Mapping NGO Competency to Reduce Human Vulnerability in Post-disaster Communities: Comparing Strategies in Sri Lanka and Bangladesh

Natural hazards trigger disasters, the scale of which is largely determined by vulnerability. Developing countries suffer the most from disasters due to various conditions of vulnerability which exist and there is an opportunity after disasters to take mitigative action. NGOs implementing post-disaster rehabilitation projects must be able to address the issues causing communities to live at risk of disaster and therefore must build dynamic capacity, capabilities and competencies, enabling them to operate in unstable environments. This research is built upon a theoretical framework of dynamic competency established by combining elements of disaster management, strategic management and project management theory. A number of NGOs which have implemented reconstruction and rehabilitation projects both in Sri Lanka following the Asian Tsunami and Bangladesh following Cyclone Sidr are being investigated in great depth using a causal mapping procedure. ‘Event’ specific maps have been developed for each organization in each disaster. This data will be analysed with a view to discovering the strategies which lead to vulnerability reduction in post-disaster communities and the competencies that NGOs must possess in order to achieve favourable outcomes. It is hypothesized that by building organizational capacity, capabilities and competencies to be dynamic in nature, while focusing on a more emergent strategic approach, with emphasis on adaptive capability and innovation, NGOs will be better equipped to contribute to sustainable community development through reconstruction. We believe that through this study it will be possible to glean a new understanding of social processes that emerge within community rehabilitation projects.

Novel breast cancer biomarkers identified by integrative proteomic and gene expression mapping

Proteomic and transcriptomic platforms both play important roles in cancer research, with differing strengths and limitations. Here, we describe a proteo-transcriptomic integrative strategy for discovering novel cancer biomarkers, combining the direct visualization of differentially expressed proteins with the high-throughput scale of gene expression profiling. Using breast cancer as a case example, we generated comprehensive two-dimensional electrophoresis (2DE)/mass spectrometry (MS) proteomic maps of cancer (MCF-7 and HCC-38) and control (CCD-1059Sk) cell lines, identifying 1724 expressed protein spots representing 484 different protein species. The differentially expressed cell-line proteins were then mapped to mRNA transcript databases of cancer cell lines and primary breast tumors to identify candidate biomarkers that were concordantly expressed at the gene expression level. Of the top nine selected biomarker candidates, we reidentified ANX1, a protein previously reported to be differentially expressed in breast cancers and normal tissues, and validated three other novel candidates, CRAB, 6PGL, and CAZ2, as differentially expressed proteins by immunohistochemistry on breast tissue microarrays. In total, close to half (4/9) of our protein biomarker candidates were successfully validated. Our study thus illustrates how the systematic integration of proteomic and transcriptomic data from both cell line and primary tissue samples can prove advantageous for accelerating cancer biomarker discovery.

Business representation and the UK regions: mapping institutional change

Political devolution in Scotland, Wales and Northern Ireland and the developing regional agenda in England are prompting changes in the organization of business interest representation within the devolved and decentralized territories. In this paper we seek to describe the realignment of business interest representation at the 'regional' scale, first through a detailed review of changes underway across specific business associations and representative fora, and secondly through an initial attempt to compare and 'map' the patterns of institutional change recorded in the various territories. In broad terms the overall scale, operation and degree of formalization of the new political arrangements for business representation tend broadly to reflect the established institutional and political contexts of the respective nations and regions and the level of devolution ceded to the territories. However, there are important variations in a complex process of uneven development. In the concluding section we present some initial thoughts on the nature of the changes observed in the institutional framework for business representation. A key argument is that to date such changes suggest a reconfiguration of business political activity rather than a step-change in the institutional foundation for sub-national business interest representation in the UK. (C) 2003 Elsevier Ltd. All rights reserved.

