mechanism and plasticity of temporal processing of sounds and are consistent with models based on spike timing dependent plasticity. Copyright 2010 Elsevier Inc. All rights reserved.

Land Cover Monitoring for Water Resources Management in Angola

NASA Astrophysics Data System (ADS)

Miguel, Irina; Navarro, Ana; Rolim, Joao; Catalao, Joao; Silva, Joel; Painho, Marco; Vekerdy, Zoltan

2016-08-01

The aim of this paper is to assess the impact of improved temporal resolution and multi-source satellite data (SAR and optical) on land cover mapping and monitoring for efficient water resources management. For that purpose, we developed an integrated approach based on image classification and on NDVI and SAR backscattering (VV and VH) time series for land cover mapping and crop's irrigation requirements computation. We analysed 28 SPOT-5 Take-5 images with high temporal revisiting time (5 days), 9 Sentinel-1 dual polarization GRD images and in-situ data acquired during the crop growing season. Results show that the combination of images from different sources provides the best information to map agricultural areas. The increase of the images temporal resolution allows the improvement of the estimation of the crop parameters, and then, to calculate of the crop's irrigation requirements. However, this aspect was not fully exploited due to the lack of EO data for the complete growing season.

Temporal ecology in the Anthropocene.

PubMed

Wolkovich, E M; Cook, B I; McLauchlan, K K; Davies, T J

2014-11-01

Two fundamental axes - space and time - shape ecological systems. Over the last 30 years spatial ecology has developed as an integrative, multidisciplinary science that has improved our understanding of the ecological consequences of habitat fragmentation and loss. We argue that accelerating climate change - the effective manipulation of time by humans - has generated a current need to build an equivalent framework for temporal ecology. Climate change has at once pressed ecologists to understand and predict ecological dynamics in non-stationary environments, while also challenged fundamental assumptions of many concepts, models and approaches. However, similarities between space and time, especially related issues of scaling, provide an outline for improving ecological models and forecasting of temporal dynamics, while the unique attributes of time, particularly its emphasis on events and its singular direction, highlight where new approaches are needed. We emphasise how a renewed, interdisciplinary focus on time would coalesce related concepts, help develop new theories and methods and guide further data collection. The next challenge will be to unite predictive frameworks from spatial and temporal ecology to build robust forecasts of when and where environmental change will pose the largest threats to species and ecosystems, as well as identifying the best opportunities for conservation. © 2014 John Wiley & Sons Ltd/CNRS.

Data Assimilation to Extract Soil Moisture Information From SMAP Observations

NASA Technical Reports Server (NTRS)

Kolassa, J.; Reichle, R. H.; Liu, Q.; Alemohammad, S. H.; Gentine, P.

2017-01-01

Statistical techniques permit the retrieval of soil moisture estimates in a model climatology while retaining the spatial and temporal signatures of the satellite observations. As a consequence, they can be used to reduce the need for localized bias correction techniques typically implemented in data assimilation (DA) systems that tend to remove some of the independent information provided by satellite observations. Here, we use a statistical neural network (NN) algorithm to retrieve SMAP (Soil Moisture Active Passive) surface soil moisture estimates in the climatology of the NASA Catchment land surface model. Assimilating these estimates without additional bias correction is found to significantly reduce the model error and increase the temporal correlation against SMAP CalVal in situ observations over the contiguous United States. A comparison with assimilation experiments using traditional bias correction techniques shows that the NN approach better retains the independent information provided by the SMAP observations and thus leads to larger model skill improvements during the assimilation. A comparison with the SMAP Level 4 product shows that the NN approach is able to provide comparable skill improvements and thus represents a viable assimilation approach.

A space-time look at two-phase estimation for improved annual inventory estimates

Treesearch

Jay Breidt; Jean Opsomer; Xiyue Liao; Gretchen Moisen

2015-01-01

Over the past several years, three sets of new temporal remote sensing data have become available improving FIA’s ability to detect, characterize and forecast land cover changes. First, historic Landsat data has been processed for the conterminous US to provide disturbance history, agents of change, and fitted spectral trajectories annually over the last 30+ years at...

Temporal and spatial resolution required for imaging myocardial function

NASA Astrophysics Data System (ADS)

Eusemann, Christian D.; Robb, Richard A.

2004-05-01

4-D functional analysis of myocardial mechanics is an area of significant interest and research in cardiology and vascular/interventional radiology. Current multidimensional analysis is limited by insufficient temporal resolution of x-ray and magnetic resonance based techniques, but recent improvements in system design holds hope for faster and higher resolution scans to improve images of moving structures allowing more accurate functional studies, such as in the heart. This paper provides a basis for the requisite temporal and spatial resolution for useful imaging during individual segments of the cardiac cycle. Multiple sample rates during systole and diastole are compared to determine an adequate sample frequency to reduce regional myocardial tracking errors. Concurrently, out-of-plane resolution has to be sufficiently high to minimize partial volume effect. Temporal resolution and out-of-plane spatial resolution are related factors that must be considered together. The data used for this study is a DSR dynamic volume image dataset with high temporal and spatial resolution using implanted fiducial markers to track myocardial motion. The results of this study suggest a reduced exposure and scan time for x-ray and magnetic resonance imaging methods, since a lower sample rate during systole is sufficient, whereas the period of rapid filling during diastole requires higher sampling. This could potentially reduce the cost of these procedures and allow higher patient throughput.

Example-Based Super-Resolution Fluorescence Microscopy.

PubMed

Jia, Shu; Han, Boran; Kutz, J Nathan

2018-04-23

Capturing biological dynamics with high spatiotemporal resolution demands the advancement in imaging technologies. Super-resolution fluorescence microscopy offers spatial resolution surpassing the diffraction limit to resolve near-molecular-level details. While various strategies have been reported to improve the temporal resolution of super-resolution imaging, all super-resolution techniques are still fundamentally limited by the trade-off associated with the longer image acquisition time that is needed to achieve higher spatial information. Here, we demonstrated an example-based, computational method that aims to obtain super-resolution images using conventional imaging without increasing the imaging time. With a low-resolution image input, the method provides an estimate of its super-resolution image based on an example database that contains super- and low-resolution image pairs of biological structures of interest. The computational imaging of cellular microtubules agrees approximately with the experimental super-resolution STORM results. This new approach may offer potential improvements in temporal resolution for experimental super-resolution fluorescence microscopy and provide a new path for large-data aided biomedical imaging.

Improving Soil Moisture Estimation through the Joint Assimilation of SMOS and GRACE Satellite Observations

NASA Technical Reports Server (NTRS)

Girotto, Manuela

2018-01-01

Observations from recent soil moisture dedicated missions (e.g. SMOS or SMAP) have been used in innovative data assimilation studies to provide global high spatial (i.e., approximately10-40 km) and temporal resolution (i.e., daily) soil moisture profile estimates from microwave brightness temperature observations. These missions are only sensitive to near-surface soil moisture 0-5 cm). In contrast, the Gravity Recovery and Climate Experiment (GRACE) mission provides accurate measurements of the entire vertically integrated terrestrial water storage (TWS) column but, it is characterized by low spatial (i.e., 150,000 km2) and temporal (i.e., monthly) resolutions. Data assimilation studies have shown that GRACE-TWS primarily affects (in absolute terms) deeper moisture storages (i.e., groundwater). In this presentation I will review benefits and drawbacks associated to the assimilation of both types of observations. In particular, I will illustrate the benefits and drawbacks of their joint assimilation for the purpose of improving the entire profile of soil moisture (i.e., surface and deeper water storages).

An improved rotated staggered-grid finite-difference method with fourth-order temporal accuracy for elastic-wave modeling in anisotropic media

DOE PAGES

Gao, Kai; Huang, Lianjie

2017-08-31

The rotated staggered-grid (RSG) finite-difference method is a powerful tool for elastic-wave modeling in 2D anisotropic media where the symmetry axes of anisotropy are not aligned with the coordinate axes. We develop an improved RSG scheme with fourth-order temporal accuracy to reduce the numerical dispersion associated with prolonged wave propagation or a large temporal step size. The high-order temporal accuracy is achieved by including high-order temporal derivatives, which can be converted to high-order spatial derivatives to reduce computational cost. Dispersion analysis and numerical tests show that our method exhibits very low temporal dispersion even with a large temporal step sizemore » for elastic-wave modeling in complex anisotropic media. Using the same temporal step size, our method is more accurate than the conventional RSG scheme. In conclusion, our improved RSG scheme is therefore suitable for prolonged modeling of elastic-wave propagation in 2D anisotropic media.« less

An improved rotated staggered-grid finite-difference method with fourth-order temporal accuracy for elastic-wave modeling in anisotropic media

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

Gao, Kai; Huang, Lianjie

The rotated staggered-grid (RSG) finite-difference method is a powerful tool for elastic-wave modeling in 2D anisotropic media where the symmetry axes of anisotropy are not aligned with the coordinate axes. We develop an improved RSG scheme with fourth-order temporal accuracy to reduce the numerical dispersion associated with prolonged wave propagation or a large temporal step size. The high-order temporal accuracy is achieved by including high-order temporal derivatives, which can be converted to high-order spatial derivatives to reduce computational cost. Dispersion analysis and numerical tests show that our method exhibits very low temporal dispersion even with a large temporal step sizemore » for elastic-wave modeling in complex anisotropic media. Using the same temporal step size, our method is more accurate than the conventional RSG scheme. In conclusion, our improved RSG scheme is therefore suitable for prolonged modeling of elastic-wave propagation in 2D anisotropic media.« less

Potential improvement for forest cover and forest degradation mapping with the forthcoming Sentinel-2 program

NASA Astrophysics Data System (ADS)

Hojas-Gascon, L.; Belward, A.; Eva, H.; Ceccherini, G.; Hagolle, O.; Garcia, J.; Cerutti, P.

2015-04-01

The forthcoming European Space Agency's Sentinel-2 mission promises to provide high (10 m) resolution optical data at higher temporal frequencies (5 day revisit with two operational satellites) than previously available. CNES, the French national space agency, launched a program in 2013, 'SPOT4 take 5', to simulate such a dataflow using the SPOT HRV sensor, which has similar spectral characteristics to the Sentinel sensor, but lower (20m) spatial resolution. Such data flow enables the analysis of the satellite images using temporal analysis, an approach previously restricted to lower spatial resolution sensors. We acquired 23 such images over Tanzania for the period from February to June 2013. The data were analysed with aim of discriminating between different forest cover percentages for landscape units of 0.5 ha over a site characterised by deciduous intact and degraded forests. The SPOT data were processed by one extracting temporal vegetation indices. We assessed the impact of the high acquisition rate with respect to the current rate of one image every 16 days. Validation data, giving the percentage of forest canopy cover in each land unit were provided by very high resolution satellite data. Results show that using the full temporal series it is possible to discriminate between forest units with differences of more than 40% tree cover or more. Classification errors fell exclusively into the adjacent forest canopy cover class of 20% or less. The analyses show that forestation mapping and degradation monitoring will be substantially improved with the Sentinel-2 program.

Prospects and pitfalls of occupational hazard mapping: 'between these lines there be dragons'.

PubMed

Koehler, Kirsten A; Volckens, John

2011-10-01

Hazard data mapping is a promising new technique that can enhance the process of occupational exposure assessment and risk communication. Hazard maps have the potential to improve worker health by providing key input for the design of hazard intervention and control strategies. Hazard maps are developed with aid from direct-reading instruments, which can collect highly spatially and temporally resolved data in a relatively short period of time. However, quantifying spatial-temporal variability in the occupational environment is not a straightforward process, and our lack of understanding of how to ascertain and model spatial and temporal variability is a limiting factor in the use and interpretation of workplace hazard maps. We provide an example of how sources of and exposures to workplace hazards may be mischaracterized in a hazard map due to a lack of completeness and representativeness of collected measurement data. Based on this example, we believe that a major priority for research in this emerging area should focus on the development of a statistical framework to quantify uncertainty in spatially and temporally varying data. In conjunction with this need is one for the development of guidelines and procedures for the proper sampling, generation, and evaluation of workplace hazard maps.

FMRI Is a Valid Noninvasive Alternative to Wada Testing

PubMed Central

Binder, Jeffrey R.

2010-01-01

Partial removal of the anterior temporal lobe (ATL) is a highly effective surgical treatment for intractable temporal lobe epilepsy, yet roughly half of patients who undergo left ATL resection show decline in language or verbal memory function postoperatively. Two recent studies demonstrate that preoperative fMRI can predict postoperative naming and verbal memory changes in such patients. Most importantly, fMRI significantly improves the accuracy of prediction relative to other noninvasive measures used alone. Addition of language and memory lateralization data from the intracarotid amobarbital (Wada) test did not improve prediction accuracy in these studies. Thus, fMRI provides patients and practitioners with a safe, non-invasive, and well-validated tool for making better-informed decisions regarding elective surgery based on a quantitative assessment of cognitive risk. PMID:20850386

DEVELOPMENT AND IMPROVEMENT OF TEMPORAL ALLOCATION FACTOR FILES

EPA Science Inventory

The report gives results of a project to: (1) evaluate the quality and completeness of data and methods being used for temporal allocation of emissions data, (2) identify and prioritize needed improvements to current methods for developing temporal allocation factors (TAFs), and ...

An evaluation of the potential of Sentinel 1 for improving flash flood predictions via soil moisture-data assimilation

NASA Astrophysics Data System (ADS)

Cenci, Luca; Pulvirenti, Luca; Boni, Giorgio; Chini, Marco; Matgen, Patrick; Gabellani, Simone; Squicciarino, Giuseppe; Pierdicca, Nazzareno

2017-11-01

The assimilation of satellite-derived soil moisture estimates (soil moisture-data assimilation, SM-DA) into hydrological models has the potential to reduce the uncertainty of streamflow simulations. The improved capacity to monitor the closeness to saturation of small catchments, such as those characterizing the Mediterranean region, can be exploited to enhance flash flood predictions. When compared to other microwave sensors that have been exploited for SM-DA in recent years (e.g. the Advanced SCATterometer - ASCAT), characterized by low spatial/high temporal resolution, the Sentinel 1 (S1) mission provides an excellent opportunity to monitor systematically soil moisture (SM) at high spatial resolution and moderate temporal resolution. The aim of this research was thus to evaluate the impact of S1-based SM-DA for enhancing flash flood predictions of a hydrological model (Continuum) that is currently exploited for civil protection applications in Italy. The analysis was carried out in a representative Mediterranean catchment prone to flash floods, located in north-western Italy, during the time period October 2014-February 2015. It provided some important findings: (i) revealing the potential provided by S1-based SM-DA for improving discharge predictions, especially for higher flows; (ii) suggesting a more appropriate pre-processing technique to be applied to S1 data before the assimilation; and (iii) highlighting that even though high spatial resolution does provide an important contribution in a SM-DA system, the temporal resolution has the most crucial role. S1-derived SM maps are still a relatively new product and, to our knowledge, this is the first work published in an international journal dealing with their assimilation within a hydrological model to improve continuous streamflow simulations and flash flood predictions. Even though the reported results were obtained by analysing a relatively short time period, and thus should be supported by further research activities, we believe this research is timely in order to enhance our understanding of the potential contribution of the S1 data within the SM-DA framework for flash flood risk mitigation.

High temporal resolution dynamic contrast-enhanced MRI using compressed sensing-combined sequence in quantitative renal perfusion measurement.

PubMed

Chen, Bin; Zhao, Kai; Li, Bo; Cai, Wenchao; Wang, Xiaoying; Zhang, Jue; Fang, Jing

2015-10-01

To demonstrate the feasibility of the improved temporal resolution by using compressed sensing (CS) combined imaging sequence in dynamic contrast-enhanced MRI (DCE-MRI) of kidney, and investigate its quantitative effects on renal perfusion measurements. Ten rabbits were included in the accelerated scans with a CS-combined 3D pulse sequence. To evaluate the image quality, the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were compared between the proposed CS strategy and the conventional full sampling method. Moreover, renal perfusion was estimated by using the separable compartmental model in both CS simulation and realistic CS acquisitions. The CS method showed DCE-MRI images with improved temporal resolution and acceptable image contrast, while presenting significantly higher SNR than the fully sampled images (p<.01) at 2-, 3- and 4-X acceleration. In quantitative measurements, renal perfusion results were in good agreement with the fully sampled one (concordance correlation coefficient=0.95, 0.91, 0.88) at 2-, 3- and 4-X acceleration in CS simulation. Moreover, in realistic acquisitions, the estimated perfusion by the separable compartmental model exhibited no significant differences (p>.05) between each CS-accelerated acquisition and the full sampling method. The CS-combined 3D sequence could improve the temporal resolution for DCE-MRI in kidney while yielding diagnostically acceptable image quality, and it could provide effective measurements of renal perfusion. Copyright © 2015 Elsevier Inc. All rights reserved.

Implementing a combined polar-geostationary algorithm for smoke emissions estimation in near real time

NASA Astrophysics Data System (ADS)

Hyer, E. J.; Schmidt, C. C.; Hoffman, J.; Giglio, L.; Peterson, D. A.

2013-12-01

Polar and geostationary satellites are used operationally for fire detection and smoke source estimation by many near-real-time operational users, including operational forecast centers around the globe. The input satellite radiance data are processed by data providers to produce Level-2 and Level -3 fire detection products, but processing these data into spatially and temporally consistent estimates of fire activity requires a substantial amount of additional processing. The most significant processing steps are correction for variable coverage of the satellite observations, and correction for conditions that affect the detection efficiency of the satellite sensors. We describe a system developed by the Naval Research Laboratory (NRL) that uses the full raster information from the entire constellation to diagnose detection opportunities, calculate corrections for factors such as angular dependence of detection efficiency, and generate global estimates of fire activity at spatial and temporal scales suitable for atmospheric modeling. By incorporating these improved fire observations, smoke emissions products, such as NRL's FLAMBE, are able to produce improved estimates of global emissions. This talk provides an overview of the system, demonstrates the achievable improvement over older methods, and describes challenges for near-real-time implementation.

PET/MRI for neurologic applications.

PubMed

Catana, Ciprian; Drzezga, Alexander; Heiss, Wolf-Dieter; Rosen, Bruce R

2012-12-01

PET and MRI provide complementary information in the study of the human brain. Simultaneous PET/MRI data acquisition allows the spatial and temporal correlation of the measured signals, creating opportunities impossible to realize using stand-alone instruments. This paper reviews the methodologic improvements and potential neurologic and psychiatric applications of this novel technology. We first present methods for improving the performance and information content of each modality by using the information provided by the other technique. On the PET side, we discuss methods that use the simultaneously acquired MRI data to improve the PET data quantification. On the MRI side, we present how improved PET quantification can be used to validate several MRI techniques. Finally, we describe promising research, translational, and clinical applications that can benefit from these advanced tools.

Improving snow fraction spatio-temporal continuity using a combination of MODIS and Fengyun-2 satellites over China

NASA Astrophysics Data System (ADS)

Jiang, L.; Wang, G.

2017-12-01

Snow cover is one of key elements in the investigations of weather, climatic change, water resource, and snow hazard. Satellites observations from on-board optical sensors provides the ability to snow cover mapping through the discrimination of snow from other surface features and cloud. MODIS provides maximum of snow cover data using 8-day composition data in order to reduce the cloud obscuration impacts. However, snow cover mapping is often required to obtain at the temporal scale of less than one day, especially in the case of disasters. Geostationary satellites provide much higher temporal resolution measurements (typically at 15 min or half or one hour), which has a great potential to reduce cloud cover problem and observe ground surface for identifying snow. The proposed method in this work is that how to take the advantages of polar-orbiting and geostationary optical sensors to accurately map snow cover without data gaps due to cloud. FY-2 geostationary satellites have high temporal resolution observations, however, they are lacking enough spectral bands essential for snow cover monitoring, such as the 1.6 μm band. Based on our recent work (Wang et al., 2017), we improved FY-2/VISSR fractional snow cover estimation with a linear spectral unmixing analysis method. The linear approach is applied then using the reflectance observed at the certain hourly image of FY-2 to calculate pixel-wise snow cover fraction. The composition of daily factional snow cover employs the sun zenith angle, where the snow fraction under lowest sun zenith angle is considered as the most confident result. FY-2/VISSR fractional snow cover map has less cloud due to the composition of multi-temporal snow maps in a single day. In order to get an accurate and cloud-reduced fractional snow cover map, both of MODIS and FY-2/VISSR daily snow fraction maps are blended together. With the combination of FY-2E/VISSR and MODIS, there are still some cloud existing in the daily snow fraction map. Then the combination snow fraction map is temporally reconstructed using MATLAB Piecewise Cubic Hermite Interpolating Polynomial (PCHIP) function to derive a completely daily cloud-free snow cover map under all the sky conditions.

Multi-source remotely sensed data fusion for improving land cover classification

NASA Astrophysics Data System (ADS)

Chen, Bin; Huang, Bo; Xu, Bing

2017-02-01

Although many advances have been made in past decades, land cover classification of fine-resolution remotely sensed (RS) data integrating multiple temporal, angular, and spectral features remains limited, and the contribution of different RS features to land cover classification accuracy remains uncertain. We proposed to improve land cover classification accuracy by integrating multi-source RS features through data fusion. We further investigated the effect of different RS features on classification performance. The results of fusing Landsat-8 Operational Land Imager (OLI) data with Moderate Resolution Imaging Spectroradiometer (MODIS), China Environment 1A series (HJ-1A), and Advanced Spaceborne Thermal Emission and Reflection (ASTER) digital elevation model (DEM) data, showed that the fused data integrating temporal, spectral, angular, and topographic features achieved better land cover classification accuracy than the original RS data. Compared with the topographic feature, the temporal and angular features extracted from the fused data played more important roles in classification performance, especially those temporal features containing abundant vegetation growth information, which markedly increased the overall classification accuracy. In addition, the multispectral and hyperspectral fusion successfully discriminated detailed forest types. Our study provides a straightforward strategy for hierarchical land cover classification by making full use of available RS data. All of these methods and findings could be useful for land cover classification at both regional and global scales.

The influence of underwater turbulence on optical phase measurements

NASA Astrophysics Data System (ADS)

Redding, Brandon; Davis, Allen; Kirkendall, Clay; Dandridge, Anthony

2016-05-01

Emerging underwater optical imaging and sensing applications rely on phase-sensitive detection to provide added functionality and improved sensitivity. However, underwater turbulence introduces spatio-temporal variations in the refractive index of water which can degrade the performance of these systems. Although the influence of turbulence on traditional, non-interferometric imaging has been investigated, its influence on the optical phase remains poorly understood. Nonetheless, a thorough understanding of the spatio-temporal dynamics of the optical phase of light passing through underwater turbulence are crucial to the design of phase-sensitive imaging and sensing systems. To address this concern, we combined underwater imaging with high speed holography to provide a calibrated characterization of the effects of turbulence on the optical phase. By measuring the modulation transfer function of an underwater imaging system, we were able to calibrate varying levels of optical turbulence intensity using the Simple Underwater Imaging Model (SUIM). We then used high speed holography to measure the temporal dynamics of the optical phase of light passing through varying levels of turbulence. Using this method, we measured the variance in the amplitude and phase of the beam, the temporal correlation of the optical phase, and recorded the turbulence induced phase noise as a function of frequency. By bench marking the effects of varying levels of turbulence on the optical phase, this work provides a basis to evaluate the real-world potential of emerging underwater interferometric sensing modalities.

Efficient Prediction Structures for H.264 Multi View Coding Using Temporal Scalability

NASA Astrophysics Data System (ADS)

Guruvareddiar, Palanivel; Joseph, Biju K.

2014-03-01

Prediction structures with "disposable view components based" hierarchical coding have been proven to be efficient for H.264 multi view coding. Though these prediction structures along with the QP cascading schemes provide superior compression efficiency when compared to the traditional IBBP coding scheme, the temporal scalability requirements of the bit stream could not be met to the fullest. On the other hand, a fully scalable bit stream, obtained by "temporal identifier based" hierarchical coding, provides a number of advantages including bit rate adaptations and improved error resilience, but lacks in compression efficiency when compared to the former scheme. In this paper it is proposed to combine the two approaches such that a fully scalable bit stream could be realized with minimal reduction in compression efficiency when compared to state-of-the-art "disposable view components based" hierarchical coding. Simulation results shows that the proposed method enables full temporal scalability with maximum BDPSNR reduction of only 0.34 dB. A novel method also has been proposed for the identification of temporal identifier for the legacy H.264/AVC base layer packets. Simulation results also show that this enables the scenario where the enhancement views could be extracted at a lower frame rate (1/2nd or 1/4th of base view) with average extraction time for a view component of only 0.38 ms.

Spatial and Temporal Evolution of Earthquake Dynamics: Case Study of the Mw 8.3 Illapel Earthquake, Chile

NASA Astrophysics Data System (ADS)

Yin, Jiuxun; Denolle, Marine A.; Yao, Huajian

2018-01-01

We develop a methodology that combines compressive sensing backprojection (CS-BP) and source spectral analysis of teleseismic P waves to provide metrics relevant to earthquake dynamics of large events. We improve the CS-BP method by an autoadaptive source grid refinement as well as a reference source adjustment technique to gain better spatial and temporal resolution of the locations of the radiated bursts. We also use a two-step source spectral analysis based on (i) simple theoretical Green's functions that include depth phases and water reverberations and on (ii) empirical P wave Green's functions. Furthermore, we propose a source spectrogram methodology that provides the temporal evolution of dynamic parameters such as radiated energy and falloff rates. Bridging backprojection and spectrogram analysis provides a spatial and temporal evolution of these dynamic source parameters. We apply our technique to the recent 2015 Mw 8.3 megathrust Illapel earthquake (Chile). The results from both techniques are consistent and reveal a depth-varying seismic radiation that is also found in other megathrust earthquakes. The low-frequency content of the seismic radiation is located in the shallow part of the megathrust, propagating unilaterally from the hypocenter toward the trench while most of the high-frequency content comes from the downdip part of the fault. Interpretation of multiple rupture stages in the radiation is also supported by the temporal variations of radiated energy and falloff rates. Finally, we discuss the possible mechanisms, either from prestress, fault geometry, and/or frictional properties to explain our observables. Our methodology is an attempt to bridge kinematic observations with earthquake dynamics.

The Impact of Participation in Music on Learning Mathematics

ERIC Educational Resources Information Center

Holmes, Sylwia; Hallam, Susan

2017-01-01

Music psychologists have established that some forms of musical activity improve intellectual performance, spatial-temporal reasoning and other skills advantageous for learning. In this research, the potential of active music-making for improving pupils' achievement in spatial- temporal reasoning was investigated. As spatial-temporal skills are…

Potential for Improved Intelligence Quotient Using Volumetric Modulated Arc Therapy Compared With Conventional 3-Dimensional Conformal Radiation for Whole-Ventricular Radiation in Children

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

Qi, X. Sharon, E-mail: xqi@mednet.ucla.edu; Department of Radiation Oncology, University of Colorado Denver, Aurora, Colorado; Stinauer, Michelle

Purpose: To compare volumetric modulated arc therapy (VMAT) with 3-dimensional conformal radiation therapy (3D-CRT) in the treatment of localized intracranial germinoma. We modeled the effect of the dosimetric differences on intelligence quotient (IQ). Method and Materials: Ten children with intracranial germinomas were used for planning. The prescription doses were 23.4 Gy to the ventricles followed by 21.6 Gy to the tumor located in the pineal region. For each child, a 3D-CRT and full arc VMAT was generated. Coverage of the target was assessed by computing a conformity index and heterogeneity index. We also generated VMAT plans with explicit temporal lobemore » sparing and with smaller ventricular margin expansions. Mean dose to the temporal lobe was used to estimate IQ 5 years after completion of radiation, using a patient age of 10 years. Results: Compared with the 3D-CRT plan, VMAT improved conformality (conformity index 1.10 vs 1.85), with slightly higher heterogeneity (heterogeneity index 1.09 vs 1.06). The averaged mean doses for left and right temporal lobes were 31.3 and 31.7 Gy, respectively, for VMAT plans and 37.7 and 37.6 Gy for 3D-CRT plans. This difference in mean temporal lobe dose resulted in an estimated IQ difference of 3.1 points at 5 years after radiation therapy. When the temporal lobes were explicitly included in the VMAT optimization, the mean temporal lobe dose was reduced 5.6-5.7 Gy, resulting in an estimated IQ difference of an additional 3 points. Reducing the ventricular margin from 1.5 cm to 0.5 cm decreased mean temporal lobe dose 11.4-13.1 Gy, corresponding to an estimated increase in IQ of 7 points. Conclusion: For treatment of children with intracranial pure germinomas, VMAT compared with 3D-CRT provides increased conformality and reduces doses to normal tissue. This may result in improvements in IQ in these children.« less

Improving tritium exposure reconstructions using accelerator mass spectrometry

PubMed Central

Hunt, J. R.; Vogel, J. S.; Knezovich, J. P.

2010-01-01

Direct measurement of tritium atoms by accelerator mass spectrometry (AMS) enables rapid low-activity tritium measurements from milligram-sized samples and permits greater ease of sample collection, faster throughput, and increased spatial and/or temporal resolution. Because existing methodologies for quantifying tritium have some significant limitations, the development of tritium AMS has allowed improvements in reconstructing tritium exposure concentrations from environmental measurements and provides an important additional tool in assessing the temporal and spatial distribution of chronic exposure. Tritium exposure reconstructions using AMS were previously demonstrated for a tree growing on known levels of tritiated water and for trees exposed to atmospheric releases of tritiated water vapor. In these analyses, tritium levels were measured from milligram-sized samples with sample preparation times of a few days. Hundreds of samples were analyzed within a few months of sample collection and resulted in the reconstruction of spatial and temporal exposure from tritium releases. Although the current quantification limit of tritium AMS is not adequate to determine natural environmental variations in tritium concentrations, it is expected to be sufficient for studies assessing possible health effects from chronic environmental tritium exposure. PMID:14735274

Modeling Geometric-Temporal Context With Directional Pyramid Co-Occurrence for Action Recognition.

PubMed

Yuan, Chunfeng; Li, Xi; Hu, Weiming; Ling, Haibin; Maybank, Stephen J

2014-02-01

In this paper, we present a new geometric-temporal representation for visual action recognition based on local spatio-temporal features. First, we propose a modified covariance descriptor under the log-Euclidean Riemannian metric to represent the spatio-temporal cuboids detected in the video sequences. Compared with previously proposed covariance descriptors, our descriptor can be measured and clustered in Euclidian space. Second, to capture the geometric-temporal contextual information, we construct a directional pyramid co-occurrence matrix (DPCM) to describe the spatio-temporal distribution of the vector-quantized local feature descriptors extracted from a video. DPCM characterizes the co-occurrence statistics of local features as well as the spatio-temporal positional relationships among the concurrent features. These statistics provide strong descriptive power for action recognition. To use DPCM for action recognition, we propose a directional pyramid co-occurrence matching kernel to measure the similarity of videos. The proposed method achieves the state-of-the-art performance and improves on the recognition performance of the bag-of-visual-words (BOVWs) models by a large margin on six public data sets. For example, on the KTH data set, it achieves 98.78% accuracy while the BOVW approach only achieves 88.06%. On both Weizmann and UCF CIL data sets, the highest possible accuracy of 100% is achieved.

Update of NOx emission temporal profiles using CMAQ-HDDM

NASA Astrophysics Data System (ADS)

Bae, C.; Lee, J. B.; Kim, H. C.; Kim, B. U.; Kim, S.

2017-12-01

This study demonstrates the impact of revised temporal profiles of NOx emissions on air quality simulations in the Seoul Metropolitan Area (SMA), South Korea. Air pollutants such as ozone and nitrogen oxides can be harmful to the human body even with short-term exposure. Since most of air quality models use predefined temporal profiles which are often outdated or taken from different chemical environment, providing accurate temporal variation of emissions are challenging in prediction of correct local air quality. Considering secondary formation of pollutants are important in mega cities and temporal variations of emissions are not coincident with those of resultant concentrations, we utilized CMAQ-HDDM to link emissions and consequential concentrations from different time steps. Base simulations were conducted using WRF, SMOKE, and CMAQ modeling frame using CREATE 2015 and CAPSS 2013 emissions inventories for East Asia and South Korea, respectively. With current modeling system, modeled NOx concentrations underestimate 4% in the daytime (10-16 LST), but overestimate 30% in the nighttime during May to August 2015. Applying revised temporal profiles based on HDDM sensitivities, model performance was improved significantly. We conclude that the proposed temporal allocation method can be useful to reduce the model-observation discrepancies when the activity data for emission sources are difficult to obtain with a bottom-up approach.

Cardiac imaging with multi-sector data acquisition in volumetric CT: variation of effective temporal resolution and its potential clinical consequences

NASA Astrophysics Data System (ADS)

Tang, Xiangyang; Hsieh, Jiang; Taha, Basel H.; Vass, Melissa L.; Seamans, John L.; Okerlund, Darin R.

2009-02-01

With increasing longitudinal detector dimension available in diagnostic volumetric CT, step-and-shoot scan is becoming popular for cardiac imaging. In comparison to helical scan, step-and-shoot scan decouples patient table movement from cardiac gating/triggering, which facilitates the cardiac imaging via multi-sector data acquisition, as well as the administration of inter-cycle heart beat variation (arrhythmia) and radiation dose efficiency. Ideally, a multi-sector data acquisition can improve temporal resolution at a factor the same as the number of sectors (best scenario). In reality, however, the effective temporal resolution is jointly determined by gantry rotation speed and patient heart beat rate, which may significantly lower than the ideal or no improvement (worst scenario). Hence, it is clinically relevant to investigate the behavior of effective temporal resolution in cardiac imaging with multi-sector data acquisition. In this study, a 5-second cine scan of a porcine heart, which cascades 6 porcine cardiac cycles, is acquired. In addition to theoretical analysis and motion phantom study, the clinical consequences due to the effective temporal resolution variation are evaluated qualitative or quantitatively. By employing a 2-sector image reconstruction strategy, a total of 15 (the permutation of P(6, 2)) cases between the best and worst scenarios are studied, providing informative guidance for the design and optimization of CT cardiac imaging in volumetric CT with multi-sector data acquisition.

Foot and ankle kinematics in patients with posterior tibial tendon dysfunction.

PubMed

Ness, Mary Ellen; Long, Jason; Marks, Richard; Harris, Gerald

2008-02-01

The purpose of this study is to provide a quantitative characterization of gait in patients with posterior tibial tendon dysfunction (PTTD), including temporal-spatial and kinematic parameters, and to compare these results to those of a Normal population. Our hypothesis was that segmental foot kinematics were significantly different in multiple segments across multiple planes. A 15 camera motion analysis system and weight-bearing radiographs were employed to evaluate 3D foot and ankle motion in a population of 34 patients with PTTD (30 females, 4 males) and 25 normal subjects (12 females, 13 males). The four-segment Milwaukee Foot Model (MFM) with radiographic indexing was used to analyze foot and ankle motion and provided kinematic data in the sagittal, coronal and transverse planes as well as temporal-spatial information. The temporal-spatial parameters revealed statistically significant deviations in all four metrics for the PTTD population. Stride length, cadence and walking speed were all significantly diminished, while stance duration was significantly prolonged (p<0.0125). Significant kinematic differences were noted between the groups (p<0.002), including: (1) diminished dorsiflexion and increased eversion of the hindfoot; (2) decreased plantarflexion of the forefoot, as well as abduction shift and loss of the varus thrust in the forefoot; and (3) decreased range of motion (ROM) with diminished dorsiflexion of the hallux. The study provides an impetus for improved orthotic and bracing designs to aid in the care of distal foot segments during the treatment of PTTD. It also provides the basis for future evaluation of surgical efficacy. The course of this investigation may ultimately lead to improved treatment planning methods, including orthotic and operative interventions.

Joint Assimilation of SMOS Brightness Temperature and GRACE Terrestrial Water Storage Observations for Improved Soil Moisture Estimation

NASA Technical Reports Server (NTRS)

Girotto, Manuela; Reichle, Rolf H.; De Lannoy, Gabrielle J. M.; Rodell, Matthew

2017-01-01

Observations from recent soil moisture missions (e.g. SMOS) have been used in innovative data assimilation studies to provide global high spatial (i.e. 40 km) and temporal resolution (i.e. 3-days) soil moisture profile estimates from microwave brightness temperature observations. In contrast with microwave-based satellite missions that are only sensitive to near-surface soil moisture (0 - 5 cm), the Gravity Recovery and Climate Experiment (GRACE) mission provides accurate measurements of the entire vertically integrated terrestrial water storage column but, it is characterized by low spatial (i.e. 150,000 km2) and temporal (i.e. monthly) resolutions. Data assimilation studies have shown that GRACE-TWS primarily affects (in absolute terms) deeper moisture storages (i.e., groundwater). This work hypothesizes that unprecedented soil water profile accuracy can be obtained through the joint assimilation of GRACE terrestrial water storage and SMOS brightness temperature observations. A particular challenge of the joint assimilation is the use of the two different types of measurements that are relevant for hydrologic processes representing different temporal and spatial scales. The performance of the joint assimilation strongly depends on the chosen assimilation methods, measurement and model error spatial structures. The optimization of the assimilation technique constitutes a fundamental step toward a multi-variate multi-resolution integrative assimilation system aiming to improve our understanding of the global terrestrial water cycle.

Joint assimilation of SMOS brightness temperature and GRACE terrestrial water storage observations for improved soil moisture estimation

NASA Astrophysics Data System (ADS)

Girotto, M.; Reichle, R. H.; De Lannoy, G.; Rodell, M.

2017-12-01

Observations from recent soil moisture missions (e.g. SMOS) have been used in innovative data assimilation studies to provide global high spatial (i.e. 40 km) and temporal resolution (i.e. 3-days) soil moisture profile estimates from microwave brightness temperature observations. In contrast with microwave-based satellite missions that are only sensitive to near-surface soil moisture (0-5 cm), the Gravity Recovery and Climate Experiment (GRACE) mission provides accurate measurements of the entire vertically integrated terrestrial water storage column but, it is characterized by low spatial (i.e. 150,000 km2) and temporal (i.e. monthly) resolutions. Data assimilation studies have shown that GRACE-TWS primarily affects (in absolute terms) deeper moisture storages (i.e., groundwater). This work hypothesizes that unprecedented soil water profile accuracy can be obtained through the joint assimilation of GRACE terrestrial water storage and SMOS brightness temperature observations. A particular challenge of the joint assimilation is the use of the two different types of measurements that are relevant for hydrologic processes representing different temporal and spatial scales. The performance of the joint assimilation strongly depends on the chosen assimilation methods, measurement and model error spatial structures. The optimization of the assimilation technique constitutes a fundamental step toward a multi-variate multi-resolution integrative assimilation system aiming to improve our understanding of the global terrestrial water cycle.

Probing the Spatio-Temporal Characteristics of Temporal Aliasing Errors and their Impact on Satellite Gravity Retrievals

NASA Astrophysics Data System (ADS)

Wiese, D. N.; McCullough, C. M.

2017-12-01

Studies have shown that both single pair low-low satellite-to-satellite tracking (LL-SST) and dual-pair LL-SST hypothetical future satellite gravimetry missions utilizing improved onboard measurement systems relative to the Gravity Recovery and Climate Experiment (GRACE) will be limited by temporal aliasing errors; that is, the error introduced through deficiencies in models of high frequency mass variations required for the data processing. Here, we probe the spatio-temporal characteristics of temporal aliasing errors to understand their impact on satellite gravity retrievals using high fidelity numerical simulations. We find that while aliasing errors are dominant at long wavelengths and multi-day timescales, improving knowledge of high frequency mass variations at these resolutions translates into only modest improvements (i.e. spatial resolution/accuracy) in the ability to measure temporal gravity variations at monthly timescales. This result highlights the reliance on accurate models of high frequency mass variations for gravity processing, and the difficult nature of reducing temporal aliasing errors and their impact on satellite gravity retrievals.

Calibrating a numerical model's morphology using high-resolution spatial and temporal datasets from multithread channel flume experiments.

NASA Astrophysics Data System (ADS)

Javernick, L.; Bertoldi, W.; Redolfi, M.

2017-12-01

Accessing or acquiring high quality, low-cost topographic data has never been easier due to recent developments of the photogrammetric techniques of Structure-from-Motion (SfM). Researchers can acquire the necessary SfM imagery with various platforms, with the ability to capture millimetre resolution and accuracy, or large-scale areas with the help of unmanned platforms. Such datasets in combination with numerical modelling have opened up new opportunities to study river environments physical and ecological relationships. While numerical models overall predictive accuracy is most influenced by topography, proper model calibration requires hydraulic data and morphological data; however, rich hydraulic and morphological datasets remain scarce. This lack in field and laboratory data has limited model advancement through the inability to properly calibrate, assess sensitivity, and validate the models performance. However, new time-lapse imagery techniques have shown success in identifying instantaneous sediment transport in flume experiments and their ability to improve hydraulic model calibration. With new capabilities to capture high resolution spatial and temporal datasets of flume experiments, there is a need to further assess model performance. To address this demand, this research used braided river flume experiments and captured time-lapse observed sediment transport and repeat SfM elevation surveys to provide unprecedented spatial and temporal datasets. Through newly created metrics that quantified observed and modeled activation, deactivation, and bank erosion rates, the numerical model Delft3d was calibrated. This increased temporal data of both high-resolution time series and long-term temporal coverage provided significantly improved calibration routines that refined calibration parameterization. Model results show that there is a trade-off between achieving quantitative statistical and qualitative morphological representations. Specifically, statistical agreement simulations suffered to represent braiding planforms (evolving toward meandering), and parameterization that ensured braided produced exaggerated activation and bank erosion rates. Marie Sklodowska-Curie Individual Fellowship: River-HMV, 656917

Remote-Sensing Time Series Analysis, a Vegetation Monitoring Tool

NASA Technical Reports Server (NTRS)

McKellip, Rodney; Prados, Donald; Ryan, Robert; Ross, Kenton; Spruce, Joseph; Gasser, Gerald; Greer, Randall

2008-01-01

The Time Series Product Tool (TSPT) is software, developed in MATLAB , which creates and displays high signal-to- noise Vegetation Indices imagery and other higher-level products derived from remotely sensed data. This tool enables automated, rapid, large-scale regional surveillance of crops, forests, and other vegetation. TSPT temporally processes high-revisit-rate satellite imagery produced by the Moderate Resolution Imaging Spectroradiometer (MODIS) and by other remote-sensing systems. Although MODIS imagery is acquired daily, cloudiness and other sources of noise can greatly reduce the effective temporal resolution. To improve cloud statistics, the TSPT combines MODIS data from multiple satellites (Aqua and Terra). The TSPT produces MODIS products as single time-frame and multitemporal change images, as time-series plots at a selected location, or as temporally processed image videos. Using the TSPT program, MODIS metadata is used to remove and/or correct bad and suspect data. Bad pixel removal, multiple satellite data fusion, and temporal processing techniques create high-quality plots and animated image video sequences that depict changes in vegetation greenness. This tool provides several temporal processing options not found in other comparable imaging software tools. Because the framework to generate and use other algorithms is established, small modifications to this tool will enable the use of a large range of remotely sensed data types. An effective remote-sensing crop monitoring system must be able to detect subtle changes in plant health in the earliest stages, before the effects of a disease outbreak or other adverse environmental conditions can become widespread and devastating. The integration of the time series analysis tool with ground-based information, soil types, crop types, meteorological data, and crop growth models in a Geographic Information System, could provide the foundation for a large-area crop-surveillance system that could identify a variety of plant phenomena and improve monitoring capabilities.

Dynamic magnetic resonance imaging method based on golden-ratio cartesian sampling and compressed sensing.

PubMed

Li, Shuo; Zhu, Yanchun; Xie, Yaoqin; Gao, Song

2018-01-01

Dynamic magnetic resonance imaging (DMRI) is used to noninvasively trace the movements of organs and the process of drug delivery. The results can provide quantitative or semiquantitative pathology-related parameters, thus giving DMRI great potential for clinical applications. However, conventional DMRI techniques suffer from low temporal resolution and long scan time owing to the limitations of the k-space sampling scheme and image reconstruction algorithm. In this paper, we propose a novel DMRI sampling scheme based on a golden-ratio Cartesian trajectory in combination with a compressed sensing reconstruction algorithm. The results of two simulation experiments, designed according to the two major DMRI techniques, showed that the proposed method can improve the temporal resolution and shorten the scan time and provide high-quality reconstructed images.

SPATIO-TEMPORAL MODELING OF AGRICULTURAL YIELD DATA WITH AN APPLICATION TO PRICING CROP INSURANCE CONTRACTS

PubMed Central

Ozaki, Vitor A.; Ghosh, Sujit K.; Goodwin, Barry K.; Shirota, Ricardo

2009-01-01

This article presents a statistical model of agricultural yield data based on a set of hierarchical Bayesian models that allows joint modeling of temporal and spatial autocorrelation. This method captures a comprehensive range of the various uncertainties involved in predicting crop insurance premium rates as opposed to the more traditional ad hoc, two-stage methods that are typically based on independent estimation and prediction. A panel data set of county-average yield data was analyzed for 290 counties in the State of Paraná (Brazil) for the period of 1990 through 2002. Posterior predictive criteria are used to evaluate different model specifications. This article provides substantial improvements in the statistical and actuarial methods often applied to the calculation of insurance premium rates. These improvements are especially relevant to situations where data are limited. PMID:19890450

Microchannel plate streak camera

DOEpatents

Wang, Ching L.

1989-01-01

An improved streak camera in which a microchannel plate electron multiplier is used in place of or in combination with the photocathode used in prior streak cameras. The improved streak camera is far more sensitive to photons (UV to gamma-rays) than the conventional x-ray streak camera which uses a photocathode. The improved streak camera offers gamma-ray detection with high temporal resolution. It also offers low-energy x-ray detection without attenuation inside the cathode. Using the microchannel plate in the improved camera has resulted in a time resolution of about 150 ps, and has provided a sensitivity sufficient for 1000 KeV x-rays.

Improved Analysis of Time Series with Temporally Correlated Errors: An Algorithm that Reduces the Computation Time.

NASA Astrophysics Data System (ADS)

Langbein, J. O.

2016-12-01

Most time series of geophysical phenomena are contaminated with temporally correlated errors that limit the precision of any derived parameters. Ignoring temporal correlations will result in biased and unrealistic estimates of velocity and its error estimated from geodetic position measurements. Obtaining better estimates of uncertainties is limited by several factors, including selection of the correct model for the background noise and the computational requirements to estimate the parameters of the selected noise model when there are numerous observations. Here, I address the second problem of computational efficiency using maximum likelihood estimates (MLE). Most geophysical time series have background noise processes that can be represented as a combination of white and power-law noise, 1/fn , with frequency, f. Time domain techniques involving construction and inversion of large data covariance matrices are employed. Bos et al. [2012] demonstrate one technique that substantially increases the efficiency of the MLE methods, but it provides only an approximate solution for power-law indices greater than 1.0. That restriction can be removed by simply forming a data-filter that adds noise processes rather than combining them in quadrature. Consequently, the inversion of the data covariance matrix is simplified and it provides robust results for a wide range of power-law indices. With the new formulation, the efficiency is typically improved by about a factor of 8 over previous MLE algorithms [Langbein, 2004]. The new algorithm can be downloaded at http://earthquake.usgs.gov/research/software/#est_noise. The main program provides a number of basic functions that can be used to model the time-dependent part of time series and a variety of models that describe the temporal covariance of the data. In addition, the program is packaged with a few companion programs and scripts that can help with data analysis and with interpretation of the noise modeling.

Quantifying Uncertainty in Daily Temporal Variations of Atmospheric NH3 Emissions Following Application of Chemical Fertilizers

NASA Astrophysics Data System (ADS)

Balasubramanian, S.; Koloutsou-Vakakis, S.; Rood, M. J.

2014-12-01

Improving modeling predictions of atmospheric particulate matter and deposition of reactive nitrogen requires representative emission inventories of precursor species, such as ammonia (NH3). Anthropogenic NH3 is primarily emitted to the atmosphere from agricultural sources (80-90%) with dominant contributions (56%) from chemical fertilizer usage (CFU) in regions like Midwest USA. Local crop management practices vary spatially and temporally, which influence regional air quality. To model the impact of CFU, NH3 emission inputs to chemical transport models are obtained from the National Emission Inventory (NEI). NH3 emissions from CFU are typically estimated by combining annual fertilizer sales data with emission factors. The Sparse Matrix Operator Kernel Emissions (SMOKE) model is used to disaggregate annual emissions to hourly scale using temporal factors. These factors are estimated by apportioning emissions within each crop season in proportion to the nitrogen applied and time-averaged to the hourly scale. Such approach does not reflect influence of CFU for different crops and local weather and soil conditions. This study provides an alternate approach for estimating temporal factors for NH3 emissions. The DeNitrification DeComposition (DNDC) model was used to estimate daily variations in NH3 emissions from CFU at 14 Central Illinois locations for 2002-2011. Weather, crop and soil data were provided as inputs. A method was developed to estimate site level CFU by combining planting and harvesting dates, nitrogen management and fertilizer sales data. DNDC results indicated that annual NH3 emissions were within ±15% of SMOKE estimates. Daily modeled emissions across 10 years followed similar distributions but varied in magnitudes within ±20%. Individual emission peaks on days after CFU were 2.5-8 times greater as compared to existing estimates from SMOKE. By identifying the episodic nature of NH3 emissions from CFU, this study is expected to provide improvements in predicting atmospheric particulate matter concentrations and deposition of reactive nitrogen.

PET/MRI for Neurological Applications

PubMed Central

Catana, Ciprian; Drzezga, Alexander; Heiss, Wolf-Dieter; Rosen, Bruce R.

2013-01-01

PET and MRI provide complementary information in the study of the human brain. Simultaneous PET/MR data acquisition allows the spatial and temporal correlation of the measured signals, opening up opportunities impossible to realize using stand-alone instruments. This paper reviews the methodological improvements and potential neurological and psychiatric applications of this novel technology. We first present methods for improving the performance and information content of each modality by using the information provided by the other technique. On the PET side, we discuss methods that use the simultaneously acquired MR data to improve the PET data quantification. On the MR side, we present how improved PET quantification could be used to validate a number of MR techniques. Finally, we describe promising research, translational and clinical applications that could benefit from these advanced tools. PMID:23143086

Single-trial EEG-informed fMRI reveals spatial dependency of BOLD signal on early and late IC-ERP amplitudes during face recognition.

PubMed

Wirsich, Jonathan; Bénar, Christian; Ranjeva, Jean-Philippe; Descoins, Médéric; Soulier, Elisabeth; Le Troter, Arnaud; Confort-Gouny, Sylviane; Liégeois-Chauvel, Catherine; Guye, Maxime

2014-10-15

Simultaneous EEG-fMRI has opened up new avenues for improving the spatio-temporal resolution of functional brain studies. However, this method usually suffers from poor EEG quality, especially for evoked potentials (ERPs), due to specific artifacts. As such, the use of EEG-informed fMRI analysis in the context of cognitive studies has particularly focused on optimizing narrow ERP time windows of interest, which ignores the rich diverse temporal information of the EEG signal. Here, we propose to use simultaneous EEG-fMRI to investigate the neural cascade occurring during face recognition in 14 healthy volunteers by using the successive ERP peaks recorded during the cognitive part of this process. N170, N400 and P600 peaks, commonly associated with face recognition, were successfully and reproducibly identified for each trial and each subject by using a group independent component analysis (ICA). For the first time we use this group ICA to extract several independent components (IC) corresponding to the sequence of activation and used single-trial peaks as modulation parameters in a general linear model (GLM) of fMRI data. We obtained an occipital-temporal-frontal stream of BOLD signal modulation, in accordance with the three successive IC-ERPs providing an unprecedented spatio-temporal characterization of the whole cognitive process as defined by BOLD signal modulation. By using this approach, the pattern of EEG-informed BOLD modulation provided improved characterization of the network involved than the fMRI-only analysis or the source reconstruction of the three ERPs; the latter techniques showing only two regions in common localized in the occipital lobe. Copyright © 2014 Elsevier Inc. All rights reserved.

The performance of the spatiotemporal Kalman filter and LORETA in seizure onset localization.

PubMed

Hamid, Laith; Sarabi, Masoud; Japaridze, Natia; Wiegand, Gert; Heute, Ulrich; Stephani, Ulrich; Galka, Andreas; Siniatchkin, Michael

2015-08-01

The assumption of spatial-smoothness is often used to solve the bioelectric inverse problem during electroencephalographic (EEG) source imaging, e.g., in low resolution electromagnetic tomography (LORETA). Since the EEG data show a temporal structure, the combination of the temporal-smoothness and the spatial-smoothness constraints may improve the solution of the EEG inverse problem. This study investigates the performance of the spatiotemporal Kalman filter (STKF) method, which is based on spatial and temporal smoothness, in the localization of a focal seizure's onset and compares its results to those of LORETA. The main finding of the study was that the STKF with an autoregressive model of order two significantly outperformed LORETA in the accuracy and consistency of the localization, provided that the source space consists of a whole-brain volumetric grid. In the future, these promising results will be confirmed using data from more patients and performing statistical analyses on the results. Furthermore, the effects of the temporal smoothness constraint will be studied using different types of focal seizures.

Task relevance modulates the behavioural and neural effects of sensory predictions

PubMed Central

Friston, Karl J.; Nobre, Anna C.

2017-01-01

The brain is thought to generate internal predictions to optimize behaviour. However, it is unclear whether predictions signalling is an automatic brain function or depends on task demands. Here, we manipulated the spatial/temporal predictability of visual targets, and the relevance of spatial/temporal information provided by auditory cues. We used magnetoencephalography (MEG) to measure participants’ brain activity during task performance. Task relevance modulated the influence of predictions on behaviour: spatial/temporal predictability improved spatial/temporal discrimination accuracy, but not vice versa. To explain these effects, we used behavioural responses to estimate subjective predictions under an ideal-observer model. Model-based time-series of predictions and prediction errors (PEs) were associated with dissociable neural responses: predictions correlated with cue-induced beta-band activity in auditory regions and alpha-band activity in visual regions, while stimulus-bound PEs correlated with gamma-band activity in posterior regions. Crucially, task relevance modulated these spectral correlates, suggesting that current goals influence PE and prediction signalling. PMID:29206225

a Comparison Study of Different Kernel Functions for Svm-Based Classification of Multi-Temporal Polarimetry SAR Data

NASA Astrophysics Data System (ADS)

Yekkehkhany, B.; Safari, A.; Homayouni, S.; Hasanlou, M.

2014-10-01

In this paper, a framework is developed based on Support Vector Machines (SVM) for crop classification using polarimetric features extracted from multi-temporal Synthetic Aperture Radar (SAR) imageries. The multi-temporal integration of data not only improves the overall retrieval accuracy but also provides more reliable estimates with respect to single-date data. Several kernel functions are employed and compared in this study for mapping the input space to higher Hilbert dimension space. These kernel functions include linear, polynomials and Radial Based Function (RBF). The method is applied to several UAVSAR L-band SAR images acquired over an agricultural area near Winnipeg, Manitoba, Canada. In this research, the temporal alpha features of H/A/α decomposition method are used in classification. The experimental tests show an SVM classifier with RBF kernel for three dates of data increases the Overall Accuracy (OA) to up to 3% in comparison to using linear kernel function, and up to 1% in comparison to a 3rd degree polynomial kernel function.

A framework for simulating map error in ecosystem models

Treesearch

Sean P. Healey; Shawn P. Urbanski; Paul L. Patterson; Chris Garrard

2014-01-01

The temporal depth and spatial breadth of observations from platforms such as Landsat provide unique perspective on ecosystem dynamics, but the integration of these observations into formal decision support will rely upon improved uncertainty accounting. Monte Carlo (MC) simulations offer a practical, empirical method of accounting for potential map errors in broader...

Spatial correlation-based side information refinement for distributed video coding

NASA Astrophysics Data System (ADS)

Taieb, Mohamed Haj; Chouinard, Jean-Yves; Wang, Demin

2013-12-01

Distributed video coding (DVC) architecture designs, based on distributed source coding principles, have benefitted from significant progresses lately, notably in terms of achievable rate-distortion performances. However, a significant performance gap still remains when compared to prediction-based video coding schemes such as H.264/AVC. This is mainly due to the non-ideal exploitation of the video sequence temporal correlation properties during the generation of side information (SI). In fact, the decoder side motion estimation provides only an approximation of the true motion. In this paper, a progressive DVC architecture is proposed, which exploits the spatial correlation of the video frames to improve the motion-compensated temporal interpolation (MCTI). Specifically, Wyner-Ziv (WZ) frames are divided into several spatially correlated groups that are then sent progressively to the receiver. SI refinement (SIR) is performed as long as these groups are being decoded, thus providing more accurate SI for the next groups. It is shown that the proposed progressive SIR method leads to significant improvements over the Discover DVC codec as well as other SIR schemes recently introduced in the literature.

Monitoring Crop Productivity over the U.S. Corn Belt using an Improved Light Use Efficiency Model

NASA Astrophysics Data System (ADS)

Wu, X.; Xiao, X.; Zhang, Y.; Qin, Y.; Doughty, R.

2017-12-01

Large-scale monitoring of crop yield is of great significance for forecasting food production and prices and ensuring food security. Satellite data that provide temporally and spatially continuous information that by themselves or in combination with other data or models, raises possibilities to monitor and understand agricultural productivity regionally. In this study, we first used an improved light use efficiency model-Vegetation Photosynthesis Model (VPM) to simulate the gross primary production (GPP). Model evaluation showed that the simulated GPP (GPPVPM) could well captured the spatio-temporal variation of GPP derived from FLUXNET sites. Then we applied the GPPVPM to further monitor crop productivity for corn and soybean over the U.S. Corn Belt and benchmarked with county-level crop yield statistics. We found VPM-based approach provides pretty good estimates (R2 = 0.88, slope = 1.03). We further showed the impacts of climate extremes on the crop productivity and carbon use efficiency. The study indicates the great potential of VPM in estimating crop yield and in understanding of crop yield responses to climate variability and change.

Coding tools investigation for next generation video coding based on HEVC

NASA Astrophysics Data System (ADS)

Chen, Jianle; Chen, Ying; Karczewicz, Marta; Li, Xiang; Liu, Hongbin; Zhang, Li; Zhao, Xin

2015-09-01

The new state-of-the-art video coding standard, H.265/HEVC, has been finalized in 2013 and it achieves roughly 50% bit rate saving compared to its predecessor, H.264/MPEG-4 AVC. This paper provides the evidence that there is still potential for further coding efficiency improvements. A brief overview of HEVC is firstly given in the paper. Then, our improvements on each main module of HEVC are presented. For instance, the recursive quadtree block structure is extended to support larger coding unit and transform unit. The motion information prediction scheme is improved by advanced temporal motion vector prediction, which inherits the motion information of each small block within a large block from a temporal reference picture. Cross component prediction with linear prediction model improves intra prediction and overlapped block motion compensation improves the efficiency of inter prediction. Furthermore, coding of both intra and inter prediction residual is improved by adaptive multiple transform technique. Finally, in addition to deblocking filter and SAO, adaptive loop filter is applied to further enhance the reconstructed picture quality. This paper describes above-mentioned techniques in detail and evaluates their coding performance benefits based on the common test condition during HEVC development. The simulation results show that significant performance improvement over HEVC standard can be achieved, especially for the high resolution video materials.

Assessing the capability of different satellite observing configurations to resolve the distribution of methane emissions at kilometer scales

NASA Astrophysics Data System (ADS)

Turner, Alexander J.; Jacob, Daniel J.; Benmergui, Joshua; Brandman, Jeremy; White, Laurent; Randles, Cynthia A.

2018-06-01

Anthropogenic methane emissions originate from a large number of fine-scale and often transient point sources. Satellite observations of atmospheric methane columns are an attractive approach for monitoring these emissions but have limitations from instrument precision, pixel resolution, and measurement frequency. Dense observations will soon be available in both low-Earth and geostationary orbits, but the extent to which they can provide fine-scale information on methane sources has yet to be explored. Here we present an observation system simulation experiment (OSSE) to assess the capabilities of different satellite observing system configurations. We conduct a 1-week WRF-STILT simulation to generate methane column footprints at 1.3 × 1.3 km2 spatial resolution and hourly temporal resolution over a 290 × 235 km2 domain in the Barnett Shale, a major oil and gas field in Texas with a large number of point sources. We sub-sample these footprints to match the observing characteristics of the recently launched TROPOMI instrument (7 × 7 km2 pixels, 11 ppb precision, daily frequency), the planned GeoCARB instrument (2.7 × 3.0 km2 pixels, 4 ppb precision, nominal twice-daily frequency), and other proposed observing configurations. The information content of the various observing systems is evaluated using the Fisher information matrix and its eigenvalues. We find that a week of TROPOMI observations should provide information on temporally invariant emissions at ˜ 30 km spatial resolution. GeoCARB should provide information available on temporally invariant emissions ˜ 2-7 km spatial resolution depending on sampling frequency (hourly to daily). Improvements to the instrument precision yield greater increases in information content than improved sampling frequency. A precision better than 6 ppb is critical for GeoCARB to achieve fine resolution of emissions. Transient emissions would be missed with either TROPOMI or GeoCARB. An aspirational high-resolution geostationary instrument with 1.3 × 1.3 km2 pixel resolution, hourly return time, and 1 ppb precision would effectively constrain the temporally invariant emissions in the Barnett Shale at the kilometer scale and provide some information on hourly variability of sources.

Integrating Eddy Covariance, Penman-Monteith and METRIC based Evapotranspiration estimates to generate high resolution space-time ET over the Brazos River Basin

NASA Astrophysics Data System (ADS)

Mbabazi, D.; Mohanty, B.; Gaur, N.

2017-12-01

Evapotranspiration (ET) is an important component of the water and energy balance and accounts for 60 -70% of precipitation losses. However, accurate estimates of ET are difficult to quantify at varying spatial and temporal scales. Eddy covariance methods estimate ET at high temporal resolutions but without capturing the spatial variation in ET within its footprint. On the other hand, remote sensing methods using Landsat imagery provide ET with high spatial resolution but low temporal resolution (16 days). In this study, we used both eddy covariance and remote sensing methods to generate high space-time resolution ET. Daily, monthly and seasonal ET estimates were obtained using the eddy covariance (EC) method, Penman-Monteith (PM) and Mapping Evapotranspiration with Internalized Calibration (METRIC) models to determine cotton and native prairie ET dynamics in the Brazos river basin characterized by varying hydro-climatic and geological gradients. Daily estimates of spatially distributed ET (30 m resolution) were generated using spatial autocorrelation and temporal interpolations between the EC flux variable footprints and METRIC ET for the 2016 and 2017 growing seasons. A comparison of the 2016 and 2017 preliminary daily ET estimates showed similar ET dynamics/trends among the EC, PM and METRIC methods, and 5-20% differences in seasonal ET estimates. This study will improve the spatial estimates of EC ET and temporal resolution of satellite derived ET thus providing better ET data for water use management.

Employing temporal self-similarity across the entire time domain in computed tomography reconstruction

PubMed Central

Kazantsev, D.; Van Eyndhoven, G.; Lionheart, W. R. B.; Withers, P. J.; Dobson, K. J.; McDonald, S. A.; Atwood, R.; Lee, P. D.

2015-01-01

There are many cases where one needs to limit the X-ray dose, or the number of projections, or both, for high frame rate (fast) imaging. Normally, it improves temporal resolution but reduces the spatial resolution of the reconstructed data. Fortunately, the redundancy of information in the temporal domain can be employed to improve spatial resolution. In this paper, we propose a novel regularizer for iterative reconstruction of time-lapse computed tomography. The non-local penalty term is driven by the available prior information and employs all available temporal data to improve the spatial resolution of each individual time frame. A high-resolution prior image from the same or a different imaging modality is used to enhance edges which remain stationary throughout the acquisition time while dynamic features tend to be regularized spatially. Effective computational performance together with robust improvement in spatial and temporal resolution makes the proposed method a competitive tool to state-of-the-art techniques. PMID:25939621

The Utility of CDOM for Improving the Resolution of Riverine DOM Fluxes and Biogeochemical Function

NASA Astrophysics Data System (ADS)

Spencer, R. G.; Aiken, G.; Mann, P. J.; Holmes, R. M.; Niggemann, J.; Dittmar, T.; Hernes, P.; Stubbins, A.

2014-12-01

A major historical limitation to geochemical studies assessing fluvial fluxes of dissolved organic matter (DOM) has been the issue of both temporal and spatial scaling. Examples will be presented from watersheds around the world highlighting how chromophoric dissolved organic matter (CDOM) measurements can be utilized as proxies for more intensive and expensive analytical analyses (e.g. molecular-level organic biomarkers). Utilizing these refined CDOM loads for terrigenous biomarkers results in improved temporal resolution and a significant change in flux estimates. Examining CDOM and dissolved organic carbon (DOC) flux data from an assortment of terrestrial biomes we establish a robust relationship between CDOM and DOC loads. The application of this relationship allows future studies to derive DOC loads from CDOM utilizing emerging in-situ or remote sensing technologies and thus refine river-to-ocean DOC fluxes, as well as exploit historic imagery to examine how fluxes may have changed. Calculated CDOM yields from a range of rivers are correlated to watershed percent wetland and highlight the importance of certain regions with respect to CDOM flux to the coastal ocean. This approach indicates that future studies might predict CDOM and DOC yields for different watershed types that could then be readily converted to loads providing for the estimation of CDOM and DOC export from ungauged watersheds. Examination of CDOM yields also highlights important geographical regions for future study with respect to the role of terrigenous CDOM in ocean color budgets and CDOM's role in biogeochemical processes. Finally, examples will be presented linking CDOM parameters to DOM composition and biogeochemical properties with the aim of providing measurements to improve the spatial and especially temporal resolution of the role DOM plays in fluvial networks.

Music and Dyslexia: A New Musical Training Method to Improve Reading and Related Disorders

PubMed Central

Habib, Michel; Lardy, Chloé; Desiles, Tristan; Commeiras, Céline; Chobert, Julie; Besson, Mireille

2016-01-01

Numerous arguments in the recent neuroscientific literature support the use of musical training as a therapeutic tool among the arsenal already available to therapists and educators for treating children with dyslexia. In the present study, we tested the efficacy of a specially-designed Cognitivo-Musical Training (CMT) method based upon three principles: (1) music-language analogies: training dyslexics with music could contribute to improve brain circuits which are common to music and language processes; (2) the temporal and rhythmic features of music, which could exert a positive effect on the multiple dimensions of the “temporal deficit” characteristic of some types of dyslexia; and (3) cross-modal integration, based on converging evidence of impaired connectivity between brain regions in dyslexia and related disorders. Accordingly, we developed a series of musical exercises involving jointly and simultaneously sensory (visual, auditory, somatosensory) and motor systems, with special emphasis on rhythmic perception and production in addition to intensive training of various features of the musical auditory signal. Two separate studies were carried out, one in which dyslexic children received intensive musical exercises concentrated over 18 h during 3 consecutive days, and the other in which the 18 h of musical training were spread over 6 weeks. Both studies showed significant improvements in some untrained, linguistic and non-linguistic variables. The first one yielded significant improvement in categorical perception and auditory perception of temporal components of speech. The second study revealed additional improvements in auditory attention, phonological awareness (syllable fusion), reading abilities, and repetition of pseudo-words. Importantly, most improvements persisted after an untrained period of 6 weeks. These results provide new additional arguments for using music as part of systematic therapeutic and instructional practice for dyslexic children. PMID:26834689

Learning Temporal Statistics for Sensory Predictions in Aging.

PubMed

Luft, Caroline Di Bernardi; Baker, Rosalind; Goldstone, Aimee; Zhang, Yang; Kourtzi, Zoe

2016-03-01

Predicting future events based on previous knowledge about the environment is critical for successful everyday interactions. Here, we ask which brain regions support our ability to predict the future based on implicit knowledge about the past in young and older age. Combining behavioral and fMRI measurements, we test whether training on structured temporal sequences improves the ability to predict upcoming sensory events; we then compare brain regions involved in learning predictive structures between young and older adults. Our behavioral results demonstrate that exposure to temporal sequences without feedback facilitates the ability of young and older adults to predict the orientation of an upcoming stimulus. Our fMRI results provide evidence for the involvement of corticostriatal regions in learning predictive structures in both young and older learners. In particular, we showed learning-dependent fMRI responses for structured sequences in frontoparietal regions and the striatum (putamen) for young adults. However, for older adults, learning-dependent activations were observed mainly in subcortical (putamen, thalamus) regions but were weaker in frontoparietal regions. Significant correlations of learning-dependent behavioral and fMRI changes in these regions suggest a strong link between brain activations and behavioral improvement rather than general overactivation. Thus, our findings suggest that predicting future events based on knowledge of temporal statistics engages brain regions involved in implicit learning in both young and older adults.

Land use regression models to assess air pollution exposure in Mexico City using finer spatial and temporal input parameters.

PubMed

Son, Yeongkwon; Osornio-Vargas, Álvaro R; O'Neill, Marie S; Hystad, Perry; Texcalac-Sangrador, José L; Ohman-Strickland, Pamela; Meng, Qingyu; Schwander, Stephan

2018-05-17

The Mexico City Metropolitan Area (MCMA) is one of the largest and most populated urban environments in the world and experiences high air pollution levels. To develop models that estimate pollutant concentrations at fine spatiotemporal scales and provide improved air pollution exposure assessments for health studies in Mexico City. We developed finer spatiotemporal land use regression (LUR) models for PM 2.5 , PM 10 , O 3 , NO 2 , CO and SO 2 using mixed effect models with the Least Absolute Shrinkage and Selection Operator (LASSO). Hourly traffic density was included as a temporal variable besides meteorological and holiday variables. Models of hourly, daily, monthly, 6-monthly and annual averages were developed and evaluated using traditional and novel indices. The developed spatiotemporal LUR models yielded predicted concentrations with good spatial and temporal agreements with measured pollutant levels except for the hourly PM 2.5 , PM 10 and SO 2 . Most of the LUR models met performance goals based on the standardized indices. LUR models with temporal scales greater than one hour were successfully developed using mixed effect models with LASSO and showed superior model performance compared to earlier LUR models, especially for time scales of a day or longer. The newly developed LUR models will be further refined with ongoing Mexico City air pollution sampling campaigns to improve personal exposure assessments. Copyright © 2018. Published by Elsevier B.V.

Temporal characteristic analysis of laser-modulated pulsed X-ray source for space X-ray communication

NASA Astrophysics Data System (ADS)

Hang, Shuang; Liu, Yunpeng; Li, Huan; Tang, Xiaobin; Chen, Da

2018-04-01

X-ray communication (XCOM) is a new communication type and is expected to realize high-speed data transmission in some special communication scenarios, such as deep space communication and blackout communication. This study proposes a high-speed modulated X-ray source scheme based on the laser-to-X-ray conversion. The temporal characteristics of the essential components of the proposed laser-modulated pulsed X-ray source (LMPXS) were analyzed to evaluate its pulse emission performance. Results show that the LMPXS can provide a maximum modulation rate up to 100 Mbps which is expected to significantly improve the data rate of XCOM.

A Bone-Thickness Map as a Guide for Bone-Anchored Port Implantation Surgery in the Temporal Bone

PubMed Central

Guignard, Jérémie; Arnold, Andreas; Weisstanner, Christian; Caversaccio, Marco; Stieger, Christof

2013-01-01

The bone-anchored port (BAP) is an investigational implant, which is intended to be fixed on the temporal bone and provide vascular access. There are a number of implants taking advantage of the stability and available room in the temporal bone. These devices range from implantable hearing aids to percutaneous ports. During temporal bone surgery, injuring critical anatomical structures must be avoided. Several methods for computer-assisted temporal bone surgery are reported, which typically add an additional procedure for the patient. We propose a surgical guide in the form of a bone-thickness map displaying anatomical landmarks that can be used for planning of the surgery, and for the intra-operative decision of the implant’s location. The retro-auricular region of the temporal and parietal bone was marked on cone-beam computed tomography scans and tridimensional surfaces displaying the bone thickness were created from this space. We compared this method using a thickness map (n = 10) with conventional surgery without assistance (n = 5) in isolated human anatomical whole head specimens. The use of the thickness map reduced the rate of Dura Mater exposition from 100% to 20% and suppressed sigmoid sinus exposures. The study shows that a bone-thickness map can be used as a low-complexity method to improve patient’s safety during BAP surgery in the temporal bone. PMID:28788390

A Bone-Thickness Map as a Guide for Bone-Anchored Port Implantation Surgery in the Temporal Bone.

PubMed

Guignard, Jérémie; Arnold, Andreas; Weisstanner, Christian; Caversaccio, Marco; Stieger, Christof

2013-11-19

The bone-anchored port (BAP) is an investigational implant, which is intended to be fixed on the temporal bone and provide vascular access. There are a number of implants taking advantage of the stability and available room in the temporal bone. These devices range from implantable hearing aids to percutaneous ports. During temporal bone surgery, injuring critical anatomical structures must be avoided. Several methods for computer-assisted temporal bone surgery are reported, which typically add an additional procedure for the patient. We propose a surgical guide in the form of a bone-thickness map displaying anatomical landmarks that can be used for planning of the surgery, and for the intra-operative decision of the implant's location. The retro-auricular region of the temporal and parietal bone was marked on cone-beam computed tomography scans and tridimensional surfaces displaying the bone thickness were created from this space. We compared this method using a thickness map ( n = 10) with conventional surgery without assistance ( n = 5) in isolated human anatomical whole head specimens. The use of the thickness map reduced the rate of Dura Mater exposition from 100% to 20% and suppressed sigmoid sinus exposures. The study shows that a bone-thickness map can be used as a low-complexity method to improve patient's safety during BAP surgery in the temporal bone.

PubMed Central

LINKE, R.; LEICHTLE, A.; SHEIKH, F.; SCHMIDT, C.; FRENZEL, H.; GRAEFE, H.; WOLLENBERG, B.; MEYER, J.E.

2013-01-01

SUMMARY Surgery on the temporal bone is technically challenging due to its complex anatomy. Precise anatomical dissection of the human temporal bone is essential and is fundamental for middle ear surgery. We assessed the possible application of a virtual reality temporal bone surgery simulator to the education of ear surgeons. Seventeen ENT physicians with different levels of surgical training and 20 medical students performed an antrotomy with a computer-based virtual temporal bone surgery simulator. The ease, accuracy and timing of the simulated temporal bone surgery were assessed using the automatic assessment software provided by the simulator device and additionally with a modified Final Product Analysis Scale. Trained ENT surgeons, physicians without temporal bone surgical training and medical students were all able to perform the antrotomy. However, the highly trained ENT surgeons were able to complete the surgery in approximately half the time, with better handling and accuracy as assessed by the significant reduction in injury to important middle ear structures. Trained ENT surgeons achieved significantly higher scores using both dissection analysis methods. Surprisingly, there were no significant differences in the results between medical students and physicians without experience in ear surgery. The virtual temporal bone training system can stratify users of known levels of experience. This system can be used not only to improve the surgical skills of trained ENT surgeons for more successful and injury-free surgeries, but also to train inexperienced physicians/medical students in developing their surgical skills for the ear. PMID:24043916

Gap Detection and Temporal Modulation Transfer Function as Behavioral Estimates of Auditory Temporal Acuity Using Band-Limited Stimuli in Young and Older Adults

PubMed Central

Shen, Yi

2015-01-01

Purpose Gap detection and the temporal modulation transfer function (TMTF) are 2 common methods to obtain behavioral estimates of auditory temporal acuity. However, the agreement between the 2 measures is not clear. This study compares results from these 2 methods and their dependencies on listener age and hearing status. Method Gap detection thresholds and the parameters that describe the TMTF (sensitivity and cutoff frequency) were estimated for young and older listeners who were naive to the experimental tasks. Stimuli were 800-Hz-wide noises with upper frequency limits of 2400 Hz, presented at 85 dB SPL. A 2-track procedure (Shen & Richards, 2013) was used for the efficient estimation of the TMTF. Results No significant correlation was found between gap detection threshold and the sensitivity or the cutoff frequency of the TMTF. No significant effect of age and hearing loss on either the gap detection threshold or the TMTF cutoff frequency was found, while the TMTF sensitivity improved with increasing hearing threshold and worsened with increasing age. Conclusion Estimates of temporal acuity using gap detection and TMTF paradigms do not seem to provide a consistent description of the effects of listener age and hearing status on temporal envelope processing. PMID:25087722

A multimodal approach to estimating vigilance using EEG and forehead EOG.

