Spatial and temporal patterns in Australian wheat yield and their relationship with ENSO

Spatial and temporal variability in wheat production in Australia is dominated by rainfall occurrence. The length of historical production records is inadequate, however, to analyse spatial and temporal patterns conclusively. In this study we used modelling and simulation to identify key spatial patterns in Australian wheat yield, identify groups of years in the historical record in which spatial patterns were similar, and examine association of those wheat yield year groups with indicators of the El Nino Southern Oscillation (ENSO). A simple stress index model was trained on 19 years of Australian Bureau of Statistics shire yield data (1975-93). The model was then used to simulate shire yield from 1901 to 1999 for all wheat-producing shires. Principal components analysis was used to determine the dominating spatial relationships in wheat yield among shires. Six major components of spatial variability were found. Five of these represented near spatially independent zones across the Australian wheatbelt that demonstrated coherent temporal (annual) variability in wheat yield. A second orthogonal component was required to explain the temporal variation in New South Wales. The principal component scores were used to identify high- and low-yielding years in each zone. Year type groupings identified in this way were tested for association with indicators of ENSO. Significant associations were found for all zones in the Australian wheatbelt. Associations were as strong or stronger when ENSO indicators preceding the wheat season (April-May phases of the Southern Oscillation Index) were used rather than indicators based on classification during the wheat season. Although this association suggests an obvious role for seasonal climate forecasting in national wheat crop forecasting, the discriminatory power of the ENSO indicators, although significant, was not strong. By examining the historical years forming the wheat yield analog sets within each zone, it may be possible to identify novel climate system or ocean-atmosphere features that may be causal and, hence, most useful in improving seasonal forecasting schemes.

Spatial distribution of vectors of Ross River virus and Barmah Forest virus on Russell Island, Moreton Bay, Queensland

We used a network of 20 carbon dioxide- and octenol-supplemented light traps to sample adult mosquitoes throughout Russell Island in southern Moreton Bay, south-east Queensland. Between February and April 2001, an estimated 1365 564 adult female mosquitoes were collected. In contrast to an average catch of 9754 female mosquitoes per trap night on Russell Island, reference traps set on Macleay Island and on the mainland returned average catches of 3172 and 222, respectively. On Russell Island, Ochlerotatus vigilax (Skuse), Coquillettidia linealis (Skuse), Culex annulirostris Skuse and Verrallina funerea (Theobald), known or suspected vectors of Ross River (RR) and/or Barmah Forest (BF) viruses, comprised 89.6% of the 25 taxa collected. When the spatial distributions of the above species were mapped and analysed using local spatial statistics, all were found to be present in highest numbers towards the southern end of the island during most of the 7 weeks. This indicated the presence of more suitable adult harbourage sites and/or suboptimal larval control efficacy. As immature stages and the breeding habitat of Cq. linealis are as yet undescribed, this species in particular presents a considerable impediment to proposed development scenarios. The method presented here of mapping the numbers of mosquitoes throughout a local government area allows specific areas that have high vector numbers to be defined.

Temporal and spatial expression of fibroblast growth factor receptor 4 isoforms in murine tissues

Fibroblast growth factor receptors (FGFRs) undergo highly regulated spatial and temporal changes of expression during development. This study describes the use of quantitative reverse transcriptase-polymerase chain reaction and immunochemistry to assess the changes in expression of FGFR4 as compared to its FGFR4-17a and -17b isoforms in mouse tissues, from early embryogenesis through to adulthood. Compared to FGFR4, the expression of the isoforms is more restricted at all developmental stages tested. The reverse transcriptase-polymerase chain reaction demonstrated that FGFR4 is expressed in more tissue types than either of its isoforms: it was found predominantly in lung, liver, brain, skeletal muscle and kidney, whereas the FGFR4-17a form was detected in lung and skeletal muscle, and the FGFR4-17b form only in lung, liver, skeletal muscle and kidney. Immunohistochemistry confirmed strong FGFR4-17b expression in the postnatal lung. When combined, the results suggest that FGFR4 variants play important roles particularly in lung and skeletal muscle development.