Cache-Integrated Network Interfaces: Flexible On-Chip Communication and Synchronization for Large-Scale CMPs

Per-core scratchpad memories (or local stores) allow direct inter-core communication, with latency and energy advantages over coherent cache-based communication, especially as CMP architectures become more distributed. We have designed cache-integrated network interfaces, appropriate for scalable multicores, that combine the best of two worlds – the flexibility of caches and the efficiency of scratchpad memories: on-chip SRAM is configurably shared among caching, scratchpad, and virtualized network interface (NI) functions. This paper presents our architecture, which provides local and remote scratchpad access, to either individual words or multiword blocks through RDMA copy. Furthermore, we introduce event responses, as a technique that enables software configurable communication and synchronization primitives. We present three event response mechanisms that expose NI functionality to software, for multiword transfer initiation, completion notifications for software selected sets of arbitrary size transfers, and multi-party synchronization queues. We implemented these mechanisms in a four-core FPGA prototype, and measure the logic overhead over a cache-only design for basic NI functionality to be less than 20%. We also evaluate the on-chip communication performance on the prototype, as well as the performance of synchronization functions with simulation of CMPs with up to 128 cores. We demonstrate efficient synchronization, low-overhead communication, and amortized-overhead bulk transfers, which allow parallelization gains for fine-grain tasks, and efficient exploitation of the hardware bandwidth.

Micron-scale fast electron filaments and recirculation determined from rear-side optical emission in high-intensity laser-solid interactions

The transport of relativistic electrons generated in the interaction of petawatt class lasers with solid targets has been studied through measurements of the second harmonic optical emission from their rear surface. The high degree of polarization of the emission indicates that it is predominantly optical transition radiation (TR). A halo that surrounds the main region of emission is also polarized and is attributed to the effect of electron recirculation. The variation of the polarization state and intensity of radiation with the angle of observation indicates that the emission of TR is highly directional and provides evidence for the presence of mu m-size filaments. A brief discussion on the possible causes of such a fine electron beam structure is given.

Towards mapping the late Quaternary vegetation change of Europe

The number of well-dated pollen diagrams in Europe has increased considerably over the last 30 years and many of them have been submitted to the European Pollen Database (EPD). This allows for the construction of increasingly precise maps of Holocene vegetation change across the continent. Chronological information in the EPD has been expressed in uncalibrated radiocarbon years, and most chronologies to date are based on this time scale. Here we present new chronologies for most of the datasets stored in the EPD based on calibrated radiocarbon years. Age information associated with pollen diagrams is often derived from the pollen stratigraphy itself or from other sedimentological information. We reviewed these chronological tie points and assigned uncertainties to them. The steps taken to generate the new chronologies are described and the rationale for a new classification system for age uncertainties is introduced. The resulting chronologies are fit for most continental-scale questions. They may not provide the best age model for particular sites, but may be viewed as general purpose chronologies. Taxonomic particularities of the data stored in the EPD are explained. An example is given of how the database can be queried to select samples with appropriate age control as well as the suitable taxonomic level to answer a specific research question. © 2013 The Author(s).

Using ancestry-informative markers to identify fine structure across 15 populations of European origin

The Wellcome Trust Case Control Consortium 3 anorexia nervosa genome-wide association scan includes 2907 cases from 15 different populations of European origin genotyped on the Illumina 670K chip. We compared methods for identifying population stratification, and suggest list of markers that may help to counter this problem. It is usual to identify population structure in such studies using only common variants with minor allele frequency (MAF) >5%; we find that this may result in highly informative SNPs being discarded, and suggest that instead all SNPs with MAF >1% may be used. We established informative axes of variation identified via principal component analysis and highlight important features of the genetic structure of diverse European-descent populations, some studied for the first time at this scale. Finally, we investigated the substructure within each of these 15 populations and identified SNPs that help capture hidden stratification. This work can provide information regarding the designing and interpretation of association results in the International Consortia. 

Using geostatistical Bayesian Updating to integrate airborne radiometrics and soil geochemistry to improve mapping for mineral exploration

