Seismic fragility assessment of nonstructural components in unreinforced clay brick masonry buildings

The results of an investigation of the probability of earthquake damage to nonstructural unreinforced masonry (URM) components are presented. The components include parapets, chimneys, and out-of-plane loaded facades typical of low-rise pre-1940 construction in Australia and New Zealand. The study is based on a street survey of component geometry, in situ data on material strength, and simplified mechanical models. Uncertainties in capacity and demand were quantified based on, respectively, stochastic and deterministic approaches. The damage probabilities were compared with relevant guidelines and empirical damage data from three earthquakes. The study established a link between the qualitative damage states reported in existing guidelines and the quantitative URM component damage states. While some median damage state thresholds correlated well with the data from the guidelines, a larger dispersion value was found in the current study due to the large variations in component properties. Comparisons with empirical data suggest that the developed fragility data provide a realistic estimate of nonstructural component damage that occurred in similar buildings, with a reasonable level of conservatism. The outcome is useful in rapid assessment of the seismic risks due to nonstructural component collapse in URM precincts.     

Implementing Moran eigenvector spatial filtering for massively large georeferenced datasets

Moran eigenvector spatial filtering (MESF) furnishes an alternative method to account for spatial autocorrelation in linear regression specifications describing georeferenced data, although spatial auto-models also are widely used. The utility of this MESF methodology is even more impressive for the non-Gaussian models because its flexible structure enables it to be easily applied to generalized linear models, which include Poisson, binomial, and negative binomial regression. However, the implementation of MESF can be computationally challenging, especially when the number of geographic units, n, is large, or massive, such as with a remotely sensed image. This intensive computation aspect has been a drawback to the use of MESF, particularly for analyzing a remotely sensed image, which can easily contain millions of pixels. Motivated by Curry, this paper proposes an approximation approach to constructing eigenvector spatial filters (ESFs) for a large spatial tessellation. This approximation is based on a divide-and-conquer approach. That is, it constructs ESFs separately for each sub-region, and then combines the resulting ESFs across an entire remotely sensed image. This paper, employing selected specimen remotely sensed images, demonstrates that the proposed technique provides a computationally efficient and successful approach to implement MESF for large or massive spatial tessellations.     

Incorporating sprawl and adjacency measures in land‐use forecasting model: A case study of Collin County,TX

Sprawl measures have largely been neglected in land‐use forecasting models. The current approach for land‐use allocation using optimization mostly utilizes objective functions and constraints that are non‐spatial in nature. Application of spatial constraints could take care of the contiguity and compactness of land uses and can be utilized to address urban sprawl. Because a land‐use model is used as an input to transportation modeling, a better spatial allocation strategy for more compact land‐use projections will promote better transportation planning and sustainable development. This study formulates a scenario‐based approach to normative modeling of urban sprawl. In doing so, it seeks to improve the land‐use projections by employing a spatial optimization model with contiguity and compactness consideration. This study incorporates urban sprawl measures based on smart growth principles together with a mixed‐use factor, and adjacency consideration of nearby land uses. The objective function used in the study maximizes net suitability based on imposed constraints. These constraints are based on smart growth principles that enhance walkability in neighborhoods, promote better health for residents, and encourage mixed‐use development. The formulated model has been applied to Collin County, TX, a fast‐developing suburban county located to the north of the Dallas–Fort Worth metroplex. The suitability of land cells indicates the probability of conversion, which is calculated using spatial discrete choice analysis with Moran eigenvector spatial filtering for vacant cells at a resolution of 150 × 150 m employing factors of the built environment, and socioeconomic and demographic characteristics. This study demonstrates how spatial proximity between land uses, which has been ignored to date, can be used to control sprawl, resulting in better mixing of different land uses based on constraints imposed in a spatial optimization problem.     

Modeling spatial autocorrelation in spatial interaction data: empirical evidence from 2002 Germany journey-to-work flows

Since before the inception of work by Okabe, the intermingling of spatial autocorrelation (i.e., local distance and configuration) and distance decay (i.e., global distance) effects has been suspected in spatial interaction data. This convolution was first treated conceptually because technology and methodology did not exist at the time to easily or fully address spatial autocorrelation effects within spatial interaction model specifications. Today, however, sufficient computer power coupled with eigenfunction-based spatial filtering offers a means for accommodating spatial autocorrelation effects within a spatial interaction model for modest-sized problems. In keeping with Okabe’s more recent efforts to dissemination spatial analysis tools, this paper summarizes how to implement the methodology utilized to analyze a particular empirical flows dataset.