Spatial and temporal changes in multiple hormone groups during lateral bud release shortly following apex decapitation of chickpea (Cicer arietinum) seedlings

Although the co-ordination of promotive root-sourced cytokinin (CK) and inhibitory shoot apex-sourced auxin (IAA) is central to all current models on lateral bud dormancy release, control by those hormones alone has appeared inadequate in many studies. Thus it was hypothesized that the IAA : CK model is the central control but that it must be considered within the relevant timeframe leading to lateral bud release and against a backdrop of interactions with other hormone groups. Therefore, IAA and a wide survey of cytokinins (CKs), were examined along with abscisic acid (ABA) and polyamines (PAs) in released buds, tissue surrounding buds and xylem sap at 1 and 4 h after apex removal, when lateral buds of chickpea are known to break dormancy. Three potential lateral bud growth inhibitors, IAA, ABA and cis-zeatin 9-riboside (ZR), declined sharply in the released buds and xylem following decapitation. This is in contrast to potential dormancy breaking CKs like trans-ZR and trans-zeantin 9-riboside 5'phosphate (ZRMP), which represented the strongest correlative changes by increasing 3.5-fold in xylem sap and 22-fold in buds. PAs had not changed significantly in buds or other tissues after 4 h, so they were not directly involved in the breaking of bud dormancy. Results from the xylem and surrounding tissues indicated that bud CK increases resulted from a combination synthesis in the bud and selective loading of CK nucleotides into the xylem from the root.

Direct visualization of Ras proteins in spatially distinct cell surface microdomains

Localization of signaling complexes to specific micro-domains coordinates signal transduction at the plasma membrane. Using immunogold electron microscopy of plasma membrane sheets coupled with spatial point pattern analysis, we have visualized morphologically featureless microdomains including lipid rafts, in situ and at high resolution. We find that an inner-plasma membrane lipid raft marker displays cholesterol-dependent clustering in microdomains with a mean diameter of 44 nm that occupy 35% of the cell surface. Cross-linking an outer-leaflet raft protein results in the redistribution of inner leaflet rafts, but they retain their modular structure. Analysis of Ras microlocalization shows that inactive H-ras is distributed between lipid rafts and a cholesterol-independent micro-domain. Conversely, activated H-ras and K-ras reside predominantly in nonoverlapping, cholesterol-independent microdomains. Galectin-1 stabilizes the association of activated H-ras with these nonraft microdomains, whereas K-ras clustering is supported by farnesylation, but not geranylgeranylation. These results illustrate that the inner plasma membrane comprises a complex mosaic of discrete microdomains. Differential spatial localization within this framework can likely account for the distinct signal outputs from the highly homologous Ras proteins.

Model-based clustering in gene expression microarrays: An application to breast cancer data

In microarray studies, the application of clustering techniques is often used to derive meaningful insights into the data. In the past, hierarchical methods have been the primary clustering tool employed to perform this task. The hierarchical algorithms have been mainly applied heuristically to these cluster analysis problems. Further, a major limitation of these methods is their inability to determine the number of clusters. Thus there is a need for a model-based approach to these. clustering problems. To this end, McLachlan et al. [7] developed a mixture model-based algorithm (EMMIX-GENE) for the clustering of tissue samples. To further investigate the EMMIX-GENE procedure as a model-based -approach, we present a case study involving the application of EMMIX-GENE to the breast cancer data as studied recently in van 't Veer et al. [10]. Our analysis considers the problem of clustering the tissue samples on the basis of the genes which is a non-standard problem because the number of genes greatly exceed the number of tissue samples. We demonstrate how EMMIX-GENE can be useful in reducing the initial set of genes down to a more computationally manageable size. The results from this analysis also emphasise the difficulty associated with the task of separating two tissue groups on the basis of a particular subset of genes. These results also shed light on why supervised methods have such a high misallocation error rate for the breast cancer data.