PubMed

Zheng, Wei-Long; Lu, Bao-Liang

2017-04-01

Covert aspects of ongoing user mental states provide key context information for user-aware human computer interactions. In this paper, we focus on the problem of estimating the vigilance of users using EEG and EOG signals. The PERCLOS index as vigilance annotation is obtained from eye tracking glasses. To improve the feasibility and wearability of vigilance estimation devices for real-world applications, we adopt a novel electrode placement for forehead EOG and extract various eye movement features, which contain the principal information of traditional EOG. We explore the effects of EEG from different brain areas and combine EEG and forehead EOG to leverage their complementary characteristics for vigilance estimation. Considering that the vigilance of users is a dynamic changing process because the intrinsic mental states of users involve temporal evolution, we introduce continuous conditional neural field and continuous conditional random field models to capture dynamic temporal dependency. We propose a multimodal approach to estimating vigilance by combining EEG and forehead EOG and incorporating the temporal dependency of vigilance into model training. The experimental results demonstrate that modality fusion can improve the performance compared with a single modality, EOG and EEG contain complementary information for vigilance estimation, and the temporal dependency-based models can enhance the performance of vigilance estimation. From the experimental results, we observe that theta and alpha frequency activities are increased, while gamma frequency activities are decreased in drowsy states in contrast to awake states. The forehead setup allows for the simultaneous collection of EEG and EOG and achieves comparative performance using only four shared electrodes in comparison with the temporal and posterior sites.

Assessment of skills using a virtual reality temporal bone surgery simulator.

PubMed

Linke, R; Leichtle, A; Sheikh, F; Schmidt, C; Frenzel, H; Graefe, H; Wollenberg, B; Meyer, J E

2013-08-01

Surgery on the temporal bone is technically challenging due to its complex anatomy. Precise anatomical dissection of the human temporal bone is essential and is fundamental for middle ear surgery. We assessed the possible application of a virtual reality temporal bone surgery simulator to the education of ear surgeons. Seventeen ENT physicians with different levels of surgical training and 20 medical students performed an antrotomy with a computer-based virtual temporal bone surgery simulator. The ease, accuracy and timing of the simulated temporal bone surgery were assessed using the automatic assessment software provided by the simulator device and additionally with a modified Final Product Analysis Scale. Trained ENT surgeons, physicians without temporal bone surgical training and medical students were all able to perform the antrotomy. However, the highly trained ENT surgeons were able to complete the surgery in approximately half the time, with better handling and accuracy as assessed by the significant reduction in injury to important middle ear structures. Trained ENT surgeons achieved significantly higher scores using both dissection analysis methods. Surprisingly, there were no significant differences in the results between medical students and physicians without experience in ear surgery. The virtual temporal bone training system can stratify users of known levels of experience. This system can be used not only to improve the surgical skills of trained ENT surgeons for more successful and injury-free surgeries, but also to train inexperienced physicians/medical students in developing their surgical skills for the ear.

High-speed adaptive optics for imaging of the living human eye

PubMed Central

Yu, Yongxin; Zhang, Tianjiao; Meadway, Alexander; Wang, Xiaolin; Zhang, Yuhua

2015-01-01

The discovery of high frequency temporal fluctuation of human ocular wave aberration dictates the necessity of high speed adaptive optics (AO) correction for high resolution retinal imaging. We present a high speed AO system for an experimental adaptive optics scanning laser ophthalmoscope (AOSLO). We developed a custom high speed Shack-Hartmann wavefront sensor and maximized the wavefront detection speed based upon a trade-off among the wavefront spatial sampling density, the dynamic range, and the measurement sensitivity. We examined the temporal dynamic property of the ocular wavefront under the AOSLO imaging condition and improved the dual-thread AO control strategy. The high speed AO can be operated with a closed-loop frequency up to 110 Hz. Experiment results demonstrated that the high speed AO system can provide improved compensation for the wave aberration up to 30 Hz in the living human eye. PMID:26368408

Evaluation of Aquarius Version-5 Sea Surface Salinity on various spatial and temporal scales

NASA Astrophysics Data System (ADS)

Lee, T.

2017-12-01

Sea surface salinity (SSS) products from Aquarius have had three public releases with progressive improvement in data quality: Versions 2, 3, and 4, with the last one being released in October 2015. A systematic assessment of the Version-4, Level-3 Aquarius SSS product was performed on various spatial and temporal scales by comparing it with gridded Argo products (Lee 2016, Geophys. Res. Lett.). The comparison showed that the consistency of Aquarius Version-4 SSS with gridded Argo products is comparable to that between two different gridded Argo products. However, significant seasonal biases remain in high-latitude oceans. Further improvements are being made by the Aquarius team. Aquarius Version 5.0 SSS is scheduled to be released in October 2017 as the final version of the Aquarius Project. This presentation provides a similar evaluation of Version-5 SSS as reported by Lee (2016) and contrast it with the current Version-4 SSS.

Improving risk-stratification of Diabetes complications using temporal data mining.

PubMed

Sacchi, Lucia; Dagliati, Arianna; Segagni, Daniele; Leporati, Paola; Chiovato, Luca; Bellazzi, Riccardo

2015-01-01

To understand which factor trigger worsened disease control is a crucial step in Type 2 Diabetes (T2D) patient management. The MOSAIC project, funded by the European Commission under the FP7 program, has been designed to integrate heterogeneous data sources and provide decision support in chronic T2D management through patients' continuous stratification. In this work we show how temporal data mining can be fruitfully exploited to improve risk stratification. In particular, we exploit administrative data on drug purchases to divide patients in meaningful groups. The detection of drug consumption patterns allows stratifying the population on the basis of subjects' purchasing attitude. Merging these findings with clinical values indicates the relevance of the applied methods while showing significant differences in the identified groups. This extensive approach emphasized the exploitation of administrative data to identify patterns able to explain clinical conditions.

A new perspective on global mean sea level (GMSL) acceleration

NASA Astrophysics Data System (ADS)

Watson, Phil J.

2016-06-01

The vast body of contemporary climate change science is largely underpinned by the premise of a measured acceleration from anthropogenic forcings evident in key climate change proxies -- greenhouse gas emissions, temperature, and mean sea level. By virtue, over recent years, the issue of whether or not there is a measurable acceleration in global mean sea level has resulted in fierce, widespread professional, social, and political debate. Attempts to measure acceleration in global mean sea level (GMSL) have often used comparatively crude analysis techniques providing little temporal instruction on these key questions. This work proposes improved techniques to measure real-time velocity and acceleration based on five GMSL reconstructions spanning the time frame from 1807 to 2014 with substantially improved temporal resolution. While this analysis highlights key differences between the respective reconstructions, there is now more robust, convincing evidence of recent acceleration in the trend of GMSL.

Optical probing of high intensity laser interaction with micron-sized cryogenic hydrogen jets

NASA Astrophysics Data System (ADS)

Ziegler, Tim; Rehwald, Martin; Obst, Lieselotte; Bernert, Constantin; Brack, Florian-Emanuel; Curry, Chandra B.; Gauthier, Maxence; Glenzer, Siegfried H.; Göde, Sebastian; Kazak, Lev; Kraft, Stephan D.; Kuntzsch, Michael; Loeser, Markus; Metzkes-Ng, Josefine; Rödel, Christian; Schlenvoigt, Hans-Peter; Schramm, Ulrich; Siebold, Mathias; Tiggesbäumker, Josef; Wolter, Steffen; Zeil, Karl

2018-07-01

Probing the rapid dynamics of plasma evolution in laser-driven plasma interactions provides deeper understanding of experiments in the context of laser-driven ion acceleration and facilitates the interplay with complementing numerical investigations. Besides the microscopic scales involved, strong plasma (self-)emission, predominantly around the harmonics of the driver laser, often complicates the data analysis. We present the concept and the implementation of a stand-alone probe laser system that is temporally synchronized to the driver laser, providing probing wavelengths beyond the harmonics of the driver laser. The capability of this system is shown during a full-scale laser proton acceleration experiment using renewable cryogenic hydrogen jet targets. For further improvements, we studied the influence of probe color, observation angle of the probe and temporal contrast of the driver laser on the probe image quality.

Vegetation Phenology Metrics Derived from Temporally Smoothed and Gap-filled MODIS Data

NASA Technical Reports Server (NTRS)

Tan, Bin; Morisette, Jeff; Wolfe, Robert; Esaias, Wayne; Gao, Feng; Ederer, Greg; Nightingale, Joanne; Nickeson, Jamie E.; Ma, Pete; Pedely, Jeff

2012-01-01

Smoothed and gap-filled VI provides a good base for estimating vegetation phenology metrics. The TIMESAT software was improved by incorporating the ancillary information from MODIS products. A simple assessment of the association between retrieved greenup dates and ground observations indicates satisfactory result from improved TIMESAT software. One application example shows that mapping Nectar Flow Phenology is tractable on a continental scale using hive weight and satellite vegetation data. The phenology data product is supporting more researches in ecology, climate change fields.

High resolution radar-rain gauge data merging for urban hydrology: current practice and beyond

NASA Astrophysics Data System (ADS)

Ochoa Rodriguez, Susana; Wang, Li-Pen; Bailey, Andy; Willems, Patrick; Onof, Christian

2017-04-01

In this work a thorough test is conducted of radar-rain gauge merging techniques at urban scales, under different climatological conditions and rain gauge density scenarios. The aim is to provide guidance regarding the suitability and application of merging methods at urban scales, which is lacking at present. The test is conducted based upon two pilot locations, i.e. the cities of Edinburgh (254 km^2) and Birmingham (431 km^2), for which a total of 96 and 84 tipping bucket rain gauges were respectively available, alongside radar QPEs, dense runoff records and urban drainage models. Three merging techniques, namely Mean Field Bias (MFB) adjustment, kriging with external (KED) and Bayesian (BAY) combination, were selected for testing on grounds of performance and common use. They were initially tested as they were originally formulated and as they are reportedly commonly applied using typically available radar and rain gauge data. Afterwards, they were tested in combination with two special treatments which were identified as having the potential to improve merging applicability for urban hydrology: (1) reduction of temporal sampling errors in radar QPEs through temporal interpolation and (2) singularity-based decomposition of radar QPEs prior to merging. These treatments ultimately aim at improving the consistency between radar and rain gauge records, which has been identified as the chief factor affecting merging performance and is particularly challenging at the fine spatial-temporal resolutions required for urban applications. The main findings of this study are the following: - All merging methods were found to improve the applicability of radar QPEs for urban hydrological applications, but the degree of improvement they provide and the added value of radar information vary for each merging method and are also a function of climatological conditions and rain gauge density scenarios. - Overall, KED displayed the best performance, with BAY being a close second and MFB providing the smallest improvements upon radar QPEs. However, as compared to BAY, KED performance is more sensitive to rain gauge density and to the ability of rain gauges to sample critical features of the rainfall field. By incorporating more information from radar than KED, BAY is less sensitive to rain gauge density and to poor rain gauge predictability and proved able to provide a good representation of convective cells even in cases in which gauges completely missed such structures. - Based on the findings of this study, it is recommended that KED be used when gauge densities are relatively high (of the order of 30 km2 per gauge or higher) and/or when the quality of radar QPEs is known to be very poor, in which case it is desirable to rely more upon rain gauge records. For low rain gauge density situations and QPEs of reasonable quality (as is the case in most of EU), BAY may be a more appropriate choice. MFB should be the last choice; however, it is better than no correction at all. - The two special treatments under consideration successfully improved overall merging performance at the spatial-temporal resolutions required for urban hydrology, with benefits being particularly evident at low rain gauge density conditions.

A Multi-Stage Method for Connecting Participatory Sensing and Noise Simulations

PubMed Central

Hu, Mingyuan; Che, Weitao; Zhang, Qiuju; Luo, Qingli; Lin, Hui

2015-01-01

Most simulation-based noise maps are important for official noise assessment but lack local noise characteristics. The main reasons for this lack of information are that official noise simulations only provide information about expected noise levels, which is limited by the use of large-scale monitoring of noise sources, and are updated infrequently. With the emergence of smart cities and ubiquitous sensing, the possible improvements enabled by sensing technologies provide the possibility to resolve this problem. This study proposed an integrated methodology to propel participatory sensing from its current random and distributed sampling origins to professional noise simulation. The aims of this study were to effectively organize the participatory noise data, to dynamically refine the granularity of the noise features on road segments (e.g., different portions of a road segment), and then to provide a reasonable spatio-temporal data foundation to support noise simulations, which can be of help to researchers in understanding how participatory sensing can play a role in smart cities. This study first discusses the potential limitations of the current participatory sensing and simulation-based official noise maps. Next, we explain how participatory noise data can contribute to a simulation-based noise map by providing (1) spatial matching of the participatory noise data to the virtual partitions at a more microscopic level of road networks; (2) multi-temporal scale noise estimations at the spatial level of virtual partitions; and (3) dynamic aggregation of virtual partitions by comparing the noise values at the relevant temporal scale to form a dynamic segmentation of each road segment to support multiple spatio-temporal noise simulations. In this case study, we demonstrate how this method could play a significant role in a simulation-based noise map. Together, these results demonstrate the potential benefits of participatory noise data as dynamic input sources for noise simulations on multiple spatio-temporal scales. PMID:25621604

A multi-stage method for connecting participatory sensing and noise simulations.

PubMed

Hu, Mingyuan; Che, Weitao; Zhang, Qiuju; Luo, Qingli; Lin, Hui

2015-01-22

Most simulation-based noise maps are important for official noise assessment but lack local noise characteristics. The main reasons for this lack of information are that official noise simulations only provide information about expected noise levels, which is limited by the use of large-scale monitoring of noise sources, and are updated infrequently. With the emergence of smart cities and ubiquitous sensing, the possible improvements enabled by sensing technologies provide the possibility to resolve this problem. This study proposed an integrated methodology to propel participatory sensing from its current random and distributed sampling origins to professional noise simulation. The aims of this study were to effectively organize the participatory noise data, to dynamically refine the granularity of the noise features on road segments (e.g., different portions of a road segment), and then to provide a reasonable spatio-temporal data foundation to support noise simulations, which can be of help to researchers in understanding how participatory sensing can play a role in smart cities. This study first discusses the potential limitations of the current participatory sensing and simulation-based official noise maps. Next, we explain how participatory noise data can contribute to a simulation-based noise map by providing (1) spatial matching of the participatory noise data to the virtual partitions at a more microscopic level of road networks; (2) multi-temporal scale noise estimations at the spatial level of virtual partitions; and (3) dynamic aggregation of virtual partitions by comparing the noise values at the relevant temporal scale to form a dynamic segmentation of each road segment to support multiple spatio-temporal noise simulations. In this case study, we demonstrate how this method could play a significant role in a simulation-based noise map. Together, these results demonstrate the potential benefits of participatory noise data as dynamic input sources for noise simulations on multiple spatio-temporal scales.

Storm Surge Measurement with an Airborne Scanning Radar Altimeter

NASA Technical Reports Server (NTRS)

Wright, C. W.; Walsh, E. J.; Krabill, W. B.; Shaffer, W. A.; Baig, S. R.; Peng, M.; Pietrafesa, L. J.; Garcia, A. W.; Marks, F. D., Jr.; Black, P. G.;

Spatial-temporal models for improved county-level annual estimates

Treesearch

Francis Roesch

2009-01-01

The consumers of data derived from extensive forest inventories often seek annual estimates at a finer spatial scale than that which the inventory was designed to provide. This paper discusses a few model-based and model-assisted estimators to consider for county level attributes that can be applied when the sample would otherwise be inadequate for producing low-...

Efficient temporal and interlayer parameter prediction for weighted prediction in scalable high efficiency video coding

NASA Astrophysics Data System (ADS)

Tsang, Sik-Ho; Chan, Yui-Lam; Siu, Wan-Chi

2017-01-01

Weighted prediction (WP) is an efficient video coding tool that was introduced since the establishment of the H.264/AVC video coding standard, for compensating the temporal illumination change in motion estimation and compensation. WP parameters, including a multiplicative weight and an additive offset for each reference frame, are required to be estimated and transmitted to the decoder by slice header. These parameters cause extra bits in the coded video bitstream. High efficiency video coding (HEVC) provides WP parameter prediction to reduce the overhead. Therefore, WP parameter prediction is crucial to research works or applications, which are related to WP. Prior art has been suggested to further improve the WP parameter prediction by implicit prediction of image characteristics and derivation of parameters. By exploiting both temporal and interlayer redundancies, we propose three WP parameter prediction algorithms, enhanced implicit WP parameter, enhanced direct WP parameter derivation, and interlayer WP parameter, to further improve the coding efficiency of HEVC. Results show that our proposed algorithms can achieve up to 5.83% and 5.23% bitrate reduction compared to the conventional scalable HEVC in the base layer for SNR scalability and 2× spatial scalability, respectively.

Working memory network plasticity after anterior temporal lobe resection: a longitudinal functional magnetic resonance imaging study

PubMed Central

Stretton, Jason; Sidhu, Meneka K.; Winston, Gavin P.; Bartlett, Philippa; McEvoy, Andrew W.; Symms, Mark R.; Koepp, Matthias J.; Thompson, Pamela J.

2014-01-01

Working memory is a crucial cognitive function that is disrupted in temporal lobe epilepsy. It is unclear whether this impairment is a consequence of temporal lobe involvement in working memory processes or due to seizure spread to extratemporal eloquent cortex. Anterior temporal lobe resection controls seizures in 50–80% of patients with drug-resistant temporal lobe epilepsy and the effect of surgery on working memory are poorly understood both at a behavioural and neural level. We investigated the impact of temporal lobe resection on the efficiency and functional anatomy of working memory networks. We studied 33 patients with unilateral medial temporal lobe epilepsy (16 left) before, 3 and 12 months after anterior temporal lobe resection. Fifteen healthy control subjects were also assessed in parallel. All subjects had neuropsychological testing and performed a visuospatial working memory functional magnetic resonance imaging paradigm on these three separate occasions. Changes in activation and deactivation patterns were modelled individually and compared between groups. Changes in task performance were included as regressors of interest to assess the efficiency of changes in the networks. Left and right temporal lobe epilepsy patients were impaired on preoperative measures of working memory compared to controls. Working memory performance did not decline following left or right temporal lobe resection, but improved at 3 and 12 months following left and, to a lesser extent, following right anterior temporal lobe resection. After left anterior temporal lobe resection, improved performance correlated with greater deactivation of the left hippocampal remnant and the contralateral right hippocampus. There was a failure of increased deactivation of the left hippocampal remnant at 3 months after left temporal lobe resection compared to control subjects, which had normalized 12 months after surgery. Following right anterior temporal lobe resection there was a progressive increase of activation in the right superior parietal lobe at 3 and 12 months after surgery. There was greater deactivation of the right hippocampal remnant compared to controls between 3 and 12 months after right anterior temporal lobe resection that was associated with lesser improvement in task performance. Working memory improved after anterior temporal lobe resection, particularly following left-sided resections. Postoperative working memory was reliant on the functional capacity of the hippocampal remnant and, following left resections, the functional reserve of the right hippocampus. These data suggest that working memory following temporal lobe resection is dependent on the engagement of the posterior medial temporal lobes and eloquent cortex. PMID:24691395

Biodiversity can support a greener revolution in Africa

PubMed Central

Snapp, Sieglinde S.; Blackie, Malcolm J.; Gilbert, Robert A.; Bezner-Kerr, Rachel; Kanyama-Phiri, George Y.

2010-01-01

The Asian green revolution trebled grain yields through agrochemical intensification of monocultures. Associated environmental costs have subsequently emerged. A rapidly changing world necessitates sustainability principles be developed to reinvent these technologies and test them at scale. The need is particularly urgent in Africa, where ecosystems are degrading and crop yields have stagnated. An unprecedented opportunity to reverse this trend is unfolding in Malawi, where a 90% subsidy has ensured access to fertilization and improved maize seed, with substantive gains in productivity for millions of farmers. To test if economic and ecological sustainability could be improved, we preformed manipulative experimentation with crop diversity in a countrywide trial (n = 991) and at adaptive, local scales through a decade of participatory research (n = 146). Spatial and temporal treatments compared monoculture maize with legume-diversified maize that included annual and semiperennial (SP) growth habits in temporal and spatial combinations, including rotation, SP rotation, intercrop, and SP intercrop systems. Modest fertilizer intensification doubled grain yield compared with monoculture maize. Biodiversity improved ecosystem function further: SP rotation systems at half-fertilizer rates produced equivalent quantities of grain, on a more stable basis (yield variability reduced from 22% to 13%) compared with monoculture. Across sites, profitability and farmer preference matched: SP rotations provided twofold superior returns, whereas diversification of maize with annual legumes provided more modest returns. In this study, we provide evidence that in Africa, crop diversification can be effective at a countrywide scale, and that shrubby, grain legumes can enhance environmental and food security. PMID:21098285

The role of multisensory interplay in enabling temporal expectations.

PubMed

Ball, Felix; Michels, Lara E; Thiele, Carsten; Noesselt, Toemme

2018-01-01

Temporal regularities can guide our attention to focus on a particular moment in time and to be especially vigilant just then. Previous research provided evidence for the influence of temporal expectation on perceptual processing in unisensory auditory, visual, and tactile contexts. However, in real life we are often exposed to a complex and continuous stream of multisensory events. Here we tested - in a series of experiments - whether temporal expectations can enhance perception in multisensory contexts and whether this enhancement differs from enhancements in unisensory contexts. Our discrimination paradigm contained near-threshold targets (subject-specific 75% discrimination accuracy) embedded in a sequence of distractors. The likelihood of target occurrence (early or late) was manipulated block-wise. Furthermore, we tested whether spatial and modality-specific target uncertainty (i.e. predictable vs. unpredictable target position or modality) would affect temporal expectation (TE) measured with perceptual sensitivity (d ' ) and response times (RT). In all our experiments, hidden temporal regularities improved performance for expected multisensory targets. Moreover, multisensory performance was unaffected by spatial and modality-specific uncertainty, whereas unisensory TE effects on d ' but not RT were modulated by spatial and modality-specific uncertainty. Additionally, the size of the temporal expectation effect, i.e. the increase in perceptual sensitivity and decrease of RT, scaled linearly with the likelihood of expected targets. Finally, temporal expectation effects were unaffected by varying target position within the stream. Together, our results strongly suggest that participants quickly adapt to novel temporal contexts, that they benefit from multisensory (relative to unisensory) stimulation and that multisensory benefits are maximal if the stimulus-driven uncertainty is highest. We propose that enhanced informational content (i.e. multisensory stimulation) enables the robust extraction of temporal regularities which in turn boost (uni-)sensory representations. Copyright © 2017 Elsevier B.V. All rights reserved.

Spatial and temporal adaptations that accompany increasing catching performance during learning.

PubMed

Mazyn, Liesbeth I N; Lenoir, Matthieu; Montagne, Gilles; Savelsbergh, Geert J P

2007-11-01

The authors studied changes in performance and kinematics during the acquisition of a 1-handed catch. Participants were 8 women who took an intensive 2-week training program during which they evolved from poor catchers to subexpert catchers. An increased temporal consistency, shift in spatial location of ball-hand contact away from the body, and higher peak velocity of the transport of the hand toward the ball accompanied their improvement in catching performance. Moreover, novice catchers first adjusted spatial characteristics of the catch to the task constraints and fine-tuned temporal features only later during learning. A principal components analysis on a large set of kinematic variables indicated that a successful catch depends on (a) forward displacement of the hand and (b) the dynamics of the hand closure, thereby providing a kinematic underpinning for the traditional transport-manipulation dissociation in the grasping and catching literature.

Full-direct method for imaging pharmacokinetic parameters in dynamic fluorescence molecular tomography

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

Zhang, Guanglei, E-mail: guangleizhang@bjtu.edu.cn; Department of Biomedical Engineering, School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044; Pu, Huangsheng

2015-02-23

Images of pharmacokinetic parameters (also known as parametric images) in dynamic fluorescence molecular tomography (FMT) can provide three-dimensional metabolic information for biological studies and drug development. However, the ill-posed nature of FMT and the high temporal variation of fluorophore concentration together make it difficult to obtain accurate parametric images in small animals in vivo. In this letter, we present a method to directly reconstruct the parametric images from the boundary measurements based on hybrid FMT/X-ray computed tomography (XCT) system. This method can not only utilize structural priors obtained from the XCT system to mitigate the ill-posedness of FMT but alsomore » make full use of the temporal correlations of boundary measurements to model the high temporal variation of fluorophore concentration. The results of numerical simulation and mouse experiment demonstrate that the proposed method leads to significant improvements in the reconstruction quality of parametric images.« less

Next generation gamma-ray Cherenkov detectors for the National Ignition Facility.

PubMed

Herrmann, H W; Kim, Y H; McEvoy, A M; Zylstra, A B; Young, C S; Lopez, F E; Griego, J R; Fatherley, V E; Oertel, J A; Stoeffl, W; Khater, H; Hernandez, J E; Carpenter, A; Rubery, M S; Horsfield, C J; Gales, S; Leatherland, A; Hilsabeck, T; Kilkenny, J D; Malone, R M; Hares, J D; Milnes, J; Shmayda, W T; Stoeckl, C; Batha, S H

2016-11-01

The newest generation of Gas Cherenkov Detector (GCD-3) employed in Inertial Confinement Fusion experiments at the Omega Laser Facility has provided improved performance over previous generations. Comparison of reaction histories measured using two different deuterium-tritium fusion products, namely gamma rays using GCD and neutrons using Neutron Temporal Diagnostic (NTD), have provided added credibility to both techniques. GCD-3 is now being brought to the National Ignition Facility (NIF) to supplement the existing Gamma Reaction History (GRH-6m) located 6 m from target chamber center (TCC). Initially it will be located in a reentrant well located 3.9 m from TCC. Data from GCD-3 will inform the design of a heavily-shielded "Super" GCD to be located as close as 20 cm from TCC. It will also provide a test-bed for faster optical detectors, potentially lowering the temporal resolution from the current ∼100 ps state-of-the-art photomultiplier tubes (PMT) to ∼10 ps Pulse Dilation PMT technology currently under development.

The retrospective binning method improves the consistency of phase binning in respiratory-gated PET/CT

NASA Astrophysics Data System (ADS)

Didierlaurent, D.; Ribes, S.; Batatia, H.; Jaudet, C.; Dierickx, L. O.; Zerdoud, S.; Brillouet, S.; Caselles, O.; Courbon, F.

2012-12-01

This study assesses the accuracy of prospective phase-gated PET/CT data binning and presents a retrospective data binning method that improves image quality and consistency. Respiratory signals from 17 patients who underwent 4D PET/CT were analysed to evaluate the reproducibility of temporal triggers used for the standard phase-based gating method. Breathing signals were reprocessed to implement retrospective PET data binning. The mean and standard deviation of time lags between automatic triggers provided by the Real-time Position Management (RPM, Varian) gating device and inhalation peaks derived from respiratory curves were computed for each patient. The total number of respiratory cycles available for 4D PET/CT according to the binning mode (prospective versus retrospective) was compared. The maximum standardized uptake value (SUVmax), biological tumour volume (BTV) and tumour trajectory measures were determined from the PET/CT images of five patients. Compared to retrospective binning (RB), prospective gating approach led to (i) a significant loss in breathing cycles (15%) and (ii) the inconsistency of data binning due to temporal dispersion of triggers (average 396 ms). Consequently, tumour characterization could be impacted. In retrospective mode, SUVmax was up to 27% higher, where no significant difference appeared in BTV. In addition, prospective mode gave an inconsistent spatial location of the tumour throughout the bins. Improved consistency with breathing patterns and greater motion amplitude of the tumour centroid were observed with retrospective mode. The detection of the tumour motion and trajectory was improved also for small temporal dispersion of triggers. This study shows that the binning mode could have a significant impact on 4D PET images. The consistency of triggers with breathing signals should be checked before clinical use of gated PET/CT images, and our RB method improves 4D PET/CT image quantification.

Review of recent advances in analytical techniques for the determination of neurotransmitters

PubMed Central

Perry, Maura; Li, Qiang; Kennedy, Robert T.

2009-01-01

Methods and advances for monitoring neurotransmitters in vivo or for tissue analysis of neurotransmitters over the last five years are reviewed. The review is organized primarily by neurotransmitter type. Transmitter and related compounds may be monitored by either in vivo sampling coupled to analytical methods or implanted sensors. Sampling is primarily performed using microdialysis, but low-flow push-pull perfusion may offer advantages of spatial resolution while minimizing the tissue disruption associated with higher flow rates. Analytical techniques coupled to these sampling methods include liquid chromatography, capillary electrophoresis, enzyme assays, sensors, and mass spectrometry. Methods for the detection of amino acid, monoamine, neuropeptide, acetylcholine, nucleoside, and soluable gas neurotransmitters have been developed and improved upon. Advances in the speed and sensitivity of these methods have enabled improvements in temporal resolution and increased the number of compounds detectable. Similar advances have enabled improved detection at tissue samples, with a substantial emphasis on single cell and other small samples. Sensors provide excellent temporal and spatial resolution for in vivo monitoring. Advances in application to catecholamines, indoleamines, and amino acids have been prominent. Improvements in stability, sensitivity, and selectivity of the sensors have been of paramount interest. PMID:19800472

A fast and flexible MRI system for the study of dynamic vocal tract shaping.

PubMed

Lingala, Sajan Goud; Zhu, Yinghua; Kim, Yoon-Chul; Toutios, Asterios; Narayanan, Shrikanth; Nayak, Krishna S

2017-01-01

The aim of this work was to develop and evaluate an MRI-based system for study of dynamic vocal tract shaping during speech production, which provides high spatial and temporal resolution. The proposed system utilizes (a) custom eight-channel upper airway coils that have high sensitivity to upper airway regions of interest, (b) two-dimensional golden angle spiral gradient echo acquisition, (c) on-the-fly view-sharing reconstruction, and (d) off-line temporal finite difference constrained reconstruction. The system also provides simultaneous noise-cancelled and temporally aligned audio. The system is evaluated in 3 healthy volunteers, and 1 tongue cancer patient, with a broad range of speech tasks. We report spatiotemporal resolutions of 2.4 × 2.4 mm 2 every 12 ms for single-slice imaging, and 2.4 × 2.4 mm 2 every 36 ms for three-slice imaging, which reflects roughly 7-fold acceleration over Nyquist sampling. This system demonstrates improved temporal fidelity in capturing rapid vocal tract shaping for tasks, such as producing consonant clusters in speech, and beat-boxing sounds. Novel acoustic-articulatory analysis was also demonstrated. A synergistic combination of custom coils, spiral acquisitions, and constrained reconstruction enables visualization of rapid speech with high spatiotemporal resolution in multiple planes. Magn Reson Med 77:112-125, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Practical low-cost visual communication using binary images for deaf sign language.

PubMed

Manoranjan, M D; Robinson, J A

2000-03-01

Deaf sign language transmitted by video requires a temporal resolution of 8 to 10 frames/s for effective communication. Conventional videoconferencing applications, when operated over low bandwidth telephone lines, provide very low temporal resolution of pictures, of the order of less than a frame per second, resulting in jerky movement of objects. This paper presents a practical solution for sign language communication, offering adequate temporal resolution of images using moving binary sketches or cartoons, implemented on standard personal computer hardware with low-cost cameras and communicating over telephone lines. To extract cartoon points an efficient feature extraction algorithm adaptive to the global statistics of the image is proposed. To improve the subjective quality of the binary images, irreversible preprocessing techniques, such as isolated point removal and predictive filtering, are used. A simple, efficient and fast recursive temporal prefiltering scheme, using histograms of successive frames, reduces the additive and multiplicative noise from low-cost cameras. An efficient three-dimensional (3-D) compression scheme codes the binary sketches. Subjective tests performed on the system confirm that it can be used for sign language communication over telephone lines.

Mapping child maltreatment risk: a 12-year spatio-temporal analysis of neighborhood influences.

PubMed

Gracia, Enrique; López-Quílez, Antonio; Marco, Miriam; Lila, Marisol

2017-10-18

'Place' matters in understanding prevalence variations and inequalities in child maltreatment risk. However, most studies examining ecological variations in child maltreatment risk fail to take into account the implications of the spatial and temporal dimensions of neighborhoods. In this study, we conduct a high-resolution small-area study to analyze the influence of neighborhood characteristics on the spatio-temporal epidemiology of child maltreatment risk. We conducted a 12-year (2004-2015) small-area Bayesian spatio-temporal epidemiological study with all families with child maltreatment protection measures in the city of Valencia, Spain. As neighborhood units, we used 552 census block groups. Cases were geocoded using the family address. Neighborhood-level characteristics analyzed included three indicators of neighborhood disadvantage-neighborhood economic status, neighborhood education level, and levels of policing activity-, immigrant concentration, and residential instability. Bayesian spatio-temporal modelling and disease mapping methods were used to provide area-specific risk estimations. Results from a spatio-temporal autoregressive model showed that neighborhoods with low levels of economic and educational status, with high levels of policing activity, and high immigrant concentration had higher levels of substantiated child maltreatment risk. Disease mapping methods were used to analyze areas of excess risk. Results showed chronic spatial patterns of high child maltreatment risk during the years analyzed, as well as stability over time in areas of low risk. Areas with increased or decreased child maltreatment risk over the years were also observed. A spatio-temporal epidemiological approach to study the geographical patterns, trends over time, and the contextual determinants of child maltreatment risk can provide a useful method to inform policy and action. This method can offer a more accurate description of the problem, and help to inform more localized prevention and intervention strategies. This new approach can also contribute to an improved epidemiological surveillance system to detect ecological variations in risk, and to assess the effectiveness of the initiatives to reduce this risk.

Assimilating a decade of hydrometeorological ship measurements across the North American Great Lakes

NASA Astrophysics Data System (ADS)

Fries, K. J.; Kerkez, B.

2015-12-01

We use a decade of measurements made by the Volunteer Observing Ships (VOS) program on the North American Great Lakes to derive spatial estimates of over-lake air temperature, sea surface temperature, dewpoint, and wind speed. This Lagrangian data set, which annually comprises over 200,000 point observations from over 80,000 ship reports across a 244,000 square kilometer study area, is assimilated using a Gaussian Process machine learning algorithm. This algorithm classifies a model for each hydrometeorological variable using a combination of latitudes, longitudes, seasons of the year, as well as predictions made by the National Digital Forecast Database (NDFD) and Great Lakes Coastal Forecasting System (GLCFS) operational models. We show that our data-driven method significantly improves the spatial and temporal estimation of overlake hydrometeorological variables, while simultaneously providing uncertainty estimates that can be used to improve historical and future predictions on dense spatial and temporal scales. This method stands to improve the prediction of water levels on the Great Lakes, which comprise over 90% of America's surface fresh water, and impact the lives of millions of people living in the basin.

High Temporal Resolution Permafrost Monitoring Using a Multiple Stack Insar Technique

NASA Astrophysics Data System (ADS)

Eppler, J.; Kubanski, M.; Sharma, J.; Busler, J.

2015-04-01

The combined effect of climate change and accelerated economic development in Northern regions increases the threat of permafrost related surface deformation to buildings and transportation infrastructure. Satellite based InSAR provides a means for monitoring infrastructure that may be both remote and spatially extensive. However, permafrost poses challenges for InSAR monitoring due to the complex temporal deformation patterns caused by both seasonal active layer fluctuations and long-term changes in permafrost thickness. These dynamics suggest a need for increasing the temporal resolution of multi-temporal InSAR methods. To address this issue we have developed a method that combines and jointly processes two or more same side geometry InSAR stacks to provide a high-temporal resolution estimate of surface deformation. The method allows for combining stacks from more than a single SAR sensor and for a combination of frequency bands. Data for this work have been collected and analysed for an area near the community of Umiujaq, Quebec in Northern Canada and include scenes from RADARSAT-2, TerraSAR-X and COSMO-SkyMed. Multiple stack based surface deformation estimates are compared for several cases including results from the three sensors individually and for all sensors combined. The test cases show substantially similar surface deformation results which correlate well with surficial geology. The best spatial coverage of coherent targets was achieved when data from all sensors were combined. The proposed multiple stack method is demonstrated to improve the estimation of surface deformation in permafrost affected areas and shows potential for deriving InSAR based permafrost classification maps to aid in the monitoring of Northern infrastructure.

Longitudinal functional connectivity changes correlate with mood improvement after regular exercise in a dose-dependent fashion.

PubMed

Tozzi, Leonardo; Carballedo, Angela; Lavelle, Grace; Doolin, Kelly; Doyle, Myles; Amico, Francesco; McCarthy, Hazel; Gormley, John; Lord, Anton; O'Keane, Veronica; Frodl, Thomas

2016-04-01

Exercise increases wellbeing and improves mood. It is however unclear how these mood changes relate to brain function. We conducted a randomized controlled trial investigating resting-state modifications in healthy adults after an extended period of aerobic physical exercise and their relationship with mood improvements. We aimed to identify novel functional networks whose activity could provide a physiological counterpart to the mood-related benefits of exercise. Thirty-eight healthy sedentary volunteers were randomised to either the aerobic exercise group of the study or a control group. Participants in the exercise group attended aerobic sessions with a physiotherapist twice a week for 16 weeks. Resting-state modifications using magnetic resonance imaging were assessed before and after the programme and related to mood changes. An unbiased approach using graph metrics and network-based statistics was adopted. Exercise reduced mood disturbance and improved emotional wellbeing. It also induced a decrease in local efficiency in the parahippocampal lobe through strengthening of the functional connections from this structure to the supramarginal gyrus, precentral area, superior temporal gyrus and temporal pole. Changes in mood disturbance following exercise were correlated with those in connectivity between parahippocampal gyrus and superior temporal gyrus as well as with the amount of training. No changes were detected in the control group. In conclusion, connectivity from the parahippocampal gyrus to motor, sensory integration and mood regulation areas was strengthened through exercise. These functional changes might be related to the benefits of regular physical activity on mood. © 2016 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

An Improved GRACE Terrestrial Water Storage Assimilation System For Estimating Large-Scale Soil Moisture and Shallow Groundwater

NASA Astrophysics Data System (ADS)

Girotto, M.; De Lannoy, G. J. M.; Reichle, R. H.; Rodell, M.

2015-12-01

The Gravity Recovery And Climate Experiment (GRACE) mission is unique because it provides highly accurate column integrated estimates of terrestrial water storage (TWS) variations. Major limitations of GRACE-based TWS observations are related to their monthly temporal and coarse spatial resolution (around 330 km at the equator), and to the vertical integration of the water storage components. These challenges can be addressed through data assimilation. To date, it is still not obvious how best to assimilate GRACE-TWS observations into a land surface model, in order to improve hydrological variables, and many details have yet to be worked out. This presentation discusses specific recent features of the assimilation of gridded GRACE-TWS data into the NASA Goddard Earth Observing System (GEOS-5) Catchment land surface model to improve soil moisture and shallow groundwater estimates at the continental scale. The major recent advancements introduced by the presented work with respect to earlier systems include: 1) the assimilation of gridded GRACE-TWS data product with scaling factors that are specifically derived for data assimilation purposes only; 2) the assimilation is performed through a 3D assimilation scheme, in which reasonable spatial and temporal error standard deviations and correlations are exploited; 3) the analysis step uses an optimized calculation and application of the analysis increments; 4) a poor-man's adaptive estimation of a spatially variable measurement error. This work shows that even if they are characterized by a coarse spatial and temporal resolution, the observed column integrated GRACE-TWS data have potential for improving our understanding of soil moisture and shallow groundwater variations.

On the use of orientation filters for 3D reconstruction in event-driven stereo vision

PubMed Central

Camuñas-Mesa, Luis A.; Serrano-Gotarredona, Teresa; Ieng, Sio H.; Benosman, Ryad B.; Linares-Barranco, Bernabe

2014-01-01

The recently developed Dynamic Vision Sensors (DVS) sense visual information asynchronously and code it into trains of events with sub-micro second temporal resolution. This high temporal precision makes the output of these sensors especially suited for dynamic 3D visual reconstruction, by matching corresponding events generated by two different sensors in a stereo setup. This paper explores the use of Gabor filters to extract information about the orientation of the object edges that produce the events, therefore increasing the number of constraints applied to the matching algorithm. This strategy provides more reliably matched pairs of events, improving the final 3D reconstruction. PMID:24744694

High Resolution Mapping of Wetland Ecosystems SPOT-5 Take 5 for Evaluation of Sentinel-2

NASA Astrophysics Data System (ADS)

Ade, Christiana; Hestir, Erin L.; Khanna, Shruti; Ustin, Susan L.

2016-08-01

Around the world wetlands are critical to human societies and ecosystems, providing services such as habitat, water, food and fiber, flood and nutrient control, and cultural, recreational and religious value. However, the dynamic nature of tidal wetlands makes measuring ecosystem responses to climate change, seasonal inundation regimes, and anthropogenic disturbance from current and previous Earth observing sensors challenging due to limited spatial and temporal resolutions. Sentinel- 2 will directly address this challenge by providing high spatial resolution data with frequent revisit time. This pilot study aims to develop methodology for future Sentinel-2 products and highlight the variability of tidal wetland ecosystems, thereby demonstrating the necessity of improved spatial particularly temporal resolution. Here the simulated Sentinel-2 dataset from the SPOT-5 Take 5 experiment reveals the capacity of the new sensor to simultaneously assess tidal wetland ecosystem phenology and water quality in inland waters.

Substituting root numbers for length: Improving the use of minirhizotrons to study fine root dynamics

Treesearch

Tracey L. Crocker; Ron L. Hendrick; Roger W. Ruess; Kurt S. Pregitzer; Andrew J. Burton; Michael F. Allen; Jianping Shan; Lawrence A. Morris

2003-01-01

Minirhizotrons provide a unique way to repeatedly measure the production and fate of individual root segments, while minimizing soil disturbance and the confounding of spatial-temporal variation. However, the time associated with processing videotaped minirhizotron images limits the amount of data that can be extracted in a reasonable amount of time. We found that this...

Exploiting Sequential Patterns Found in Users' Solutions and Virtual Tutor Behavior to Improve Assistance in ITS

ERIC Educational Resources Information Center

Fournier-Viger, Philippe; Faghihi, Usef; Nkambou, Roger; Nguifo, Engelbert Mephu

2010-01-01

We propose to mine temporal patterns in Intelligent Tutoring Systems (ITSs) to uncover useful knowledge that can enhance their ability to provide assistance. To discover patterns, we suggest using a custom, sequential pattern-mining algorithm. Two ways of applying the algorithm to enhance an ITS's capabilities are addressed. The first is to…

Broadband, red-edge information from satellites improves early stress detection in a New Mexico conifer woodland

Treesearch

Jan U.H. Eitel; Lee A. Vierling; Marcy E. Litvak; Dan S. Long; Urs Schulthess; Alan A. Ager; Dan J. Krofcheck; Leo Stoscheck

2011-01-01

Multiple plant stresses can affect the health, esthetic condition, and timber harvest value of conifer forests. To monitor spatial and temporal dynamic forest stress conditions, timely, accurate, and cost-effective information is needed that could be provided by remote sensing. Recently, satellite imagery has become available via the RapidEye satellite constellation to...

Mapping of land cover in northern California with simulated hyperspectral satellite imagery

NASA Astrophysics Data System (ADS)

Clark, Matthew L.; Kilham, Nina E.

2016-09-01

Land-cover maps are important science products needed for natural resource and ecosystem service management, biodiversity conservation planning, and assessing human-induced and natural drivers of land change. Analysis of hyperspectral, or imaging spectrometer, imagery has shown an impressive capacity to map a wide range of natural and anthropogenic land cover. Applications have been mostly with single-date imagery from relatively small spatial extents. Future hyperspectral satellites will provide imagery at greater spatial and temporal scales, and there is a need to assess techniques for mapping land cover with these data. Here we used simulated multi-temporal HyspIRI satellite imagery over a 30,000 km2 area in the San Francisco Bay Area, California to assess its capabilities for mapping classes defined by the international Land Cover Classification System (LCCS). We employed a mapping methodology and analysis framework that is applicable to regional and global scales. We used the Random Forests classifier with three sets of predictor variables (reflectance, MNF, hyperspectral metrics), two temporal resolutions (summer, spring-summer-fall), two sample scales (pixel, polygon) and two levels of classification complexity (12, 20 classes). Hyperspectral metrics provided a 16.4-21.8% and 3.1-6.7% increase in overall accuracy relative to MNF and reflectance bands, respectively, depending on pixel or polygon scales of analysis. Multi-temporal metrics improved overall accuracy by 0.9-3.1% over summer metrics, yet increases were only significant at the pixel scale of analysis. Overall accuracy at pixel scales was 72.2% (Kappa 0.70) with three seasons of metrics. Anthropogenic and homogenous natural vegetation classes had relatively high confidence and producer and user accuracies were over 70%; in comparison, woodland and forest classes had considerable confusion. We next focused on plant functional types with relatively pure spectra by removing open-canopy shrublands, woodlands and mixed forests from the classification. This 12-class map had significantly improved accuracy of 85.1% (Kappa 0.83) and most classes had over 70% producer and user accuracies. Finally, we summarized important metrics from the multi-temporal Random Forests to infer the underlying chemical and structural properties that best discriminated our land-cover classes across seasons.

Visual search of cyclic spatio-temporal events

NASA Astrophysics Data System (ADS)

Gautier, Jacques; Davoine, Paule-Annick; Cunty, Claire

2018-05-01

The analysis of spatio-temporal events, and especially of relationships between their different dimensions (space-time-thematic attributes), can be done with geovisualization interfaces. But few geovisualization tools integrate the cyclic dimension of spatio-temporal event series (natural events or social events). Time Coil and Time Wave diagrams represent both the linear time and the cyclic time. By introducing a cyclic temporal scale, these diagrams may highlight the cyclic characteristics of spatio-temporal events. However, the settable cyclic temporal scales are limited to usual durations like days or months. Because of that, these diagrams cannot be used to visualize cyclic events, which reappear with an unusual period, and don't allow to make a visual search of cyclic events. Also, they don't give the possibility to identify the relationships between the cyclic behavior of the events and their spatial features, and more especially to identify localised cyclic events. The lack of possibilities to represent the cyclic time, outside of the temporal diagram of multi-view geovisualization interfaces, limits the analysis of relationships between the cyclic reappearance of events and their other dimensions. In this paper, we propose a method and a geovisualization tool, based on the extension of Time Coil and Time Wave, to provide a visual search of cyclic events, by allowing to set any possible duration to the diagram's cyclic temporal scale. We also propose a symbology approach to push the representation of the cyclic time into the map, in order to improve the analysis of relationships between space and the cyclic behavior of events.

A multimodal approach to estimating vigilance using EEG and forehead EOG

NASA Astrophysics Data System (ADS)

Zheng, Wei-Long; Lu, Bao-Liang

2017-04-01

Objective. Covert aspects of ongoing user mental states provide key context information for user-aware human computer interactions. In this paper, we focus on the problem of estimating the vigilance of users using EEG and EOG signals. Approach. The PERCLOS index as vigilance annotation is obtained from eye tracking glasses. To improve the feasibility and wearability of vigilance estimation devices for real-world applications, we adopt a novel electrode placement for forehead EOG and extract various eye movement features, which contain the principal information of traditional EOG. We explore the effects of EEG from different brain areas and combine EEG and forehead EOG to leverage their complementary characteristics for vigilance estimation. Considering that the vigilance of users is a dynamic changing process because the intrinsic mental states of users involve temporal evolution, we introduce continuous conditional neural field and continuous conditional random field models to capture dynamic temporal dependency. Main results. We propose a multimodal approach to estimating vigilance by combining EEG and forehead EOG and incorporating the temporal dependency of vigilance into model training. The experimental results demonstrate that modality fusion can improve the performance compared with a single modality, EOG and EEG contain complementary information for vigilance estimation, and the temporal dependency-based models can enhance the performance of vigilance estimation. From the experimental results, we observe that theta and alpha frequency activities are increased, while gamma frequency activities are decreased in drowsy states in contrast to awake states. Significance. The forehead setup allows for the simultaneous collection of EEG and EOG and achieves comparative performance using only four shared electrodes in comparison with the temporal and posterior sites.

Improving temporal bone dissection using self-directed virtual reality simulation: results of a randomized blinded control trial.

PubMed

Zhao, Yi Chen; Kennedy, Gregor; Yukawa, Kumiko; Pyman, Brian; O'Leary, Stephen

2011-03-01

A significant benefit of virtual reality (VR) simulation is the ability to provide self-direct learning for trainees. This study aims to determine whether there are any differences in performance of cadaver temporal bone dissections between novices who received traditional teaching methods and those who received unsupervised self-directed learning in a VR temporal bone simulator. Randomized blinded control trial. Royal Victorian Eye and Ear Hospital. Twenty novice trainees. After receiving an hour lecture, participants were randomized into 2 groups to receive an additional 2 hours of training via traditional teaching methods or self-directed learning using a VR simulator with automated guidance. The simulation environment presented participants with structured training tasks, which were accompanied by real-time computer-generated feedback as well as real operative videos and photos. After the training, trainees were asked to perform a cortical mastoidectomy on a cadaveric temporal bone. The dissection was videotaped and assessed by 3 otologists blinded to participants' teaching group. The overall performance scores of the simulator-based training group were significantly higher than those of the traditional training group (67% vs 29%; P < .001), with an intraclass correlation coefficient of 0.93, indicating excellent interrater reliability. Using other assessments of performance, such as injury size, the VR simulator-based training group also performed better than the traditional group. This study indicates that self-directed learning on VR simulators can be used to improve performance on cadaver dissection in novice trainees compared with traditional teaching methods alone.

Improving spatio-temporal benefit transfers for pest control by generalist predators in cotton in the southwestern U.S.

USGS Publications Warehouse

Wiederholt, Ruscena; Bagstad, Kenneth J.; McCracken, Gary F.; Diffendorfer, Jay E.; Loomis, John B.; Semmens, Darius J.; Russell, Amy L.; Sansone, Chris; LaSharr, Kelsie; Cryan, Paul; Reynoso, Claudia; Medellin, Rodrigo A.; Lopez-Hoffman, Laura

2017-01-01

Given rapid changes in agricultural practice, it is critical to understand how alterations in ecological, technological, and economic conditions over time and space impact ecosystem services in agroecosystems. Here, we present a benefit transfer approach to quantify cotton pest-control services provided by a generalist predator, the Mexican free-tailed bat (Tadarida brasiliensis mexicana), in the southwestern United States. We show that pest-control estimates derived using (1) a compound spatial–temporal model – which incorporates spatial and temporal variability in crop pest-control service values – are likely to exhibit less error than those derived using (2) a simple-spatial model (i.e., a model that extrapolates values derived for one area directly, without adjustment, to other areas) or (3) a simple-temporal model (i.e., a model that extrapolates data from a few points in time over longer time periods). Using our compound spatial–temporal approach, the annualized pest-control value was \\$12.2 million, in contrast to an estimate of \\$70.1 million (5.7 times greater), obtained from the simple-spatial approach. Using estimates from one year (simple-temporal approach) revealed large value differences (0.4 times smaller to 2 times greater). Finally, we present a detailed protocol for valuing pest-control services, which can be used to develop robust pest-control transfer functions for generalist predators in agroecosystems.

Temporal cognition: Connecting subjective time to perception, attention, and memory.

PubMed

Matthews, William J; Meck, Warren H

2016-08-01

Time is a universal psychological dimension, but time perception has often been studied and discussed in relative isolation. Increasingly, researchers are searching for unifying principles and integrated models that link time perception to other domains. In this review, we survey the links between temporal cognition and other psychological processes. Specifically, we describe how subjective duration is affected by nontemporal stimulus properties (perception), the allocation of processing resources (attention), and past experience with the stimulus (memory). We show that many of these connections instantiate a "processing principle," according to which perceived time is positively related to perceptual vividity and the ease of extracting information from the stimulus. This empirical generalization generates testable predictions and provides a starting-point for integrated theoretical frameworks. By outlining some of the links between temporal cognition and other domains, and by providing a unifying principle for understanding these effects, we hope to encourage time-perception researchers to situate their work within broader theoretical frameworks, and that researchers from other fields will be inspired to apply their insights, techniques, and theorizing to improve our understanding of the representation and judgment of time. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Spectral Unmixing Analysis of Time Series Landsat 8 Images

NASA Astrophysics Data System (ADS)

Zhuo, R.; Xu, L.; Peng, J.; Chen, Y.

2018-05-01

Temporal analysis of Landsat 8 images opens up new opportunities in the unmixing procedure. Although spectral analysis of time series Landsat imagery has its own advantage, it has rarely been studied. Nevertheless, using the temporal information can provide improved unmixing performance when compared to independent image analyses. Moreover, different land cover types may demonstrate different temporal patterns, which can aid the discrimination of different natures. Therefore, this letter presents time series K-P-Means, a new solution to the problem of unmixing time series Landsat imagery. The proposed approach is to obtain the "purified" pixels in order to achieve optimal unmixing performance. The vertex component analysis (VCA) is used to extract endmembers for endmember initialization. First, nonnegative least square (NNLS) is used to estimate abundance maps by using the endmember. Then, the estimated endmember is the mean value of "purified" pixels, which is the residual of the mixed pixel after excluding the contribution of all nondominant endmembers. Assembling two main steps (abundance estimation and endmember update) into the iterative optimization framework generates the complete algorithm. Experiments using both simulated and real Landsat 8 images show that the proposed "joint unmixing" approach provides more accurate endmember and abundance estimation results compared with "separate unmixing" approach.

Applications of the BIOPHYS Algorithm for Physically-Based Retrieval of Biophysical, Structural and Forest Disturbance Information

NASA Technical Reports Server (NTRS)

Peddle, Derek R.; Huemmrich, K. Fred; Hall, Forrest G.; Masek, Jeffrey G.; Soenen, Scott A.; Jackson, Chris D.

2011-01-01

Canopy reflectance model inversion using look-up table approaches provides powerful and flexible options for deriving improved forest biophysical structural information (BSI) compared with traditional statistical empirical methods. The BIOPHYS algorithm is an improved, physically-based inversion approach for deriving BSI for independent use and validation and for monitoring, inventory and quantifying forest disturbance as well as input to ecosystem, climate and carbon models. Based on the multiple-forward mode (MFM) inversion approach, BIOPHYS results were summarized from different studies (Minnesota/NASA COVER; Virginia/LEDAPS; Saskatchewan/BOREAS), sensors (airborne MMR; Landsat; MODIS) and models (GeoSail; GOMS). Applications output included forest density, height, crown dimension, branch and green leaf area, canopy cover, disturbance estimates based on multi-temporal chronosequences, and structural change following recovery from forest fires over the last century. Good correspondences with validation field data were obtained. Integrated analyses of multiple solar and view angle imagery further improved retrievals compared with single pass data. Quantifying ecosystem dynamics such as the area and percent of forest disturbance, early regrowth and succession provide essential inputs to process-driven models of carbon flux. BIOPHYS is well suited for large-area, multi-temporal applications involving multiple image sets and mosaics for assessing vegetation disturbance and quantifying biophysical structural dynamics and change. It is also suitable for integration with forest inventory, monitoring, updating, and other programs.

Spatio-temporal Granger causality: a new framework

PubMed Central

Luo, Qiang; Lu, Wenlian; Cheng, Wei; Valdes-Sosa, Pedro A.; Wen, Xiaotong; Ding, Mingzhou; Feng, Jianfeng

2015-01-01

That physiological oscillations of various frequencies are present in fMRI signals is the rule, not the exception. Herein, we propose a novel theoretical framework, spatio-temporal Granger causality, which allows us to more reliably and precisely estimate the Granger causality from experimental datasets possessing time-varying properties caused by physiological oscillations. Within this framework, Granger causality is redefined as a global index measuring the directed information flow between two time series with time-varying properties. Both theoretical analyses and numerical examples demonstrate that Granger causality is a monotonically increasing function of the temporal resolution used in the estimation. This is consistent with the general principle of coarse graining, which causes information loss by smoothing out very fine-scale details in time and space. Our results confirm that the Granger causality at the finer spatio-temporal scales considerably outperforms the traditional approach in terms of an improved consistency between two resting-state scans of the same subject. To optimally estimate the Granger causality, the proposed theoretical framework is implemented through a combination of several approaches, such as dividing the optimal time window and estimating the parameters at the fine temporal and spatial scales. Taken together, our approach provides a novel and robust framework for estimating the Granger causality from fMRI, EEG, and other related data. PMID:23643924

Optimization of the Reconstruction Interval in Neurovascular 4D-CTA Imaging

PubMed Central

Hoogenboom, T.C.H.; van Beurden, R.M.J.; van Teylingen, B.; Schenk, B.; Willems, P.W.A.

2012-01-01

Summary Time resolved whole brain CT angiography (4D-CTA) is a novel imaging technology providing information regarding blood flow. One of the factors that influence the diagnostic value of this examination is the temporal resolution, which is affected by the gantry rotation speed during acquisition and the reconstruction interval during post-processing. Post-processing determines the time spacing between two reconstructed volumes and, unlike rotation speed, does not affect radiation burden. The data sets of six patients who underwent a cranial 4D-CTA were used for this study. Raw data was acquired using a 320-slice scanner with a rotation speed of 2 Hz. The arterial to venous passage of an intravenous contrast bolus was captured during a 15 s continuous scan. The raw data was reconstructed using four different reconstruction-intervals: 0.2, 0.3, 0.5 and 1.0 s. The results were rated by two observers using a standardized score sheet. The appearance of each lesion was rated correctly in all readings. Scoring for quality of temporal resolution revealed a stepwise improvement from the 1.0 s interval to the 0.3 s interval, while no discernable improvement was noted between the 0.3 s and 0.2 s interval. An increase in temporal resolution may improve the diagnostic quality of cranial 4D-CTA. Using a rotation speed of 0.5 s, the optimal reconstruction interval appears to be 0.3 s, beyond which, changes can no longer be discerned. PMID:23217631

Design of 4D x-ray tomography experiments for reconstruction using regularized iterative algorithms

NASA Astrophysics Data System (ADS)

Mohan, K. Aditya

2017-10-01

4D X-ray computed tomography (4D-XCT) is widely used to perform non-destructive characterization of time varying physical processes in various materials. The conventional approach to improving temporal resolution in 4D-XCT involves the development of expensive and complex instrumentation that acquire data faster with reduced noise. It is customary to acquire data with many tomographic views at a high signal to noise ratio. Instead, temporal resolution can be improved using regularized iterative algorithms that are less sensitive to noise and limited views. These algorithms benefit from optimization of other parameters such as the view sampling strategy while improving temporal resolution by reducing the total number of views or the detector exposure time. This paper presents the design principles of 4D-XCT experiments when using regularized iterative algorithms derived using the framework of model-based reconstruction. A strategy for performing 4D-XCT experiments is presented that allows for improving the temporal resolution by progressively reducing the number of views or the detector exposure time. Theoretical analysis of the effect of the data acquisition parameters on the detector signal to noise ratio, spatial reconstruction resolution, and temporal reconstruction resolution is also presented in this paper.

Nonlinear spatio-temporal filtering of dynamic PET data using a four-dimensional Gaussian filter and expectation-maximization deconvolution

NASA Astrophysics Data System (ADS)

Floberg, J. M.; Holden, J. E.

2013-02-01

We introduce a method for denoising dynamic PET data, spatio-temporal expectation-maximization (STEM) filtering, that combines four-dimensional Gaussian filtering with EM deconvolution. The initial Gaussian filter suppresses noise at a broad range of spatial and temporal frequencies and EM deconvolution quickly restores the frequencies most important to the signal. We aim to demonstrate that STEM filtering can improve variance in both individual time frames and in parametric images without introducing significant bias. We evaluate STEM filtering with a dynamic phantom study, and with simulated and human dynamic PET studies of a tracer with reversible binding behaviour, [C-11]raclopride, and a tracer with irreversible binding behaviour, [F-18]FDOPA. STEM filtering is compared to a number of established three and four-dimensional denoising methods. STEM filtering provides substantial improvements in variance in both individual time frames and in parametric images generated with a number of kinetic analysis techniques while introducing little bias. STEM filtering does bias early frames, but this does not affect quantitative parameter estimates. STEM filtering is shown to be superior to the other simple denoising methods studied. STEM filtering is a simple and effective denoising method that could be valuable for a wide range of dynamic PET applications.

Emissions Estimation from Satellite Retrievals: a Review of Current Capability

NASA Technical Reports Server (NTRS)

Streets, David; Canty, Timothy; Carmichael, Gregory R.; deFoy, Benjamin; Dickerson, Russell R.; Duncan, Bryan N.; Edwards, David P.; Haynes, John A.; Henze, Daven K.; Houyoux, Marc R.;

Emissions estimation from satellite retrievals: A review of current capability

NASA Astrophysics Data System (ADS)

Streets, David G.; Canty, Timothy; Carmichael, Gregory R.; de Foy, Benjamin; Dickerson, Russell R.; Duncan, Bryan N.; Edwards, David P.; Haynes, John A.; Henze, Daven K.; Houyoux, Marc R.; Jacob, Daniel J.; Krotkov, Nickolay A.; Lamsal, Lok N.; Liu, Yang; Lu, Zifeng; Martin, Randall V.; Pfister, Gabriele G.; Pinder, Robert W.; Salawitch, Ross J.; Wecht, Kevin J.

2013-10-01

Since the mid-1990s a new generation of Earth-observing satellites has been able to detect tropospheric air pollution at increasingly high spatial and temporal resolution. Most primary emitted species can be measured by one or more of the instruments. This review article addresses the question of how well we can relate the satellite measurements to quantification of primary emissions and what advances are needed to improve the usability of the measurements by U.S. air quality managers. Built on a comprehensive literature review and comprising input by both satellite experts and emission inventory specialists, the review identifies several targets that seem promising: large point sources of NOx and SO2, species that are difficult to measure by other means (NH3 and CH4, for example), area sources that cannot easily be quantified by traditional bottom-up methods (such as unconventional oil and gas extraction, shipping, biomass burning, and biogenic sources), and the temporal variation of emissions (seasonal, diurnal, episodic). Techniques that enhance the usefulness of current retrievals (data assimilation, oversampling, multi-species retrievals, improved vertical profiles, etc.) are discussed. Finally, we point out the value of having new geostationary satellites like GEO-CAPE and TEMPO over North America that could provide measurements at high spatial (few km) and temporal (hourly) resolution.

A geostatistical state-space model of animal densities for stream networks.

PubMed

Hocking, Daniel J; Thorson, James T; O'Neil, Kyle; Letcher, Benjamin H

2018-06-21

Population dynamics are often correlated in space and time due to correlations in environmental drivers as well as synchrony induced by individual dispersal. Many statistical analyses of populations ignore potential autocorrelations and assume that survey methods (distance and time between samples) eliminate these correlations, allowing samples to be treated independently. If these assumptions are incorrect, results and therefore inference may be biased and uncertainty under-estimated. We developed a novel statistical method to account for spatio-temporal correlations within dendritic stream networks, while accounting for imperfect detection in the surveys. Through simulations, we found this model decreased predictive error relative to standard statistical methods when data were spatially correlated based on stream distance and performed similarly when data were not correlated. We found that increasing the number of years surveyed substantially improved the model accuracy when estimating spatial and temporal correlation coefficients, especially from 10 to 15 years. Increasing the number of survey sites within the network improved the performance of the non-spatial model but only marginally improved the density estimates in the spatio-temporal model. We applied this model to Brook Trout data from the West Susquehanna Watershed in Pennsylvania collected over 34 years from 1981 - 2014. We found the model including temporal and spatio-temporal autocorrelation best described young-of-the-year (YOY) and adult density patterns. YOY densities were positively related to forest cover and negatively related to spring temperatures with low temporal autocorrelation and moderately-high spatio-temporal correlation. Adult densities were less strongly affected by climatic conditions and less temporally variable than YOY but with similar spatio-temporal correlation and higher temporal autocorrelation. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Spatio-temporal distribution of soil-transmitted helminth infections in Brazil.

PubMed

Chammartin, Frédérique; Guimarães, Luiz H; Scholte, Ronaldo Gc; Bavia, Mara E; Utzinger, Jürg; Vounatsou, Penelope

2014-09-18

In Brazil, preventive chemotherapy targeting soil-transmitted helminthiasis is being scaled-up. Hence, spatially explicit estimates of infection risks providing information about the current situation are needed to guide interventions. Available high-resolution national model-based estimates either rely on analyses of data restricted to a given period of time, or on historical data collected over a longer period. While efforts have been made to take into account the spatial structure of the data in the modelling approach, little emphasis has been placed on the temporal dimension. We extracted georeferenced survey data on the prevalence of infection with soil-transmitted helminths (i.e. Ascaris lumbricoides, hookworm and Trichuris trichiura) in Brazil from the Global Neglected Tropical Diseases (GNTD) database. Selection of the most important predictors of infection risk was carried out using a Bayesian geostatistical approach and temporal models that address non-linearity and correlation of the explanatory variables. The spatial process was estimated through a predictive process approximation. Spatio-temporal models were built on the selected predictors with integrated nested Laplace approximation using stochastic partial differential equations. Our models revealed that, over the past 20 years, the risk of soil-transmitted helminth infection has decreased in Brazil, mainly because of the reduction of A. lumbricoides and hookworm infections. From 2010 onwards, we estimate that the infection prevalences with A. lumbricoides, hookworm and T. trichiura are 3.6%, 1.7% and 1.4%, respectively. We also provide a map highlighting municipalities in need of preventive chemotherapy, based on a predicted soil-transmitted helminth infection risk in excess of 20%. The need for treatments in the school-aged population at the municipality level was estimated at 1.8 million doses of anthelminthic tablets per year. The analysis of the spatio-temporal aspect of the risk of infection with soil-transmitted helminths contributes to a better understanding of the evolution of risk over time. Risk estimates provide the soil-transmitted helminthiasis control programme in Brazil with useful benchmark information for prioritising and improving spatial and temporal targeting of interventions.

A spatiotemporal data model for incorporating time in geographic information systems (GEN-STGIS)

NASA Astrophysics Data System (ADS)

Narciso, Flor Eugenia

Temporal Geographic Information Systems (TGIS) is a new technology, which is being developed to work with Geographic Information Systems (GIS) that deal with geographic phenomena that change over time. The capabilities of TGIS depend on the underlying data model. However, a literature review of current spatiotemporal GIS data models has shown that they are not adequate for managing time when representing temporal data. In addition, the majority of these data models have been designed to support the requirements of specific-purpose applications. In an effort to resolve this problem, the related literature has been explored. A comparative investigation of the current spatiotemporal GIS data models has been made to identify their characteristics, advantages and disadvantages, similarities and differences, and to determine why they do not work adequately. A new object-oriented General-purpose Spatiotemporal GIS (GEN-STGIS) data model is proposed here. This model provides better representation, storage and management of data related to geographic phenomena that change over time and overcomes some of the problems detected in the reviewed data models. The proposed data model has four key benefits. First, it provides the capabilities of a standard vector-based GIS embedded in the 2-D Euclidean space. Second, it includes the two temporal dimensions, valid time and transaction time, supported by temporal databases. Third, it inherits, from the object oriented approach, the flexibility, modularity and ability to handle the complexities introduced by spatial and temporal dimensions. Fourth, it improves the geographic query capabilities of current TGIS with the introduction of the concept of bounding box while providing temporal and spatiotemporal query capabilities. The data model is then evaluated in order to assess its strengths and weaknesses as a spatiotemporal GIS data model, and to determine how well the model satisfies the requirements imposed by TGIS applications. The practicality of the data model is demonstrated by the creation of a TGIS example and the partial implementation of the model using the POET Java software for developing the object-oriented database. the object-oriented database.

Integration of sUAS Imagery and Atmospheric Data Collection for Improved Agricultural Greenhouse Gas Emissions Monitoring

NASA Astrophysics Data System (ADS)

Barbieri, L.; Adair, C.; Galford, G. L.; Wyngaard, J.

2017-12-01

We present on a full season of low-cost sUAS agricultural monitoring for improved GHG emissions accounting and mitigation. Agriculture contributes 10-12% of global anthropogenic GHG emissions, and roughly half are from agricultural soils. A variety of land management strategies can be implemented to reduce GHG emissions, but agricultural lands are complex and heterogenous. Nutrient cycling processes that ultimately regulate GHG emission rates are affected by environmental and management dynamics that vary spatially and temporally (e.g. soil properties, manure spreading). Thus, GHG mitigation potential is also variable, and determining best practices for mitigation is challenging, especially considering potential conflicting pressure to manage agricultural lands for other objectives (e.g. decrease agricultural runoff). Monitoring complexity from agricultural lands is critical for regional GHG accounting and decision making, but current methods (e.g., static chambers) are time intensive, expensive, and use in-situ equipment. These methods lack the spatio-temporal flexibility necessary to reduce the high uncertainty in regional emissions estimates, while traditional remote sensing methods often do not provide adequate spatio-temporal resolution for robust field-level monitoring. Small Unmanned Aerial Systems (sUAS) provide the range and the rapid response data collection needed to monitor key variables on the landscape (imagery) and from the atmosphere (CO2 concentrations), and can provide ways to bridge between in-situ and remote sensing data. Initial results show good agreement between sUAS CO2 sensors with more traditional equipment, and at a fraction of the cost. We present results from test flights over managed agricultural landscapes in Vermont, showcasing capabilities from both sUAS imagery and atmospheric data collected from on-board sensors (CO2, PTH). We then compare results from two different in-flight data collection methods: Vertical Profile and Horizontal Surveys. We conclude with results from the integration of these sUAS data with concurrently collected in-field measurements from static chambers and Landsat imagery, demonstrating enhanced understanding of agricultural landscapes and improved GHG emissions monitoring with the addition of sUAS collected data.

Temporal structure of motor variability is dynamically regulated and predicts motor learning ability.

PubMed

Wu, Howard G; Miyamoto, Yohsuke R; Gonzalez Castro, Luis Nicolas; Ölveczky, Bence P; Smith, Maurice A

2014-02-01

Individual differences in motor learning ability are widely acknowledged, yet little is known about the factors that underlie them. Here we explore whether movement-to-movement variability in motor output, a ubiquitous if often unwanted characteristic of motor performance, predicts motor learning ability. Surprisingly, we found that higher levels of task-relevant motor variability predicted faster learning both across individuals and across tasks in two different paradigms, one relying on reward-based learning to shape specific arm movement trajectories and the other relying on error-based learning to adapt movements in novel physical environments. We proceeded to show that training can reshape the temporal structure of motor variability, aligning it with the trained task to improve learning. These results provide experimental support for the importance of action exploration, a key idea from reinforcement learning theory, showing that motor variability facilitates motor learning in humans and that our nervous systems actively regulate it to improve learning.

Behavioral demand modulates object category representation in the inferior temporal cortex

PubMed Central

Emadi, Nazli

2014-01-01

Visual object categorization is a critical task in our daily life. Many studies have explored category representation in the inferior temporal (IT) cortex at the level of single neurons and population. However, it is not clear how behavioral demands modulate this category representation. Here, we recorded from the IT single neurons in monkeys performing two different tasks with identical visual stimuli: passive fixation and body/object categorization. We found that category selectivity of the IT neurons was improved in the categorization compared with the passive task where reward was not contingent on image category. The category improvement was the result of larger rate enhancement for the preferred category and smaller response variability for both preferred and nonpreferred categories. These specific modulations in the responses of IT category neurons enhanced signal-to-noise ratio of the neural responses to discriminate better between the preferred and nonpreferred categories. Our results provide new insight into the adaptable category representation in the IT cortex, which depends on behavioral demands. PMID:25080572

Temporal structure of motor variability is dynamically regulated and predicts motor learning ability

PubMed Central

Wu, Howard G; Miyamoto, Yohsuke R; Castro, Luis Nicolas Gonzalez; Ölveczky, Bence P; Smith, Maurice A

2015-01-01

Individual differences in motor learning ability are widely acknowledged, yet little is known about the factors that underlie them. Here we explore whether movement-to-movement variability in motor output, a ubiquitous if often unwanted characteristic of motor performance, predicts motor learning ability. Surprisingly, we found that higher levels of task-relevant motor variability predicted faster learning both across individuals and across tasks in two different paradigms, one relying on reward-based learning to shape specific arm movement trajectories and the other relying on error-based learning to adapt movements in novel physical environments. We proceeded to show that training can reshape the temporal structure of motor variability, aligning it with the trained task to improve learning. These results provide experimental support for the importance of action exploration, a key idea from reinforcement learning theory, showing that motor variability facilitates motor learning in humans and that our nervous systems actively regulate it to improve learning. PMID:24413700

Speeding up dynamic spiral chemical shift imaging with incoherent sampling and low-rank matrix completion.

PubMed

DeVience, Stephen J; Mayer, Dirk

2017-03-01

To improve the temporal and spatial resolution of dynamic 13 C spiral chemical shift imaging via incoherent sampling and low-rank matrix completion (LRMC). Spiral CSI data were both simulated and acquired in rats, and undersampling was implemented retrospectively and prospectively by pseudorandomly omitting a fraction of the spiral interleaves. Undersampled data were reconstructed with both LRMC and a conventional inverse nonuniform fast Fourier transform (iNUFFT) and compared with fully sampled data. Two-fold undersampling with LRMC reconstruction enabled a two-fold improvement in temporal or spatial resolution without significant artifacts or spatiotemporal distortion. Conversely, undersampling with iNUFFT reconstruction created strong artifacts that obscured the image. LRMC performed better at time points with strong metabolite signal. Incoherent undersampling and LRMC provides a way to increase the spatiotemporal resolution of spiral CSI without degrading data integrity. Magn Reson Med 77:951-960, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

A matter of time: improvement of visual temporal processing during training-induced restoration of light detection performance

PubMed Central

Poggel, Dorothe A.; Treutwein, Bernhard; Sabel, Bernhard A.; Strasburger, Hans

2015-01-01

The issue of how basic sensory and temporal processing are related is still unresolved. We studied temporal processing, as assessed by simple visual reaction times (RT) and double-pulse resolution (DPR), in patients with partial vision loss after visual pathway lesions and investigated whether vision restoration training (VRT), a training program designed to improve light detection performance, would also affect temporal processing. Perimetric and campimetric visual field tests as well as maps of DPR thresholds and RT were acquired before and after a 3 months training period with VRT. Patient performance was compared to that of age-matched healthy subjects. Intact visual field size increased during training. Averaged across the entire visual field, DPR remained constant while RT improved slightly. However, in transition zones between the blind and intact areas (areas of residual vision) where patients had shown between 20 and 80% of stimulus detection probability in pre-training visual field tests, both DPR and RT improved markedly. The magnitude of improvement depended on the defect depth (or degree of intactness) of the respective region at baseline. Inter-individual training outcome variability was very high, with some patients showing little change and others showing performance approaching that of healthy controls. Training-induced improvement of light detection in patients with visual field loss thus generalized to dynamic visual functions. The findings suggest that similar neural mechanisms may underlie the impairment and subsequent training-induced functional recovery of both light detection and temporal processing. PMID:25717307

Blind identification of full-field vibration modes of output-only structures from uniformly-sampled, possibly temporally-aliased (sub-Nyquist), video measurements

NASA Astrophysics Data System (ADS)

Yang, Yongchao; Dorn, Charles; Mancini, Tyler; Talken, Zachary; Nagarajaiah, Satish; Kenyon, Garrett; Farrar, Charles; Mascareñas, David

2017-03-01

Enhancing the spatial and temporal resolution of vibration measurements and modal analysis could significantly benefit dynamic modelling, analysis, and health monitoring of structures. For example, spatially high-density mode shapes are critical for accurate vibration-based damage localization. In experimental or operational modal analysis, higher (frequency) modes, which may be outside the frequency range of the measurement, contain local structural features that can improve damage localization as well as the construction and updating of the modal-based dynamic model of the structure. In general, the resolution of vibration measurements can be increased by enhanced hardware. Traditional vibration measurement sensors such as accelerometers have high-frequency sampling capacity; however, they are discrete point-wise sensors only providing sparse, low spatial sensing resolution measurements, while dense deployment to achieve high spatial resolution is expensive and results in the mass-loading effect and modification of structure's surface. Non-contact measurement methods such as scanning laser vibrometers provide high spatial and temporal resolution sensing capacity; however, they make measurements sequentially that requires considerable acquisition time. As an alternative non-contact method, digital video cameras are relatively low-cost, agile, and provide high spatial resolution, simultaneous, measurements. Combined with vision based algorithms (e.g., image correlation or template matching, optical flow, etc.), video camera based measurements have been successfully used for experimental and operational vibration measurement and subsequent modal analysis. However, the sampling frequency of most affordable digital cameras is limited to 30-60 Hz, while high-speed cameras for higher frequency vibration measurements are extremely costly. This work develops a computational algorithm capable of performing vibration measurement at a uniform sampling frequency lower than what is required by the Shannon-Nyquist sampling theorem for output-only modal analysis. In particular, the spatio-temporal uncoupling property of the modal expansion of structural vibration responses enables a direct modal decoupling of the temporally-aliased vibration measurements by existing output-only modal analysis methods, yielding (full-field) mode shapes estimation directly. Then the signal aliasing properties in modal analysis is exploited to estimate the modal frequencies and damping ratios. The proposed method is validated by laboratory experiments where output-only modal identification is conducted on temporally-aliased acceleration responses and particularly the temporally-aliased video measurements of bench-scale structures, including a three-story building structure and a cantilever beam.

