Pattern formation and spatial solitons in bistable liquid-crystal microcavities

We report on spatial pattern formation, and appearances of 'optical bullet holes' in single-mode microcavities that are filled with liquid-crystals, when pumped above the cavity resonance frequency. These phenomena only occur beyond the bistability threshold. ��2002 Optical Society of America.

Distribution patterns of chlorophyll a in spring and autumn in association with hydrological features in the southern Yellow Sea and northern East China Sea

Two field studies were conducted to measure pigments in the Southern Yellow Sea (SYS) and the northern East China Sea (NECS) in April (spring) and September (autumn) to evaluate the distribution pattern of phytoplankton stock (Chl a concentration) and the impact of hydrological features such as water mass, mixing and tidal front on these patterns. The results indicated that the Chl a concentration was 2.43 +/- 2.64 (Mean +/- SD) mg m(-3) in April (range, 0.35 to 17.02 mg m(-3)) and 1.75 +/- 3.10 mg m(-3) in September (from 0.07 to 36.54 mg m(-3)) in 2003. Additionally, four areas with higher Chl a concentrations were observed in the surface water in April, while two were observed in September, and these areas were located within or near the point at which different water masses converged (temperature front area). The distribution pattern of Chl a was generally consistent between onshore and offshore stations at different depths in April and September. Specifically, higher Chl a concentrations were observed along the coastal line in September, which consisted of a mixing area and a tidal front area, although the distributional pattern of Chl a concentrations varied along transects in April. The maximum Chl a concentration at each station was observed in the surface and subsurface layer (0-10 m) for onshore stations and the thermocline layer (10-30 m) for offshore stations in September, while the greatest concentrations were generally observed in surface and subsurface water (0-10 m) in April. The formation of the Chl a distributional pattern in the SYS and NECS and its relationship with possible influencing factors is also discussed. Although physical forces had a close relationship with Chl a distribution, more data are required to clearly and comprehensively elucidate the spatial pattern dynamics of Chl a in the SYS and NECS.

The Spatial Signature of Biotic Interactions of a Clonal and a Non-clonal Palmetto in a Subtropical Plant Community

Spatial analyses of plant-distribution patterns can provide inferences about intra- and interspecific biotic interactions. Yet, such analyses are rare for clonal plants because effective tools (i.e., molecular markers) needed to map naturally occurring clonal individuals have only become available recently. Clonal plants are unique in that a single genotype has a potential to spatially place new individuals (i.e., ramets) in response to intra- and interspecific biotic interactions. Laboratory and greenhouse studies suggest that some clonal plants can avoid intra-genet, inter-genet, and inter-specific competition via rootplacement patterns. An intriguing and yet to be explored question is whether a spatial signature of such multi-level biotic interactions can be detected in natural plant communities. The facultatively clonal Serenoa repens and non-clonal Sabal etonia are ecologically similar and co-dominant palmettos that sympatrically occur in the Florida peninsula. We used amplified fragment length polymorphisms (AFLPs) to identify Serenoa genets and also to assign field-unidentifiable small individuals as Sabal seedlings, Serenoa seedlings, or Serenoa vegetative sprouts. Then, we conducted univariate and bivariate multi-distance spatial analyses to examine the spatial interactions of Serenoa (n=271) and Sabal (n=137) within a 20x20 m grid at three levels, intragenet, intergenet and interspecific. We found that spatial interactions were not random at all three levels of biotic interactions. Serenoa genets appear to spatially avoid self-competition as well as intergenet competition. Furthermore, Serenoa and Sabal were spatially negatively associated with each other. However, this negative association pattern was also evident in a spatial comparison between non-clonal Serenoa and Sabal, suggesting that Serenoa genets��� spatial avoidance of Sabal through placement of new ramets is not the explanation of the interspecific-level negative spatial pattern. Our results emphasize the importance of investigating spatial signatures of biotic as well as abiotic interactions at multiple levels in understanding spatial distribution patterns of clonal plants in natural plant communities.

GIS technologies and spatial organization patterns among hunter-gatherers: an archaeological case study from Southern Patagonia (southern South America)

This paper discusses some aspects of hunter-gatherer spatial organization in southern South Patagonia, in later times to 10,000 cal yr BP. Various methods of spatial analysis, elaborated with a Geographic Information System (GIS) were applied to the distributional pattern of archaeological sites with radiocarbon dates. The shift in the distributional pattern of chronological information was assessed in conjunction with other lines of evidence within a biogeographic framework. Accordingly, the varying degrees of occupation and integration of coastal and interior spaces in human spatial organization are explained in association with the adaptive strategies hunter-gatherers have used over time. Both are part of the same human response to changes in risk and uncertainty variability in the region in terms of resource availability and environmental dynamics.