Mineral exploration programmes around the world use data from remote sensing, geophysics and direct sampling. On a regional scale, the combination of airborne geophysics and ground-based geochemical sampling can aid geological mapping and economic minerals exploration. The fact that airborne geophysical and traditional soil-sampling data are generated at different spatial resolutions means that they are not immediately comparable due to their different sampling density. Several geostatistical techniques, including indicator cokriging and collocated cokriging, can be used to integrate different types of data into a geostatistical model. With increasing numbers of variables the inference of the cross-covariance model required for cokriging can be demanding in terms of effort and computational time. In this paper a Gaussian-based Bayesian updating approach is applied to integrate airborne radiometric data and ground-sampled geochemical soil data to maximise information generated from the soil survey, to enable more accurate geological interpretation for the exploration and development of natural resources. The Bayesian updating technique decomposes the collocated estimate into a production of two models: prior and likelihood models. The prior model is built from primary information and the likelihood model is built from secondary information. The prior model is then updated with the likelihood model to build the final model. The approach allows multiple secondary variables to be simultaneously integrated into the mapping of the primary variable. The Bayesian updating approach is demonstrated using a case study from Northern Ireland where the history of mineral prospecting for precious and base metals dates from the 18th century. Vein-hosted, strata-bound and volcanogenic occurrences of mineralisation are found. The geostatistical technique was used to improve the resolution of soil geochemistry, collected one sample per 2 km2, by integrating more closely measured airborne geophysical data from the GSNI Tellus Survey, measured over a footprint of 65 x 200 m. The directly measured geochemistry data were considered as primary data in the Bayesian approach and the airborne radiometric data were used as secondary data. The approach produced more detailed updated maps and in particular maximized information on mapped estimates of zinc, copper and lead. Greater delineation of an elongated northwest/southeast trending zone in the updated maps strengthened the potential to investigate stratabound base metal deposits.

Combining multi-scale geophysical techniques for robust hydro-structural characterisation in catchments underlain by hard rock in post-glacial regions

Accurate conceptual models of groundwater systems are essential for correct interpretation of monitoring data in catchment studies. In surface-water dominated hard rock regions, modern ground and surface water monitoring programmes often have very high resolution chemical, meteorological and hydrological observations but lack an equivalent emphasis on the subsurface environment, the properties of which exert a strong control on flow pathways and interactions with surface waters. The reasons for this disparity are the complexity of the system and the difficulty in accurately characterising the subsurface, except locally at outcrops or in boreholes. This is particularly the case in maritime north-western Europe, where a legacy of glacial activity, combined with large areas underlain by heterogeneous igneous and metamorphic bedrock, make the structure and weathering of bedrock difficult to map or model. Traditional approaches which seek to extrapolate information from borehole to field-scale are of limited application in these environments due to the high degree of spatial heterogeneity. Here we apply an integrative and multi-scale approach, optimising and combining standard geophysical techniques to generate a three-dimensional geological conceptual model of the subsurface in a catchment in NE Ireland. Available airborne LiDAR, electromagnetic and magnetic data sets were analysed for the region. At field-scale surface geophysical methods, including electrical resistivity tomography, seismic refraction, ground penetrating radar and magnetic surveys, were used and combined with field mapping of outcrops and borehole testing. The study demonstrates how combined interpretation of multiple methods at a range of scales produces robust three-dimensional conceptual models and a stronger basis for interpreting groundwater and surface water monitoring data.

Spatially-resolved mapping of history-dependent coupled electrochemical and electronical behaviors of electroresistive NiO

Bias-induced oxygen ion dynamics underpins a broad spectrum of electroresistive and memristive phenomena in oxide materials. Although widely studied by device-level and local voltage-current spectroscopies, the relationship between electroresistive phenomena, local electrochemical behaviors, and microstructures remains elusive. Here, the interplay between history-dependent electronic transport and electrochemical phenomena in a NiO single crystalline thin film with a number of well-defined defect types is explored on the nanometer scale using an atomic force microscopy-based technique. A variety of electrochemically-active regions were observed and spatially resolved relationship between the electronic and electrochemical phenomena was revealed. The regions with pronounced electroresistive activity were further correlated with defects identified by scanning transmission electron microscopy. Using fully coupled mechanical-electrochemical modeling, we illustrate that the spatial distribution of strain plays an important role in electrochemical and electroresistive phenomena. These studies illustrate an approach for simultaneous mapping of the electronic and ionic transport on a single defective structure level such as dislocations or interfaces, and pave the way for creating libraries of defect-specific electrochemical responses.

