Everglades R-EMAP 2005

The Everglades R-EMAP project for year 2005 produced large quantities of data collected at 232 sampling sites. Data collection and analysis is an on-going long-term activity conducted by scientists of different disciplines at irregular intervals of several years. The data sets collected for 2005 include bio-geo-chemical (including mercury and hydro period), fish, invertebrate, periphyton, and plant data. Each sampling site is associated with a location, a description of the site to provide a general overview and photographs to provide a pictorial impression. The Geographic Information Systems and Remote Sensing Center(GISRSC) at Florida International University (FIU) has designed and implemented an enterprise database for long-term storage of the project�s data in a central repository, providing the framework of data storage for the continuity of future sampling campaigns and allowing integration of new sample data as it becomes available. In addition GISRSC provides this interactive web application for easy, quick and effective retrieval and visualization of that data.

Direct visualization of magnetic-field-induced magnetoelectric switching in multiferroic Aurivillius phase thin films

Multiferroic materials displaying coupled ferroelectric and ferromagnetic order parameters could provide a means for data storage whereby bits could be written electrically and read magnetically, or vice versa. Thin films of Aurivillius phase Bi6Ti2.8Fe1.52Mn0.68O18, previously prepared by a chemical solution deposition (CSD) technique, are multiferroics demonstrating magnetoelectric coupling at room temperature. Here, we demonstrate the growth of a similar composition, Bi6Ti2.99Fe1.46Mn0.55O18, via the liquid injection chemical vapor deposition technique. High-resolution magnetic measurements reveal a considerably higher in-plane ferromagnetic signature than CSD grown films (MS = 24.25 emu/g (215 emu/cm3), MR = 9.916 emu/g (81.5 emu/cm3), HC = 170 Oe). A statistical analysis of the results from a thorough microstructural examination of the samples, allows us to conclude that the ferromagnetic signature can be attributed to the Aurivillius phase, with a confidence level of 99.95%. In addition, we report the direct piezoresponse force microscopy visualization of ferroelectric switching while going through a full in-plane magnetic field cycle, where increased volumes (8.6 to 14% compared with 4 to 7% for the CSD-grown films) of the film engage in magnetoelectric coupling and demonstrate both irreversible and reversible magnetoelectric domain switching.

Data collection, storage and retrieval with an underwater sensor network

In this paper we present a novel platform for underwater sensor networks to be used for long-term monitoring of coral reefs and �sheries. The sensor network consists of static and mobile underwater sensor nodes. The nodes communicate point-to-point using a novel high-speed optical communication system integrated into the TinyOS stack, and they broadcast using an acoustic protocol integrated in the TinyOS stack. The nodes have a variety of sensing capabilities, including cameras, water temperature, and pressure. The mobile nodes can locate and hover above the static nodes for data muling, and they can perform network maintenance functions such as deployment, relocation, and recovery. In this paper we describe the hardware and software architecture of this underwater sensor network. We then describe the optical and acoustic networking protocols and present experimental networking and data collected in a pool, in rivers, and in the ocean. Finally, we describe our experiments with mobility for data muling in this network.

An assessment of terrestrial water storage, rainfall and river discharge over Northern India from satellite data

Terrestrial water storage (TWS) plays a key role in the global water cycle and is highly influenced by climate variability and human activities. In this study, monthly TWS, rainfall and Ganga-Brahmaputra river discharge (GBRD) are analysed over India for the period of 2003-12 using remote sensing satellite data. The spatial pattern of mean TWS shows a decrease over a large and populous region of Northern India comprising the foothills of the Himalayas, the Indo-Gangetic Plains and North East India. Over this region, the mean monthly TWS exhibits a pronounced seasonal cycle and a large interannual variability, highly correlated with rainfall and GBRD variations (r > 0.8) with a lag time of 2 months and 1 month respectively. The time series of monthly TWS shows a consistent and statistically significant decrease of about 1 cm year(-1) over Northern India, which is not associated with changes in rainfall and GBRD. This recent change in TWS suggests a possible impact of rapid industrialization, urbanization and increase in population on land water resources. Our analysis highlights the potential of the Earth-observation satellite data for hydrological applications.