Utilizing the Landsat spectral-temporal domain for improved mapping and monitoring of ecosystem state and dynamics

NASA Astrophysics Data System (ADS)

Pasquarella, Valerie J.

Just as the carbon dioxide observations that form the Keeling curve revolutionized the study of the global carbon cycle, free and open access to all available Landsat imagery is fundamentally changing how the Landsat record is being used to study ecosystems and ecological dynamics. This dissertation advances the use of Landsat time series for visualization, classification, and detection of changes in terrestrial ecological processes. More specifically, it includes new examples of how complex ecological patterns manifest in time series of Landsat observations, as well as novel approaches for detecting and quantifying these patterns. Exploration of the complexity of spectral-temporal patterns in the Landsat record reveals both seasonal variability and longer-term trajectories difficult to characterize using conventional bi-temporal or even annual observations. These examples provide empirical evidence of hypothetical ecosystem response functions proposed by Kennedy et al. (2014). Quantifying observed seasonal and phenological differences in the spectral reflectance of Massachusetts' forest communities by combining existing harmonic curve fitting and phenology detection algorithms produces stable feature sets that consistently out-performed more traditional approaches for detailed forest type classification. This study addresses the current lack of species-level forest data at Landsat resolutions, demonstrating the advantages of spectral-temporal features as classification inputs. Development of a targeted change detection method using transformations of time series data improves spatial and temporal information on the occurrence of flood events in landscapes actively modified by recovering North American beaver (Castor canadensis) populations. These results indicate the utility of the Landsat record for the study of species-habitat relationships, even in complex wetland environments. Overall, this dissertation confirms the value of the Landsat archive as a continuous record of terrestrial ecosystem state and dynamics. Given the global coverage of remote sensing datasets, the time series visualization and analysis approaches presented here can be extended to other areas. These approaches will also be improved by more frequent collection of moderate resolution imagery, as planned by the Landsat and Sentinel-2 programs. In the modern era of global environmental change, use of the Landsat spectral-temporal domain presents new and exciting opportunities for the long-term large-scale study of ecosystem extent, composition, condition, and change.

The Eyes Know Time: A Novel Paradigm to Reveal the Development of Temporal Memory

ERIC Educational Resources Information Center

Pathman, Thanujeni; Ghetti, Simona

2014-01-01

Temporal memory in 7-year-olds, 10-year-olds, and young adults (N = 78) was examined introducing a novel eye-movement paradigm. Participants learned object sequences and were tested under three conditions: temporal order, temporal context, and recognition. Age-related improvements in accuracy were found across conditions; accuracy in the temporal…

Crop classification using multidate/multifrequency radar data. [Colby, Kansas

NASA Technical Reports Server (NTRS)

Ulaby, F. T. (Principal Investigator); Shanmugam, K. S.; Narayanan, V.; Dobson, C.

1981-01-01

Both C- and L-band radar data acquired over a test site near Colby, Kansas during the summer of 1978 were used to identify three types of vegetation cover and bare soil. The effects of frequency, polarization, and the look angle on the overall accuracy of recognizing the four types of ground cover were analyzed. In addition, multidate data were used to study the improvement in recognition accuracy possible with the addition of temporal information. The soil moisture conditions had changed considerably during the temporal sequence of the data; hence, the effects of soil moisture on the ability to discriminate between cover types were also analyzed. The results provide useful information needed for selecting the parameters of a radar system for monitoring crops.

Robust phase-shifting interferometry resistant to multiple disturbances

NASA Astrophysics Data System (ADS)

Liu, Qian; Yue, Xiaobin; Li, Lulu; Zhang, Hui; He, Jianguo

2018-04-01

Phase-shifting interferometry (PSI) is sensitive to many disturbances, including the environmental vibration, laser instability, phase-shifting error and camera nonlinearity. A robust PSI (RPSI) based on the temporal spectrum analysis is proposed to suppress the effects of these common disturbances. RPSI retrieves wavefront phase from the temporal Fourier spectrum peak, which is identified by detecting the modulus of spectrum, and a referencing method is presented to improve the phase extracting accuracy. Simulations demonstrate the feasibility and effectiveness of RPSI. Experimental results indicate that RPSI is resistant to common disturbances in implementing PSI and achieves accuracy better than 0.03 rad in the disturbed environment. RPSI relaxes requirements on the hardware, environment and operator, and provides an easy-to-use design of an interferometer.

Future climate risk from compound events

NASA Astrophysics Data System (ADS)

Zscheischler, Jakob; Westra, Seth; van den Hurk, Bart J. J. M.; Seneviratne, Sonia I.; Ward, Philip J.; Pitman, Andy; AghaKouchak, Amir; Bresch, David N.; Leonard, Michael; Wahl, Thomas; Zhang, Xuebin

2018-06-01

Floods, wildfires, heatwaves and droughts often result from a combination of interacting physical processes across multiple spatial and temporal scales. The combination of processes (climate drivers and hazards) leading to a significant impact is referred to as a `compound event'. Traditional risk assessment methods typically only consider one driver and/or hazard at a time, potentially leading to underestimation of risk, as the processes that cause extreme events often interact and are spatially and/or temporally dependent. Here we show how a better understanding of compound events may improve projections of potential high-impact events, and can provide a bridge between climate scientists, engineers, social scientists, impact modellers and decision-makers, who need to work closely together to understand these complex events.

The inferior, anterior temporal lobes and semantic memory clarified: novel evidence from distortion-corrected fMRI.

PubMed

Visser, M; Embleton, K V; Jefferies, E; Parker, G J; Ralph, M A Lambon

2010-05-01

The neural basis of semantic memory generates considerable debate. Semantic dementia results from bilateral anterior temporal lobe (ATL) atrophy and gives rise to a highly specific impairment of semantic memory, suggesting that this region is a critical neural substrate for semantic processing. Recent rTMS experiments with neurologically-intact participants also indicate that the ATL are a necessary substrate for semantic memory. Exactly which regions within the ATL are important for semantic memory are difficult to detect from these methods (because the damage in SD covers a large part of the ATL). Functional neuroimaging might provide important clues about which specific areas exhibit activation that correlates with normal semantic performance. Neuroimaging studies, however, have not consistently found anterior temporal lobe activation in semantic tasks. A recent meta-analysis indicates that this inconsistency may be due to a collection of technical limitations associated with previous studies, including a reduced field-of-view and magnetic susceptibility artefacts associated with standard gradient echo fMRI. We conducted an fMRI study of semantic memory using a combination of techniques which improve sensitivity to ATL activations whilst preserving whole-brain coverage. As expected from SD patients and ATL rTMS experiments, this method revealed bilateral temporal activation extending from the inferior temporal lobe along the fusiform gyrus to the anterior temporal regions, bilaterally. We suggest that the inferior, anterior temporal lobe region makes a crucial contribution to semantic cognition and utilising this version of fMRI will enable further research on the semantic role of the ATL. 2010 Elsevier Ltd. All rights reserved.

Postural Motor Learning Deficits in People With MS in Spatial but Not Temporal Control of Center of Mass.

PubMed

Gera, Geetanjali; Fling, Brett W; Van Ooteghem, Karen; Cameron, Michelle; Frank, James S; Horak, Fay B

2016-09-01

Multiple sclerosis (MS) is associated with balance deficits resulting in falls and impaired mobility. Although rehabilitation has been recommended to address these balance deficits, the extent to which people with MS can learn and retain improvements in postural responses is unknown. To determine the ability of people with MS to improve postural control with surface perturbation training. A total of 24 patients with mild MS and 14 age-matched controls underwent postural control training with a set pattern of continuous, forward-backward, sinusoidal, and surface translations provided by a force platform. Postural control was then tested the following day for retention. The primary outcome measures were the relative phase and center-of-mass (CoM) gain between the body CoM and the platform motion. People with MS demonstrated similar improvements in acquiring and retaining changes in the temporal control of the CoM despite significant deficits in postural motor performance at the baseline. Both MS and control groups learned to anticipate the pattern of forward-backward perturbations, so body CoM shifted from a phase-lag (age-matched controls [CS] = -7.1 ± 1.3; MS = -12.9 ± 1.0) toward a phase-lead (CS = -0.7 ± 1.8; MS = -6.1 ± 1.4) relationship with the surface oscillations. However, MS patients were not able to retain the changes in the spatial control of the CoM acquired during training. People with MS have the capacity to improve use of a feed-forward postural strategy with practice and retain the learned behavior for temporal not spatial control of CoM, despite their significant postural response impairments. © The Author(s) 2015.

Mapping Crop Patterns in Central US Agricultural Systems from 2000 to 2014 Based on Landsat Data: To What Degree Does Fusing MODIS Data Improve Classification Accuracies?

NASA Astrophysics Data System (ADS)

Zhu, L.; Radeloff, V.; Ives, A. R.; Barton, B.

2015-12-01

Deriving crop pattern with high accuracy is of great importance for characterizing landscape diversity, which affects the resilience of food webs in agricultural systems in the face of climatic and land cover changes. Landsat sensors were originally designed to monitor agricultural areas, and both radiometric and spatial resolution are optimized for monitoring large agricultural fields. Unfortunately, few clear Landsat images per year are available, which has limited the use of Landsat for making crop classification, and this situation is worse in cloudy areas of the Earth. Meanwhile, the MODerate Resolution Imaging Spectroradiometer (MODIS) data has better temporal resolution but cannot capture fine spatial heterogeneity of agricultural systems. Our question was to what extent fusing imagery from both sensors could improve crop classifications. We utilized the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) algorithm to simulate Landsat-like images at MODIS temporal resolution. Based on Random Forests (RF) classifier, we tested whether and by what degree crop maps from 2000 to 2014 of the Arlington Agricultural Research Station (Wisconsin, USA) were improved by integrating available clear Landsat images each year with synthetic images. We predicted that the degree to which classification accuracy can be improved by incorporating synthetic imagery depends on the number and acquisition time of clear Landsat images. Moreover, multi-season data are essential for mapping crop types by capturing their phenological dynamics, and STARFM-simulated images can be used to compensate for missing Landsat observations. Our study is helpful for eliminating the limits of the use of Landsat data in mapping crop patterns, and can provide a benchmark of accuracy when choosing STARFM-simulated images to make crop classification at broader scales.

Content-based management service for medical videos.

PubMed

Mendi, Engin; Bayrak, Coskun; Cecen, Songul; Ermisoglu, Emre

2013-01-01

Development of health information technology has had a dramatic impact to improve the efficiency and quality of medical care. Developing interoperable health information systems for healthcare providers has the potential to improve the quality and equitability of patient-centered healthcare. In this article, we describe an automated content-based medical video analysis and management service that provides convenience and ease in accessing the relevant medical video content without sequential scanning. The system facilitates effective temporal video segmentation and content-based visual information retrieval that enable a more reliable understanding of medical video content. The system is implemented as a Web- and mobile-based service and has the potential to offer a knowledge-sharing platform for the purpose of efficient medical video content access.

Application of glas laser altimetry to detect elevation changes in East Antarctica

NASA Astrophysics Data System (ADS)

Scaioni, M.; Tong, X.; Li, R.

2013-10-01

In this paper the use of ICESat/GLAS laser altimeter for estimating multi-temporal elevation changes on polar ice sheets is afforded. Due to non-overlapping laser spots during repeat passes, interpolation methods are required to make comparisons. After reviewing the main methods described in the literature (crossover point analysis, cross-track DEM projection, space-temporal regressions), the last one has been chosen for its capability of providing more elevation change rate measurements. The standard implementation of the space-temporal linear regression technique has been revisited and improved to better cope with outliers and to check the estimability of model's parameters. GLAS data over the PANDA route in East Antarctica have been used for testing. Obtained results have been quite meaningful from a physical point of view, confirming the trend reported by the literature of a constant snow accumulation in the area during the two past decades, unlike the most part of the continent that has been losing mass.

Visualization of spatial-temporal data based on 3D virtual scene

NASA Astrophysics Data System (ADS)

Wang, Xianghong; Liu, Jiping; Wang, Yong; Bi, Junfang

2009-10-01

The main purpose of this paper is to realize the expression of the three-dimensional dynamic visualization of spatialtemporal data based on three-dimensional virtual scene, using three-dimensional visualization technology, and combining with GIS so that the people's abilities of cognizing time and space are enhanced and improved by designing dynamic symbol and interactive expression. Using particle systems, three-dimensional simulation, virtual reality and other visual means, we can simulate the situations produced by changing the spatial location and property information of geographical entities over time, then explore and analyze its movement and transformation rules by changing the interactive manner, and also replay history and forecast of future. In this paper, the main research object is the vehicle track and the typhoon path and spatial-temporal data, through three-dimensional dynamic simulation of its track, and realize its timely monitoring its trends and historical track replaying; according to visualization techniques of spatialtemporal data in Three-dimensional virtual scene, providing us with excellent spatial-temporal information cognitive instrument not only can add clarity to show spatial-temporal information of the changes and developments in the situation, but also be used for future development and changes in the prediction and deduction.

On temporal stochastic modeling of precipitation, nesting models across scales

NASA Astrophysics Data System (ADS)

Paschalis, Athanasios; Molnar, Peter; Fatichi, Simone; Burlando, Paolo

2014-01-01

We analyze the performance of composite stochastic models of temporal precipitation which can satisfactorily reproduce precipitation properties across a wide range of temporal scales. The rationale is that a combination of stochastic precipitation models which are most appropriate for specific limited temporal scales leads to better overall performance across a wider range of scales than single models alone. We investigate different model combinations. For the coarse (daily) scale these are models based on Alternating renewal processes, Markov chains, and Poisson cluster models, which are then combined with a microcanonical Multiplicative Random Cascade model to disaggregate precipitation to finer (minute) scales. The composite models were tested on data at four sites in different climates. The results show that model combinations improve the performance in key statistics such as probability distributions of precipitation depth, autocorrelation structure, intermittency, reproduction of extremes, compared to single models. At the same time they remain reasonably parsimonious. No model combination was found to outperform the others at all sites and for all statistics, however we provide insight on the capabilities of specific model combinations. The results for the four different climates are similar, which suggests a degree of generality and wider applicability of the approach.

Evaluation of a haptics-based virtual reality temporal bone simulator for anatomy and surgery training.

PubMed

Fang, Te-Yung; Wang, Pa-Chun; Liu, Chih-Hsien; Su, Mu-Chun; Yeh, Shih-Ching

2014-02-01

Virtual reality simulation training may improve knowledge of anatomy and surgical skills. We evaluated a 3-dimensional, haptic, virtual reality temporal bone simulator for dissection training. The subjects were 7 otolaryngology residents (3 training sessions each) and 7 medical students (1 training session each). The virtual reality temporal bone simulation station included a computer with software that was linked to a force-feedback hand stylus, and the system recorded performance and collisions with vital anatomic structures. Subjects performed virtual reality dissections and completed questionnaires after the training sessions. Residents and students had favorable responses to most questions of the technology acceptance model (TAM) questionnaire. The average TAM scores were above neutral for residents and medical students in all domains, and the average TAM score for residents was significantly higher for the usefulness domain and lower for the playful domain than students. The average satisfaction questionnaire for residents showed that residents had greater overall satisfaction with cadaver temporal bone dissection training than training with the virtual reality simulator or plastic temporal bone. For medical students, the average comprehension score was significantly increased from before to after training for all anatomic structures. Medical students had significantly more collisions with the dura than residents. The residents had similar mean performance scores after the first and third training sessions for all dissection procedures. The virtual reality temporal bone simulator provided satisfactory training for otolaryngology residents and medical students. Copyright © 2013. Published by Elsevier Ireland Ltd.

Observations and Modelling of Winds and Waves during the Surface Wave Dynamics Experiment. Report 1. Intensive Observation Period IOP-1, 20-31 October 1990

DTIC Science & Technology

1993-04-01

wave buoy provided by SEATEX, Norway (Figure 3). The modified Mills-cross array was designed to provide spatial estimates of the variation in wave, wind... designed for SWADE to examine the wave physics at different spatial and temporal scales, and the usefulness of a nested system. Each grid is supposed to...field specification. SWADE Model This high-resolution grid was designed to simulate the small scale wave physics and to improve and verify the source

Temporal Sensitivity Measured Shortly After Cochlear Implantation Predicts 6-Month Speech Recognition Outcome.

PubMed

Erb, Julia; Ludwig, Alexandra Annemarie; Kunke, Dunja; Fuchs, Michael; Obleser, Jonas

2018-04-24

Psychoacoustic tests assessed shortly after cochlear implantation are useful predictors of the rehabilitative speech outcome. While largely independent, both spectral and temporal resolution tests are important to provide an accurate prediction of speech recognition. However, rapid tests of temporal sensitivity are currently lacking. Here, we propose a simple amplitude modulation rate discrimination (AMRD) paradigm that is validated by predicting future speech recognition in adult cochlear implant (CI) patients. In 34 newly implanted patients, we used an adaptive AMRD paradigm, where broadband noise was modulated at the speech-relevant rate of ~4 Hz. In a longitudinal study, speech recognition in quiet was assessed using the closed-set Freiburger number test shortly after cochlear implantation (t0) as well as the open-set Freiburger monosyllabic word test 6 months later (t6). Both AMRD thresholds at t0 (r = -0.51) and speech recognition scores at t0 (r = 0.56) predicted speech recognition scores at t6. However, AMRD and speech recognition at t0 were uncorrelated, suggesting that those measures capture partially distinct perceptual abilities. A multiple regression model predicting 6-month speech recognition outcome with deafness duration and speech recognition at t0 improved from adjusted R = 0.30 to adjusted R = 0.44 when AMRD threshold was added as a predictor. These findings identify AMRD thresholds as a reliable, nonredundant predictor above and beyond established speech tests for CI outcome. This AMRD test could potentially be developed into a rapid clinical temporal-resolution test to be integrated into the postoperative test battery to improve the reliability of speech outcome prognosis.

Evaluation of feature selection algorithms for classification in temporal lobe epilepsy based on MR images

NASA Astrophysics Data System (ADS)

Lai, Chunren; Guo, Shengwen; Cheng, Lina; Wang, Wensheng; Wu, Kai

2017-02-01

It's very important to differentiate the temporal lobe epilepsy (TLE) patients from healthy people and localize the abnormal brain regions of the TLE patients. The cortical features and changes can reveal the unique anatomical patterns of brain regions from the structural MR images. In this study, structural MR images from 28 normal controls (NC), 18 left TLE (LTLE), and 21 right TLE (RTLE) were acquired, and four types of cortical feature, namely cortical thickness (CTh), cortical surface area (CSA), gray matter volume (GMV), and mean curvature (MCu), were explored for discriminative analysis. Three feature selection methods, the independent sample t-test filtering, the sparse-constrained dimensionality reduction model (SCDRM), and the support vector machine-recursive feature elimination (SVM-RFE), were investigated to extract dominant regions with significant differences among the compared groups for classification using the SVM classifier. The results showed that the SVM-REF achieved the highest performance (most classifications with more than 92% accuracy), followed by the SCDRM, and the t-test. Especially, the surface area and gray volume matter exhibited prominent discriminative ability, and the performance of the SVM was improved significantly when the four cortical features were combined. Additionally, the dominant regions with higher classification weights were mainly located in temporal and frontal lobe, including the inferior temporal, entorhinal cortex, fusiform, parahippocampal cortex, middle frontal and frontal pole. It was demonstrated that the cortical features provided effective information to determine the abnormal anatomical pattern and the proposed method has the potential to improve the clinical diagnosis of the TLE.

Reshaping the brain after stroke: The effect of prismatic adaptation in patients with right brain damage.

PubMed

Crottaz-Herbette, Sonia; Fornari, Eleonora; Notter, Michael P; Bindschaedler, Claire; Manzoni, Laura; Clarke, Stephanie

2017-09-01

Prismatic adaptation has been repeatedly reported to alleviate neglect symptoms; in normal subjects, it was shown to enhance the representation of the left visual space within the left inferior parietal cortex. Our study aimed to determine in humans whether similar compensatory mechanisms underlie the beneficial effect of prismatic adaptation in neglect. Fifteen patients with right hemispheric lesions and 11 age-matched controls underwent a prismatic adaptation session which was preceded and followed by fMRI using a visual detection task. In patients, the prismatic adaptation session improved the accuracy of target detection in the left and central space and enhanced the representation of this visual space within the left hemisphere in parts of the temporal convexity, inferior parietal lobule and prefrontal cortex. Across patients, the increase in neuronal activation within the temporal regions correlated with performance improvements in this visual space. In control subjects, prismatic adaptation enhanced the representation of the left visual space within the left inferior parietal lobule and decreased it within the left temporal cortex. Thus, a brief exposure to prismatic adaptation enhances, both in patients and in control subjects, the competence of the left hemisphere for the left space, but the regions extended beyond the inferior parietal lobule to the temporal convexity in patients. These results suggest that the left hemisphere provides compensatory mechanisms in neglect by assuming the representation of the whole space within the ventral attentional system. The rapidity of the change suggests that the underlying mechanism relies on uncovering pre-existing synaptic connections. Copyright © 2017 Elsevier Ltd. All rights reserved.

The acute and medium-term effects of treatment with electroconvulsive therapy on memory in patients with major depressive disorder.

PubMed

Maric, N P; Stojanovic, Z; Andric, S; Soldatovic, I; Dolic, M; Spiric, Z

2016-03-01

Current literature provides insufficient information on the degree of cognitive impairment during and after electroconvulsive therapy (ECT), mostly due to the fact that applied tests lacked sensitivity and flexibility. Our goal was to evaluate cognitive functioning in adult depressed patients treated with bi-temporal ECT, using tests sensitive for detection of possible acute and medium-term memory changes. Thirty adult patients with major depressive disorder, treated with a course of bi-temporal ECT, underwent clinical and cognitive measurements three times: at baseline, immediately after a course of ECT, and 1 month later. For cognition assessment, we used learning and visual, spatial and figural memory tests from the Cambridge Neuropsychological Test Automated Battery (CANTAB). Bi-temporal ECT has proven to be an effective treatment. The linear mixed model, used to analyze changes in depression severity and patients' cognitive performances over time and to assess dynamic correlations between aforementioned features, did not show any significant memory impairment as a potential acute or medium-term ECT effect. However, it yielded significant improvement on visual memory and learning at the follow-up, which positively correlated with the improvement of depression. Good progress is being made in the search for ECT-related acute and medium-term cognitive side-effects by using the tests sensitive to detect memory dysfunction with parallel forms of the tasks (to counter practice effects on repeat testing). Our results on learning and memory in relation to ECT during treatment of depression did not bring forth any prolonged and significant bi-temporal ECT-related memory deficit.

Impedance matched joined drill pipe for improved acoustic transmission

DOEpatents

Moss, William C.

2000-01-01

An impedance matched jointed drill pipe for improved acoustic transmission. A passive means and method that maximizes the amplitude and minimize the temporal dispersion of acoustic signals that are sent through a drill string, for use in a measurement while drilling telemetry system. The improvement in signal transmission is accomplished by replacing the standard joints in a drill string with joints constructed of a material that is impedance matched acoustically to the end of the drill pipe to which it is connected. Provides improvement in the measurement while drilling technique which can be utilized for well logging, directional drilling, and drilling dynamics, as well as gamma-ray spectroscopy while drilling post shot boreholes, such as utilized in drilling post shot boreholes.

An improved genetic algorithm for designing optimal temporal patterns of neural stimulation

NASA Astrophysics Data System (ADS)

Cassar, Isaac R.; Titus, Nathan D.; Grill, Warren M.

2017-12-01

Objective. Electrical neuromodulation therapies typically apply constant frequency stimulation, but non-regular temporal patterns of stimulation may be more effective and more efficient. However, the design space for temporal patterns is exceedingly large, and model-based optimization is required for pattern design. We designed and implemented a modified genetic algorithm (GA) intended for design optimal temporal patterns of electrical neuromodulation. Approach. We tested and modified standard GA methods for application to designing temporal patterns of neural stimulation. We evaluated each modification individually and all modifications collectively by comparing performance to the standard GA across three test functions and two biophysically-based models of neural stimulation. Main results. The proposed modifications of the GA significantly improved performance across the test functions and performed best when all were used collectively. The standard GA found patterns that outperformed fixed-frequency, clinically-standard patterns in biophysically-based models of neural stimulation, but the modified GA, in many fewer iterations, consistently converged to higher-scoring, non-regular patterns of stimulation. Significance. The proposed improvements to standard GA methodology reduced the number of iterations required for convergence and identified superior solutions.

Temporal Learning Analytics for Adaptive Assessment

ERIC Educational Resources Information Center

Papamitsiou, Zacharoula; Economides, Anastasios A.

2014-01-01

Accurate and early predictions of student performance could significantly affect interventions during teaching and assessment, which gradually could lead to improved learning outcomes. In our research, we seek to identify and formalize temporal parameters as predictors of performance ("temporal learning analytics" or TLA) and examine…

Accelerated long-term forgetting in temporal lobe epilepsy: evidence of improvement after left temporal pole lobectomy.

PubMed

Gallassi, Roberto; Sambati, Luisa; Poda, Roberto; Stanzani Maserati, Michelangelo; Oppi, Federico; Giulioni, Marco; Tinuper, Paolo

2011-12-01

Accelerated long term forgetting (ALF) is a characteristic cognitive aspect in patients affected by temporal lobe epilepsy that is probably due to an impairment of memory consolidation and retrieval caused by epileptic activity in hippocampal and parahippocampal regions. We describe a case of a patient with TLE who showed improvement in ALF and in remote memory impairment after an anterior left temporal pole lobectomy including the uncus and amygdala. Our findings confirm that impairment of hippocampal functioning leads to pathological ALF, whereas restoration of hippocampal functioning brings ALF to a level comparable to that of controls. Copyright © 2011 Elsevier Inc. All rights reserved.

Next Generation Gamma-Ray Cherenkov Detectors for the National Ignition Facility

DOE PAGES

Herrmann, Hans W.; Kim, Yong Ho; McEvoy, Aaron Matthew; ...

2016-10-19

The newest generation of Gas Cherenkov Detector (GCD-3) employed in Inertial Confinement Fusion experiments at the Omega Laser Facility has provided improved performance over previous generations. Comparison of reaction histories measured using two different deuterium-tritium fusion products, namely gamma rays using GCD and neutrons using Neutron Temporal Diagnostic (NTD), have provided added credibility to both techniques. GCD-3 is now being brought to the National Ignition Facility (NIF) to supplement the existing Gamma Reaction History (GRH-6m) located 6 m from target chamber center (TCC). Initially it will be located in a reentrant well located 3.9 m from TCC. Data from GCD-3more » will inform the design of a heavily-shielded “Super” GCD to be located as close as 20 cm from TCC. In conclusion, it will also provide a test-bed for faster optical detectors, potentially lowering the temporal resolution from the current ~100 ps state-of-the-art photomultiplier tubes (PMT) to ~10 ps Pulse Dilation PMT technology currently under development.« less

Temporally Adaptive Sampling: A Case Study in Rare Species Survey Design with Marbled Salamanders (Ambystoma opacum)

PubMed Central

Charney, Noah D.; Kubel, Jacob E.; Eiseman, Charles S.

2015-01-01

Improving detection rates for elusive species with clumped distributions is often accomplished through adaptive sampling designs. This approach can be extended to include species with temporally variable detection probabilities. By concentrating survey effort in years when the focal species are most abundant or visible, overall detection rates can be improved. This requires either long-term monitoring at a few locations where the species are known to occur or models capable of predicting population trends using climatic and demographic data. For marbled salamanders (Ambystoma opacum) in Massachusetts, we demonstrate that annual variation in detection probability of larvae is regionally correlated. In our data, the difference in survey success between years was far more important than the difference among the three survey methods we employed: diurnal surveys, nocturnal surveys, and dipnet surveys. Based on these data, we simulate future surveys to locate unknown populations under a temporally adaptive sampling framework. In the simulations, when pond dynamics are correlated over the focal region, the temporally adaptive design improved mean survey success by as much as 26% over a non-adaptive sampling design. Employing a temporally adaptive strategy costs very little, is simple, and has the potential to substantially improve the efficient use of scarce conservation funds. PMID:25799224

High frequency repetitive sensory stimulation improves temporal discrimination in healthy subjects.

PubMed

Erro, Roberto; Rocchi, Lorenzo; Antelmi, Elena; Palladino, Raffaele; Tinazzi, Michele; Rothwell, John; Bhatia, Kailash P

2016-01-01

High frequency electrical stimulation of an area of skin on a finger improves two-point spatial discrimination in the stimulated area, likely depending on plastic changes in the somatosensory cortex. However, it is unknown whether improvement also applies to temporal discrimination. Twelve young and ten elderly volunteers underwent the stimulation protocol onto the palmar skin of the right index finger. Somatosensory temporal discrimination threshold (STDT) was evaluated before and immediately after stimulation as well as 2.5h and 24h later. There was a significant reduction in somatosensory temporal threshold only on the stimulated finger. The effect was reversible, with STDT returning to the baseline values within 24h, and was smaller in the elderly than in the young participants. High frequency stimulation of the skin focally improves temporal discrimination in the area of stimulation. Given previous suggestions that the perceptual effects rely on plastic changes in the somatosensory cortex, our results are consistent with the idea that the timing of sensory stimuli is, at least partially, encoded in the primary somatosensory cortex. Such a protocol could potentially be used as a therapeutic intervention to ameliorate physiological decline in the elderly or in other disorders of sensorimotor integration. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Blind Compressed Sensing Enables 3-Dimensional Dynamic Free Breathing Magnetic Resonance Imaging of Lung Volumes and Diaphragm Motion.

PubMed

Bhave, Sampada; Lingala, Sajan Goud; Newell, John D; Nagle, Scott K; Jacob, Mathews

2016-06-01

The objective of this study was to increase the spatial and temporal resolution of dynamic 3-dimensional (3D) magnetic resonance imaging (MRI) of lung volumes and diaphragm motion. To achieve this goal, we evaluate the utility of the proposed blind compressed sensing (BCS) algorithm to recover data from highly undersampled measurements. We evaluated the performance of the BCS scheme to recover dynamic data sets from retrospectively and prospectively undersampled measurements. We also compared its performance against that of view-sharing, the nuclear norm minimization scheme, and the l1 Fourier sparsity regularization scheme. Quantitative experiments were performed on a healthy subject using a fully sampled 2D data set with uniform radial sampling, which was retrospectively undersampled with 16 radial spokes per frame to correspond to an undersampling factor of 8. The images obtained from the 4 reconstruction schemes were compared with the fully sampled data using mean square error and normalized high-frequency error metrics. The schemes were also compared using prospective 3D data acquired on a Siemens 3 T TIM TRIO MRI scanner on 8 healthy subjects during free breathing. Two expert cardiothoracic radiologists (R1 and R2) qualitatively evaluated the reconstructed 3D data sets using a 5-point scale (0-4) on the basis of spatial resolution, temporal resolution, and presence of aliasing artifacts. The BCS scheme gives better reconstructions (mean square error = 0.0232 and normalized high frequency = 0.133) than the other schemes in the 2D retrospective undersampling experiments, producing minimally distorted reconstructions up to an acceleration factor of 8 (16 radial spokes per frame). The prospective 3D experiments show that the BCS scheme provides visually improved reconstructions than the other schemes do. The BCS scheme provides improved qualitative scores over nuclear norm and l1 Fourier sparsity regularization schemes in the temporal blurring and spatial blurring categories. The qualitative scores for aliasing artifacts in the images reconstructed by nuclear norm scheme and BCS scheme are comparable.The comparisons of the tidal volume changes also show that the BCS scheme has less temporal blurring as compared with the nuclear norm minimization scheme and the l1 Fourier sparsity regularization scheme. The minute ventilation estimated by BCS for tidal breathing in supine position (4 L/min) and the measured supine inspiratory capacity (1.5 L) is in good correlation with the literature. The improved performance of BCS can be explained by its ability to efficiently adapt to the data, thus providing a richer representation of the signal. The feasibility of the BCS scheme was demonstrated for dynamic 3D free breathing MRI of lung volumes and diaphragm motion. A temporal resolution of ∼500 milliseconds, spatial resolution of 2.7 × 2.7 × 10 mm, with whole lung coverage (16 slices) was achieved using the BCS scheme.

Perceptual adaptation of voice gender discrimination with spectrally shifted vowels.

PubMed

Li, Tianhao; Fu, Qian-Jie

2011-08-01

To determine whether perceptual adaptation improves voice gender discrimination of spectrally shifted vowels and, if so, which acoustic cues contribute to the improvement. Voice gender discrimination was measured for 10 normal-hearing subjects, during 5 days of adaptation to spectrally shifted vowels, produced by processing the speech of 5 male and 5 female talkers with 16-channel sine-wave vocoders. The subjects were randomly divided into 2 groups; one subjected to 50-Hz, and the other to 200-Hz, temporal envelope cutoff frequencies. No preview or feedback was provided. There was significant adaptation in voice gender discrimination with the 200-Hz cutoff frequency, but significant improvement was observed only for 3 female talkers with F(0) > 180 Hz and 3 male talkers with F(0) < 170 Hz. There was no significant adaptation with the 50-Hz cutoff frequency. Temporal envelope cues are important for voice gender discrimination under spectral shift conditions with perceptual adaptation, but spectral shift may limit the exclusive use of spectral information and/or the use of formant structure on voice gender discrimination. The results have implications for cochlear implant users and for understanding voice gender discrimination.

Perceptual Adaptation of Voice Gender Discrimination with Spectrally Shifted Vowels

PubMed Central

Li, Tianhao; Fu, Qian-Jie

2013-01-01

Purpose To determine whether perceptual adaptation improves voice gender discrimination of spectrally shifted vowels and, if so, which acoustic cues contribute to the improvement. Method Voice gender discrimination was measured for 10 normal-hearing subjects, during 5 days of adaptation to spectrally shifted vowels, produced by processing the speech of 5 male and 5 female talkers with 16-channel sine-wave vocoders. The subjects were randomly divided into 2 groups; one subjected to 50-Hz, and the other to 200-Hz, temporal envelope cutoff frequencies. No preview or feedback was provided. Results: There was significant adaptation in voice gender discrimination with the 200-Hz cutoff frequency, but significant improvement was observed only for 3 female talkers with F0 > 180 Hz and 3 male talkers with F0 < 170 Hz. There was no significant adaptation with the 50-Hz cutoff frequency. Conclusions Temporal envelope cues are important for voice gender discrimination under spectral shift conditions with perceptual adaptation, but spectral shift may limit the exclusive use of spectral information and/or the use of formant structure on voice gender discrimination. The results have implications for cochlear implant users and for understanding voice gender discrimination. PMID:21173392

Effects of linking a soil-water-balance model with a groundwater-flow model

USGS Publications Warehouse

Stanton, Jennifer S.; Ryter, Derek W.; Peterson, Steven M.

2013-01-01

A previously published regional groundwater-flow model in north-central Nebraska was sequentially linked with the recently developed soil-water-balance (SWB) model to analyze effects to groundwater-flow model parameters and calibration results. The linked models provided a more detailed spatial and temporal distribution of simulated recharge based on hydrologic processes, improvement of simulated groundwater-level changes and base flows at specific sites in agricultural areas, and a physically based assessment of the relative magnitude of recharge for grassland, nonirrigated cropland, and irrigated cropland areas. Root-mean-squared (RMS) differences between the simulated and estimated or measured target values for the previously published model and linked models were relatively similar and did not improve for all types of calibration targets. However, without any adjustment to the SWB-generated recharge, the RMS difference between simulated and estimated base-flow target values for the groundwater-flow model was slightly smaller than for the previously published model, possibly indicating that the volume of recharge simulated by the SWB code was closer to actual hydrogeologic conditions than the previously published model provided. Groundwater-level and base-flow hydrographs showed that temporal patterns of simulated groundwater levels and base flows were more accurate for the linked models than for the previously published model at several sites, particularly in agricultural areas.

Postsurgical changes in self-reported mood and Composite IQ in a matched sample of patients with frontal and temporal lobe epilepsy.

PubMed

Suchy, Y; Chelune, G

2001-08-01

Changes in self-reported mood assessed by the Beck Depression Inventory (BDI) were examined in a sample of 60 left-hemisphere speech-dominant patients who underwent epilepsy surgery (15 right frontal, 15 left frontal, 15 right temporal, 15 left temporal). Temporal lobectomy patients were matched to frontal lobectomy patients by presurgical BDI scores, premorbid K-BIT composite IQ, sex, age, and years since seizure onset. Overall, self-reported mood improved following surgery, with men showing a greater improvement than women. There were no differences among the four groups in terms of pre-surgical and post-surgical reported mood. However, frontal patients showed more extreme changes in mood in either direction than temporal patients. Additionally, while temporal patients showed gains in Composite IQ, no such gains were observed in frontal patients. Changes in mood in frontal patients were not related to postsurgical seizure outcome or time since surgery, but were related to changes in Composite IQ.

Temporal Coding of Volumetric Imagery

NASA Astrophysics Data System (ADS)

Llull, Patrick Ryan

'Image volumes' refer to realizations of images in other dimensions such as time, spectrum, and focus. Recent advances in scientific, medical, and consumer applications demand improvements in image volume capture. Though image volume acquisition continues to advance, it maintains the same sampling mechanisms that have been used for decades; every voxel must be scanned and is presumed independent of its neighbors. Under these conditions, improving performance comes at the cost of increased system complexity, data rates, and power consumption. This dissertation explores systems and methods capable of efficiently improving sensitivity and performance for image volume cameras, and specifically proposes several sampling strategies that utilize temporal coding to improve imaging system performance and enhance our awareness for a variety of dynamic applications. Video cameras and camcorders sample the video volume (x,y,t) at fixed intervals to gain understanding of the volume's temporal evolution. Conventionally, one must reduce the spatial resolution to increase the framerate of such cameras. Using temporal coding via physical translation of an optical element known as a coded aperture, the compressive temporal imaging (CACTI) camera emonstrates a method which which to embed the temporal dimension of the video volume into spatial (x,y) measurements, thereby greatly improving temporal resolution with minimal loss of spatial resolution. This technique, which is among a family of compressive sampling strategies developed at Duke University, temporally codes the exposure readout functions at the pixel level. Since video cameras nominally integrate the remaining image volume dimensions (e.g. spectrum and focus) at capture time, spectral (x,y,t,lambda) and focal (x,y,t,z) image volumes are traditionally captured via sequential changes to the spectral and focal state of the system, respectively. The CACTI camera's ability to embed video volumes into images leads to exploration of other information within that video; namely, focal and spectral information. The next part of the thesis demonstrates derivative works of CACTI: compressive extended depth of field and compressive spectral-temporal imaging. These works successfully show the technique's extension of temporal coding to improve sensing performance in these other dimensions. Geometrical optics-related tradeoffs, such as the classic challenges of wide-field-of-view and high resolution photography, have motivated the development of mulitscale camera arrays. The advent of such designs less than a decade ago heralds a new era of research- and engineering-related challenges. One significant challenge is that of managing the focal volume (x,y,z ) over wide fields of view and resolutions. The fourth chapter shows advances on focus and image quality assessment for a class of multiscale gigapixel cameras developed at Duke. Along the same line of work, we have explored methods for dynamic and adaptive addressing of focus via point spread function engineering. We demonstrate another form of temporal coding in the form of physical translation of the image plane from its nominal focal position. We demonstrate this technique's capability to generate arbitrary point spread functions.

A Geographic Information Science (GISc) Approach to Characterizing Spatiotemporal Patterns of Terrorist Incidents in Iraq, 2004-2009

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

Medina, Richard M; Siebeneck, Laura K.; Hepner, George F.

2011-01-01

As terrorism on all scales continues, it is necessary to improve understanding of terrorist and insurgent activities. This article takes a Geographic Information Systems (GIS) approach to advance the understanding of spatial, social, political, and cultural triggers that influence terrorism incidents. Spatial, temporal, and spatiotemporal patterns of terrorist attacks are examined to improve knowledge about terrorist systems of training, planning, and actions. The results of this study aim to provide a foundation for understanding attack patterns and tactics in emerging havens as well as inform the creation and implementation of various counterterrorism measures.

Young Children's Memory for the Times of Personal Past Events

PubMed Central

Pathman, Thanujeni; Larkina, Marina; Burch, Melissa; Bauer, Patricia J.

2012-01-01

Remembering the temporal information associated with personal past events is critical for autobiographical memory, yet we know relatively little about the development of this capacity. In the present research, we investigated temporal memory for naturally occurring personal events in 4-, 6-, and 8-year-old children. Parents recorded unique events in which their children participated during a 4-month period. At test, children made relative recency judgments and estimated the time of each event using conventional time-scales (time of day, day of week, month of year, and season). Children also were asked to provide justifications for their time-scale judgments. Six- and 8-year-olds, but not 4-year-olds, accurately judged the order of two distinct events. There were age-related improvements in children's estimation of the time of events using conventional time-scales. Older children provided more justifications for their time-scale judgments compared to younger children. Relations between correct responding on the time-scale judgments and provision of meaningful justifications suggest that children may use that information to reconstruct the times associated with past events. The findings can be used to chart a developmental trajectory of performance in temporal memory for personal past events, and have implications for our understanding of autobiographical memory development. PMID:23687467

Opportunities to improve monitoring of temporal trends with FIA panel data

Treesearch

Raymond Czaplewski; Michael Thompson

2009-01-01

The Forest Inventory and Analysis (FIA) Program of the Forest Service, Department of Agriculture, is an annual monitoring system for the entire United States. Each year, an independent "panel" of FIA field plots is measured. To improve accuracy, FIA uses the "Moving Average" or "Temporally Indifferent" method to combine estimates from...

A Prediction Algorithm for Drug Response in Patients with Mesial Temporal Lobe Epilepsy Based on Clinical and Genetic Information

PubMed Central

Carvalho, Benilton S.; Bilevicius, Elizabeth; Alvim, Marina K. M.; Lopes-Cendes, Iscia

2017-01-01

Mesial temporal lobe epilepsy is the most common form of adult epilepsy in surgical series. Currently, the only characteristic used to predict poor response to clinical treatment in this syndrome is the presence of hippocampal sclerosis. Single nucleotide polymorphisms (SNPs) located in genes encoding drug transporter and metabolism proteins could influence response to therapy. Therefore, we aimed to evaluate whether combining information from clinical variables as well as SNPs in candidate genes could improve the accuracy of predicting response to drug therapy in patients with mesial temporal lobe epilepsy. For this, we divided 237 patients into two groups: 75 responsive and 162 refractory to antiepileptic drug therapy. We genotyped 119 SNPs in ABCB1, ABCC2, CYP1A1, CYP1A2, CYP1B1, CYP2C9, CYP2C19, CYP2D6, CYP2E1, CYP3A4, and CYP3A5 genes. We used 98 additional SNPs to evaluate population stratification. We assessed a first scenario using only clinical variables and a second one including SNP information. The random forests algorithm combined with leave-one-out cross-validation was used to identify the best predictive model in each scenario and compared their accuracies using the area under the curve statistic. Additionally, we built a variable importance plot to present the set of most relevant predictors on the best model. The selected best model included the presence of hippocampal sclerosis and 56 SNPs. Furthermore, including SNPs in the model improved accuracy from 0.4568 to 0.8177. Our findings suggest that adding genetic information provided by SNPs, located on drug transport and metabolism genes, can improve the accuracy for predicting which patients with mesial temporal lobe epilepsy are likely to be refractory to drug treatment, making it possible to identify patients who may benefit from epilepsy surgery sooner. PMID:28052106

Hypoglossal-facial nerve "side"-to-side neurorrhaphy for facial paralysis resulting from closed temporal bone fractures.

PubMed

Su, Diya; Li, Dezhi; Wang, Shiwei; Qiao, Hui; Li, Ping; Wang, Binbin; Wan, Hong; Schumacher, Michael; Liu, Song

2018-06-06

Closed temporal bone fractures due to cranial trauma often result in facial nerve injury, frequently inducing incomplete facial paralysis. Conventional hypoglossal-facial nerve end-to-end neurorrhaphy may not be suitable for these injuries because sacrifice of the lesioned facial nerve for neurorrhaphy destroys the remnant axons and/or potential spontaneous innervation. we modified the classical method by hypoglossal-facial nerve "side"-to-side neurorrhaphy using an interpositional predegenerated nerve graft to treat these injuries. Five patients who experienced facial paralysis resulting from closed temporal bone fractures due to cranial trauma were treated with the "side"-to-side neurorrhaphy. An additional 4 patients did not receive the neurorrhaphy and served as controls. Before treatment, all patients had suffered House-Brackmann (H-B) grade V or VI facial paralysis for a mean of 5 months. During the 12-30 months of follow-up period, no further detectable deficits were observed, but an improvement in facial nerve function was evidenced over time in the 5 neurorrhaphy-treated patients. At the end of follow-up, the improved facial function reached H-B grade II in 3, grade III in 1 and grade IV in 1 of the 5 patients, consistent with the electrophysiological examinations. In the control group, two patients showed slightly spontaneous innervation with facial function improved from H-B grade VI to V, and the other patients remained unchanged at H-B grade V or VI. We concluded that the hypoglossal-facial nerve "side"-to-side neurorrhaphy can preserve the injured facial nerve and is suitable for treating significant incomplete facial paralysis resulting from closed temporal bone fractures, providing an evident beneficial effect. Moreover, this treatment may be performed earlier after the onset of facial paralysis in order to reduce the unfavorable changes to the injured facial nerve and atrophy of its target muscles due to long-term denervation and allow axonal regrowth in a rich supportive environment.

Wheat seed weight and quality differ temporally in sensitivity to warm or cool conditions during seed development and maturation

PubMed Central

Nasehzadeh, M

2017-01-01

Abstract Background and aims Short periods of extreme temperature may affect wheat (Triticum aestivum) seed weight, but also quality. Temporal sensitivity to extreme temperature during seed development and maturation was investigated. Methods Plants of ‘Tybalt’ grown at ambient temperature were moved to growth cabinets at 29/20°C or 34/20°C (2010), or 15/10°C or 34/20°C (2011), for successive 7-d periods from 7 DAA (days after anthesis) onwards, and also 7–65 DAA in 2011. Seed samples were harvested serially and moisture content, weight, ability to germinate, subsequent longevity in air-dry storage and bread-making quality were determined. Key Results High temperature (34/20°C) reduced final seed weight, with greatest temporal sensitivity at 7–14 or 14–21 DAA. Several aspects of bread-making quality were also most sensitive to high temperature then, but whereas protein quality decreased protein and sulphur concentrations improved. Early exposure to high temperature provided earlier development of ability to germinate and tolerate desiccation, but had little effect on maximum germination capacity. All treatments at 15/10°C resulted in ability to germinate declining between 58 and 65 DAA. Early exposure to high temperature hastened improvement in seed storage longevity, but the subsequent decline in late maturation preceded that in the control. Long (7–65 DAA) exposure to 15/10°C disrupted the development of seed longevity, with no improvement after seed filling ended. Longevity improved during maturation drying in other treatments. Early (7–14 DAA) exposure to high temperature reduced and low temperature increased subsequent longevity at harvest maturity, whereas late (35 or 42–49 DAA) exposure to high temperature increased and low temperature reduced it. Conclusions Temporal sensitivity to extreme temperature was detected. It varied considerably amongst the contrasting seed variables investigated. Subsequent seed longevity at harvest maturity responded negatively to temperature early in development, but positively later in development and throughout maturation. PMID:28637252

Temporal subtraction contrast-enhanced dedicated breast CT

NASA Astrophysics Data System (ADS)

Gazi, Peymon M.; Aminololama-Shakeri, Shadi; Yang, Kai; Boone, John M.

2016-09-01

The development of a framework of deformable image registration and segmentation for the purpose of temporal subtraction contrast-enhanced breast CT is described. An iterative histogram-based two-means clustering method was used for the segmentation. Dedicated breast CT images were segmented into background (air), adipose, fibroglandular and skin components. Fibroglandular tissue was classified as either normal or contrast-enhanced then divided into tiers for the purpose of categorizing degrees of contrast enhancement. A variant of the Demons deformable registration algorithm, intensity difference adaptive Demons (IDAD), was developed to correct for the large deformation forces that stemmed from contrast enhancement. In this application, the accuracy of the proposed method was evaluated in both mathematically-simulated and physically-acquired phantom images. Clinical usage and accuracy of the temporal subtraction framework was demonstrated using contrast-enhanced breast CT datasets from five patients. Registration performance was quantified using normalized cross correlation (NCC), symmetric uncertainty coefficient, normalized mutual information (NMI), mean square error (MSE) and target registration error (TRE). The proposed method outperformed conventional affine and other Demons variations in contrast enhanced breast CT image registration. In simulation studies, IDAD exhibited improvement in MSE (0-16%), NCC (0-6%), NMI (0-13%) and TRE (0-34%) compared to the conventional Demons approaches, depending on the size and intensity of the enhancing lesion. As lesion size and contrast enhancement levels increased, so did the improvement. The drop in the correlation between the pre- and post-contrast images for the largest enhancement levels in phantom studies is less than 1.2% (150 Hounsfield units). Registration error, measured by TRE, shows only submillimeter mismatches between the concordant anatomical target points in all patient studies. The algorithm was implemented using a parallel processing architecture resulting in rapid execution time for the iterative segmentation and intensity-adaptive registration techniques. Characterization of contrast-enhanced lesions is improved using temporal subtraction contrast-enhanced dedicated breast CT. Adaptation of Demons registration forces as a function of contrast-enhancement levels provided a means to accurately align breast tissue in pre- and post-contrast image acquisitions, improving subtraction results. Spatial subtraction of the aligned images yields useful diagnostic information with respect to enhanced lesion morphology and uptake.

Spatio-temporal Variability of Stratified Snowpack Cold Content Observed in the Rocky Mountains

NASA Astrophysics Data System (ADS)

Schmidt, J. S.; Sexstone, G. A.; Serreze, M. C.

2017-12-01

Snowpack cold content (CCsnow) is the energy required to bring a snowpack to an isothermal temperature of 0.0°C. The spatio-temporal variability of CCsnow is complex as it is a measure that integrates the response of a snowpack to each component of the snow-cover energy balance. Snow and ice at high elevation is climate sensitive water storage for the Western U.S. Therefore, an improved understanding of the spatio-temporal variability of CCsnow may provide insight into snowpack dynamics and sensitivity to climate change. In this study, stratified snowpit observations of snow water equivalent (SWE) and snow temperature (Tsnow) from the USGS Rocky Mountain Snowpack network (USGS RMS) were used to evaluate vertical CCsnow profiles over a 16-year period in Montana, Idaho, Wyoming, Colorado and New Mexico. Since 1993, USGS RMS has collected snow chemistry, snow temperature, and SWE data throughout the Rocky Mountain region, making it well positioned for Anthropocene cryosphere benchmarking and climate change interpretation. Spatial grouping of locations based on similar CCsnow characteristics was evaluated and trend analyses were performed. Additionally, we evaluated the regional relation of CCsnow to snowmelt timing. CCsnow was more precisely calculated and more representative using vertically stratified field observed values than bulk values, which highlights the utility of the snowpack dataset presented here. Location specific annual and 16 year mean stratified snowpit profiles of SWE, Tsnow, and CCsnow well represent the physical geography and past weather patterns acting on the snowpack. Observed trends and spatial variability of CCsnow profiles explored by this study provides an improved understanding of changing snowpack behavior in the western U.S., and will be useful for assessing the regional sensitivity of snowpacks to future climate change.

Coastal On-line Assessment and Synthesis Tool 2.0

NASA Technical Reports Server (NTRS)

Brown, Richard; Navard, Andrew; Nguyen, Beth

2011-01-01

COAST (Coastal On-line Assessment and Synthesis Tool) is a 3D, open-source Earth data browser developed by leveraging and enhancing previous NASA open-source tools. These tools use satellite imagery and elevation data in a way that allows any user to zoom from orbit view down into any place on Earth, and enables the user to experience Earth terrain in a visually rich 3D view. The benefits associated with taking advantage of an open-source geo-browser are that it is free, extensible, and offers a worldwide developer community that is available to provide additional development and improvement potential. What makes COAST unique is that it simplifies the process of locating and accessing data sources, and allows a user to combine them into a multi-layered and/or multi-temporal visual analytical look into possible data interrelationships and coeffectors for coastal environment phenomenology. COAST provides users with new data visual analytic capabilities. COAST has been upgraded to maximize use of open-source data access, viewing, and data manipulation software tools. The COAST 2.0 toolset has been developed to increase access to a larger realm of the most commonly implemented data formats used by the coastal science community. New and enhanced functionalities that upgrade COAST to COAST 2.0 include the development of the Temporal Visualization Tool (TVT) plug-in, the Recursive Online Remote Data-Data Mapper (RECORD-DM) utility, the Import Data Tool (IDT), and the Add Points Tool (APT). With these improvements, users can integrate their own data with other data sources, and visualize the resulting layers of different data types (such as spatial and spectral, for simultaneous visual analysis), and visualize temporal changes in areas of interest.

Joint inversion of crosshole GPR and temporal moments of tracer data for improved estimation of hydraulic conductivity at the aquifer scale

NASA Astrophysics Data System (ADS)

Lochbühler, T.; Linde, N.

2012-04-01

Geophysical methods are widely used for aquifer characterization, but they usually fail to directly provide models of hydraulic conductivity. Here, a method is presented to jointly invert crosshole ground-penetrating radar (GPR) travel times and hydrological data to estimate the 2-D distribution of both GPR velocities and hydraulic conductivities. The hydrological data are the first temporal moments of tracer breakthrough curves measured at different depths (i.e., the mean arrival times of the tracer at the given locations). Structural resemblance between the geophysical and the hydrological model is enforced by strongly penalizing models for which the cross products of the model gradients are non-zero. The proposed method was first tested on a synthetic categorical facies model. The high resolution of the GPR velocity model markedly improves the hydraulic conductivity model by adding small-scale structures that remain unresolved by the individual inversion of the hydrological data. The method was then applied to field data acquired within a gravel aquifer located close to the Thur River, northeastern Switzerland. The hydrological data used were derived from transfer functions obtained by deconvolving groundwater electrical conductivity time series with electrical conductivity variations of the river water. These data were recorded over several years at three depth levels in three boreholes aligned along the main groundwater flow direction. The transfer functions are interpreted as breakthrough curves of a pulse injection in the river from which we retrieve the first temporal moments. These data were complemented with crosshole GPR data acquired between the three boreholes. Both the individual and joint inversion models provide a smooth hydraulic conductivity model that retrieves the same general trend as EM flowmeter data, but does not resolve small-scale variability.

Cognitive Enhancement Therapy Improves Resting-State Functional Connectivity in Early Course Schizophrenia

PubMed Central

Eack, Shaun M.; Newhill, Christina E.; Keshavan, Matcheri S.

2016-01-01

Objective Cognitive remediation is emerging as an effective psychosocial intervention for addressing untreated cognitive and functional impairments in persons with schizophrenia, and might achieve its benefits through neuroplastic changes in brain connectivity. This study seeks to examine the effects of cognitive enhancement therapy (CET) on fronto-temporal brain connectivity in a randomized controlled trial with individuals in the early course of schizophrenia. Method Stabilized, early course outpatients with schizophrenia or schizoaffective disorder (N = 41) were randomly assigned to CET (n = 25) or an active enriched supportive therapy (EST) control (n = 16) and treated for 2 years. Functional MRI data were collected annually, and pseudo resting-state functional connectivity analysis was used to examine differential changes in fronto-temporal connectivity between those treated with CET compared with EST. Results Individuals receiving CET evidenced significantly less functional connectivity loss between the resting-state network and the left dorsolateral prefrontal cortex as well as significantly increased connectivity with the right insular cortex compared to EST (all corrected p < .01). These neural networks are involved in emotion processing and problem-solving. Increased connectivity with the right insula significantly mediated CET effects on improved emotion perception (z′ = −1.96, p = .021), and increased connectivity with the left dorsolateral prefrontal cortex mediated CET-related improvements in emotion regulation (z′ = −1.71, p = .052). Conclusions These findings provide preliminary evidence that CET, a psychosocial cognitive remediation intervention, may enhance connectivity between frontal and temporal brain regions implicated in problem-solving and emotion processing in service of cognitive enhancement in schizophrenia. PMID:27713804

Concurrent temporal stability of the apparent electrical conductivity and soil water content

USDA-ARS?s Scientific Manuscript database

Knowledge of spatio-temporal soil water content (SWC) variability within agricultural fields is useful to improve crop management. Spatial patterns of soil water contents can be characterized using the temporal stability analysis, however high density sampling is required. Soil apparent electrical c...

Temporal network analysis identifies early physiological and transcriptomic indicators of mild drought in Brassica rapa

PubMed Central

Gehan, Malia A; Mockler, Todd C; Weinig, Cynthia; Ewers, Brent E

2017-01-01

The dynamics of local climates make development of agricultural strategies challenging. Yield improvement has progressed slowly, especially in drought-prone regions where annual crop production suffers from episodic aridity. Underlying drought responses are circadian and diel control of gene expression that regulate daily variations in metabolic and physiological pathways. To identify transcriptomic changes that occur in the crop Brassica rapa during initial perception of drought, we applied a co-expression network approach to associate rhythmic gene expression changes with physiological responses. Coupled analysis of transcriptome and physiological parameters over a two-day time course in control and drought-stressed plants provided temporal resolution necessary for correlation of network modules with dynamic changes in stomatal conductance, photosynthetic rate, and photosystem II efficiency. This approach enabled the identification of drought-responsive genes based on their differential rhythmic expression profiles in well-watered versus droughted networks and provided new insights into the dynamic physiological changes that occur during drought. PMID:28826479

Are well functioning civil registration and vital statistics systems associated with better health outcomes?

PubMed

Phillips, David E; AbouZahr, Carla; Lopez, Alan D; Mikkelsen, Lene; de Savigny, Don; Lozano, Rafael; Wilmoth, John; Setel, Philip W

2015-10-03

In this Series paper, we examine whether well functioning civil registration and vital statistics (CRVS) systems are associated with improved population health outcomes. We present a conceptual model connecting CRVS to wellbeing, and describe an ecological association between CRVS and health outcomes. The conceptual model posits that the legal identity that civil registration provides to individuals is key to access entitlements and services. Vital statistics produced by CRVS systems provide essential information for public health policy and prevention. These outcomes benefit individuals and societies, including improved health. We use marginal linear models and lag-lead analysis to measure ecological associations between a composite metric of CRVS performance and three health outcomes. Results are consistent with the conceptual model: improved CRVS performance coincides with improved health outcomes worldwide in a temporally consistent manner. Investment to strengthen CRVS systems is not only an important goal for individuals and societies, but also a development imperative that is good for health. Copyright © 2015 Elsevier Ltd. All rights reserved.

Fast fMRI provides high statistical power in the analysis of epileptic networks.

PubMed

Jacobs, Julia; Stich, Julia; Zahneisen, Benjamin; Assländer, Jakob; Ramantani, Georgia; Schulze-Bonhage, Andreas; Korinthenberg, Rudolph; Hennig, Jürgen; LeVan, Pierre

2014-03-01

EEG-fMRI is a unique method to combine the high temporal resolution of EEG with the high spatial resolution of MRI to study generators of intrinsic brain signals such as sleep grapho-elements or epileptic spikes. While the standard EPI sequence in fMRI experiments has a temporal resolution of around 2.5-3s a newly established fast fMRI sequence called MREG (Magnetic-Resonance-Encephalography) provides a temporal resolution of around 100ms. This technical novelty promises to improve statistics, facilitate correction of physiological artifacts and improve the understanding of epileptic networks in fMRI. The present study compares simultaneous EEG-EPI and EEG-MREG analyzing epileptic spikes to determine the yield of fast MRI in the analysis of intrinsic brain signals. Patients with frequent interictal spikes (>3/20min) underwent EEG-MREG and EEG-EPI (3T, 20min each, voxel size 3×3×3mm, EPI TR=2.61s, MREG TR=0.1s). Timings of the spikes were used in an event-related analysis to generate activation maps of t-statistics. (FMRISTAT, |t|>3.5, cluster size: 7 voxels, p<0.05 corrected). For both sequences, the amplitude and location of significant BOLD activations were compared with the spike topography. 13 patients were recorded and 33 different spike types could be analyzed. Peak T-values were significantly higher in MREG than in EPI (p<0.0001). Positive BOLD effects correlating with the spike topography were found in 8/29 spike types using the EPI and in 22/33 spikes types using the MREG sequence. Negative BOLD responses in the default mode network could be observed in 3/29 spike types with the EPI and in 19/33 with the MREG sequence. With the latter method, BOLD changes were observed even when few spikes occurred during the investigation. Simultaneous EEG-MREG thus is possible with good EEG quality and shows higher sensitivity in regard to the localization of spike-related BOLD responses than EEG-EPI. The development of new methods of analysis for this sequence such as modeling of physiological noise, temporal analysis of the BOLD signal and defining appropriate thresholds is required to fully profit from its high temporal resolution. © 2013.

Subcortical aphasia: a longitudinal PET study.

PubMed

de Boissezon, Xavier; Démonet, Jean-François; Puel, Michèle; Marie, Nathalie; Raboyeau, Gaëlle; Albucher, Jean-François; Chollet, François; Cardebat, Dominique

2005-07-01

Very few neuroimaging studies have focused on follow-up of subcortical aphasia. Here, overt language production tasks were used to correlate regional cerebral blood flow (rCBF) changes and language performance in patients with vascular subcortical lesions. Seven aphasic patients were scanned twice with positron emission tomography (PET) at 1-year interval during a word-generation task. Using SPM2, Language-Rest contrast at PET1 was correlated to language performance and to time-lag from stroke. The same contrast was performed at PET2 and session effect (PET2-PET1) was correlated with performance improvement. At PET1, correlation between rCBF and delay from stroke involved mainly ventral regions of the left temporal cortex and mesial frontal cortex. Correlations between rCBF and performance showed predominantly left dorsal regions in the frontal, temporal, and parietal lobes, but also the left ventral temporal cortex. One year apart, language performance improved and rCBF increased in perisylvian regions bilaterally. Best performers at PET2 showed an increase of activity in left ventral temporal cortex as well as in right middle temporal gyrus. On follow-up, expected language improvement and increase of activation in the classical language areas and their counterparts were observed. Moreover, all correlational analyses both at PET1 and on follow-up implicated the anterior part of the left inferior temporal gyrus, suggesting a disconnection between the superior and inferior parts of the left temporal cortex and a specific role for this region in lexical semantic processing.

Temporal abstraction-based clinical phenotyping with Eureka!

PubMed

Post, Andrew R; Kurc, Tahsin; Willard, Richie; Rathod, Himanshu; Mansour, Michel; Pai, Akshatha Kalsanka; Torian, William M; Agravat, Sanjay; Sturm, Suzanne; Saltz, Joel H

2013-01-01

Temporal abstraction, a method for specifying and detecting temporal patterns in clinical databases, is very expressive and performs well, but it is difficult for clinical investigators and data analysts to understand. Such patterns are critical in phenotyping patients using their medical records in research and quality improvement. We have previously developed the Analytic Information Warehouse (AIW), which computes such phenotypes using temporal abstraction but requires software engineers to use. We have extended the AIW's web user interface, Eureka! Clinical Analytics, to support specifying phenotypes using an alternative model that we developed with clinical stakeholders. The software converts phenotypes from this model to that of temporal abstraction prior to data processing. The model can represent all phenotypes in a quality improvement project and a growing set of phenotypes in a multi-site research study. Phenotyping that is accessible to investigators and IT personnel may enable its broader adoption.

The Impact of Horizontal and Temporal Resolution on Convection and Precipitation with High-Resolution GEOS-5

NASA Technical Reports Server (NTRS)

Putman, William P.

2012-01-01

Using a high-resolution non-hydrostatic version of GEOS-5 with the cubed-sphere finite-volume dynamical core, the impact of spatial and temporal resolution on cloud properties will be evaluated. There are indications from examining convective cluster development in high resolution GEOS-5 forecasts that the temporal resolution within the model may playas significant a role as horizontal resolution. Comparing modeled convective cloud clusters versus satellite observations of brightness temperature, we have found that improved. temporal resolution in GEOS-S accounts for a significant portion of the improvements in the statistical distribution of convective cloud clusters. Using satellite simulators in GEOS-S we will compare the cloud optical properties of GEOS-S at various spatial and temporal resolutions with those observed from MODIS. The potential impact of these results on tropical cyclone formation and intensity will be examined as well.

Dynamic Network Model for Smart City Data-Loss Resilience Case Study: City-to-City Network for Crime Analytics

PubMed Central

Kotevska, Olivera; Kusne, A. Gilad; Samarov, Daniel V.; Lbath, Ahmed; Battou, Abdella

2017-01-01

Today’s cities generate tremendous amounts of data, thanks to a boom in affordable smart devices and sensors. The resulting big data creates opportunities to develop diverse sets of context-aware services and systems, ensuring smart city services are optimized to the dynamic city environment. Critical resources in these smart cities will be more rapidly deployed to regions in need, and those regions predicted to have an imminent or prospective need. For example, crime data analytics may be used to optimize the distribution of police, medical, and emergency services. However, as smart city services become dependent on data, they also become susceptible to disruptions in data streams, such as data loss due to signal quality reduction or due to power loss during data collection. This paper presents a dynamic network model for improving service resilience to data loss. The network model identifies statistically significant shared temporal trends across multivariate spatiotemporal data streams and utilizes these trends to improve data prediction performance in the case of data loss. Dynamics also allow the system to respond to changes in the data streams such as the loss or addition of new information flows. The network model is demonstrated by city-based crime rates reported in Montgomery County, MD, USA. A resilient network is developed utilizing shared temporal trends between cities to provide improved crime rate prediction and robustness to data loss, compared with the use of single city-based auto-regression. A maximum improvement in performance of 7.8% for Silver Spring is found and an average improvement of 5.6% among cities with high crime rates. The model also correctly identifies all the optimal network connections, according to prediction error minimization. City-to-city distance is designated as a predictor of shared temporal trends in crime and weather is shown to be a strong predictor of crime in Montgomery County. PMID:29250476

Dynamic Network Model for Smart City Data-Loss Resilience Case Study: City-to-City Network for Crime Analytics.

PubMed

Kotevska, Olivera; Kusne, A Gilad; Samarov, Daniel V; Lbath, Ahmed; Battou, Abdella

2017-01-01

Today's cities generate tremendous amounts of data, thanks to a boom in affordable smart devices and sensors. The resulting big data creates opportunities to develop diverse sets of context-aware services and systems, ensuring smart city services are optimized to the dynamic city environment. Critical resources in these smart cities will be more rapidly deployed to regions in need, and those regions predicted to have an imminent or prospective need. For example, crime data analytics may be used to optimize the distribution of police, medical, and emergency services. However, as smart city services become dependent on data, they also become susceptible to disruptions in data streams, such as data loss due to signal quality reduction or due to power loss during data collection. This paper presents a dynamic network model for improving service resilience to data loss. The network model identifies statistically significant shared temporal trends across multivariate spatiotemporal data streams and utilizes these trends to improve data prediction performance in the case of data loss. Dynamics also allow the system to respond to changes in the data streams such as the loss or addition of new information flows. The network model is demonstrated by city-based crime rates reported in Montgomery County, MD, USA. A resilient network is developed utilizing shared temporal trends between cities to provide improved crime rate prediction and robustness to data loss, compared with the use of single city-based auto-regression. A maximum improvement in performance of 7.8% for Silver Spring is found and an average improvement of 5.6% among cities with high crime rates. The model also correctly identifies all the optimal network connections, according to prediction error minimization. City-to-city distance is designated as a predictor of shared temporal trends in crime and weather is shown to be a strong predictor of crime in Montgomery County.

Enhanced SAR data processing for land instability forecast.

NASA Astrophysics Data System (ADS)

Argentiero, Ilenia; Pellicani, Roberta; Spilotro, Giuseppe; Parisi, Alessandro; Bovenga, Fabio; Pasquariello, Guido; Refice, Alberto; Nutricato, Raffaele; Nitti, Davide Oscar; Chiaradia, Maria Teresa

2017-04-01

Monitoring represents the main tool for carrying out evaluation procedures and criteria for spatial and temporal landslide forecast. The forecast of landslide behaviour depends on the possibility to identify either evidences of activity (displacement, velocity, volume of unstable mass, direction of displacement, and their temporal variation) or triggering parameters (rainfalls). Generally, traditional geotechnical landslide monitoring technologies permit to define, if correctly positioned and with adequate accuracy, the critical value of displacement and/or acceleration into landslide body. In most cases, they do not allow real time warning signs to be generated, due to environmental induced errors, and the information is related to few points on unstable area. Remote-sensing monitoring instruments are capable of inspecting an unstable slope with high spatial and temporal frequency, but allow solely measurements of superficial displacements and deformations. Among these latest technologies, the satellite Persistent Scatterer SAR Interferometry (PSInSAR) is very useful to investigate the unstable area both in terms of space and time. Indeed, this technique allows to analyse wide areas, individuate critical unstable areas, not identifiable by means detailed in situ surveys, and study the phenomenon evolution in a long time-scale. Although this technique usually adopts, as first approximation, a linear model to describe the displacement of the detected targets, also non-linear models can be used. However, the satellite revisit time, which defines the time sampling of the detected displacement signal, limits the maximum measurable velocity and acceleration. This makes it difficult to assess in the short time any acceleration indicating a loss of equilibrium and, therefore, a probable reactivation of the landslide. The recent Sentinel-1 mission from the European Space Agency (ESA), provides a spatial resolution comparable to the previous ESA missions, but a nominal revisit time reduced to 6 days. By offering regular global-scale coverage, better temporal resolution and freely available imagery, Sentinel-1 improves the performance of PSInSAR for ground displacement investigations. In particular, the short revisit time allows a better time series analysis by improving the temporal sampling and the chances to catch pre-failure signals characterised by high rate and non-linear behaviour signals. Moreover, it allows collecting large data stacks in a short time period, thus improving the PSInSAR performance in emergency (post-event) scenarios. In the present work, we propose to match satellite data with numerical analysis techniques appropriate to evidence unsteady kinematics and, thanks to the high resolution of satellite data and improved temporal sampling, to detect early stages of land instability phenomena. The test area is situated in a small town in the Southern Apennine, Basilicata region, affected by old and new huge landslides, now close to a lived outskirt.

Plant functional traits improve diversity-based predictions of temporal stability of grassland productivity

USDA-ARS?s Scientific Manuscript database

Aboveground net primary productivity (ANPP) varies in response to temporal fluctuations in weather. Temporal stability (mean/standard deviation) of community ANPP may be increased, on average, by increasing plant species richness, but stability also may differ widely at a given richness level imply...

Assessment of gait parameters and fatigue in MS patients during inpatient rehabilitation: a pilot trial.

PubMed

Sacco, Rosaria; Bussman, Rita; Oesch, Peter; Kesselring, Jürg; Beer, Serafin

2011-05-01

Gait impairment and fatigue are common and disabling problems in multiple sclerosis (MS). Characterisation of abnormal gait in MS patients has been done mainly using observational studies and simple walking tests providing only limited quantitative and no qualitative data, or using intricate and time-consuming assessment procedures. In addition, the correlation of gait impairments with fatigue is largely unknown. The aim of this study was to characterise spatio-temporal gait parameters by a simple and easy-to-use gait analysis system (GAITRite®) in MS patients compared with healthy controls, and to analyse changes and correlation with fatigue during inpatient rehabilitation. Twenty-four MS patients (EDSS <6.5) admitted for inpatient rehabilitation and 19 healthy subjects were evaluated using the GAITRite® Functional Ambulation System. Between-group differences and changes of gait parameters during inpatient rehabilitation were analysed, and correlation with fatigue, using the Wurzburg Fatigue Inventory for Multiple Sclerosis (WEIMuS), was determined. Compared to healthy controls MS patients showed significant impairments in different spatio-temporal gait parameters, which showed a significant improvement during inpatient rehabilitation. Different gait parameters were correlated with fatigue physical score, and change of gait parameters was correlated with improvement of fatigue. Spatio-temporal gait analysis is helpful to assess specific walking impairments in MS patients and subtle changes during rehabilitation. Correlation with fatigue may indicate a possible negative impact of fatigue on rehabilitation outcome.

Simultaneous Multi-Slice fMRI using Spiral Trajectories

PubMed Central

Zahneisen, Benjamin; Poser, Benedikt A.; Ernst, Thomas; Stenger, V. Andrew

2014-01-01

Parallel imaging methods using multi-coil receiver arrays have been shown to be effective for increasing MRI acquisition speed. However parallel imaging methods for fMRI with 2D sequences show only limited improvements in temporal resolution because of the long echo times needed for BOLD contrast. Recently, Simultaneous Multi-Slice (SMS) imaging techniques have been shown to increase fMRI temporal resolution by factors of four and higher. In SMS fMRI multiple slices can be acquired simultaneously using Echo Planar Imaging (EPI) and the overlapping slices are un-aliased using a parallel imaging reconstruction with multiple receivers. The slice separation can be further improved using the “blipped-CAIPI” EPI sequence that provides a more efficient sampling of the SMS 3D k-space. In this paper a blipped-spiral SMS sequence for ultra-fast fMRI is presented. The blipped-spiral sequence combines the sampling efficiency of spiral trajectories with the SMS encoding concept used in blipped-CAIPI EPI. We show that blipped spiral acquisition can achieve almost whole brain coverage at 3 mm isotropic resolution in 168 ms. It is also demonstrated that the high temporal resolution allows for dynamic BOLD lag time measurement using visual/motor and retinotopic mapping paradigms. The local BOLD lag time within the visual cortex following the retinotopic mapping stimulation of expanding flickering rings is directly measured and easily translated into an eccentricity map of the cortex. PMID:24518259

Considering low-rank, sparse and gas-inflow effects constraints for accelerated pulmonary dynamic hyperpolarized 129Xe MRI

NASA Astrophysics Data System (ADS)

Xiao, Sa; Deng, He; Duan, Caohui; Xie, Junshuai; Zhang, Huiting; Sun, Xianping; Ye, Chaohui; Zhou, Xin

2018-05-01

Dynamic hyperpolarized (HP) 129Xe MRI is able to visualize the process of lung ventilation, which potentially provides unique information about lung physiology and pathophysiology. However, the longitudinal magnetization of HP 129Xe is nonrenewable, making it difficult to achieve high image quality while maintaining high temporal-spatial resolution in the pulmonary dynamic MRI. In this paper, we propose a new accelerated dynamic HP 129Xe MRI scheme incorporating the low-rank, sparse and gas-inflow effects (L + S + G) constraints. According to the gas-inflow effects of HP gas during the lung inspiratory process, a variable-flip-angle (VFA) strategy is designed to compensate for the rapid attenuation of the magnetization. After undersampling k-space data, an effective reconstruction algorithm considering the low-rank, sparse and gas-inflow effects constraints is developed to reconstruct dynamic MR images. In this way, the temporal and spatial resolution of dynamic MR images is improved and the artifacts are lessened. Simulation and in vivo experiments implemented on the phantom and healthy volunteers demonstrate that the proposed method is not only feasible and effective to compensate for the decay of the magnetization, but also has a significant improvement compared with the conventional reconstruction algorithms (P-values are less than 0.05). This confirms the superior performance of the proposed designs and their ability to maintain high quality and temporal-spatial resolution.