Determination of biodiversity and spatial and temporal distribution pattern of demersal fishes in the Oman Sea

In this project, have been studied to determine the appropriate model to spatial, temporal and diversity of demersal fishes in the Sea of Oman, including Trichiuridae, Nemipteridae, Haemulidae, Arridae, Synodontidae, Batoidfishes, Carangidae, Scianidae, Carchariniformes and Serranidae. This research became operational from catch data during 2003 to 2013 (in 2007, due to the lack of ship failed). Processing and calculations was evaluated by using the software Excel, SPSS, Arc GIS and table curve 3D highest biomass and abundance was showed in strata A and C and 10-30 m depth layers was showed the best condition biomass. In other words, highest biomass was showed in the eastern region in the Oman Sea than the central and western regions. Batoidfishes and Trichiuridae had the highest biomass .Depth factors was showed a significant correlation with the biomass. Scianidae, Serranidae and Haemulidae were showed a large decline. Synodontidae was showed a very large increase. The largest of Shannon index belong to central and western region of the Oman Sea. The highest Shannon index was showed 10-20 and 50-100 m, respectively. The Distribution maps based on the biomass was analyzed by using Arc GIS software. So that were identified in the first time in a ten-year period and carefully catch stations any economic of aquatic group. In conclusion, the depth can be found in the pattern of distribution, abundance and diversity of fish from away the beach so that follow specific pattern.

Exploratory spatial analysis of social and environmental factors associated with the incidence of Ross River Virus in Brisbane, Australia

We used geographic information systems and a spatial analysis approach to explore the pattern of Ross River virus (RRV) incidence in Brisbane, Australia. Climate, vegetation and socioeconomic data in 2001 were obtained from the Australian Bureau of Meteorology, the Brisbane City Council and the Australian Bureau of Statistics, respectively. Information on the RRV cases was obtained from the Queensland Department of Health. Spatial and multiple negative binomial regression models were used to identify the socioeconomic and environmental determinants of RRV transmission. The results show that RRV activity was primarily concentrated in the northeastern, northwestern, and southeastern regions in Brisbane. Multiple negative binomial regression models showed that the spatial pattern of RRV disease in Brisbane seemed to be determined by a combination of local ecologic, socioeconomic, and environmental factors.

Spatial and temporal analysis of Barmah Forest virus disease in Queensland, Australia

