Early Warning of Food Security Crises in Urban Areas: The Case of Harare, Zimbabwe, 2007

In 2007, the citizens of Harare, Zimbabwe began experiencing an intense food security crisis. The crisis, due to a complex mix of poor government policies, high inflation rates and production decline due to drought, resulted in a massive increase in the number of food insecure people in Harare. The international humanitarian aid response to this crisis was largely successful due to the early agreement among donors and humanitarian aid officials as to the size and nature of the problem. Remote sensing enabled an early and decisive movement of resources greatly assisting the delivery of food aid in a timely manner. Remote sensing data gave a clear and compelling assessment of significant crop production shortfalls, and provided donors of humanitarian assistance a single number around which they could come to agreement. This use of remote sensing data typifies how remote sensing may be used in early warning systems in Africa

Quantitative empirical trends in technical performance

Technological improvement trends such as Moore’s law and experience curves have been widely used to understand how technologies change over time and to forecast the future through extrapolation. Such studies can also potentially provide a deeper understanding of R&D management and strategic issues associated with technical change. However, this requires that methodological approaches for these analyses be addressed and compared to more effectively interpret results. Our analysis of methodological issues recommends less ambiguous approaches to: 1) the unit of analysis; 2) choice of the metrics within a unit of analysis; 3) the relationships among possible independent variables; and 4) qualitative and quantitative data quality considerations. The paper then uses this methodology to analyze performance trends for 28 technological domains with the following findings: 1. Sahal’s relationship is tested for several effort variables (for patents and revenue in addition to cumulative production where it was first developed). 2. The relationship is quite accurate when all three relationships, ( a. an exponential between performance and time, b. an exponential of effort and time and c. a power law between performance and the effort variable) have good data fits (r2 >0.7) . 3. The power law and effort exponents determined are dependent upon the choice of effort variable but the time dependence exponential is not. 4. In domains where the quantity of patents do not increase exponentially with time, Sahal’s relationship gives poor estimates even though Moore’s law is followed even for these domains. 5. Good data quality for any of the relationships depends upon adequate screening involving not only r2 but also the confidence interval based upon two different statistical tests; by these measures, all 28 domains have high quality fits between the log of performance and time whereas less than ½ show this level of quality for power law fits with patents as the effort variable. Overall, the results are interpreted as indicating that Moore’s law is a better description of longer-term technological change when the performance data come from various designs whereas experience curves may be more relevant when a singular design in a given factory is considered

Gene Ontology synonym generation rules lead to increased performance in biomedical concept recognition

BACKGROUND: Gene Ontology (GO) terms represent the standard for annotation and representation of molecular functions, biological processes and cellular compartments, but a large gap exists between the way concepts are represented in the ontology and how they are expressed in natural language text. The construction of highly specific GO terms is formulaic, consisting of parts and pieces from more simple terms. RESULTS: We present two different types of manually generated rules to help capture the variation of how GO terms can appear in natural language text. The first set of rules takes into account the compositional nature of GO and recursively decomposes the terms into their smallest constituent parts. The second set of rules generates derivational variations of these smaller terms and compositionally combines all generated variants to form the original term. By applying both types of rules, new synonyms are generated for two-thirds of all GO terms and an increase in F-measure performance for recognition of GO on the CRAFT corpus from 0.498 to 0.636 is observed. Additionally, we evaluated the combination of both types of rules over one million full text documents from Elsevier; manual validation and error analysis show we are able to recognize GO concepts with reasonable accuracy (88 %) based on random sampling of annotations. CONCLUSIONS: In this work we present a set of simple synonym generation rules that utilize the highly compositional and formulaic nature of the Gene Ontology concepts. We illustrate how the generated synonyms aid in improving recognition of GO concepts on two different biomedical corpora. We discuss other applications of our rules for GO ontology quality assurance, explore the issue of overgeneration, and provide examples of how similar methodologies could be applied to other biomedical terminologies. Additionally, we provide all generated synonyms for use by the text-mining community

Comment on 'Shang S. 2012. Calculating actual crop evapotranspiration under soil water stress conditions with appropriate numerical methods and time step. Hydrological Processes 26: 3338-3343. DOI: 10.1002/hyp.8405'