Effect of radar rainfall time resolution on the predictive capability of a distributed hydrologic model

NASA Astrophysics Data System (ADS)

Atencia, A.; Llasat, M. C.; Garrote, L.; Mediero, L.

2010-10-01

The performance of distributed hydrological models depends on the resolution, both spatial and temporal, of the rainfall surface data introduced. The estimation of quantitative precipitation from meteorological radar or satellite can improve hydrological model results, thanks to an indirect estimation at higher spatial and temporal resolution. In this work, composed radar data from a network of three C-band radars, with 6-minutal temporal and 2 × 2 km2 spatial resolution, provided by the Catalan Meteorological Service, is used to feed the RIBS distributed hydrological model. A Window Probability Matching Method (gage-adjustment method) is applied to four cases of heavy rainfall to improve the observed rainfall sub-estimation in both convective and stratiform Z/R relations used over Catalonia. Once the rainfall field has been adequately obtained, an advection correction, based on cross-correlation between two consecutive images, was introduced to get several time resolutions from 1 min to 30 min. Each different resolution is treated as an independent event, resulting in a probable range of input rainfall data. This ensemble of rainfall data is used, together with other sources of uncertainty, such as the initial basin state or the accuracy of discharge measurements, to calibrate the RIBS model using probabilistic methodology. A sensitivity analysis of time resolutions was implemented by comparing the various results with real values from stream-flow measurement stations.

Neuropsychological outcomes after Gamma Knife radiosurgery for mesial temporal lobe epilepsy: a prospective multicenter study.

PubMed

Quigg, Mark; Broshek, Donna K; Barbaro, Nicholas M; Ward, Mariann M; Laxer, Kenneth D; Yan, Guofen; Lamborn, Kathleen

2011-05-01

To assess outcomes of language, verbal memory, cognitive efficiency and mental flexibility, mood, and quality of life (QOL) in a prospective, multicenter pilot study of Gamma Knife radiosurgery (RS) for mesial temporal lobe epilepsy (MTLE). RS, randomized to 20 Gy or 24 Gy comprising 5.5-7.5 ml at the 50% isodose volume, was performed on mesial temporal structures of patients with unilateral MTLE. Neuropsychological evaluations were performed at preoperative baseline, and mean change scores were described at 12 and 24 months postoperatively. QOL data were also available at 36 months. Thirty patients were treated and 26 were available for the final 24-month neuropsychological evaluation. Language (Boston Naming Test), verbal memory (California Verbal Learning Test and Logical Memory subtest of the Wechsler Memory Scale-Revised), cognitive efficiency and mental flexibility (Trail Making Test), and mood (Beck Depression Inventory) did not differ from baseline. QOL scores improved at 24 and 36 months, with those patients attaining seizure remission by month 24s accounting for the majority of the improvement. The serial changes in cognitive outcomes, mood, and QOL are unremarkable following RS for MTLE. RS may provide an alternative to open surgery, especially in those patients at risk of cognitive impairment or who desire a noninvasive alternative to open surgery. Wiley Periodicals, Inc. © 2011 International League Against Epilepsy.

Comparison between two time-resolved approaches for prostate cancer diagnosis: high rate imager vs. photon counting system

NASA Astrophysics Data System (ADS)

Boutet, J.; Debourdeau, M.; Laidevant, A.; Hervé, L.; Dinten, J.-M.

2010-02-01

Finding a way to combine ultrasound and fluorescence optical imaging on an endorectal probe may improve early detection of prostate cancer. A trans-rectal probe adapted to fluorescence diffuse optical tomography measurements was developed by our team. This probe is based on a pulsed NIR laser source, an optical fiber network and a time-resolved detection system. A reconstruction algorithm was used to help locate and quantify fluorescent prostate tumors. In this study, two different kinds of time-resolved detectors are compared: High Rate Imaging system (HRI) and a photon counting system. The HRI is based on an intensified multichannel plate and a CCD Camera. The temporal resolution is obtained through a gating of the HRI. Despite a low temporal resolution (300ps), this system allows a simultaneous acquisition of the signal from a large number of detection fibers. In the photon counting setup, 4 photomultipliers are connected to a Time Correlated Single Photon Counting (TCSPC) board, providing a better temporal resolution (0.1 ps) at the expense of a limited number of detection fibers (4). At last, we show that the limited number of detection fibers of the photon counting setup is enough for a good localization and dramatically improves the overall acquisition time. The photon counting approach is then validated through the localization of fluorescent inclusions in a prostate-mimicking phantom.

Space-based observations of nitrogen dioxide: Trends in anthropogenic emissions

NASA Astrophysics Data System (ADS)

Russell, Ashley Ray

Space-based instruments provide routine global observations, offering a unique perspective on the spatial and temporal variation of atmospheric constituents. In this dissertation, trends in regional-scale anthropogenic nitrogen oxide emissions (NO + NO2 ≡ NOx) are investigated using high resolution observations from the Ozone Monitoring Instrument (OMI). By comparing trends in OMI observations with those from ground-based measurements and an emissions inventory, I show that satellite observations are well-suited for capturing changes in emissions over time. The high spatial and temporal resolutions of the observations provide a uniquely complete view of regional-scale changes in the spatial patterns of NO 2. I show that NOx concentrations have decreased significantly in urban regions of the United States between 2005 and 2011, with an average reduction of 32 ± 7%. By examining day-of-week and interannual trends, I show that these reductions can largely be attributed to improved emission control technology in the mobile source fleet; however, I also show that the economic downturn of the late 2000's has impacted emissions. Additionally, I describe the development of a high-resolution retrieval of NO2 from OMI observations known as the Berkeley High Resolution (BEHR) retrieval. The BEHR product uses higher spatial and temporal resolution terrain and profile parameters than the operational retrievals and is shown to provide a more quantitative measure of tropospheric NO2 column density. These results have important implications for future retrievals of NO2 from space-based observations.

A Flexible Spatio-Temporal Model for Air Pollution with Spatial and Spatio-Temporal Covariates.

PubMed

Lindström, Johan; Szpiro, Adam A; Sampson, Paul D; Oron, Assaf P; Richards, Mark; Larson, Tim V; Sheppard, Lianne

2014-09-01

The development of models that provide accurate spatio-temporal predictions of ambient air pollution at small spatial scales is of great importance for the assessment of potential health effects of air pollution. Here we present a spatio-temporal framework that predicts ambient air pollution by combining data from several different monitoring networks and deterministic air pollution model(s) with geographic information system (GIS) covariates. The model presented in this paper has been implemented in an R package, SpatioTemporal, available on CRAN. The model is used by the EPA funded Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air) to produce estimates of ambient air pollution; MESA Air uses the estimates to investigate the relationship between chronic exposure to air pollution and cardiovascular disease. In this paper we use the model to predict long-term average concentrations of NO x in the Los Angeles area during a ten year period. Predictions are based on measurements from the EPA Air Quality System, MESA Air specific monitoring, and output from a source dispersion model for traffic related air pollution (Caline3QHCR). Accuracy in predicting long-term average concentrations is evaluated using an elaborate cross-validation setup that accounts for a sparse spatio-temporal sampling pattern in the data, and adjusts for temporal effects. The predictive ability of the model is good with cross-validated R 2 of approximately 0.7 at subject sites. Replacing four geographic covariate indicators of traffic density with the Caline3QHCR dispersion model output resulted in very similar prediction accuracy from a more parsimonious and more interpretable model. Adding traffic-related geographic covariates to the model that included Caline3QHCR did not further improve the prediction accuracy.

Predicting heavy episodic drinking using an extended temporal self-regulation theory.

PubMed

Black, Nicola; Mullan, Barbara; Sharpe, Louise

2017-10-01

Alcohol consumption contributes significantly to the global burden from disease and injury, and specific patterns of heavy episodic drinking contribute uniquely to this burden. Temporal self-regulation theory and the dual-process model describe similar theoretical constructs that might predict heavy episodic drinking. The aims of this study were to test the utility of temporal self-regulation theory in predicting heavy episodic drinking, and examine whether the theoretical relationships suggested by the dual-process model significantly extend temporal self-regulation theory. This was a predictive study with 149 Australian adults. Measures were questionnaires (self-report habit index, cues to action scale, purpose-made intention questionnaire, timeline follow-back questionnaire) and executive function tasks (Stroop, Tower of London, operation span). Participants completed measures of theoretical constructs at baseline and reported their alcohol consumption two weeks later. Data were analysed using hierarchical multiple linear regression. Temporal self-regulation theory significantly predicted heavy episodic drinking (R 2 =48.0-54.8%, p<0.001) and the hypothesised extension significantly improved the prediction of heavy episodic drinking frequency (ΔR 2 =4.5%, p=0.001) but not peak consumption (ΔR 2 =1.4%, p=0.181). Intention and behavioural prepotency directly predicted heavy episodic drinking (p<0.01). Planning ability moderated the intention-behaviour relationship and inhibitory control moderated the behavioural prepotency-behaviour relationship (p<0.05). Both temporal self-regulation theory and the extended temporal self-regulation theory provide good prediction of heavy episodic drinking. Intention, behavioural prepotency, planning ability and inhibitory control may be good targets for interventions designed to decrease heavy episodic drinking. Copyright © 2017 Elsevier Ltd. All rights reserved.

Temporal resolution and motion artifacts in single-source and dual-source cardiac CT.

PubMed

Schöndube, Harald; Allmendinger, Thomas; Stierstorfer, Karl; Bruder, Herbert; Flohr, Thomas

2013-03-01

The temporal resolution of a given image in cardiac computed tomography (CT) has so far mostly been determined from the amount of CT data employed for the reconstruction of that image. The purpose of this paper is to examine the applicability of such measures to the newly introduced modality of dual-source CT as well as to methods aiming to provide improved temporal resolution by means of an advanced image reconstruction algorithm. To provide a solid base for the examinations described in this paper, an extensive review of temporal resolution in conventional single-source CT is given first. Two different measures for assessing temporal resolution with respect to the amount of data involved are introduced, namely, either taking the full width at half maximum of the respective data weighting function (FWHM-TR) or the total width of the weighting function (total TR) as a base of the assessment. Image reconstruction using both a direct fan-beam filtered backprojection with Parker weighting as well as using a parallel-beam rebinning step are considered. The theory of assessing temporal resolution by means of the data involved is then extended to dual-source CT. Finally, three different advanced iterative reconstruction methods that all use the same input data are compared with respect to the resulting motion artifact level. For brevity and simplicity, the examinations are limited to two-dimensional data acquisition and reconstruction. However, all results and conclusions presented in this paper are also directly applicable to both circular and helical cone-beam CT. While the concept of total TR can directly be applied to dual-source CT, the definition of the FWHM of a weighting function needs to be slightly extended to be applicable to this modality. The three different advanced iterative reconstruction methods examined in this paper result in significantly different images with respect to their motion artifact level, despite exactly the same amount of data being used in the reconstruction process. The concept of assessing temporal resolution by means of the data employed for reconstruction can nicely be extended from single-source to dual-source CT. However, for advanced (possibly nonlinear iterative) reconstruction algorithms the examined approach fails to deliver accurate results. New methods and measures to assess the temporal resolution of CT images need to be developed to be able to accurately compare the performance of such algorithms.

Research on Visual Analysis Methods of Terrorism Events

NASA Astrophysics Data System (ADS)

Guo, Wenyue; Liu, Haiyan; Yu, Anzhu; Li, Jing

2016-06-01

Under the situation that terrorism events occur more and more frequency throughout the world, improving the response capability of social security incidents has become an important aspect to test governments govern ability. Visual analysis has become an important method of event analysing for its advantage of intuitive and effective. To analyse events' spatio-temporal distribution characteristics, correlations among event items and the development trend, terrorism event's spatio-temporal characteristics are discussed. Suitable event data table structure based on "5W" theory is designed. Then, six types of visual analysis are purposed, and how to use thematic map and statistical charts to realize visual analysis on terrorism events is studied. Finally, experiments have been carried out by using the data provided by Global Terrorism Database, and the results of experiments proves the availability of the methods.

An Advanced simulation Code for Modeling Inductive Output Tubes

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

Thuc Bui; R. Lawrence Ives

2012-04-27

During the Phase I program, CCR completed several major building blocks for a 3D large signal, inductive output tube (IOT) code using modern computer language and programming techniques. These included a 3D, Helmholtz, time-harmonic, field solver with a fully functional graphical user interface (GUI), automeshing and adaptivity. Other building blocks included the improved electrostatic Poisson solver with temporal boundary conditions to provide temporal fields for the time-stepping particle pusher as well as the self electric field caused by time-varying space charge. The magnetostatic field solver was also updated to solve for the self magnetic field caused by time changing currentmore » density in the output cavity gap. The goal function to optimize an IOT cavity was also formulated, and the optimization methodologies were investigated.« less

Influenza forecasting with Google Flu Trends.

PubMed

Dugas, Andrea Freyer; Jalalpour, Mehdi; Gel, Yulia; Levin, Scott; Torcaso, Fred; Igusa, Takeru; Rothman, Richard E

2013-01-01

We developed a practical influenza forecast model based on real-time, geographically focused, and easy to access data, designed to provide individual medical centers with advanced warning of the expected number of influenza cases, thus allowing for sufficient time to implement interventions. Secondly, we evaluated the effects of incorporating a real-time influenza surveillance system, Google Flu Trends, and meteorological and temporal information on forecast accuracy. Forecast models designed to predict one week in advance were developed from weekly counts of confirmed influenza cases over seven seasons (2004-2011) divided into seven training and out-of-sample verification sets. Forecasting procedures using classical Box-Jenkins, generalized linear models (GLM), and generalized linear autoregressive moving average (GARMA) methods were employed to develop the final model and assess the relative contribution of external variables such as, Google Flu Trends, meteorological data, and temporal information. A GARMA(3,0) forecast model with Negative Binomial distribution integrating Google Flu Trends information provided the most accurate influenza case predictions. The model, on the average, predicts weekly influenza cases during 7 out-of-sample outbreaks within 7 cases for 83% of estimates. Google Flu Trend data was the only source of external information to provide statistically significant forecast improvements over the base model in four of the seven out-of-sample verification sets. Overall, the p-value of adding this external information to the model is 0.0005. The other exogenous variables did not yield a statistically significant improvement in any of the verification sets. Integer-valued autoregression of influenza cases provides a strong base forecast model, which is enhanced by the addition of Google Flu Trends confirming the predictive capabilities of search query based syndromic surveillance. This accessible and flexible forecast model can be used by individual medical centers to provide advanced warning of future influenza cases.

Evaluating the capacity of GF-4 satellite data for estimating fractional vegetation cover

NASA Astrophysics Data System (ADS)

Zhang, C.; Qin, Q.; Ren, H.; Zhang, T.; Sun, Y.

2016-12-01

Fractional vegetation cover (FVC) is a crucial parameter for many agricultural, environmental, meteorological and ecological applications, which is of great importance for studies on ecosystem structure and function. The Chinese GaoFen-4 (GF-4) geostationary satellite designed for the purpose of environmental and ecological observation was launched in December 29, 2015, and official use has been started by Chinese Government on June 13, 2016. Multi-spectral images with spatial resolution of 50 m and high temporal resolution, could be acquired by the sensor on GF-4 satellite on the 36000 km-altitude orbit. To take full advantage of the outstanding performance of GF-4 satellite, this study evaluated the capacity of GF-4 satellite data for monitoring FVC. To the best of our knowledge, this is the first research about estimating FVC from GF-4 satellite images. First, we developed a procedure for preprocessing GF-4 satellite data, including radiometric calibration and atmospheric correction, to acquire surface reflectance. Then single image and multi-temporal images were used for extracting the endmembers of vegetation and soil, respectively. After that, dimidiate pixel model and square model based on vegetation indices were used for estimating FVC. Finally, the estimation results were comparatively analyzed with FVC estimated by other existing sensors. The experimental results showed that satisfying accuracy of FVC estimation could be achieved from GF-4 satellite images using dimidiate pixel model and square model based on vegetation indices. What's more, the multi-temporal images increased the probability to find pure vegetation and soil endmembers, thus the characteristic of high temporal resolution of GF-4 satellite images improved the accuracy of FVC estimation. This study demonstrated the capacity of GF-4 satellite data for monitoring FVC. The conclusions reached by this study are significant for improving the accuracy and spatial-temporal resolution of existing FVC products, which provides a basis for the studies on ecosystem structure and function using remote sensing data acquired by GF-4 satellite.

Highly accelerated intracranial 4D flow MRI: evaluation of healthy volunteers and patients with intracranial aneurysms.

PubMed

Liu, Jing; Koskas, Louise; Faraji, Farshid; Kao, Evan; Wang, Yan; Haraldsson, Henrik; Kefayati, Sarah; Zhu, Chengcheng; Ahn, Sinyeob; Laub, Gerhard; Saloner, David

2018-04-01

To evaluate an accelerated 4D flow MRI method that provides high temporal resolution in a clinically feasible acquisition time for intracranial velocity imaging. Accelerated 4D flow MRI was developed by using a pseudo-random variable-density Cartesian undersampling strategy (CIRCUS) with the combination of k-t, parallel imaging and compressed sensing image reconstruction techniques (k-t SPARSE-SENSE). Four-dimensional flow data were acquired on five healthy volunteers and eight patients with intracranial aneurysms using CIRCUS (acceleration factor of R = 4, termed CIRCUS4) and GRAPPA (R = 2, termed GRAPPA2) as the reference method. Images with three times higher temporal resolution (R = 12, CIRCUS12) were also reconstructed from the same acquisition as CIRCUS4. Qualitative and quantitative image assessment was performed on the images acquired with different methods, and complex flow patterns in the aneurysms were identified and compared. Four-dimensional flow MRI with CIRCUS was achieved in 5 min and allowed further improved temporal resolution of <30 ms. Volunteer studies showed similar qualitative and quantitative evaluation obtained with the proposed approach compared to the reference (overall image scores: GRAPPA2 3.2 ± 0.6; CIRCUS4 3.1 ± 0.7; CIRCUS12 3.3 ± 0.4; difference of the peak velocities: -3.83 ± 7.72 cm/s between CIRCUS4 and GRAPPA2, -1.72 ± 8.41 cm/s between CIRCUS12 and GRAPPA2). In patients with intracranial aneurysms, the higher temporal resolution improved capturing of the flow features in intracranial aneurysms (pathline visualization scores: GRAPPA2 2.2 ± 0.2; CIRCUS4 2.5 ± 0.5; CIRCUS12 2.7 ± 0.6). The proposed rapid 4D flow MRI with a high temporal resolution is a promising tool for evaluating intracranial aneurysms in a clinically feasible acquisition time.

Estimating Gross Primary Production in Cropland with High Spatial and Temporal Scale Remote Sensing Data

NASA Astrophysics Data System (ADS)

Lin, S.; Li, J.; Liu, Q.

2018-04-01

Satellite remote sensing data provide spatially continuous and temporally repetitive observations of land surfaces, and they have become increasingly important for monitoring large region of vegetation photosynthetic dynamic. But remote sensing data have their limitation on spatial and temporal scale, for example, higher spatial resolution data as Landsat data have 30-m spatial resolution but 16 days revisit period, while high temporal scale data such as geostationary data have 30-minute imaging period, which has lower spatial resolution (> 1 km). The objective of this study is to investigate whether combining high spatial and temporal resolution remote sensing data can improve the gross primary production (GPP) estimation accuracy in cropland. For this analysis we used three years (from 2010 to 2012) Landsat based NDVI data, MOD13 vegetation index product and Geostationary Operational Environmental Satellite (GOES) geostationary data as input parameters to estimate GPP in a small region cropland of Nebraska, US. Then we validated the remote sensing based GPP with the in-situ measurement carbon flux data. Results showed that: 1) the overall correlation between GOES visible band and in-situ measurement photosynthesis active radiation (PAR) is about 50 % (R2 = 0.52) and the European Center for Medium-Range Weather Forecasts ERA-Interim reanalysis data can explain 64 % of PAR variance (R2 = 0.64); 2) estimating GPP with Landsat 30-m spatial resolution data and ERA daily meteorology data has the highest accuracy(R2 = 0.85, RMSE < 3 gC/m2/day), which has better performance than using MODIS 1-km NDVI/EVI product import; 3) using daily meteorology data as input for GPP estimation in high spatial resolution data would have higher relevance than 8-day and 16-day input. Generally speaking, using the high spatial resolution and high frequency satellite based remote sensing data can improve GPP estimation accuracy in cropland.

Structural Controllability of Temporal Networks with a Single Switching Controller

PubMed Central

Yao, Peng; Hou, Bao-Yu; Pan, Yu-Jian; Li, Xiang

2017-01-01

Temporal network, whose topology evolves with time, is an important class of complex networks. Temporal trees of a temporal network describe the necessary edges sustaining the network as well as their active time points. By a switching controller which properly selects its location with time, temporal trees are used to improve the controllability of the network. Therefore, more nodes are controlled within the limited time. Several switching strategies to efficiently select the location of the controller are designed, which are verified with synthetic and empirical temporal networks to achieve better control performance. PMID:28107538

Using Spatial-Temporal Primitives to Improve Geographic Skills for Preservice Teachers

ERIC Educational Resources Information Center

Kaufman, Martin M.

2004-01-01

An exercise to help improve the geographic skills of preservice teachers was developed and tested during a six year period on over 500 students. The exercise required these students to map two arrangements of roads and facilities within a small neighborhood. A set of special-temporal primitives (place, size, shape, distance, direction,…

Monitoring cotton root rot by synthetic Sentinel-2 NDVI time series using improved spatial and temporal data fusion

USDA-ARS?s Scientific Manuscript database

Airborne imagery has been successfully used for mapping cotton root rot within cotton fields toward the end of the growing season. To better understand the progression of cotton root rot within the season, time series monitoring is required. In this study, an improved spatial and temporal data fusio...

Spatial attention does improve temporal discrimination.

PubMed

Chica, Ana B; Christie, John

2009-02-01

It has recently been stated that exogenous attention impairs temporal-resolution tasks (Hein, Rolke, & Ulrich, 2006; Rolke, Dinkelbach, Hein, & Ulrich, 2008; Yeshurun, 2004; Yeshurun & Levy, 2003). In comparisons of performance on spatially cued trials versus neutral cued trials, the results have suggested that spatial attention decreases temporal resolution. However, when performance on cued and uncued trials has been compared in order to equate for cue salience, typically speed-accuracy trade-offs (SATs) have been observed, making the interpretation of the results difficult. In the present experiments, we aimed at studying the effect of spatial attention in temporal resolution while using a procedure to control for SATs. We controlled reaction times (RTs) by constraining the time to respond, so that response decisions would be made within comparable time windows. The results revealed that when RT was controlled, performance was impaired for cued trials as compared with neutral trials, replicating previous findings. However, when cued and uncued trials were compared, performance was actually improved for cued trials as compared with uncued trials. These results suggest that SAT effects may have played an important role in the previous studies, because when they were controlled and measured, the results reversed, revealing that exogenous attention does improve performance on temporal-resolution tasks.

Decrease in gamma-band activity tracks sequence learning

PubMed Central

Madhavan, Radhika; Millman, Daniel; Tang, Hanlin; Crone, Nathan E.; Lenz, Fredrick A.; Tierney, Travis S.; Madsen, Joseph R.; Kreiman, Gabriel; Anderson, William S.

2015-01-01

Learning novel sequences constitutes an example of declarative memory formation, involving conscious recall of temporal events. Performance in sequence learning tasks improves with repetition and involves forming temporal associations over scales of seconds to minutes. To further understand the neural circuits underlying declarative sequence learning over trials, we tracked changes in intracranial field potentials (IFPs) recorded from 1142 electrodes implanted throughout temporal and frontal cortical areas in 14 human subjects, while they learned the temporal-order of multiple sequences of images over trials through repeated recall. We observed an increase in power in the gamma frequency band (30–100 Hz) in the recall phase, particularly in areas within the temporal lobe including the parahippocampal gyrus. The degree of this gamma power enhancement decreased over trials with improved sequence recall. Modulation of gamma power was directly correlated with the improvement in recall performance. When presenting new sequences, gamma power was reset to high values and decreased again after learning. These observations suggest that signals in the gamma frequency band may play a more prominent role during the early steps of the learning process rather than during the maintenance of memory traces. PMID:25653598

The Advanced Pair Telescope (APT) Mission Concept

NASA Technical Reports Server (NTRS)

Hunter, Stanley; Buckley, James H.

2008-01-01

We present a mission concept for the Advanced Pair Telescope (APT), a high-energy gamma-ray instrument with an order of magnitude improvement in sensitivity, 6 sr field of view, and angular resolution a factor of 3-10 times that of GLAST. With its very wide instantaneous field-of-view and large effective area, this instrument would be capable of detecting GRBs at very large redshifts, would enable a very high resolution study of SNRs and PWN, and could provide hour-scale temporal resolution of transients from many AGN and galactic sources. The APT instrument will consist of a Xe time-projection-chamber tracker that bridges the energy regime between Compton scattering and pair production and will provide an unprecedented improvement in angular resolution; a thick scintillating-fiber trackerlcalorimeter that will provide sensitivity and energy resolution to higher energies and will possess a factor of 10 improvement in geometric factor over GLAST; and an anticoincidence detector using scintillator-tiles to reject charged particles. After the anticipated 10-years of GLAST operation , the APT instrument would provide continued coverage of the critial high-energy gamma-ray band (between 30 MeV to 100 GeV), providing an essential component of broad-band multiwavelength studies of the high-energy universe.

Analysing the Advantages of High Temporal Resolution Geostationary MSG SEVIRI Data Compared to Polar Operational Environmental Satellite Data for Land Surface Monitoring in Africa

NASA Technical Reports Server (NTRS)

Fensholt, R.; Anyamba, A.; Huber, S.; Proud, S. R.; Tucker, C. J.; Small, J.; Pak, E.; Rasmussen, M. O.; Sandholt, I.; Shisanya, C.

2011-01-01

Since 1972, satellite remote sensing of the environment has been dominated by polar-orbiting sensors providing useful data for monitoring the earth s natural resources. However their observation and monitoring capacity are inhibited by daily to monthly looks for any given ground surface which often is obscured by frequent and persistent cloud cover creating large gaps in time series measurements. The launch of the Meteosat Second Generation (MSG) satellite into geostationary orbit has opened new opportunities for land surface monitoring. The Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument on-board MSG with an imaging capability every 15 minutes which is substantially greater than any temporal resolution that can be obtained from existing polar operational environmental satellites (POES) systems currently in use for environmental monitoring. Different areas of the African continent were affected by droughts and floods in 2008 caused by periods of abnormally low and high rainfall, respectively. Based on the effectiveness of monitoring these events from Earth Observation (EO) data the current analyses show that the new generation of geostationary remote sensing data can provide higher temporal resolution cloud-free (less than 5 days) measurements of the environment as compared to existing POES systems. SEVIRI MSG 5-day continental scale composites will enable rapid assessment of environmental conditions and improved early warning of disasters for the African continent such as flooding or droughts. The high temporal resolution geostationary data will complement existing higher spatial resolution polar-orbiting satellite data for various dynamic environmental and natural resource applications of terrestrial ecosystems.

Multiscale temporal variability and regional patterns in 555 years of conterminous U.S. streamflow

NASA Astrophysics Data System (ADS)

Ho, Michelle; Lall, Upmanu; Sun, Xun; Cook, Edward R.

2017-04-01

The development of paleoclimate streamflow reconstructions in the conterminous United States (CONUS) has provided water resource managers with improved insights into multidecadal and centennial scale variability that cannot be reliably detected using shorter instrumental records. Paleoclimate streamflow reconstructions have largely focused on individual catchments limiting the ability to quantify variability across the CONUS. The Living Blended Drought Atlas (LBDA), a spatially and temporally complete 555 year long paleoclimate record of summer drought across the CONUS, provides an opportunity to reconstruct and characterize streamflow variability at a continental scale. We explore the validity of the first paleoreconstructions of streamflow that span the CONUS informed by the LBDA targeting a set of U.S. Geological Survey streamflow sites. The reconstructions are skillful under cross validation across most of the country, but the variance explained is generally low. Spatial and temporal structures of streamflow variability are analyzed using hierarchical clustering, principal component analysis, and wavelet analyses. Nine spatially coherent clusters are identified. The reconstructions show signals of contemporary droughts such as the Dust Bowl (1930s) and 1950s droughts. Decadal-scale variability was detected in the late 1900s in the western U.S., however, similar modes of temporal variability were rarely present prior to the 1950s. The twentieth century featured longer wet spells and shorter dry spells compared with the preceding 450 years. Streamflows in the Pacific Northwest and Northeast are negatively correlated with the central U.S. suggesting the potential to mitigate some drought impacts by balancing economic activities and insurance pools across these regions during major droughts.

Temporal lobe structures and facial emotion recognition in schizophrenia patients and nonpsychotic relatives.

PubMed

Goghari, Vina M; Macdonald, Angus W; Sponheim, Scott R

2011-11-01

Temporal lobe abnormalities and emotion recognition deficits are prominent features of schizophrenia and appear related to the diathesis of the disorder. This study investigated whether temporal lobe structural abnormalities were associated with facial emotion recognition deficits in schizophrenia and related to genetic liability for the disorder. Twenty-seven schizophrenia patients, 23 biological family members, and 36 controls participated. Several temporal lobe regions (fusiform, superior temporal, middle temporal, amygdala, and hippocampus) previously associated with face recognition in normative samples and found to be abnormal in schizophrenia were evaluated using volumetric analyses. Participants completed a facial emotion recognition task and an age recognition control task under time-limited and self-paced conditions. Temporal lobe volumes were tested for associations with task performance. Group status explained 23% of the variance in temporal lobe volume. Left fusiform gray matter volume was decreased by 11% in patients and 7% in relatives compared with controls. Schizophrenia patients additionally exhibited smaller hippocampal and middle temporal volumes. Patients were unable to improve facial emotion recognition performance with unlimited time to make a judgment but were able to improve age recognition performance. Patients additionally showed a relationship between reduced temporal lobe gray matter and poor facial emotion recognition. For the middle temporal lobe region, the relationship between greater volume and better task performance was specific to facial emotion recognition and not age recognition. Because schizophrenia patients exhibited a specific deficit in emotion recognition not attributable to a generalized impairment in face perception, impaired emotion recognition may serve as a target for interventions.

Dynamic CT perfusion imaging of the myocardium: a technical note on improvement of image quality.

PubMed

Muenzel, Daniela; Kabus, Sven; Gramer, Bettina; Leber, Vivian; Vembar, Mani; Schmitt, Holger; Wildgruber, Moritz; Fingerle, Alexander A; Rummeny, Ernst J; Huber, Armin; Noël, Peter B

2013-01-01

To improve image and diagnostic quality in dynamic CT myocardial perfusion imaging (MPI) by using motion compensation and a spatio-temporal filter. Dynamic CT MPI was performed using a 256-slice multidetector computed tomography scanner (MDCT). Data from two different patients-with and without myocardial perfusion defects-were evaluated to illustrate potential improvements for MPI (institutional review board approved). Three datasets for each patient were generated: (i) original data (ii) motion compensated data and (iii) motion compensated data with spatio-temporal filtering performed. In addition to the visual assessment of the tomographic slices, noise and contrast-to-noise-ratio (CNR) were measured for all data. Perfusion analysis was performed using time-density curves with regions-of-interest (ROI) placed in normal and hypoperfused myocardium. Precision in definition of normal and hypoperfused areas was determined in corresponding coloured perfusion maps. The use of motion compensation followed by spatio-temporal filtering resulted in better alignment of the cardiac volumes over time leading to a more consistent perfusion quantification and improved detection of the extend of perfusion defects. Additionally image noise was reduced by 78.5%, with CNR improvements by a factor of 4.7. The average effective radiation dose estimate was 7.1±1.1 mSv. The use of motion compensation and spatio-temporal smoothing will result in improved quantification of dynamic CT MPI using a latest generation CT scanner.

Training in rapid auditory processing ameliorates auditory comprehension in aphasic patients: a randomized controlled pilot study.

PubMed

Szelag, Elzbieta; Lewandowska, Monika; Wolak, Tomasz; Seniow, Joanna; Poniatowska, Renata; Pöppel, Ernst; Szymaszek, Aneta

2014-03-15

Experimental studies have often reported close associations between rapid auditory processing and language competency. The present study was aimed at improving auditory comprehension in aphasic patients following specific training in the perception of temporal order (TO) of events. We tested 18 aphasic patients showing both comprehension and TO perception deficits. Auditory comprehension was assessed by the Token Test, phonemic awareness and Voice-Onset-Time Test. The TO perception was assessed using auditory Temporal-Order-Threshold, defined as the shortest interval between two consecutive stimuli, necessary to report correctly their before-after relation. Aphasic patients participated in eight 45-minute sessions of either specific temporal training (TT, n=11) aimed to improve sequencing abilities, or control non-temporal training (NT, n=7) focussed on volume discrimination. The TT yielded improved TO perception; moreover, a transfer of improvement was observed from the time domain to the language domain, which was untrained during the training. The NT did not improve either the TO perception or comprehension in any language test. These results are in agreement with previous literature studies which proved ameliorated language competency following the TT in language-learning-impaired or dyslexic children. Our results indicated for the first time such benefits also in aphasic patients. Copyright © 2013 Elsevier B.V. All rights reserved.

Blind identification of full-field vibration modes of output-only structures from uniformly-sampled, possibly temporally-aliased (sub-Nyquist), video measurements

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

Yang, Yongchao; Dorn, Charles; Mancini, Tyler

Enhancing the spatial and temporal resolution of vibration measurements and modal analysis could significantly benefit dynamic modelling, analysis, and health monitoring of structures. For example, spatially high-density mode shapes are critical for accurate vibration-based damage localization. In experimental or operational modal analysis, higher (frequency) modes, which may be outside the frequency range of the measurement, contain local structural features that can improve damage localization as well as the construction and updating of the modal-based dynamic model of the structure. In general, the resolution of vibration measurements can be increased by enhanced hardware. Traditional vibration measurement sensors such as accelerometers havemore » high-frequency sampling capacity; however, they are discrete point-wise sensors only providing sparse, low spatial sensing resolution measurements, while dense deployment to achieve high spatial resolution is expensive and results in the mass-loading effect and modification of structure's surface. Non-contact measurement methods such as scanning laser vibrometers provide high spatial and temporal resolution sensing capacity; however, they make measurements sequentially that requires considerable acquisition time. As an alternative non-contact method, digital video cameras are relatively low-cost, agile, and provide high spatial resolution, simultaneous, measurements. Combined with vision based algorithms (e.g., image correlation or template matching, optical flow, etc.), video camera based measurements have been successfully used for experimental and operational vibration measurement and subsequent modal analysis. However, the sampling frequency of most affordable digital cameras is limited to 30–60 Hz, while high-speed cameras for higher frequency vibration measurements are extremely costly. This work develops a computational algorithm capable of performing vibration measurement at a uniform sampling frequency lower than what is required by the Shannon-Nyquist sampling theorem for output-only modal analysis. In particular, the spatio-temporal uncoupling property of the modal expansion of structural vibration responses enables a direct modal decoupling of the temporally-aliased vibration measurements by existing output-only modal analysis methods, yielding (full-field) mode shapes estimation directly. Then the signal aliasing properties in modal analysis is exploited to estimate the modal frequencies and damping ratios. Furthermore, the proposed method is validated by laboratory experiments where output-only modal identification is conducted on temporally-aliased acceleration responses and particularly the temporally-aliased video measurements of bench-scale structures, including a three-story building structure and a cantilever beam.« less

Blind identification of full-field vibration modes of output-only structures from uniformly-sampled, possibly temporally-aliased (sub-Nyquist), video measurements

DOE PAGES

Yang, Yongchao; Dorn, Charles; Mancini, Tyler; ...

2016-12-05

Enhancing the spatial and temporal resolution of vibration measurements and modal analysis could significantly benefit dynamic modelling, analysis, and health monitoring of structures. For example, spatially high-density mode shapes are critical for accurate vibration-based damage localization. In experimental or operational modal analysis, higher (frequency) modes, which may be outside the frequency range of the measurement, contain local structural features that can improve damage localization as well as the construction and updating of the modal-based dynamic model of the structure. In general, the resolution of vibration measurements can be increased by enhanced hardware. Traditional vibration measurement sensors such as accelerometers havemore » high-frequency sampling capacity; however, they are discrete point-wise sensors only providing sparse, low spatial sensing resolution measurements, while dense deployment to achieve high spatial resolution is expensive and results in the mass-loading effect and modification of structure's surface. Non-contact measurement methods such as scanning laser vibrometers provide high spatial and temporal resolution sensing capacity; however, they make measurements sequentially that requires considerable acquisition time. As an alternative non-contact method, digital video cameras are relatively low-cost, agile, and provide high spatial resolution, simultaneous, measurements. Combined with vision based algorithms (e.g., image correlation or template matching, optical flow, etc.), video camera based measurements have been successfully used for experimental and operational vibration measurement and subsequent modal analysis. However, the sampling frequency of most affordable digital cameras is limited to 30–60 Hz, while high-speed cameras for higher frequency vibration measurements are extremely costly. This work develops a computational algorithm capable of performing vibration measurement at a uniform sampling frequency lower than what is required by the Shannon-Nyquist sampling theorem for output-only modal analysis. In particular, the spatio-temporal uncoupling property of the modal expansion of structural vibration responses enables a direct modal decoupling of the temporally-aliased vibration measurements by existing output-only modal analysis methods, yielding (full-field) mode shapes estimation directly. Then the signal aliasing properties in modal analysis is exploited to estimate the modal frequencies and damping ratios. Furthermore, the proposed method is validated by laboratory experiments where output-only modal identification is conducted on temporally-aliased acceleration responses and particularly the temporally-aliased video measurements of bench-scale structures, including a three-story building structure and a cantilever beam.« less

Object Segmentation from Motion Discontinuities and Temporal Occlusions–A Biologically Inspired Model

PubMed Central

Beck, Cornelia; Ognibeni, Thilo; Neumann, Heiko

2008-01-01

Background Optic flow is an important cue for object detection. Humans are able to perceive objects in a scene using only kinetic boundaries, and can perform the task even when other shape cues are not provided. These kinetic boundaries are characterized by the presence of motion discontinuities in a local neighbourhood. In addition, temporal occlusions appear along the boundaries as the object in front covers the background and the objects that are spatially behind it. Methodology/Principal Findings From a technical point of view, the detection of motion boundaries for segmentation based on optic flow is a difficult task. This is due to the problem that flow detected along such boundaries is generally not reliable. We propose a model derived from mechanisms found in visual areas V1, MT, and MSTl of human and primate cortex that achieves robust detection along motion boundaries. It includes two separate mechanisms for both the detection of motion discontinuities and of occlusion regions based on how neurons respond to spatial and temporal contrast, respectively. The mechanisms are embedded in a biologically inspired architecture that integrates information of different model components of the visual processing due to feedback connections. In particular, mutual interactions between the detection of motion discontinuities and temporal occlusions allow a considerable improvement of the kinetic boundary detection. Conclusions/Significance A new model is proposed that uses optic flow cues to detect motion discontinuities and object occlusion. We suggest that by combining these results for motion discontinuities and object occlusion, object segmentation within the model can be improved. This idea could also be applied in other models for object segmentation. In addition, we discuss how this model is related to neurophysiological findings. The model was successfully tested both with artificial and real sequences including self and object motion. PMID:19043613

LACIE analyst interpretation keys

NASA Technical Reports Server (NTRS)

Baron, J. G.; Payne, R. W.; Palmer, W. F. (Principal Investigator)

1979-01-01

Two interpretation aids, 'The Image Analysis Guide for Wheat/Small Grains Inventories' and 'The United States and Canadian Great Plains Regional Keys', were developed during LACIE phase 2 and implemented during phase 3 in order to provide analysts with a better understanding of the expected ranges in color variation of signatures for individual biostages and of the temporal sequences of LANDSAT signatures. The keys were tested using operational LACIE data, and the results demonstrate that their use provides improved labeling accuracy in all analyst experience groupings, in all geographic areas within the U.S. Great Plains, and during all periods of crop development.

Dynamics of resilience of wheat to drought in Australia from 1991-2010.

PubMed

Huai, Jianjun

2017-08-25

Although enhancing resilience is a well-recognized adaptation to climate change, little research has been undertaken on the dynamics of resilience. This occurs because complex relationships exist between adaptive capacity and resilience, and some issues also create challenges related to the construction, operation, and application of resilience. This study identified the dynamics of temporal, spatial changes of resilience found in a sample of wheat-drought resilience in Australia's wheat-sheep production zone during 1991-2010. I estimated resilience using principal component analysis, mapped resilience and its components, distinguished resilient and sensitive regions, and provided recommendations related to improving resilience. I frame that resilience is composed of social resilience including on- and off-site adaptive capacity as well as biophysical resilience including resistance and absorption. I found that resilience and its components have different temporal trends, spatial shifts and growth ratios in each region during different years, which results from complicated interactions, such as complementation and substitution among its components. In wheat-sheep zones, I recommend that identifying regional bottlenecks, science-policy engagement, and managing resilience components are the priorities for improving resilience.

Neural correlates of face gender discrimination learning.

PubMed

Su, Junzhu; Tan, Qingleng; Fang, Fang

2013-04-01

Using combined psychophysics and event-related potentials (ERPs), we investigated the effect of perceptual learning on face gender discrimination and probe the neural correlates of the learning effect. Human subjects were trained to perform a gender discrimination task with male or female faces. Before and after training, they were tested with the trained faces and other faces with the same and opposite genders. ERPs responding to these faces were recorded. Psychophysical results showed that training significantly improved subjects' discrimination performance and the improvement was specific to the trained gender, as well as to the trained identities. The training effect indicates that learning occurs at two levels-the category level (gender) and the exemplar level (identity). ERP analyses showed that the gender and identity learning was associated with the N170 latency reduction at the left occipital-temporal area and the N170 amplitude reduction at the right occipital-temporal area, respectively. These findings provide evidence for the facilitation model and the sharpening model on neuronal plasticity from visual experience, suggesting a faster processing speed and a sparser representation of face induced by perceptual learning.

Using Enhanced Grace Water Storage Data to Improve Drought Detection by the U.S. and North American Drought Monitors

NASA Technical Reports Server (NTRS)

Houborg, Rasmus; Rodell, Matthew; Lawrimore, Jay; Li, Bailing; Reichle, Rolf; Heim, Richard; Rosencrans, Matthew; Tinker, Rich; Famiglietti, James S.; Svoboda, Mark;

Voice gender discrimination provides a measure of more than pitch-related perception in cochlear implant users.

PubMed

Li, Tianhao; Fu, Qian-Jie

2011-08-01

(1) To investigate whether voice gender discrimination (VGD) could be a useful indicator of the spectral and temporal processing abilities of individual cochlear implant (CI) users; (2) To examine the relationship between VGD and speech recognition with CI when comparable acoustic cues are used for both perception processes. VGD was measured using two talker sets with different inter-gender fundamental frequencies (F(0)), as well as different acoustic CI simulations. Vowel and consonant recognition in quiet and noise were also measured and compared with VGD performance. Eleven postlingually deaf CI users. The results showed that (1) mean VGD performance differed for different stimulus sets, (2) VGD and speech recognition performance varied among individual CI users, and (3) individual VGD performance was significantly correlated with speech recognition performance under certain conditions. VGD measured with selected stimulus sets might be useful for assessing not only pitch-related perception, but also spectral and temporal processing by individual CI users. In addition to improvements in spectral resolution and modulation detection, the improvement in higher modulation frequency discrimination might be particularly important for CI users in noisy environments.

A hyper-temporal remote sensing protocol for high-resolution mapping of ecological sites

PubMed Central

Karl, Jason W.

2017-01-01

Ecological site classification has emerged as a highly effective land management framework, but its utility at a regional scale has been limited due to the spatial ambiguity of ecological site locations in the U.S. or the absence of ecological site maps in other regions of the world. In response to these shortcomings, this study evaluated the use of hyper-temporal remote sensing (i.e., hundreds of images) for high spatial resolution mapping of ecological sites. We posit that hyper-temporal remote sensing can provide novel insights into the spatial variability of ecological sites by quantifying the temporal response of land surface spectral properties. This temporal response provides a spectral ‘fingerprint’ of the soil-vegetation-climate relationship which is central to the concept of ecological sites. Consequently, the main objective of this study was to predict the spatial distribution of ecological sites in a semi-arid rangeland using a 28-year time series of normalized difference vegetation index from Landsat TM 5 data and modeled using support vector machine classification. Results from this study show that support vector machine classification using hyper-temporal remote sensing imagery was effective in modeling ecological site classes, with a 62% correct classification. These results were compared to Gridded Soil Survey Geographic database and expert delineated maps of ecological sites which had a 51 and 89% correct classification, respectively. An analysis of the effects of ecological state on ecological site misclassifications revealed that sites in degraded states (e.g., shrub-dominated/shrubland and bare/annuals) had a higher rate of misclassification due to their close spectral similarity with other ecological sites. This study identified three important factors that need to be addressed to improve future model predictions: 1) sampling designs need to fully represent the range of both within class (i.e., states) and between class (i.e., ecological sites) spectral variability through time, 2) field sampling protocols that accurately characterize key soil properties (e.g., texture, depth) need to be adopted, and 3) additional environmental covariates (e.g. terrain attributes) need to be evaluated that may help further differentiate sites with similar spectral signals. Finally, the proposed hyper-temporal remote sensing framework may provide a standardized approach to evaluate and test our ecological site concepts through examining differences in vegetation dynamics in response to climatic variability and other drivers of land-use change. Results from this study demonstrate the efficacy of the hyper-temporal remote sensing approach for high resolution mapping of ecological sites, and highlights its utility in terms of reduced cost and time investment relative to traditional manual mapping approaches. PMID:28414731

A hyper-temporal remote sensing protocol for high-resolution mapping of ecological sites.

PubMed

Maynard, Jonathan J; Karl, Jason W

2017-01-01

Ecological site classification has emerged as a highly effective land management framework, but its utility at a regional scale has been limited due to the spatial ambiguity of ecological site locations in the U.S. or the absence of ecological site maps in other regions of the world. In response to these shortcomings, this study evaluated the use of hyper-temporal remote sensing (i.e., hundreds of images) for high spatial resolution mapping of ecological sites. We posit that hyper-temporal remote sensing can provide novel insights into the spatial variability of ecological sites by quantifying the temporal response of land surface spectral properties. This temporal response provides a spectral 'fingerprint' of the soil-vegetation-climate relationship which is central to the concept of ecological sites. Consequently, the main objective of this study was to predict the spatial distribution of ecological sites in a semi-arid rangeland using a 28-year time series of normalized difference vegetation index from Landsat TM 5 data and modeled using support vector machine classification. Results from this study show that support vector machine classification using hyper-temporal remote sensing imagery was effective in modeling ecological site classes, with a 62% correct classification. These results were compared to Gridded Soil Survey Geographic database and expert delineated maps of ecological sites which had a 51 and 89% correct classification, respectively. An analysis of the effects of ecological state on ecological site misclassifications revealed that sites in degraded states (e.g., shrub-dominated/shrubland and bare/annuals) had a higher rate of misclassification due to their close spectral similarity with other ecological sites. This study identified three important factors that need to be addressed to improve future model predictions: 1) sampling designs need to fully represent the range of both within class (i.e., states) and between class (i.e., ecological sites) spectral variability through time, 2) field sampling protocols that accurately characterize key soil properties (e.g., texture, depth) need to be adopted, and 3) additional environmental covariates (e.g. terrain attributes) need to be evaluated that may help further differentiate sites with similar spectral signals. Finally, the proposed hyper-temporal remote sensing framework may provide a standardized approach to evaluate and test our ecological site concepts through examining differences in vegetation dynamics in response to climatic variability and other drivers of land-use change. Results from this study demonstrate the efficacy of the hyper-temporal remote sensing approach for high resolution mapping of ecological sites, and highlights its utility in terms of reduced cost and time investment relative to traditional manual mapping approaches.

Evaluating Climate Causation of Conflict in Darfur Using Multi-temporal, Multi-resolution Satellite Image Datasets With Novel Analyses

NASA Astrophysics Data System (ADS)

Brown, I.; Wennbom, M.

2013-12-01

Climate change, population growth and changes in traditional lifestyles have led to instabilities in traditional demarcations between neighboring ethic and religious groups in the Sahel region. This has resulted in a number of conflicts as groups resort to arms to settle disputes. Such disputes often centre on or are justified by competition for resources. The conflict in Darfur has been controversially explained by resource scarcity resulting from climate change. Here we analyse established methods of using satellite imagery to assess vegetation health in Darfur. Multi-decadal time series of observations are available using low spatial resolution visible-near infrared imagery. Typically normalized difference vegetation index (NDVI) analyses are produced to describe changes in vegetation ';greenness' or ';health'. Such approaches have been widely used to evaluate the long term development of vegetation in relation to climate variations across a wide range of environments from the Arctic to the Sahel. These datasets typically measure peak NDVI observed over a given interval and may introduce bias. It is furthermore unclear how the spatial organization of sparse vegetation may affect low resolution NDVI products. We develop and assess alternative measures of vegetation including descriptors of the growing season, wetness and resource availability. Expanding the range of parameters used in the analysis reduces our dependence on peak NDVI. Furthermore, these descriptors provide a better characterization of the growing season than the single NDVI measure. Using multi-sensor data we combine high temporal/moderate spatial resolution data with low temporal/high spatial resolution data to improve the spatial representativity of the observations and to provide improved spatial analysis of vegetation patterns. The approach places the high resolution observations in the NDVI context space using a longer time series of lower resolution imagery. The vegetation descriptors derived are evaluated using independent high spatial resolution datasets that reveal the pattern and health of vegetation at metre scales. We also use climate variables to support the interpretation of these data. We conclude that the spatio-temporal patterns in Darfur vegetation and climate datasets suggest that labelling the conflict a climate-change conflict is inaccurate and premature.

Reliability of MEG source imaging of anterior temporal spikes: analysis of an intracranially characterized spike focus.

PubMed

Wennberg, Richard; Cheyne, Douglas

2014-05-01

To assess the reliability of MEG source imaging (MSI) of anterior temporal spikes through detailed analysis of the localization and orientation of source solutions obtained for a large number of spikes that were separately confirmed by intracranial EEG to be focally generated within a single, well-characterized spike focus. MSI was performed on 64 identical right anterior temporal spikes from an anterolateral temporal neocortical spike focus. The effects of different volume conductors (sphere and realistic head model), removal of noise with low frequency filters (LFFs) and averaging multiple spikes were assessed in terms of the reliability of the source solutions. MSI of single spikes resulted in scattered dipole source solutions that showed reasonable reliability for localization at the lobar level, but only for solutions with a goodness-of-fit exceeding 80% using a LFF of 3 Hz. Reliability at a finer level of intralobar localization was limited. Spike averaging significantly improved the reliability of source solutions and averaging 8 or more spikes reduced dependency on goodness-of-fit and data filtering. MSI performed on topographically identical individual spikes from an intracranially defined classical anterior temporal lobe spike focus was limited by low reliability (i.e., scattered source solutions) in terms of fine, sublobar localization within the ipsilateral temporal lobe. Spike averaging significantly improved reliability. MSI performed on individual anterior temporal spikes is limited by low reliability. Reduction of background noise through spike averaging significantly improves the reliability of MSI solutions. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

The Transplantation of hBM-MSCs Increases Bone Neo-Formation and Preserves Hearing Function in the Treatment of Temporal Bone Defects - on the Experience of Two Month Follow Up.

PubMed

Školoudík, Lukáš; Chrobok, Viktor; Kočí, Zuzana; Popelář, Jiří; Syka, Josef; Laco, Jan; Filipová, Alžběta; Syková, Eva; Filip, Stanislav

2018-06-03

Temporal bone reconstruction is a persisting problem following middle ear cholesteatoma surgery. Seeking to advance the clinical transfer of stem cell therapy we attempted the reconstruction of temporal bone using a composite bioartificial graft based on a hydroxyapatite bone scaffold combined with human bone marrow-derived mesenchymal stromal cells (hBM-MSCs). The aim of this study was to evaluate the effect of the combined biomaterial on the healing of postoperative temporal bone defects and the preservation of physiological hearing functions in a guinea pig model. The treatment's effect could be observed at 1 and 2 months after implantation of the biomaterial, as opposed to the control group. The clinical evaluation of our results included animal survival, clinical signs of an inflammatory response, and exploration of the tympanic bulla. Osteogenesis, angiogenesis, and inflammation were evaluated by histopathological analyses, whereas hBM-MSCs survival was evaluated by immunofluorescence assays. Hearing capacity was evaluated by objective audiometric methods, i.e. auditory brainstem responses and otoacoustic emission. Our study shows that hBM-MSCs, in combination with hydroxyapatite scaffolds, improves the repair of bone defects providing a safe and effective alternative in their treatment following middle ear surgery due to cholesteatoma.

Application of the Karhunen-Loeve transform temporal image filter to reduce noise in real-time cardiac cine MRI

NASA Astrophysics Data System (ADS)

Ding, Yu; Chung, Yiu-Cho; Raman, Subha V.; Simonetti, Orlando P.

2009-06-01

Real-time dynamic magnetic resonance imaging (MRI) typically sacrifices the signal-to-noise ratio (SNR) to achieve higher spatial and temporal resolution. Spatial and/or temporal filtering (e.g., low-pass filtering or averaging) of dynamic images improves the SNR at the expense of edge sharpness. We describe the application of a temporal filter for dynamic MR image series based on the Karhunen-Loeve transform (KLT) to remove random noise without blurring stationary or moving edges and requiring no training data. In this paper, we present several properties of this filter and their effects on filter performance, and propose an automatic way to find the filter cutoff based on the autocorrelation of the eigenimages. Numerical simulation and in vivo real-time cardiac cine MR image series spanning multiple cardiac cycles acquired using multi-channel sensitivity-encoded MRI, i.e., parallel imaging, are used to validate and demonstrate these properties. We found that in this application, the noise standard deviation was reduced to 42% of the original with no apparent image blurring by using the proposed filter cutoff. Greater noise reduction can be achieved by increasing the length of the image series. This advantage of KLT filtering provides flexibility in the form of another scan parameter to trade for SNR.

Coherent diffractive imaging of time-evolving samples with improved temporal resolution

DOE PAGES

Ulvestad, A.; Tripathi, A.; Hruszkewycz, S. O.; ...

2016-05-19

Bragg coherent x-ray diffractive imaging is a powerful technique for investigating dynamic nanoscale processes in nanoparticles immersed in reactive, realistic environments. Its temporal resolution is limited, however, by the oversampling requirements of three-dimensional phase retrieval. Here, we show that incorporating the entire measurement time series, which is typically a continuous physical process, into phase retrieval allows the oversampling requirement at each time step to be reduced, leading to a subsequent improvement in the temporal resolution by a factor of 2-20 times. The increased time resolution will allow imaging of faster dynamics and of radiation-dose-sensitive samples. Furthermore, this approach, which wemore » call "chrono CDI," may find use in improving the time resolution in other imaging techniques.« less

Uncertainty assessment of PM2.5 contamination mapping using spatiotemporal sequential indicator simulations and multi-temporal monitoring data.

PubMed

Yang, Yong; Christakos, George; Huang, Wei; Lin, Chengda; Fu, Peihong; Mei, Yang

2016-04-12

Because of the rapid economic growth in China, many regions are subjected to severe particulate matter pollution. Thus, improving the methods of determining the spatiotemporal distribution and uncertainty of air pollution can provide considerable benefits when developing risk assessments and environmental policies. The uncertainty assessment methods currently in use include the sequential indicator simulation (SIS) and indicator kriging techniques. However, these methods cannot be employed to assess multi-temporal data. In this work, a spatiotemporal sequential indicator simulation (STSIS) based on a non-separable spatiotemporal semivariogram model was used to assimilate multi-temporal data in the mapping and uncertainty assessment of PM2.5 distributions in a contaminated atmosphere. PM2.5 concentrations recorded throughout 2014 in Shandong Province, China were used as the experimental dataset. Based on the number of STSIS procedures, we assessed various types of mapping uncertainties, including single-location uncertainties over one day and multiple days and multi-location uncertainties over one day and multiple days. A comparison of the STSIS technique with the SIS technique indicate that a better performance was obtained with the STSIS method.

Uncertainty assessment of PM2.5 contamination mapping using spatiotemporal sequential indicator simulations and multi-temporal monitoring data

NASA Astrophysics Data System (ADS)

Yang, Yong; Christakos, George; Huang, Wei; Lin, Chengda; Fu, Peihong; Mei, Yang

2016-04-01

Because of the rapid economic growth in China, many regions are subjected to severe particulate matter pollution. Thus, improving the methods of determining the spatiotemporal distribution and uncertainty of air pollution can provide considerable benefits when developing risk assessments and environmental policies. The uncertainty assessment methods currently in use include the sequential indicator simulation (SIS) and indicator kriging techniques. However, these methods cannot be employed to assess multi-temporal data. In this work, a spatiotemporal sequential indicator simulation (STSIS) based on a non-separable spatiotemporal semivariogram model was used to assimilate multi-temporal data in the mapping and uncertainty assessment of PM2.5 distributions in a contaminated atmosphere. PM2.5 concentrations recorded throughout 2014 in Shandong Province, China were used as the experimental dataset. Based on the number of STSIS procedures, we assessed various types of mapping uncertainties, including single-location uncertainties over one day and multiple days and multi-location uncertainties over one day and multiple days. A comparison of the STSIS technique with the SIS technique indicate that a better performance was obtained with the STSIS method.

Brief communication: Improved simulation of the present-day Greenland firn layer (1960-2016)

NASA Astrophysics Data System (ADS)

Ligtenberg, Stefan R. M.; Kuipers Munneke, Peter; Noël, Brice P. Y.; van den Broeke, Michiel R.

2018-05-01

By providing pore space for storage or refreezing of meltwater, the Greenland ice sheet firn layer strongly modulates runoff. Correctly representing the firn layer is therefore crucial for Greenland (surface) mass balance studies. Here, we present a simulation of the Greenland firn layer with the firn model IMAU-FDM forced by the latest output of the regional climate model RACMO2, version 2.3p2. In the percolation zone, much improved agreement is found with firn density and temperature observations. A full simulation of Greenland firn at high temporal (10 days) and spatial (11 km) resolution is available for the period 1960-2016.

Developing a Multicomponent Model of Nutritious Food Access and Related Implications for Community and Policy Practice.

PubMed

Freedman, Darcy A; Blake, Christine E; Liese, Angela D

2013-01-01

Access to nutritious foods is limited in disenfranchised communities in the United States. Policies are beginning to focus on improving nutritious food access in these contexts; yet, few theories are available to guide this work. We developed a conceptual model of nutritious food access based on the qualitative responses of food consumers in 2 different regions of the American South. Five domains (economic, service delivery, spatial-temporal, social, and personal) and related dimensions of nutritious food access were identified. The conceptual model provides practical guidance to researchers, policy makers, and practitioners working to improve nutritious food access in communities.

Improved Background Removal in Sounding Rocket Neutral Atom Imaging Data

NASA Astrophysics Data System (ADS)

Smith, M. R.; Rowland, D. E.

2017-12-01

The VISIONS sounding rocket, launched into a substorm on Feb 7, 2013 from Poker Flat, Alaska had a novel miniaturized energetic neutral atom (ENA) imager onboard. We present further analysis of the ENA data from this rocket flight, including improved removal of ultraviolet and electron contamination. In particular, the relative error source contributions due to geocoronal, auroral, and airglow UV, as well as energetic electrons from 10 eV to 3 keV were assessed. The resulting data provide a more clear understanding of the spatial and temporal variations of the ion populations that are energized to tens or hundreds of eV.

Developing a Multicomponent Model of Nutritious Food Access and Related Implications for Community and Policy Practice

PubMed Central

FREEDMAN, DARCY A.; BLAKE, CHRISTINE E.; LIESE, ANGELA D.

2014-01-01

Access to nutritious foods is limited in disenfranchised communities in the United States. Policies are beginning to focus on improving nutritious food access in these contexts; yet, few theories are available to guide this work. We developed a conceptual model of nutritious food access based on the qualitative responses of food consumers in 2 different regions of the American South. Five domains (economic, service delivery, spatial–temporal, social, and personal) and related dimensions of nutritious food access were identified. The conceptual model provides practical guidance to researchers, policy makers, and practitioners working to improve nutritious food access in communities. PMID:24563605

Cognitive improvement following repair of a basal encephalocele.

PubMed

Tulloch, Isabel; Palmer, Siobhan; Scott, Richard; Lozsadi, Dora; Martin, Andrew J

2018-06-01

We report the case of a 55-year-old woman presenting with progressive memory impairment secondary to a transsphenoidal encephalocele involving her dominant medial temporal lobe. Her clinical deterioration was accompanied by radiological progression in the encephalocele's size and associated encephalomalacia. Through a temporal craniotomy, her encephalocele was resected and the defect closed. Baseline neuropsychological assessment indicated global cognitive impairment, but post-operatively, she reported improved memory and concentration. Standardized assessment reflected an improvement in perceptual skills and an associated improved recall of a complex figure. This is the first case report to date of a patient's memory improving following treatment of a basal encephalocele.

Land science with Sentinel-2 and Sentinel-3 data series synergy

NASA Astrophysics Data System (ADS)

Moreno, Jose; Guanter, Luis; Alonso, Luis; Gomez, Luis; Amoros, Julia; Camps, Gustavo; Delegido, Jesus

2010-05-01

Although the GMES/Sentinel satellite series were primarily designed to provide observations for operational services and routine applications, there is a growing interest in the scientific community towards the usage of Sentinel data for more advanced and innovative science. Apart from the improved spatial and spectral capabilities, the availability of consistent time series covering a period of over 20 years opens possibilities never explored before, such as systematic data assimilation approaches exploiting the time-series concept, or the incorporation in the modelling approaches of processes covering time scales from weeks to decades. Sentinel-3 will provide continuity to current ENVISAT MERIS/AATSR capabilities. The results already derived from MERIS/AATRS will be more systematically exploited by using OLCI in synergy with SLST. Particularly innovative is the case of Sentinel-2, which is specifically designed for land applications. Built on a constellation of two satellites operating simultaneously to provide 5 days geometric revisit time, the Sentinel-2 system will providing global and systematic acquisitions with high spatial resolution and with a high revisit time tailored towards the needs of land monitoring. Apart from providing continuity to Landsat and SPOT time series, the Sentinel-2 Multi-Spectral Instrument (MSI) incorporates new narrow bands around the red-edge for improved retrievals of biophysical parameters. The limitations imposed by the need of a proper cloud screening and atmospheric corrections have represented a serious constraint in the past for optical data. The fact that both Sentinel-2 and 3 have dedicated bands to allow such needed corrections for optical data represents an important step towards a proper exploitation, guarantying consistent time series showing actual variability in land surface conditions without the artefacts introduced by the atmosphere. Expected operational products (such as Land Cover maps, Leaf Area Index, Fractional Vegetation Cover, Fraction of Absorbed Photosynthetically Active Radiation, and Leaf Chlorophyll and Water Contents), will be enhanced with new scientific applications. Higher level products will also be provided, by means of mosaicking, averaging, synthesising or compositing of spatially and temporally resampled data. A key element in the exploitation of the Sentinel series will be the adequate use of data synergy, which will open new possibilities for improved Land Models. This paper analyses in particular the possibilities offered by mosaicking and compositing information derived from Sentinel-2 observations in high spatial resolution to complement dense time series derived from Sentinel-3 data with more frequent coverage. Interpolation of gaps in high spatial resolution time series (from Sentinel-2 data) by using medium/low resolution data from Sentinel-3 (OLCI and SLSTR) is also a way of making series more temporally consistent with high spatial resolution. The primary goal of such temporal interpolation / spatial mosaicking techniques is to derive consistent surface reflectance data virtually for every date and geographical location, no matter the initial spatial/temporal coverage of the original data used to produce the composite. As a result, biophysical products can be derived in a more consistent way from the spectral information of Sentinel-3 data by making use of a description of surface heterogeneity derived from Sentinel-2 data. Using data from dedicated experiments (SEN2FLEX, CEFLES2, SEN3EXP), that include a large dataset of satellite and airborne data and of ground-based measurements of atmospheric and vegetation parameters, different techniques are tested, including empirical / statistical approaches that builds nonlinear regression by mapping spectra to a high dimensional space, up to model inversion / data assimilation scenarios. Exploitation of the temporal domain and spatial multi-scale domain becomes then a driver for the systematic exploitation of GMES/Sentinels data time series. This paper review current status, and identifies research priorities in such direction.

A case of temporal lobe epilepsy with improvement of clinical symptoms and single photon emission computed tomography findings after treatment with clonazepam.

PubMed

Ide, M; Mizukami, K; Suzuki, T; Shiraishi, H

2000-10-01

A 26-year-old female presented psychomotor seizures, deja vu and amnestic syndrome after meningitis at the age of 14 years. Repeated electroencephalograms (EEG) demonstrated occasional spikes localized in the right temporal region in addition to a considerable amount of theta waves mainly in the right fronto-temporal region. Single photon emission computed tomography (SPECT) showed a marked hypoperfusion corresponding to the region in which the EEG showed abnormal findings, although magnetic resonance imaging (MRI) demonstrated no abnormal findings associated with the clinical features. Treatment with clonazepam in addition to sodium valproate resulted in a remarkable improvement of clinical symptoms (i.e. psychomotor seizures and deja vu), as well as of the EEG and SPECT findings. The present study suggests that SPECT is a useful method not only to determine the localization of regions associated with temporal lobe epilepsy but also to evaluate the effect of treatment in temporal lobe epilepsy.

Identification of hydrological model parameter variation using ensemble Kalman filter

NASA Astrophysics Data System (ADS)

Deng, Chao; Liu, Pan; Guo, Shenglian; Li, Zejun; Wang, Dingbao

2016-12-01

Hydrological model parameters play an important role in the ability of model prediction. In a stationary context, parameters of hydrological models are treated as constants; however, model parameters may vary with time under climate change and anthropogenic activities. The technique of ensemble Kalman filter (EnKF) is proposed to identify the temporal variation of parameters for a two-parameter monthly water balance model (TWBM) by assimilating the runoff observations. Through a synthetic experiment, the proposed method is evaluated with time-invariant (i.e., constant) parameters and different types of parameter variations, including trend, abrupt change and periodicity. Various levels of observation uncertainty are designed to examine the performance of the EnKF. The results show that the EnKF can successfully capture the temporal variations of the model parameters. The application to the Wudinghe basin shows that the water storage capacity (SC) of the TWBM model has an apparent increasing trend during the period from 1958 to 2000. The identified temporal variation of SC is explained by land use and land cover changes due to soil and water conservation measures. In contrast, the application to the Tongtianhe basin shows that the estimated SC has no significant variation during the simulation period of 1982-2013, corresponding to the relatively stationary catchment properties. The evapotranspiration parameter (C) has temporal variations while no obvious change patterns exist. The proposed method provides an effective tool for quantifying the temporal variations of the model parameters, thereby improving the accuracy and reliability of model simulations and forecasts.

An improved approximate-Bayesian model-choice method for estimating shared evolutionary history

PubMed Central

2014-01-01

Background To understand biological diversification, it is important to account for large-scale processes that affect the evolutionary history of groups of co-distributed populations of organisms. Such events predict temporally clustered divergences times, a pattern that can be estimated using genetic data from co-distributed species. I introduce a new approximate-Bayesian method for comparative phylogeographical model-choice that estimates the temporal distribution of divergences across taxa from multi-locus DNA sequence data. The model is an extension of that implemented in msBayes. Results By reparameterizing the model, introducing more flexible priors on demographic and divergence-time parameters, and implementing a non-parametric Dirichlet-process prior over divergence models, I improved the robustness, accuracy, and power of the method for estimating shared evolutionary history across taxa. Conclusions The results demonstrate the improved performance of the new method is due to (1) more appropriate priors on divergence-time and demographic parameters that avoid prohibitively small marginal likelihoods for models with more divergence events, and (2) the Dirichlet-process providing a flexible prior on divergence histories that does not strongly disfavor models with intermediate numbers of divergence events. The new method yields more robust estimates of posterior uncertainty, and thus greatly reduces the tendency to incorrectly estimate models of shared evolutionary history with strong support. PMID:24992937

Understanding dynamic pattern and process across spatial scales in river systems using simultaneous deployments of in situ sensors

NASA Astrophysics Data System (ADS)

Wollheim, W. M.; Mulukutla, G.; Cook, C.; Carey, R. O.

2014-12-01

Biogeochemical conditions throughout aquatic landscapes are spatially varied and temporally dynamic due to interactions of upstream land use, climate, hydrologic responses, and internal aquatic processes. One of the key goals in aquatic ecosystem ecology is to parse the upstream influences of terrestrial and aquatic processes on local conditions, which becomes progressively more difficult as watershed size increases and as processes are altered by diverse human activities. Simultaneous deployments of high frequency, in situ aquatic sensors for multiple constituents (e.g. NO3-N, CDOM, turbidity, conductivity, D.O., water temperature, along with flow) offer a new approach for understanding patterns along the aquatic continuum. For this talk, we explore strategies for deployments within single watersheds to improve understanding of terrestrial and aquatic processes. We address applications regarding mobilization of non-point nutrient sources across temporal scales, interactions with land use and watershed size, and the importance of aquatic processes. We also explore ways in which simultaneous sensor deployments can be designed to improve parameterization and testing of river network biogeochemical models. We will provide several specific examples using conductivity, nitrate and carbon from ongoing sensor deployments in New England, USA. We expect that improved deployments of sensors and sensor networks will benefit the management of critical freshwater resources.

Direct current stimulation over the anterior temporal areas boosts semantic processing in primary progressive aphasia.

PubMed

Teichmann, Marc; Lesoil, Constance; Godard, Juliette; Vernet, Marine; Bertrand, Anne; Levy, Richard; Dubois, Bruno; Lemoine, Laurie; Truong, Dennis Q; Bikson, Marom; Kas, Aurélie; Valero-Cabré, Antoni

2016-11-01

Noninvasive brain stimulation in primary progressive aphasia (PPA) is a promising approach. Yet, applied to single cases or insufficiently controlled small-cohort studies, it has not clarified its therapeutic value. We here address the effectiveness of transcranial direct current stimulation (tDCS) on the semantic PPA variant (sv-PPA), applying a rigorous study design to a large, homogeneous sv-PPA cohort. Using a double-blind, sham-controlled counterbalanced cross-over design, we applied three tDCS conditions targeting the temporal poles of 12 sv-PPA patients. Efficiency was assessed by a semantic matching task orthogonally manipulating "living"/"nonliving" categories and verbal/visual modalities. Conforming to predominantly left-lateralized damage in sv-PPA and accounts of interhemispheric inhibition, we applied left hemisphere anodal-excitatory and right hemisphere cathodal-inhibitory tDCS, compared to sham stimulation. Prestimulation data, compared to 15 healthy controls, showed that patients had semantic disorders predominating with living categories in the verbal modality. Stimulation selectively impacted these most impaired domains: Left-excitatory and right-inhibitory tDCS improved semantic accuracy in verbal modality, and right-inhibitory tDCS improved processing speed with living categories and accuracy and processing speed in the combined verbal × living condition. Our findings demonstrate the efficiency of tDCS in sv-PPA by generating highly specific intrasemantic effects. They provide "proof of concept" for future applications of tDCS in therapeutic multiday regimes, potentially driving sustained improvement of semantic processing. Our data also support the hotly debated existence of a left temporal-pole network for verbal semantics selectively modulated through both left-excitatory and right-inhibitory brain stimulation. Ann Neurol 2016;80:693-707. © 2016 American Neurological Association.

High Temporal and Spatial Resolution Coverage of Earth from Commercial AVSTAR Systems in Geostationary Orbit

NASA Astrophysics Data System (ADS)

Lecompte, M. A.; Heaps, J. F.; Williams, F. H.

Imaging the earth from Geostationary Earth Orbit (GEO) allows frequent updates of environmental conditions within an observable hemisphere at time and spatial scales appropriate to the most transient observable terrestrial phenomena. Coverage provided by current GEO Meteorological Satellites (METSATS) fails to fully exploit this advantage due primarily to obsolescent technology and also institutional inertia. With the full benefit of GEO based imaging unrealized, rapidly evolving phenomena, occurring at the smallest spatial and temporal scales that frequently have significant environmental impact remain unobserved. These phenomena may be precursors for the most destructive natural processes that adversely effect society. Timely distribution of information derived from "real-time" observations thus may provide opportunities to mitigate much of the damage to life and property that would otherwise occur. AstroVision International's AVStar Earth monitoring system is designed to overcome the current limitations if GEO Earth coverage and to provide real time monitoring of changes to the Earth's complete atmospheric, land and marine surface environments including fires, volcanic events, lightning and meteoritic events on a "live," true color, and multispectral basis. The understanding of severe storm dynamics and its coupling to the earth's electro-sphere will be greatly enhanced by observations at unprecedented sampling frequencies and spatial resolution. Better understanding of these natural phenomena and AVStar operational real-time coverage may also benefit society through improvements in severe weather prediction and warning. AstroVision's AVStar system, designed to provide this capability with the first of a constellation of GEO- based commercial environmental monitoring satellites to be launched in late 2003 will be discussed, including spatial and temporal resolution, spectral coverage with applications and an inventory of the potential benefits to society, science, commerce and education.

Next Generation of Air Quality Measurements from Geo Orbits: Breaking The Temporal Barrier

NASA Astrophysics Data System (ADS)

Gupta, P.; Levy, R. C.; Mattoo, S.; Remer, L.; Heidinger, A.

2017-12-01

NASA's dark target (DT) aerosol algorithm provides operational retrieval of atmospheric aerosols from multiple polar orbiting satellites. The DT algorithm, initially developed for MODIS observations, has been continuously improved since the first MODIS launch in early 2000. Now, we are adapting the DT algorithm to retrieve on new-generation geostationary (GEO) sensors, including the Advanced Himawari Imager (AHI) on Japan's Himawari-8 (H8) satellite and Advanced Baseline Imager (ABI) on NOAA's GOES-16 (or GOES-R). H8 is a weather geostationary satellite operating since July 2015, and AHI observes earth-atmosphere system over the Asia-Pacific region at spatial resolutions of 1km or less. GOES-R is launched in Nov 2016 and provides high temporal resolution observations over Americas. With 16 spectral channels, including 7 bands that observe similar wavelengths as the MODIS bands used for DT aerosol retrieval. Most exciting, however, is that both ABI and AHI provides full disk observations every 10-15 minutes and zoom mode observations every 30 second to 2.5 minutes. Therefore, spectral, spatial and temporal resolution observations from these GEO satellites provide opportunity to monitor atmospheric aerosols in the region, plus a new capability to monitor aerosol transport and aerosol/cloud diurnal cycles. In this paper, we will introduce retrieval results from AHI using the DT algorithm during the KORUS-AQ field campaign during summer 2016. These results are evaluated against surface measurements (e.g. AERONET). . We will also discuss, its potential applications in monitoring diurnal cycles of urban pollution, smoke and dust in the region. The same DT algorithm will also be adapted to retrieve aerosol properties using GOES-16 over Americas.

Specification/Verification of Temporal Properties for Distributed Systems: Issues and Approaches. Volume 1

DTIC Science & Technology

1990-02-01

copies Pl ,...,P. of a multiple module fp resolve nondeterminism (local or global) in an identical manner. 5. The copies PI,...,P, axe physically...recovery block. A recovery block consists of a conventional block (like in ALGOL or PL /I) which is provided with a means of error detection, called an...improved failures model for communicating processes. In Proceeding. NSF- SERC Seminar on Concurrency, volume 197 of Lecture Notes in Computer Science

Temporal Changes in Left Ventricular Mechanics: Impact of Bed Rest and Exercise

NASA Technical Reports Server (NTRS)

Scott, J. M.; Downs, M.; Ploutz-Snyder, L. L.