Barmah Forest virus (BFV) disease is one of the most widespread mosquito-borne diseases in Australia. The number of outbreaks and the incidence rate of BFV in Australia have attracted growing concerns about the spatio-temporal complexity and underlying risk factors of BFV disease. A large number of notifications has been recorded continuously in Queensland since 1992. Yet, little is known about the spatial and temporal characteristics of the disease. I aim to use notification data to better understand the effects of climatic, demographic, socio-economic and ecological risk factors on the spatial epidemiology of BFV disease transmission, develop predictive risk models and forecast future disease risks under climate change scenarios. Computerised data files of daily notifications of BFV disease and climatic variables in Queensland during 1992-2008 were obtained from Queensland Health and Australian Bureau of Meteorology, respectively. Projections on climate data for years 2025, 2050 and 2100 were obtained from Council of Scientific Industrial Research Organisation. Data on socio-economic, demographic and ecological factors were also obtained from relevant government departments as follows: 1) socio-economic and demographic data from Australian Bureau of Statistics; 2) wetlands data from Department of Environment and Resource Management and 3) tidal readings from Queensland Department of Transport and Main roads. Disease notifications were geocoded and spatial and temporal patterns of disease were investigated using geostatistics. Visualisation of BFV disease incidence rates through mapping reveals the presence of substantial spatio-temporal variation at statistical local areas (SLA) over time. Results reveal high incidence rates of BFV disease along coastal areas compared to the whole area of Queensland. A Mantel-Haenszel Chi-square analysis for trend reveals a statistically significant relationship between BFV disease incidence rates and age groups (����2 = 7587, p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the state. A cluster analysis was used to detect the hot spots/clusters of BFV disease at a SLA level. Most likely spatial and space-time clusters are detected at the same locations across coastal Queensland (p<0.05). The study demonstrates heterogeneity of disease risk at a SLA level and reveals the spatial and temporal clustering of BFV disease in Queensland. Discriminant analysis was employed to establish a link between wetland classes, climate zones and BFV disease. This is because the importance of wetlands in the transmission of BFV disease remains unclear. The multivariable discriminant modelling analyses demonstrate that wetland types of saline 1, riverine and saline tidal influence were the most significant risk factors for BFV disease in all climate and buffer zones, while lacustrine, palustrine, estuarine and saline 2 and saline 3 wetlands were less important. The model accuracies were 76%, 98% and 100% for BFV risk in subtropical, tropical and temperate climate zones, respectively. This study demonstrates that BFV disease risk varied with wetland class and climate zone. The study suggests that wetlands may act as potential breeding habitats for BFV vectors. Multivariable spatial regression models were applied to assess the impact of spatial climatic, socio-economic and tidal factors on the BFV disease in Queensland. Spatial regression models were developed to account for spatial effects. Spatial regression models generated superior estimates over a traditional regression model. In the spatial regression models, BFV disease incidence shows an inverse relationship with minimum temperature, low tide and distance to coast, and positive relationship with rainfall in coastal areas whereas in whole Queensland the disease shows an inverse relationship with minimum temperature and high tide and positive relationship with rainfall. This study determines the most significant spatial risk factors for BFV disease across Queensland. Empirical models were developed to forecast the future risk of BFV disease outbreaks in coastal Queensland using existing climatic, socio-economic and tidal conditions under climate change scenarios. Logistic regression models were developed using BFV disease outbreak data for the existing period (2000-2008). The most parsimonious model had high sensitivity, specificity and accuracy and this model was used to estimate and forecast BFV disease outbreaks for years 2025, 2050 and 2100 under climate change scenarios for Australia. Important contributions arising from this research are that: (i) it is innovative to identify high-risk coastal areas by creating buffers based on grid-centroid and the use of fine-grained spatial units, i.e., mesh blocks; (ii) a spatial regression method was used to account for spatial dependence and heterogeneity of data in the study area; (iii) it determined a range of potential spatial risk factors for BFV disease; and (iv) it predicted the future risk of BFV disease outbreaks under climate change scenarios in Queensland, Australia. In conclusion, the thesis demonstrates that the distribution of BFV disease exhibits a distinct spatial and temporal variation. Such variation is influenced by a range of spatial risk factors including climatic, demographic, socio-economic, ecological and tidal variables. The thesis demonstrates that spatial regression method can be applied to better understand the transmission dynamics of BFV disease and its risk factors. The research findings show that disease notification data can be integrated with multi-factorial risk factor data to develop build-up models and forecast future potential disease risks under climate change scenarios. This thesis may have implications in BFV disease control and prevention programs in Queensland.

Spatial variation of particle number concentration in school microscale environments and its impact on exposure assessment

It has not yet been established whether the spatial variation of particle number concentration (PNC) within a microscale environment can have an effect on exposure estimation results. In general, the degree of spatial variation within microscale environments remains unclear, since previous studies have only focused on spatial variation within macroscale environments. The aims of this study were to determine the spatial variation of PNC within microscale school environments, in order to assess the importance of the number of monitoring sites on exposure estimation. Furthermore, this paper aims to identify which parameters have the largest influence on spatial variation, as well as the relationship between those parameters and spatial variation. Air quality measurements were conducted for two consecutive weeks at each of the 25 schools across Brisbane, Australia. PNC was measured at three sites within the grounds of each school, along with the measurement of meteorological and several other air quality parameters. Traffic density was recorded for the busiest road adjacent to the school. Spatial variation at each school was quantified using coefficient of variation (CV). The portion of CV associated with instrument uncertainty was found to be 0.3 and therefore, CV was corrected so that only non-instrument uncertainty was analysed in the data. The median corrected CV (CVc) ranged from 0 to 0.35 across the schools, with 12 schools found to exhibit spatial variation. The study determined the number of required monitoring sites at schools with spatial variability and tested the deviation in exposure estimation arising from using only a single site. Nine schools required two measurement sites and three schools required three sites. Overall, the deviation in exposure estimation from using only one monitoring site was as much as one order of magnitude. The study also tested the association of spatial variation with wind speed/direction and traffic density, using partial correlation coefficients to identify sources of variation and non-parametric function estimation to quantify the level of variability. Traffic density and road to school wind direction were found to have a positive effect on CVc, and therefore, also on spatial variation. Wind speed was found to have a decreasing effect on spatial variation when it exceeded a threshold of 1.5 (m/s), while it had no effect below this threshold. Traffic density had a positive effect on spatial variation and its effect increased until it reached a density of 70 vehicles per five minutes, at which point its effect plateaued and did not increase further as a result of increasing traffic density.

