Threat-evoked anxiety disrupts spatial working memory performance:an attentional account

It is proposed that threat-evoked anxiety and spatial Working Memory (WM) rely on a common visuospatial attention mechanism. A prediction of this hypothesis is that spatial but not verbal WM should be disrupted in conditions of threat anxiety. Participants performed verbal and spatial n-back WM tasks in the presence or absence of threat of shock (shocks were not delivered). The presence of anxiety was assessed via heart rate recordings and self-report. Both measures clearly distinguished between WM blocks associated with threat of shock (Threat) and blocks, in which threat was absent (Safety). Performance on the spatial WM task was impaired in Threat relative to Safety. Furthermore, the more anxiety participants reported and the higher their heart rate in Threat compared to Safety, the more impaired was their spatial WM performance. This effect was not observed for verbal WM. The results indicate selective disruption of spatial WM performance by threat-evoked anxiety, interpreted in terms of more overlap in visuospatial attention between anxiety and spatial WM vs. anxiety and verbal WM.

Best Constant in the Weighted Hardy Inequality: The Spatial and Spherical Version

Mathematics Subject Classification: 26D10.

A comparison of two distributed large-volume measurement systems:the mobile spatial co-ordinate measuring system and the indoor global positioning system

Advances in the area of industrial metrology have generated new technologies that are capable of measuring components with complex geometry and large dimensions. However, no standard or best-practice guides are available for the majority of such systems. Therefore, these new systems require appropriate testing and verification in order for the users to understand their full potential prior to their deployment in a real manufacturing environment. This is a crucial stage, especially when more than one system can be used for a specific measurement task. In this paper, two relatively new large-volume measurement systems, the mobile spatial co-ordinate measuring system (MScMS) and the indoor global positioning system (iGPS), are reviewed. These two systems utilize different technologies: the MScMS is based on ultrasound and radiofrequency signal transmission and the iGPS uses laser technology. Both systems have components with small dimensions that are distributed around the measuring area to form a network of sensors allowing rapid dimensional measurements to be performed in relation to large-size objects, with typical dimensions of several decametres. The portability, reconfigurability, and ease of installation make these systems attractive for many industries that manufacture large-scale products. In this paper, the major technical aspects of the two systems are briefly described and compared. Initial results of the tests performed to establish the repeatability and reproducibility of these systems are also presented. © IMechE 2009.

The spatial patterns of β-amyloid (Aβ) deposits and neurofibrillary tangles (NFT) in late-onset sporadic Alzheimer's disease

The spatial patterns of β-amyloid (Aβ) deposits and neurofibrillary tangles (NFT) were studied in areas of the cerebral cortex in 16 patients with the late-onset, sporadic form of Alzheimer's disease (AD). Diffuse, primitive, and classic Aβ deposits and NFT were aggregated into clusters; the clusters being regularly distributed parallel to the pia mater in many areas. In a significant proportion of regions, the sizes of the regularly distributed clusters approximated to those of the cells of origin of the cortico-cortical projections. The diffuse and primitive Aβ deposits exhibited a similar range of spatial patterns but the classic Aβ deposits occurred less frequently in large clusters >6400m. In addition, the NFT often occurred in larger regularly distributed clusters than the Aβ deposits. The location, size, and distribution of the clusters of Aβ deposits and NFT supports the hypothesis that AD is a 'disconnection syndrome' in which degeneration of specific cortico-cortical and cortico-hippocampal pathways results in synaptic disconnection and the formation of clusters of NFT and Aβ deposits. © 2011 Nova Science Publishers, Inc.