2014-01-01

The use of more sensitive and specific echocardiographic techniques such as speckle tracking imaging may address the current limitations of conventional cardiac imaging techniques to provide insight into the extent and time course of cardiac deconditioning following spaceflight or headdown tilt bed rest (HDTBR). METHODS Speckle tracking assessment of longitudinal, radial, and circumferential strain and twist was used to evaluate the impact of 70 days of HDTBR (n=7) and HDTBR + exercise (n=11) on temporal changes in LV mechanics. Echocardiograms were performed pre (BR-2), during (BR31, 70), and following (BR+4hr) HDTBR. Repeated measures ANOVA was used to evaluate the effect of HDTBR on cardiac variables in control and exercise subjects. RESULTS After sedentary HDTBR, longitudinal (-19.0 +/- 1.8% vs. -14.9 +/- 2.4%) and radial (15.0 +/- 1.9% vs. 11.3 +/- 2.2%) strain and twist (18.0 +/- 4.0deg vs. 17.0 +/- 3.6deg) were significantly impaired. In contrast, exercise preserved LV mechanics, and there were non-significant improvements from BR-2 to BR70 in longitudinal strain (-18.7 +/- 1.5% vs. -20.4 +/- 2.7%), radial strain (13.2 +/- 2.4% vs. 14.2 +/- 1.6%), and twist (16.3 +/- 3.6deg vs. 18.6 +/- 5.9deg). CONCLUSIONS Using speckle tracking echocardiography provides important new insights into temporal changes in LV mechanics during disuse and exercise training.

Towards an integrated strategy for monitoring wetland inundation with virtual constellations of optical and radar satellites

NASA Astrophysics Data System (ADS)

DeVries, B.; Huang, W.; Huang, C.; Jones, J. W.; Lang, M. W.; Creed, I. F.; Carroll, M.

2017-12-01

The function of wetlandscapes in hydrological and biogeochemical cycles is largely governed by surface inundation, with small wetlands that experience periodic inundation playing a disproportionately large role in these processes. However, the spatial distribution and temporal dynamics of inundation in these wetland systems are still poorly understood, resulting in large uncertainties in global water, carbon and greenhouse gas budgets. Satellite imagery provides synoptic and repeat views of the Earth's surface and presents opportunities to fill this knowledge gap. Despite the proliferation of Earth Observation satellite missions in the past decade, no single satellite sensor can simultaneously provide the spatial and temporal detail needed to adequately characterize inundation in small, dynamic wetland systems. Surface water data products must therefore integrate observations from multiple satellite sensors in order to address this objective, requiring the development of improved and coordinated algorithms to generate consistent estimates of surface inundation. We present a suite of algorithms designed to detect surface inundation in wetlands using data from a virtual constellation of optical and radar sensors comprising the Landsat and Sentinel missions (DeVries et al., 2017). Both optical and radar algorithms were able to detect inundation in wetlands without the need for external training data, allowing for high-efficiency monitoring of wetland inundation at large spatial and temporal scales. Applying these algorithms across a gradient of wetlands in North America, preliminary findings suggest that while these fully automated algorithms can detect wetland inundation at higher spatial and temporal resolutions than currently available surface water data products, limitations specific to the satellite sensors and their acquisition strategies are responsible for uncertainties in inundation estimates. Further research is needed to investigate strategies for integrating optical and radar data from virtual constellations, with a focus on reducing uncertainties, maximizing spatial and temporal detail, and establishing consistent records of wetland inundation over time. The findings and conclusions in this article do not necessarily represent the views of the U.S. Government.

Singing can improve speech function in aphasics associated with intact right basal ganglia and preserve right temporal glucose metabolism: Implications for singing therapy indication.

PubMed

Akanuma, Kyoko; Meguro, Kenichi; Satoh, Masayuki; Tashiro, Manabu; Itoh, Masatoshi

2016-01-01

Clinically, we know that some aphasic patients can sing well despite their speech disturbances. Herein, we report 10 patients with non-fluent aphasia, of which half of the patients improved their speech function after singing training. We studied ten patients with non-fluent aphasia complaining of difficulty finding words. All had lesions in the left basal ganglia or temporal lobe. They selected the melodies they knew well, but which they could not sing. We made a new lyric with a familiar melody using words they could not name. The singing training using these new lyrics was performed for 30 minutes once a week for 10 weeks. Before and after the training, their speech functions were assessed by language tests. At baseline, 6 of them received positron emission tomography to evaluate glucose metabolism. Five patients exhibited improvements after intervention; all but one exhibited intact right basal ganglia and left temporal lobes, but all exhibited left basal ganglia lesions. Among them, three subjects exhibited preserved glucose metabolism in the right temporal lobe. We considered that patients who exhibit intact right basal ganglia and left temporal lobes, together with preserved right hemispheric glucose metabolism, might be an indication of the effectiveness of singing therapy.

Improving temporal resolution and speed sensitivity of laser speckle contrast analysis imaging based on noise reduction with an anisotropic diffusion filter

NASA Astrophysics Data System (ADS)

Song, Lipei; Wang, Xueyan; Zhang, Ru; Zhang, Kuanshou; Zhou, Zhen; Elson, Daniel S.

2018-07-01

The fluctuation of contrast caused by statistical noise degenerates the temporal/spatial resolution of laser speckle contrast imaging (LSCI) and limits the maximum speed when imaging. In this study, we investigated the application of the anisotropic diffusion filter (ADF) to temporal LSCI and found that the edge magnitude parameter of the ADF can be determined by the mean of the contrast image. Because the edge magnitude parameter is usually denoted as K, we term this the K-constant ADF (KC-ADF) and show that temporal sensitivity is improved when imaging because of the enhanced signal-to-noise ratio when using the KC-ADF in small-animal experiments. The cardiac cycle of a rat as high as 390 bpm can be imaged with an industrial camera.

RSS Fingerprint Based Indoor Localization Using Sparse Representation with Spatio-Temporal Constraint

PubMed Central

Piao, Xinglin; Zhang, Yong; Li, Tingshu; Hu, Yongli; Liu, Hao; Zhang, Ke; Ge, Yun

2016-01-01

The Received Signal Strength (RSS) fingerprint-based indoor localization is an important research topic in wireless network communications. Most current RSS fingerprint-based indoor localization methods do not explore and utilize the spatial or temporal correlation existing in fingerprint data and measurement data, which is helpful for improving localization accuracy. In this paper, we propose an RSS fingerprint-based indoor localization method by integrating the spatio-temporal constraints into the sparse representation model. The proposed model utilizes the inherent spatial correlation of fingerprint data in the fingerprint matching and uses the temporal continuity of the RSS measurement data in the localization phase. Experiments on the simulated data and the localization tests in the real scenes show that the proposed method improves the localization accuracy and stability effectively compared with state-of-the-art indoor localization methods. PMID:27827882

Mapping of CO2 at High Spatiotemporal Resolution using Satellite Observations: Global distributions from OCO-2

NASA Technical Reports Server (NTRS)

Hammerling, Dorit M.; Michalak, Anna M.; Kawa, S. Randolph

2012-01-01

Satellite observations of CO2 offer new opportunities to improve our understanding of the global carbon cycle. Using such observations to infer global maps of atmospheric CO2 and their associated uncertainties can provide key information about the distribution and dynamic behavior of CO2, through comparison to atmospheric CO2 distributions predicted from biospheric, oceanic, or fossil fuel flux emissions estimates coupled with atmospheric transport models. Ideally, these maps should be at temporal resolutions that are short enough to represent and capture the synoptic dynamics of atmospheric CO2. This study presents a geostatistical method that accomplishes this goal. The method can extract information about the spatial covariance structure of the CO2 field from the available CO2 retrievals, yields full coverage (Level 3) maps at high spatial resolutions, and provides estimates of the uncertainties associated with these maps. The method does not require information about CO2 fluxes or atmospheric transport, such that the Level 3 maps are informed entirely by available retrievals. The approach is assessed by investigating its performance using synthetic OCO-2 data generated from the PCTM/ GEOS-4/CASA-GFED model, for time periods ranging from 1 to 16 days and a target spatial resolution of 1deg latitude x 1.25deg longitude. Results show that global CO2 fields from OCO-2 observations can be predicted well at surprisingly high temporal resolutions. Even one-day Level 3 maps reproduce the large-scale features of the atmospheric CO2 distribution, and yield realistic uncertainty bounds. Temporal resolutions of two to four days result in the best performance for a wide range of investigated scenarios, providing maps at an order of magnitude higher temporal resolution relative to the monthly or seasonal Level 3 maps typically reported in the literature.

Exploiting COSMO-Skymed Data and Multi-Temporal Interferometry for Early Detection of Landslide Hazard: A Case of Slope Failure and Train Derailment Near Marina Di Andora, Italy.

NASA Astrophysics Data System (ADS)

Wasowski, J.; Chiaradia, M.; Bovenga, F.; Nutricato, R.; Nitti, D. O.; Milillo, G.; Guerriero, L.

2014-12-01

The improving temporal and spatial resolutions of new generation space-borne X-Band SAR sensors such as COSMO-SkyMed (CSK) constellation, and therefore their better monitoring capabilities, will guarantee increasing and more efficient use of multi-temporal interferometry (MTI) in landslide investigations. Thanks to their finer spatial resolution with respect to C-band data, X-band InSAR applications are very promising also for monitoring smaller landslides and single engineering structures sited on potentially unstable slopes. This work is focused on the detection of precursory signals of an impending slope failure from MTI time series of ground deformations obtained by exploiting 3 m resolution CSK data. We show the case of retrospectively captured pre-failure strains related to the landslide which occurred on January 2014 close to the town of Marina di Andora. The landslide caused the derailment of a train and the interruption of the railway line connecting north-western Italy to France. A dataset of 56 images acquired in STRIPMAP HIMAGE mode by CSK constellation from October 2008 to May 2014 was processed through SPINUA algorithm to derive the ground surface deformation map and the time series of displacement rates for each coherent radar target. We show that a cluster of moving targets coincides with the structures (buildings and terraces) affected by the 2014 landslide. The analysis of the MTI time series further shows that the targets had been moving since 2009, and thus could have provided a forewarning signal about ongoing slope or engineering structure instability. Although temporal landslide prediction remains difficult even via in situ monitoring, the presented case study indicates that MTI relying on high resolution radars such as CSK can provide very useful information for slope hazard mapping and possibly for early warning. Acknowledgments DIF provided contribution to data analysis within the framework of CAR-SLIDE project funded by MIUR (PON01_00536).

Rhythms can overcome temporal orienting deficit after right frontal damage.

PubMed

Triviño, Mónica; Arnedo, Marisa; Lupiáñez, Juan; Chirivella, Javier; Correa, Angel

2011-12-01

The main aim of this study was to test whether the use of rhythmic information to induce temporal expectations can overcome the deficit in controlled temporal preparation shown by patients with frontal damage (i.e. temporal orienting and foreperiod effects). Two tasks were administered to a group of 15 patients with a frontal brain lesion and a group of 15 matched control subjects: a Symbolic Cued Task where the predictive information regarding the time of target appearance was provided by a symbolic cue (short line-early vs. long line-late interval) and a Rhythm Cued Task where the predictive temporal information was provided by a rhythm (fast rhythm-early vs. slow rhythm-late interval). The results of the Symbolic Cued Task replicated both the temporal orienting deficit in right frontal patients and the absence of foreperiod effects in both right and left frontal patients, reported in our previous study (Triviño, Correa, Arnedo, & Lupiañez, 2010). However, in the Rhythm Cued Task, the right frontal group showed normal temporal orienting and foreperiod effects, while the left frontal group showed a significant deficit of both effects. These findings show that automatic temporal preparation, as induced by a rhythm, can help frontal patients to make effective use of implicit temporal information to respond at the optimum time. Our neuropsychological findings also provide a novel suggestion for a neural model, in which automatic temporal preparation is left-lateralized and controlled temporal preparation is right-lateralized in the frontal lobes. Copyright © 2011 Elsevier Ltd. All rights reserved.

Comparisons of aerosol optical depth provided by seviri satellite observations and CAMx air quality modelling

NASA Astrophysics Data System (ADS)

Fernandes, A.; Riffler, M.; Ferreira, J.; Wunderle, S.; Borrego, C.; Tchepel, O.

2015-04-01

Satellite data provide high spatial coverage and characterization of atmospheric components for vertical column. Additionally, the use of air pollution modelling in combination with satellite data opens the challenging perspective to analyse the contribution of different pollution sources and transport processes. The main objective of this work is to study the AOD over Portugal using satellite observations in combination with air pollution modelling. For this purpose, satellite data provided by Spinning Enhanced Visible and Infra-Red Imager (SEVIRI) on-board the geostationary Meteosat-9 satellite on AOD at 550 nm and modelling results from the Chemical Transport Model (CAMx - Comprehensive Air quality Model) were analysed. The study period was May 2011 and the aim was to analyse the spatial variations of AOD over Portugal. In this study, a multi-temporal technique to retrieve AOD over land from SEVIRI was used. The proposed method takes advantage of SEVIRI's high temporal resolution of 15 minutes and high spatial resolution. CAMx provides the size distribution of each aerosol constituent among a number of fixed size sections. For post processing, CAMx output species per size bin have been grouped into total particulate sulphate (PSO4), total primary and secondary organic aerosols (POA + SOA), total primary elemental carbon (PEC) and primary inert material per size bin (CRST1 to CRST_4) to be used in AOD quantification. The AOD was calculated by integration of aerosol extinction coefficient (Qext) on the vertical column. The results were analysed in terms of temporal and spatial variations. The analysis points out that the implemented methodology provides a good spatial agreement between modelling results and satellite observation for dust outbreak studied (10th -17th of May 2011). A correlation coefficient of r=0.79 was found between the two datasets. This work provides relevant background to start the integration of these two different types of the data in order to improve air pollution assessment.

Temporal binning of time-correlated single photon counting data improves exponential decay fits and imaging speed

PubMed Central

Walsh, Alex J.; Sharick, Joe T.; Skala, Melissa C.; Beier, Hope T.

2016-01-01

Time-correlated single photon counting (TCSPC) enables acquisition of fluorescence lifetime decays with high temporal resolution within the fluorescence decay. However, many thousands of photons per pixel are required for accurate lifetime decay curve representation, instrument response deconvolution, and lifetime estimation, particularly for two-component lifetimes. TCSPC imaging speed is inherently limited due to the single photon per laser pulse nature and low fluorescence event efficiencies (<10%) required to reduce bias towards short lifetimes. Here, simulated fluorescence lifetime decays are analyzed by SPCImage and SLIM Curve software to determine the limiting lifetime parameters and photon requirements of fluorescence lifetime decays that can be accurately fit. Data analysis techniques to improve fitting accuracy for low photon count data were evaluated. Temporal binning of the decays from 256 time bins to 42 time bins significantly (p<0.0001) improved fit accuracy in SPCImage and enabled accurate fits with low photon counts (as low as 700 photons/decay), a 6-fold reduction in required photons and therefore improvement in imaging speed. Additionally, reducing the number of free parameters in the fitting algorithm by fixing the lifetimes to known values significantly reduced the lifetime component error from 27.3% to 3.2% in SPCImage (p<0.0001) and from 50.6% to 4.2% in SLIM Curve (p<0.0001). Analysis of nicotinamide adenine dinucleotide–lactate dehydrogenase (NADH-LDH) solutions confirmed temporal binning of TCSPC data and a reduced number of free parameters improves exponential decay fit accuracy in SPCImage. Altogether, temporal binning (in SPCImage) and reduced free parameters are data analysis techniques that enable accurate lifetime estimation from low photon count data and enable TCSPC imaging speeds up to 6x and 300x faster, respectively, than traditional TCSPC analysis. PMID:27446663

Cholinergic enhancement reduces functional connectivity and BOLD variability in visual extrastriate cortex during selective attention

PubMed Central

Ricciardi, Emiliano; Handjaras, Giacomo; Bernardi, Giulio; Pietrini, Pietro; Furey, Maura L.

2012-01-01

Enhancing cholinergic function improves performance on various cognitive tasks and alters neural responses in task specific brain regions. Previous findings by our group strongly suggested that the changes in neural activity observed during increased cholinergic function may reflect an increase in neural efficiency that leads to improved task performance. The current study was designed to assess the effects of cholinergic enhancement on regional brain connectivity and BOLD signal variability. Nine subjects participated in a double-blind, placebo-controlled crossover functional magnetic resonance imaging (fMRI) study. Following an infusion of physostigmine (1mg/hr) or placebo, echo-planar imaging (EPI) was conducted as participants performed a selective attention task. During the task, two images comprised of superimposed pictures of faces and houses were presented. Subjects were instructed periodically to shift their attention from one stimulus component to the other and to perform a matching task using hand held response buttons. A control condition included phase-scrambled images of superimposed faces and houses that were presented in the same temporal and spatial manner as the attention task; participants were instructed to perform a matching task. Cholinergic enhancement improved performance during the selective attention task, with no change during the control task. Functional connectivity analyses showed that the strength of connectivity between ventral visual processing areas and task-related occipital, parietal and prefrontal regions was reduced significantly during cholinergic enhancement, exclusively during the selective attention task. Cholinergic enhancement also reduced BOLD signal temporal variability relative to placebo throughout temporal and occipital visual processing areas, again during the selective attention task only. Together with the observed behavioral improvement, the decreases in connectivity strength throughout task-relevant regions and BOLD variability within stimulus processing regions provide further support to the hypothesis that cholinergic augmentation results in enhanced neural efficiency. PMID:22906685

The ambiguity of drought events, a bottleneck for Amazon forest drought response modelling

NASA Astrophysics Data System (ADS)

De Deurwaerder, Hannes; Verbeeck, Hans; Baker, Timothy; Christoffersen, Bradley; Ciais, Philippe; Galbraith, David; Guimberteau, Matthieu; Kruijt, Bart; Langerwisch, Fanny; Meir, Patrick; Rammig, Anja; Thonicke, Kirsten; Von Randow, Celso; Zhang, Ke

2016-04-01

Considering the important role of the Amazon forest in the global water and carbon cycle, the prognosis of altered hydrological patterns resulting from climate change provides strong incentive for apprehending the direct implications of drought on the vegetation of this ecosystem. Dynamic global vegetation models have the potential of providing a useful tool to study drought impacts on various spatial and temporal scales. This however assumes the models being able to properly represent drought impact mechanisms. But how well do the models succeed in meeting this assumption? Within this study meteorological driver data and model output data of 4 different DGVMs, i.e. ORCHIDEE, JULES, INLAND and LPGmL, are studied. Using the palmer drought severity index (PDSI) and the mean cumulative water deficit (MWD), temporal and spatial representation of drought events are studied in the driver data and are referenced to historical extreme drought events in the Amazon. Subsequently, within the resulting temporal and spatial frame, we studied the drought impact on the above ground biomass (AGB) and gross primary production (GPP) fluxes. Flux tower data, field inventory data and the JUNG data-driven GPP product for the Amazon region are used for validation. Our findings not only suggest that the current state of the studied DGVMs is inadequate in representing Amazon droughts in general, but also highlights strong inter-model differences in drought responses. Using scatterplot-studies and input-output correlations, we provide insight in the origin of these encountered inter-model differences. In addition, we present directives of model development and improvement in scope of Amazon forest drought response modelling.

Quantitative MRI in refractory temporal lobe epilepsy: relationship with surgical outcomes

PubMed Central

Bonilha, Leonardo

2015-01-01

Medically intractable temporal lobe epilepsy (TLE) remains a serious health problem. Across treatment centers, up to 40% of patients with TLE will continue to experience persistent postoperative seizures at 2-year follow-up. It is unknown why such a large number of patients continue to experience seizures despite being suitable candidates for resective surgery. Preoperative quantitative MRI techniques may provide useful information on why some patients continue to experience disabling seizures, and may have the potential to develop prognostic markers of surgical outcome. In this article, we provide an overview of how quantitative MRI morphometric and diffusion tensor imaging (DTI) data have improved the understanding of brain structural alterations in patients with refractory TLE. We subsequently review the studies that have applied quantitative structural imaging techniques to identify the neuroanatomical factors that are most strongly related to a poor postoperative prognosis. In summary, quantitative imaging studies strongly suggest that TLE is a disorder affecting a network of neurobiological systems, characterized by multiple and inter-related limbic and extra-limbic network abnormalities. The relationship between brain alterations and postoperative outcome are less consistent, but there is emerging evidence suggesting that seizures are less likely to remit with surgery when presurgical abnormalities are observed in the connectivity supporting brain regions serving as network nodes located outside the resected temporal lobe. Future work, possibly harnessing the potential from multimodal imaging approaches, may further elucidate the etiology of persistent postoperative seizures in patients with refractory TLE. Furthermore, quantitative imaging techniques may be explored to provide individualized measures of postoperative seizure freedom outcome. PMID:25853080

General Temporal Knowledge for Planning and Data Mining

NASA Technical Reports Server (NTRS)

Morris, Robert; Khatib, Lina

2001-01-01

We consider the architecture of systems that combine temporal planning and plan execution and introduce a layer of temporal reasoning that potential1y improves both the communication between humans and such systems, and the performance of the temporal planner itself. In particular, this additional layer simultaneously supports more flexibility in specifying and maintaining temporal constraints on plans within an uncertain and changing execution environment, and the ability to understand and trace the progress of plan execution. It is shown how a representation based on single set of abstractions of temporal information can be used to characterize the reasoning underlying plan generation and execution interpretation. The complexity of such reasoning is discussed.

A Relational Encoding of a Conceptual Model with Multiple Temporal Dimensions

NASA Astrophysics Data System (ADS)

Gubiani, Donatella; Montanari, Angelo

The theoretical interest and the practical relevance of a systematic treatment of multiple temporal dimensions is widely recognized in the database and information system communities. Nevertheless, most relational databases have no temporal support at all. A few of them provide a limited support, in terms of temporal data types and predicates, constructors, and functions for the management of time values (borrowed from the SQL standard). One (resp., two) temporal dimensions are supported by historical and transaction-time (resp., bitemporal) databases only. In this paper, we provide a relational encoding of a conceptual model featuring four temporal dimensions, namely, the classical valid and transaction times, plus the event and availability times. We focus our attention on the distinctive technical features of the proposed temporal extension of the relation model. In the last part of the paper, we briefly show how to implement it in a standard DBMS.

Flood extent and water level estimation from SAR using data-model integration

NASA Astrophysics Data System (ADS)

Ajadi, O. A.; Meyer, F. J.

2017-12-01

Synthetic Aperture Radar (SAR) images have long been recognized as a valuable data source for flood mapping. Compared to other sources, SAR's weather and illumination independence and large area coverage at high spatial resolution supports reliable, frequent, and detailed observations of developing flood events. Accordingly, SAR has the potential to greatly aid in the near real-time monitoring of natural hazards, such as flood detection, if combined with automated image processing. This research works towards increasing the reliability and temporal sampling of SAR-derived flood hazard information by integrating information from multiple SAR sensors and SAR modalities (images and Interferometric SAR (InSAR) coherence) and by combining SAR-derived change detection information with hydrologic and hydraulic flood forecast models. First, the combination of multi-temporal SAR intensity images and coherence information for generating flood extent maps is introduced. The application of least-squares estimation integrates flood information from multiple SAR sensors, thus increasing the temporal sampling. SAR-based flood extent information will be combined with a Digital Elevation Model (DEM) to reduce false alarms and to estimate water depth and flood volume. The SAR-based flood extent map is assimilated into the Hydrologic Engineering Center River Analysis System (Hec-RAS) model to aid in hydraulic model calibration. The developed technology is improving the accuracy of flood information by exploiting information from data and models. It also provides enhanced flood information to decision-makers supporting the response to flood extent and improving emergency relief efforts.

Upscaling Ameriflux observations to assess drought impacts on gross primary productivity across the Southwest

NASA Astrophysics Data System (ADS)

Barnes, M.; Moore, D. J.; Scott, R. L.; MacBean, N.; Ponce-Campos, G. E.; Breshears, D. D.

2017-12-01

Both satellite observations and eddy covariance estimates provide crucial information about the Earth's carbon, water and energy cycles. Continuous measurements from flux towers facilitate exploration of the exchange of carbon dioxide, water and energy between the land surface and the atmosphere at fine temporal and spatial scales, while satellite observations can fill in the large spatial gaps of in-situ measurements and provide long-term temporal continuity. The Southwest (Southwest United States and Northwest Mexico) and other semi-arid regions represent a key uncertainty in interannual variability in carbon uptake. Comparisons of existing global upscaled gross primary production (GPP) products with flux tower data at sites across the Southwest show widespread mischaracterization of seasonality in vegetation carbon uptake, resulting in large (up to 200%) errors in annual carbon uptake estimates. Here, remotely sensed and distributed meteorological inputs are used to upscale GPP estimates from 25 Ameriflux towers across the Southwest to the regional scale using a machine learning approach. Our random forest model incorporates two novel features that improve the spatial and temporal variability in GPP. First, we incorporate a multi-scalar drought index at multiple timescales to account for differential seasonality between ecosystem types. Second, our machine learning algorithm was trained on twenty five ecologically diverse sites to optimize both the monthly variability in and the seasonal cycle of GPP. The product and its components will be used to examine drought impacts on terrestrial carbon cycling across the Southwest including the effects of drought seasonality and on carbon uptake. Our spatially and temporally continuous upscaled GPP product drawing from both ground and satellite data over the Southwest region helps us understand linkages between the carbon and water cycles in semi-arid ecosystems and informs predictions of vegetation response to future climate conditions.

The Influence of temporal sampling regime on the WFD classification of catchments within the Eden Demonstration Test Catchment Project

NASA Astrophysics Data System (ADS)

Jonczyk, Jennine; Haygarth, Phil; Quinn, Paul; Reaney, Sim

2014-05-01

A high temporal resolution data set from the Eden Demonstration Test Catchment (DTC) project is used to investigate the processes causing pollution and the influence of temporal sampling regime on the WFD classification of three catchments. This data highlights WFD standards may not be fit for purpose. The Eden DTC project is part of a UK government-funded project designed to provide robust evidence regarding how diffuse pollution can be cost-effectively controlled to improve and maintain water quality in rural river catchments. The impact of multiple water quality parameters on ecosystems and sustainable food production are being studied at the catchment scale. Three focus catchments approximately 10 km2 each, have been selected to represent the different farming practices and geophysical characteristics across the Eden catchment, Northern England. A field experimental programme has been designed to monitor the dynamics of agricultural diffuse pollution at multiple scales using state of the art sensors providing continuous real time data. The data set, which includes Total Phosphorus and Total Reactive Phosphorus, Nitrate, Ammonium, pH, Conductivity, Turbidity and Chlorophyll a reveals the frequency and duration of nutrient concentration target exceedance which arises from the prevalence of storm events of increasing magnitude. This data set is sub-sampled at different time intervals to explore how different sampling regimes affects our understanding of nutrient dynamics and the ramification of the different regimes to WFD chemical status. This presentation seeks to identify an optimum temporal resolution of data for effective catchment management and to question the usefulness of the WFD status metric for determining health of a system. Criteria based on high frequency short duration events needs to be accounted for.

Improved pattern scaling approaches for the use in climate impact studies

NASA Astrophysics Data System (ADS)

Herger, Nadja; Sanderson, Benjamin M.; Knutti, Reto

2015-05-01

Pattern scaling is a simple way to produce climate projections beyond the scenarios run with expensive global climate models (GCMs). The simplest technique has known limitations and assumes that a spatial climate anomaly pattern obtained from a GCM can be scaled by the global mean temperature (GMT) anomaly. We propose alternatives and assess their skills and limitations. One approach which avoids scaling is to consider a period in a different scenario with the same GMT change. It is attractive as it provides patterns of any temporal resolution that are consistent across variables, and it does not distort variability. Second, we extend the traditional approach with a land-sea contrast term, which provides the largest improvements over the traditional technique. When interpolating between known bounding scenarios, the proposed methods significantly improve the accuracy of the pattern scaled scenario with little computational cost. The remaining errors are much smaller than the Coupled Model Intercomparison Project Phase 5 model spread.

Central tendency effects in time interval reproduction in autism

PubMed Central

Karaminis, Themelis; Cicchini, Guido Marco; Neil, Louise; Cappagli, Giulia; Aagten-Murphy, David; Burr, David; Pellicano, Elizabeth

2016-01-01

Central tendency, the tendency of judgements of quantities (lengths, durations etc.) to gravitate towards their mean, is one of the most robust perceptual effects. A Bayesian account has recently suggested that central tendency reflects the integration of noisy sensory estimates with prior knowledge representations of a mean stimulus, serving to improve performance. The process is flexible, so prior knowledge is weighted more heavily when sensory estimates are imprecise, requiring more integration to reduce noise. In this study we measure central tendency in autism to evaluate a recent theoretical hypothesis suggesting that autistic perception relies less on prior knowledge representations than typical perception. If true, autistic children should show reduced central tendency than theoretically predicted from their temporal resolution. We tested autistic and age- and ability-matched typical children in two child-friendly tasks: (1) a time interval reproduction task, measuring central tendency in the temporal domain; and (2) a time discrimination task, assessing temporal resolution. Central tendency reduced with age in typical development, while temporal resolution improved. Autistic children performed far worse in temporal discrimination than the matched controls. Computational simulations suggested that central tendency was much less in autistic children than predicted by theoretical modelling, given their poor temporal resolution. PMID:27349722

Minimally invasive surgical approaches for temporal lobe epilepsy

PubMed Central

Chang, Edward F.; Englot, Dario J.; Vadera, Sumeet

2016-01-01

Surgery can be a highly effective treatment for medically refractory temporal lobe epilepsy (TLE). The emergence of minimally invasive resective and nonresective treatment options has led to interest in epilepsy surgery among patients and providers. Nevertheless, not all procedures are appropriate for all patients, and it is critical to consider seizure outcomes with each of these approaches, as seizure freedom is the greatest predictor of patient quality of life. Standard anterior temporal lobectomy (ATL) remains the gold standard in the treatment of TLE, with seizure freedom resulting in 60–80% of patients. It is currently the only resective epilepsy surgery supported by randomized controlled trials and offers the best protection against lateral temporal seizure onset. Selective amygdalohippocampectomy techniques preserve the lateral cortex and temporal stem to varying degrees and can result in favorable rates of seizure freedom but the risk of recurrent seizures appears slightly greater than with ATL, and it is not clear whether neuropsychological outcomes are improved with selective approaches. Stereotactic radiosurgery presents an opportunity to avoid surgery altogether, with seizure outcomes now under investigation. Stereotactic laser thermo-ablation allows destruction of the mesial temporal structures with low complication rates and minimal recovery time, and outcomes are also under study. Finally, while neuromodulatory devices such as responsive neurostimulation, vagus nerve stimulation, and deep brain stimulation have a role in the treatment of certain patients, these remain palliative procedures for those who are not candidates for resection or ablation, as complete seizure freedom rates are low. Further development and investigation of both established and novel strategies for the surgical treatment of TLE will be critical moving forward, given the significant burden of this disease. PMID:26017774

Performance of the Multi-Radar Multi-Sensor System over the Lower Colorado River, Texas

NASA Astrophysics Data System (ADS)

Bayabil, H. K.; Sharif, H. O.; Fares, A.; Awal, R.; Risch, E.

2017-12-01

Recently observed increases in intensities and frequencies of climate extremes (e.g., floods, dam failure, and overtopping of river banks) necessitate the development of effective disaster prevention and mitigation strategies. Hydrologic models can be useful tools in predicting such events at different spatial and temporal scales. However, accuracy and prediction capability of such models are often constrained by the availability of high-quality representative hydro-meteorological data (e.g., precipitation) that are required to calibrate and validate such models. Improved technologies and products such as the Multi-Radar Multi-Sensor (MRMS) system that allows gathering and transmission of vast meteorological data have been developed to provide such data needs. While the MRMS data are available with high spatial and temporal resolutions (1 km and 15 min, respectively), its accuracy in estimating precipitation is yet to be fully investigated. Therefore, the main objective of this study is to evaluate the performance of the MRMS system in effectively capturing precipitation over the Lower Colorado River, Texas using observations from a dense rain gauge network. In addition, effects of spatial and temporal aggregation scales on the performance of the MRMS system were evaluated. Point scale comparisons were made at 215 gauging locations using rain gauges and MRMS data from May 2015. Moreover, the effects of temporal and spatial data aggregation scales (30, 45, 60, 75, 90, 105, and 120 min) and (4 to 50 km), respectively on the performance of the MRMS system were tested. Overall, the MRMS system (at 15 min temporal resolution) captured precipitation reasonably well, with an average R2 value of 0.65 and RMSE of 0.5 mm. In addition, spatial and temporal data aggregations resulted in increases in R2 values. However, reduction in RMSE was achieved only with an increase in spatial aggregations.

From mobile ADCP to high-resolution SSC: a cross-section calibration tool

USGS Publications Warehouse

Boldt, Justin A.

2015-01-01

Sediment is a major cause of stream impairment, and improved sediment monitoring is a crucial need. Point samples of suspended-sediment concentration (SSC) are often not enough to provide an understanding to answer critical questions in a changing environment. As technology has improved, there now exists the opportunity to obtain discrete measurements of SSC and flux while providing a spatial scale unmatched by any other device. Acoustic instruments are ubiquitous in the U.S. Geological Survey (USGS) for making streamflow measurements but when calibrated with physical sediment samples, they may be used for sediment measurements as well. The acoustic backscatter measured by an acoustic Doppler current profiler (ADCP) has long been known to correlate well with suspended sediment, but until recently, it has mainly been qualitative in nature. This new method using acoustic surrogates has great potential to leverage the routine data collection to provide calibrated, quantitative measures of SSC which hold promise to be more accurate, complete, and cost efficient than other methods. This extended abstract presents a method for the measurement of high spatial and temporal resolution SSC using a down-looking, mobile ADCP from discrete cross-sections. The high-resolution scales of sediment data are a primary advantage and a vast improvement over other discrete methods for measuring SSC. Although acoustic surrogate technology using continuous, fixed-deployment ADCPs (side-looking) is proven, the same methods cannot be used with down-looking ADCPs due to the fact that the SSC and particle-size distribution variation in the vertical profile violates theory and complicates assumptions. A software tool was developed to assist in using acoustic backscatter from a down-looking, mobile ADCP as a surrogate for SSC. This tool has a simple graphical user interface that loads the data, assists in the calibration procedure, and provides data visualization and output options. This tool is designed to improve ongoing efforts to monitor and predict resource responses to a changing environment. Because ADCPs are used routinely for streamflow measurements, using acoustic backscatter from ADCPs as a surrogate for SSC has the potential to revolutionize sediment measurements by providing rapid measurements of sediment flux and distribution at spatial and temporal scales that are far beyond the capabilities of traditional physical samplers.

Advancing the quantification of humid tropical forest cover loss with multi-resolution optical remote sensing data: Sampling & wall-to-wall mapping

NASA Astrophysics Data System (ADS)

Broich, Mark

Humid tropical forest cover loss is threatening the sustainability of ecosystem goods and services as vast forest areas are rapidly cleared for industrial scale agriculture and tree plantations. Despite the importance of humid tropical forest in the provision of ecosystem services and economic development opportunities, the spatial and temporal distribution of forest cover loss across large areas is not well quantified. Here I improve the quantification of humid tropical forest cover loss using two remote sensing-based methods: sampling and wall-to-wall mapping. In all of the presented studies, the integration of coarse spatial, high temporal resolution data with moderate spatial, low temporal resolution data enable advances in quantifying forest cover loss in the humid tropics. Imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) are used as the source of coarse spatial resolution, high temporal resolution data and imagery from the Landsat Enhanced Thematic Mapper Plus (ETM+) sensor are used as the source of moderate spatial, low temporal resolution data. In a first study, I compare the precision of different sampling designs for the Brazilian Amazon using the annual deforestation maps derived by the Brazilian Space Agency for reference. I show that sampling designs can provide reliable deforestation estimates; furthermore, sampling designs guided by MODIS data can provide more efficient estimates than the systematic design used for the United Nations Food and Agricultural Organization Forest Resource Assessment 2010. Sampling approaches, such as the one demonstrated, are viable in regions where data limitations, such as cloud contamination, limit exhaustive mapping methods. Cloud-contaminated regions experiencing high rates of change include Insular Southeast Asia, specifically Indonesia and Malaysia. Due to persistent cloud cover, forest cover loss in Indonesia has only been mapped at a 5-10 year interval using photo interpretation of single best Landsat images. Such an approach does not provide timely results, and cloud cover reduces the utility of map outputs. In a second study, I develop a method to exhaustively mine the recently opened Landsat archive for cloud-free observations and automatically map forest cover loss for Sumatra and Kalimantan for the 2000-2005 interval. In a comparison with a reference dataset consisting of 64 Landsat sample blocks, I show that my method, using per pixel time-series, provides more accurate forest cover loss maps for multiyear intervals than approaches using image composites. In a third study, I disaggregate Landsat-mapped forest cover loss, mapped over a multiyear interval, by year using annual forest cover loss maps generated from coarse spatial, high temporal resolution MODIS imagery. I further disaggregate and analyze forest cover loss by forest land use, and provinces. Forest cover loss trends show high spatial and temporal variability. These results underline the importance of annual mapping for the quantification of forest cover loss in Indonesia, specifically in the light of the developing Reducing Emissions from Deforestation and Forest Degradation in Developing Countries policy framework (REDD). All three studies highlight the advances in quantifying forest cover loss in the humid tropics made by integrating coarse spatial, high temporal resolution data with moderate spatial, low temporal resolution data. The three methods presented can be combined into an integrated monitoring strategy.

Temporal subtraction contrast-enhanced dedicated breast CT

PubMed Central

Gazi, Peymon M.; Aminololama-Shakeri, Shadi; Yang, Kai; Boone, John M.

2016-01-01

Purpose To develop a framework of deformable image registration and segmentation for the purpose of temporal subtraction contrast-enhanced breast CT is described. Methods An iterative histogram-based two-means clustering method was used for the segmentation. Dedicated breast CT images were segmented into background (air), adipose, fibroglandular and skin components. Fibroglandular tissue was classified as either normal or contrast-enhanced then divided into tiers for the purpose of categorizing degrees of contrast enhancement. A variant of the Demons deformable registration algorithm, Intensity Difference Adaptive Demons (IDAD), was developed to correct for the large deformation forces that stemmed from contrast enhancement. In this application, the accuracy of the proposed method was evaluated in both mathematically-simulated and physically-acquired phantom images. Clinical usage and accuracy of the temporal subtraction framework was demonstrated using contrast-enhanced breast CT datasets from five patients. Registration performance was quantified using Normalized Cross Correlation (NCC), Symmetric Uncertainty Coefficient (SUC), Normalized Mutual Information (NMI), Mean Square Error (MSE) and Target Registration Error (TRE). Results The proposed method outperformed conventional affine and other Demons variations in contrast enhanced breast CT image registration. In simulation studies, IDAD exhibited improvement in MSE(0–16%), NCC (0–6%), NMI (0–13%) and TRE (0–34%) compared to the conventional Demons approaches, depending on the size and intensity of the enhancing lesion. As lesion size and contrast enhancement levels increased, so did the improvement. The drop in the correlation between the pre- and post-contrast images for the largest enhancement levels in phantom studies is less than 1.2% (150 Hounsfield units). Registration error, measured by TRE, shows only submillimeter mismatches between the concordant anatomical target points in all patient studies. The algorithm was implemented using a parallel processing architecture resulting in rapid execution time for the iterative segmentation and intensity-adaptive registration techniques. Conclusion Characterization of contrast-enhanced lesions is improved using temporal subtraction contrast-enhanced dedicated breast CT. Adaptation of Demons registration forces as a function of contrast-enhancement levels provided a means to accurately align breast tissue in pre- and post-contrast image acquisitions, improving subtraction results. Spatial subtraction of the aligned images yields useful diagnostic information with respect to enhanced lesion morphology and uptake. PMID:27494376

The Efficacy of Fast ForWord-Language Intervention in School-Age Children with Language Impairment: A Randomized Controlled Trial

PubMed Central

Gillam, Ronald B.; Loeb, Diane Frome; Hoffman, LaVae M.; Bohman, Thomas; Champlin, Craig A.; Thibodeau, Linda; Widen, Judith; Brandel, Jayne; Friel-Patti, Sandy

2008-01-01

Purpose A randomized controlled trial (RCT) was conducted to compare the language and auditory processing outcomes of children assigned to Fast ForWord-Language (FFW-L) to the outcomes of children assigned to nonspecific or specific language intervention comparison treatments that did not contain modified speech. Method Two hundred and sixteen children between the ages of 6 and 9 years with language impairments were randomly assigned to one of four arms: Fast ForWord-Language (FFW-L), academic enrichment (AE), computer-assisted language intervention (CALI), or individualized language intervention (ILI) provided by a speech-language pathologist. All children received 1 hour and 40 minutes of treatment, 5 days per week, for 6 weeks. Language and auditory processing measures were administered to the children by blinded examiners before treatment, immediately after treatment, 3 months after treatment, and 6 months after treatment. Results The children in all four arms improved significantly on a global language test and a test of backward masking. Children with poor backward masking scores who were randomized to the FFW-L arm did not present greater improvement on the language measures than children with poor backward masking scores who were randomized to the other three arms. Effect sizes, analyses of standard error of measurement, and normalization percentages supported the clinical significance of the improvements on the CASL. There was a treatment effect for the Blending Words subtest on the Comprehensive Test of Phonological Processing (Wagner, Torgesen, & Rashotte, 1999). Participants in the FFW-L and CALI arms earned higher phonological awareness scores than children in the ILI and AE arms at the six-month follow-up testing. Conclusion Fast ForWord-Language, the language intervention that provided modified speech to address a hypothesized underlying auditory processing deficit, was not more effective at improving general language skills or temporal processing skills than a nonspecific comparison treatment (AE) or specific language intervention comparison treatments (CALI and ILI) that did not contain modified speech stimuli. These findings call into question the temporal processing hypothesis of language impairment and the hypothesized benefits of using acoustically modified speech to improve language skills. The finding that children in the three treatment arms and the active comparison arm made clinically relevant gains on measures of language and temporal auditory processing informs our understanding of the variety of intervention activities that can facilitate development. PMID:18230858

Research on spatio-temporal database techniques for spatial information service

NASA Astrophysics Data System (ADS)

Zhao, Rong; Wang, Liang; Li, Yuxiang; Fan, Rongshuang; Liu, Ping; Li, Qingyuan

2007-06-01

Geographic data should be described by spatial, temporal and attribute components, but the spatio-temporal queries are difficult to be answered within current GIS. This paper describes research into the development and application of spatio-temporal data management system based upon GeoWindows GIS software platform which was developed by Chinese Academy of Surveying and Mapping (CASM). Faced the current and practical requirements of spatial information application, and based on existing GIS platform, one kind of spatio-temporal data model which integrates vector and grid data together was established firstly. Secondly, we solved out the key technique of building temporal data topology, successfully developed a suit of spatio-temporal database management system adopting object-oriented methods. The system provides the temporal data collection, data storage, data management and data display and query functions. Finally, as a case study, we explored the application of spatio-temporal data management system with the administrative region data of multi-history periods of China as the basic data. With all the efforts above, the GIS capacity of management and manipulation in aspect of time and attribute of GIS has been enhanced, and technical reference has been provided for the further development of temporal geographic information system (TGIS).

Max CAPR: high-resolution 3D contrast-enhanced MR angiography with acquisition times under 5 seconds.

PubMed

Haider, Clifton R; Borisch, Eric A; Glockner, James F; Mostardi, Petrice M; Rossman, Phillip J; Young, Phillip M; Riederer, Stephen J

2010-10-01

High temporal and spatial resolution is desired in imaging of vascular abnormalities having short arterial-to-venous transit times. Methods that exploit temporal correlation to reduce the observed frame time demonstrate temporal blurring, obfuscating bolus dynamics. Previously, a Cartesian acquisition with projection reconstruction-like (CAPR) sampling method has been demonstrated for three-dimensional contrast-enhanced angiographic imaging of the lower legs using two-dimensional sensitivity-encoding acceleration and partial Fourier acceleration, providing 1mm isotropic resolution of the calves, with 4.9-sec frame time and 17.6-sec temporal footprint. In this work, the CAPR acquisition is further undersampled to provide a net acceleration approaching 40 by eliminating all view sharing. The tradeoff of frame time and temporal footprint in view sharing is presented and characterized in phantom experiments. It is shown that the resultant 4.9-sec acquisition time, three-dimensional images sets have sufficient spatial and temporal resolution to clearly portray arterial and venous phases of contrast passage. It is further hypothesized that these short temporal footprint sequences provide diagnostic quality images. This is tested and shown in a series of nine contrast-enhanced MR angiography patient studies performed with the new method.

Simulation Study of a Follow-on Gravity Mission to GRACE

NASA Technical Reports Server (NTRS)

Loomis, Bryant D.; Nerem, R. S.; Luthcke, Scott B.

2012-01-01

The gravity recovery and climate experiment (GRACE) has been providing monthly estimates of the Earth's time-variable gravity field since its launch in March 2002. The GRACE gravity estimates are used to study temporal mass variations on global and regional scales, which are largely caused by a redistribution of water mass in the Earth system. The accuracy of the GRACE gravity fields are primarily limited by the satellite-to-satellite range-rate measurement noise, accelerometer errors, attitude errors, orbit errors, and temporal aliasing caused by unmodeled high-frequency variations in the gravity signal. Recent work by Ball Aerospace and Technologies Corp., Boulder, CO has resulted in the successful development of an interferometric laser ranging system to specifically address the limitations of the K-band microwave ranging system that provides the satellite-to-satellite measurements for the GRACE mission. Full numerical simulations are performed for several possible configurations of a GRACE Follow-On (GFO) mission to determine if a future satellite gravity recovery mission equipped with a laser ranging system will provide better estimates of time-variable gravity, thus benefiting many areas of Earth systems research. The laser ranging system improves the range-rate measurement precision to approximately 0.6 nm/s as compared to approx. 0.2 micro-seconds for the GRACE K-band microwave ranging instrument. Four different mission scenarios are simulated to investigate the effect of the better instrument at two different altitudes. The first pair of simulated missions is flown at GRACE altitude (approx. 480 km) assuming on-board accelerometers with the same noise characteristics as those currently used for GRACE. The second pair of missions is flown at an altitude of approx. 250 km which requires a drag-free system to prevent satellite re-entry. In addition to allowing a lower satellite altitude, the drag-free system also reduces the errors associated with the accelerometer. All simulated mission scenarios assume a two satellite co-orbiting pair similar to GRACE in a near-polar, near-circular orbit. A method for local time variable gravity recovery through mass concentration blocks (mascons) is used to form simulated gravity estimates for Greenland and the Amazon region for three GFO configurations and GRACE. Simulation results show that the increased precision of the laser does not improve gravity estimation when flown with on-board accelerometers at the same altitude and spacecraft separation as GRACE, even when time-varying background models are not included. This study also shows that only modest improvement is realized for the best-case scenario (laser, low-altitude, drag-free) as compared to GRACE due to temporal aliasing errors. These errors are caused by high-frequency variations in the hydrology signal and imperfections in the atmospheric, oceanographic, and tidal models which are used to remove unwanted signal. This work concludes that applying the updated technologies alone will not immediately advance the accuracy of the gravity estimates. If the scientific objectives of a GFO mission require more accurate gravity estimates, then future work should focus on improvements in the geophysical models, and ways in which the mission design or data processing could reduce the effects of temporal aliasing.

Long-period fiber gratings as ultrafast optical differentiators.

PubMed

Kulishov, Mykola; Azaña, José

2005-10-15

It is demonstrated that a single, uniform long-period fiber grating (LPFG) working in the linear regime inherently behaves as an ultrafast optical temporal differentiator. Specifically, we show that the output temporal waveform in the core mode of a LPFG providing full energy coupling into the cladding mode is proportional to the first derivative of the optical temporal signal (e.g., optical pulse) launched at the input of the LPFG. Moreover, a LPFG providing full energy recoupling back from the cladding mode into the core mode inherently implements second-order temporal differentiation. Our numerical results have confirmed the feasibility of this simple, all-fiber approach to processing optical signals with temporal features in the picosecond and subpicosecond ranges.

Training in Temporal Information Processing Ameliorates Phonetic Identification.

PubMed

Szymaszek, Aneta; Dacewicz, Anna; Urban, Paulina; Szelag, Elzbieta

2018-01-01

Many studies revealed a link between temporal information processing (TIP) in a millisecond range and speech perception. Previous studies indicated a dysfunction in TIP accompanied by deficient phonemic hearing in children with specific language impairment (SLI). In this study we concentrate in SLI on phonetic identification, using the voice-onset-time (VOT) phenomenon in which TIP is built-in. VOT is crucial for speech perception, as stop consonants (like /t/ vs. /d/) may be distinguished by an acoustic difference in time between the onsets of the consonant (stop release burst) and the following vibration of vocal folds (voicing). In healthy subjects two categories (voiced and unvoiced) are determined using VOT task. The present study aimed at verifying whether children with SLI indicate a similar pattern of phonetic identification as their healthy peers and whether the intervention based on TIP results in improved performance on the VOT task. Children aged from 5 to 8 years ( n = 47) were assigned into two groups: normal children without any language disability (NC, n = 20), and children with SLI ( n = 27). In the latter group participants were randomly classified into two treatment subgroups, i.e., experimental temporal training (EG, n = 14) and control non-temporal training (CG, n = 13). The analyzed indicators of phonetic identification were: (1) the boundary location (α) determined as the VOT value corresponding to 50% voicing/unvoicing distinctions; (2) ranges of voiced/unvoiced categories; (3) the slope of identification curve (β) reflecting the identification correctness; (4) percent of voiced distinctions within the applied VOT spectrum. The results indicated similar α values and similar ranges of voiced/unvoiced categories between SLI and NC. However, β in SLI was significantly higher than that in NC. After the intervention, the significant improvement of β was observed only in EG. They achieved the level of performance comparable to that observed in NC. The training-related improvement in CG was non-significant. Furthermore, only in EG the β values in post-test correlated with measures of TIP as well as with phonemic hearing obtained in our previous studies. These findings provide another evidence that TIP is omnipresent in language communication and reflected not only in phonemic hearing but also in phonetic identification.

Objective Interpolation of Scatterometer Winds

NASA Technical Reports Server (NTRS)

Tang, Wenquing; Liu, W. Timothy

1996-01-01

Global wind fields are produced by successive corrections that use measurements by the European Remote Sensing Satellite (ERS-1) scatterometer. The methodology is described. The wind fields at 10-meter height provided by the European Center for Medium-Range Weather Forecasting (ECMWF) are used to initialize the interpolation process. The interpolated wind field product ERSI is evaluated in terms of its improvement over the initial guess field (ECMWF) and the bin-averaged ERS-1 wind field (ERSB). Spatial and temporal differences between ERSI, ECMWF and ERSB are presented and discussed.

Near-Continuous Profiling of Temperature, Moisture, and Atmospheric Stability Using the Atmospheric Emitted Radiance Interferometer (AERI).

NASA Astrophysics Data System (ADS)

Feltz, W. F.; Smith, W. L.; Howell, H. B.; Knuteson, R. O.; Woolf, H.; Revercomb, H. E.

2003-05-01

The Department of Energy Atmospheric Radiation Measurement Program (ARM) has funded the development and installation of five ground-based atmospheric emitted radiance interferometer (AERI) systems at the Southern Great Plains (SGP) site. The purpose of this paper is to provide an overview of the AERI instrument, improvement of the AERI temperature and moisture retrieval technique, new profiling utility, and validation of high-temporal-resolution AERI-derived stability indices important for convective nowcasting. AERI systems have been built at the University of Wisconsin-Madison, Madison, Wisconsin, and deployed in the Oklahoma-Kansas area collocated with National Oceanic and Atmospheric Administration 404-MHz wind profilers at Lamont, Vici, Purcell, and Morris, Oklahoma, and Hillsboro, Kansas. The AERI systems produce absolutely calibrated atmospheric infrared emitted radiances at one-wavenumber resolution from 3 to 20 m at less than 10-min temporal resolution. The instruments are robust, are automated in the field, and are monitored via the Internet in near-real time. The infrared radiances measured by the AERI systems contain meteorological information about the vertical structure of temperature and water vapor in the planetary boundary layer (PBL; 0-3 km). A mature temperature and water vapor retrieval algorithm has been developed over a 10-yr period that provides vertical profiles at less than 10-min temporal resolution to 3 km in the PBL. A statistical retrieval is combined with the hourly Geostationary Operational Environmental Satellite (GOES) sounder water vapor or Rapid Update Cycle, version 2, numerical weather prediction (NWP) model profiles to provide a nominal hybrid first guess of temperature and moisture to the AERI physical retrieval algorithm. The hourly satellite or NWP data provide a best estimate of the atmospheric state in the upper PBL; the AERI radiances provide the mesoscale temperature and moisture profile correction in the PBL to the large-scale GOES and NWP model profiles at high temporal resolution. The retrieval product has been named AERIplus because the first guess used for the mathematical physical inversion uses an optimal combination of statistical climatological, satellite, and numerical model data to provide a best estimate of the atmospheric state. The AERI physical retrieval algorithm adjusts the boundary layer temperature and moisture structure provided by the hybrid first guess to fit the observed AERI downwelling radiance measurement. This provides a calculated AERI temperature and moisture profile using AERI-observed radiances `plus' the best-known atmospheric state above the boundary layer using NWP or satellite data. AERIplus retrieval accuracy for temperature has been determined to be better than 1 K, and water vapor retrieval accuracy is approximately 5% in absolute water vapor when compared with well-calibrated radiosondes from the surface to an altitude of 3 km. Because AERI can monitor the thermodynamics where the atmosphere usually changes most rapidly, atmospheric stability tendency information is readily available from the system. High-temporal-resolution retrieval of convective available potential energy, convective inhibition, and PBL equivalent potential temperature e are provided in near-real time from all five AERI systems at the ARM SGP site, offering a unique look at the atmospheric state. This new source of meteorological data has shown excellent skill in detecting rapid synoptic and mesoscale meteorological changes within clear atmospheric conditions. This method has utility in nowcasting temperature inversion strength and destabilization caused by e advection. This high-temporal-resolution monitoring of rapid atmospheric destabilization is especially important for nowcasting severe convection.

The effects of context and musical training on auditory temporal-interval discrimination.

PubMed

Banai, Karen; Fisher, Shirley; Ganot, Ron

2012-02-01

Non sensory factors such as stimulus context and musical experience are known to influence auditory frequency discrimination, but whether the context effect extends to auditory temporal processing remains unknown. Whether individual experiences such as musical training alter the context effect is also unknown. The goal of the present study was therefore to investigate the effects of stimulus context and musical experience on auditory temporal-interval discrimination. In experiment 1, temporal-interval discrimination was compared between fixed context conditions in which a single base temporal interval was presented repeatedly across all trials and variable context conditions in which one of two base intervals was randomly presented on each trial. Discrimination was significantly better in the fixed than in the variable context conditions. In experiment 2 temporal discrimination thresholds of musicians and non-musicians were compared across 3 conditions: a fixed context condition in which the target interval was presented repeatedly across trials, and two variable context conditions differing in the frequencies used for the tones marking the temporal intervals. Musicians outperformed non-musicians on all 3 conditions, but the effects of context were similar for the two groups. Overall, it appears that, like frequency discrimination, temporal-interval discrimination benefits from having a fixed reference. Musical experience, while improving performance, did not alter the context effect, suggesting that improved discrimination skills among musicians are probably not an outcome of more sensitive contextual facilitation or predictive coding mechanisms. Copyright © 2011 Elsevier B.V. All rights reserved.

Spectral and Temporal Laser Fluorescence Analysis Such as for Natural Aquatic Environments

NASA Technical Reports Server (NTRS)

Chekalyuk, Alexander (Inventor)

2015-01-01

An Advanced Laser Fluorometer (ALF) can combine spectrally and temporally resolved measurements of laser-stimulated emission (LSE) for characterization of dissolved and particulate matter, including fluorescence constituents, in liquids. Spectral deconvolution (SDC) analysis of LSE spectral measurements can accurately retrieve information about individual fluorescent bands, such as can be attributed to chlorophyll-a (Chl-a), phycobiliprotein (PBP) pigments, or chromophoric dissolved organic matter (CDOM), among others. Improved physiological assessments of photosynthesizing organisms can use SDC analysis and temporal LSE measurements to assess variable fluorescence corrected for SDC-retrieved background fluorescence. Fluorescence assessments of Chl-a concentration based on LSE spectral measurements can be improved using photo-physiological information from temporal measurements. Quantitative assessments of PBP pigments, CDOM, and other fluorescent constituents, as well as basic structural characterizations of photosynthesizing populations, can be performed using SDC analysis of LSE spectral measurements.

The precision of today's satellite laser ranging systems

NASA Astrophysics Data System (ADS)

Dunn, Peter J.; Torrence, Mark H.; Hussen, Van S.; Pearlman, Michael R.

1993-06-01

Recent improvements in the accuracy of modern satellite laser ranging (SLR) systems are strengthened by the new capability of many instruments to track an increasing number of geodetic satellite targets without significant scheduling conflict. This will allow the refinement of some geophysical parameters, such as solid Earth tidal effects and GM, and the improved temporal resolution of others, such as Earth orientation and station position. Better time resolution for the locations of fixed observatories will allow us to monitor more subtle motions at the stations, and transportable systems will be able to provide indicators of long term trends with shorter occupations. If we are to take advantage of these improvements, care must be taken to preserve the essential accuracy of an increasing volume of range observations at each stage of the data reduction process.

The precision of today's satellite laser ranging systems

NASA Technical Reports Server (NTRS)

Dunn, Peter J.; Torrence, Mark H.; Hussen, Van S.; Pearlman, Michael R.

1993-01-01

Recent improvements in the accuracy of modern satellite laser ranging (SLR) systems are strengthened by the new capability of many instruments to track an increasing number of geodetic satellite targets without significant scheduling conflict. This will allow the refinement of some geophysical parameters, such as solid Earth tidal effects and GM, and the improved temporal resolution of others, such as Earth orientation and station position. Better time resolution for the locations of fixed observatories will allow us to monitor more subtle motions at the stations, and transportable systems will be able to provide indicators of long term trends with shorter occupations. If we are to take advantage of these improvements, care must be taken to preserve the essential accuracy of an increasing volume of range observations at each stage of the data reduction process.

Diabetes Interactive Atlas

PubMed Central

Burrows, Nilka R.; Geiss, Linda S.

2014-01-01

The Diabetes Interactive Atlas is a recently released Web-based collection of maps that allows users to view geographic patterns and examine trends in diabetes and its risk factors over time across the United States and within states. The atlas provides maps, tables, graphs, and motion charts that depict national, state, and county data. Large amounts of data can be viewed in various ways simultaneously. In this article, we describe the design and technical issues for developing the atlas and provide an overview of the atlas’ maps and graphs. The Diabetes Interactive Atlas improves visualization of geographic patterns, highlights observation of trends, and demonstrates the concomitant geographic and temporal growth of diabetes and obesity. PMID:24503340

SubClonal Hierarchy Inference from Somatic Mutations: Automatic Reconstruction of Cancer Evolutionary Trees from Multi-region Next Generation Sequencing

PubMed Central

Niknafs, Noushin; Beleva-Guthrie, Violeta; Naiman, Daniel Q.; Karchin, Rachel

2015-01-01

Recent improvements in next-generation sequencing of tumor samples and the ability to identify somatic mutations at low allelic fractions have opened the way for new approaches to model the evolution of individual cancers. The power and utility of these models is increased when tumor samples from multiple sites are sequenced. Temporal ordering of the samples may provide insight into the etiology of both primary and metastatic lesions and rationalizations for tumor recurrence and therapeutic failures. Additional insights may be provided by temporal ordering of evolving subclones—cellular subpopulations with unique mutational profiles. Current methods for subclone hierarchy inference tightly couple the problem of temporal ordering with that of estimating the fraction of cancer cells harboring each mutation. We present a new framework that includes a rigorous statistical hypothesis test and a collection of tools that make it possible to decouple these problems, which we believe will enable substantial progress in the field of subclone hierarchy inference. The methods presented here can be flexibly combined with methods developed by others addressing either of these problems. We provide tools to interpret hypothesis test results, which inform phylogenetic tree construction, and we introduce the first genetic algorithm designed for this purpose. The utility of our framework is systematically demonstrated in simulations. For most tested combinations of tumor purity, sequencing coverage, and tree complexity, good power (≥ 0.8) can be achieved and Type 1 error is well controlled when at least three tumor samples are available from a patient. Using data from three published multi-region tumor sequencing studies of (murine) small cell lung cancer, acute myeloid leukemia, and chronic lymphocytic leukemia, in which the authors reconstructed subclonal phylogenetic trees by manual expert curation, we show how different configurations of our tools can identify either a single tree in agreement with the authors, or a small set of trees, which include the authors’ preferred tree. Our results have implications for improved modeling of tumor evolution and the importance of multi-region tumor sequencing. PMID:26436540

Merging Satellite Precipitation Products for Improved Streamflow Simulations

NASA Astrophysics Data System (ADS)

Maggioni, V.; Massari, C.; Barbetta, S.; Camici, S.; Brocca, L.

2017-12-01

Accurate quantitative precipitation estimation is of great importance for water resources management, agricultural planning and forecasting and monitoring of natural hazards such as flash floods and landslides. In situ observations are limited around the Earth, especially in remote areas (e.g., complex terrain, dense vegetation), but currently available satellite precipitation products are able to provide global precipitation estimates with an accuracy that depends upon many factors (e.g., type of storms, temporal sampling, season, etc.). The recent SM2RAIN approach proposes to estimate rainfall by using satellite soil moisture observations. As opposed to traditional satellite precipitation methods, which sense cloud properties to retrieve instantaneous estimates, this new bottom-up approach makes use of two consecutive soil moisture measurements for obtaining an estimate of the fallen precipitation within the interval between two satellite overpasses. As a result, the nature of the measurement is different and complementary to the one of classical precipitation products and could provide a different valid perspective to substitute or improve current rainfall estimates. Therefore, we propose to merge SM2RAIN and the widely used TMPA 3B42RT product across Italy for a 6-year period (2010-2015) at daily/0.25deg temporal/spatial scale. Two conceptually different merging techniques are compared to each other and evaluated in terms of different statistical metrics, including hit bias, threat score, false alarm rates, and missed rainfall volumes. The first is based on the maximization of the temporal correlation with a reference dataset, while the second is based on a Bayesian approach, which provides a probabilistic satellite precipitation estimate derived from the joint probability distribution of observations and satellite estimates. The merged precipitation products show a better performance with respect to the parental satellite-based products in terms of categorical statistics, as well as bias reduction and correlation coefficient, with the Bayesian approach being superior to other methods. A study case in the Tiber river basin is also presented to discuss the performance of forcing a hydrological model with the merged satellite precipitation product to simulate streamflow time series.

Sleep to the beat: A nap favours consolidation of timing.

PubMed

Verweij, Ilse M; Onuki, Yoshiyuki; Van Someren, Eus J W; Van der Werf, Ysbrand D

2016-06-01

Growing evidence suggests that sleep is important for procedural learning, but few studies have investigated the effect of sleep on the temporal aspects of motor skill learning. We assessed the effect of a 90-min day-time nap on learning a motor timing task, using 2 adaptations of a serial interception sequence learning (SISL) task. Forty-two right-handed participants performed the task before and after a 90-min period of sleep or wake. Electroencephalography (EEG) was recorded throughout. The motor task consisted of a sequential spatial pattern and was performed according to 2 different timing conditions, that is, either following a sequential or a random temporal pattern. The increase in accuracy was compared between groups using a mixed linear regression model. Within the sleep group, performance improvement was modeled based on sleep characteristics, including spindle- and slow-wave density. The sleep group, but not the wake group, showed improvement in the random temporal, but especially and significantly more strongly in the sequential temporal condition. None of the sleep characteristics predicted improvement on either general of the timing conditions. In conclusion, a daytime nap improves performance on a timing task. We show that performance on the task with a sequential timing sequence benefits more from sleep than motor timing. More important, the temporal sequence did not benefit initial learning, because differences arose only after an offline period and specifically when this period contained sleep. Sleep appears to aid in the extraction of regularities for optimal subsequent performance. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Sensitivity of Land Surface Parameters on Thunderstorm Simulation through HRLDAS-WRF Coupling Mode

NASA Astrophysics Data System (ADS)

Kumar, Dinesh; Kumar, Krishan; Mohanty, U. C.; Kisore Osuri, Krishna

2016-07-01

Land surface characteristics play an important role in large scale, regional and mesoscale atmospheric process. Representation of land surface characteristics can be improved through coupling of mesoscale atmospheric models with land surface models. Mesoscale atmospheric models depend on Land Surface Models (LSM) to provide land surface variables such as fluxes of heat, moisture, and momentum for lower boundary layer evolution. Studies have shown that land surface properties such as soil moisture, soil temperature, soil roughness, vegetation cover, have considerable effect on lower boundary layer. Although, the necessity to initialize soil moisture accurately in NWP models is widely acknowledged, monitoring soil moisture at regional and global scale is a very tough task due to high spatial and temporal variability. As a result, the available observation network is unable to provide the required spatial and temporal data for the most part of the globe. Therefore, model for land surface initializations rely on updated land surface properties from LSM. The solution for NWP land-state initialization can be found by combining data assimilation techniques, satellite-derived soil data, and land surface models. Further, it requires an intermediate step to use observed rainfall, satellite derived surface insolation, and meteorological analyses to run an uncoupled (offline) integration of LSM, so that the evolution of modeled soil moisture can be forced by observed forcing conditions. Therefore, for accurate land-state initialization, high resolution land data assimilation system (HRLDAS) is used to provide the essential land surface parameters. Offline-coupling of HRLDAS-WRF has shown much improved results over Delhi, India for four thunder storm events. The evolution of land surface variables particularly soil moisture, soil temperature and surface fluxes have provided more realistic condition. Results have shown that most of domain part became wetter and warmer after assimilation of soil moisture and soil temperature at the initial condition which helped to improve the exchange fluxes at lower atmospheric level. Mixing ratio were increased along with elevated theta-e at lower level giving a signature of improvement in LDAS experiment leading to a suitable condition for convection. In the analysis, moisture convergence, mixing ratio and vertical velocities have improved significantly in terms of intensity and time lag. Surface variables like soil moisture, soil temperature, sensible heat flux and latent heat flux have progressed in a possible realistic pattern. Above discussion suggests that assimilation of soil moisture and soil temperature improves the overall simulations significantly.

Mining Recent Temporal Patterns for Event Detection in Multivariate Time Series Data

PubMed Central

Batal, Iyad; Fradkin, Dmitriy; Harrison, James; Moerchen, Fabian; Hauskrecht, Milos

2015-01-01

Improving the performance of classifiers using pattern mining techniques has been an active topic of data mining research. In this work we introduce the recent temporal pattern mining framework for finding predictive patterns for monitoring and event detection problems in complex multivariate time series data. This framework first converts time series into time-interval sequences of temporal abstractions. It then constructs more complex temporal patterns backwards in time using temporal operators. We apply our framework to health care data of 13,558 diabetic patients and show its benefits by efficiently finding useful patterns for detecting and diagnosing adverse medical conditions that are associated with diabetes. PMID:25937993

NASA Land Information System (LIS) Water Availability to Support Reclamation ET Estimation

NASA Technical Reports Server (NTRS)

Toll, David; Arsenault, Kristi; Pinheiro, Ana; Peters-Lidard, Christa; Houser, Paul; Kumar, Sujay; Engman, Ted; Nigro, Joe; Triggs, Jonathan

2005-01-01

The U.S. Bureau of Reclamation identified the remote sensing of evapotranspiration (ET) as an important water flux for study and designated a test site in the Lower Colorado River basin. A consortium of groups will work together with the goal to develop more accurate and cost effective techniques using the enhanced spatial and temporal coverage afforded by remote sensing. ET is a critical water loss flux where improved estimation should lead to better management of Reclamation responsibilities. There are several areas where NASA satellite and modeling data may be useful to meet Reclamation's objectives for improved ET estimation. In this paper we outline one possible contribution to use NASA's data integration capability of the Land Information System (LIS) to provide a merger of observational (in situ and satellite) with physical process models to provide estimates of ET and other water availability outputs (e.g., runoff, soil moisture) retrospectively, in near real-time, and also providing short-term predictions.

Improving temporal resolution in fMRI using a 3D spiral acquisition and low rank plus sparse (L+S) reconstruction.

PubMed

Petrov, Andrii Y; Herbst, Michael; Andrew Stenger, V

2017-08-15

Rapid whole-brain dynamic Magnetic Resonance Imaging (MRI) is of particular interest in Blood Oxygen Level Dependent (BOLD) functional MRI (fMRI). Faster acquisitions with higher temporal sampling of the BOLD time-course provide several advantages including increased sensitivity in detecting functional activation, the possibility of filtering out physiological noise for improving temporal SNR, and freezing out head motion. Generally, faster acquisitions require undersampling of the data which results in aliasing artifacts in the object domain. A recently developed low-rank (L) plus sparse (S) matrix decomposition model (L+S) is one of the methods that has been introduced to reconstruct images from undersampled dynamic MRI data. The L+S approach assumes that the dynamic MRI data, represented as a space-time matrix M, is a linear superposition of L and S components, where L represents highly spatially and temporally correlated elements, such as the image background, while S captures dynamic information that is sparse in an appropriate transform domain. This suggests that L+S might be suited for undersampled task or slow event-related fMRI acquisitions because the periodic nature of the BOLD signal is sparse in the temporal Fourier transform domain and slowly varying low-rank brain background signals, such as physiological noise and drift, will be predominantly low-rank. In this work, as a proof of concept, we exploit the L+S method for accelerating block-design fMRI using a 3D stack of spirals (SoS) acquisition where undersampling is performed in the k z -t domain. We examined the feasibility of the L+S method to accurately separate temporally correlated brain background information in the L component while capturing periodic BOLD signals in the S component. We present results acquired in control human volunteers at 3T for both retrospective and prospectively acquired fMRI data for a visual activation block-design task. We show that a SoS fMRI acquisition with an acceleration of four and L+S reconstruction can achieve a brain coverage of 40 slices at 2mm isotropic resolution and 64 x 64 matrix size every 500ms. Copyright © 2017 Elsevier Inc. All rights reserved.

A review of simulation platforms in surgery of the temporal bone.

PubMed

Bhutta, M F

2016-10-01

Surgery of the temporal bone is a high-risk activity in an anatomically complex area. Simulation enables rehearsal of such surgery. The traditional simulation platform is the cadaveric temporal bone, but in recent years other simulation platforms have been created, including plastic and virtual reality platforms. To undertake a review of simulation platforms for temporal bone surgery, specifically assessing their educational value in terms of validity and in enabling transition to surgery. Systematic qualitative review. Search of the Pubmed, CINAHL, BEI and ERIC databases. Assessment of reported outcomes in terms of educational value. A total of 49 articles were included, covering cadaveric, animal, plastic and virtual simulation platforms. Cadaveric simulation is highly rated as an educational tool, but there may be a ceiling effect on educational outcomes after drilling 8-10 temporal bones. Animal models show significant anatomical variation from man. Plastic temporal bone models offer much potential, but at present lack sufficient anatomical or haptic validity. Similarly, virtual reality platforms lack sufficient anatomical or haptic validity, but with technological improvements they are advancing rapidly. At present, cadaveric simulation remains the best platform for training in temporal bone surgery. Technological advances enabling improved materials or modelling mean that in the future plastic or virtual platforms may become comparable to cadaveric platforms, and also offer additional functionality including patient-specific simulation from CT data. © 2015 John Wiley & Sons Ltd.

Development of a spatio-temporal disaggregation method (DisNDVI) for generating a time series of fine resolution NDVI images

NASA Astrophysics Data System (ADS)

Bindhu, V. M.; Narasimhan, B.

2015-03-01

Normalized Difference Vegetation Index (NDVI), a key parameter in understanding the vegetation dynamics, has high spatial and temporal variability. However, continuous monitoring of NDVI is not feasible at fine spatial resolution (<60 m) owing to the long revisit time needed by the satellites to acquire the fine spatial resolution data. Further, the study attains significance in the case of humid tropical regions of the earth, where the prevailing atmospheric conditions restrict availability of fine resolution cloud free images at a high temporal frequency. As an alternative to the lack of high resolution images, the current study demonstrates a novel disaggregation method (DisNDVI) which integrates the spatial information from a single fine resolution image and temporal information in terms of crop phenology from time series of coarse resolution images to generate estimates of NDVI at fine spatial and temporal resolution. The phenological variation of the pixels captured at the coarser scale provides the basis for relating the temporal variability of the pixel with the NDVI available at fine resolution. The proposed methodology was tested over a 30 km × 25 km spatially heterogeneous study area located in the south of Tamil Nadu, India. The robustness of the algorithm was assessed by an independent comparison of the disaggregated NDVI and observed NDVI obtained from concurrent Landsat ETM+ imagery. The results showed good spatial agreement across the study area dominated with agriculture and forest pixels, with a root mean square error of 0.05. The validation done at the coarser scale showed that disaggregated NDVI spatially averaged to 240 m compared well with concurrent MODIS NDVI at 240 m (R2 > 0.8). The validation results demonstrate the effectiveness of DisNDVI in improving the spatial and temporal resolution of NDVI images for utility in fine scale hydrological applications such as crop growth monitoring and estimation of evapotranspiration.

Precipitation data in a mountainous catchment in Honduras: quality assessment and spatiotemporal characteristics

NASA Astrophysics Data System (ADS)

Westerberg, I.; Walther, A.; Guerrero, J.-L.; Coello, Z.; Halldin, S.; Xu, C.-Y.; Chen, D.; Lundin, L.-C.

2010-08-01

An accurate description of temporal and spatial precipitation variability in Central America is important for local farming, water supply and flood management. Data quality problems and lack of consistent precipitation data impede hydrometeorological analysis in the 7,500 km2 Choluteca River basin in central Honduras, encompassing the capital Tegucigalpa. We used precipitation data from 60 daily and 13 monthly stations in 1913-2006 from five local authorities and NOAA's Global Historical Climatology Network. Quality control routines were developed to tackle the specific data quality problems. The quality-controlled data were characterised spatially and temporally, and compared with regional and larger-scale studies. Two gap-filling methods for daily data and three interpolation methods for monthly and mean annual precipitation were compared. The coefficient-of-correlation-weighting method provided the best results for gap-filling and the universal kriging method for spatial interpolation. In-homogeneity in the time series was the main quality problem, and 22% of the daily precipitation data were too poor to be used. Spatial autocorrelation for monthly precipitation was low during the dry season, and correlation increased markedly when data were temporally aggregated from a daily time scale to 4-5 days. The analysis manifested the high spatial and temporal variability caused by the diverse precipitation-generating mechanisms and the need for an improved monitoring network.

Imaging structural and functional brain networks in temporal lobe epilepsy.

PubMed

Bernhardt, Boris C; Hong, Seokjun; Bernasconi, Andrea; Bernasconi, Neda

2013-10-01

Early imaging studies in temporal lobe epilepsy (TLE) focused on the search for mesial temporal sclerosis, as its surgical removal results in clinically meaningful improvement in about 70% of patients. Nevertheless, a considerable subgroup of patients continues to suffer from post-operative seizures. Although the reasons for surgical failure are not fully understood, electrophysiological and imaging data suggest that anomalies extending beyond the temporal lobe may have negative impact on outcome. This hypothesis has revived the concept of human epilepsy as a disorder of distributed brain networks. Recent methodological advances in non-invasive neuroimaging have led to quantify structural and functional networks in vivo. While structural networks can be inferred from diffusion MRI tractography and inter-regional covariance patterns of structural measures such as cortical thickness, functional connectivity is generally computed based on statistical dependencies of neurophysiological time-series, measured through functional MRI or electroencephalographic techniques. This review considers the application of advanced analytical methods in structural and functional connectivity analyses in TLE. We will specifically highlight findings from graph-theoretical analysis that allow assessing the topological organization of brain networks. These studies have provided compelling evidence that TLE is a system disorder with profound alterations in local and distributed networks. In addition, there is emerging evidence for the utility of network properties as clinical diagnostic markers. Nowadays, a network perspective is considered to be essential to the understanding of the development, progression, and management of epilepsy.

