What defines a geochemical map? Implications for environmental assessment.

The environmental quality of land is often assessed by the calculation of threshold values which aim to differentiate between concentrations of elements based on whether the soils are in residential or industrial sites. In Europe, for example, soil guideline values exist for agricultural and grazing land. A threshold is often set to differentiate between concentrations of the element that naturally occur in the soil and concentrations that result from diffuse anthropogenic sources. Regional geochemistry and, in particular, single component geochemical maps are increasingly being used to determine these baseline environmental assessments. The key question raised in this paper is whether the geochemical map can provide an accurate interpretation on its own. Implicit is the thought that single component geochemical maps represent absolute abundances. However,because of the compositional (closed) nature of the data univariate geochemical maps cannot be compared directly with one another.. As a result, any interpretation based on them is vulnerable to spurious correlation problems. What does this mean for soil geochemistry mapping, baseline quality documentation, soil resource assessment or risk evaluation? Despite the limitation of relative abundances, individual raw geochemical maps are deemed fundamental to several applications of geochemical maps including environmental assessments. However, element toxicity is related to its bioavailable concentration, which is lowered if its source is mixed with another source. Elements interact, for example under reducing conditions with iron oxides, its solid state is lost and arsenic becomes soluble and mobile. Both of these matters may be more adequately dealt with if a single component map is not interpreted in isolation to determine baseline and threshold assessments. A range of alternative compositionally compliant representations based on log-ratio and log-contrast approaches are explored to supplement the classical single component maps for environmental assessment. Case study examples are shown based on the Tellus soil geochemical dataset, covering Northern Ireland and the results of in vitro oral bioaccessibility testing carried out on a sub-set of archived Tellus Survey shallow soils following the Unified BARGE (Bioaccessibility Research Group of Europe).

Praying for Salvation: A Map of Relatedness

This article attempts to push Mauss’ work on the sociality of prayer (1909) to its fullest conclusion by arguing that prayer can be viewed anthropologically as providing a map for social and emotional relatedness. Based on fieldwork among deep-sea fisher families living in Gamrie, North-East Scotland (home to 700 people and six Protestant churches), the author takes as his primary ethnographic departure the ritual of the ‘mid-week prayer meeting’. Among the self-proclaimed ‘fundamentalists’ of Gamrie’s Brethren and Presbyterian churches, attending the prayer meeting means praying for salvation. Yet, contrary to the stereotype of Protestant soteriology as highly individualist, in the context of Gamrie, salvation is not principally focused upon the self, but is instead sought on behalf of the ‘unconverted’ other. Locally, this ‘other’ is made sense of with reference to three different categories of relatedness: the family, the village and the nation. The author’s argument is that each category of relatedness carries with it a different affective quality: anguish for one’s family, resentment toward one’s village, and resignation towards one’s nation. As such, prayers for salvation establish and maintain not only vertical – human-divine – relatedness, but also horizontal relatedness between persons, while also giving them their emotional tenor. In ‘fundamentalist’ Gamrie, these human relationships, and crucially their affective asymmetries, may be mapped, therefore, by treating prayers as social phenomena that seek to engage with a world dichotomised into vice and virtue, rebellion and submission, and, ultimately, damnation and salvation.

Automated retinal image quality assessment on the UK Biobank dataset for epidemiological studies

Morphological changes in the retinal vascular network are associated with future risk of many systemic and vascular diseases. However, uncertainty over the presence and nature of some of these associations exists. Analysis of data from large population based studies will help to resolve these uncertainties. The QUARTZ (QUantitative Analysis of Retinal vessel Topology and siZe) retinal image analysis system allows automated processing of large numbers of retinal images. However, an image quality assessment module is needed to achieve full automation. In this paper, we propose such an algorithm, which uses the segmented vessel map to determine the suitability of retinal images for use in the creation of vessel morphometric data suitable for epidemiological studies. This includes an effective 3-dimensional feature set and support vector machine classification. A random subset of 800 retinal images from UK Biobank (a large prospective study of 500,000 middle aged adults; where 68,151 underwent retinal imaging) was used to examine the performance of the image quality algorithm. The algorithm achieved a sensitivity of 95.33% and a specificity of 91.13% for the detection of inadequate images. The strong performance of this image quality algorithm will make rapid automated analysis of vascular morphometry feasible on the entire UK Biobank dataset (and other large retinal datasets), with minimal operator involvement, and at low cost.