Data structures for highly efficient querying of spatial data

The virtual quadrilateral is the coalescence of novel data structures that reduces the storage requirements of spatial data without jeopardizing the quality and operability of the inherent information. The data representative of the observed area is parsed to ascertain the necessary contiguous measures that, when contained, implicitly define a quadrilateral. The virtual quadrilateral then represents a geolocated area of the observed space where all of the measures are the same. The area, contoured as a rectangle, is pseudo-delimited by the opposite coordinates of the bounding area. Once defined, the virtual quadrilateral is representative of an area in the observed space and is represented in a database by the attributes of its bounding coordinates and measure of its contiguous space. Virtual quadrilaterals have been found to ensure a lossless reduction of the physical storage, maintain the implied features of the data, facilitate the rapid retrieval of vast amount of the represented spatial data and accommodate complex queries. The methods presented herein demonstrate that virtual quadrilaterals are created quite easily, are stable and versatile objects in a database and have proven to be beneficial to exigent spatial data applications such as geographic information systems. ^

Data partitioning and replication management in distributed geographic information system (GIS) database

This research presents several components encompassing the scope of the objective of Data Partitioning and Replication Management in Distributed GIS Database. Modern Geographic Information Systems (GIS) databases are often large and complicated. Therefore data partitioning and replication management problems need to be addresses in development of an efficient and scalable solution. ^ Part of the research is to study the patterns of geographical raster data processing and to propose the algorithms to improve availability of such data. These algorithms and approaches are targeting granularity of geographic data objects as well as data partitioning in geographic databases to achieve high data availability and Quality of Service(QoS) considering distributed data delivery and processing. To achieve this goal a dynamic, real-time approach for mosaicking digital images of different temporal and spatial characteristics into tiles is proposed. This dynamic approach reuses digital images upon demand and generates mosaicked tiles only for the required region according to user's requirements such as resolution, temporal range, and target bands to reduce redundancy in storage and to utilize available computing and storage resources more efficiently. ^ Another part of the research pursued methods for efficient acquiring of GIS data from external heterogeneous databases and Web services as well as end-user GIS data delivery enhancements, automation and 3D virtual reality presentation. ^ There are vast numbers of computing, network, and storage resources idling or not fully utilized available on the Internet. Proposed "Crawling Distributed Operating System "(CDOS) approach employs such resources and creates benefits for the hosts that lend their CPU, network, and storage resources to be used in GIS database context. ^ The results of this dissertation demonstrate effective ways to develop a highly scalable GIS database. The approach developed in this dissertation has resulted in creation of TerraFly GIS database that is used by US government, researchers, and general public to facilitate Web access to remotely-sensed imagery and GIS vector information. ^

Spatial-temporal mining of archived automatic vehicle location (AVL) data for transit service planning applications

An Automatic Vehicle Location (AVL) system is a computer-based vehicle tracking system that is capable of determining a vehicle's location in real time. As a major technology of the Advanced Public Transportation System (APTS), AVL systems have been widely deployed by transit agencies for purposes such as real-time operation monitoring, computer-aided dispatching, and arrival time prediction. AVL systems make a large amount of transit performance data available that are valuable for transit performance management and planning purposes. However, the difficulties of extracting useful information from the huge spatial-temporal database have hindered off-line applications of the AVL data. ^ In this study, a data mining process, including data integration, cluster analysis, and multiple regression, is proposed. The AVL-generated data are first integrated into a Geographic Information System (GIS) platform. The model-based cluster method is employed to investigate the spatial and temporal patterns of transit travel speeds, which may be easily translated into travel time. The transit speed variations along the route segments are identified. Transit service periods such as morning peak, mid-day, afternoon peak, and evening periods are determined based on analyses of transit travel speed variations for different times of day. The seasonal patterns of transit performance are investigated by using the analysis of variance (ANOVA). Travel speed models based on the clustered time-of-day intervals are developed using important factors identified as having significant effects on speed for different time-of-day periods. ^ It has been found that transit performance varied from different seasons and different time-of-day periods. The geographic location of a transit route segment also plays a role in the variation of the transit performance. The results of this research indicate that advanced data mining techniques have good potential in providing automated techniques of assisting transit agencies in service planning, scheduling, and operations control. ^