The UK WTC 9/11 evacuation study: methodologies used in the elicitation and storage of human factors data

This paper describes the methodologies employed in the collection and storage of first-hand accounts of evacuation experiences derived from face-to-face interviews with evacuees from the World Trade Center (WTC) Twin Towers complex on 11 September 2001. In particular the paper describes the development of the High-rise Evacuation Evaluation Database (HEED). This is a flexible qualitative research tool which contains the full transcribed interview accounts and coded evacuee experiences extracted from those transcripts. The data and information captured and stored in the HEED database is not only unique, but it provides a means to address current and emerging issues relating to human factors associated with the evacuation of high-rise buildings.

"One of our hosts in another country": Challenges of data geolocation in cloud storage

Physical location of data in cloud storage is an increasingly urgent problem. In a short time, it has evolved from the concern of a few regulated businesses to an important consideration for many cloud storage users. One of the characteristics of cloud storage is fluid transfer of data both within and among the data centres of a cloud provider. However, this has weakened the guarantees with respect to control over data replicas, protection of data in transit and physical location of data. This paper addresses the lack of reliable solutions for data placement control in cloud storage systems. We analyse the currently available solutions and identify their shortcomings. Furthermore, we describe a high-level architecture for a trusted, geolocation-based mechanism for data placement control in distributed cloud storage systems, which are the basis of an on-going work to define the detailed protocol and a prototype of such a solution. This mechanism aims to provide granular control over the capabilities of tenants to access data placed on geographically dispersed storage units comprising the cloud storage.

Generation, description and storage of dendritic morphology data

It is generally assumed that the variability of neuronal morphology has an important effect on both the connectivity and the activity of the nervous system, but this effect has not been thoroughly investigated. Neuroanatomical archives represent a crucial tool to explore structure–function relationships in the brain. We are developing computational tools to describe, generate, store and render large sets of three–dimensional neuronal structures in a format that is compact, quantitative, accurate and readily accessible to the neuroscientist. Single–cell neuroanatomy can be characterized quantitatively at several levels. In computer–aided neuronal tracing files, a dendritic tree is described as a series of cylinders, each represented by diameter, spatial coordinates and the connectivity to other cylinders in the tree. This ‘Cartesian’ description constitutes a completely accurate mapping of dendritic morphology but it bears little intuitive information for the neuroscientist. In contrast, a classical neuroanatomical analysis characterizes neuronal dendrites on the basis of the statistical distributions of morphological parameters, e.g. maximum branching order or bifurcation asymmetry. This description is intuitively more accessible, but it only yields information on the collective anatomy of a group of dendrites, i.e. it is not complete enough to provide a precise ‘blueprint’ of the original data. We are adopting a third, intermediate level of description, which consists of the algorithmic generation of neuronal structures within a certain morphological class based on a set of ‘fundamental’, measured parameters. This description is as intuitive as a classical neuroanatomical analysis (parameters have an intuitive interpretation), and as complete as a Cartesian file (the algorithms generate and display complete neurons). The advantages of the algorithmic description of neuronal structure are immense. If an algorithm can measure the values of a handful of parameters from an experimental database and generate virtual neurons whose anatomy is statistically indistinguishable from that of their real counterparts, a great deal of data compression and amplification can be achieved. Data compression results from the quantitative and complete description of thousands of neurons with a handful of statistical distributions of parameters. Data amplification is possible because, from a set of experimental neurons, many more virtual analogues can be generated. This approach could allow one, in principle, to create and store a neuroanatomical database containing data for an entire human brain in a personal computer. We are using two programs, L–NEURON and ARBORVITAE, to investigate systematically the potential of several different algorithms for the generation of virtual neurons. Using these programs, we have generated anatomically plausible virtual neurons for several morphological classes, including guinea pig cerebellar Purkinje cells and cat spinal cord motor neurons. These virtual neurons are stored in an online electronic archive of dendritic morphology. This process highlights the potential and the limitations of the ‘computational neuroanatomy’ strategy for neuroscience databases.

Design of a unified data with business rules storage model for OLTP and OLAP systems

