Masking device Patent

Reusable masking boot for chemical machining operation

Pink landscapes: 1/f spectra of spatial environmental variability and bird community composition

Temporal and spatial environmental variability are predicted to have reddened spectra that reveal increases in variance with the period or length sampled. However, spectral analyses have seldom been performed on ecological data to determine whether these predictions hold true in the case of spatial environmental variability. For a 50 km long continuous transect of 128 point samples across a heterogeneous cultural landscape in the Czech Republic, both habitat composition and bird species composition decomposed by standard ordination techniques did indeed exhibit reddened spectra. The values of main ordination axes have relationships between log spectral density and log frequency with slopes close to -1, indicating 1/f, or 'pink' noise type of variability that is characterized by scale invariance. However, when habitat composition was controlled for and only residuals for bird species composition were analysed, the spectra revealed a peak at intermediate frequencies, indicating that population processes that structure bird communities but are not directly related to the structure of the environment might have some typical correlation length. Spatial variability of abundances of individual species was mostly reddened as well, but the degree was positively correlated to their total abundance and niche position (strength of species-habitat association). If 'pink' noise type of variability is as generally typical for spatial environmental variability as for temporal variability, the consequences may be profound for patterns of species diversity on different spatial scales, the form of species-area relationships and the distribution of abundances within species ranges

Focusing on the Big Picture: Insights into a Systems Approach to Deep Learning for Satellite Imagery

Deep learning tasks are often complicated and require a variety of components working together efficiently to perform well. Due to the often large scale of these tasks, there is a necessity to iterate quickly in order to attempt a variety of methods and to find and fix bugs. While participating in IARPA's Functional Map of the World challenge, we identified challenges along the entire deep learning pipeline and found various solutions to these challenges. In this paper, we present the performance, engineering, and deep learning considerations with processing and modeling data, as well as underlying infrastructure considerations that support large-scale deep learning tasks. We also discuss insights and observations with regard to satellite imagery and deep learning for image classification.Comment: Accepted to IEEE Big Data 201

Causality in 3D Massive Gravity Theories

We study the constraints coming from local causality requirement in various $2+1$ dimensional dynamical theories of gravity. In topologically massive gravity, with a single parity non-invariant massive degree of freedom, and in new massive gravity, with two massive spin-$2$ degrees of freedom, causality and unitarity are compatible with each other and both require the Newton's constant to be negative. In their extensions, such as the Born-Infeld gravity and the minimal massive gravity the situation is similar and quite different from their higher dimensional counterparts, such as quadratic (e.g., Einstein-Gauss-Bonnet) or cubic theories, where causality and unitarity are in conflict. We study the problem both in asymptotically flat and asymptotically anti-de Sitter spaces.Comment: This version has significant improvements: causality discussion of all the well-known gravity theories in flat space is extended to the AdS space, references added, 29 pages, latest version matches the published on

Structure of the species-energy relationship

The relationship between energy availability and species richness (the species-energy relationship) is one of the best documented macroecological phenomena. However, the structure of species distribution along the gradient, the proximate driver of the relationship, is poorly known. Here, using data on the distribution of birds in southern Africa, for which species richness increases linearly with energy availability, we provide an explicit determination of this structure. We show that most species exhibit increasing occupancy towards more productive regions (occurring in more grid cells within a productivity class). However, average reporting rates per species within occupied grid cells, a correlate of local density, do not show a similar increase. The mean range of used energy levels and the mean geographical range size of species in southern Africa decreases along the energy gradient, as most species are present at high productivity levels but only some can extend their ranges towards lower levels. Species turnover among grid cells consequently decreases towards high energy levels. In summary, these patterns support the hypothesis that higher productivity leads to more species by increasing the probability of occurrence of resources that enable the persistence of viable populations, without necessarily affecting local population densities

Using presence-absence data to establish reserve selection procedures that are robust to temporal species turnover

Previous studies suggest that a network of nature reserves with maximum efficiency (obtained by selecting the minimum area such that each species is represented once) is likely to be insufficient to maintain species in the network over time. Here, we test the performance of three selection strategies which require presence-absence data, two of them previously proposed (multiple representations and selecting an increasing percentage of each species' range) and a novel one based on selecting the site where each species has exhibited a higher permanence rate in the past. Multiple representations appear to be a safer strategy than selecting a percentage of range because the former gives priority to rarer species while the latter favours the most widespread. The most effective strategy was the one based on the permanence rate, indicating that the robustness of reserve networks can be improved by adopting reserve selection procedures that integrate information about the relative value of sites. This strategy was also very efficient, suggesting that the investment made in the monitoring schemes may be compensated for by a lower cost in reserve acquisition

Robustness of reserve selection procedures under temporal species turnover

Complementarity-based algorithms for the selection of reserve networks emphasize the need to represent biodiversity features efficiently, but this may not be sufficient to maintain those features in the long term. Here, we use data from the Common Birds Census in Britain as an exemplar data set to determine guidelines for the selection of reserve networks which are more robust to temporal turnover in features. The extinction patterns found over the 1981-1991 interval suggest that two such guidelines are to represent species in the best sites where they occur (higher local abundance) and to give priority to the rarer species. We tested five reserve selection strategies, one which finds the minimum representation set and others which incorporate the first or both guidelines proposed. Strategies were tested in terms of their efficiency (inversely related to the total area selected) and effectiveness (inversely related to the percentage of species lost) using data on eight pairs of ten-year intervals. The minimum set strategy was always the most efficient, but suffered higher species loss than the others, suggesting that there is a trade-off between efficiency and effectiveness. A desirable compromise can be achieved by embedding the concerns about the long-term maintenance of the biodiversity features of interest in the complementarity-based algorithms

Mapping biodiversity value worldwide: combining higher-taxon richness from different groups

Maps of large-scale biodiversity are urgently needed to guide conservation, and yet complete enumeration of organisms is impractical at present. One indirect approach is to measure richness at higher taxonomic ranks, such as families. The difficulty is how to combine information from different groups on numbers of higher taxa, when these taxa may in effect have been defined in different ways, particularly for more distantly related major groups. In this paper, the regional family richness of terrestrial and freshwater seed plants, amphibians, reptiles and mammals is mapped worldwide by combining: (i) absolute family richness; (ii) proportional family richness; and (iii) proportional family richness weighted for the total species richness in each major group. The assumptions of the three methods and their effects on the results are discussed, although for these data the broad pattern is surprisingly robust with respect to the method of combination. Scores from each of the methods of combining families are used to rank the top five richness hotspots and complementary areas, and hotspots of endemism are mapped by unweighted combination of range-size rarity scores