Spatial scale and abundance patterns of large fish communities in freshwater marshes of the Florida Everglades

Anthropogenic habitat alterations and water-management practices have imposed an artificial spatial scale onto the once contiguous freshwater marshes of the Florida Everglades. To gain insight into how these changes may affect biotic communities, we examined whether variation in the abundance and community structure of large fishes (SL . 8 cm) in Everglades marshes varied more at regional or intraregional scales, and whether this variation was related to hydroperiod, water depth, floating mat volume, and vegetation density. From October 1997 to October 2002, we used an airboat electrofisher to sample large fishes at sites within three regions of the Everglades. Each of these regions is subject to unique watermanagement schedules. Dry-down events (water depth , 10 cm) occurred at several sites during spring in 1999, 2000, 2001, and 2002. The 2001 dry-down event was the most severe and widespread. Abundance of several fishes decreased significantly through time, and the number of days post-dry-down covaried significantly with abundance for several species. Processes operating at the regional scale appear to play important roles in regulating large fishes. The most pronounced patterns in abundance and community structure occurred at the regional scale, and the effect size for region was greater than the effect size for sites nested within region for abundance of all species combined, all predators combined, and each of the seven most abundant species. Non-metric multi-dimensional scaling revealed distinct groupings of sites corresponding to the three regions. We also found significant variation in community structure through time that correlated with the number of days post-dry-down. Our results suggest that hydroperiod and water management at the regional scale influence large fish communities of Everglades marshes.

Spatial and temporal patterns of aboveground net primary productivity (ANPP) along two freshwater-estuarine transects in the Florida Coastal Everglades

We present here a 4-year dataset (2001–2004) on the spatial and temporal patterns of aboveground net primary production (ANPP) by dominant primary producers (sawgrass, periphyton, mangroves, and seagrasses) along two transects in the oligotrophic Florida Everglades coastal landscape. The 17 sites of the Florida Coastal Everglades Long Term Ecological Research (FCE LTER) program are located along fresh-estuarine gradients in Shark River Slough (SRS) and Taylor River/C-111/Florida Bay (TS/Ph) basins that drain the western and southern Everglades, respectively. Within the SRS basin, sawgrass and periphyton ANPP did not differ significantly among sites but mangrove ANPP was highest at the site nearest the Gulf of Mexico. In the southern Everglades transect, there was a productivity peak in sawgrass and periphyton at the upper estuarine ecotone within Taylor River but no trends were observed in the C-111 Basin for either primary producer. Over the 4 years, average sawgrass ANPP in both basins ranged from 255 to 606 g m−2 year−1. Average periphyton productivity at SRS and TS/Ph was 17–68 g C m−2 year−1 and 342–10371 g C m−2 year−1, respectively. Mangrove productivity ranged from 340 g m−2 year−1 at Taylor River to 2208 g m−2 year−1 at the lower estuarine Shark River site. Average Thalassia testudinum productivity ranged from 91 to 396 g m−2 year−1 and was 4-fold greater at the site nearest the Gulf of Mexico than in eastern Florida Bay. There were no differences in periphyton productivity at Florida Bay. Interannual comparisons revealed no significant differences within each primary producer at either SRS or TS/Ph with the exception of sawgrass at SRS and the C−111 Basin. Future research will address difficulties in assessing and comparing ANPP of different primary producers along gradients as well as the significance of belowground production to the total productivity of this ecosystem.

Temporal and Spatial Variability of Mesozooplankton in a Shallow Sub-Tropical Bay: Influence of Top-Down Control

Quantifying the relationship between mesozooplankton and water quality parameters identifies the factors that structure the mesozooplankton community and can be used to generate hypotheses regarding the mechanisms that control the mesozooplankton population and potentially the trophic network. To investigate this relationship, mesozooplankton and water quality data were collected in Florida Bay from 1994 to 2004. Three key characteristics were found in the mesozooplankton community structure: (1) there are significant differences between the four sub-regions of Florida Bay; (2) there is a break in May of 1997 with significant differences before and after this date; and (3) there is a positive correlation between mesozooplankton abundance and salinity. The latter two characteristics are closely correlated with predator abundance, indicating the importance of top-down control. Hypersaline periods appear to provide a refuge from predators, allowing mesozooplankton to increase in abundance despite the increased physiological stress.