Electropalatographic assessment of tongue-to-palate contacts exhibited in dysarthria following traumatic brain injury: Spatial characteristics

Consonant imprecision has been reported to be a common feature of the dysarthric speech disturbances exhibited by individuals who have sustained a traumatic brain injury (TBI). Inaccurate tongue placements against the hard palate during consonant articulation may be one factor underlying the imprecision. To investigate this hypothesis, electropalatography (EPG) was used to assess the spatial characteristics of the tongue-to-palate contacts exhibited by three males (aged 23-29 years) with dysarthria following severe TBI. Five nonneurologically impaired adults served as control subjects. Twelve single-syllable words of CV or CVC construction (where initial C = /t, d, S, z, k, g/, V=/i, a/) were read aloud three times by each subject while wearing an EPG palate. Spatial characteristics were analyzed in terms of the location, pattern, and amount of tongue-to-palate contact at the frame of maximum contact during production of each consonant. The results revealed that for the majority of consonants, the patterns and locations of contacts exhibited by the TBI subjects were consistent with the contacts generated by the group of control subjects. One notable exception was one subject's production of the alveolar fricatives in which complete closure across the palate was demonstrated, rather than the characteristic groove configuration. Major discrepancies were also noted in relation to the amount of tongue-to-palate contact exhibited, with two TBI subjects consistently demonstrating increased contacts compared to the control subjects. The implications of these findings for the development of treatment programs for dysarthric speech disorders subsequent to TBI are highlighted.

Spatial variability in nutritional status of arabic coffee based on dris index

The combined use of precision agriculture and the Diagnosis and Recommendation Integrated System (DRIS) allows the spatial monitoring of coffee nutrient balance to provide more balanced and cost-effective fertilizer recommendations. The objective of this work was to evaluate the spatial variability in the nutritional status of two coffee varieties using the Mean Nutritional Balance Index (NBIm) and its relationship with their respective yields. The experiment was conducted in eastern Minas Gerais in two areas, one planted with variety Catucaí and another with variety Catuaí. The NBIm of the two varieties and their yields were analyzed through geostatistics and, based on the models and parameters of the variograms, were interpolated to obtain their spatial distribution in the studied areas. Variety Catucai, with grater spatial variability, was more nutritional unbalanced than variety Catuai, and consequently produced lower yields. Excess of Fe and Mn makes these elements limiting yield factors.

Spatial variability of particle size fractions of an Oxisol cultivated with conilon coffee

Information on the spatial distribution of particle size fractions is essential for use planning and management of soils. The aim of this work to was to study the spatial variability of particle size fractions of a Typic Hapludox cultivated with conilon coffee. The soil samples were collected at depths of 0-0.20 and 0.20-0.40 m in the coffee canopy projection, totaling 109 georeferentiated points. At the depth of 0.2-0.4 m the clay fraction showed average value significantly higher, while the sand fraction showed was higher in the depth of 0-0.20 m. The silt showed no significant difference between the two depths. The particle size fractions showed medium and high spatial variability. The levels of total sand and clay have positive and negative correlation, respectively, with the altitude of the sampling points, indicating the influence of landscape configuration.

Effect of spatial arrangement on the production components and yield of sunflower

ABSTRACT The sunflower plant is an oilseed crop that has aroused a great interest in the Brazilian and international scenery especillay because of the possibility of using its oil for biodiesel production. The objective of this study was to evaluate productivity and yield components of Embrapa 122 sunflower according to the spatial arrangement. Treatments were arranged in 4 x 4 factorial arrangement, which are the four spacings between rows (0.30; 0.50; 0.70 and 0.90 m) and four sowing densities (30,000; 45,000; 60,000 and 75,000 plants ha-1). The experiment was carried out in a complete randomized block design with four replications. The experiments were conducted in the experimental area of the Plant Science Department in Fortaleza, State of Ceará-Brazil and on the Curu Vale Experimental Farm in Pentecoste, State of Ceará-Brazil. Productivity and the following production components were analyzed in the end of the crop cycle: harvested capitula, capitulum diameter, capitulum mass, achene mass per capitulum, mass of 100 achenes, achenes per capitulum, harvest index and oil content in the achenes. The experiments were analyzed jointly in relation to the cropping area and the data submitted to analysis of variance and quantitative factors tested by polynomial regression. The variables, spacing, density and cropping area did not interact with these variables and the spatial arrangement of the plants affected only the components. The cropping area influences the productive behavior of sunflower Embrapa 122. The spatial arrangement of the plants of sunflower of variety Embrapa 122 influences yield components but does not affect productivity.