A previous study analyzed errors in the numerical calculation of actual crop evapotranspiration (ET(sub a)) under soil water stress. Assuming no irrigation or precipitation, it constructed equations for ET(sub a) over limited soil-water ranges in a root zone drying out due to evapotranspiration. It then used a single crop-soil composite to provide recommendations about the appropriate usage of numerical methods under different values of the time step and the maximum crop evapotranspiration (ET(sub c)). This comment reformulates those ET(sub a) equations for applicability over the full range of soil water values, revealing a dependence of the relative error in numerical ET(sub a) on the initial soil water that was not seen in the previous study. It is shown that the recommendations based on a single crop-soil composite can be invalid for other crop-soil composites. Finally, a consideration of the numerical error in the time-cumulative value of ET(sub a) is discussed besides the existing consideration of that error over individual time steps as done in the previous study. This cumulative ET(sub a) is more relevant to the final crop yield

Elements of Moral Functioning in Sport and School

Moral functioning is complex and implicates numerous cognitive and affective processes. Drawing upon Rest’s four-component model of moral functioning and more recent dual-process accounts of cognition, the current study examined a model of moral functioning in both sport and school contexts. Specifically, drawing upon the empirical record, a model of moral functioning was proposed and tested wherein moral identity influenced the adoption of specific contesting orientations, which, in turn, influenced prosocial and antisocial behaviors, both directly and indirectly via moral foundations and moral disengagement. Fit of the model was moderately strong in both contexts, though significant contextual differences emerged, both in terms of interrelationships between moral variables and in intra-individual variability within moral variables. Findings suggested that moral identity, a partnership approach to contesting, and moral foundations that emphasize care and fairness were associated with reduced antisocial behavior across contexts, while a war approach to contesting and moral disengagement were associated with increased antisocial behavior across contexts. Thus, practitioners concerned with athletes’ moral behavior may do well to: 1) promote the importance of moral concerns to the athlete’s self-identity; 2) highlight the cooperative and mutually-beneficial aspects of contests; and, 3) emphasize the importance of the moral values of care and fairness

Globally Gridded Satellite (GridSat) Observations for Climate Studies

Geostationary satellites have provided routine, high temporal resolution Earth observations since the 1970s. Despite the long period of record, use of these data in climate studies has been limited for numerous reasons, among them: there is no central archive of geostationary data for all international satellites, full temporal and spatial resolution data are voluminous, and diverse calibration and navigation formats encumber the uniform processing needed for multi-satellite climate studies. The International Satellite Cloud Climatology Project set the stage for overcoming these issues by archiving a subset of the full resolution geostationary data at approx.10 km resolution at 3 hourly intervals since 1983. Recent efforts at NOAA s National Climatic Data Center to provide convenient access to these data include remapping the data to a standard map projection, recalibrating the data to optimize temporal homogeneity, extending the record of observations back to 1980, and reformatting the data for broad public distribution. The Gridded Satellite (GridSat) dataset includes observations from the visible, infrared window, and infrared water vapor channels. Data are stored in the netCDF format using standards that permit a wide variety of tools and libraries to quickly and easily process the data. A novel data layering approach, together with appropriate satellite and file metadata, allows users to access GridSat data at varying levels of complexity based on their needs. The result is a climate data record already in use by the meteorological community. Examples include reanalysis of tropical cyclones, studies of global precipitation, and detection and tracking of the intertropical convergence zone

An Event-Based Approach for the Conservative Compression of Covariance Matrices

This work introduces a flexible and versatile method for the data-efficient yet conservative transmission of covariance matrices, where a matrix element is only transmitted if a so-called triggering condition is satisfied for the element. Here, triggering conditions can be parametrized on a per-element basis, applied simultaneously to yield combined triggering conditions or applied only to certain subsets of elements. This allows, e.g., to specify transmission accuracies for individual elements or to constrain the bandwidth available for the transmission of subsets of elements. Additionally, a methodology for learning triggering condition parameters from an application-specific dataset is presented. The performance of the proposed approach is quantitatively assessed in terms of data reduction and conservativeness using estimate data derived from real-world vehicle trajectories from the InD-dataset, demonstrating substantial data reduction ratios with minimal over-conservativeness. The feasibility of learning triggering condition parameters is demonstrated.Comment: 12 pages, 9 figures, submitted to: IEEE Transactions on Automatic Contro