Spatio-temporal conditional inference and hypothesis tests for neural ensemble spiking precision

PubMed Central

Harrison, Matthew T.; Amarasingham, Asohan; Truccolo, Wilson

2014-01-01

The collective dynamics of neural ensembles create complex spike patterns with many spatial and temporal scales. Understanding the statistical structure of these patterns can help resolve fundamental questions about neural computation and neural dynamics. Spatio-temporal conditional inference (STCI) is introduced here as a semiparametric statistical framework for investigating the nature of precise spiking patterns from collections of neurons that is robust to arbitrarily complex and nonstationary coarse spiking dynamics. The main idea is to focus statistical modeling and inference, not on the full distribution of the data, but rather on families of conditional distributions of precise spiking given different types of coarse spiking. The framework is then used to develop families of hypothesis tests for probing the spatio-temporal precision of spiking patterns. Relationships among different conditional distributions are used to improve multiple hypothesis testing adjustments and to design novel Monte Carlo spike resampling algorithms. Of special note are algorithms that can locally jitter spike times while still preserving the instantaneous peri-stimulus time histogram (PSTH) or the instantaneous total spike count from a group of recorded neurons. The framework can also be used to test whether first-order maximum entropy models with possibly random and time-varying parameters can account for observed patterns of spiking. STCI provides a detailed example of the generic principle of conditional inference, which may be applicable in other areas of neurostatistical analysis. PMID:25380339

Local collective motion analysis for multi-probe dynamic imaging and microrheology

NASA Astrophysics Data System (ADS)

Khan, Manas; Mason, Thomas G.

2016-08-01

Dynamical artifacts, such as mechanical drift, advection, and hydrodynamic flow, can adversely affect multi-probe dynamic imaging and passive particle-tracking microrheology experiments. Alternatively, active driving by molecular motors can cause interesting non-Brownian motion of probes in local regions. Existing drift-correction techniques, which require large ensembles of probes or fast temporal sampling, are inadequate for handling complex spatio-temporal drifts and non-Brownian motion of localized domains containing relatively few probes. Here, we report an analytical method based on local collective motion (LCM) analysis of as few as two probes for detecting the presence of non-Brownian motion and for accurately eliminating it to reveal the underlying Brownian motion. By calculating an ensemble-average, time-dependent, LCM mean square displacement (MSD) of two or more localized probes and comparing this MSD to constituent single-probe MSDs, we can identify temporal regimes during which either thermal or athermal motion dominates. Single-probe motion, when referenced relative to the moving frame attached to the multi-probe LCM trajectory, provides a true Brownian MSD after scaling by an appropriate correction factor that depends on the number of probes used in LCM analysis. We show that LCM analysis can be used to correct many different dynamical artifacts, including spatially varying drifts, gradient flows, cell motion, time-dependent drift, and temporally varying oscillatory advection, thereby offering a significant improvement over existing approaches.

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

Wang, Jiali; Swati, F. N. U.; Stein, Michael L.

Regional climate models (RCMs) are a standard tool for downscaling climate forecasts to finer spatial scales. The evaluation of RCMs against observational data is an important step in building confidence in the use of RCMs for future prediction. In addition to model performance in climatological means and marginal distributions, a model’s ability to capture spatio-temporal relationships is important. This study develops two approaches: (1) spatial correlation/variogram for a range of spatial lags, with total monthly precipitation and non-seasonal precipitation components used to assess the spatial variations of precipitation; and (2) spatio-temporal correlation for a wide range of distances, directions, andmore » time lags, with daily precipitation occurrence used to detect the dynamic features of precipitation. These measures of spatial and spatio-temporal dependence are applied to a high-resolution RCM run and to the National Center for Environmental Prediction (NCEP)-U.S. Department of Energy (DOE) AMIP II reanalysis data (NCEP-R2), which provides initial and lateral boundary conditions for the RCM. The RCM performs better than NCEP-R2 in capturing both the spatial variations of total and non-seasonal precipitation components and the spatio-temporal correlations of daily precipitation occurrences, which are related to dynamic behaviors of precipitating systems. The improvements are apparent not just at resolutions finer than that of NCEP-R2, but also when the RCM and observational data are aggregated to the resolution of NCEP-R2.« less

Surgical Considerations of Intractable Mesial Temporal Lobe Epilepsy

PubMed Central

Boling, Warren W.

2018-01-01

Surgery of temporal lobe epilepsy is the best opportunity for seizure freedom in medically intractable patients. The surgical approach has evolved to recognize the paramount importance of the mesial temporal structures in the majority of patients with temporal lobe epilepsy who have a seizure origin in the mesial temporal structures. For those individuals with medically intractable mesial temporal lobe epilepsy, a selective amygdalohippocampectomy surgery can be done that provides an excellent opportunity for seizure freedom and limits the resection to temporal lobe structures primarily involved in seizure genesis. PMID:29461485

Microwave Radiometer and Lidar Synergy for High Vertical Resolution Thermodynamic Profiling in a Cloudy Scenario

NASA Astrophysics Data System (ADS)

Barrera Verdejo, M.; Crewell, S.; Loehnert, U.; Di Girolamo, P.

2016-12-01

Continuous monitoring of thermodynamic atmospheric profiles is important for many applications, e.g. assessment of atmospheric stability and cloud formation. Nowadays there is a wide variety of ground-based sensors for atmospheric profiling. However, no single instrument is able to simultaneously provide measurements with complete vertical coverage, high vertical and temporal resolution, and good performance under all weather conditions. For this reason, instrument synergies of a wide range of complementary measurements are more and more considered for improving the quality of atmospheric observations. The current work presents synergetic use of a microwave radiometer (MWR) and Raman lidar (RL) within a physically consistent optimal estimation approach. On the one hand, lidar measurements provide humidity and temperature measurements with a high vertical resolution albeit with limited vertical coverage, due to overlapping function problems, sunlight contamination and the presence of clouds. On the other hand, MWRs obtain humidity, temperature and cloud information throughout the troposphere, with however only a very limited vertical resolution. The benefits of MWR+RL synergy have been previously demonstrated for clear sky cases. This work expands this approach to cloudy scenarios. Consistent retrievals of temperature, absolute and relative humidity as well as liquid water path are analyzed. In addition, different measures are presented to demonstrate the improvements achieved via the synergy compared to individual retrievals, e.g. degrees of freedom or theoretical error. We also demonstrate that, compared to the lidar, the higher temporal resolution of the MWR presents a strong advantage for capturing the high temporal variability of the liquid water cloud.. Finally, the results are compared with independent information sources, e.g. GPS or radiosondes, showing good consistency. The study demonstrates the benefits of the sensor combination, being especially strong in regions where lidar data is not available, whereas if both instruments are available, the lidar measurements dominate the retrieval.

Remote Sensing from Geostationary Orbit: GEO TROPSAT, A New Concept for Atmospheric Remote Sensing

NASA Technical Reports Server (NTRS)

Little, Alan D.; Neil, Doreen O.; Sachse, Glen W.; Fishman, Jack; Krueger, Arlin J.

1997-01-01

The Geostationary Tropospheric Pollution Satellite (GEO TROPSAT) mission is a new approach to measuring the critical constituents of tropospheric ozone chemistry: ozone, carbon monoxide, nitrogen dioxide, and aerosols. The GEO TROPSAT mission comprises a constellation of three instruments flying as secondary payloads on geostationary communications satellites around the world. This proposed approach can significantly reduce the cost of getting a science payload to geostationary orbit and also generates revenue for the satellite owners. The geostationary vantage point enables simultaneous high temporal and spatial resolution measurement of tropospheric trace gases, leading to greatly improved atmospheric ozone chemistry knowledge. The science data processing, conducted as a research (not operational) activity, will provide atmospheric trace gas data many times per day over the same region at better than 25 km ground footprint. The high temporal resolution identifies short time scale processes, diurnal variations, seasonal trends, and interannual variation.

Large scale mass redistribution and surface displacement from GRACE and SLR

NASA Astrophysics Data System (ADS)

Cheng, M.; Ries, J. C.; Tapley, B. D.

2012-12-01

Mass transport between the atmosphere, ocean and solid earth results in the temporal variations in the Earth gravity field and loading induced deformation of the Earth. Recent space-borne observations, such as GRACE mission, are providing extremely high precision temporal variations of gravity field. The results from 10-yr GRACE data has shown a significant annual variations of large scale vertical and horizontal displacements occurring over the Amazon, Himalayan region and South Asia, African, and Russian with a few mm amplitude. Improving understanding from monitoring and modeling of the large scale mass redistribution and the Earth's response are a critical for all studies in the geosciences, in particular for determination of Terrestrial Reference System (TRS), including geocenter motion. This paper will report results for the observed seasonal variations in the 3-dimentional surface displacements of SLR and GPS tracking stations and compare with the prediction from time series of GRACE monthly gravity solution.

Dissection of culture media for embryos: the most important and less important components and characteristics.

PubMed

Gardner, David K

2008-01-01

Improvements in culture media formulations have led to an increase in the ability to maintain the mammalian embryo in culture throughout the preimplantation and pre-attachment period. Amino acids and specific macromolecules have been identified as being key medium components, whereas temporal dynamics have been recognised as important media characteristics. Furthermore, other laboratory factors that directly impact embryo development and viability have been identified. Such factors include the use of a reduced oxygen tension, an appropriate incubation system and an adequate prescreening of all contact supplies. With rigourous quality systems in place, it is possible to obtain in vivo rates of embryo development in vitro using new media formulations while maintaining high levels of embryo viability. The future of embryo culture will likely be based on novel culture chips capable of providing temporal dynamics while facilitating real-time analysis of embryo physiology.

Summary statistics in auditory perception.

PubMed

McDermott, Josh H; Schemitsch, Michael; Simoncelli, Eero P

2013-04-01

Sensory signals are transduced at high resolution, but their structure must be stored in a more compact format. Here we provide evidence that the auditory system summarizes the temporal details of sounds using time-averaged statistics. We measured discrimination of 'sound textures' that were characterized by particular statistical properties, as normally result from the superposition of many acoustic features in auditory scenes. When listeners discriminated examples of different textures, performance improved with excerpt duration. In contrast, when listeners discriminated different examples of the same texture, performance declined with duration, a paradoxical result given that the information available for discrimination grows with duration. These results indicate that once these sounds are of moderate length, the brain's representation is limited to time-averaged statistics, which, for different examples of the same texture, converge to the same values with increasing duration. Such statistical representations produce good categorical discrimination, but limit the ability to discern temporal detail.

Efficient robust reconstruction of dynamic PET activity maps with radioisotope decay constraints.

PubMed

Gao, Fei; Liu, Huafeng; Shi, Pengcheng

2010-01-01

Dynamic PET imaging performs sequence of data acquisition in order to provide visualization and quantification of physiological changes in specific tissues and organs. The reconstruction of activity maps is generally the first step in dynamic PET. State space Hinfinity approaches have been proved to be a robust method for PET image reconstruction where, however, temporal constraints are not considered during the reconstruction process. In addition, the state space strategies for PET image reconstruction have been computationally prohibitive for practical usage because of the need for matrix inversion. In this paper, we present a minimax formulation of the dynamic PET imaging problem where a radioisotope decay model is employed as physics-based temporal constraints on the photon counts. Furthermore, a robust steady state Hinfinity filter is developed to significantly improve the computational efficiency with minimal loss of accuracy. Experiments are conducted on Monte Carlo simulated image sequences for quantitative analysis and validation.

Improving depiction of temporal bone anatomy with low-radiation dose CT by an integrated circuit detector in pediatric patients: a preliminary study.

PubMed

He, Jingzhen; Zu, Yuliang; Wang, Qing; Ma, Xiangxing

2014-12-01

The purpose of this study was to determine the performance of low-dose computed tomography (CT) scanning with integrated circuit (IC) detector in defining fine structures of temporal bone in children by comparing with the conventional detector. The study was performed with the approval of our institutional review board and the patients' anonymity was maintained. A total of 86 children<3 years of age underwent imaging of temporal bone with low-dose CT (80 kV/150 mAs) equipped with either IC detector or conventional discrete circuit (DC) detector. The image noise was measured for quantitative analysis. Thirty-five structures of temporal bone were further assessed and rated by 2 radiologists for qualitative analysis. κ Statistics were performed to determine the agreement reached between the 2 radiologists on each image. Mann-Whitney U test was used to determine the difference in image quality between the 2 detector systems. Objective analysis showed that the image noise was significantly lower (P<0.001) with the IC detector than with the DC detector. The κ values for qualitative assessment of the 35 fine anatomical structures revealed high interobserver agreement. The delineation for 30 of the 35 landmarks (86%) with the IC detector was superior to that with the conventional DC detector (P<0.05) although there were no differences in the delineation of the remaining 5 structures (P>0.05). The low-dose CT images acquired with the IC detector provide better depiction of fine osseous structures of temporal bone than that with the conventional DC detector.

A Sensitive Dynamic and Active Pixel Vision Sensor for Color or Neural Imaging Applications.

PubMed

Moeys, Diederik Paul; Corradi, Federico; Li, Chenghan; Bamford, Simeon A; Longinotti, Luca; Voigt, Fabian F; Berry, Stewart; Taverni, Gemma; Helmchen, Fritjof; Delbruck, Tobi

2018-02-01

Applications requiring detection of small visual contrast require high sensitivity. Event cameras can provide higher dynamic range (DR) and reduce data rate and latency, but most existing event cameras have limited sensitivity. This paper presents the results of a 180-nm Towerjazz CIS process vision sensor called SDAVIS192. It outputs temporal contrast dynamic vision sensor (DVS) events and conventional active pixel sensor frames. The SDAVIS192 improves on previous DAVIS sensors with higher sensitivity for temporal contrast. The temporal contrast thresholds can be set down to 1% for negative changes in logarithmic intensity (OFF events) and down to 3.5% for positive changes (ON events). The achievement is possible through the adoption of an in-pixel preamplification stage. This preamplifier reduces the effective intrascene DR of the sensor (70 dB for OFF and 50 dB for ON), but an automated operating region control allows up to at least 110-dB DR for OFF events. A second contribution of this paper is the development of characterization methodology for measuring DVS event detection thresholds by incorporating a measure of signal-to-noise ratio (SNR). At average SNR of 30 dB, the DVS temporal contrast threshold fixed pattern noise is measured to be 0.3%-0.8% temporal contrast. Results comparing monochrome and RGBW color filter array DVS events are presented. The higher sensitivity of SDAVIS192 make this sensor potentially useful for calcium imaging, as shown in a recording from cultured neurons expressing calcium sensitive green fluorescent protein GCaMP6f.

On the Comparison of the Global Surface Soil Moisture product and Land Surface Modeling

NASA Astrophysics Data System (ADS)

Delorme, B., Jr.; Ottlé, C.; Peylin, P.; Polcher, J.

2016-12-01

Thanks to its large spatio-temporal coverage, the new ESA CCI multi-instruments dataset offers a good opportunity to assess and improve land surface models parametrization. In this study, the ESA CCI surface soil moisture (SSM) combined product (v2.2) has been compared to the simulated top first layers of the ORCHIDEE LSM (the continental part of the IPSL earth system model), in order to evaluate its potential of improvements with data assimilation techniques. The ambition of the work was to develop a comprehensive comparison methodology by analyzing simultaneously the temporal and spatial structures of both datasets. We analyzed the SSM synoptic, seasonal, and inter-annual variations by decomposing the signals into fast and slow components. ORCHIDEE was shown to adequately reproduce the observed SSM dynamics in terms of temporal correlation. However, these correlation scores are supposed to be strongly influenced by SSM seasonal variability and the quality of the model input forcing. Autocorrelation and spectral analyses brought out disagreements in the temporal inertia of the upper soil moisture reservoirs. By linking our results to land cover maps, we found that ORCHIDEE is more dependent on rainfall events compared to the observations in regions with sparse vegetation cover. These diflerences might be due to a wrong partition of rainfall between soil evaporation, transpiration, runofl and drainage in ORCHIDEE. To refine this analysis, a single value decomposition (SVD) of the co-variability between rainfall provided by WFDEI and soil moisture was pursued over Central Europe and South Africa. It showed that spatio-temporal co-varying patterns between ORCHIDEE and rainfall and the ESA-CCI product and rainfall are in relatively good agreement. However, the leading SVD pattern, which exhibits a strong annual cycle and explains the same portion of covariance for both datasets, explains a much larger fraction of variance for ORCHIDEE than for the ESA-CCI product. These results highlight that the role of other surface variables presenting a strong seasonal variability (like vegetation cover, possibly irrigation) is not accounted for similarly in both the model and the product, and that further work is needed to explore these discrepancies.

Adaptation and Mitigation in Agriculture: A Review of Synergies and Tradeoffs and How EO Could Improve Understanding and Outcomes

NASA Astrophysics Data System (ADS)

Barbieri, L.; Wollenberg, E.

2017-12-01

We present a review of the published literature on agricultural adaptation and mitigation, and report on the current evidence as to whether changes in agricultural practices meant to achieve mitigation or adaptation goals can be dual purpose: simultaneously reducing greenhouse gas (GHG) emissions and helping to facilitate adaptation. We characterize the spatio-temporal and system trends in how adaptation and mitigation outcomes are being achieved, and report on the current technical and knowledge gaps that exist and where Earth observations (EO) could improve our understanding. Agriculture contributes 12% GHG emissions globally, roughly one third from the developing world. Nearly 70% of the technical mitigation potential in agriculture sector occurs in these countries, however, while the mitigation potential is high, agricultural productivity also relies heavily on climate factors. With climate change, agricultural systems already, and will increasingly, need to adapt to extreme events and variability in temperatures and precipitation. This underscores the importance of implementing agricultural practices that can both reduce GHG emissions and help facilitate adaptation. Until recently, these objectives have been treated separately, but policy makers are increasingly calling for a joint approach to improve synergies, and avoid tradeoffs. There remain many complications in considering a joint approach: lack of clear conceptual frameworks, knowledge gaps in scientific understanding and evidence associated with adaptation and mitigation outcomes, and the abilities and motivations of stakeholders to consider both objectives. We review 56 peer-reviewed publications and present results from an in-depth analysis to answer two major concerns: to what extent is evidence provided for claims of synergistic outcomes, and what uncertainty surrounds this evidence. Our results show that only 21% of studies empirically measured both mitigation and adaptation outcomes, and claims of synergies are not well substantiated, and evidence is provided at questionable spatio-temporal scales. We highlight information that could be provided by coordinated, comprehensive and sustained EO which could benefit this critical goal of simultaneously achieving agricultural adaptation and mitigation.

The Satellite View of Extra-Tropical Stratosphere-Troposphere Exchange and the UT/LS

NASA Technical Reports Server (NTRS)

Schoeberl, Mark R.

2004-01-01

This talk will review satellite studies which have helped define the UT/LS and stratosphere-troposphere exchange. Satellites have provided a global perspective but have had limited temporal and spatial measurements for stratosphere-troposphere exchange (STE) studies. Nonetheless, long lived tracer measurements from satellites can be used as proxies for age-of-air can thus provide estimates of mixing and transport processes in the UT/LS. These measurements can be compared to model estimates of the mean age-of-air and trace gas fluxes providing an important model diagnostic. With the launch of EOS Aura, the potential for satellite trace gas measurements of the lower-most stratosphere and STE is significantly improved, and Aura s mission will be briefly described.

Temporal signal processing of dolphin biosonar echoes from salmon prey.

PubMed

Au, Whitlow W L; Ou, Hui Helen

2014-08-01

Killer whales project short broadband biosonar clicks. The broadband nature of the clicks provides good temporal resolution of echo highlights and allows for the discriminations of salmon prey. The echoes contain many highlights as the signals reflect off different surfaces and parts of the fish body and swim bladder. The temporal characteristics of echoes from salmon are highly aspect dependent and six temporal parameters were used in a support vector machine to discriminate between species. Results suggest that killer whales can classify salmon based on their echoes and provide some insight as to which features might enable the classification.

Electrical brain activity and response to olanzapine in schizophrenia: a study with LORETA images of P300.

PubMed

Sumiyoshi, Tomiki; Higuchi, Yuko; Kawasaki, Yasuhiro; Matsui, Mie; Kato, Kanade; Yuuki, Hiromi; Arai, Hirofumi; Kurachi, Masayoshi

2006-09-30

The aim of this study was to evaluate the change in the distribution for the P300 generator, as demonstrated by Low Resolution Electromagnetic Tomography (LORETA) images, in patients with schizophrenia during treatment with olanzapine. Data were obtained from five right-handed patients treated with olanzapine for 6 months. Five right-handed normal volunteers also participated in the study. LORETA images of P300 in response to the odd-ball auditory discrimination task revealed a left dominant lateralized high current source density in the temporal lobes in all control subjects. Although this pattern of brain activation was not evident in patients at baseline, 6-month treatment with olanzapine recovered the left dominant pattern of the electrical density in the temporal regions, such as the Heschl gyrus, and improved performance on a test of verbal learning and memory. Scores of the Brief Psychiatric Rating Scale and the Global Assessment of Functioning Scale also improved during treatment. These results provide the first suggestion that enhancement of verbal memory and the functional status by treatment with some antipsychotic drugs may be associated with modulations of the anatomical configuration of electrical brain activity in patients with schizophrenia.

An Inexpensive High-Temporal Resolution Electronic Sun Journal for Monitoring Personal Day to Day Sun Exposure Patterns

PubMed Central

Downs, Nathan J.; Parisi, Alfio V.; Butler, Harry; Rawlings, Alex; Elrahoumi, Raja Salem

2017-01-01

Exposure to natural sunlight, specifically solar ultraviolet (UV) radiation contributes to lifetime risks of skin cancer, eye disease, and diseases associated with vitamin D insufficiency. Improved knowledge of personal sun exposure patterns can inform public health policy; and help target high-risk population groups. Subsequently, an extensive number of studies have been conducted to measure personal solar UV exposure in a variety of settings. Many of these studies, however, use digital or paper-based journals (self-reported volunteer recall), or employ cost prohibitive electronic UV dosimeters (that limit the size of sample populations), to estimate periods of exposure. A cost effective personal electronic sun journal (ESJ) built from readily available infrared photodiodes is presented in this research. The ESJ can be used to complement traditional UV dosimeters that measure total biologically effective exposure by providing a time-stamped sun exposure record. The ESJ can be easily attached to clothing and data logged to personal devices (including fitness monitors or smartphones). The ESJ improves upon self-reported exposure recording and is a cost effective high-temporal resolution option for monitoring personal sun exposure behavior in large population studies. PMID:29201865

Intelligent Performance Analysis with a Natural Language Interface

NASA Astrophysics Data System (ADS)

Juuso, Esko K.

2017-09-01

Performance improvement is taken as the primary goal in the asset management. Advanced data analysis is needed to efficiently integrate condition monitoring data into the operation and maintenance. Intelligent stress and condition indices have been developed for control and condition monitoring by combining generalized norms with efficient nonlinear scaling. These nonlinear scaling methodologies can also be used to handle performance measures used for management since management oriented indicators can be presented in the same scale as intelligent condition and stress indices. Performance indicators are responses of the process, machine or system to the stress contributions analyzed from process and condition monitoring data. Scaled values are directly used in intelligent temporal analysis to calculate fluctuations and trends. All these methodologies can be used in prognostics and fatigue prediction. The meanings of the variables are beneficial in extracting expert knowledge and representing information in natural language. The idea of dividing the problems into the variable specific meanings and the directions of interactions provides various improvements for performance monitoring and decision making. The integrated temporal analysis and uncertainty processing facilitates the efficient use of domain expertise. Measurements can be monitored with generalized statistical process control (GSPC) based on the same scaling functions.

Voice gender discrimination provides a measure of more than pitch-related perception in cochlear implant users

PubMed Central

Li, Tianhao; Fu, Qian-Jie

2013-01-01

Objectives (1) To investigate whether voice gender discrimination (VGD) could be a useful indicator of the spectral and temporal processing abilities of individual cochlear implant (CI) users; (2) To examine the relationship between VGD and speech recognition with CI when comparable acoustic cues are used for both perception processes. Design VGD was measured using two talker sets with different inter-gender fundamental frequencies (F0), as well as different acoustic CI simulations. Vowel and consonant recognition in quiet and noise were also measured and compared with VGD performance. Study sample Eleven postlingually deaf CI users. Results The results showed that (1) mean VGD performance differed for different stimulus sets, (2) VGD and speech recognition performance varied among individual CI users, and (3) individual VGD performance was significantly correlated with speech recognition performance under certain conditions. Conclusions VGD measured with selected stimulus sets might be useful for assessing not only pitch-related perception, but also spectral and temporal processing by individual CI users. In addition to improvements in spectral resolution and modulation detection, the improvement in higher modulation frequency discrimination might be particularly important for CI users in noisy environments. PMID:21696330

Improvements in Raman Lidar Measurements Using New Interference Filter Technology

NASA Technical Reports Server (NTRS)

Whiteman, David N.; Potter, John R.; Tola, Rebecca; Veselovskii, Igor; Cadirola, Martin; Rush, Kurt; Comer, Joseph

2006-01-01

Narrow-band interference filters with improved transmission in the ultra-violet have been developed under NASA-funded research and used in the Raman Airborne Spectroscopic Lidar (RASL) in ground-based, upward-looking tests. Measurements were made of atmospheric water vapor, cirrus cloud optical properties and carbon dioxide that improve upon any previously demonstrated using Raman lidar. Daytime boundary and mixed layer profiling of water vapor mixing ratio up to an altitude of approximately 4 h is performed with less than 5% random error using temporal and spatial resolution of 2-minutes and 60 - 210, respectively. Daytime cirrus cloud optical depth and extinction-to-backscatter ratio measurements are made using 1 -minute average. Sufficient signal strength is demonstrated to permit the simultaneous profiling of carbon dioxide and water vapor mixing ratio into the free troposphere during the nighttime. A description of the filter technology developments is provided followed by examples of the improved Raman lidar measurements.

Corrections to the MODIS Aqua Calibration Derived From MODIS Aqua Ocean Color Products

NASA Technical Reports Server (NTRS)

Meister, Gerhard; Franz, Bryan Alden

2013-01-01

Ocean color products such as, e.g., chlorophyll-a concentration, can be derived from the top-of-atmosphere radiances measured by imaging sensors on earth-orbiting satellites. There are currently three National Aeronautics and Space Administration sensors in orbit capable of providing ocean color products. One of these sensors is the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Aqua satellite, whose ocean color products are currently the most widely used of the three. A recent improvement to the MODIS calibration methodology has used land targets to improve the calibration accuracy. This study evaluates the new calibration methodology and describes further calibration improvements that are built upon the new methodology by including ocean measurements in the form of global temporally averaged water-leaving reflectance measurements. The calibration improvements presented here mainly modify the calibration at the scan edges, taking advantage of the good performance of the land target trending in the center of the scan.

Microsurgical anatomy of the transsylvian translimen insula approach to the mediobasal temporal lobe: Technical considerations and case illustration.

PubMed

Straus, David; Byrne, Richard W; Sani, Sepehr; Serici, Anthony; Moftakhar, Roham

2013-01-01

Various vascular, neoplastic, and epileptogenic pathologies occur in the mediobasal temporal region. A transsylvian translimen insula (TTI) approach can be used as an alternative to temporal transcortical approach to the mediobasal temporal region. The aim of this study was to demonstrate the surgical anatomy of the TTI approach, including the gyral, sulcal, and vascular anatomy in and around the limen insula. The use of this approach is illustrated in the resection of a complex arteriovenous malformation. The TTI approach to the mediobasal temporal region was performed on three silicone-injected cadaveric heads. The gyral, sulcal, and arterial anatomy of the limen insula was studied in six formalin-fixed injected hemispheres. The TTI approach provided access to the anterior and middle segments of the mediobasal temporal lobe region as well as allowing access to temporal horn of the lateral ventricle. Using this approach we were able to successfully resect an arteriovenous malformation of the dominant medial temporal lobe. The TTI approach provides a viable surgical route to the region of mediobasal temporal lobe region. This approach offers an advantage over the temporal transcortical route in that there is less risk of damage to optic radiations and speech area in the dominant hemisphere.

Decoding-Accuracy-Based Sequential Dimensionality Reduction of Spatio-Temporal Neural Activities

NASA Astrophysics Data System (ADS)

Funamizu, Akihiro; Kanzaki, Ryohei; Takahashi, Hirokazu

Performance of a brain machine interface (BMI) critically depends on selection of input data because information embedded in the neural activities is highly redundant. In addition, properly selected input data with a reduced dimension leads to improvement of decoding generalization ability and decrease of computational efforts, both of which are significant advantages for the clinical applications. In the present paper, we propose an algorithm of sequential dimensionality reduction (SDR) that effectively extracts motor/sensory related spatio-temporal neural activities. The algorithm gradually reduces input data dimension by dropping neural data spatio-temporally so as not to undermine the decoding accuracy as far as possible. Support vector machine (SVM) was used as the decoder, and tone-induced neural activities in rat auditory cortices were decoded into the test tone frequencies. SDR reduced the input data dimension to a quarter and significantly improved the accuracy of decoding of novel data. Moreover, spatio-temporal neural activity patterns selected by SDR resulted in significantly higher accuracy than high spike rate patterns or conventionally used spatial patterns. These results suggest that the proposed algorithm can improve the generalization ability and decrease the computational effort of decoding.

Musical Scales in Tone Sequences Improve Temporal Accuracy.

PubMed

Li, Min S; Di Luca, Massimiliano

2018-01-01

Predicting the time of stimulus onset is a key component in perception. Previous investigations of perceived timing have focused on the effect of stimulus properties such as rhythm and temporal irregularity, but the influence of non-temporal properties and their role in predicting stimulus timing has not been exhaustively considered. The present study aims to understand how a non-temporal pattern in a sequence of regularly timed stimuli could improve or bias the detection of temporal deviations. We presented interspersed sequences of 3, 4, 5, and 6 auditory tones where only the timing of the last stimulus could slightly deviate from isochrony. Participants reported whether the last tone was 'earlier' or 'later' relative to the expected regular timing. In two conditions, the tones composing the sequence were either organized into musical scales or they were random tones. In one experiment, all sequences ended with the same tone; in the other experiment, each sequence ended with a different tone. Results indicate higher discriminability of anisochrony with musical scales and with longer sequences, irrespective of the knowledge of the final tone. Such an outcome suggests that the predictability of non-temporal properties, as enabled by the musical scale pattern, can be a factor in determining the sensitivity of time judgments.

Standardized shrinking LORETA-FOCUSS (SSLOFO): a new algorithm for spatio-temporal EEG source reconstruction.

PubMed

Liu, Hesheng; Schimpf, Paul H; Dong, Guoya; Gao, Xiaorong; Yang, Fusheng; Gao, Shangkai

2005-10-01

This paper presents a new algorithm called Standardized Shrinking LORETA-FOCUSS (SSLOFO) for solving the electroencephalogram (EEG) inverse problem. Multiple techniques are combined in a single procedure to robustly reconstruct the underlying source distribution with high spatial resolution. This algorithm uses a recursive process which takes the smooth estimate of sLORETA as initialization and then employs the re-weighted minimum norm introduced by FOCUSS. An important technique called standardization is involved in the recursive process to enhance the localization ability. The algorithm is further improved by automatically adjusting the source space according to the estimate of the previous step, and by the inclusion of temporal information. Simulation studies are carried out on both spherical and realistic head models. The algorithm achieves very good localization ability on noise-free data. It is capable of recovering complex source configurations with arbitrary shapes and can produce high quality images of extended source distributions. We also characterized the performance with noisy data in a realistic head model. An important feature of this algorithm is that the temporal waveforms are clearly reconstructed, even for closely spaced sources. This provides a convenient way to estimate neural dynamics directly from the cortical sources.

Methods for evaluating temporal trends in noise exposure

PubMed Central

Neitzel, RL; Galusha, D; Dixon-Ernst, C; Rabinowitz, PM

2014-01-01

Objective Hearing conservation programs have been mandatory in many US industries since 1983. Since then, three program elements (audiometric testing, hearing protection, and training) have been the focus of much research. By comparison, little has been done on noise exposure evaluation. Design and study sample Utilizing a large dataset (>10,000 measurements over 20 years) from eight facilities operated by a multinational aluminum manufacturing company, we evaluated several approaches to assessing temporal trends in Time Weighted Average (TWA) exposures and the fraction of measurements exceeding 85 dBA by facility, by exposure group within facility, and by individual worker within facility. Results Overall, exposures declined across locations over the study period. Several facilities demonstrated substantial reductions in exposure, and the results of mean noise levels and exceedance fractions generally showed good agreement. The results of analyses at the individual level diverged with analyses by facility and exposure group within facility, suggesting that individual-level analyses, while challenging, may provide important information not available from coarser levels of analysis. Conclusions Validated metrics are needed to allow for assessment of temporal trends in noise exposure. Such metrics will improve our ability to characterize, in a standardized manner, efforts to reduce noise-induced hearing loss. PMID:24564696

Methods for evaluating temporal trends in noise exposure.

PubMed

Neitzel, R L; Galusha, D; Dixon-Ernst, C; Rabinowitz, P M

2014-03-01

Hearing conservation programs have been mandatory in many US industries since 1983. Since then, three program elements (audiometric testing, hearing protection, and training) have been the focus of much research. By comparison, little has been done on noise exposure evaluation. Temporal trends in time weighted average (TWA) exposures and the fraction of measurements exceeding 85 dBA were evaluated by facility, by exposure group within facility, and by individual worker within facility. A large dataset (> 10 000 measurements over 20 years) from eight facilities operated by a multinational aluminum manufacturing company was studied. Overall, exposures declined across locations over the study period. Several facilities demonstrated substantial reductions in exposure, and the results of mean noise levels and exceedance fractions generally showed good agreement. The results of analyses at the individual level diverged with analyses by facility and exposure group within facility, suggesting that individual-level analyses, while challenging, may provide important information not available from coarser levels of analysis. Validated metrics are needed to allow for assessment of temporal trends in noise exposure. Such metrics will improve our ability to characterize, in a standardized manner, efforts to reduce noise-induced hearing loss.

Speaker recognition with temporal cues in acoustic and electric hearing

NASA Astrophysics Data System (ADS)

Vongphoe, Michael; Zeng, Fan-Gang

2005-08-01

Natural spoken language processing includes not only speech recognition but also identification of the speaker's gender, age, emotional, and social status. Our purpose in this study is to evaluate whether temporal cues are sufficient to support both speech and speaker recognition. Ten cochlear-implant and six normal-hearing subjects were presented with vowel tokens spoken by three men, three women, two boys, and two girls. In one condition, the subject was asked to recognize the vowel. In the other condition, the subject was asked to identify the speaker. Extensive training was provided for the speaker recognition task. Normal-hearing subjects achieved nearly perfect performance in both tasks. Cochlear-implant subjects achieved good performance in vowel recognition but poor performance in speaker recognition. The level of the cochlear implant performance was functionally equivalent to normal performance with eight spectral bands for vowel recognition but only to one band for speaker recognition. These results show a disassociation between speech and speaker recognition with primarily temporal cues, highlighting the limitation of current speech processing strategies in cochlear implants. Several methods, including explicit encoding of fundamental frequency and frequency modulation, are proposed to improve speaker recognition for current cochlear implant users.

Planning nonlinear access paths for temporal bone surgery.

PubMed

Fauser, Johannes; Sakas, Georgios; Mukhopadhyay, Anirban

2018-05-01

Interventions at the otobasis operate in the narrow region of the temporal bone where several highly sensitive organs define obstacles with minimal clearance for surgical instruments. Nonlinear trajectories for potential minimally invasive interventions can provide larger distances to risk structures and optimized orientations of surgical instruments, thus improving clinical outcomes when compared to existing linear approaches. In this paper, we present fast and accurate planning methods for such nonlinear access paths. We define a specific motion planning problem in [Formula: see text] with notable constraints in computation time and goal pose that reflect the requirements of temporal bone surgery. We then present [Formula: see text]-RRT-Connect: two suitable motion planners based on bidirectional Rapidly exploring Random Tree (RRT) to solve this problem efficiently. The benefits of [Formula: see text]-RRT-Connect are demonstrated on real CT data of patients. Their general performance is shown on a large set of realistic synthetic anatomies. We also show that these new algorithms outperform state-of-the-art methods based on circular arcs or Bézier-Splines when applied to this specific problem. With this work, we demonstrate that preoperative and intra-operative planning of nonlinear access paths is possible for minimally invasive surgeries at the otobasis.

Temporal Properties of Liquid Crystal Displays: Implications for Vision Science Experiments

PubMed Central

Elze, Tobias; Tanner, Thomas G.

2012-01-01

Liquid crystal displays (LCD) are currently replacing the previously dominant cathode ray tubes (CRT) in most vision science applications. While the properties of the CRT technology are widely known among vision scientists, the photometric and temporal properties of LCDs are unfamiliar to many practitioners. We provide the essential theory, present measurements to assess the temporal properties of different LCD panel types, and identify the main determinants of the photometric output. Our measurements demonstrate that the specifications of the manufacturers are insufficient for proper display selection and control for most purposes. Furthermore, we show how several novel display technologies developed to improve fast transitions or the appearance of moving objects may be accompanied by side–effects in some areas of vision research. Finally, we unveil a number of surprising technical deficiencies. The use of LCDs may cause problems in several areas in vision science. Aside from the well–known issue of motion blur, the main problems are the lack of reliable and precise onsets and offsets of displayed stimuli, several undesirable and uncontrolled components of the photometric output, and input lags which make LCDs problematic for real–time applications. As a result, LCDs require extensive individual measurements prior to applications in vision science. PMID:22984458

Sequential detection of temporal communities by estrangement confinement.

PubMed

Kawadia, Vikas; Sreenivasan, Sameet

2012-01-01

Temporal communities are the result of a consistent partitioning of nodes across multiple snapshots of an evolving network, and they provide insights into how dense clusters in a network emerge, combine, split and decay over time. To reliably detect temporal communities we need to not only find a good community partition in a given snapshot but also ensure that it bears some similarity to the partition(s) found in the previous snapshot(s), a particularly difficult task given the extreme sensitivity of community structure yielded by current methods to changes in the network structure. Here, motivated by the inertia of inter-node relationships, we present a new measure of partition distance called estrangement, and show that constraining estrangement enables one to find meaningful temporal communities at various degrees of temporal smoothness in diverse real-world datasets. Estrangement confinement thus provides a principled approach to uncovering temporal communities in evolving networks.

Spatio-temporal Analysis for New York State SPARCS Data

PubMed Central

Chen, Xin; Wang, Yu; Schoenfeld, Elinor; Saltz, Mary; Saltz, Joel; Wang, Fusheng

2017-01-01

Increased accessibility of health data provides unique opportunities to discover spatio-temporal patterns of diseases. For example, New York State SPARCS (Statewide Planning and Research Cooperative System) data collects patient level detail on patient demographics, diagnoses, services, and charges for each hospital inpatient stay and outpatient visit. Such data also provides home addresses for each patient. This paper presents our preliminary work on spatial, temporal, and spatial-temporal analysis of disease patterns for New York State using SPARCS data. We analyzed spatial distribution patterns of typical diseases at ZIP code level. We performed temporal analysis of common diseases based on 12 years’ historical data. We then compared the spatial variations for diseases with different levels of clustering tendency, and studied the evolution history of such spatial patterns. Case studies based on asthma demonstrated that the discovered spatial clusters are consistent with prior studies. We visualized our spatial-temporal patterns as animations through videos. PMID:28815148

Temporal Characteristics of Electron Flux Events at Geosynchronous Orbit

NASA Astrophysics Data System (ADS)

Olson, D. K.; Larsen, B.; Henderson, M. G.

2017-12-01

Geosynchronous satellites such as the LANL-GEO fleet are exposed to hazardous conditions when they encounter regions of hot, intense plasma such as that from the plasma sheet. These conditions can lead to the build-up of charge on the surface of a spacecraft, with undesired, and often dangerous, side effects. Observation of electron flux levels at geosynchronous orbit (GEO) with multiple satellites provides a unique view of plasma sheet access to that region. Flux "events", or periods when fluxes are elevated continuously above the LANL-GEO spacecraft charging threshold, can be characterized by duration in two dimensions: a spatial dimension of local time, describing the duration of an event from the perspective of a single spacecraft, and a temporal dimension describing the duration in time in which high energy plasma sheet particles have access to geosynchronous orbit. We examine the statistical properties of the temporal duration of 8 keV electron flux events at geosynchronous orbit over a twelve-year period. These results, coupled with the spatial duration characteristics, provide the key information needed to formulate a statistical model for forecasting the electron flux conditions at GEO that are correlated with LANL-GEO surface charging. Forecasting models are an essential component to understanding space weather and mitigating the dangers of surface charging on our satellites. We also examine the correlation of flux event durations with solar wind parameters and geomagnetic indices, identifying the data needed to improve upon a statistical forecasting model

Comparative analysis of recent satellite missions for multi-temporal SAR interferometry

NASA Astrophysics Data System (ADS)

Bovenga, Fabio; Refice, Alberto; Belmonte, Antonella; Pasquariello, Guido

2016-10-01

Multi-temporal InSAR (MTI) applications pose challenges related to the availability of coherent scattering from the ground surface, the complexity of the ground deformations, the atmospheric artifacts, the visibility problems related to the ground elevation. Nowadays, several satellite missions are available providing interferometric SAR data at different wavelengths, spatial resolutions, and revisit time. A new interesting opportunity is provided by Sentinel-1 mission, which has a spatial resolution comparable to previous ESA C-band missions, and revisit times reduced to up to 6 days. It is envisioned that, by offering regular, global-scale coverage, improved temporal resolution and freely available imagery, Sentinel-1 will guarantee an increasing use of MTI for ground displacement investigations. According to these different SAR space-borne missions, the present work discusses current and future opportunities of MTI applications to ground instability monitoring. Issues related to coherent target detection and mean velocity precision will be addressed through a simple theoretical model assuming backscattering mechanisms related to point scatterers. The paper also presents an example of multi-sensor ground instability investigation over the site of Marina di Lesina, Southern Italy, a village lying over a gypsum diapir, where a hydration process, involving the underlying anhydride, causes a smooth uplift pattern affecting the entire village area, and the formation of scattered sinkholes. More than 20 years of MTI SAR data have been used, coming from both legacy ERS and ENVISAT missions, and last-generation Radarsat-2, COSMO-SkyMed, and Sentinel-1A sensors.

Rain radar measurement error estimation using data assimilation in an advection-based nowcasting system

NASA Astrophysics Data System (ADS)

Merker, Claire; Ament, Felix; Clemens, Marco

2017-04-01

The quantification of measurement uncertainty for rain radar data remains challenging. Radar reflectivity measurements are affected, amongst other things, by calibration errors, noise, blocking and clutter, and attenuation. Their combined impact on measurement accuracy is difficult to quantify due to incomplete process understanding and complex interdependencies. An improved quality assessment of rain radar measurements is of interest for applications both in meteorology and hydrology, for example for precipitation ensemble generation, rainfall runoff simulations, or in data assimilation for numerical weather prediction. Especially a detailed description of the spatial and temporal structure of errors is beneficial in order to make best use of the areal precipitation information provided by radars. Radar precipitation ensembles are one promising approach to represent spatially variable radar measurement errors. We present a method combining ensemble radar precipitation nowcasting with data assimilation to estimate radar measurement uncertainty at each pixel. This combination of ensemble forecast and observation yields a consistent spatial and temporal evolution of the radar error field. We use an advection-based nowcasting method to generate an ensemble reflectivity forecast from initial data of a rain radar network. Subsequently, reflectivity data from single radars is assimilated into the forecast using the Local Ensemble Transform Kalman Filter. The spread of the resulting analysis ensemble provides a flow-dependent, spatially and temporally correlated reflectivity error estimate at each pixel. We will present first case studies that illustrate the method using data from a high-resolution X-band radar network.

Spatiotemporal Filtering Using Principal Component Analysis and Karhunen-Loeve Expansion Approaches for Regional GPS Network Analysis

NASA Technical Reports Server (NTRS)

Dong, D.; Fang, P.; Bock, F.; Webb, F.; Prawirondirdjo, L.; Kedar, S.; Jamason, P.

2006-01-01

Spatial filtering is an effective way to improve the precision of coordinate time series for regional GPS networks by reducing so-called common mode errors, thereby providing better resolution for detecting weak or transient deformation signals. The commonly used approach to regional filtering assumes that the common mode error is spatially uniform, which is a good approximation for networks of hundreds of kilometers extent, but breaks down as the spatial extent increases. A more rigorous approach should remove the assumption of spatially uniform distribution and let the data themselves reveal the spatial distribution of the common mode error. The principal component analysis (PCA) and the Karhunen-Loeve expansion (KLE) both decompose network time series into a set of temporally varying modes and their spatial responses. Therefore they provide a mathematical framework to perform spatiotemporal filtering.We apply the combination of PCA and KLE to daily station coordinate time series of the Southern California Integrated GPS Network (SCIGN) for the period 2000 to 2004. We demonstrate that spatially and temporally correlated common mode errors are the dominant error source in daily GPS solutions. The spatial characteristics of the common mode errors are close to uniform for all east, north, and vertical components, which implies a very long wavelength source for the common mode errors, compared to the spatial extent of the GPS network in southern California. Furthermore, the common mode errors exhibit temporally nonrandom patterns.

Understanding high magnitude flood risk: evidence from the past

NASA Astrophysics Data System (ADS)

MacDonald, N.

2009-04-01

The average length of gauged river flow records in the UK is ~25 years, which presents a problem in determining flood risk for high-magnitude flood events. Severe floods have been recorded in many UK catchments during the past 10 years, increasing the uncertainty in conventional flood risk estimates based on river flow records. Current uncertainty in flood risk has implications for society (insurance costs), individuals (personal vulnerability) and water resource managers (flood/drought risk). An alternative approach is required which can improve current understanding of the flood frequency/magnitude relationship. Historical documentary accounts are now recognised as a valuable resource when considering the flood frequency/magnitude relationship, but little consideration has been given to the temporal and spatial distribution of these records. Building on previous research based on British rivers (urban centre): Ouse (York), Trent (Nottingham), Tay (Perth), Severn (Shrewsbury), Dee (Chester), Great Ouse (Cambridge), Sussex Ouse (Lewes), Thames (Oxford), Tweed (Kelso) and Tyne (Hexham), this work considers the spatial and temporal distribution of historical flooding. The selected sites provide a network covering many of the largest river catchments in Britain, based on urban centres with long detailed documentary flood histories. The chronologies offer an opportunity to assess long-term patterns of flooding, indirectly determining periods of climatic variability and potentially increased geomorphic activity. This research represents the first coherent large scale analysis undertaken of historical multi-catchment flood chronologies, providing an unparalleled network of sites, permitting analysis of the spatial and temporal distribution of historical flood patterns on a national scale.

Wave-driven spatial and temporal variability in sea-floor sediment mobility in the Monterey Bay, Cordell Bank, and Gulf of the Farallones National Marine Sanctuaries

USGS Publications Warehouse

Storlazzi, Curt D.; Reid, Jane A.; Golden, Nadine E.

2007-01-01

Wind and wave patterns affect many aspects of continental shelves and shorelines geomorphic evolution. Although our understanding of the processes controlling sediment suspension on continental shelves has improved over the past decade, our ability to predict sediment mobility over large spatial and temporal scales remains limited. The deployment of robust operational buoys along the U.S. West Coast in the early 1980s provides large quantities of high-resolution oceanographic and meteorologic data. By 2006, these data sets were long enough to clearly identify long-term trends and compute statistically significant probability estimates of wave and wind behavior during annual and interannual climatic cycles (that is, El Niño and La Niña). Wave-induced sediment mobility on the shelf and upper slope off central California was modeled using synthesized oceanographic and meteorologic data as boundary input for the Delft SWAN model, sea-floor grain-size data provided by the usSEABED database, and regional bathymetry. Differences in waves (heights, periods, and directions) and winds (speeds and directions) between El Niño and La Niña months cause temporal and spatial variations in peak wave-induced bed shear stresses. These variations, in conjunction with spatially heterogeneous unconsolidated sea-floor sedimentary cover, result in predicted sediment mobility widely varying in both time and space. These findings indicate that these factors have significant consequences for both geological and biological processes.

Improved detection following Neuro-Eye Therapy in patients with post-geniculate brain damage.

PubMed

Sahraie, Arash; Macleod, Mary-Joan; Trevethan, Ceri T; Robson, Siân E; Olson, John A; Callaghan, Paula; Yip, Brigitte

2010-09-01

Damage to the optic radiation or the occipital cortex results in loss of vision in the contralateral visual field, termed partial cortical blindness or hemianopia. Previously, we have demonstrated that stimulation in the field defect using visual stimuli with optimal properties for blindsight detection can lead to increases in visual sensitivity within the blind field of a group of patients. The present study was aimed to extend the previous work by investigating the effect of positive feedback on recovery of visual sensitivity. Patients' abilities for detection of a range of spatial frequencies within their field defect were determined using a temporal two-alternative forced-choice technique, before and after a period of visual training (n = 4). Patients underwent Neuro-Eye Therapy which involved detection of temporally modulated spatial grating patches at specific retinal locations within their field defect. Three patients showed improved detection ability following visual training. Based on our previous studies, we had hypothesised that should the occipital brain lesion extend anteriorly to the thalamus, little recovery would be expected. Here, we describe one such case who showed no improvements after extensive training. The present study provides further evidence that recovery (a) can be gradual and may require a large number of training sessions (b) can be accelerated using positive feedback and (c) may be less likely to take place if the occipital damage extends anteriorly to the thalamus.

An improved RST approach for timely alert and Near Real Time monitoring of oil spill disasters by using AVHRR data

NASA Astrophysics Data System (ADS)

Grimaldi, C. S. L.; Casciello, D.; Coviello, I.; Lacava, T.; Pergola, N.; Tramutoli, V.

2011-05-01

Information acquired and provided in Near Real Time is fundamental in contributing to reduce the impact of different sea pollution sources on the maritime environment. Optical data acquired by sensors aboard meteorological satellites, thanks to their high temporal resolution as well as to their delivery policy, can be profitably used for a Near Real Time sea monitoring, provided that accurate and reliable methodologies for analysis and investigation are designed, implemented and fully assessed. In this paper, the results achieved by the application of an improved version of RST (Robust Satellite Technique) to oil spill detection and monitoring will be shown. In particular, thermal infrared data acquired by the NOAA-AVHRR (National Oceanic and Atmospheric Administration-Advanced Very High Resolution Radiometer) have been analyzed and a new RST-based change detection index applied to the case of the oil spills that occurred off the Kuwait and Saudi Arabian coasts in January 1991 and during the Lebanon War in July 2006. The results obtained, even in comparison with those achieved by other AVHRR-based techniques, confirm the unique performance of the proposed approach in automatically detecting the presence of oil spill with a high level of reliability and sensitivity. Moreover, the potential of the extension of the proposed technique to sensors onboard geostationary satellites will be discussed within the context of oil spill monitoring systems, integrating products generated by high temporal (optical) and high spatial (radar) resolution satellite systems.

Modeling astronomical adaptive optics performance with temporally filtered Wiener reconstruction of slope data

NASA Astrophysics Data System (ADS)

Correia, Carlos M.; Bond, Charlotte Z.; Sauvage, Jean-François; Fusco, Thierry; Conan, Rodolphe; Wizinowich, Peter L.

2017-10-01

We build on a long-standing tradition in astronomical adaptive optics (AO) of specifying performance metrics and error budgets using linear systems modeling in the spatial-frequency domain. Our goal is to provide a comprehensive tool for the calculation of error budgets in terms of residual temporally filtered phase power spectral densities and variances. In addition, the fast simulation of AO-corrected point spread functions (PSFs) provided by this method can be used as inputs for simulations of science observations with next-generation instruments and telescopes, in particular to predict post-coronagraphic contrast improvements for planet finder systems. We extend the previous results and propose the synthesis of a distributed Kalman filter to mitigate both aniso-servo-lag and aliasing errors whilst minimizing the overall residual variance. We discuss applications to (i) analytic AO-corrected PSF modeling in the spatial-frequency domain, (ii) post-coronagraphic contrast enhancement, (iii) filter optimization for real-time wavefront reconstruction, and (iv) PSF reconstruction from system telemetry. Under perfect knowledge of wind velocities, we show that $\\sim$60 nm rms error reduction can be achieved with the distributed Kalman filter embodying anti- aliasing reconstructors on 10 m class high-order AO systems, leading to contrast improvement factors of up to three orders of magnitude at few ${\\lambda}/D$ separations ($\\sim1-5{\\lambda}/D$) for a 0 magnitude star and reaching close to one order of magnitude for a 12 magnitude star.

miRNA Temporal Analyzer (mirnaTA): a bioinformatics tool for identifying differentially expressed microRNAs in temporal studies using normal quantile transformation.

PubMed

Cer, Regina Z; Herrera-Galeano, J Enrique; Anderson, Joseph J; Bishop-Lilly, Kimberly A; Mokashi, Vishwesh P

2014-01-01

Understanding the biological roles of microRNAs (miRNAs) is a an active area of research that has produced a surge of publications in PubMed, particularly in cancer research. Along with this increasing interest, many open-source bioinformatics tools to identify existing and/or discover novel miRNAs in next-generation sequencing (NGS) reads become available. While miRNA identification and discovery tools are significantly improved, the development of miRNA differential expression analysis tools, especially in temporal studies, remains substantially challenging. Further, the installation of currently available software is non-trivial and steps of testing with example datasets, trying with one's own dataset, and interpreting the results require notable expertise and time. Subsequently, there is a strong need for a tool that allows scientists to normalize raw data, perform statistical analyses, and provide intuitive results without having to invest significant efforts. We have developed miRNA Temporal Analyzer (mirnaTA), a bioinformatics package to identify differentially expressed miRNAs in temporal studies. mirnaTA is written in Perl and R (Version 2.13.0 or later) and can be run across multiple platforms, such as Linux, Mac and Windows. In the current version, mirnaTA requires users to provide a simple, tab-delimited, matrix file containing miRNA name and count data from a minimum of two to a maximum of 20 time points and three replicates. To recalibrate data and remove technical variability, raw data is normalized using Normal Quantile Transformation (NQT), and linear regression model is used to locate any miRNAs which are differentially expressed in a linear pattern. Subsequently, remaining miRNAs which do not fit a linear model are further analyzed in two different non-linear methods 1) cumulative distribution function (CDF) or 2) analysis of variances (ANOVA). After both linear and non-linear analyses are completed, statistically significant miRNAs (P < 0.05) are plotted as heat maps using hierarchical cluster analysis and Euclidean distance matrix computation methods. mirnaTA is an open-source, bioinformatics tool to aid scientists in identifying differentially expressed miRNAs which could be further mined for biological significance. It is expected to provide researchers with a means of interpreting raw data to statistical summaries in a fast and intuitive manner.

Integrating wetland connectivity into models for watershed ...

EPA Pesticide Factsheets

Geographically isolated wetlands (GIW), or wetlands embedded in uplands, exist along a spatial and temporal hydrologic connectivity continuum to downstream waters. Via these connections and disconnections, GIWs provide numerous hydrological, biogeochemical, and biological functions linked to human health and watershed-scale ecosystem services. Often, a clear demonstration of these functions and the individual and cumulative effects of GIWs on downstream waters is required for their protection or restoration. Measurements alone are typically too resource intensive to do this. In this presentation, we discuss the use of various modeling approaches to quantify the hydrologic connectivity of GIWs and their associated watershed-scale cumulative effects. Our goal is to improve the science behind understanding the functions and connectivity of GIWs via models that are complemented with various types of novel data. We synthesize what is meant by GIW connectivity and its broad significance to science and decision-making. We further discuss case studies that provide insights to diverse modeling approaches, with varying levels of complexity, for how to estimate GIW connectivity and associated watershed-scale impacts to hydrology. We finally provide insights to the key opportunities and priorities for integrating GIW connectivity into the next generation of models. Geographically isolated wetlands (GIW), or wetlands embedded in uplands, exist along a spatial and temporal h

Orthopaedic Application Of Spatio Temporal Analysis Of Body Form And Function

NASA Astrophysics Data System (ADS)

Tauber, C.; Au, J.; Bernstein, S.; Grant, A.; Pugh, J.

1983-07-01

Spatial and temporal analysis of walking provides the orthopaedist with objective evidence of functional ability and improvement in a patient. Patients with orthopaedic problems experiencing extreme pain and, consequently, irregularities in joint motions on weightbearing are videorecorded before, during and after a course of rehabilitative treatment and/or surgical correction of their disability. A specially-programmed computer analyzes these tapes for the parameters of walking by locating reflective spots which indicate the centers of the lower limb joints. The following parameters of gait are then generated: dynamic hip, knee and foot angles at various intervals during walking; vertical, horizontal and lateral displacements of each joint at various time intervals; linear and angular velocities of each joint; and the relationships between the joints during various phases of the gait cycle. The systematic sampling and analysis of the videorecordings by computer enable such information to be converted into and presented as computer graphics, as well as organized into tables of gait variables. This format of presentation of the skeletal adjustments involved in normal human motion provides the clinician with a visual format of gait information which objectively illuminates the multifaceted and complex factors involved. This system provides the clinician a method by which to evaluate the success of the regimen in terms of patient comfort and function.

Using single cell sequencing data to model the evolutionary history of a tumor.

PubMed

Kim, Kyung In; Simon, Richard

2014-01-24

The introduction of next-generation sequencing (NGS) technology has made it possible to detect genomic alterations within tumor cells on a large scale. However, most applications of NGS show the genetic content of mixtures of cells. Recently developed single cell sequencing technology can identify variation within a single cell. Characterization of multiple samples from a tumor using single cell sequencing can potentially provide information on the evolutionary history of that tumor. This may facilitate understanding how key mutations accumulate and evolve in lineages to form a heterogeneous tumor. We provide a computational method to infer an evolutionary mutation tree based on single cell sequencing data. Our approach differs from traditional phylogenetic tree approaches in that our mutation tree directly describes temporal order relationships among mutation sites. Our method also accommodates sequencing errors. Furthermore, we provide a method for estimating the proportion of time from the earliest mutation event of the sample to the most recent common ancestor of the sample of cells. Finally, we discuss current limitations on modeling with single cell sequencing data and possible improvements under those limitations. Inferring the temporal ordering of mutational sites using current single cell sequencing data is a challenge. Our proposed method may help elucidate relationships among key mutations and their role in tumor progression.

Development of spatial-temporal ventilation heterogeneity and probability analysis tools for hyperpolarized 3He magnetic resonance imaging

NASA Astrophysics Data System (ADS)

Choy, S.; Ahmed, H.; Wheatley, A.; McCormack, D. G.; Parraga, G.

2010-03-01

We developed image analysis tools to evaluate spatial and temporal 3He magnetic resonance imaging (MRI) ventilation in asthma and cystic fibrosis. We also developed temporal ventilation probability maps to provide a way to describe and quantify ventilation heterogeneity over time, as a way to test respiratory exacerbations or treatment predictions and to provide a discrete probability measurement of 3He ventilation defect persistence.

Deficits in Visuo-Motor Temporal Integration Impacts Manual Dexterity in Probable Developmental Coordination Disorder.

PubMed

Nobusako, Satoshi; Sakai, Ayami; Tsujimoto, Taeko; Shuto, Takashi; Nishi, Yuki; Asano, Daiki; Furukawa, Emi; Zama, Takuro; Osumi, Michihiro; Shimada, Sotaro; Morioka, Shu; Nakai, Akio

2018-01-01

The neurological basis of developmental coordination disorder (DCD) is thought to be deficits in the internal model and mirror-neuron system (MNS) in the parietal lobe and cerebellum. However, it is not clear if the visuo-motor temporal integration in the internal model and automatic-imitation function in the MNS differs between children with DCD and those with typical development (TD). The current study aimed to investigate these differences. Using the manual dexterity test of the Movement Assessment Battery for Children (second edition), the participants were either assigned to the probable DCD (pDCD) group or TD group. The former was comprised of 29 children with clumsy manual dexterity, while the latter consisted of 42 children with normal manual dexterity. Visuo-motor temporal integration ability and automatic-imitation function were measured using the delayed visual feedback detection task and motor interference task, respectively. Further, the current study investigated whether autism-spectrum disorder (ASD) traits, attention-deficit hyperactivity disorder (ADHD) traits, and depressive symptoms differed among the two groups, since these symptoms are frequent comorbidities of DCD. In addition, correlation and multiple regression analyses were performed to extract factors affecting clumsy manual dexterity. In the results, the delay-detection threshold (DDT) and steepness of the delay-detection probability curve, which indicated visuo-motor temporal integration ability, were significantly prolonged and decreased, respectively, in children with pDCD. The interference effect, which indicated automatic-imitation function, was also significantly reduced in this group. These results highlighted that children with clumsy manual dexterity have deficits in visuo-motor temporal integration and automatic-imitation function. There was a significant correlation between manual dexterity, and measures of visuo-motor temporal integration, and ASD traits and ADHD traits and ASD. Multiple regression analysis revealed that the DDT, which indicated visuo-motor temporal integration, was the greatest predictor of poor manual dexterity. The current results supported and provided further evidence for the internal model deficit hypothesis. Further, they suggested a neurorehabilitation technique that improved visuo-motor temporal integration could be therapeutically effective for children with DCD.

Deficits in Visuo-Motor Temporal Integration Impacts Manual Dexterity in Probable Developmental Coordination Disorder

PubMed Central

Nobusako, Satoshi; Sakai, Ayami; Tsujimoto, Taeko; Shuto, Takashi; Nishi, Yuki; Asano, Daiki; Furukawa, Emi; Zama, Takuro; Osumi, Michihiro; Shimada, Sotaro; Morioka, Shu; Nakai, Akio

2018-01-01

The neurological basis of developmental coordination disorder (DCD) is thought to be deficits in the internal model and mirror-neuron system (MNS) in the parietal lobe and cerebellum. However, it is not clear if the visuo-motor temporal integration in the internal model and automatic-imitation function in the MNS differs between children with DCD and those with typical development (TD). The current study aimed to investigate these differences. Using the manual dexterity test of the Movement Assessment Battery for Children (second edition), the participants were either assigned to the probable DCD (pDCD) group or TD group. The former was comprised of 29 children with clumsy manual dexterity, while the latter consisted of 42 children with normal manual dexterity. Visuo-motor temporal integration ability and automatic-imitation function were measured using the delayed visual feedback detection task and motor interference task, respectively. Further, the current study investigated whether autism-spectrum disorder (ASD) traits, attention-deficit hyperactivity disorder (ADHD) traits, and depressive symptoms differed among the two groups, since these symptoms are frequent comorbidities of DCD. In addition, correlation and multiple regression analyses were performed to extract factors affecting clumsy manual dexterity. In the results, the delay-detection threshold (DDT) and steepness of the delay-detection probability curve, which indicated visuo-motor temporal integration ability, were significantly prolonged and decreased, respectively, in children with pDCD. The interference effect, which indicated automatic-imitation function, was also significantly reduced in this group. These results highlighted that children with clumsy manual dexterity have deficits in visuo-motor temporal integration and automatic-imitation function. There was a significant correlation between manual dexterity, and measures of visuo-motor temporal integration, and ASD traits and ADHD traits and ASD. Multiple regression analysis revealed that the DDT, which indicated visuo-motor temporal integration, was the greatest predictor of poor manual dexterity. The current results supported and provided further evidence for the internal model deficit hypothesis. Further, they suggested a neurorehabilitation technique that improved visuo-motor temporal integration could be therapeutically effective for children with DCD. PMID:29556211

Long-term particulate matter modeling for health effects studies in California - Part 1: Model performance on temporal and spatial variations

NASA Astrophysics Data System (ADS)

Hu, J.; Zhang, H.; Ying, Q.; Chen, S.-H.; Vandenberghe, F.; Kleeman, M. J.

2014-08-01

For the first time, a decadal (9 years from 2000 to 2008) air quality model simulation with 4 km horizontal resolution and daily time resolution has been conducted in California to provide air quality data for health effects studies. Model predictions are compared to measurements to evaluate the accuracy of the simulation with an emphasis on spatial and temporal variations that could be used in epidemiology studies. Better model performance is found at longer averaging times, suggesting that model results with averaging times ≥ 1 month should be the first to be considered in epidemiological studies. The UCD/CIT model predicts spatial and temporal variations in the concentrations of O3, PM2.5, EC, OC, nitrate, and ammonium that meet standard modeling performance criteria when compared to monthly-averaged measurements. Predicted sulfate concentrations do not meet target performance metrics due to missing sulfur sources in the emissions. Predicted seasonal and annual variations of PM2.5, EC, OC, nitrate, and ammonium have mean fractional biases that meet the model performance criteria in 95%, 100%, 71%, 73%, and 92% of the simulated months, respectively. The base dataset provides an improvement for predicted population exposure to PM concentrations in California compared to exposures estimated by central site monitors operated one day out of every 3 days at a few urban locations. Uncertainties in the model predictions arise from several issues. Incomplete understanding of secondary organic aerosol formation mechanisms leads to OC bias in the model results in summertime but does not affect OC predictions in winter when concentrations are typically highest. The CO and NO (species dominated by mobile emissions) results reveal temporal and spatial uncertainties associated with the mobile emissions generated by the EMFAC 2007 model. The WRF model tends to over-predict wind speed during stagnation events, leading to under-predictions of high PM concentrations, usually in winter months. The WRF model also generally under-predicts relative humidity, resulting in less particulate nitrate formation especially during winter months. These issues will be improved in future studies. All model results included in the current manuscript can be downloaded free of charge at http://faculty.engineering.ucdavis.edu/kleeman/.

Improving Coastal Ocean Color Validation Capabilities through Application of Inherent Optical Properties (IOPs)

NASA Technical Reports Server (NTRS)

Mannino, Antonio

2008-01-01

Understanding how the different components of seawater alter the path of incident sunlight through scattering and absorption is essential to using remotely sensed ocean color observations effectively. This is particularly apropos in coastal waters where the different optically significant components (phytoplankton, detrital material, inorganic minerals, etc.) vary widely in concentration, often independently from one another. Inherent Optical Properties (IOPs) form the link between these biogeochemical constituents and the Apparent Optical Properties (AOPs). understanding this interrelationship is at the heart of successfully carrying out inversions of satellite-measured radiance to biogeochemical properties. While sufficient covariation of seawater constituents in case I waters typically allows empirical algorithms connecting AOPs and biogeochemical parameters to behave well, these empirical algorithms normally do not hold for case I1 regimes (Carder et al. 2003). Validation in the context of ocean color remote sensing refers to in-situ measurements used to verify or characterize algorithm products or any assumption used as input to an algorithm. In this project, validation capabilities are considered those measurement capabilities, techniques, methods, models, etc. that allow effective validation. Enhancing current validation capabilities by incorporating state-of-the-art IOP measurements and optical models is the purpose of this work. Involved in this pursuit is improving core IOP measurement capabilities (spectral, angular, spatio-temporal resolutions), improving our understanding of the behavior of analytical AOP-IOP approximations in complex coastal waters, and improving the spatial and temporal resolution of biogeochemical data for validation by applying biogeochemical-IOP inversion models so that these parameters can be computed from real-time IOP sensors with high sampling rates. Research cruises supported by this project provides for collection and processing of seawater samples for biogeochemical (pigments, DOC and POC) and optical (CDOM and POM absorption coefficients) analyses to enhance our understanding of the linkages between in-water optical measurements (IOPs and AOPs) and biogeochemical constituents and to provide a more comprehensive suite of validation products.

Performance of European chemistry transport models as function of horizontal resolution

NASA Astrophysics Data System (ADS)

Schaap, M.; Cuvelier, C.; Hendriks, C.; Bessagnet, B.; Baldasano, J. M.; Colette, A.; Thunis, P.; Karam, D.; Fagerli, H.; Graff, A.; Kranenburg, R.; Nyiri, A.; Pay, M. T.; Rouïl, L.; Schulz, M.; Simpson, D.; Stern, R.; Terrenoire, E.; Wind, P.

2015-07-01

Air pollution causes adverse effects on human health as well as ecosystems and crop yield and also has an impact on climate change trough short-lived climate forcers. To design mitigation strategies for air pollution, 3D Chemistry Transport Models (CTMs) have been developed to support the decision process. Increases in model resolution may provide more accurate and detailed information, but will cubically increase computational costs and pose additional challenges concerning high resolution input data. The motivation for the present study was therefore to explore the impact of using finer horizontal grid resolution for policy support applications of the European Monitoring and Evaluation Programme (EMEP) model within the Long Range Transboundary Air Pollution (LRTAP) convention. The goal was to determine the "optimum resolution" at which additional computational efforts do not provide increased model performance using presently available input data. Five regional CTMs performed four runs for 2009 over Europe at different horizontal resolutions. The models' responses to an increase in resolution are broadly consistent for all models. The largest response was found for NO2 followed by PM10 and O3. Model resolution does not impact model performance for rural background conditions. However, increasing model resolution improves the model performance at stations in and near large conglomerations. The statistical evaluation showed that the increased resolution better reproduces the spatial gradients in pollution regimes, but does not help to improve significantly the model performance for reproducing observed temporal variability. This study clearly shows that increasing model resolution is advantageous, and that leaving a resolution of 50 km in favour of a resolution between 10 and 20 km is practical and worthwhile. As about 70% of the model response to grid resolution is determined by the difference in the spatial emission distribution, improved emission allocation procedures at high spatial and temporal resolution are a crucial factor for further model resolution improvements.

Towards improving the NASA standard soil moisture retrieval algorithm and product

NASA Astrophysics Data System (ADS)

Mladenova, I. E.; Jackson, T. J.; Njoku, E. G.; Bindlish, R.; Cosh, M. H.; Chan, S.

2013-12-01

Soil moisture mapping using passive-based microwave remote sensing techniques has proven to be one of the most effective ways of acquiring reliable global soil moisture information on a routine basis. An important step in this direction was made by the launch of the Advanced Microwave Scanning Radiometer on the NASA's Earth Observing System Aqua satellite (AMSR-E). Along with the standard NASA algorithm and operational AMSR-E product, the easy access and availability of the AMSR-E data promoted the development and distribution of alternative retrieval algorithms and products. Several evaluation studies have demonstrated issues with the standard NASA AMSR-E product such as dampened temporal response and limited range of the final retrievals and noted that the available global passive-based algorithms, even though based on the same electromagnetic principles, produce different results in terms of accuracy and temporal dynamics. Our goal is to identify the theoretical causes that determine the reduced sensitivity of the NASA AMSR-E product and outline ways to improve the operational NASA algorithm, if possible. Properly identifying the underlying reasons that cause the above mentioned features of the NASA AMSR-E product and differences between the alternative algorithms requires a careful examination of the theoretical basis of each approach. Specifically, the simplifying assumptions and parametrization approaches adopted by each algorithm to reduce the dimensionality of unknowns and characterize the observing system. Statistically-based error analyses, which are useful and necessary, provide information on the relative accuracy of each product but give very little information on the theoretical causes, knowledge that is essential for algorithm improvement. Thus, we are currently examining the possibility of improving the standard NASA AMSR-E global soil moisture product by conducting a thorough theoretically-based review of and inter-comparisons between several well established global retrieval techniques. A detailed discussion focused on the theoretical basis of each approach and algorithms sensitivity to assumptions and parametrization approaches will be presented. USDA is an equal opportunity provider and employer.

Improved motion compensation in 3D-CT using respiratory-correlated segment reconstruction: diagnostic and radiotherapy applications.

PubMed

Mori, S; Endo, M; Kohno, R; Minohara, S

2006-09-01

Conventional respiratory-gated CT and four-dimensional CT (4DCT) are disadvantaged by their low temporal resolution, which results in the inclusion of anatomic motion-induced artefacts. These represent a significant source of error both in radiotherapy treatment planning for the thorax and upper abdomen and in diagnostic procedures. In particular, temporal resolution and image quality are vitally important to accurate diagnosis and the minimization of planning target volume margin due to respiratory motion. To improve both temporal resolution and signal-to-noise ratio (SNR), we developed a respiratory-correlated segment reconstruction method (RS) and adapted it to the Feldkamp-Davis-Kress algorithm (FDK) with a 256 multidetector row CT (256MDCT). The 256MDCT scans approximately 100 mm in the craniocaudal direction with a 0.5 mm slice thickness in one rotation. Data acquisition for the RS-FDK relies on the assistance of a respiratory sensing system operating in cine scan mode (continuous axial scan with the table stationary). We evaluated the RS-FDK for volume accuracy and image noise in a phantom study with the 256MDCT and compared results with those for a full scan (FS-FDK), which is usually employed in conventional 4DCT and in half scan (HS-FDK). Results showed that the RS-FDK gave a more accurate volume than the others and had the same SNR as the FS-FDK. In a subsequent animal study, we demonstrated a practical sorting process for projection data which was unaffected by variations in respiratory period, and found that the RS-FDK gave the clearest visualization among the three algorithms of the margins of the liver and pulmonary vessels. In summary, the RS-FDK algorithm provides multi-phase images with higher temporal resolution and better SNR. This method should prove useful when combined with new radiotherapeutic and diagnostic techniques.

Landscape analysis of methane flux across complex terrain

NASA Astrophysics Data System (ADS)

Kaiser, K. E.; McGlynn, B. L.; Dore, J. E.

2014-12-01

Greenhouse gas (GHG) fluxes into and out of the soil are influenced by environmental conditions resulting in landscape-mediated patterns of spatial heterogeneity. The temporal variability of inputs (e.g. precipitation) and internal redistribution (e.g. groundwater flow) and dynamics (e.g. microbial communities) make predicating these fluxes challenging. Complex terrain can provide a laboratory for improving understanding of the spatial patterns, temporal dynamics, and drivers of trace gas flux rates, requisite to constraining current GHG budgets and future scenarios. Our research builds on previous carbon cycle research at the USFS Tenderfoot Creek Experimental Forest, Little Belt Mountains, Montana that highlighted the relationships between landscape position and seasonal CO2 efflux, induced by the topographic redistribution of water. Spatial patterns and landscape scale mediation of CH4 fluxes in seasonally aerobic soils have not yet been elucidated. We measured soil methane concentrations and fluxes across a full range of landscape positions, leveraging topographic and seasonal gradients, to examine the relationships between environmental variables, hydrologic dynamics, and CH4 production and consumption. We determined that a threshold of ~30% VWC distinguished the direction of flux at individual time points, with the riparian area and uplands having distinct source/sink characteristics respectively. Riparian locations were either strong sources or fluctuated between sink and source behavior, resulting in near neutral seasonal flux. Upland sites however, exhibited significant relationships between sink strength and topographic/energy balance indices. Our results highlight spatial and temporal coherence to landscape scale heterogeneity of CH4 dynamics that can improve estimates of landscape scale CH4 balances and sensitivity to change.

Modeling spatial-temporal dynamics of global wetlands: Comprehensive evaluation of a new sub-grid TOPMODEL parameterization and uncertainties

NASA Astrophysics Data System (ADS)

Zhang, Z.; Zimmermann, N. E.; Poulter, B.

2015-12-01

Simulations of the spatial-temporal dynamics of wetlands is key to understanding the role of wetland biogeochemistry under past and future climate variability. Hydrologic inundation models, such as TOPMODEL, are based on a fundamental parameter known as the compound topographic index (CTI) and provide a computationally cost-efficient approach to simulate global wetland dynamics. However, there remains large discrepancy in the implementations of TOPMODEL in land-surface models (LSMs) and thus their performance against observations. This study describes new improvements to TOPMODEL implementation and estimates of global wetland dynamics using the LPJ-wsl DGVM, and quantifies uncertainties by comparing three digital elevation model products (HYDRO1k, GMTED, and HydroSHEDS) at different spatial resolution and accuracy on simulated inundation dynamics. We found that calibrating TOPMODEL with a benchmark dataset can help to successfully predict the seasonal and interannual variations of wetlands, as well as improve the spatial distribution of wetlands to be consistent with inventories. The HydroSHEDS DEM, using a river-basin scheme for aggregating the CTI, shows best accuracy for capturing the spatio-temporal dynamics of wetland among three DEM products. This study demonstrates the feasibility to capture spatial heterogeneity of inundation and to estimate seasonal and interannual variations in wetland by coupling a hydrological module in LSMs with appropriate benchmark datasets. It additionally highlight the importance of an adequate understanding of topographic indices for simulating global wetlands and show the opportunity to converge wetland estimations in LSMs by identifying the uncertainty associated with existing wetland products.