The carbohydrate‐to‐protein ratio as a biological indicator of water movement

We investigated temporal (day‐to‐day and season) and spatial (reach) variability of drift with the aim of guiding sampling protocol for quantifying drift at the whole river or reach scale. Overall, we found aquatic drift density and biomass varied considerably seasonally (CV = 72.9, 88.1) and to a lesser extent spatially (CV = 31.3, 30.7) and from day‐to‐day (CV = 45.2, 39.4). Although spatial and day‐to‐day variation in drift density and biomass were similar, sampling logistics suggest spatial sampling would be more cost‐effective and less time consuming. Drift density and biomass estimated from top samplers was often higher than estimates from samplers near the streambed or mid‐water column. A reliable estimate of mean densities and biomass at a site may require only two samplers— a top sampler and either a middle or bottom sampler. In our study, we calculated that sampling at four sites over 1 or 4 days at one site would be required to obtain a 95% CI within 50% of the mean drift density. Eight sites over 1 or 10 days at one site would be required to achieve a 95% CI within 25% of the mean drift density.     

Sympatric seagrass shrimp show similar structure and selection along the seashore: a comparison of two cryptic Phycomenes zostericola lineages

Small crustaceans are diverse and abundant in seagrass habitats and provide many ecological services. Further information is needed about their long‐ and short‐term response to habitat fragmentation and loss. Shrimp specimens were sampled from coastal seagrasses: latitudes 9°–27° S (Torres Strait to Moreton Bay, Queensland, Australia) and longitudes 141°–153° E (Weipa to Moreton Bay, Queensland, Australia). The seagrass shrimp Phycomenes zostericola (Caridea: Decapoda) underwent phylogeographic analysis using mitochondrial and nuclear sequence data. Lineage relationships were investigated and two deeply divergent sympatric lineages of P. zostericola were discovered in northern samples. The two lineages display vastly different demographic histories in spite of similar overall phylogeographic patterns. The two lineages appear to be in secondary contact with each other, detailing independent histories of sea level change, long distance colonisation and habitat fragmentation. Their regional structure is evidence that the potential for dispersal is only realised under specific environmental conditions. Nuclear data, used to determine reproductive status between lineages, instead displayed a non‐random latitudinal geographic distribution suggesting directional selection, possibly in response to ocean temperatures. The differences between the two deeply divergent lineages highlight the importance of understanding variability among cryptic taxa and their response to habitat change.     

A space–time parallel framework for fine-scale visualization of pollen levels across the Eastern United States

ABSTRACT

Allergic rhinitis (hay fever) resulting from seasonal pollen affects 15–30% of the population in the United States, and can exacerbate several related conditions, including asthma, atopic eczema, and allergic conjunctivitis. Timely monitoring, accurate prediction, and visualization of pollen levels are critical for public health prevention purposes, such as limiting outdoor exposure or physical activity. The low density of pollen detecting stations and complex movement of pollen represent a challenge for accurate prediction and modeling. In this paper, we reconstruct the dynamics of pollen variation across the Eastern United States for 2016 using space–time interpolation. Pollen levels were extracted according to a stratified spatial sampling design, augmented by additional samples in densely populated areas. These measurements were then used to estimate the space–time cross-correlation, inferring optimal spatial and temporal ranges to calibrate the space–time interpolation. Given the computational requirements of the interpolation algorithm, we implement a spatiotemporal domain decomposition algorithm, and use parallel computing to reduce the computational burden. We visualize our results in a 3D environment to identify the seasonal dynamics of pollen levels. Our approach is also portable to analyze other large space–time explicit datasets, such as air pollution, ash clouds, and precipitation.     

Microstructures of phosphatic porcelain from sintering to vitrification: Evidence from sherds excavated in Charleston,South Carolina

Eight phosphatic porcelain sherds recovered from various historical sites in Charleston were analyzed by electron microprobe. Some sherds contain sulfur (2.3–3.1wt.% SO₃); others contain only traces of this component. The analytical data suggest that the sulfurous sherds are Bow porcelain (London, Bowcock period, ca. 1755–1769). The origin(s) of the low‐S samples remains unidentified; one compositionally resembles “gold‐anchor period” (phosphatic) Chelsea porcelain (London, ca. 1756–1769) but its decoration is inconsistent with known wares produced by this factory during that era. The degree of vitrification is highly variable, particularly among the SO₃‐poor samples. The melt phase is strongly enriched in incompatible elements (Ti, Fe, Na, K). The phosphate phase [calcined bone ash (hydroxyapatite)] in poorly vitrified samples hosts minute melt blebs, but remains porous. With increasing vitrification, these melt blebs increase in size and begin to coalesce, ultimately forming ameboid patches up to ∼10 μm in diameter. In the most vitrified samples, the coalesced melt “leaks” into the matrix, leaving behind a phosphate phase that lacks pores and melt and has a lower CaO/P₂O₅ ratio (=2.7, molecular proportions) than either hydroxyapatite (3.3) or β‐whitlockite (3.0). The two varieties of phosphate occur in some poorly vitrified samples, suggesting the recycling of high‐fired wasters (as “grog”) in their ceramic pastes. Melt compositions vary with contiguous mineralogy, accounting for their divergence from the ternary eutectic in the Ca₃(PO₄)₂‐CaAl₂Si₂O₈‐SiO₂ system. The resorption of phosphate by the matrix melt virtually precludes recognition of anorthite formed by the “non‐phosphate glass equation.” © 2011 Wiley Periodicals, Inc.