Implementation of a service quality strategy: application to the Algarve hotel industry

Tese dout., Doctor of Philisophy, Sheffield Hallam University, 2001

Groundwater quality, vulnerability and potential assessment in Kobo Valley development project, Ethiopia

This study deals with investigating the groundwater quality for irrigation purpose, the vulnerability of the aquifer system to pollution and also the aquifer potential for sustainable water resources development in Kobo Valley development project. The groundwater quality is evaluated up on predicting the best possible distribution of hydrogeochemicals using geostatistical method and comparing them with the water quality guidelines given for the purpose of irrigation. The hydro geochemical parameters considered are SAR, EC, TDS, Cl-, Na+, Ca++, SO4 2- and HCO3 -. The spatial variability map reveals that these parameters falls under safe, moderate and severe or increasing problems. In order to present it clearly, the aggregated Water Quality Index (WQI) map is constructed using Weighted Arithmetic Mean method. It is found that Kobo-Gerbi sub basin is suffered from bad water quality for the irrigation purpose. Waja Golesha sub-basin has moderate and Hormat Golena is the better sub basin in terms of water quality. The groundwater vulnerability assessment of the study area is made using the GOD rating system. It is found that the whole area is experiencing moderate to high risk of vulnerability and it is a good warning for proper management of the resource. The high risks of vulnerability are noticed in Hormat Golena and Waja Golesha sub basins. The aquifer potential of the study area is obtained using weighted overlay analysis and 73.3% of the total area is a good site for future water well development. The rest 26.7% of the area is not considered as a good site for spotting groundwater wells. Most of this area fall under Kobo-Gerbi sub basin.

Clustering quality and topology preservation in fast learning SOMs

The Self-Organizing Map (SOM) is a popular unsupervised neural network able to provide effective clustering and data visualization for data represented in multidimensional input spaces. In this paper, we describe Fast Learning SOM (FLSOM) which adopts a learning algorithm that improves the performance of the standard SOM with respect to the convergence time in the training phase. We show that FLSOM also improves the quality of the map by providing better clustering quality and topology preservation of multidimensional input data. Several tests have been carried out on different multidimensional datasets, which demonstrate better performances of the algorithm in comparison with the original SOM.

Interpreters’ perception of linguistic and non linguistic factors affecting quality: a survey through the World Wide Web

This paper will present and discuss the results of an empirical study on perception of quality in interpretation carried out on a sample of 286 interpreters across five continents. Since the 1980’s the field of Interpreting Studies has been witnessing an ever growing interest in the issue of quality in interpretation both in academia and in professional circles, but research undertaken so far is surprisingly lacking in methodological rigour. This survey is an attempt to revise previous studies on interpreters’ perception of quality through the implementation of new Information Technology which allowed us to administer a traditional research tool such as a questionnaire, in a highly innovative way; i.e., through the World Wide Web. Using multidimensional scaling, a perceptual map based upon the results of the manner in which interpreters ranked a list of linguistic and nonlinguistic criteria according to their perception of importance in the interpretative process,was devised.

Season changes in water quality and Sargassum biomass in Southwest Australia

Sargassum C. Agardh is one of the most diverse genera of marine macro-algae and commonly inhabits shallow tropical and sub-tropical waters. This study aimed to investigate the effect of seasonality and the associated water quality changes on the distribution, canopy cover, mean thallus length and the biomass of Sargassum beds around Point Peron, Shoalwater Islands Marine Park, Southwest Australia. Samples of Sargassum and seawater were collected every three months from summer 2012 to summer 2014 from four different reef zones. A combination of in situ observations and WorldView-2 satellite remote-sensing images were used to map the spatial distribution of Sargassum beds and other associated benthic habitats. The results demonstrated a strong seasonal variation in the environmental parameters, canopy cover, mean thallus length, and biomass of Sargassum, which were significantly (P < 0.05) influenced by the nutrient concentration (PO43-, NO3-, NH4+) and rainfall. However, no variation in any studied parameter was observed among the four reef zones. The highest Sargassum biomass peaks occurred between late spring and early summer (from September to January). The results provide essential information to guide effective conservation and management, as well as sustainable utilisation of this coastal marine renewable resource.

Road network and GPS tracking with data processing and quality assessment

GPS technology has been embedded into portable, low-cost electronic devices nowadays to track the movements of mobile objects. This implication has greatly impacted the transportation field by creating a novel and rich source of traffic data on the road network. Although the promise offered by GPS devices to overcome problems like underreporting, respondent fatigue, inaccuracies and other human errors in data collection is significant; the technology is still relatively new that it raises many issues for potential users. These issues tend to revolve around the following areas: reliability, data processing and the related application. This thesis aims to study the GPS tracking form the methodological, technical and practical aspects. It first evaluates the reliability of GPS based traffic data based on data from an experiment containing three different traffic modes (car, bike and bus) traveling along the road network. It then outline the general procedure for processing GPS tracking data and discuss related issues that are uncovered by using real-world GPS tracking data of 316 cars. Thirdly, it investigates the influence of road network density in finding optimal location for enhancing travel efficiency and decreasing travel cost. The results show that the geographical positioning is reliable. Velocity is slightly underestimated, whereas altitude measurements are unreliable.Post processing techniques with auxiliary information is found necessary and important when solving the inaccuracy of GPS data. The densities of the road network influence the finding of optimal locations. The influence will stabilize at a certain level and do not deteriorate when the node density is higher.