Plant community assembly at small scales: spatial versus environmental factors in a central European grassland

Dispersal limitation and environmental conditions are crucial drivers of plant species distribution and establishment. As these factors operate at different spatial scales, we asked: Do the environmental factors known to determine community assembly at broad scales operate at fine scales (few meters)? How much do these factors account for community variation at fine scales? In which way do biotic and abiotic interactions drive changes in species composition? We surveyed the plant community within a dry grassland along a very steep gradient of soil characteristics like pH and nutrients. We used a spatially explicit sampling design, based on three replicated macroplots of 15x15, 12x12 and 12x12 meters in extent. Soil samples were taken to quantify several soil properties (carbon, nitrogen, plant available phosphorus, pH, water content and dehydrogenase activity as a proxy for overall microbial activity). We performed variance partitioning to assess the effect of these variables on plant composition and statistically controlled for spatial autocorrelation via eigenvector mapping. We also applied null model analysis to test for non-random patterns in species co-occurrence using randomization schemes that account for patterns expected under species interactions. At a fine spatial scale, environmental factors explained 18% of variation when controlling for spatial autocorrelation in the distribution of plant species, whereas purely spatial processes accounted for 14% variation. Null model analysis showed that species spatially segregated in a non-random way and these spatial patterns could be due to a combination of environmental filtering and biotic interactions. Our grassland study suggests that environmental factors found to be directly relevant in broad scale studies are present also at small scales, but are supplemented by spatial processes and more direct interactions like competition.

Connectivity mapping using a combined gene signature from multiple colorectal cancer datasets identified candidate drugs including existing chemotherapies

BACKGROUND: While the discovery of new drugs is a complex, lengthy and costly process, identifying new uses for existing drugs is a cost-effective approach to therapeutic discovery. Connectivity mapping integrates gene expression profiling with advanced algorithms to connect genes, diseases and small molecule compounds and has been applied in a large number of studies to identify potential drugs, particularly to facilitate drug repurposing. Colorectal cancer (CRC) is a commonly diagnosed cancer with high mortality rates, presenting a worldwide health problem. With the advancement of high throughput omics technologies, a number of large scale gene expression profiling studies have been conducted on CRCs, providing multiple datasets in gene expression data repositories. In this work, we systematically apply gene expression connectivity mapping to multiple CRC datasets to identify candidate therapeutics to this disease.

RESULTS: We developed a robust method to compile a combined gene signature for colorectal cancer across multiple datasets. Connectivity mapping analysis with this signature of 148 genes identified 10 candidate compounds, including irinotecan and etoposide, which are chemotherapy drugs currently used to treat CRCs. These results indicate that we have discovered high quality connections between the CRC disease state and the candidate compounds, and that the gene signature we created may be used as a potential therapeutic target in treating the disease. The method we proposed is highly effective in generating quality gene signature through multiple datasets; the publication of the combined CRC gene signature and the list of candidate compounds from this work will benefit both cancer and systems biology research communities for further development and investigations.

A large scale model experimental study of a tidal turbine in uniform steady flow

An experimental study measuring the performance and wake characteristics of a 1:10th scale horizontal axis turbine in steady uniform flow conditions is presented in this paper.
Large scale towing tests conducted in a lake were devised to model the performance of the tidal turbine and measure the wake produced. As a simplification of the marine environment, towing the turbine in a lake provides approximately steady, uniform inflow conditions. A 16m long x 6m wide catamaran was constructed for the test programme. This doubled as a towing rig and flow measurement platform, providing a fixed frame of reference for measurements in the wake of a horizontal axis tidal turbine. Velocity mapping was conducted using Acoustic Doppler Velocimeters.
The results indicate varying the inflow speed yielded little difference in the efficiency of the turbine or the wake velocity deficit characteristics provided the same tip speed ratio is used. Increasing the inflow velocity from 0.9 m/s to 1.2 m/s influenced the turbulent wake characteristics more markedly. The results also demonstrate that the flow field in the wake of a horizontal axis tidal turbine is strongly affected by the turbine support structure

Fine-structure photoionization cross sections of Fe II

We present the first calculation of fine-structure photoionization cross sections for the ground state of singly ionized Fe. These large-scale ab initio calculations, limited to the near-threshold region, were performed in the close-coupling approximation using a Dirac–Coulomb R -matrix method implemented within a modified version of the DARC package. Our calculated cross sections reproduce in detail the resonance structures observed in previous experimental determinations.

Cortical object segregation and categorization by multi-scale line and edge coding

In this paper we present an improved scheme for line and edge detection in cortical area V1, based on responses of simple and complex cells, truly multi-scale with no free parameters. We illustrate the multi-scale representation for visual reconstruction, and show how object segregation can be achieved with coarse-to-finescale groupings. A two-level object categorization scenario is tested in which pre-categorization is based on coarse scales only, and final categorization on coarse plus fine scales. Processing schemes are discussed in the framework of a complete cortical architecture.