New p-i-n Si : H imager configuration for spatial resolution improvement

Amorphous glass/ZnO-Al/p(a-Si:H)/i(a-Si:H)/n(a-Si1-xCx:H)/Al imagers with different n-layer resistivities were produced by plasma enhanced chemical vapour deposition technique (PE-CVD). An image is projected onto the sensing element and leads to spatially confined depletion regions that can be readout by scanning the photodiode with a low-power modulated laser beam. The essence of the scheme is the analog readout, and the absence of semiconductor arrays or electrode potential manipulations to transfer the information coming from the transducer. The influence of the intensity of the optical image projected onto the sensor surface is correlated with the sensor output characteristics (sensitivity, linearity blooming, resolution and signal-to-noise ratio) are analysed for different material compositions (0.5 < x < 1). The results show that the responsivity and the spatial resolution are limited by the conductivity of the doped layers. An enhancement of one order of magnitude in the image intensity signal and on the spatial resolution are achieved at 0.2 mW cm(-2) light flux by decreasing the n-layer conductivity by the same amount. A physical model supported by electrical simulation gives insight into the image-sensing technique used.

Incidence rate and spatio-temporal clustering of type 1 diabetes in Santiago, Chile, from 1997 to 1998

OBJECTIVE: To estimate the incidence rate of type 1 diabetes in the urban area of Santiago, Chile, from March 21, 1997 to March 20, 1998, and to assess the spatio-temporal clustering of cases during that period. METHODS: All sixty-one incident cases were located temporally (day of diagnosis) and spatially (place of residence) in the area of study. Knox's method was used to assess spatio-temporal clustering of incident cases. RESULTS: The overall incidence rate of type 1 diabetes was 4.11 cases per 100,000 children aged less than 15 years per year (95% confidence interval: 3.06--5.14). The incidence rate seems to have increased since the last estimate of the incidence calculated for the years 1986--1992 in the metropolitan region of Santiago. Different combinations of space-time intervals have been evaluated to assess spatio-temporal clustering. The smallest p-value was found for the combination of critical distances of 750 meters and 60 days (uncorrected p-value = 0.048). CONCLUSIONS: Although these are preliminary results regarding space-time clustering in Santiago, exploratory analysis of the data method would suggest a possible aggregation of incident cases in space-time coordinates.

Definition of MV Load Diagrams via Weighted Evidence Accumulation Clustering using Subsampling

A definition of medium voltage (MV) load diagrams was made, based on the data base knowledge discovery process. Clustering techniques were used as support for the agents of the electric power retail markets to obtain specific knowledge of their customers’ consumption habits. Each customer class resulting from the clustering operation is represented by its load diagram. The Two-step clustering algorithm and the WEACS approach based on evidence accumulation (EAC) were applied to an electricity consumption data from a utility client’s database in order to form the customer’s classes and to find a set of representative consumption patterns. The WEACS approach is a clustering ensemble combination approach that uses subsampling and that weights differently the partitions in the co-association matrix. As a complementary step to the WEACS approach, all the final data partitions produced by the different variations of the method are combined and the Ward Link algorithm is used to obtain the final data partition. Experiment results showed that WEACS approach led to better accuracy than many other clustering approaches. In this paper the WEACS approach separates better the customer’s population than Two-step clustering algorithm.

Determination of electricity consumers’ load profiles via weighted evidence accumulation clustering using subsampling

With the electricity market liberalization, the distribution and retail companies are looking for better market strategies based on adequate information upon the consumption patterns of its electricity consumers. A fair insight on the consumers’ behavior will permit the definition of specific contract aspects based on the different consumption patterns. In order to form the different consumers’ classes, and find a set of representative consumption patterns we use electricity consumption data from a utility client’s database and two approaches: Two-step clustering algorithm and the WEACS approach based on evidence accumulation (EAC) for combining partitions in a clustering ensemble. While EAC uses a voting mechanism to produce a co-association matrix based on the pairwise associations obtained from N partitions and where each partition has equal weight in the combination process, the WEACS approach uses subsampling and weights differently the partitions. As a complementary step to the WEACS approach, we combine the partitions obtained in the WEACS approach with the ALL clustering ensemble construction method and we use the Ward Link algorithm to obtain the final data partition. The characterization of the obtained consumers’ clusters was performed using the C5.0 classification algorithm. Experiment results showed that the WEACS approach leads to better results than many other clustering approaches.