Soil loss risk and habitat quality in streams of a meso-scale river basin

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Identification of microsatellites markers associated with yield components and quality parameters in sugarcane

Marker assisted selection depends on the identification of tightly linked association between marker and the trait of interest. In the present work, functional (EST-SSRs) and genomic (gSSRs) microsatellite markers were used to detect putative QTLs for sugarcane yield components (stalk number, diameter and height) and as well as for quality parameters (Brix, Pol and fibre) in plant cane. The mapping population (200 individuals) was derived from a bi-parental cross (IACSP95-3018 x IACSP93-3046) from the IAC Sugarcane Breeding Program. As the map is under construction, single marker trait association analysis based on the likelihood ratio test was undertaken to detect the QTLs. Of the 215 single dose markers evaluated (1:1 and 3:1), 90 (42%) were associated with putative QTLs involving 43 microsatellite primers (18 gSSRs and 25 EST-SSRs). For the yield components, 41 marker/trait associations were found: 20 for height, 6 for diameter and 15 for stalk number. An EST-SSRs marker with homology to non-phototropic hypocotyls 4 (NPH4) protein was associated with a putative QTL with positive effect for diameter as also with a negative effect for stalk number. In relation to the quality parameters, 18 marker trait associations were found for Brix, 19 for Pol, and 12 for fibre. For fibre, 58% of the QTLs detected showed a negative effect on this trait. Some makers associated with QTLs with a negative effect for fibre showed a positive effect for Pol, reflecting the negative correlation generally observed between these traits.

Agroclimatic zoning of the state of Minas Gerais for the production of high quality soybean seeds

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Towards a Brazilian radon map: consortium radon Brazil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

QUANTITATIVE TRAIT LOCI FOR AGRONOMIC AND END-USE QUALITY PERFORMANCE AND THE EFFECT OF SOILBORNE WHEAT MOSAIC VIRUS IN A HARD WINTER WHEAT POPULATION IN NEBRASKA

To better understand agronomic and end-use quality in wheat (Triticum aestivum L.) we developed a population containing 154 F6:8 recombinant inbred lines (RILs) from the cross TAM107-R7/Arlin. The parental lines and RILs were phenotyped at six environments in Nebraska and differed for resistance to Wheat soilborne mosaic virus (WSBMV), morphological, agronomic, and end-use quality traits. Additionally, a 2300 cM genome-wide linkage map was created for quantitative trait loci (QTL) analysis. Based on our results across multiple environments, the best RILs could be used for cultivar improvement. The population and marker data are publicly available for interested researchers for future research. The population was used to determine the effect of WSBMV on agronomic and end-use quality and for the mapping of a resistance locus. Results from two infected environments showed that all but two agronomic traits were significantly affected by the disease. Specifically, the disease reduced grain yield by 30% of susceptible RILs and they flowered 5 d later and were 11 cm shorter. End-use quality traits were not negatively affected but flour protein content was increased in susceptible RILs. The resistance locus SbmTmr1 mapped to 27.1 cM near marker wPt-5870 on chromosome 5DL using ELISA data. Finally, we investigated how WSBMV affected QTL detection in the population. QTLs were mapped at two WSBMV infected environments, four uninfected environments, and in the resistant and susceptible RIL subpopulations in the infected environments. Fifty-two significant (LOD≥3) QTLs were mapped in RILs at uninfected environments. Many of the QTLs were pleiotropic or closely linked at 6 chromosomal regions. Forty-seven QTLs were mapped in RILs at WSBMV infected environments. Comparisons between uninfected and infected environments identified 20 common QTLs and 21 environmentally specific QTLs. Finally, 24 QTLs were determined to be affected by WSBMV by comparing the subpopulations in QTL analyses within the same environment. The comparisons were statistically validated using marker by disease interactions. These results showed that QTLs can be affected by WSBMV and careful interpretation of QTL results is needed where biotic stresses are present. Finally, beneficial QTLs not affected by WSBMV or the environment are candidates for marker-assisted selection.

Bayesian space-time data fusion for real-time forecasting and map uncertainty

Environmental computer models are deterministic models devoted to predict several environmental phenomena such as air pollution or meteorological events. Numerical model output is given in terms of averages over grid cells, usually at high spatial and temporal resolution. However, these outputs are often biased with unknown calibration and not equipped with any information about the associated uncertainty. Conversely, data collected at monitoring stations is more accurate since they essentially provide the true levels. Due the leading role played by numerical models, it now important to compare model output with observations. Statistical methods developed to combine numerical model output and station data are usually referred to as data fusion. In this work, we first combine ozone monitoring data with ozone predictions from the Eta-CMAQ air quality model in order to forecast real-time current 8-hour average ozone level defined as the average of the previous four hours, current hour, and predictions for the next three hours. We propose a Bayesian downscaler model based on first differences with a flexible coefficient structure and an efficient computational strategy to fit model parameters. Model validation for the eastern United States shows consequential improvement of our fully inferential approach compared with the current real-time forecasting system. Furthermore, we consider the introduction of temperature data from a weather forecast model into the downscaler, showing improved real-time ozone predictions. Finally, we introduce a hierarchical model to obtain spatially varying uncertainty associated with numerical model output. We show how we can learn about such uncertainty through suitable stochastic data fusion modeling using some external validation data. We illustrate our Bayesian model by providing the uncertainty map associated with a temperature output over the northeastern United States.