Time Relevance of Convective Weather Forecast for Air Traffic Automation

NASA Technical Reports Server (NTRS)

Chan, William N.

2006-01-01

The Federal Aviation Administration (FAA) is handling nearly 120,000 flights a day through its Air Traffic Management (ATM) system and air traffic congestion is expected to increse substantially over the next 20 years. Weather-induced impacts to throughput and efficiency are the leading cause of flight delays accounting for 70% of all delays with convective weather accounting for 60% of all weather related delays. To support the Next Generation Air Traffic System goal of operating at 3X current capacity in the NAS, ATC decision support tools are being developed to create advisories to assist controllers in all weather constraints. Initial development of these decision support tools did not integrate information regarding weather constraints such as thunderstorms and relied on an additional system to provide that information. Future Decision Support Tools should move towards an integrated system where weather constraints are factored into the advisory of a Decision Support Tool (DST). Several groups such at NASA-Ames, Lincoln Laboratories, and MITRE are integrating convective weather data with DSTs. A survey of current convective weather forecast and observation data show they span a wide range of temporal and spatial resolutions. Short range convective observations can be obtained every 5 mins with longer range forecasts out to several days updated every 6 hrs. Today, the short range forecasts of less than 2 hours have a temporal resolution of 5 mins. Beyond 2 hours, forecasts have much lower temporal. resolution of typically 1 hour. Spatial resolutions vary from 1km for short range to 40km for longer range forecasts. Improving the accuracy of long range convective forecasts is a major challenge. A report published by the National Research Council states improvements for convective forecasts for the 2 to 6 hour time frame will only be achieved for a limited set of convective phenomena in the next 5 to 10 years. Improved longer range forecasts will be probabilistic as opposed to the deterministic shorter range forecasts. Despite the known low level of confidence with respect to long range convective forecasts, these data are still useful to a DST routing algorithm. It is better to develop an aircraft route using the best information available than no information. The temporally coarse long range forecast data needs to be interpolated to be useful to a DST. A DST uses aircraft trajectory predictions that need to be evaluated for impacts by convective storms. Each time-step of a trajectory prediction n&s to be checked against weather data. For the case of coarse temporal data, there needs to be a method fill in weather data where there is none. Simply using the coarse weather data without any interpolation can result in DST routes that are impacted by regions of strong convection. Increasing the temporal resolution of these data can be achieved but result in a large dataset that may prove to be an operational challenge in transmission and loading by a DST. Currently, it takes about 7mins retrieve a 7mb RUC2 forecast file from NOAA at NASA-Ames Research Center. A prototype NCWF6 1 hour forecast is about 3mb in size. A Six hour NCWFG forecast with a 1hr forecast time-step will be about l8mb (6 x 3mb). A 6 hour NCWF6 forecast with a l5min forecast time-step will be about 7mb (24 x 3mb). Based on the time it takes to retrieve a 7mb RUC2 forecast, it will take approximately 70mins to retrieve a 6 hour NCWF forecast with 15min time steps. Until those issues are addressed, there is a need to develop an algorithm that interpolates between these temporally coarse long range forecasts. This paper describes a method of how to use low temporal resolution probabilistic weather forecasts in a DST. The beginning of this paper is a description of some convective weather forecast and observation products followed by an example of how weather data are used by a DST. The subsequent sections will describe probabilistic forecasts followed by a descrtion of a method to use low temporal resolution probabilistic weather forecasts by providing a relevance value to these data outside of their valid times.

Clinical characteristics, surgical and neuropsychological outcomes in drug resistant tumoral temporal lobe epilepsy.

PubMed

Ravat, Sangeeta; Iyer, Vivek; Muzumdar, Dattatraya; Shah, Urvashi; Pradhan, Pranjali; Jain, Neeraj; Godge, Yogesh

2016-12-01

Glioneuronal tumors are found in nearly one third patients who undergo surgery for pharmacoresistant epilepsy with temporal lobe being the most common location. Few studies, however have concentrated on the neurological and neuropsychological outcomes after surgery, hitherto none from India. We studied 34 patients with temporal lobe tumors and drug resistant epilepsy. These patients underwent anterior temporal lobectomy or lesionectomy based on the involvement of the hippocampus and mesial temporal structures. The clinical history, EEG, neuropsychology profile and MRI were compared. Seizure outcome was categorized using Engel's classification. At a mean follow up of 62 months, 85.29% of the patients were seizure free (Engel's Class I). All 8 patients with intraoperative electrocorticography (ECoG) guided resection were seizure free. Presence of a residual lesion was significantly associated with persistence of seizures post surgery (p = 0.002). Group analysis revealed no significant shifts in IQ and memory scores postoperatively. There was a significant improvement in the quality of life scores (total and across all subdomains) in all patients (p < 0.001). Postoperative EEG abnormalities predicted unfavorable ​seizure outcome. Surgery for temporal lobe tumors and refractory epilepsy offers complete seizure freedom in majority. Complete surgical excision of the epileptogenic zone is of paramount importance in achieving seizure freedom. Intraoperative electrocorticography (EcoG) is a useful adjunct to ensure complete removal of epileptogenic zone, thus achieving optimal seizure freedom. There is a significant improvement in the quality of life scores (p < 0.001) with no negative impact of surgery on memory and intelligence. Even the patients who are not seizure free can achieve worthwhile improvement post surgery. Copyright © 2015 IJS Publishing Group Ltd. Published by Elsevier Ltd. All rights reserved.

Learning temporal context shapes prestimulus alpha oscillations and improves visual discrimination performance.

PubMed

Toosi, Tahereh; K Tousi, Ehsan; Esteky, Hossein

2017-08-01

Time is an inseparable component of every physical event that we perceive, yet it is not clear how the brain processes time or how the neuronal representation of time affects our perception of events. Here we asked subjects to perform a visual discrimination task while we changed the temporal context in which the stimuli were presented. We collected electroencephalography (EEG) signals in two temporal contexts. In predictable blocks stimuli were presented after a constant delay relative to a visual cue, and in unpredictable blocks stimuli were presented after variable delays relative to the visual cue. Four subsecond delays of 83, 150, 400, and 800 ms were used in the predictable and unpredictable blocks. We observed that predictability modulated the power of prestimulus alpha oscillations in the parieto-occipital sites: alpha power increased in the 300-ms window before stimulus onset in the predictable blocks compared with the unpredictable blocks. This modulation only occurred in the longest delay period, 800 ms, in which predictability also improved the behavioral performance of the subjects. Moreover, learning the temporal context shaped the prestimulus alpha power: modulation of prestimulus alpha power grew during the predictable block and correlated with performance enhancement. These results suggest that the brain is able to learn the subsecond temporal context of stimuli and use this to enhance sensory processing. Furthermore, the neural correlate of this temporal prediction is reflected in the alpha oscillations. NEW & NOTEWORTHY It is not well understood how the uncertainty in the timing of an external event affects its processing, particularly at subsecond scales. Here we demonstrate how a predictable timing scheme improves visual processing. We found that learning the predictable scheme gradually shaped the prestimulus alpha power. These findings indicate that the human brain is able to extract implicit subsecond patterns in the temporal context of events. Copyright © 2017 the American Physiological Society.

Conformable actively multiplexed high-density surface electrode array for brain interfacing

DOEpatents

Rogers, John; Kim, Dae-Hyeong; Litt, Brian; Viventi, Jonathan

2015-01-13

Provided are methods and devices for interfacing with brain tissue, specifically for monitoring and/or actuation of spatio-temporal electrical waveforms. The device is conformable having a high electrode density and high spatial and temporal resolution. A conformable substrate supports a conformable electronic circuit and a barrier layer. Electrodes are positioned to provide electrical contact with a brain tissue. A controller monitors or actuates the electrodes, thereby interfacing with the brain tissue. In an aspect, methods are provided to monitor or actuate spatio-temporal electrical waveform over large brain surface areas by any of the devices disclosed herein.

Numerical simulation of electrophoresis separation processes

NASA Technical Reports Server (NTRS)

Ganjoo, D. K.; Tezduyar, T. E.

1986-01-01

A new Petrov-Galerkin finite element formulation has been proposed for transient convection-diffusion problems. Most Petrov-Galerkin formulations take into account the spatial discretization, and the weighting functions so developed give satisfactory solutions for steady state problems. Though these schemes can be used for transient problems, there is scope for improvement. The schemes proposed here, which consider temporal as well as spatial discretization, provide improved solutions. Electrophoresis, which involves the motion of charged entities under the influence of an applied electric field, is governed by equations similiar to those encountered in fluid flow problems, i.e., transient convection-diffusion equations. Test problems are solved in electrophoresis and fluid flow. The results obtained are satisfactory. It is also expected that these schemes, suitably adapted, will improve the numerical solutions of the compressible Euler and the Navier-Stokes equations.

Mining Temporal Patterns to Improve Agents Behavior: Two Case Studies

NASA Astrophysics Data System (ADS)

Fournier-Viger, Philippe; Nkambou, Roger; Faghihi, Usef; Nguifo, Engelbert Mephu

We propose two mechanisms for agent learning based on the idea of mining temporal patterns from agent behavior. The first one consists of extracting temporal patterns from the perceived behavior of other agents accomplishing a task, to learn the task. The second learning mechanism consists in extracting temporal patterns from an agent's own behavior. In this case, the agent then reuses patterns that brought self-satisfaction. In both cases, no assumption is made on how the observed agents' behavior is internally generated. A case study with a real application is presented to illustrate each learning mechanism.

Temporal and nonlinear dispersal patterns of Ludwigia hexapetala in a regulated river

USDA-ARS?s Scientific Manuscript database

Rivers are vulnerable to biological invasion due to hydrologic connectivity, which facilitates post-entry movement of aquatic plant propagules by water currents. Ecological and watershed factors may influence spatial and temporal dispersal patterns. Field-based data on dispersal could improve risk...

TEMPORALLY-RESOLVED AMMONIA EMISSION INVENTORIES: CURRENT ESTIMATES, EVALUATION TOOLS, AND MEASUREMENT NEEDS

EPA Science Inventory

In this study, we evaluate the suitability of a three-dimensional chemical transport model (CTM) as a tool for assessing ammonia emission inventories, calculate the improvement in CTM performance owing to recent advances in temporally-varying ammonia emission estimates, and ident...

The Temporal Course of Anxiety Sensitivity in Outpatients with Anxiety and Mood Disorders: Relationships with Behavioral Inhibition and Depression

PubMed Central

Rosellini, Anthony J.; Fairholme, Christopher P.; Brown, Timothy A.

2011-01-01

The present study evaluated the temporal course of three dimensions of anxiety sensitivity (AS; concerns over physical symptoms, mental incapacitation, and social embarrassment) and their relationships with behavioral inhibition (BI) and depression (DEP) in 606 outpatients with anxiety and mood disorders. A semi-structured interview and self-report questionnaires were administered on three occasions over a two-year period. All three constructs decreased over the study period and AS temporally functioned more similar to DEP than BI. Cross-sectional and temporal correlations supported the discriminant validity of AS from BI. As expected, initial levels of BI predicted less improvement in all AS dimensions. In contrast, higher initial levels of mental incapacitation AS were associated with greater improvement in DEP. Our results are discussed in regard to the measurement of AS in clinical samples, conceptualizations of AS as a lower-order vulnerability, and prognostic implications of directional paths between BI and AS and AS and DEP. PMID:21377316

A framework for combining multiple soil moisture retrievals based on maximizing temporal correlation

NASA Astrophysics Data System (ADS)

Kim, Seokhyeon; Parinussa, Robert M.; Liu, Yi. Y.; Johnson, Fiona M.; Sharma, Ashish

2015-08-01

A method for combining two microwave satellite soil moisture products by maximizing the temporal correlation with a reference data set has been developed. The method was applied to two global soil moisture data sets, Japan Aerospace Exploration Agency (JAXA) and Land Parameter Retrieval Model (LPRM), retrieved from the Advanced Microwave Scanning Radiometer 2 observations for the period 2012-2014. A global comparison revealed superior results of the combined product compared to the individual products against the reference data set of ERA-Interim volumetric water content. The global mean temporal correlation coefficient of the combined product with this reference was 0.52 which outperforms the individual JAXA (0.35) as well as the LPRM (0.45) product. Additionally, the performance was evaluated against in situ observations from the International Soil Moisture Network. The combined data set showed a significant improvement in temporal correlation coefficients in the validation compared to JAXA and minor improvements for the LPRM product.

Temporal artery biopsy size does not matter.

PubMed

Kaptanis, Sarantos; Perera, Joanne K; Halkias, Constantine; Caton, Nadine; Alarcon, Lida; Vig, Stella

2014-12-01

This study aimed to clarify whether positive temporal artery biopsies had a greater sample length than negative biopsies in temporal arteritis. It has been suggested that biopsy length should be at least 1 cm to improve diagnostic accuracy. A retrospective review of 149 patients who had 151 temporal artery biopsies was conducted. Twenty biopsies were positive (13.3%), 124 negative (82.1%) and seven samples were insufficient (4.6%). There was no clinically significant difference in the mean biopsy size between positive (0.7 cm) and negative samples (0.65 cm) (t-test: p = .43 NS). Ninety-four patients fulfilled all three ACR criteria prior to biopsy (62.3%) and four patients (2.6%) changed ACR score from 2 to 3 after biopsy. Treatment should not be delayed in anticipation of the biopsy or withheld in the case of a negative biopsy if the patient's symptoms improve. © The Author(s) 2013 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Evaluation of Skin Temperatures Retrieved from GOES-8

NASA Technical Reports Server (NTRS)

Suggs, Ronnie, J.; Jedlovec, G. J.; Lapenta, W. M.; Haines, S. L.

2000-01-01

Skin temperatures derived from geostationary satellites have the potential of providing the temporal and spatial resolution needed for model assimilation. To adequately assess the potential improvements in numerical model forecasts that can be made by assimilating satellite data, an estimate of the accuracy of the skin temperature product is necessary. A particular skin temperature algorithm, the Physical Split Window Technique, that uses the longwave infrared channels of the GOES Imager has shown promise in recent model assimilation studies to provide land surface temperatures with reasonable accuracy. A comparison of retrieved GOES-8 skin temperatures from this algorithm with in situ measurements is presented. Various retrieval algorithm issues are addressed including surface emissivity

Figure-background in dichotic task and their relation to skills untrained.

PubMed

Cibian, Aline Priscila; Pereira, Liliane Desgualdo

2015-01-01

To evaluate the effectiveness of auditory training in dichotic task and to compare the responses of trained skills with the responses of untrained skills, after 4-8 weeks. Nineteen subjects, aged 12-15 years, underwent an auditory training based on dichotic interaural intensity difference (DIID), organized in eight sessions, each lasting 50 min. The assessment of auditory processing was conducted in three stages: before the intervention, after the intervention, and in the middle and at the end of the training. Data from this evaluation were analyzed as per group of disorder, according to the changes in the auditory processes evaluated: selective attention and temporal processing. Each of them was named selective attention group (SAG) and temporal processing group (TPG), and, for both the processes, selective attention and temporal processing group (SATPG). The training improved both the trained and untrained closing skill, normalizing all individuals. Untrained solving and temporal ordering skills did not reach normality for SATPG and TPG. Individuals reached normality for the trained figure-ground skill and for the untrained closing skill. The untrained solving and temporal ordering skills improved in some individuals but failed to reach normality.

Effect of chromatic-dispersion-induced chirp on the temporal coherence properties of individual beams from spontaneous four-wave mixing

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

Ma Xiaoxin; Li Xiaoying; Cui Liang

2011-08-15

Temporal coherence of individual signal or idler beam, determined by the spectral correlation property of photon pairs, is important for realizing quantum interference among independent sources. Based on spontaneous four-wave mixing in optical fibers, we study the effect of chirp on the temporal coherence property by introducing a different amount of chirp into either the pulsed pump or individual signal (idler) beam. The investigation shows that the pump chirp induces additional frequency correlation into photon pairs; the mutual spectral correlation of photon pairs and the coherence of individual beam can be characterized by measuring the intensity correlation function g{sup (2)}more » of the individual beam. To improve the coherence degree, the pump chirp should be minimized. Moreover, a Hong-Ou-Mandel-type two-photon interference experiment with the signal beams generated in two different fibers illustrates that the chirp of the individual signal (idler) beam does not change the temporal coherence degree, but affects the temporal mode matching. To achieve high visibility among multiple sources, apart from improving the coherence degree, mode matching should be optimized by managing the chirps of individual beams.« less

Rapid MODIS-based detection of tree cover loss

NASA Astrophysics Data System (ADS)

Wheeler, David; Guzder-Williams, Brook; Petersen, Rachael; Thau, David

2018-07-01

This paper reports on recent improvements made to the FORMA (Hammer et al., 2014a) data product. The resulting system, FORMA250, is a 250-m alerting system updated daily. FORMA250 alerts are available through Global Forest Watch. These alerts can empower law enforcement officials, government agencies responsible for protecting forests, nongovernmental organizations, companies committed to sustainable forest management practices and supply chains, indigenous groups and forest-dependent communities. In addition, the alerts provide useful information for researchers who study temporal and spatial patterns of forest clearing.

Reprocessing of multi-channel seismic-reflection data collected in the Chukchi Sea

USGS Publications Warehouse

Agena, W.F.; Lee, M.W.; Hart, P.E.

2001-01-01

Contained on this set of two CD-ROMs are stacked and migrated multi-channel seismic-reflection data for 44 lines recorded in the Chukchi Sea, northern Alaska, by the United States Geological Survey in 1977, 1978, and 1980. All data were reprocessed by the USGS in 2000 using updated methods. The resulting final data have both increased temporal and spatial resolution thus providing improved interpretability. An added benefit of these CD-ROMs is that they are a more stable, long-term archival medium for the data.

A system for tracking braille readers using a Wii Remote and a refreshable braille display.

PubMed

Aranyanak, Inthraporn; Reilly, Ronan G

2013-03-01

This article describes a cheap and easy-to-use finger-tracking system for studying braille reading. It provides improved spatial and temporal resolution over the current available solutions and can be used with either a refreshable braille display or braille-embossed paper. In conjunction with a refreshable braille display, the tracking system has the unique capacity to implement display-change paradigms derived from sighted reading research. This will allow researchers to probe skilled braille reading in significantly more depth than has heretofore been possible.

Development and evaluation of an automatic labeling technique for spring small grains

NASA Technical Reports Server (NTRS)

Crist, E. P.; Malila, W. A. (Principal Investigator)

1981-01-01

A labeling technique is described which seeks to associate a sampling entity with a particular crop or crop group based on similarity of growing season and temporal-spectral patterns of development. Human analyst provide contextual information, after which labeling decisions are made automatically. Results of a test of the technique on a large, multi-year data set are reported. Grain labeling accuracies are similar to those achieved by human analysis techniques, while non-grain accuracies are lower. Recommendations for improvments and implications of the test results are discussed.

Assimilation of Satellite to Improve Cloud Simulation in Wrf Model

NASA Astrophysics Data System (ADS)

Park, Y. H.; Pour Biazar, A.; McNider, R. T.

2012-12-01

A simple approach has been introduced to improve cloud simulation spatially and temporally in a meteorological model. The first step for this approach is to use Geostationary Operational Environmental Satellite (GOES) observations to identify clouds and estimate the clouds structure. Then by comparing GOES observations to model cloud field, we identify areas in which model has under-predicted or over-predicted clouds. Next, by introducing subsidence in areas with over-prediction and lifting in areas with under-prediction, erroneous clouds are removed and new clouds are formed. The technique estimates a vertical velocity needed for the cloud correction and then uses a one dimensional variation schemes (1D_Var) to calculate the horizontal divergence components and the consequent horizontal wind components needed to sustain such vertical velocity. Finally, the new horizontal winds are provided as a nudging field to the model. This nudging provides the dynamical support needed to create/clear clouds in a sustainable manner. The technique was implemented and tested in the Weather Research and Forecast (WRF) Model and resulted in substantial improvement in model simulated clouds. Some of the results are presented here.

Ocean heat content estimation from in situ observations at the National Centers for Environmental Information: Improvements and Uncertainties

NASA Astrophysics Data System (ADS)

Boyer, T.; Locarnini, R. A.; Mishonov, A. V.; Reagan, J. R.; Seidov, D.; Zweng, M.; Levitus, S.

2017-12-01

Ocean heat uptake is the major factor in sequestering the Earth's Energy Imbalance (EEI). Since 2000, the National Centers for Environmental Information (NCEI) have been estimating historical ocean heat content (OHC) changes back to the 1950s, as well as monitoring recent OHC. Over these years, through worldwide community efforts, methods of calculating OHC have substantially improved. Similarly, estimation of the uncertainty of ocean heat content calculations provide new insight into how well EEI estimates can be constrained using in situ measurements and models. The changing ocean observing system, especially with the near-global year-round coverage afforded by Argo, has also allowed more confidence in regional and global OHC estimates and provided a benchmark for better understanding of historical OHC changes. NCEI is incorporating knowledge gained through these global efforts into the basic methods, instrument bias corrections, uncertainty measurements, and temporal and spatial resolution capabilities of historic OHC change estimation and recent monitoring. The nature of these improvements and their consequences for estimation of OHC in relation to the EEI will be discussed.

Training in Contrast Detection Improves Motion Perception of Sinewave Gratings in Amblyopia

PubMed Central

Hou, Fang; Huang, Chang-bing; Tao, Liming; Feng, Lixia; Zhou, Yifeng; Lu, Zhong-Lin

2011-01-01

Purpose. One critical concern about using perceptual learning to treat amblyopia is whether training with one particular stimulus and task generalizes to other stimuli and tasks. In the spatial domain, it has been found that the bandwidth of contrast sensitivity improvement is much broader in amblyopes than in normals. Because previous studies suggested the local motion deficits in amblyopia are explained by the spatial vision deficits, the hypothesis for this study was that training in the spatial domain could benefit motion perception of sinewave gratings. Methods. Nine adult amblyopes (mean age, 22.1 ± 5.6 years) were trained in a contrast detection task in the amblyopic eye for 10 days. Visual acuity, spatial contrast sensitivity functions, and temporal modulation transfer functions (MTF) for sinewave motion detection and discrimination were measured for each eye before and after training. Eight adult amblyopes (mean age, 22.6 ± 6.7 years) served as control subjects. Results. In the amblyopic eye, training improved (1) contrast sensitivity by 6.6 dB (or 113.8%) across spatial frequencies, with a bandwidth of 4.4 octaves; (2) sensitivity of motion detection and discrimination by 3.2 dB (or 44.5%) and 3.7 dB (or 53.1%) across temporal frequencies, with bandwidths of 3.9 and 3.1 octaves, respectively; (3) visual acuity by 3.2 dB (or 44.5%). The fellow eye also showed a small amount of improvement in contrast sensitivities and no significant change in motion perception. Control subjects who received no training demonstrated no obvious improvement in any measure. Conclusions. The results demonstrate substantial plasticity in the amblyopic visual system, and provide additional empirical support for perceptual learning as a potential treatment for amblyopia. PMID:21693615

Adrenergic Transmission Facilitates Extinction of Conditional Fear in Mice

ERIC Educational Resources Information Center

Barad, Mark; Cain, Christopher K.; Blouin, Ashley M.

2004-01-01

Extinction of classically conditioned fear, like its acquisition, is active learning, but little is known about its molecular mechanisms. We recently reported that temporal massing of conditional stimulus (CS) presentations improves extinction memory acquisition, and suggested that temporal spacing was less effective because individual CS…

Evolving Patient Compliance Trends: Integrating Clinical, Insurance, and Extrapolated Socioeconomic Data

PubMed Central

Klobusicky, Joseph J.; Aryasomayajula, Arun; Marko, Nicholas

2015-01-01

Efforts toward improving patient compliance in medication focus on either identifying trends in patient features or studying changes through an intervention. Our study seeks to provide an important link between these two approaches through defining trends of evolving compliance. In addition to using clinical covariates provided through insurance claims and health records, we also extracted census based data to provide socioeconomic covariates such as income and population density. Through creating quadrants based on periods of medicine intake, we derive several novel definitions of compliance. These definitions revealed additional compliance trends through considering refill histories later in a patient’s length of therapy. These results suggested that the link between patient features and compliance includes a temporal component, and should be considered in policymaking when identifying compliant subgroups. PMID:26958212

Observing tectonic plate motions and deformations from satellite laser ranging

NASA Technical Reports Server (NTRS)

Christodoulidis, D. C.; Smith, D. E.; Kolenkiewicz, R.; Klosko, S. M.; Torrence, M. H.

1985-01-01

The scope of geodesy has been greatly affected by the advent of artificial near-earth satellites. The present paper provides a description of the results obtained from the reduction of data collected with the aid of satellite laser ranging. It is pointed out that dynamic reduction of satellite laser ranging (SLR) data provides very precise positions in three dimensions for the laser tracking network. The vertical components of the stations, through the tracking geometry provided by the global network and the accurate knowledge of orbital dynamics, are uniquely related to the center of mass of the earth. Attention is given to the observations, the methodologies for reducing satellite observations to estimate station positions, Lageos-observed tectonic plate motions, an improved temporal resolution of SLR plate motions, and the SLR vertical datum.

Spatiotemporal hurdle models for zero-inflated count data: Exploring trends in emergency department visits.

PubMed

Neelon, Brian; Chang, Howard H; Ling, Qiang; Hastings, Nicole S

2016-12-01

Motivated by a study exploring spatiotemporal trends in emergency department use, we develop a class of two-part hurdle models for the analysis of zero-inflated areal count data. The models consist of two components-one for the probability of any emergency department use and one for the number of emergency department visits given use. Through a hierarchical structure, the models incorporate both patient- and region-level predictors, as well as spatially and temporally correlated random effects for each model component. The random effects are assigned multivariate conditionally autoregressive priors, which induce dependence between the components and provide spatial and temporal smoothing across adjacent spatial units and time periods, resulting in improved inferences. To accommodate potential overdispersion, we consider a range of parametric specifications for the positive counts, including truncated negative binomial and generalized Poisson distributions. We adopt a Bayesian inferential approach, and posterior computation is handled conveniently within standard Bayesian software. Our results indicate that the negative binomial and generalized Poisson hurdle models vastly outperform the Poisson hurdle model, demonstrating that overdispersed hurdle models provide a useful approach to analyzing zero-inflated spatiotemporal data. © The Author(s) 2014.

Time-resolved Analysis of Proteome Dynamics by Tandem Mass Tags and Stable Isotope Labeling in Cell Culture (TMT-SILAC) Hyperplexing*

PubMed Central

Welle, Kevin A.; Zhang, Tian; Hryhorenko, Jennifer R.; Shen, Shichen; Qu, Jun; Ghaemmaghami, Sina

2016-01-01

Recent advances in mass spectrometry have enabled system-wide analyses of protein turnover. By globally quantifying the kinetics of protein clearance and synthesis, these methodologies can provide important insights into the regulation of the proteome under varying cellular and environmental conditions. To facilitate such analyses, we have employed a methodology that combines metabolic isotopic labeling (Stable Isotope Labeling in Cell Culture - SILAC) with isobaric tagging (Tandem Mass Tags - TMT) for analysis of multiplexed samples. The fractional labeling of multiple time-points can be measured in a single mass spectrometry run, providing temporally resolved measurements of protein turnover kinetics. To demonstrate the feasibility of the approach, we simultaneously measured the kinetics of protein clearance and accumulation for more than 3000 proteins in dividing and quiescent human fibroblasts and verified the accuracy of the measurements by comparison to established non-multiplexed approaches. The results indicate that upon reaching quiescence, fibroblasts compensate for lack of cellular growth by globally downregulating protein synthesis and upregulating protein degradation. The described methodology significantly reduces the cost and complexity of temporally-resolved dynamic proteomic experiments and improves the precision of proteome-wide turnover data. PMID:27765818

Enhanced laser conditioning using temporally shaped pulses

DOE PAGES

Kafka, K. R. P.; Papernov, S.; Demos, S. G.

2018-03-06

Laser conditioning was investigated as a function of the temporal shape and duration of 351-nm, nanosecond pulses for fused-silica substrates polished via magnetorheological finishing. Here, the aim is to advance our understanding of the dynamics involved to enable improved control of the interaction of laser light with the material to optimize laser conditioning. Gaussian pulses that are temporally truncated at the intensity peak are observed to enhance laser conditioning, in comparison to a Gaussian pulse shape.

Enhanced laser conditioning using temporally shaped pulses.

PubMed

Kafka, K R P; Papernov, S; Demos, S G

2018-03-15

Laser conditioning was investigated as a function of the temporal shape and duration of 351 nm nanosecond pulses for fused-silica substrates polished via magnetorheological finishing. The aim is to advance our understanding of the dynamics involved to enable improved control of the interaction of laser light with the material to optimize laser conditioning. Gaussian pulses that are temporally truncated at the intensity peak are observed to enhance laser conditioning, in comparison to a Gaussian pulse shape.

Enhanced laser conditioning using temporally shaped pulses

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

Kafka, K. R. P.; Papernov, S.; Demos, S. G.

Laser conditioning was investigated as a function of the temporal shape and duration of 351-nm, nanosecond pulses for fused-silica substrates polished via magnetorheological finishing. Here, the aim is to advance our understanding of the dynamics involved to enable improved control of the interaction of laser light with the material to optimize laser conditioning. Gaussian pulses that are temporally truncated at the intensity peak are observed to enhance laser conditioning, in comparison to a Gaussian pulse shape.

The role of spectral and temporal cues in voice gender discrimination by normal-hearing listeners and cochlear implant users.

PubMed

Fu, Qian-Jie; Chinchilla, Sherol; Galvin, John J

2004-09-01

The present study investigated the relative importance of temporal and spectral cues in voice gender discrimination and vowel recognition by normal-hearing subjects listening to an acoustic simulation of cochlear implant speech processing and by cochlear implant users. In the simulation, the number of speech processing channels ranged from 4 to 32, thereby varying the spectral resolution; the cutoff frequencies of the channels' envelope filters ranged from 20 to 320 Hz, thereby manipulating the available temporal cues. For normal-hearing subjects, results showed that both voice gender discrimination and vowel recognition scores improved as the number of spectral channels was increased. When only 4 spectral channels were available, voice gender discrimination significantly improved as the envelope filter cutoff frequency was increased from 20 to 320 Hz. For all spectral conditions, increasing the amount of temporal information had no significant effect on vowel recognition. Both voice gender discrimination and vowel recognition scores were highly variable among implant users. The performance of cochlear implant listeners was similar to that of normal-hearing subjects listening to comparable speech processing (4-8 spectral channels). The results suggest that both spectral and temporal cues contribute to voice gender discrimination and that temporal cues are especially important for cochlear implant users to identify the voice gender when there is reduced spectral resolution.

Robust Flood Monitoring Using Sentinel-1 SAR Time Series

NASA Astrophysics Data System (ADS)

DeVries, B.; Huang, C.; Armston, J.; Huang, W.

2017-12-01

The 2017 hurricane season in North and Central America has resulted in unprecedented levels of flooding that have affected millions of people and continue to impact communities across the region. The extent of casualties and damage to property incurred by these floods underscores the need for reliable systems to track flood location, timing and duration to aid response and recovery efforts. While a diverse range of data sources provide vital information on flood status in near real-time, only spaceborne Synthetic Aperture Radar (SAR) sensors can ensure wall-to-wall coverage over large areas, mostly independently of weather conditions or site accessibility. The European Space Agency's Sentinel-1 constellation represents the only SAR mission currently providing open access and systematic global coverage, allowing for a consistent stream of observations over flood-prone regions. Importantly, both the data and pre-processing software are freely available, enabling the development of improved methods, tools and data products to monitor floods in near real-time. We tracked flood onset and progression in Southeastern Texas, Southern Florida, and Puerto Rico using a novel approach based on temporal backscatter anomalies derived from times series of Sentinel-1 observations and historic baselines defined for each of the three sites. This approach was shown to provide a more objective measure of flood occurrence than the simple backscatter thresholds often employed in operational flood monitoring systems. Additionally, the use of temporal anomaly measures allowed us to partially overcome biases introduced by varying sensor view angles and image acquisition modes, allowing increased temporal resolution in areas where additional targeted observations are available. Our results demonstrate the distinct advantages offered by data from operational SAR missions such as Sentinel-1 and NASA's planned NISAR mission, and call attention to the continuing need for SAR Earth Observation missions that provide systematic repeat observations to facilitate continuous monitoring of flood-affected regions.

Soil Infiltration Characteristics in Agroforestry Systems and Their Relationships with the Temporal Distribution of Rainfall on the Loess Plateau in China

PubMed Central

Wang, Lai; Zhong, Chonggao; Gao, Pengxiang; Xi, Weimin; Zhang, Shuoxin

2015-01-01

Many previous studies have shown that land use patterns are the main factors influencing soil infiltration. Thus, increasing soil infiltration and reducing runoff are crucial for soil and water conservation, especially in semi-arid environments. To explore the effects of agroforestry systems on soil infiltration and associated properties in a semi-arid area of the Loess Plateau in China, we compared three plant systems: a walnut (Juglans regia) monoculture system (JRMS), a wheat (Triticum aestivum) monoculture system (TAMS), and a walnut-wheat alley cropping system (JTACS) over a period of 11 years. Our results showed that the JTACS facilitated infiltration, and its infiltration rate temporal distribution showed a stronger relationship coupled with the rainfall temporal distribution compared with the two monoculture systems during the growing season. However, the effect of JTACS on the infiltration capacity was only significant in shallow soil layer, i.e., the 0–40 cm soil depth. Within JTACS, the speed of the wetting front’s downward movement was significantly faster than that in the two monoculture systems when the amount of rainfall and its intensity were higher. The soil infiltration rate was improved, and the two peaks of soil infiltration rate temporal distribution and the rainfall temporal distribution coupled in rainy season in the alley cropping system, which has an important significance in soil and water conservation. The results of this empirical study provide new insights into the sustainability of agroforestry, which may help farmers select rational planting patterns in this region, as well as other regions with similar climatic and environmental characteristics throughout the world. PMID:25893832

Time-dependence of graph theory metrics in functional connectivity analysis

PubMed Central

Chiang, Sharon; Cassese, Alberto; Guindani, Michele; Vannucci, Marina; Yeh, Hsiang J.; Haneef, Zulfi; Stern, John M.

2016-01-01

Brain graphs provide a useful way to computationally model the network structure of the connectome, and this has led to increasing interest in the use of graph theory to quantitate and investigate the topological characteristics of the healthy brain and brain disorders on the network level. The majority of graph theory investigations of functional connectivity have relied on the assumption of temporal stationarity. However, recent evidence increasingly suggests that functional connectivity fluctuates over the length of the scan. In this study, we investigate the stationarity of brain network topology using a Bayesian hidden Markov model (HMM) approach that estimates the dynamic structure of graph theoretical measures of whole-brain functional connectivity. In addition to extracting the stationary distribution and transition probabilities of commonly employed graph theory measures, we propose two estimators of temporal stationarity: the S-index and N-index. These indexes can be used to quantify different aspects of the temporal stationarity of graph theory measures. We apply the method and proposed estimators to resting-state functional MRI data from healthy controls and patients with temporal lobe epilepsy. Our analysis shows that several graph theory measures, including small-world index, global integration measures, and betweenness centrality, may exhibit greater stationarity over time and therefore be more robust. Additionally, we demonstrate that accounting for subject-level differences in the level of temporal stationarity of network topology may increase discriminatory power in discriminating between disease states. Our results confirm and extend findings from other studies regarding the dynamic nature of functional connectivity, and suggest that using statistical models which explicitly account for the dynamic nature of functional connectivity in graph theory analyses may improve the sensitivity of investigations and consistency across investigations. PMID:26518632

Soil Infiltration Characteristics in Agroforestry Systems and Their Relationships with the Temporal Distribution of Rainfall on the Loess Plateau in China.

PubMed

Wang, Lai; Zhong, Chonggao; Gao, Pengxiang; Xi, Weimin; Zhang, Shuoxin

2015-01-01

Many previous studies have shown that land use patterns are the main factors influencing soil infiltration. Thus, increasing soil infiltration and reducing runoff are crucial for soil and water conservation, especially in semi-arid environments. To explore the effects of agroforestry systems on soil infiltration and associated properties in a semi-arid area of the Loess Plateau in China, we compared three plant systems: a walnut (Juglans regia) monoculture system (JRMS), a wheat (Triticum aestivum) monoculture system (TAMS), and a walnut-wheat alley cropping system (JTACS) over a period of 11 years. Our results showed that the JTACS facilitated infiltration, and its infiltration rate temporal distribution showed a stronger relationship coupled with the rainfall temporal distribution compared with the two monoculture systems during the growing season. However, the effect of JTACS on the infiltration capacity was only significant in shallow soil layer, i.e., the 0-40 cm soil depth. Within JTACS, the speed of the wetting front's downward movement was significantly faster than that in the two monoculture systems when the amount of rainfall and its intensity were higher. The soil infiltration rate was improved, and the two peaks of soil infiltration rate temporal distribution and the rainfall temporal distribution coupled in rainy season in the alley cropping system, which has an important significance in soil and water conservation. The results of this empirical study provide new insights into the sustainability of agroforestry, which may help farmers select rational planting patterns in this region, as well as other regions with similar climatic and environmental characteristics throughout the world.

Time-dependence of graph theory metrics in functional connectivity analysis.

PubMed

Chiang, Sharon; Cassese, Alberto; Guindani, Michele; Vannucci, Marina; Yeh, Hsiang J; Haneef, Zulfi; Stern, John M

2016-01-15

Brain graphs provide a useful way to computationally model the network structure of the connectome, and this has led to increasing interest in the use of graph theory to quantitate and investigate the topological characteristics of the healthy brain and brain disorders on the network level. The majority of graph theory investigations of functional connectivity have relied on the assumption of temporal stationarity. However, recent evidence increasingly suggests that functional connectivity fluctuates over the length of the scan. In this study, we investigate the stationarity of brain network topology using a Bayesian hidden Markov model (HMM) approach that estimates the dynamic structure of graph theoretical measures of whole-brain functional connectivity. In addition to extracting the stationary distribution and transition probabilities of commonly employed graph theory measures, we propose two estimators of temporal stationarity: the S-index and N-index. These indexes can be used to quantify different aspects of the temporal stationarity of graph theory measures. We apply the method and proposed estimators to resting-state functional MRI data from healthy controls and patients with temporal lobe epilepsy. Our analysis shows that several graph theory measures, including small-world index, global integration measures, and betweenness centrality, may exhibit greater stationarity over time and therefore be more robust. Additionally, we demonstrate that accounting for subject-level differences in the level of temporal stationarity of network topology may increase discriminatory power in discriminating between disease states. Our results confirm and extend findings from other studies regarding the dynamic nature of functional connectivity, and suggest that using statistical models which explicitly account for the dynamic nature of functional connectivity in graph theory analyses may improve the sensitivity of investigations and consistency across investigations. Copyright © 2015 Elsevier Inc. All rights reserved.

Understanding the relationship between vegetation phenology and productivity across key dryland ecosystem types through the integration of PhenoCam, satellite, and eddy covariance data

NASA Astrophysics Data System (ADS)

Yan, D.; Scott, R. L.; Moore, D. J.; Biederman, J. A.; Smith, W. K.

2017-12-01

Land surface phenology (LSP) - defined as remotely sensed seasonal variations in vegetation greenness - is intrinsically linked to seasonal carbon uptake, and is thus commonly used as a proxy for vegetation productivity (gross primary productivity; GPP). Yet, the relationship between LSP and GPP remains uncertain, particularly for understudied dryland ecosystems characterized by relatively large spatial and temporal variability. Here, we explored the relationship between LSP and the phenology of GPP for three dominant dryland ecosystem types, and we evaluated how these relationships change as a function of spatial and temporal scale. We focused on three long-term dryland eddy covariance flux tower sites: Walnut Gulch Lucky Hills Shrubland (WHS), Walnut Gulch Kendall Grassland (WKG), and Santa Rita Mesquite (SRM). We analyzed daily canopy-level, 16-day 30m, and 8-day 500m time series of greenness indices from PhenoCam, Landsat 7 ETM+/Landsat 8 OLI, and MODIS, respectively. We first quantified the impact of spatial scale by temporally resampling canopy-level PhenoCam, 30m Landsat, and 500m MODIS to 16-day intervals and then comparing against flux tower GPP estimates. We next quantified the impact of temporal scale by spatially resampling daily PhenoCam, 16-day Landsat, and 8-day MODIS to 500m time series and then comparing against flux tower GPP estimates. We find evidence of critical periods of decoupling between LSP and the phenology of GPP that vary according to the spatial and temporal scale, and as a function of ecosystem type. Our results provide key insight into dryland LSP and GPP dynamics that can be used in future efforts to improve ecosystem process models and satellite-based vegetation productivity algorithms.

CXCR4 antagonist AMD3100 reverses the neurogenesis promoted by enriched environment and suppresses long-term seizure activity in adult rats of temporal lobe epilepsy.

PubMed

Zhou, Zhike; Liu, Tingting; Sun, Xiaoyu; Mu, Xiaopeng; Zhu, Gang; Xiao, Ting; Zhao, Mei; Zhao, Chuansheng

2017-03-30

It has been showed that enriched environment (EE) enhances the hippocampal neurogenesis and improves the cognitive impairments, accompanied by the increased expressions of stromal cell-derived factor-1 (SDF-1) in adult rats of temporal lobe epilepsy (TLE). We examined whether the enhanced neurogenesis and improved cognitive functions induced by EE following seizures were mediated by SDF-1/CXCR4 pathway. Therefore, we investigated the effects of the EE combined with CXCR4 antagonist AMD3100 on neurogenesis, cognitive functions and the long-term seizure activity in the TLE model. Adult rats were randomly assigned as control rats, rats treated with EE, rats subjected to status epilepticus (SE), post-SE rats treated with EE, AMD3100 or EE combined with AMD3100 respectively. We used immunofluorescence staining to analyze the hippocampal neurogenesis and Nissl staining to evaluate hippocampal damage. Electroencephalography was used to measure the frequency and mean duration of spontaneous seizures. Cognitive function was evaluated by Morris water maze test. EE treatment significantly, as well as improved cognitive impairments and decreased long-term seizure activity, and that these effects might be mediated through SDF-1/CXCR4 pathway during the chronic stage of TLE. Although AMD3100 reversed the effect of EE on neurogenesis, it did not abolish the cognitive improvement induced by EE following seizures. More importantly, EE combined with AMD3100 treatment significantly suppressed long-term seizure activity, which provided promising evidences to treat TLE. Copyright © 2017 Elsevier B.V. All rights reserved.

Improving the depth sensitivity of time-resolved measurements by extracting the distribution of times-of-flight

PubMed Central

Diop, Mamadou; St. Lawrence, Keith

2013-01-01

Time-resolved (TR) techniques provide a means of discriminating photons based on their time-of-flight. Since early arriving photons have a lower probability of probing deeper tissue than photons with long time-of-flight, time-windowing has been suggested as a method for improving depth sensitivity. However, TR measurements also contain instrument contributions (instrument-response-function, IRF), which cause temporal broadening of the measured temporal point-spread function (TPSF) compared to the true distribution of times-of-flight (DTOF). The purpose of this study was to investigate the influence of the IRF on the depth sensitivity of TR measurements. TPSFs were acquired on homogeneous and two-layer tissue-mimicking phantoms with varying optical properties. The measured IRF and TPSFs were deconvolved using a stable algorithm to recover the DTOFs. The microscopic Beer-Lambert law was applied to the TPSFs and DTOFs to obtain depth-resolved absorption changes. In contrast to the DTOF, the latest part of the TPSF was not the most sensitive to absorption changes in the lower layer, which was confirmed by computer simulations. The improved depth sensitivity of the DTOF was illustrated in a pig model of the adult human head. Specifically, it was shown that dynamic absorption changes obtained from the late part of the DTOFs recovered from TPSFs acquired by probes positioned on the scalp were similar to absorption changes measured directly on the brain. These results collectively demonstrate that this method improves the depth sensitivity of TR measurements by removing the effects of the IRF. PMID:23504445

Remote Sensing Time Series Product Tool

NASA Technical Reports Server (NTRS)

Predos, Don; Ryan, Robert E.; Ross, Kenton W.

2006-01-01

The TSPT (Time Series Product Tool) software was custom-designed for NASA to rapidly create and display single-band and band-combination time series, such as NDVI (Normalized Difference Vegetation Index) images, for wide-area crop surveillance and for other time-critical applications. The TSPT, developed in MATLAB, allows users to create and display various MODIS (Moderate Resolution Imaging Spectroradiometer) or simulated VIIRS (Visible/Infrared Imager Radiometer Suite) products as single images, as time series plots at a selected location, or as temporally processed image videos. Manually creating these types of products is extremely labor intensive; however, the TSPT development tool makes the process simplified and efficient. MODIS is ideal for monitoring large crop areas because of its wide swath (2330 km), its relatively small ground sample distance (250 m), and its high temporal revisit time (twice daily). Furthermore, because MODIS imagery is acquired daily, rapid changes in vegetative health can potentially be detected. The new TSPT technology provides users with the ability to temporally process high-revisit-rate satellite imagery, such as that acquired from MODIS and from its successor, the VIIRS. The TSPT features the important capability of fusing data from both MODIS instruments onboard the Terra and Aqua satellites, which drastically improves cloud statistics. With the TSPT, MODIS metadata is used to find and optionally remove bad and suspect data. Noise removal and temporal processing techniques allow users to create low-noise time series plots and image videos and to select settings and thresholds that tailor particular output products. The TSPT GUI (graphical user interface) provides an interactive environment for crafting what-if scenarios by enabling a user to repeat product generation using different settings and thresholds. The TSPT Application Programming Interface provides more fine-tuned control of product generation, allowing experienced programmers to bypass the GUI and to create more user-specific output products, such as comparison time plots or images. This type of time series analysis tool for remotely sensed imagery could be the basis of a large-area vegetation surveillance system. The TSPT has been used to generate NDVI time series over growing seasons in California and Argentina and for hurricane events, such as Hurricane Katrina.

The Huaihe Basin Water Resource and Water Quality Management Platform Implemented with a Spatio-Temporal Data Model

NASA Astrophysics Data System (ADS)

Liu, Y.; Zhang, W.; Yan, C.

2012-07-01

Presently, planning and assessment in maintenance, renewal and decision-making for watershed hydrology, water resource management and water quality assessment are evolving toward complex, spatially explicit regional environmental assessments. These problems have to be addressed with object-oriented spatio-temporal data models that can restore, manage, query and visualize various historic and updated basic information concerning with watershed hydrology, water resource management and water quality as well as compute and evaluate the watershed environmental conditions so as to provide online forecasting to police-makers and relevant authorities for supporting decision-making. The extensive data requirements and the difficult task of building input parameter files, however, has long been an obstacle to use of such complex models timely and effectively by resource managers. Success depends on an integrated approach that brings together scientific, education and training advances made across many individual disciplines and modified to fit the needs of the individuals and groups who must write, implement, evaluate, and adjust their watershed management plans. The centre for Hydro-science Research, Nanjing University, in cooperation with the relevant watershed management authorities, has developed a WebGIS management platform to facilitate this complex process. Improve the management of watersheds over the Huaihe basin through the development, promotion and use of a web-based, user-friendly, geospatial watershed management data and decision support system (WMDDSS) involved many difficulties for the development of this complicated System. In terms of the spatial and temporal characteristics of historic and currently available information on meteorological, hydrological, geographical, environmental and other relevant disciplines, we designed an object-oriented spatiotemporal data model that combines spatial, attribute and temporal information to implement the management system. Using this system, we can update, query and analyze environmental information as well as manage historical data, and a visualization tool was provided to help the user interpret results so as to provide scientific support for decision-making. The utility of the system has been demonstrated its values by being used in watershed management and environmental assessments.

Understanding Variability in Beach Slope to Improve Forecasts of Storm-induced Water Levels

NASA Astrophysics Data System (ADS)

Doran, K. S.; Stockdon, H. F.; Long, J.

2014-12-01

The National Assessment of Hurricane-Induced Coastal Erosion Hazards combines measurements of beach morphology with storm hydrodynamics to produce forecasts of coastal change during storms for the Gulf of Mexico and Atlantic coastlines of the United States. Wave-induced water levels are estimated using modeled offshore wave height and period and measured beach slope (from dune toe to shoreline) through the empirical parameterization of Stockdon et al. (2006). Spatial and temporal variability in beach slope leads to corresponding variability in predicted wave setup and swash. Seasonal and storm-induced changes in beach slope can lead to differences on the order of a meter in wave runup elevation, making accurate specification of this parameter essential to skillful forecasts of coastal change. Spatial variation in beach slope is accounted for through alongshore averaging, but temporal variability in beach slope is not included in the final computation of the likelihood of coastal change. Additionally, input morphology may be years old and potentially very different than the conditions present during forecast storm. In order to improve our forecasts of hurricane-induced coastal erosion hazards, the temporal variability of beach slope must be included in the final uncertainty of modeled wave-induced water levels. Frequently collected field measurements of lidar-based beach morphology are examined for study sites in Duck, North Carolina, Treasure Island, Florida, Assateague Island, Virginia, and Dauphin Island, Alabama, with some records extending over a period of 15 years. Understanding the variability of slopes at these sites will help provide estimates of associated water level uncertainty which can then be applied to other areas where lidar observations are infrequent, and improve the overall skill of future forecasts of storm-induced coastal change. Stockdon, H. F., Holman, R. A., Howd, P. A., and Sallenger Jr, A. H. (2006). Empirical parameterization of setup,swash, and runup. Coastal engineering, 53(7), 573-588.

Temporal Change of Seismic Earth's Inner Core Phases: Inner Core Differential Rotation Or Temporal Change of Inner Core Surface?

NASA Astrophysics Data System (ADS)

Yao, J.; Tian, D.; Sun, L.; Wen, L.

2017-12-01

Since Song and Richards [1996] first reported seismic evidence for temporal change of PKIKP wave (a compressional wave refracted in the inner core) and proposed inner core differential rotation as its explanation, it has generated enormous interests in the scientific community and the public, and has motivated many studies on the implications of the inner core differential rotation. However, since Wen [2006] reported seismic evidence for temporal change of PKiKP wave (a compressional wave reflected from the inner core boundary) that requires temporal change of inner core surface, both interpretations for the temporal change of inner core phases have existed, i.e., inner core rotation and temporal change of inner core surface. In this study, we discuss the issue of the interpretation of the observed temporal changes of those inner core phases and conclude that inner core differential rotation is not only not required but also in contradiction with three lines of seismic evidence from global repeating earthquakes. Firstly, inner core differential rotation provides an implausible explanation for a disappearing inner core scatterer between a doublet in South Sandwich Islands (SSI), which is located to be beneath northern Brazil based on PKIKP and PKiKP coda waves of the earlier event of the doublet. Secondly, temporal change of PKIKP and its coda waves among a cluster in SSI is inconsistent with the interpretation of inner core differential rotation, with one set of the data requiring inner core rotation and the other requiring non-rotation. Thirdly, it's not reasonable to invoke inner core differential rotation to explain travel time change of PKiKP waves in a very small time scale (several months), which is observed for repeating earthquakes in Middle America subduction zone. On the other hand, temporal change of inner core surface could provide a consistent explanation for all the observed temporal changes of PKIKP and PKiKP and their coda waves. We conclude that the observed temporal changes of the inner core phases are caused by temporal changes of inner core surface. The temporal changes of inner core surface are found to occur in some localized regions within a short time scale (years to months), a phenomenon that should provide important clues to a potentially fundamental change of our understanding of core dynamics.

Induction of Fear by Intraoperative Stimulation During Awake Craniotomy: Case Presentation and Systematic Review of the Literature.

PubMed

Nowacki, Andreas; Seidel, Kathleen; Schucht, Philippe; Schindler, Kaspar; Abela, Eugenio; Heinemann, Dorothea; Gutbrod, Klemens; Wiest, Roland; Raabe, Andreas; Pollo, Claudio

2015-08-01

A case is presented and a systematic review of the literature is provided to update our current knowledge of induction of fear by cortical stimulation. We present a case of refractory epilepsy associated with a lesion where fear could be induced by intraoperative electrical stimulation of the posterior inner part of the superior temporal gyrus. We performed a systematic review of the literature using PubMed with the key words "epilepsy AND emotion", "cortical stimulation AND emotion," and "human brain stimulation AND behavior". Intraoperative cortical stimulation of the inner part of the posterior superior temporal gyrus reliably induced fear and progressive screaming behavior. Stimulation through subdural grid electrodes did not induce this phenomenon. A systematic review of the literature identified fear induction by stimulation of different widespread cortical areas including the temporal pole, the insula, and the anterior cingulate cortex. The posterior part of the superior temporal gyrus has so far not been associated with fear induction after electrical stimulation. Although our observation suggests that this area of the brain could be part of a network involved in the elicitation of fear, dysfunction of this network induced by epilepsy could also explain the observed phenomenon. Electrophysiologic and imaging studies must be conducted to improve our understanding of the cortical networks forming the neuroanatomical substrate of higher brain functions and experiences such as fear. Copyright © 2015 Elsevier Inc. All rights reserved.

Whole-animal imaging with high spatio-temporal resolution

NASA Astrophysics Data System (ADS)

Chhetri, Raghav; Amat, Fernando; Wan, Yinan; Höckendorf, Burkhard; Lemon, William C.; Keller, Philipp J.

2016-03-01

We developed isotropic multiview (IsoView) light-sheet microscopy in order to image fast cellular dynamics, such as cell movements in an entire developing embryo or neuronal activity throughput an entire brain or nervous system, with high resolution in all dimensions, high imaging speeds, good physical coverage and low photo-damage. To achieve high temporal resolution and high spatial resolution at the same time, IsoView microscopy rapidly images large specimens via simultaneous light-sheet illumination and fluorescence detection along four orthogonal directions. In a post-processing step, these four views are then combined by means of high-throughput multiview deconvolution to yield images with a system resolution of ≤ 450 nm in all three dimensions. Using IsoView microscopy, we performed whole-animal functional imaging of Drosophila embryos and larvae at a spatial resolution of 1.1-2.5 μm and at a temporal resolution of 2 Hz for up to 9 hours. We also performed whole-brain functional imaging in larval zebrafish and multicolor imaging of fast cellular dynamics across entire, gastrulating Drosophila embryos with isotropic, sub-cellular resolution. Compared with conventional (spatially anisotropic) light-sheet microscopy, IsoView microscopy improves spatial resolution at least sevenfold and decreases resolution anisotropy at least threefold. Compared with existing high-resolution light-sheet techniques, such as lattice lightsheet microscopy or diSPIM, IsoView microscopy effectively doubles the penetration depth and provides subsecond temporal resolution for specimens 400-fold larger than could previously be imaged.

Imaging structural and functional brain networks in temporal lobe epilepsy

PubMed Central

Bernhardt, Boris C.; Hong, SeokJun; Bernasconi, Andrea; Bernasconi, Neda

2013-01-01

Early imaging studies in temporal lobe epilepsy (TLE) focused on the search for mesial temporal sclerosis, as its surgical removal results in clinically meaningful improvement in about 70% of patients. Nevertheless, a considerable subgroup of patients continues to suffer from post-operative seizures. Although the reasons for surgical failure are not fully understood, electrophysiological and imaging data suggest that anomalies extending beyond the temporal lobe may have negative impact on outcome. This hypothesis has revived the concept of human epilepsy as a disorder of distributed brain networks. Recent methodological advances in non-invasive neuroimaging have led to quantify structural and functional networks in vivo. While structural networks can be inferred from diffusion MRI tractography and inter-regional covariance patterns of structural measures such as cortical thickness, functional connectivity is generally computed based on statistical dependencies of neurophysiological time-series, measured through functional MRI or electroencephalographic techniques. This review considers the application of advanced analytical methods in structural and functional connectivity analyses in TLE. We will specifically highlight findings from graph-theoretical analysis that allow assessing the topological organization of brain networks. These studies have provided compelling evidence that TLE is a system disorder with profound alterations in local and distributed networks. In addition, there is emerging evidence for the utility of network properties as clinical diagnostic markers. Nowadays, a network perspective is considered to be essential to the understanding of the development, progression, and management of epilepsy. PMID:24098281

Temporal lobe surgery in childhood and neuroanatomical predictors of long-term declarative memory outcome

PubMed Central

Skirrow, Caroline; Cross, J. Helen; Harrison, Sue; Cormack, Francesca; Harkness, William; Coleman, Rosie; Meierotto, Ellen; Gaiottino, Johanna; Vargha-Khadem, Faraneh

2015-01-01

The temporal lobes play a prominent role in declarative memory function, including episodic memory (memory for events) and semantic memory (memory for facts and concepts). Surgical resection for medication-resistant and well-localized temporal lobe epilepsy has good prognosis for seizure freedom, but is linked to memory difficulties in adults, especially when the removal is on the left side. Children may benefit most from surgery, because brain plasticity may facilitate post-surgical reorganization, and seizure cessation may promote cognitive development. However, the long-term impact of this intervention in children is not known. We examined memory function in 53 children (25 males, 28 females) who were evaluated for epilepsy surgery: 42 underwent unilateral temporal lobe resections (25 left, 17 right, mean age at surgery 13.8 years), 11 were treated only pharmacologically. Average follow-up was 9 years (range 5–15). Post-surgical change in visual and verbal episodic memory, and semantic memory at follow-up were examined. Pre- and post-surgical T1-weighted MRI brain scans were analysed to extract hippocampal and resection volumes, and evaluate post-surgical temporal lobe integrity. Language lateralization indices were derived from functional magnetic resonance imaging. There were no significant pre- to postoperative decrements in memory associated with surgery. In contrast, gains in verbal episodic memory were seen after right temporal lobe surgery, and visual episodic memory improved after left temporal lobe surgery, indicating a functional release in the unoperated temporal lobe after seizure reduction or cessation. Pre- to post-surgical change in memory function was not associated with any indices of brain structure derived from MRI. However, better verbal memory at follow-up was linked to greater post-surgical residual hippocampal volumes, most robustly in left surgical participants. Better semantic memory at follow-up was associated with smaller resection volumes and greater temporal pole integrity after left temporal surgery. Results were independent of post-surgical intellectual function and language lateralization. Our findings indicate post-surgical, hemisphere-dependent material-specific improvement in memory functions in the intact temporal lobe. However, outcome was linked to the anatomical integrity of the temporal lobe memory system, indicating that compensatory mechanisms are constrained by the amount of tissue which remains in the operated temporal lobe. Careful tailoring of resections for children undergoing epilepsy surgery may enhance long-term memory outcome. PMID:25392199

Improving Evapotranspiration Estimates Using Multi-Platform Remote Sensing

NASA Astrophysics Data System (ADS)

Knipper, Kyle; Hogue, Terri; Franz, Kristie; Scott, Russell

2016-04-01

Understanding the linkages between energy and water cycles through evapotranspiration (ET) is uniquely challenging given its dependence on a range of climatological parameters and surface/atmospheric heterogeneity. A number of methods have been developed to estimate ET either from primarily remote-sensing observations, in-situ measurements, or a combination of the two. However, the scale of many of these methods may be too large to provide needed information about the spatial and temporal variability of ET that can occur over regions with acute or chronic land cover change and precipitation driven fluxes. The current study aims to improve the spatial and temporal variability of ET utilizing only satellite-based observations by incorporating a potential evapotranspiration (PET) methodology with satellite-based down-scaled soil moisture estimates in southern Arizona, USA. Initially, soil moisture estimates from AMSR2 and SMOS are downscaled to 1km through a triangular relationship between MODIS land surface temperature (MYD11A1), vegetation indices (MOD13Q1/MYD13Q1), and brightness temperature. Downscaled soil moisture values are then used to scale PET to actual ET (AET) at a daily, 1km resolution. Derived AET estimates are compared to observed flux tower estimates, the North American Land Data Assimilation System (NLDAS) model output (i.e. Variable Infiltration Capacity (VIC) Macroscale Hydrologic Model, Mosiac Model, and Noah Model simulations), the Operational Simplified Surface Energy Balance Model (SSEBop), and a calibrated empirical ET model created specifically for the region. Preliminary results indicate a strong increase in correlation when incorporating the downscaling technique to original AMSR2 and SMOS soil moisture values, with the added benefit of being able to decipher small scale heterogeneity in soil moisture (riparian versus desert grassland). AET results show strong correlations with relatively low error and bias when compared to flux tower estimates. In addition, AET results show improved bias to those reported by SSEBop, with similar correlations and errors when compared to the empirical ET model. Spatial patterns of estimated AET display patterns representative of the basin's elevation and vegetation characteristics, with improved spatial resolution and temporal heterogeneity when compared to previous models.

Markup of temporal information in electronic health records.

PubMed

Hyun, Sookyung; Bakken, Suzanne; Johnson, Stephen B

2006-01-01

Temporal information plays a critical role in the understanding of clinical narrative (i.e., free text). We developed a representation for marking up temporal information in a narrative, consisting of five elements: 1) reference point, 2) direction, 3) number, 4) time unit, and 5) pattern. We identified 254 temporal expressions from 50 discharge summaries and represented them using our scheme. The overall inter-rater reliability among raters applying the representation model was 75 percent agreement. The model can contribute to temporal reasoning in computer systems for decision support, data mining, and process and outcomes analyses by providing structured temporal information.

Deriving video content type from HEVC bitstream semantics

NASA Astrophysics Data System (ADS)

Nightingale, James; Wang, Qi; Grecos, Christos; Goma, Sergio R.

2014-05-01

As network service providers seek to improve customer satisfaction and retention levels, they are increasingly moving from traditional quality of service (QoS) driven delivery models to customer-centred quality of experience (QoE) delivery models. QoS models only consider metrics derived from the network however, QoE models also consider metrics derived from within the video sequence itself. Various spatial and temporal characteristics of a video sequence have been proposed, both individually and in combination, to derive methods of classifying video content either on a continuous scale or as a set of discrete classes. QoE models can be divided into three broad categories, full reference, reduced reference and no-reference models. Due to the need to have the original video available at the client for comparison, full reference metrics are of limited practical value in adaptive real-time video applications. Reduced reference metrics often require metadata to be transmitted with the bitstream, while no-reference metrics typically operate in the decompressed domain at the client side and require significant processing to extract spatial and temporal features. This paper proposes a heuristic, no-reference approach to video content classification which is specific to HEVC encoded bitstreams. The HEVC encoder already makes use of spatial characteristics to determine partitioning of coding units and temporal characteristics to determine the splitting of prediction units. We derive a function which approximates the spatio-temporal characteristics of the video sequence by using the weighted averages of the depth at which the coding unit quadtree is split and the prediction mode decision made by the encoder to estimate spatial and temporal characteristics respectively. Since the video content type of a sequence is determined by using high level information parsed from the video stream, spatio-temporal characteristics are identified without the need for full decoding and can be used in a timely manner to aid decision making in QoE oriented adaptive real time streaming.

Temporal transcriptional logic of dynamic regulatory networks underlying nitrogen signaling and use in plants.

PubMed

Varala, Kranthi; Marshall-Colón, Amy; Cirrone, Jacopo; Brooks, Matthew D; Pasquino, Angelo V; Léran, Sophie; Mittal, Shipra; Rock, Tara M; Edwards, Molly B; Kim, Grace J; Ruffel, Sandrine; McCombie, W Richard; Shasha, Dennis; Coruzzi, Gloria M

2018-06-19

This study exploits time, the relatively unexplored fourth dimension of gene regulatory networks (GRNs), to learn the temporal transcriptional logic underlying dynamic nitrogen (N) signaling in plants. Our "just-in-time" analysis of time-series transcriptome data uncovered a temporal cascade of cis elements underlying dynamic N signaling. To infer transcription factor (TF)-target edges in a GRN, we applied a time-based machine learning method to 2,174 dynamic N-responsive genes. We experimentally determined a network precision cutoff, using TF-regulated genome-wide targets of three TF hubs (CRF4, SNZ, and CDF1), used to "prune" the network to 155 TFs and 608 targets. This network precision was reconfirmed using genome-wide TF-target regulation data for four additional TFs (TGA1, HHO5/6, and PHL1) not used in network pruning. These higher-confidence edges in the GRN were further filtered by independent TF-target binding data, used to calculate a TF "N-specificity" index. This refined GRN identifies the temporal relationship of known/validated regulators of N signaling (NLP7/8, TGA1/4, NAC4, HRS1, and LBD37/38/39) and 146 additional regulators. Six TFs-CRF4, SNZ, CDF1, HHO5/6, and PHL1-validated herein regulate a significant number of genes in the dynamic N response, targeting 54% of N-uptake/assimilation pathway genes. Phenotypically, inducible overexpression of CRF4 in planta regulates genes resulting in altered biomass, root development, and 15 NO 3 - uptake, specifically under low-N conditions. This dynamic N-signaling GRN now provides the temporal "transcriptional logic" for 155 candidate TFs to improve nitrogen use efficiency with potential agricultural applications. Broadly, these time-based approaches can uncover the temporal transcriptional logic for any biological response system in biology, agriculture, or medicine. Copyright © 2018 the Author(s). Published by PNAS.

Temporal processing of speech in a time-feature space

NASA Astrophysics Data System (ADS)

Avendano, Carlos

1997-09-01

The performance of speech communication systems often degrades under realistic environmental conditions. Adverse environmental factors include additive noise sources, room reverberation, and transmission channel distortions. This work studies the processing of speech in the temporal-feature or modulation spectrum domain, aiming for alleviation of the effects of such disturbances. Speech reflects the geometry of the vocal organs, and the linguistically dominant component is in the shape of the vocal tract. At any given point in time, the shape of the vocal tract is reflected in the short-time spectral envelope of the speech signal. The rate of change of the vocal tract shape appears to be important for the identification of linguistic components. This rate of change, or the rate of change of the short-time spectral envelope can be described by the modulation spectrum, i.e. the spectrum of the time trajectories described by the short-time spectral envelope. For a wide range of frequency bands, the modulation spectrum of speech exhibits a maximum at about 4 Hz, the average syllabic rate. Disturbances often have modulation frequency components outside the speech range, and could in principle be attenuated without significantly affecting the range with relevant linguistic information. Early efforts for exploiting the modulation spectrum domain (temporal processing), such as the dynamic cepstrum or the RASTA processing, used ad hoc designed processing and appear to be suboptimal. As a major contribution, in this dissertation we aim for a systematic data-driven design of temporal processing. First we analytically derive and discuss some properties and merits of temporal processing for speech signals. We attempt to formalize the concept and provide a theoretical background which has been lacking in the field. In the experimental part we apply temporal processing to a number of problems including adaptive noise reduction in cellular telephone environments, reduction of reverberation for speech enhancement, and improvements on automatic recognition of speech degraded by linear distortions and reverberation.

Memory Functions following Surgery for Temporal Lobe Epilepsy in Children

ERIC Educational Resources Information Center

Jambaque, Isabelle; Dellatolas, Georges; Fohlen, Martine; Bulteau, Christine; Watier, Laurence; Dorfmuller, Georg; Chiron, Catherine; Delalande, Olivier

2007-01-01

Surgical treatment appears to improve the cognitive prognosis in children undergoing surgery for temporal lobe epilepsy (TLE). The beneficial effects of surgery on memory functions, particularly on material-specific memory, are more difficult to assess because of potentially interacting factors such as age range, intellectual level,…

The error structure of the SMAP single and dual channel soil moisture retrievals

USDA-ARS?s Scientific Manuscript database

Knowledge of the temporal error structure for remotely-sensed surface soil moisture retrievals can improve our ability to exploit them for hydrology and climate studies. This study employs a triple collocation type analysis to investigate both the total variance and temporal auto-correlation of erro...

Music Exposure and the Development of Spatial Intelligence in Children.

ERIC Educational Resources Information Center

Rauscher, Frances H.

1999-01-01

Presents research on the effects of music instruction on spatial-temporal reasoning in children. Summarizes past studies that tested whether music training transfers to spatial-temporal task performance. A work-in-progress focuses on whether music training can improve economically-disadvantaged preschoolers' abstract reasoning and why…

Improved Cerebral Function in Mesial Temporal Lobe Epilepsy after Subtemporal Amygdalohippocampectomy

ERIC Educational Resources Information Center

Takaya, Shigetoshi; Mikuni, Nobuhiro; Mitsueda, Takahiro; Satow, Takeshi; Taki, Junya; Kinoshita, Masako; Miyamoto, Susumu; Hashimoto, Nobuo; Ikeda, Akio; Fukuyama, Hidenao

2009-01-01

The functional changes that occur throughout the human brain after the selective removal of an epileptogenic lesion remain unclear. Subtemporal selective amygdalohippocampectomy (SAH) has been advocated as a minimally invasive surgical procedure for patients with medically intractable mesial temporal lobe epilepsy (MTLE). We evaluated the effects…

Why risk managers need information about spatio-temporal variability of natural hazards. Examples from practice

NASA Astrophysics Data System (ADS)

Zischg, Andreas

2013-04-01

Integrated risk management consists of risk prevention, early warning, intervention during an event and restoration/re-construction after an event. The prevention phase consists of land use planning measures with a long-term time horizon and of structural measures that sometimes have a lifespan of more than 30-50 years. In this case, it is important to analyse the long-term evolvement of natural risks due to climate changes or land use changes. Besides of this, the spatial and temporal variability of a natural hazard process during the course of an event is also important. The shift from "static" hazard and risk assessment towards a "dynamic" assessment offers benefits for improving the intervention phase in risk management. This contribution describes some examples and points out the benefits of this shift for risk management. One example is the variable disposition of small alpine catchments for runoff and its relevance for early warning. The disposition for runoff depends on the actual status of environmental variables such as soil moisture and the snowpack characteristics. A feasibility study showed how the monitoring of soil moisture and the status of the snowpack can be incorporated into a rule base for describing the temporal variability of the disposition for high runoff in alpine catchments. The study showed that this information about the system state of alpine catchments can be used to improve the assessment of the consequences of a weather forecast for risk management. Another example is the use of snowpack and weather monitoring and traffic intensity measurements for avalanche risk management on alpine roads. Here, the information about the spatio-temporal variability of the snow avalanches and the presence of vehicles can be used for improving the procedures for road closure and re-opening. Another example is the preparation of intervention plans for fire brigades and other relief units during urban floods. The simulation of the temporal evolvement of a single flood event (time horizon of 0-24 hours) provides information for the elaboration of the intervention tactic. The following questions can be answered only by knowing the temporal and spatial evolvement during an event itself: Which intervention priorities have to be set if the resources of the relief units are limited? Which early interventions could be turn out to be unhelpful because in a later step the object to be protected will be flooded anyway? What is the time available for setting up object protection measures and other flood protection measures? The most important factor to implement the theory in practice is the focus on the interlinkages between the simulation of all possible scenarios in advance (scenario techniques, analysing the time-steps in flood simulation), the monitoring system (now-casting, real-time-data), the scenarios of intervention measures and their interdependency with the hazard scenarios. The interlinkages can be set up and described with the expert system approach.

A Spatio-Temporal Enhancement Method for medium resolution LAI (STEM-LAI)

NASA Astrophysics Data System (ADS)

Houborg, Rasmus; McCabe, Matthew F.; Gao, Feng

2016-05-01

Satellite remote sensing has been used successfully to map leaf area index (LAI) across landscapes, but advances are still needed to exploit multi-scale data streams for producing LAI at both high spatial and temporal resolution. A multi-scale Spatio-Temporal Enhancement Method for medium resolution LAI (STEM-LAI) has been developed to generate 4-day time-series of Landsat-scale LAI from existing medium resolution LAI products. STEM-LAI has been designed to meet the demands of applications requiring frequent and spatially explicit information, such as effectively resolving rapidly evolving vegetation dynamics at sub-field (30 m) scales. In this study, STEM-LAI is applied to Moderate Resolution Imaging Spectroradiometer (MODIS) based LAI data and utilizes a reference-based regression tree approach for producing MODIS-consistent, but Landsat-based, LAI. The Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) is used to interpolate the downscaled LAI between Landsat acquisition dates, providing a high spatial and temporal resolution improvement over existing LAI products. STARFM predicts high resolution LAI by blending MODIS and Landsat based information from a common acquisition date, with MODIS data from a prediction date. To demonstrate its capacity to reproduce fine-scale spatial features observed in actual Landsat LAI, the STEM-LAI approach is tested over an agricultural region in Nebraska. The implementation of a 250 m resolution LAI product, derived from MODIS 1 km data and using a scale consistent approach based on the Normalized Difference Vegetation Index (NDVI), is found to significantly improve accuracies of spatial pattern prediction, with the coefficient of efficiency (E) ranging from 0.77-0.94 compared to 0.01-0.85 when using 1 km LAI inputs alone. Comparisons against an 11-year record of in-situ measured LAI over maize and soybean highlight the utility of STEM-LAI in reproducing observed LAI dynamics (both characterized by r2 = 0.86) over a range of plant development stages. Overall, STEM-LAI represents an effective downscaling and temporal enhancement mechanism that predicts in-situ measured LAI better than estimates derived through linear interpolation between Landsat acquisitions. This is particularly true when the in-situ measurement date is greater than 10 days from the nearest Landsat acquisition, with prediction errors reduced by up to 50%. With a streamlined and completely automated processing interface, STEM-LAI represents a flexible tool for LAI disaggregation in space and time that is adaptable to different land cover types, landscape heterogeneities, and cloud cover conditions.

Improving exposure assessment in environmental epidemiology: Application of spatio-temporal visualization tools

NASA Astrophysics Data System (ADS)

Meliker, Jaymie R.; Slotnick, Melissa J.; Avruskin, Gillian A.; Kaufmann, Andrew; Jacquez, Geoffrey M.; Nriagu, Jerome O.

2005-05-01

A thorough assessment of human exposure to environmental agents should incorporate mobility patterns and temporal changes in human behaviors and concentrations of contaminants; yet the temporal dimension is often under-emphasized in exposure assessment endeavors, due in part to insufficient tools for visualizing and examining temporal datasets. Spatio-temporal visualization tools are valuable for integrating a temporal component, thus allowing for examination of continuous exposure histories in environmental epidemiologic investigations. An application of these tools to a bladder cancer case-control study in Michigan illustrates continuous exposure life-lines and maps that display smooth, continuous changes over time. Preliminary results suggest increased risk of bladder cancer from combined exposure to arsenic in drinking water (>25 μg/day) and heavy smoking (>30 cigarettes/day) in the 1970s and 1980s, and a possible cancer cluster around automotive, paint, and organic chemical industries in the early 1970s. These tools have broad application for examining spatially- and temporally-specific relationships between exposures to environmental risk factors and disease.

Combining multiple approaches and optimized data resolution for an improved understanding of stream temperature dynamics of a forested headwater basin in the Southern Appalachians

NASA Astrophysics Data System (ADS)

Belica, L.; Mitasova, H.; Caldwell, P.; McCarter, J. B.; Nelson, S. A. C.

2017-12-01

Thermal regimes of forested headwater streams continue to be an area of active research as climatic, hydrologic, and land cover changes can influence water temperature, a key aspect of aquatic ecosystems. Widespread monitoring of stream temperatures have provided an important data source, yielding insights on the temporal and spatial patterns and the underlying processes that influence stream temperature. However, small forested streams remain challenging to model due to the high spatial and temporal variability of stream temperatures and the climatic and hydrologic conditions that drive them. Technological advances and increased computational power continue to provide new tools and measurement methods and have allowed spatially explicit analyses of dynamic natural systems at greater temporal resolutions than previously possible. With the goal of understanding how current stream temperature patterns and processes may respond to changing landcover and hydroclimatoligical conditions, we combined high-resolution, spatially explicit geospatial modeling with deterministic heat flux modeling approaches using data sources that ranged from traditional hydrological and climatological measurements to emerging remote sensing techniques. Initial analyses of stream temperature monitoring data revealed that high temporal resolution (5 minutes) and measurement resolutions (<0.1°C) were needed to adequately describe diel stream temperature patterns and capture the differences between paired 1st order and 4th order forest streams draining north and south facing slopes. This finding along with geospatial models of subcanopy solar radiation and channel morphology were used to develop hypotheses and guide field data collection for further heat flux modeling. By integrating multiple approaches and optimizing data resolution for the processes being investigated, small, but ecologically significant differences in stream thermal regimes were revealed. In this case, multi-approach research contributed to the identification of the dominant mechanisms driving stream temperature in the study area and advanced our understanding of the current thermal fluxes and how they may change as environmental conditions change in the future.