Valence and spatial explanations for voting in the 2013 Australian election

This paper examines the 2013 Australian federal election to test two competing models of vote choice: spatial politics and valence issues. Using data from the 2013 Australian Election Study, the analysis finds that spatial politics (measured by party identification and self-placement on the left-right spectrum) and valence issues both have significant effects on vote choice. However, spatial measures are more important than valence issues in explaining vote choice, in contrast with recent studies from Britain, Canada and the United States. Explanations for these differences are speculative, but may relate to Australia���s stable party and electoral system, including compulsory voting and the frequency of elections. The consequently high information burden faced by Australian voters may lead to a greater reliance on spatial heuristics than is found elsewhere.

Influence of spatial variability of permeability property on steady state seepage flow and slope stability analysis

In recent years, spatial variability modeling of soil parameters using random field theory has gained distinct importance in geotechnical analysis. In the present Study, commercially available finite difference numerical code FLAC 5.0 is used for modeling the permeability parameter as spatially correlated log-normally distributed random variable and its influence on the steady state seepage flow and on the slope stability analysis are studied. Considering the case of a 5.0 m high cohesive-frictional soil slope of 30 degrees, a range of coefficients of variation (CoV%) from 60 to 90% in the permeability Values, and taking different values of correlation distance in the range of 0.5-15 m, parametric studies, using Monte Carlo simulations, are performed to study the following three aspects, i.e., (i) effect ostochastic soil permeability on the statistics of seepage flow in comparison to the analytic (Dupuit's) solution available for the uniformly constant permeability property; (ii) strain and deformation pattern, and (iii) stability of the given slope assessed in terms of factor of safety (FS). The results obtained in this study are useful to understand the role of permeability variations in slope stability analysis under different slope conditions and material properties. (C) 2009 Elsevier B.V. All rights reserved.

Spatial Decision Support System for Assessing Micro, Mini and Small Hydel Potential

This study describes the design and implementation of DSS for assessment of Mini, Micro and Small Schemes. The design links a set of modelling, manipulation, spatial analyses and display tools to a structured database that has the facility to store both observed and simulated data. The main hypothesis is that this tool can be used to form a core of practical methodology that will result in more resilient in less time and can be used by decision-making bodies to assess the impacts of various scenarios (e.g.: changes in land use pattern) and to review, cost and benefits of decisions to be made. It also offers means of entering, accessing and interpreting the information for the purpose of sound decision making. Thus, the overall objective of this DSS is the development of set of tools aimed at transforming data into information and aid decisions at different scales.

Small-scale spatial and temporal variability in growth and mortality of fish larvae in the subtropical northcentral Gulf of Mexico: implications for assessing recruitment success

Extensive plankton collections were taken during seven September cruises (1990���93) along the inner continental shelf of the northcentral Gulf of Mexico (GOM). Despite the high productivity and availability of food during these cruises, significant small-scale spatial variability was found in larval growth rates for both Atlantic bumper (Chloroscombrus chrysurus, Carangidae) and vermilion snapper (Rhomboplites aurorubens, Lutjanidae). The observed variability in larval growth rates was not correlated with changes in water temperature or associated with conspicuous hydrographic features and suggested the existence of less-recognizable regions where conditions for growth vary. Cruise estimates of mortality coefficients (Z) for larval Atlantic bumper (n=32,241 larvae from six cruises) and vermilion snapper (n= 2581 larvae from four cruises) ranged from 0.20 to 0.37 and 0.19 to 0.29, respectively. Even in a subtropical climate like the GOM, where larval-stage durations may be as short as two weeks, observed variability in growth rates, particularly when combined with small changes in mortality rates, can cause order-of-magnitude differences in cumulative larval survival. To what extent the observed differences in growth rates at small spatial scales are fine-scale ���noise��� that ultimately is smoothed by larger-scale processes is not known. Future research is needed to further characterize the small-scale variability in growth rates of larvae, particularly with regard to microzooplankton patchiness and the temporal and spatial pattern of potential predators. Small-scale spatial variability in larval growth rates may in fact be the norm, and understanding the implications of this subtle mosaic may help us to better evaluate our ability to partition the causes of recruitment variability.