Application of excitation emission matrix fluorescence monitoring in the assessment of spatial and seasonal drivers of dissolved organic matter composition: Sources and physical disturbance controls

The environmental dynamics of dissolved organic matter (DOM) were characterized for a shallow, subtropical, seagrass-dominated estuarine bay, namely Florida Bay, USA. Large spatial and seasonal variations in DOM quantity and quality were assessed using dissolved organic C (DOC) measurements and spectrophotometric properties including excitation emission matrix (EEM) fluorescence with parallel factor analysis (PARAFAC). Surface water samples were collected monthly for 2 years across the bay. DOM characteristics were statistically different across the bay, and the bay was spatially characterized into four basins based on chemical characteristics of DOM as determined by EEM-PARAFAC. Differences between zones were explained based on hydrology, geomorphology, and primary productivity of the local seagrass community. In addition, potential disturbance effects from a very active hurricane season were identified. Although the overall seasonal patterns of DOM variations were not significantly affected on a bay-wide scale by this disturbance, enhanced freshwater delivery and associated P and DOM inputs (both quantity and quality) were suggested as potential drivers for the appearance of algal blooms in high impact areas. The application of EEM-PARAFAC proved to be ideally suited for studies requiring high sample throughput methods to assess spatial and temporal ecological drivers and to determine disturbance-induced impacts in aquatic ecosystems.

Regional processes in mangrove ecosystems: spatial scaling relationships, biomass, and turnover rates following catastrophic disturbance

Physiological processes and local-scale structural dynamics of mangroves are relatively well studied. Regional-scale processes, however, are not as well understood. Here we provide long-term data on trends in structure and forest turnover at a large scale, following hurricane damage in mangrove ecosystems of South Florida, U.S.A. Twelve mangrove vegetation plots were monitored at periodic intervals, between October 1992 and March 2005. Mangrove forests of this region are defined by a −1.5 scaling relationship between mean stem diameter and stem density, mirroring self-thinning theory for mono-specific stands. This relationship is reflected in tree size frequency scaling exponents which, through time, have exhibited trends toward a community average that is indicative of full spatial resource utilization. These trends, together with an asymptotic standing biomass accumulation, indicate that coastal mangrove ecosystems do adhere to size-structured organizing principles as described for upland tree communities. Regenerative dynamics are different between areas inside and outside of the primary wind-path of Hurricane Andrew which occurred in 1992. Forest dynamic turnover rates, however, are steady through time. This suggests that ecological, more-so than structural factors, control forest productivity. In agreement, the relative mean rate of biomass growth exhibits an inverse relationship with the seasonal range of porewater salinities. The ecosystem average in forest scaling relationships may provide a useful investigative tool of mangrove community biomass relationships, as well as offer a robust indicator of general ecosystem health for use in mangrove forest ecosystem management and restoration.

Semantic geographic information system

This thesis research describes the design and implementation of a Semantic Geographic Information System (GIS) and the creation of its spatial database. The database schema is designed and created, and all textual and spatial data are loaded into the database with the help of the Semantic DBMS's Binary Database Interface currently being developed at the FIU's High Performance Database Research Center (HPDRC). A friendly graphical user interface is created together with the other main system's areas: displaying process, data animation, and data retrieval. All these components are tightly integrated to form a novel and practical semantic GIS that has facilitated the interpretation, manipulation, analysis, and display of spatial data like: Ocean Temperature, Ozone(TOMS), and simulated SeaWiFS data. At the same time, this system has played a major role in the testing process of the HPDRC's high performance and efficient parallel Semantic DBMS.