This paper reviews the literature concerning the practice of using Online Analytical Processing (OLAP) systems to recall information stored by Online Transactional Processing (OLTP) systems. Such a review provides a basis for discussion on the need for the information that are recalled through OLAP systems to maintain the contexts of transactions with the data captured by the respective OLTP system. The paper observes an industry trend involving the use of OLTP systems to process information into data, which are then stored in databases without the business rules that were used to process information and data stored in OLTP databases without associated business rules. This includes the necessitation of a practice, whereby, sets of business rules are used to extract, cleanse, transform and load data from disparate OLTP systems into OLAP databases to support the requirements for complex reporting and analytics. These sets of business rules are usually not the same as business rules used to capture data in particular OLTP systems. The paper argues that, differences between the business rules used to interpret these same data sets, risk gaps in semantics between information captured by OLTP systems and information recalled through OLAP systems. Literature concerning the modeling of business transaction information as facts with context as part of the modelling of information systems were reviewed to identify design trends that are contributing to the design quality of OLTP and OLAP systems. The paper then argues that; the quality of OLTP and OLAP systems design has a critical dependency on the capture of facts with associated context, encoding facts with contexts into data with business rules, storage and sourcing of data with business rules, decoding data with business rules into the facts with the context and recall of facts with associated contexts. The paper proposes UBIRQ, a design model to aid the co-design of data with business rules storage for OLTP and OLAP purposes. The proposed design model provides the opportunity for the implementation and use of multi-purpose databases, and business rules stores for OLTP and OLAP systems. Such implementations would enable the use of OLTP systems to record and store data with executions of business rules, which will allow for the use of OLTP and OLAP systems to query data with business rules used to capture the data. Thereby ensuring information recalled via OLAP systems preserves the contexts of transactions as per the data captured by the respective OLTP system.

Influence of salinity on the interannual heat storage trends in the Atlantic estimated from altimeters and Pilot Research Moored Array in the Tropical Atlantic data

Changes in the oceanic heat storage (HS) can reveal important evidences of climate variability related to ocean heat fluxes. Specifically, long-term variations in HS are a powerful indicator of climate change as HS represents the balance between the net surface energy flux and the poleward heat transported by the ocean currents. HS is estimated from sea surface height anomaly measured from the altimeters TOPEX/Poseidon and Jason 1 from 1993 to 2006. To characterize and validate the altimeter-based HS in the Atlantic, we used the data from the Pilot Research Moored Array in the Tropical Atlantic (PIRATA) array. Correlations and rms differences are used as statistical figures of merit to compare the HS estimates. The correlations range from 0.50 to 0.87 in the buoys located at the equator and at the southern part of the array. In that region the rms differences range between 0.40 and 0.51 x 10(9) Jm(-2). These results are encouraging and indicate that the altimeter has the precision necessary to capture the interannual trends in HS in the Atlantic. Albeit relatively small, salinity changes can also have an effect on the sea surface height anomaly. To account for this effect, NCEP/GODAS reanalysis data are used to estimate the haline contraction. To understand which dynamical processes are involved in the HS variability, the total signal is decomposed into nonpropagating basin-scale and seasonal (HS(l)) planetary waves, mesoscale eddies, and small-scale residual components. In general, HS(l) is the dominant signal in the tropical region. Results show a warming trend of HS(l) in the past 13 years almost all over the Atlantic basin with the most prominent slopes found at high latitudes. Positive interannual trends are found in the halosteric component at high latitudes of the South Atlantic and near the Labrador Sea. This could be an indication that the salinity anomaly increased in the upper layers during this period. The dynamics of the South Atlantic subtropical gyre could also be subject to low-frequency changes caused by a trend in the halosteric component on each side of the South Atlantic Current.

VALIDATION OF THE LAND WATER STORAGE FROM GRAVITY RECOVERY AND CLIMATE EXPERIMENT (GRACE) WITH GAUGE DATA IN THE AMAZON BASIN

The Amazon basin is a region of constant scientific interest due to its environmental importance and its biodiversity and climate on a global scale. The seasonal variations in water volume are one of the examples of topics studied nowadays. In general, the variations in river levels depend primarily on the climate and physics characteristics of the corresponding basins. The main factor which influences the water level in the Amazon Basin is the intensive rainfall over this region as a consequence of the humidity of the tropical climate. Unfortunately, the Amazon basin is an area with lack of water level information due to difficulties in access for local operations. The purpose of this study is to compare and evaluate the Equivalent Water Height (Ewh) from GRACE (Gravity Recovery And Climate Experiment) mission, to study the connection between water loading and vertical variations of the crust due to the hydrologic. In order to achieve this goal, the Ewh is compared with in-situ information from limnimeter. For the analysis it was computed the correlation coefficients, phase and amplitude of GRACE Ewh solutions and in-situ data, as well as the timing of periods of drought in different parts of the basin. The results indicated that vertical variations of the lithosphere due to water mass loading could reach 7 to 5 cm per year, in the sedimentary and flooded areas of the region, where water level variations can reach 10 to 8 m.