High-Resolution Hydrological Sub-Seasonal Forecasting for Water Resources Management Over Europe

NASA Astrophysics Data System (ADS)

Wood, E. F.; Wanders, N.; Pan, M.; Sheffield, J.; Samaniego, L. E.; Thober, S.; Kumar, R.; Prudhomme, C.; Houghton-Carr, H.

2017-12-01

For decision-making at the sub-seasonal and seasonal time scale, hydrological forecasts with a high temporal and spatial resolution are required by water managers. So far such forecasts have been unavailable due to 1) lack of availability of meteorological seasonal forecasts, 2) coarse temporal resolution of meteorological seasonal forecasts, requiring temporal downscaling, 3) lack of consistency between observations and seasonal forecasts, requiring bias-correction. The EDgE (End-to-end Demonstrator for improved decision making in the water sector in Europe) project commissioned by the ECMWF (C3S) created a unique dataset of hydrological seasonal forecasts derived from four global climate models (CanCM4, FLOR-B01, ECMF, LFPW) in combination with four global hydrological models (PCR-GLOBWB, VIC, mHM, Noah-MP), resulting in 208 forecasts for any given day. The forecasts provide a daily temporal and 5-km spatial resolution, and are bias corrected against E-OBS meteorological observations. The forecasts are communicated to stakeholders via Sectoral Climate Impact Indicators (SCIIs), created in collaboration with the end-user community of the EDgE project (e.g. the percentage of ensemble realizations above the 10th percentile of monthly river flow, or below the 90th). Results show skillful forecasts for discharge from 3 months to 6 months (latter for N Europe due to snow); for soil moisture up to three months due precipitation forecast skill and short initial condition memory; and for groundwater greater than 6 months (lowest skill in western Europe.) The SCIIs are effective in communicating both forecast skill and uncertainty. Overall the new system provides an unprecedented ensemble for seasonal forecasts with significant skill over Europe to support water management. The consistency in both the GCM forecasts and the LSM parameterization ensures a stable and reliable forecast framework and methodology, even if additional GCMs or LSMs are added in the future.

An effective approach for gap-filling continental scale remotely sensed time-series

PubMed Central

Weiss, Daniel J.; Atkinson, Peter M.; Bhatt, Samir; Mappin, Bonnie; Hay, Simon I.; Gething, Peter W.

2014-01-01

The archives of imagery and modeled data products derived from remote sensing programs with high temporal resolution provide powerful resources for characterizing inter- and intra-annual environmental dynamics. The impressive depth of available time-series from such missions (e.g., MODIS and AVHRR) affords new opportunities for improving data usability by leveraging spatial and temporal information inherent to longitudinal geospatial datasets. In this research we develop an approach for filling gaps in imagery time-series that result primarily from cloud cover, which is particularly problematic in forested equatorial regions. Our approach consists of two, complementary gap-filling algorithms and a variety of run-time options that allow users to balance competing demands of model accuracy and processing time. We applied the gap-filling methodology to MODIS Enhanced Vegetation Index (EVI) and daytime and nighttime Land Surface Temperature (LST) datasets for the African continent for 2000–2012, with a 1 km spatial resolution, and an 8-day temporal resolution. We validated the method by introducing and filling artificial gaps, and then comparing the original data with model predictions. Our approach achieved R2 values above 0.87 even for pixels within 500 km wide introduced gaps. Furthermore, the structure of our approach allows estimation of the error associated with each gap-filled pixel based on the distance to the non-gap pixels used to model its fill value, thus providing a mechanism for including uncertainty associated with the gap-filling process in downstream applications of the resulting datasets. PMID:25642100

Ecohydrodynamics of cold-water coral reefs: a case study of the Mingulay Reef Complex (western Scotland).

PubMed

Moreno Navas, Juan; Miller, Peter I; Miller, Peter L; Henry, Lea-Anne; Hennige, Sebastian J; Roberts, J Murray

2014-01-01

Ecohydrodynamics investigates the hydrodynamic constraints on ecosystems across different temporal and spatial scales. Ecohydrodynamics play a pivotal role in the structure and functioning of marine ecosystems, however the lack of integrated complex flow models for deep-water ecosystems beyond the coastal zone prevents further synthesis in these settings. We present a hydrodynamic model for one of Earth's most biologically diverse deep-water ecosystems, cold-water coral reefs. The Mingulay Reef Complex (western Scotland) is an inshore seascape of cold-water coral reefs formed by the scleractinian coral Lophelia pertusa. We applied single-image edge detection and composite front maps using satellite remote sensing, to detect oceanographic fronts and peaks of chlorophyll a values that likely affect food supply to corals and other suspension-feeding fauna. We also present a high resolution 3D ocean model to incorporate salient aspects of the regional and local oceanography. Model validation using in situ current speed, direction and sea elevation data confirmed the model's realistic representation of spatial and temporal aspects of circulation at the reef complex including a tidally driven current regime, eddies, and downwelling phenomena. This novel combination of 3D hydrodynamic modelling and remote sensing in deep-water ecosystems improves our understanding of the temporal and spatial scales of ecological processes occurring in marine systems. The modelled information has been integrated into a 3D GIS, providing a user interface for visualization and interrogation of results that allows wider ecological application of the model and that can provide valuable input for marine biodiversity and conservation applications.

Ecohydrodynamics of Cold-Water Coral Reefs: A Case Study of the Mingulay Reef Complex (Western Scotland)

PubMed Central

Navas, Juan Moreno; Miller, Peter L.; Henry, Lea-Anne; Hennige, Sebastian J.; Roberts, J. Murray

2014-01-01

Ecohydrodynamics investigates the hydrodynamic constraints on ecosystems across different temporal and spatial scales. Ecohydrodynamics play a pivotal role in the structure and functioning of marine ecosystems, however the lack of integrated complex flow models for deep-water ecosystems beyond the coastal zone prevents further synthesis in these settings. We present a hydrodynamic model for one of Earth's most biologically diverse deep-water ecosystems, cold-water coral reefs. The Mingulay Reef Complex (western Scotland) is an inshore seascape of cold-water coral reefs formed by the scleractinian coral Lophelia pertusa. We applied single-image edge detection and composite front maps using satellite remote sensing, to detect oceanographic fronts and peaks of chlorophyll a values that likely affect food supply to corals and other suspension-feeding fauna. We also present a high resolution 3D ocean model to incorporate salient aspects of the regional and local oceanography. Model validation using in situ current speed, direction and sea elevation data confirmed the model's realistic representation of spatial and temporal aspects of circulation at the reef complex including a tidally driven current regime, eddies, and downwelling phenomena. This novel combination of 3D hydrodynamic modelling and remote sensing in deep-water ecosystems improves our understanding of the temporal and spatial scales of ecological processes occurring in marine systems. The modelled information has been integrated into a 3D GIS, providing a user interface for visualization and interrogation of results that allows wider ecological application of the model and that can provide valuable input for marine biodiversity and conservation applications. PMID:24873971

Proterozoic Milankovitch cycles and the history of the solar system.

PubMed

Meyers, Stephen R; Malinverno, Alberto

2018-06-19

The geologic record of Milankovitch climate cycles provides a rich conceptual and temporal framework for evaluating Earth system evolution, bestowing a sharp lens through which to view our planet's history. However, the utility of these cycles for constraining the early Earth system is hindered by seemingly insurmountable uncertainties in our knowledge of solar system behavior (including Earth-Moon history), and poor temporal control for validation of cycle periods (e.g., from radioisotopic dates). Here we address these problems using a Bayesian inversion approach to quantitatively link astronomical theory with geologic observation, allowing a reconstruction of Proterozoic astronomical cycles, fundamental frequencies of the solar system, the precession constant, and the underlying geologic timescale, directly from stratigraphic data. Application of the approach to 1.4-billion-year-old rhythmites indicates a precession constant of 85.79 ± 2.72 arcsec/year (2σ), an Earth-Moon distance of 340,900 ± 2,600 km (2σ), and length of day of 18.68 ± 0.25 hours (2σ), with dominant climatic precession cycles of ∼14 ky and eccentricity cycles of ∼131 ky. The results confirm reduced tidal dissipation in the Proterozoic. A complementary analysis of Eocene rhythmites (∼55 Ma) illustrates how the approach offers a means to map out ancient solar system behavior and Earth-Moon history using the geologic archive. The method also provides robust quantitative uncertainties on the eccentricity and climatic precession periods, and derived astronomical timescales. As a consequence, the temporal resolution of ancient Earth system processes is enhanced, and our knowledge of early solar system dynamics is greatly improved.

Quality of a fished resource: Assessing spatial and temporal dynamics

PubMed Central

Lorda, Julio; Shears, Nick T.; Ben-Horin, Tal; Toseland, Rebecca E.; Rathbone, Sarah T.; Rudie, Dave; Gaines, Steven D.

2018-01-01

Understanding spatio-temporal variability in the demography of harvested species is essential to improve sustainability, especially if there is large geographic variation in demography. Reproductive patterns commonly vary spatially, which is particularly important for management of “roe”-based fisheries, since profits depend on both the number and reproductive condition of individuals. The red sea urchin, Mesocentrotus franciscanus, is harvested in California for its roe (gonad), which is sold to domestic and international sushi markets. The primary driver of price within this multi-million-dollar industry is gonad quality. A relatively simple measure of the fraction of the body mass that is gonad, the gonadosomatic index (GSI), provides important insight into the ecological and environmental factors associated with variability in reproductive quality, and hence value within the industry. We identified the seasonality of the reproductive cycle and determined whether it varied within a heavily fished region. We found that fishermen were predictable both temporally and spatially in collecting urchins according to the reproductive dynamics of urchins. We demonstrated the use of red sea urchin GSI as a simple, quantitative tool to predict quality, effort, landings, price, and value of the fishery. We found that current management is not effectively realizing some objectives for the southern California fishery, since the reproductive cycle does not match the cycle in northern California, where these management guidelines were originally shaped. Although regulations may not be meeting initial management goals, the scheme may in fact provide conservation benefits by curtailing effort during part of the high-quality fishing season right before spawning. PMID:29874229

Identifying Optimal Temporal Scale for the Correlation of AOD and Ground Measurements of PM2.5 to Improve the Model Performance in a Real-time Air Quality Estimation System

NASA Technical Reports Server (NTRS)

Li, Hui; Faruque, Fazlay; Williams, Worth; Al-Hamdan, Mohammad; Luvall, Jeffrey C.; Crosson, William; Rickman, Douglas; Limaye, Ashutosh

2009-01-01

Aerosol optical depth (AOD), an indirect estimate of particle matter using satellite observations, has shown great promise in improving estimates of PM 2.5 air quality surface. Currently, few studies have been conducted to explore the optimal way to apply AOD data to improve the model accuracy of PM 2.5 surface estimation in a real-time air quality system. We believe that two major aspects may be worthy of consideration in that area: 1) the approach to integrate satellite measurements with ground measurements in the pollution estimation, and 2) identification of an optimal temporal scale to calculate the correlation of AOD and ground measurements. This paper is focused on the second aspect on the identifying the optimal temporal scale to correlate AOD with PM2.5. Five following different temporal scales were chosen to evaluate their impact on the model performance: 1) within the last 3 days, 2) within the last 10 days, 3) within the last 30 days, 4) within the last 90 days, and 5) the time period with the highest correlation in a year. The model performance is evaluated for its accuracy, bias, and errors based on the following selected statistics: the Mean Bias, the Normalized Mean Bias, the Root Mean Square Error, Normalized Mean Error, and the Index of Agreement. This research shows that the model with the temporal scale of within the last 30 days displays the best model performance in this study area using 2004 and 2005 data sets.

Assessing the Resolution Adaptability of the Zhang-McFarlane Cumulus Parameterization With Spatial and Temporal Averaging: RESOLUTION ADAPTABILITY OF ZM SCHEME

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

Yun, Yuxing; Fan, Jiwen; Xiao, Heng

Realistic modeling of cumulus convection at fine model resolutions (a few to a few tens of km) is problematic since it requires the cumulus scheme to adapt to higher resolution than they were originally designed for (~100 km). To solve this problem, we implement the spatial averaging method proposed in Xiao et al. (2015) and also propose a temporal averaging method for the large-scale convective available potential energy (CAPE) tendency in the Zhang-McFarlane (ZM) cumulus parameterization. The resolution adaptability of the original ZM scheme, the scheme with spatial averaging, and the scheme with both spatial and temporal averaging at 4-32more » km resolution is assessed using the Weather Research and Forecasting (WRF) model, by comparing with Cloud Resolving Model (CRM) results. We find that the original ZM scheme has very poor resolution adaptability, with sub-grid convective transport and precipitation increasing significantly as the resolution increases. The spatial averaging method improves the resolution adaptability of the ZM scheme and better conserves the total transport of moist static energy and total precipitation. With the temporal averaging method, the resolution adaptability of the scheme is further improved, with sub-grid convective precipitation becoming smaller than resolved precipitation for resolution higher than 8 km, which is consistent with the results from the CRM simulation. Both the spatial distribution and time series of precipitation are improved with the spatial and temporal averaging methods. The results may be helpful for developing resolution adaptability for other cumulus parameterizations that are based on quasi-equilibrium assumption.« less

Feasibility of high temporal resolution breast DCE-MRI using compressed sensing theory.

PubMed

Wang, Haoyu; Miao, Yanwei; Zhou, Kun; Yu, Yanming; Bao, Shanglian; He, Qiang; Dai, Yongming; Xuan, Stephanie Y; Tarabishy, Bisher; Ye, Yongquan; Hu, Jiani

2010-09-01

To investigate the feasibility of high temporal resolution breast DCE-MRI using compressed sensing theory. Two experiments were designed to investigate the feasibility of using reference image based compressed sensing (RICS) technique in DCE-MRI of the breast. The first experiment examined the capability of RICS to faithfully reconstruct uptake curves using undersampled data sets extracted from fully sampled clinical breast DCE-MRI data. An average approach and an approach using motion estimation and motion compensation (ME/MC) were implemented to obtain reference images and to evaluate their efficacy in reducing motion related effects. The second experiment, an in vitro phantom study, tested the feasibility of RICS for improving temporal resolution without degrading the spatial resolution. For the uptake-curve reconstruction experiment, there was a high correlation between uptake curves reconstructed from fully sampled data by Fourier transform and from undersampled data by RICS, indicating high similarity between them. The mean Pearson correlation coefficients for RICS with the ME/MC approach and RICS with the average approach were 0.977 +/- 0.023 and 0.953 +/- 0.031, respectively. The comparisons of final reconstruction results between RICS with the average approach and RICS with the ME/MC approach suggested that the latter was superior to the former in reducing motion related effects. For the in vitro experiment, compared to the fully sampled method, RICS improved the temporal resolution by an acceleration factor of 10 without degrading the spatial resolution. The preliminary study demonstrates the feasibility of RICS for faithfully reconstructing uptake curves and improving temporal resolution of breast DCE-MRI without degrading the spatial resolution.

Temporal grouping effects in musical short-term memory.

PubMed

Gorin, Simon; Mengal, Pierre; Majerus, Steve

2018-07-01

Recent theoretical accounts of verbal and visuo-spatial short-term memory (STM) have proposed the existence of domain-general mechanisms for the maintenance of serial order information. These accounts are based on the observation of similar behavioural effects across several modalities, such as temporal grouping effects. Across two experiments, the present study aimed at extending these findings, by exploring a STM modality that has received little interest so far, STM for musical information. Given its inherent rhythmic, temporal and serial organisation, the musical domain is of interest for investigating serial order STM processes such as temporal grouping. In Experiment 1, the data did not allow to determine the presence or the absence of temporal grouping effects. In Experiment 2, we observed that temporal grouping of tone sequences during encoding improves short-term recognition for serially presented probe tones. Furthermore, the serial position curves included micro-primacy and micro-recency effects, which are the hallmark characteristic of temporal grouping. Our results suggest that the encoding of serial order information in musical STM may be supported by temporal positional coding mechanisms similar to those reported in the verbal domain.

Remote Sensing Technologies for Estuary Research and Management (Invited)

NASA Astrophysics Data System (ADS)

Hestir, E. L.; Ustin, S.; Khanna, S.; Botha, E.; Santos, M. J.; Anstee, J.; Greenberg, J. A.

2013-12-01

Estuarine ecosystems and their biogeochemical processes are extremely vulnerable to climate and environmental changes, and are threatened by sea level rise and upstream activities such as land use/land cover and hydrological changes. Despite the recognized threat to estuaries, most aspects of how change will affect estuaries are not well understood due to the poorly resolved understanding of the complex physical, chemical and biological processes and their interactions in estuarine systems. New and innovative remote sensing technologies such as high spectral resolution optical and thermal imagers and lidar, microwave radiometers and radar imagers enable measurements of key environmental parameters needed to establish baseline conditions and improve modeling efforts. Radar's sensitivity to water provides information about water height and velocity, channel geometry and wetland inundation. Water surface temperature and salinity and can be measured from microwave radiometry, and when combined with radar-derived information can provide information about estuarine hydrodynamics. Optical and thermal hyperspectral imagers provide information about sediment, plant and water chemistry including chlorophyll, dissolved organic matter and mineralogical composition. Lidar can measure bathymetry, microtopography and emergent plant structure. Plant functional types, wetland community distributions, turbidity, suspended and deposited sediments, dissolved organic matter, water column chlorophyll and phytoplankton functional types may be estimated from these measurements. Innovative deployment of advanced remote sensing technologies on airborne and submersible un-piloted platforms provides temporally and spatially continuous measurement in temporally dynamic and spatially complex tidal systems. Through biophysically-based retrievals, these technologies provide direct measurement of physical, biological and biogeochemical conditions that can be used as models to understand estuarine processes and forecast responses to change. We demonstrate that innovative remote sensing technologies, coupled with long term datasets from satellite earth observing missions and in situ sensor networks provide the spatially contiguous measurements needed to make 'supra-regional' (e.g. river to coast) assessments of ecological communities, habitat distribution, ecosystem function, sediment, nutrient and carbon source and transport. We show that this information can be used to improve environmental modeling with increased confidence and support informed environmental management.

Temporal and Statistical Information in Causal Structure Learning

ERIC Educational Resources Information Center

McCormack, Teresa; Frosch, Caren; Patrick, Fiona; Lagnado, David

2015-01-01

Three experiments examined children's and adults' abilities to use statistical and temporal information to distinguish between common cause and causal chain structures. In Experiment 1, participants were provided with conditional probability information and/or temporal information and asked to infer the causal structure of a 3-variable mechanical…

Thalamocortical NMDA conductances and intracortical inhibition can explain cortical temporal tuning

NASA Technical Reports Server (NTRS)

Krukowski, A. E.; Miller, K. D.

2001-01-01

Cells in cerebral cortex fail to respond to fast-moving stimuli that evoke strong responses in the thalamic nuclei innervating the cortex. The reason for this behavior has remained a mystery. We study an experimentally motivated model of the thalamic input-recipient layer of cat primary visual cortex that accounts for many aspects of cortical orientation tuning. In this circuit, inhibition dominates over excitation, but temporal modulations of excitation and inhibition occur out of phase with one another, allowing excitation to transiently drive cells. We show that this circuit provides a natural explanation of cortical low-pass temporal frequency tuning, provided N-methyl-D-aspartate (NMDA) receptors are present in thalamocortical synapses in proportions measured experimentally. This suggests a new and unanticipated role for NMDA conductances in shaping the temporal response properties of cortical cells, and suggests that common cortical circuit mechanisms underlie both spatial and temporal response tuning.

The Mathematics of Dispatchability, Revisited

NASA Technical Reports Server (NTRS)

Morris, Paul

2016-01-01

Dispatchability is an important property for the efficient execution of temporal plans where the temporal constraints are represented as a Simple Temporal Network (STN). It has been shown that every STN may be reformulated as a dispatchable STN, and dispatchability ensures that the temporal constraints need only be satisfied locally during execution. Recently, it has also been shown that Simple Temporal Networks with Uncertainty, augmented with wait edges, are Dynamically Controllable provided every projection is dispatchable. Thus, dispatchability has considerable theoretical as well as practical significance. One thing that hampers further work in this area is the underdeveloped theory. Moreover, the existing foundation is inadequate in certain respects. In this paper, we develop a new mathematical theory of dispatchability and its relationship to execution. We also provide several characterizations of dispatchability, including characterizations in terms of the structural properties of the STN graph. This facilitates the potential application of the theory to other areas.

Hyperspectral imaging spectro radiometer improves radiometric accuracy

NASA Astrophysics Data System (ADS)

Prel, Florent; Moreau, Louis; Bouchard, Robert; Bullis, Ritchie D.; Roy, Claude; Vallières, Christian; Levesque, Luc

2013-06-01

Reliable and accurate infrared characterization is necessary to measure the specific spectral signatures of aircrafts and associated infrared counter-measures protections (i.e. flares). Infrared characterization is essential to improve counter measures efficiency, improve friend-foe identification and reduce the risk of friendly fire. Typical infrared characterization measurement setups include a variety of panchromatic cameras and spectroradiometers. Each instrument brings essential information; cameras measure the spatial distribution of targets and spectroradiometers provide the spectral distribution of the emitted energy. However, the combination of separate instruments brings out possible radiometric errors and uncertainties that can be reduced with Hyperspectral imagers. These instruments combine both spectral and spatial information into the same data. These instruments measure both the spectral and spatial distribution of the energy at the same time ensuring the temporal and spatial cohesion of collected information. This paper presents a quantitative analysis of the main contributors of radiometric uncertainties and shows how a hyperspectral imager can reduce these uncertainties.

Soil erodibility for water erosion: A perspective and Chinese experiences

NASA Astrophysics Data System (ADS)

Wang, Bin; Zheng, Fenli; Römkens, Mathias J. M.; Darboux, Frédéric

2013-04-01

Knowledge of soil erodibility is an essential requirement for erosion prediction, conservation planning, and the assessment of sediment related environmental effects of watershed agricultural practices. This paper reviews the status of soil erodibility evaluations and determinations based on 80 years of upland area erosion research mainly in China and the USA. The review synthesizes the general research progress made by discussing the basic concepts of erodibility and its evaluation, determination, and prediction as well as knowledge of its spatio-temporal variations. The authors found that soil erodibility is often inappropriately or inaccurately applied in describing soil loss caused by different soil erosion component processes and mechanisms. Soil erodibility indicators were related to intrinsic soil properties and exogenic erosional forces, measurements, and calculations. The present review describes major needs including: (1) improved definition of erodibility, (2) modified erodibility determinations in erosion models, especially for specific geographical locations and in the context of different erosion sub-processes, (3) advanced methodologies for quantifying erodibilities of different soil erosion sub-processes, and (4) a better understanding of the mechanism that causes temporal variations in soil erodibility. The review also provides a more rational basis for future research on soil erodibility and supports predictive modeling of soil erosion processes and the development of improved conservation practices.

Electrocortical changes associated with minocycline treatment in fragile X syndrome.

PubMed

Schneider, Andrea; Leigh, Mary Jacena; Adams, Patrick; Nanakul, Rawi; Chechi, Tasleem; Olichney, John; Hagerman, Randi; Hessl, David

2013-10-01

Minocycline normalizes synaptic connections and behavior in the knockout mouse model of fragile X syndrome (FXS). Human-targeted treatment trials with minocycline have shown benefits in behavioral measures and parent reports. Event-related potentials (ERPs) may provide a sensitive method of monitoring treatment response and changes in coordinated brain activity. Measurement of electrocortical changes due to minocycline was done in a double-blind, placebo-controlled crossover treatment trial in children with FXS. Children with FXS (Meanage 10.5 years) were randomized to minocycline or placebo treatment for 3 months then changed to the other treatment for 3 months. The minocycline dosage ranged from 25-100 mg daily, based on weight. Twelve individuals with FXS (eight male, four female) completed ERP studies using a passive auditory oddball paradigm. Current source density (CSD) and ERP analysis at baseline showed high-amplitude, long-latency components over temporal regions. After 3 months of treatment with minocycline, the temporal N1 and P2 amplitudes were significantly reduced compared with placebo. There was a significant amplitude increase of the central P2 component on minocycline. Electrocortical habituation to auditory stimuli improved with minocycline treatment. Our study demonstrated improvements of the ERP in children with FXS treated with minocycline, and the potential feasibility and sensitivity of ERPs as a cognitive biomarker in FXS treatment trials.

Precipitation Characteristics in Tropical Africa Using Satellite and In-Situ Observations

NASA Technical Reports Server (NTRS)

Dezfuli, Amin; Ichoku, Charles; Huffman, George; Mohr, Karen

2017-01-01

Tropical Africa receives nearly all its precipitation as a result of convection. The characteristics of rain-producing systems in this region, despite their crucial role in regional and global circulation, have not been well-understood. This is mainly due to the lack of in situ observations. Here, we have used precipitation records from the Trans-African Hydro-Meteorological Observatory (TAHMO) to improve our knowledge about the rainfall systems in the region, and to validate the recently-released IMERG precipitation product. The high temporal resolution of the gauge data has allowed us to identify three classes of rain events based on their duration and intensity. The contribution of each class to the total rainfall and the favorable surface atmospheric conditions for each class have been examined. As IMERG aims to continue the legacy of its predecessor, TMPA, and provide higher resolution data, continent-wide comparisons are made between these two products. IMERG, due to its improved temporal resolution, shows some advantages over TMPA in capturing the diurnal cycle and propagation of the meso-scale convective systems. However, the performance of the two satellite-based products varies by season, region and the evaluation statistics. The results of this study serve as a basis for our ongoing work on the impacts of biomass burning on precipitation processes in Africa.

Joint level-set and spatio-temporal motion detection for cell segmentation.

PubMed

Boukari, Fatima; Makrogiannis, Sokratis

2016-08-10

Cell segmentation is a critical step for quantification and monitoring of cell cycle progression, cell migration, and growth control to investigate cellular immune response, embryonic development, tumorigenesis, and drug effects on live cells in time-lapse microscopy images. In this study, we propose a joint spatio-temporal diffusion and region-based level-set optimization approach for moving cell segmentation. Moving regions are initially detected in each set of three consecutive sequence images by numerically solving a system of coupled spatio-temporal partial differential equations. In order to standardize intensities of each frame, we apply a histogram transformation approach to match the pixel intensities of each processed frame with an intensity distribution model learned from all frames of the sequence during the training stage. After the spatio-temporal diffusion stage is completed, we compute the edge map by nonparametric density estimation using Parzen kernels. This process is followed by watershed-based segmentation and moving cell detection. We use this result as an initial level-set function to evolve the cell boundaries, refine the delineation, and optimize the final segmentation result. We applied this method to several datasets of fluorescence microscopy images with varying levels of difficulty with respect to cell density, resolution, contrast, and signal-to-noise ratio. We compared the results with those produced by Chan and Vese segmentation, a temporally linked level-set technique, and nonlinear diffusion-based segmentation. We validated all segmentation techniques against reference masks provided by the international Cell Tracking Challenge consortium. The proposed approach delineated cells with an average Dice similarity coefficient of 89 % over a variety of simulated and real fluorescent image sequences. It yielded average improvements of 11 % in segmentation accuracy compared to both strictly spatial and temporally linked Chan-Vese techniques, and 4 % compared to the nonlinear spatio-temporal diffusion method. Despite the wide variation in cell shape, density, mitotic events, and image quality among the datasets, our proposed method produced promising segmentation results. These results indicate the efficiency and robustness of this method especially for mitotic events and low SNR imaging, enabling the application of subsequent quantification tasks.

NHM-SMAP: spatially and temporally high-resolution nonhydrostatic atmospheric model coupled with detailed snow process model for Greenland Ice Sheet

NASA Astrophysics Data System (ADS)

Niwano, Masashi; Aoki, Teruo; Hashimoto, Akihiro; Matoba, Sumito; Yamaguchi, Satoru; Tanikawa, Tomonori; Fujita, Koji; Tsushima, Akane; Iizuka, Yoshinori; Shimada, Rigen; Hori, Masahiro

2018-02-01

To improve surface mass balance (SMB) estimates for the Greenland Ice Sheet (GrIS), we developed a 5 km resolution regional climate model combining the Japan Meteorological Agency Non-Hydrostatic atmospheric Model and the Snow Metamorphism and Albedo Process model (NHM-SMAP) with an output interval of 1 h, forced by the Japanese 55-year reanalysis (JRA-55). We used in situ data to evaluate NHM-SMAP in the GrIS during the 2011-2014 mass balance years. We investigated two options for the lower boundary conditions of the atmosphere: an offline configuration using snow, firn, and ice albedo, surface temperature data from JRA-55, and an online configuration using values from SMAP. The online configuration improved model performance in simulating 2 m air temperature, suggesting that the surface analysis provided by JRA-55 is inadequate for the GrIS and that SMAP results can better simulate physical conditions of snow/firn/ice. It also reproduced the measured features of the GrIS climate, diurnal variations, and even a strong mesoscale wind event. In particular, it successfully reproduced the temporal evolution of the GrIS surface melt area extent as well as the record melt event around 12 July 2012, at which time the simulated melt area extent reached 92.4 %. Sensitivity tests showed that the choice of calculation schemes for vertical water movement in snow and firn has an effect as great as 200 Gt year-1 in the GrIS-wide accumulated SMB estimates; a scheme based on the Richards equation provided the best performance.

Four-dimensional optical coherence tomography imaging of total liquid ventilated rats

NASA Astrophysics Data System (ADS)

Kirsten, Lars; Schnabel, Christian; Gaertner, Maria; Koch, Edmund

2013-06-01

Optical coherence tomography (OCT) can be utilized for the spatially and temporally resolved visualization of alveolar tissue and its dynamics in rodent models, which allows the investigation of lung dynamics on the microscopic scale of single alveoli. The findings could provide experimental input data for numerical simulations of lung tissue mechanics and could support the development of protective ventilation strategies. Real four-dimensional OCT imaging permits the acquisition of several OCT stacks within one single ventilation cycle. Thus, the entire four-dimensional information is directly obtained. Compared to conventional virtual four-dimensional OCT imaging, where the image acquisition is extended over many ventilation cycles and is triggered on pressure levels, real four-dimensional OCT is less vulnerable against motion artifacts and non-reproducible movement of the lung tissue over subsequent ventilation cycles, which widely reduces image artifacts. However, OCT imaging of alveolar tissue is affected by refraction and total internal reflection at air-tissue interfaces. Thus, only the first alveolar layer beneath the pleura is visible. To circumvent this effect, total liquid ventilation can be carried out to match the refractive indices of lung tissue and the breathing medium, which improves the visibility of the alveolar structure, the image quality and the penetration depth and provides the real structure of the alveolar tissue. In this study, a combination of four-dimensional OCT imaging with total liquid ventilation allowed the visualization of the alveolar structure in rat lung tissue benefiting from the improved depth range beneath the pleura and from the high spatial and temporal resolution.

Rod Electroretinograms Elicited by Silent Substitution Stimuli from the Light-Adapted Human Eye

PubMed Central

Maguire, John; Parry, Neil R. A.; Kremers, Jan; Kommanapalli, Deepika; Murray, Ian J.; McKeefry, Declan J.

2016-01-01

Purpose To demonstrate that silent substitution stimuli can be used to generate electroretinograms (ERGs) that effectively isolate rod photoreceptor function in humans without the need for dark adaptation, and that this approach constitutes a viable alternative to current clinical standard testing protocols. Methods Rod-isolating and non-isolating sinusoidal flicker stimuli were generated on a 4 primary light-emitting diode (LED) Ganzfeld stimulator to elicit ERGs from participants with normal and compromised rod function who had not undergone dark-adaptation. Responses were subjected to Fourier analysis, and the amplitude and phase of the fundamental were used to examine temporal frequency and retinal illuminance response characteristics. Results Electroretinograms elicited by rod-isolating silent substitution stimuli exhibit low-pass temporal frequency response characteristics with an upper response limit of 30 Hz. Responses are optimal between 5 and 8 Hz and between 10 and 100 photopic trolands (Td). There is a significant correlation between the response amplitudes obtained with the silent substitution method and current standard clinical protocols. Analysis of signal-to-noise ratios reveals significant differences between subjects with normal and compromised rod function. Conclusions Silent substitution provides an effective method for the isolation of human rod photoreceptor function in subjects with normal as well as compromised rod function when stimuli are used within appropriate parameter ranges. Translational Relevance This method of generating rod-mediated ERGs can be achieved without time-consuming periods of dark adaptation, provides improved isolation of rod- from cone-based activity, and will lead to the development of faster clinical electrophysiologic testing protocols with improved selectivity. PMID:27617180

Towards Enhanced Underwater Lidar Detection via Source Separation

NASA Astrophysics Data System (ADS)

Illig, David W.

Interest in underwater optical sensors has grown as technologies enabling autonomous underwater vehicles have been developed. Propagation of light through water is complicated by the dual challenges of absorption and scattering. While absorption can be reduced by operating in the blue-green region of the visible spectrum, reducing scattering is a more significant challenge. Collection of scattered light negatively impacts underwater optical ranging, imaging, and communications applications. This thesis concentrates on the ranging application, where scattering reduces operating range as well as range accuracy. The focus of this thesis is on the problem of backscatter, which can create a "clutter" return that may obscure submerged target(s) of interest. The main contributions of this thesis are explorations of signal processing approaches to increase the separation between the target and backscatter returns. Increasing this separation allows detection of weak targets in the presence of strong scatter, increasing both operating range and range accuracy. Simulation and experimental results will be presented for a variety of approaches as functions of water clarity and target position. This work provides several novel contributions to the underwater lidar field: 1. Quantification of temporal separation approaches: While temporal separation has been studied extensively, this work provides a quantitative assessment of the extent to which both high frequency modulation and spatial filter approaches improve the separation between target and backscatter. 2. Development and assessment of frequency separation: This work includes the first frequency-based separation approach for underwater lidar, in which the channel frequency response is measured with a wideband waveform. Transforming to the time-domain gives a channel impulse response, in which target and backscatter returns may appear in unique range bins and thus be separated. 3. Development and assessment of statistical separation: The first investigations of statistical separation approaches for underwater lidar are presented. By demonstrating that target and backscatter returns have different statistical properties, a new separation axis is opened. This work investigates and quantifies performance of three statistical separation approaches. 4. Application of detection theory to underwater lidar: While many similar applications use detection theory to assess performance, less development has occurred in the underwater lidar field. This work applies these concepts to statistical separation approaches, providing another perspective in which to assess performance. In addition, by using detection theory approaches, statistical metrics can be used to associate a level of confidence in each ranging measurement. 5. Preliminary investigation of forward scatter suppression: If backscatter is sufficiently suppressed, forward scattering becomes a performance-limiting factor. This work presents a proof-of-concept demonstration of the potential for statistical separation approaches to suppress both forward and backward scatter. These results provide a demonstration of the capability that signal processing has to improve separation between target and backscatter. Separation capability improves in the transition from temporal to frequency to statistical separation approaches, with the statistical separation approaches improving target detection sensitivity by as much as 30 dB. Ranging and detection results demonstrate the enhanced performance this would allow in ranging applications. This increased performance is an important step in moving underwater lidar capability towards the requirements of the next generation of sensors.

Harmful algal bloom characterization at ultra-high spatial and temporal resolution using small unmanned aircraft systems.

PubMed

Van der Merwe, Deon; Price, Kevin P

2015-03-27

Harmful algal blooms (HABs) degrade water quality and produce toxins. The spatial distribution of HAbs may change rapidly due to variations wind, water currents, and population dynamics. Risk assessments, based on traditional sampling methods, are hampered by the sparseness of water sample data points, and delays between sampling and the availability of results. There is a need for local risk assessment and risk management at the spatial and temporal resolution relevant to local human and animal interactions at specific sites and times. Small, unmanned aircraft systems can gather color-infrared reflectance data at appropriate spatial and temporal resolutions, with full control over data collection timing, and short intervals between data gathering and result availability. Data can be interpreted qualitatively, or by generating a blue normalized difference vegetation index (BNDVI) that is correlated with cyanobacterial biomass densities at the water surface, as estimated using a buoyant packed cell volume (BPCV). Correlations between BNDVI and BPCV follow a logarithmic model, with r(2)-values under field conditions from 0.77 to 0.87. These methods provide valuable information that is complimentary to risk assessment data derived from traditional risk assessment methods, and could help to improve risk management at the local level.

Right Fronto-Temporal EEG can Differentiate the Affective Responses to Award-Winning Advertisements.

PubMed

Wang, Regina W Y; Huarng, Shy-Peih; Chuang, Shang-Wen

2018-04-01

Affective engineering aims to improve service/product design by translating the customer's psychological feelings. Award-winning advertisements (AAs) were selected on the basis of the professional standards that consider creativity as a prerequisite. However, it is unknown if AA is related to satisfactory advertising performance among customers or only to the experts' viewpoints towards the advertisements. This issue in the field of affective engineering and design merits in-depth evaluation. We recruited 30 subjects and performed an electroencephalography (EEG) experiment while watching AAs and non-AAs (NAAs). The event-related potential (ERP) data showed that AAs evoked larger positive potentials 250-1400 [Formula: see text]ms after stimulus onset, particularly in the right fronto-temporal regions. The behavioral results were consistent with the professional recognition given to AAs by experts. The perceived levels of creativity and "product-like" quality were higher for the AAs than for the NAAs. Event-related spectral perturbation (ERSP) analysis further revealed statistically significant differences in the theta, alpha, beta, and gamma band activity in the right fronto-temporal regions between the AAs and NAAs. Our results confirm that EEG features from the time/frequency domains can differentiate affective responses to AAs at a neural circuit level, and provide scientific evidence to support the identification of AAs.

Light-sheet enhanced resolution of light field microscopy for rapid imaging of large volumes

NASA Astrophysics Data System (ADS)

Madrid Wolff, Jorge; Castro, Diego; Arbeláez, Pablo; Forero-Shelton, Manu

2018-02-01

Whole-brain imaging is challenging because it demands microscopes with high temporal and spatial resolution, which are often at odds, especially in the context of large fields of view. We have designed and built a light-sheet microscope with digital micromirror illumination and light-field detection. On the one hand, light sheets provide high resolution optical sectioning on live samples without compromising their viability. On the other hand, light field imaging makes it possible to reconstruct full volumes of relatively large fields of view from a single camera exposure; however, its enhanced temporal resolution comes at the expense of spatial resolution, limiting its applicability. We present an approach to increase the resolution of light field images using DMD-based light sheet illumination. To that end, we develop a method to produce synthetic resolution targets for light field microscopy and a procedure to correct the depth at which planes are refocused with rendering software. We measured the axial resolution as a function of depth and show a three-fold potential improvement with structured illumination, albeit by sacrificing some temporal resolution, also three-fold. This results in an imaging system that may be adjusted to specific needs without having to reassemble and realign it. This approach could be used to image relatively large samples at high rates.

Determination of Earth outgoing radiation using a constellation of satellites

NASA Astrophysics Data System (ADS)

Gristey, Jake; Chiu, Christine; Gurney, Robert; Han, Shin-Chan; Morcrette, Cyril

2017-04-01

The outgoing radiation fluxes at the top of the atmosphere, referred to as Earth outgoing radiation (EOR), constitute a vital component of the Earth's energy budget. This EOR exhibits strong diurnal signatures and is inherently connected to the rapidly evolving scene from which the radiation originates, so our ability to accurately monitor EOR with sufficient temporal resolution and spatial coverage is crucial for weather and climate studies. Despite vast improvements in satellite observations in recent decades, achieving these criteria remains challenging from current measurements. A technology revolution in small satellites and sensor miniaturisation has created a new and exciting opportunity for a novel, viable and sustainable observation strategy from a constellation of satellites, capable of providing both global coverage and high temporal resolution simultaneously. To explore the potential of a constellation approach for observing EOR we perform a series of theoretical simulation experiments. Using the results from these simulation experiments, we will demonstrate a baseline constellation configuration capable of accurately monitoring global EOR at unprecedented temporal resolution. We will also show whether it is possible to reveal synoptic scale, fast evolving phenomena by applying a deconvolution technique to the simulated measurements. The ability to observe and understand the relationship between these phenomena and changes in EOR is of fundamental importance in constraining future warming of our climate system.

Harmful Algal Bloom Characterization at Ultra-High Spatial and Temporal Resolution Using Small Unmanned Aircraft Systems

PubMed Central

Van der Merwe, Deon; Price, Kevin P.

2015-01-01

Harmful algal blooms (HABs) degrade water quality and produce toxins. The spatial distribution of HAbs may change rapidly due to variations wind, water currents, and population dynamics. Risk assessments, based on traditional sampling methods, are hampered by the sparseness of water sample data points, and delays between sampling and the availability of results. There is a need for local risk assessment and risk management at the spatial and temporal resolution relevant to local human and animal interactions at specific sites and times. Small, unmanned aircraft systems can gather color-infrared reflectance data at appropriate spatial and temporal resolutions, with full control over data collection timing, and short intervals between data gathering and result availability. Data can be interpreted qualitatively, or by generating a blue normalized difference vegetation index (BNDVI) that is correlated with cyanobacterial biomass densities at the water surface, as estimated using a buoyant packed cell volume (BPCV). Correlations between BNDVI and BPCV follow a logarithmic model, with r2-values under field conditions from 0.77 to 0.87. These methods provide valuable information that is complimentary to risk assessment data derived from traditional risk assessment methods, and could help to improve risk management at the local level. PMID:25826055

Rate discrimination at low pulse rates in normal-hearing and cochlear implant listeners: Influence of intracochlear stimulation site.

PubMed

Stahl, Pierre; Macherey, Olivier; Meunier, Sabine; Roman, Stéphane

2016-04-01

Temporal pitch perception in cochlear implantees remains weaker than in normal hearing listeners and is usually limited to rates below about 300 pulses per second (pps). Recent studies have suggested that stimulating the apical part of the cochlea may improve the temporal coding of pitch by cochlear implants (CIs), compared to stimulating other sites. The present study focuses on rate discrimination at low pulse rates (ranging from 20 to 104 pps). Two experiments measured and compared pulse rate difference limens (DLs) at four fundamental frequencies (ranging from 20 to 104 Hz) in both CI and normal-hearing (NH) listeners. Experiment 1 measured DLs in users of the (Med-El CI, Innsbruck, Austria) device for two electrodes (one apical and one basal). In experiment 2, DLs for NH listeners were compared for unresolved harmonic complex tones filtered in two frequency regions (lower cut-off frequencies of 1200 and 3600 Hz, respectively) and for different bandwidths. Pulse rate discrimination performance was significantly better when stimulation was provided by the apical electrode in CI users and by the lower-frequency tone complexes in NH listeners. This set of data appears consistent with better temporal coding when stimulation originates from apical regions of the cochlea.

Mechanisms of impulsive choice: II. Time-based interventions to improve self-control

PubMed Central

Smith, Aaron P.; Marshall, Andrew T.; Kirkpatrick, Kimberly

2014-01-01

Impulsive choice behavior has been proposed as a primary risk factor for other maladaptive behaviors (e.g., gambling, substance abuse). Recent research has suggested that timing processes may play a key role in impulsive choice behavior, and could provide an avenue for altering impulsive choice. Accordingly, the current experiments assessed a set of time-based behavioral interventions to increase self-control while simultaneously assessing effects on timing processes within the impulsive choice task. Three experiments assessed temporal interventions using a differential reinforcement of low rates task (Experiment 1) and exposure to either a variable or fixed interval schedule (Experiments 2–3). The efficacy of the interventions was assessed in Sprague-Dawley (Experiments 1–2) and Lewis (Experiment 3) rat strains. Impulsive choice behavior was assessed by measuring preferences of a smaller-sooner (SS) versus a larger-later (LL) reward, while timing of the SS and LL durations was measured during peak trials within the impulsive choice procedure. The rats showed an increased preference for the LL following all three time-based interventions and also displayed increased temporal precision. These results add to the increasing evidence that supports a possible role for temporal processing in impulsive choice behavior and supply novel behavioral interventions to decrease impulsive behavior. PMID:25444771

Photon gating in four-dimensional ultrafast electron microscopy.

PubMed

Hassan, Mohammed T; Liu, Haihua; Baskin, John Spencer; Zewail, Ahmed H

2015-10-20

Ultrafast electron microscopy (UEM) is a pivotal tool for imaging of nanoscale structural dynamics with subparticle resolution on the time scale of atomic motion. Photon-induced near-field electron microscopy (PINEM), a key UEM technique, involves the detection of electrons that have gained energy from a femtosecond optical pulse via photon-electron coupling on nanostructures. PINEM has been applied in various fields of study, from materials science to biological imaging, exploiting the unique spatial, energy, and temporal characteristics of the PINEM electrons gained by interaction with a "single" light pulse. The further potential of photon-gated PINEM electrons in probing ultrafast dynamics of matter and the optical gating of electrons by invoking a "second" optical pulse has previously been proposed and examined theoretically in our group. Here, we experimentally demonstrate this photon-gating technique, and, through diffraction, visualize the phase transition dynamics in vanadium dioxide nanoparticles. With optical gating of PINEM electrons, imaging temporal resolution was improved by a factor of 3 or better, being limited only by the optical pulse widths. This work enables the combination of the high spatial resolution of electron microscopy and the ultrafast temporal response of the optical pulses, which provides a promising approach to attain the resolution of few femtoseconds and attoseconds in UEM.

Photon gating in four-dimensional ultrafast electron microscopy

PubMed Central

Hassan, Mohammed T.; Liu, Haihua; Baskin, John Spencer; Zewail, Ahmed H.

2015-01-01

Ultrafast electron microscopy (UEM) is a pivotal tool for imaging of nanoscale structural dynamics with subparticle resolution on the time scale of atomic motion. Photon-induced near-field electron microscopy (PINEM), a key UEM technique, involves the detection of electrons that have gained energy from a femtosecond optical pulse via photon–electron coupling on nanostructures. PINEM has been applied in various fields of study, from materials science to biological imaging, exploiting the unique spatial, energy, and temporal characteristics of the PINEM electrons gained by interaction with a “single” light pulse. The further potential of photon-gated PINEM electrons in probing ultrafast dynamics of matter and the optical gating of electrons by invoking a “second” optical pulse has previously been proposed and examined theoretically in our group. Here, we experimentally demonstrate this photon-gating technique, and, through diffraction, visualize the phase transition dynamics in vanadium dioxide nanoparticles. With optical gating of PINEM electrons, imaging temporal resolution was improved by a factor of 3 or better, being limited only by the optical pulse widths. This work enables the combination of the high spatial resolution of electron microscopy and the ultrafast temporal response of the optical pulses, which provides a promising approach to attain the resolution of few femtoseconds and attoseconds in UEM. PMID:26438835

Algorithm for Stabilizing a POD-Based Dynamical System

NASA Technical Reports Server (NTRS)

Kalb, Virginia L.

2010-01-01

This algorithm provides a new way to improve the accuracy and asymptotic behavior of a low-dimensional system based on the proper orthogonal decomposition (POD). Given a data set representing the evolution of a system of partial differential equations (PDEs), such as the Navier-Stokes equations for incompressible flow, one may obtain a low-dimensional model in the form of ordinary differential equations (ODEs) that should model the dynamics of the flow. Temporal sampling of the direct numerical simulation of the PDEs produces a spatial time series. The POD extracts the temporal and spatial eigenfunctions of this data set. Truncated to retain only the most energetic modes followed by Galerkin projection of these modes onto the PDEs obtains a dynamical system of ordinary differential equations for the time-dependent behavior of the flow. In practice, the steps leading to this system of ODEs entail numerically computing first-order derivatives of the mean data field and the eigenfunctions, and the computation of many inner products. This is far from a perfect process, and often results in the lack of long-term stability of the system and incorrect asymptotic behavior of the model. This algorithm describes a new stabilization method that utilizes the temporal eigenfunctions to derive correction terms for the coefficients of the dynamical system to significantly reduce these errors.

Phase-Locked Responses to Speech in Human Auditory Cortex are Enhanced During Comprehension

PubMed Central

Peelle, Jonathan E.; Gross, Joachim; Davis, Matthew H.

2013-01-01

A growing body of evidence shows that ongoing oscillations in auditory cortex modulate their phase to match the rhythm of temporally regular acoustic stimuli, increasing sensitivity to relevant environmental cues and improving detection accuracy. In the current study, we test the hypothesis that nonsensory information provided by linguistic content enhances phase-locked responses to intelligible speech in the human brain. Sixteen adults listened to meaningful sentences while we recorded neural activity using magnetoencephalography. Stimuli were processed using a noise-vocoding technique to vary intelligibility while keeping the temporal acoustic envelope consistent. We show that the acoustic envelopes of sentences contain most power between 4 and 7 Hz and that it is in this frequency band that phase locking between neural activity and envelopes is strongest. Bilateral oscillatory neural activity phase-locked to unintelligible speech, but this cerebro-acoustic phase locking was enhanced when speech was intelligible. This enhanced phase locking was left lateralized and localized to left temporal cortex. Together, our results demonstrate that entrainment to connected speech does not only depend on acoustic characteristics, but is also affected by listeners’ ability to extract linguistic information. This suggests a biological framework for speech comprehension in which acoustic and linguistic cues reciprocally aid in stimulus prediction. PMID:22610394

Phase-locked responses to speech in human auditory cortex are enhanced during comprehension.

PubMed

Peelle, Jonathan E; Gross, Joachim; Davis, Matthew H

2013-06-01

A growing body of evidence shows that ongoing oscillations in auditory cortex modulate their phase to match the rhythm of temporally regular acoustic stimuli, increasing sensitivity to relevant environmental cues and improving detection accuracy. In the current study, we test the hypothesis that nonsensory information provided by linguistic content enhances phase-locked responses to intelligible speech in the human brain. Sixteen adults listened to meaningful sentences while we recorded neural activity using magnetoencephalography. Stimuli were processed using a noise-vocoding technique to vary intelligibility while keeping the temporal acoustic envelope consistent. We show that the acoustic envelopes of sentences contain most power between 4 and 7 Hz and that it is in this frequency band that phase locking between neural activity and envelopes is strongest. Bilateral oscillatory neural activity phase-locked to unintelligible speech, but this cerebro-acoustic phase locking was enhanced when speech was intelligible. This enhanced phase locking was left lateralized and localized to left temporal cortex. Together, our results demonstrate that entrainment to connected speech does not only depend on acoustic characteristics, but is also affected by listeners' ability to extract linguistic information. This suggests a biological framework for speech comprehension in which acoustic and linguistic cues reciprocally aid in stimulus prediction.

Quantifying the imprint of mesoscale and synoptic-scale atmospheric transport on total column carbon dioxide measurements

NASA Astrophysics Data System (ADS)

Torres, A. D.; Keppel-Aleks, G.; Doney, S. C.; Feng, S.; Lauvaux, T.; Fendrock, M. A.; Rheuben, J.

2017-12-01

Remote sensing instruments provide an unprecedented density of observations of the atmospheric CO2 column average mole fraction (denoted as XCO2), which can be used to constrain regional scale carbon fluxes. Inferring fluxes from XCO2 observations is challenging, as measurements and inversion methods are sensitive to not only the imprint local and large-scale fluxes, but also mesoscale and synoptic-scale atmospheric transport. Quantifying the fine-scale variability in XCO2 from mesoscale and synoptic-scale atmospheric transport will likely improve overall error estimates from flux inversions by improving estimates of representation errors that occur when XCO2 observations are compared to modeled XCO2 in relatively coarse transport models. Here, we utilize various statistical methods to quantify the imprint of atmospheric transport on XCO2 observations. We compare spatial variations along Orbiting Carbon Observatory (OCO-2) satellite tracks to temporal variations observed by the Total Column Carbon Observing Network (TCCON). We observe a coherent seasonal cycle of both within-day temporal and fine-scale spatial variability (of order 10 km) of XCO2 from these two datasets, suggestive of the imprint of mesoscale systems. To account for other potential sources of error in XCO2 retrieval, we compare observed temporal and spatial variations of XCO2 to high-resolution output from the Weather Research and Forecasting (WRF) model run at 9 km resolution. In both simulations and observations, the Northern hemisphere mid-latitude XCO2 showed peak variability during the growing season when atmospheric gradients are largest. These results are qualitatively consistent with our expectations of seasonal variations of the imprint of synoptic and mesoscale atmospheric transport on XCO2 observations; suggesting that these statistical methods could be sensitive to the imprint of atmospheric transport on XCO2 observations.

Differential effects of rhythmic auditory stimulation and neurodevelopmental treatment/Bobath on gait patterns in adults with cerebral palsy: a randomized controlled trial.

PubMed

Kim, Soo Ji; Kwak, Eunmi E; Park, Eun Sook; Cho, Sung-Rae

2012-10-01

To investigate the effects of rhythmic auditory stimulation (RAS) on gait patterns in comparison with changes after neurodevelopmental treatment (NDT/Bobath) in adults with cerebral palsy. A repeated-measures analysis between the pretreatment and posttreatment tests and a comparison study between groups. Human gait analysis laboratory. Twenty-eight cerebral palsy patients with bilateral spasticity participated in this study. The subjects were randomly allocated to either neurodevelopmental treatment (n = 13) or rhythmic auditory stimulation (n = 15). Gait training with rhythmic auditory stimulation or neurodevelopmental treatment was performed three sessions per week for three weeks. Temporal and kinematic data were analysed before and after the intervention. Rhythmic auditory stimulation was provided using a combination of a metronome beat set to the individual's cadence and rhythmic cueing from a live keyboard, while neurodevelopmental treatment was implemented following the traditional method. Temporal data, kinematic parameters and gait deviation index as a measure of overall gait pathology were assessed. Temporal gait measures revealed that rhythmic auditory stimulation significantly increased cadence, walking velocity, stride length, and step length (P < 0.05). Kinematic data demonstrated that anterior tilt of the pelvis and hip flexion during a gait cycle was significantly ameliorated after rhythmic auditory stimulation (P < 0.05). Gait deviation index also showed modest improvement in cerebral palsy patients treated with rhythmic auditory stimulation (P < 0.05). However, neurodevelopmental treatment showed that internal and external rotations of hip joints were significantly improved, whereas rhythmic auditory stimulation showed aggravated maximal internal rotation in the transverse plane (P < 0.05). Gait training with rhythmic auditory stimulation or neurodevelopmental treatment elicited differential effects on gait patterns in adults with cerebral palsy.

UAS Developments Supporting Wildfire Observations

NASA Astrophysics Data System (ADS)

Ambrosia, V. G.; Dahlgren, R. P.; Watts, A.; Reynolds, K. W.; Ball, T.

2014-12-01

Wildfires are regularly occurring emergency events that threaten life, property, and natural resources in every U.S. State and many countries around the world. Despite projections that $1.8 billion will be spent by U.S. Federal agencies alone on wildfires in 2014, the decades-long trend of increasing fire size, severity, and cost is expected to continue. Furthermore, the enormous potential for UAS (and concomitant sensor systems) to serve as geospatial intelligence tools to improve the safety and effectiveness of fire management, and our ability to forecast fire and smoke movements, remains barely tapped. Although orbital sensor assets are can provide the geospatial extent of wildfires, generally those resources are limited in use due to their spatial and temporal resolution limitations. These two critical elements make orbital assets of limited utility for tactical, real-time wildfire management, or for continuous scientific analysis of the temporal dynamics related to fire energy release rates and plume concentrations that vary significantly thru a fire's progression. Large UAS platforms and sensors can and have been used to monitor wildfire events at improved temporal, spatial and radiometric scales, but more focus is being placed on the use of small UAS (sUAS) and sensors to support wildfire observation strategies. The use of sUAS is therefore more critical for TACTICAL management purposes, rather than strategic observations, where small-scale fire developments are critical to understand. This paper will highlight the historical development and use of UAS for fire observations, as well as the current shift in focus to smaller, more affordable UAS for more rapid integration into operational use on wildfire events to support tactical observation strategies, and support wildfire science measurement inprovements.

Extreme storm surge modelling in the North Sea. The role of the sea state, forcing frequency and spatial forcing resolution

NASA Astrophysics Data System (ADS)

Ridder, Nina; de Vries, Hylke; Drijfhout, Sybren; van den Brink, Henk; van Meijgaard, Erik; de Vries, Hans

2018-02-01

This study shows that storm surge model performance in the North Sea is mostly unaffected by the application of temporal variations of surface drag due to changes in sea state provided the choice of a suitable constant Charnock parameter in the sea-state-independent case. Including essential meteorological features on smaller scales and minimising interpolation errors by increasing forcing data resolution are shown to be more important for the improvement of model performance particularly at the high tail of the probability distribution. This is found in a modelling study using WAQUA/DCSMv5 by evaluating the influence of a realistic air-sea momentum transfer parameterization and comparing it to the influence of changes in the spatial and temporal resolution of the applied forcing fields in an effort to support the improvement of impact and climate analysis studies. Particular attention is given to the representation of extreme water levels over the past decades based on the example of the Netherlands. For this, WAQUA/DCSMv5 is forced with ERA-Interim reanalysis data. Model results are obtained from a set of different forcing fields, which either (i) include a wave-state-dependent Charnock parameter or (ii) apply a constant Charnock parameter ( α C h = 0.032) tuned for young sea states in the North Sea, but differ in their spatial and/or temporal resolution. Increasing forcing field resolution from roughly 79 to 12 km through dynamically downscaling can reduce the modelled low bias, depending on coastal station, by up to 0.25 m for the modelled extreme water levels with a 1-year return period and between 0.1 m and 0.5 m for extreme surge heights.

Stochastic Generation of Spatiotemporal Rainfall Events for Flood Risk Assessment

NASA Astrophysics Data System (ADS)

Diederen, D.; Liu, Y.; Gouldby, B.; Diermanse, F.

2017-12-01

Current flood risk analyses that only consider peaks of hydrometeorological forcing variables have limitations regarding their representation of reality. Simplistic assumptions regarding antecedent conditions are required, often different sources of flooding are considered in isolation, and the complex temporal and spatial evolution of the events is not considered. Mid-latitude storms, governed by large scale climatic conditions, often exhibit a high degree of temporal dependency, for example. For sustainable flood risk management, that accounts appropriately for climate change, it is desirable for flood risk analyses to reflect reality more appropriately. Analysis of risk mitigation measures and comparison of their relative performance is therefore likely to be more robust and lead to improved solutions. We provide a new framework for the provision of boundary conditions to flood risk analyses that more appropriately reflects reality. The boundary conditions capture the temporal dependencies of complex storms whilst preserving the extreme values and associated spatial dependencies. We demonstrate the application of this framework to generate a synthetic rainfall events time series boundary condition set from reanalysis rainfall data (CFSR) on the continental scale. We define spatiotemporal clusters of rainfall as events, extract hydrological parameters for each event, generate synthetic parameter sets with a multivariate distribution with a focus on the joint tail probability [Heffernan and Tawn, 2004], and finally create synthetic events from the generated synthetic parameters. We highlight the stochastic integration of (a) spatiotemporal features, e.g. event occurrence intensity over space-time, or time to previous event, which we use for the spatial placement and sequencing of the synthetic events, and (b) value-specific parameters, e.g. peak intensity and event extent. We contrast this to more traditional approaches to highlight the significant improvements in terms of representing the reality of extreme flood events.

Modeling spatial-temporal dynamics of global wetlands: comprehensive evaluation of a new sub-grid TOPMODEL parameterization and uncertainties

NASA Astrophysics Data System (ADS)

Zhang, Z.; Zimmermann, N. E.; Poulter, B.

2015-11-01

Simulations of the spatial-temporal dynamics of wetlands are key to understanding the role of wetland biogeochemistry under past and future climate variability. Hydrologic inundation models, such as TOPMODEL, are based on a fundamental parameter known as the compound topographic index (CTI) and provide a computationally cost-efficient approach to simulate wetland dynamics at global scales. However, there remains large discrepancy in the implementations of TOPMODEL in land-surface models (LSMs) and thus their performance against observations. This study describes new improvements to TOPMODEL implementation and estimates of global wetland dynamics using the LPJ-wsl dynamic global vegetation model (DGVM), and quantifies uncertainties by comparing three digital elevation model products (HYDRO1k, GMTED, and HydroSHEDS) at different spatial resolution and accuracy on simulated inundation dynamics. In addition, we found that calibrating TOPMODEL with a benchmark wetland dataset can help to successfully delineate the seasonal and interannual variations of wetlands, as well as improve the spatial distribution of wetlands to be consistent with inventories. The HydroSHEDS DEM, using a river-basin scheme for aggregating the CTI, shows best accuracy for capturing the spatio-temporal dynamics of wetlands among the three DEM products. The estimate of global wetland potential/maximum is ∼ 10.3 Mkm2 (106 km2), with a mean annual maximum of ∼ 5.17 Mkm2 for 1980-2010. This study demonstrates the feasibility to capture spatial heterogeneity of inundation and to estimate seasonal and interannual variations in wetland by coupling a hydrological module in LSMs with appropriate benchmark datasets. It additionally highlights the importance of an adequate investigation of topographic indices for simulating global wetlands and shows the opportunity to converge wetland estimates across LSMs by identifying the uncertainty associated with existing wetland products.

The monaural temporal window based on masking period pattern data in school-aged children and adults.

PubMed

Buss, Emily; He, Shuman; Grose, John H; Hall, Joseph W

2013-03-01

Several lines of evidence indicate that auditory temporal resolution improves over childhood, whereas other data implicate the development of processing efficiency. The present study used the masking period pattern paradigm to examine the maturation of temporal processing in normal-hearing children (4.8 to 10.7 yrs) compared to adults. Thresholds for a brief tone were measured at 6 temporal positions relative to the period of a 5-Hz quasi-square-wave masker envelope, with a 20-dB modulation depth, as well as in 2 steady maskers. The signal was a pure tone at either 1000 or 6500 Hz, and the masker was a band of noise, either spectrally wide or narrow (21.3 and 1.4 equivalent rectangular bandwidths, respectively). Masker modulation improved thresholds more for wide than narrow bandwidths, and adults tended to receive more benefit from modulation than young children. Fits to data for the wide maskers indicated a change in window symmetry with development, reflecting relatively greater backward masking for the youngest listeners. Data for children >6.5 yrs of age appeared more adult-like for the 6500- than the 1000-Hz signal. Differences in temporal window asymmetry with listener age cannot be entirely explained as a consequence of a higher criterion for detection in children, a form of inefficiency.

Peripheral resolution and contrast sensitivity: Effects of stimulus drift.

PubMed

Venkataraman, Abinaya Priya; Lewis, Peter; Unsbo, Peter; Lundström, Linda

2017-04-01

Optimal temporal modulation of the stimulus can improve foveal contrast sensitivity. This study evaluates the characteristics of the peripheral spatiotemporal contrast sensitivity function in normal-sighted subjects. The purpose is to identify a temporal modulation that can potentially improve the remaining peripheral visual function in subjects with central visual field loss. High contrast resolution cut-off for grating stimuli with four temporal frequencies (0, 5, 10 and 15Hz drift) was first evaluated in the 10° nasal visual field. Resolution contrast sensitivity for all temporal frequencies was then measured at four spatial frequencies between 0.5 cycles per degree (cpd) and the measured stationary cut-off. All measurements were performed with eccentric optical correction. Similar to foveal vision, peripheral contrast sensitivity is highest for a combination of low spatial frequency and 5-10Hz drift. At higher spatial frequencies, there was a decrease in contrast sensitivity with 15Hz drift. Despite this decrease, the resolution cut-off did not vary largely between the different temporal frequencies tested. Additional measurements of contrast sensitivity at 0.5 cpd and resolution cut-off for stationary (0Hz) and 7.5Hz stimuli performed at 10, 15, 20 and 25° in the nasal visual field also showed the same characteristics across eccentricities. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

The Feasibility of Conformal Thermal Therapy with Transurethral Ultrasound Heating Applicators and MR Temperature Feedback

NASA Astrophysics Data System (ADS)

Choy, Vanessa; Tang, Kee; Wachsmuth, Jeff; Chopra, Rajiv; Bronskill, Michael

2006-05-01

Transurethral thermal therapy offers a minimally invasive alternative for the treatment of prostate diseases including benign prostate hyperplasia (BPH) and prostate cancer. Accurate heating of a targeted region of the gland can be achieved through the use of a rotating directional heating source incorporating planar ultrasound transducers, and the implementation of active temperature feedback along the beam direction during heating provided by magnetic resonance (MR) thermometry. The performance of this control method with practical spatial, temporal, and temperature resolution (such as angular alignment, spatial resolution, update rate for temperature feedback (imaging time), and the presence of noise) for thermal feedback using a clinical 1.5 T MR scanner was investigated in simulations. As expected, the control algorithm was most sensitive to the presence of noise, with noticeable degradation in its performance above ±2°C of temperature uncertainty. With respect to temporal resolution, acceptable performance was achieved at update rates of 5s or faster. The control algorithm was relatively insensitive to reduced spatial resolution due to the broad nature of the heating pattern produced by the heating applicator, this provides an opportunity to improve signal-to-noise ratio (SNR). The overall simulation results confirm that existing clinical 1.5T MR imagers are capable of providing adequate temperature feedback for transurethral thermal therapy without special pulse sequences or enhanced imaging hardware.

Novel 16-channel receive coil array for accelerated upper airway MRI at 3 Tesla.

PubMed

Kim, Yoon-Chul; Hayes, Cecil E; Narayanan, Shrikanth S; Nayak, Krishna S

2011-06-01

Upper airway MRI can provide a noninvasive assessment of speech and swallowing disorders and sleep apnea. Recent work has demonstrated the value of high-resolution three-dimensional imaging and dynamic two-dimensional imaging and the importance of further improvements in spatio-temporal resolution. The purpose of the study was to describe a novel 16-channel 3 Tesla receive coil that is highly sensitive to the human upper airway and investigate the performance of accelerated upper airway MRI with the coil. In three-dimensional imaging of the upper airway during static posture, 6-fold acceleration is demonstrated using parallel imaging, potentially leading to capturing a whole three-dimensional vocal tract with 1.25 mm isotropic resolution within 9 sec of sustained sound production. Midsagittal spiral parallel imaging of vocal tract dynamics during natural speech production is demonstrated with 2 × 2 mm(2) in-plane spatial and 84 ms temporal resolution. Copyright © 2010 Wiley-Liss, Inc.

Using stable isotopes to assess surface water source dynamics and hydrological connectivity in a high-latitude wetland and permafrost influenced landscape

NASA Astrophysics Data System (ADS)

Ala-aho, P.; Soulsby, C.; Pokrovsky, O. S.; Kirpotin, S. N.; Karlsson, J.; Serikova, S.; Vorobyev, S. N.; Manasypov, R. M.; Loiko, S.; Tetzlaff, D.

2018-01-01

Climate change is expected to alter hydrological and biogeochemical processes in high-latitude inland waters. A critical question for understanding contemporary and future responses to environmental change is how the spatio-temporal dynamics of runoff generation processes will be affected. We sampled stable water isotopes in soils, lakes and rivers on an unprecedented spatio-temporal scale along a 1700 km transect over three years in the Western Siberia Lowlands. Our findings suggest that snowmelt mixes with, and displaces, large volumes of water stored in the organic soils and lakes to generate runoff during the thaw season. Furthermore, we saw a persistent hydrological connection between water bodies and the landscape across permafrost regions. Our findings help to bridge the understanding between small and large scale hydrological studies in high-latitude systems. These isotope data provide a means to conceptualise hydrological connectivity in permafrost and wetland influenced regions, which is needed for an improved understanding of future biogeochemical changes.

Dynamic MRI of Grid-Tagged Hyperpolarized Helium-3 for the Assessment of Lung Motion During Breathing

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

Cai Jing; Sheng Ke; Benedict, Stanley H.

2009-09-01

Purpose: To develop a dynamic magnetic resonance imaging (MRI) tagging technique using hyperpolarized helium-3 (HP He-3) to track lung motion. Methods and Materials: An accelerated non-Cartesian k-space trajectory was used to gain acquisition speed, at the cost of introducing image artifacts, providing a viable strategy for obtaining whole-lung coverage with adequate temporal resolution. Multiple-slice two-dimensional dynamic images of the lung were obtained in three healthy subjects after inhaling He-3 gas polarized to 35%-40%. Displacement, strain, and ventilation maps were computed from the observed motion of the grid peaks. Results: Both temporal and spatial variations of pulmonary mechanics were observed inmore » normal subjects, including shear motion between different lobes of the same lung. Conclusion: These initial results suggest that dynamic imaging of grid-tagged hyperpolarized magnetization may potentially be a powerful tool for observing and quantifying pulmonary biomechanics on a regional basis and for assessing, validating, and improving lung deformable image registration algorithms.« less

Dynamic chirp control of all-optical format-converted pulsed data from a multi-wavelength inverse-optical-comb injected semiconductor optical amplifier.

PubMed

Lin, Gong-Ru; Pan, Ci-Ling; Yu, Kun-Chieh

2007-10-01

By spectrally and temporally reshaping the gain-window of a traveling-wave semiconductor optical amplifier (TWSOA) with a backward injected multi- or single-wavelength inverse-optical-comb, we theoretically and experimentally investigate the dynamic frequency chirp of the all-optical 10GBit/s Return-to-Zero (RZ) data-stream format-converted from the TWSOA under strong cross-gain depletion scheme. The multi-wavelength inverse-optical-comb injection effectively depletes the TWSOA gain spectrally and temporally, remaining a narrow gain-window and a reduced spectral linewidth and provide a converted RZ data with a smaller peak-to-peak frequency chirp of 6.7 GHz. Even at high inverse-optical-comb injection power and highly biased current condition for improving the operational bit-rate, the chirp of the multi-wavelength-injection converted RZ pulse is still 2.1-GHz smaller than that obtained by using single-wavelength injection at a cost of slight pulse-width broadening by 1 ps.

Decoding Hemodynamics of Large Vessels via Dispersion of Contrast Agent in Cardiac Computed Tomography

NASA Astrophysics Data System (ADS)

Eslami, Parastou; Seo, Jung-Hee; Abd, Thura T.; George, Richard; Lardo, Albert C.; Chen, Marcus Y.; Mittal, Rajat

2015-11-01

Computed tomography angiography (CTA) has emerged as a powerful tool for the assessment of coronary artery disease and other cardiac conditions. Continuous improvements in the spatial and temporal resolution of CT scanners are revealing details regarding the spatially and temporally varying contrast concentration in the vasculature, that were not evident before. These contrast dispersion patterns offer the possibility of extracting useful information about the hemodynamics from the scans. In the current presentation, we will describe experimental studies carried out with CT compatible phantoms of coronary vessels that provide insights into the effect of imaging artifacts on the observed intracoronary contrast gradients. In addition, we will describe a series of computational fluid dynamics studies that explore the dispersion of contrast through the ascending-descending aorta with particular focus on the effect of the aortic curvature on the dispersion patterns. PE is supported by the NIH Graduate Partnership Program. RM and ACL pending patents in CTA based flow diagnostics and have other significant financial interests in these technologies.

Bayesian hierarchical model of ceftriaxone resistance proportions among Salmonella serotype Heidelberg infections.

PubMed

Gu, Weidong; Medalla, Felicita; Hoekstra, Robert M

2018-02-01

The National Antimicrobial Resistance Monitoring System (NARMS) at the Centers for Disease Control and Prevention tracks resistance among Salmonella infections. The annual number of Salmonella isolates of a particular serotype from states may be small, making direct estimation of resistance proportions unreliable. We developed a Bayesian hierarchical model to improve estimation by borrowing strength from relevant sampling units. We illustrate the models with different specifications of spatio-temporal interaction using 2004-2013 NARMS data for ceftriaxone-resistant Salmonella serotype Heidelberg. Our results show that Bayesian estimates of resistance proportions were smoother than observed values, and the difference between predicted and observed proportions was inversely related to the number of submitted isolates. The model with interaction allowed for tracking of annual changes in resistance proportions at the state level. We demonstrated that Bayesian hierarchical models provide a useful tool to examine spatio-temporal patterns of small sample size such as those found in NARMS. Published by Elsevier Ltd.

Analysis of Temporal-spatial Co-variation within Gene Expression Microarray Data in an Organogenesis Model

NASA Astrophysics Data System (ADS)

Ehler, Martin; Rajapakse, Vinodh; Zeeberg, Barry; Brooks, Brian; Brown, Jacob; Czaja, Wojciech; Bonner, Robert F.

The gene networks underlying closure of the optic fissure during vertebrate eye development are poorly understood. We used a novel clustering method based on Laplacian Eigenmaps, a nonlinear dimension reduction method, to analyze microarray data from laser capture microdissected (LCM) cells at the site and developmental stages (days 10.5 to 12.5) of optic fissure closure. Our new method provided greater biological specificity than classical clustering algorithms in terms of identifying more biological processes and functions related to eye development as defined by Gene Ontology at lower false discovery rates. This new methodology builds on the advantages of LCM to isolate pure phenotypic populations within complex tissues and allows improved ability to identify critical gene products expressed at lower copy number. The combination of LCM of embryonic organs, gene expression microarrays, and extracting spatial and temporal co-variations appear to be a powerful approach to understanding the gene regulatory networks that specify mammalian organogenesis.

Groundwater–surface water mixing shifts ecological assembly processes and stimulates organic carbon turnover

DOE PAGES

Stegen, James C.; Fredrickson, James K.; Wilkins, Michael J.; ...

2016-04-07

Environmental transition zones are associated with geochemical gradients that overcome energy limitations to microbial metabolism, resulting in biogeochemical hot spots and moments. Riverine systems where groundwater mixes with surface water (the hyporheic zone) are spatially complex and temporally dynamic, making development of predictive models challenging. Spatial and temporal variations in hyporheic zone microbial communities are a key, but understudied, component of riverine biogeochemical function. To investigate the coupling among groundwater-surface water mixing, microbial communities, and biogeochemistry we applied ecological theory, aqueous biogeochemistry, DNA sequencing, and ultra-high resolution organic carbon profiling to field samples collected across times and locations representing amore » broad range of mixing conditions. Mixing of groundwater and surface water resulted in a shift from transport-driven stochastic dynamics to a deterministic microbial structure associated with elevated biogeochemical rates. While the dynamics of the hyporheic make predictive modeling a challenge, we provide new knowledge that can improve the tractability of such models.« less

Ambiguous Figures – What Happens in the Brain When Perception Changes But Not the Stimulus

PubMed Central

Kornmeier, Jürgen; Bach, Michael

2011-01-01

During observation of ambiguous figures our perception reverses spontaneously although the visual information stays unchanged. Research on this phenomenon so far suffered from the difficulty to determine the instant of the endogenous reversals with sufficient temporal precision. A novel experimental paradigm with discontinuous stimulus presentation improved on previous temporal estimates of the reversal event by a factor of three. It revealed that disambiguation of ambiguous visual information takes roughly 50 ms or two loops of recurrent neural activity. Further, the decision about the perceptual outcome has taken place at least 340 ms before the observer is able to indicate the consciously perceived reversal manually. We provide a short review about physiological studies on multistable perception with a focus on electrophysiological data. We further present a new perspective on multistable perception that can easily integrate previous apparently contradicting explanatory approaches. Finally we propose possible extensions toward other research fields where ambiguous figure perception may be useful as an investigative tool. PMID:22461773

On the Feasibility of Studying Shortwave Aerosol Radiative Forcing of Climate Using Dual-Wavelength Aerosol Backscatter Lidar

NASA Technical Reports Server (NTRS)

Redemann, Jens; Russell, Philip B.; Winker, David M.; McCormick, M. Patrick; Hipskind, R. Stephen (Technical Monitor)

2000-01-01

The current low confidence in the estimates of aerosol-induced perturbations of Earth's radiation balance is caused by the highly non-uniform compositional, spatial and temporal distributions of tropospheric aerosols on a global scale owing to their heterogeneous sources and short lifetimes. Nevertheless, recent studies have shown that the inclusion of aerosol effects in climate model calculations can improve agreement with observed spatial and temporal temperature distributions. In light of the short lifetimes of aerosols, determination of their global distribution with space-borne sensors seems to be a necessary approach. Until recently, satellite measurements of tropospheric aerosols have been approximate and did not provide the full set of information required to determine their radiative effects. With the advent of active aerosol remote sensing from space (e.g., PICASSO-CENA), the applicability fo lidar-derived aerosol 180 deg -backscatter data to radiative flux calculations and hence studies of aerosol effects on climate needs to be investigated.