STUDY ON THE SPATIAL PATTERNS OF LAND-USE CHANGE AND ANALYSES OF DRIVING FORCES IN NORTHEASTERN CHINA DURING 1990-2000

Land-use change is an important aspect of global environment change. It is, in a sense, the direct result of human activities influencing our physical environment. Supported by the dynamic serving system of national resources, including both the environment database and GIS technology, this paper analyzed the land-use change in northeastern China in the past ten years (1990 - 2000). It divides northeastern China into five land-use zones based on the dynamic degree (DD) of land-use: woodland/grassland - arable land conversion zone, dry land - paddy field conversion zone, urban expansion zone, interlocked zone of farming and pasturing, and reclamation and abandoned zone. In the past ten years, land-use change of northeastern China can be generalized as follows: increase of cropland area was obvious, paddy field and dry land increased by 74. 9 and 276. 0 thousand ha respectively; urban area expanded rapidly, area of town and rural residence increased by 76. 8 thousand ha; area of forest and grassland decreased sharply with the amount of 1399. 0 and 1521. 3 thousand ha respectively; area of water body and unused land increased by 148. 4 and 513. 9 thousand ha respectively. Besides a comprehensive analysis of the spatial patterns of land use, this paper also discusses the driving forces in each land-use dynamic zones. The study shows that some key biophysical factors affect conspicuously the conversion of different land- use types. In this paper, the relationships between land- use conversion and DEM, accnmlated temperature(&gt;= 10 degrees C) and precipitation were analysed and represented. We conclude that the land- use changes in northeast China resulted from the change of macro social and economic factors and local physical elements. Rapid population growth and management changes, in some sense, can explain the shaping of woodland/grassland - cropland conversion zone. The conversion from dry land to paddy field in the dry land - paddy field conversion zone, apart from the physical elements change promoting the expansion of paddy field, results from two reasons: one is that the implementation of market-economy in China has given farmers the right to decide what they plant and how they plant their crops, the other factor is originated partially from the change of dietary habit with the social and economic development. The conversion from paddy field to dry land is caused primarily by the shortfall of irrigation water, which in turn is caused by poor water allocation managed by local governments. The shaping of the reclamation and abandoned zone is partially due to the lack of environment protection consciousness among pioneer settlers. The reason for the conversion from grassland to cropland is the relatively higher profits of fanning than that of pasturing in the interlocked zone of farming and pasturing. In northeastern China, the rapid expansion of built-up areas results from two factors: the first is its small number of towns; the second comes from the huge potential for expansion of existing towns and cities. It is noticeable that urban expansion in the northeastern China is characterized by gentle topographic relief and low population density. Physiognomy, transportation and economy exert great influences on the urban expansion.

The regional types of China's floating population: Identification methods and spatial patterns

With the rapid increase of the number and influence of floating population in China, it is urgently needed to understand the regional types of China's floating population and their spatial characteristics. After reviewing the current methods for identifying regional types of floating population, this paper puts forward a new composite-index identification method and its modification version which is consisted of two indexes of the net migration rate and gross migration rate. Then, the traditional single-index and the new composite-index identification methods are empirically tested to explore their spatial patterns and characteristics by using China's 2000 census data at county level. The results show: (1) The composite-index identification method is much better than traditional single-index method because it can measure the migration direction and scale of floating simultaneously, and in particular it can identify the unique regional types of floating population with large scale of immigration and emigration. (2) The modified composite-index identification method, by using the share of a region's certain type of floating population to the total in China as weights, can effectively correct the over- or under-estimated errors due to the rather large or small total population of a region. (3) The spatial patterns of different regional types of China's floating population are closely related to the regional differentiation of their natural environment, population density and socio-economic development level. The three active regional types of floating population are mainly located in the eastern part of China with lower elevation, more than 800 mm precipitation, rather higher population densities and economic development levels.

Testing the possible negative association of type 1 diabetes and atopic disease by analysis of the interleukin 4 receptor gene

Variations in the interleukin 4 receptor A (IL4RA) gene have been reported to be associated with atopy, asthma, and allergy, which may occur less frequently in subjects with type 1 diabetes (T1D). Since atopy shows a humoral immune reactivity pattern, and T1D results from a cellular (T lymphocyte) response, we hypothesised that alleles predisposing to atopy could be protective for T1D and transmitted less often than the expected 50% from heterozygous parents to offspring with T1D. We genotyped seven exonic single nucleotide polymorphisms (SNPs) and the -3223 C&gt;T SNP in the putative promoter region of IL4RA in up to 3475 T1D families, including 1244 Finnish T1D families. Only the -3223 C&gt;T SNP showed evidence of negative association (P=0.014). There was some evidence for an interaction between -3233 C&gt;T and the T1D locus IDDM2 in the insulin gene region (P=0.001 in the combined and P=0.02 in the Finnish data set). We, therefore, cannot rule out a genetic effect of IL4RA in T1D, but it is not a major one.