Climate change and irrigation water requirement at Jaguaribe river basin, semi-arid northeast of Brazil.

Summary: Climate change has a potential to impact rainfall, temperature and air humidity, which have relation to plant evapotranspiration and crop water requirement. The purpose of this research is to assess climate change impacts on irrigation water demand, based on future scenarios derived from the PRECIS (Providing Regional Climates for Impacts Studies), using boundary conditions of the HadCM3 submitted to a dynamic downscaling nested to the Hadley Centre regional circulation model HadRM3P. Monthly time series for average temperature and rainfall were generated for 1961-90 (baseline) and the future (2040). The reference evapotranspiration was estimated using monthly average temperature. Projected climate change impact on irrigation water demand demonstrated to be a result of evapotranspiration and rainfall trend. Impacts were mapped over the target region by using geostatistical methods. An increase of the average crop water needs was estimated to be 18.7% and 22.2% higher for 2040 A2 and B2 scenarios, respectively. Objective ? To analyze the climate change impacts on irrigation water requirements, using downscaling techniques of a climate change model, at the river basin scale. Method: The study area was delimited between 4º39?30? and 5º40?00? South and 37º35?30? and 38º27?00? West. The crop pattern in the target area was characterized, regarding type of irrigated crops, respective areas and cropping schedules, as well as the area and type of irrigation systems adopted. The PRECIS (Providing Regional Climates for Impacts Studies) system (Jones et al., 2004) was used for generating climate predictions for the target area, using the boundary conditions of the Hadley Centre model HadCM3 (Johns et al., 2003). The considered time scale of interest for climate change impacts evaluation was the year of 2040, representing the period of 2025 to 2055. The output data from the climate model was interpolated, considering latitude/longitude, by applying ordinary kriging tools available at a Geographic Information System, in order to produce thematic maps.

Validation of the interRAI Cognitive Performance Scale against independent clinical diagnosis and the Mini-Mental State Examination in older hospitalized patients

Objective To compare the diagnostic accuracy of the interRAI Acute Care (AC) Cognitive Performance Scale (CPS2) and the Mini-Mental State Examination (MMSE), against independent clinical diagnosis for detecting dementia in older hospitalized patients. Design, Setting, and Participants The study was part of a prospective observational cohort study of patients aged ≥70 years admitted to four acute hospitals in Queensland, Australia, between 2008 and 2010. Recruitment was consecutive and patients expected to remain in hospital for ≥48 hours were eligible to participate. Data for 462 patients were available for this study. Measurements Trained research nurses completed comprehensive geriatric assessments and administered the interRAI AC and MMSE to patients. Two physicians independently reviewed patients’ medical records and assessments to establish the diagnosis of dementia. Indicators of diagnostic accuracy included sensitivity, specificity, predictive values, likelihood ratios and areas under receiver (AUC) operating characteristic curves. Results 85 patients (18.4%) were considered to have dementia according to independent clinical diagnosis. The sensitivity of the CPS2 [0.68 (95%CI: 0.58–0.77)] was not statistically different to the MMSE [0.75 (0.64–0.83)] in predicting physician diagnosed dementia. The AUCs for the 2 instruments were also not statistically different: CPS2 AUC = 0.83 (95%CI: 0.78–0.89) and MMSE AUC = 0.87 (95%CI: 0.83–0.91), while the CPS2 demonstrated higher specificity [0.92 95%CI: 0.89–0.95)] than the MMSE [0.82 (0.77–0.85)]. Agreement between the CPS2 and clinical diagnosis was substantial (87.4%; κ=0.61). Conclusion The CPS2 appears to be a reliable screening tool for assessing cognitive impairment in acutely unwell older hospitalized patients. These findings add to the growing body of evidence supporting the utility of the interRAI AC, within which the CPS2 is embedded. The interRAI AC offers the advantage of being able to accurately screen for both dementia and delirium without the need to use additional assessments, thus increasing assessment efficiency.

Local stress-strain distribution and load transfer across cartilage matrix at micro-scale using combined microscopy-based finite element method

Articular cartilage is the load-bearing tissue that consists of proteoglycan macromolecules entrapped between collagen fibrils in a three-dimensional architecture. To date, the drudgery of searching for mathematical models to represent the biomechanics of such a system continues without providing a fitting description of its functional response to load at micro-scale level. We believe that the major complication arose when cartilage was first envisaged as a multiphasic model with distinguishable components and that quantifying those and searching for the laws that govern their interaction is inadequate. To the thesis of this paper, cartilage as a bulk is as much continuum as is the response of its components to the external stimuli. For this reason, we framed the fundamental question as to what would be the mechano-structural functionality of such a system in the total absence of one of its key constituents-proteoglycans. To answer this, hydrated normal and proteoglycan depleted samples were tested under confined compression while finite element models were reproduced, for the first time, based on the structural microarchitecture of the cross-sectional profile of the matrices. These micro-porous in silico models served as virtual transducers to produce an internal noninvasive probing mechanism beyond experimental capabilities to render the matrices micromechanics and several others properties like permeability, orientation etc. The results demonstrated that load transfer was closely related to the microarchitecture of the hyperelastic models that represent solid skeleton stress and fluid response based on the state of the collagen network with and without the swollen proteoglycans. In other words, the stress gradient during deformation was a function of the structural pattern of the network and acted in concert with the position-dependent compositional state of the matrix. This reveals that the interaction between indistinguishable components in real cartilage is superimposed by its microarchitectural state which directly influences macromechanical behavior.

Physical activity recognition from accelerometer data using a multi-scale ensemble method

Accurate and detailed measurement of an individual's physical activity is a key requirement for helping researchers understand the relationship between physical activity and health. Accelerometers have become the method of choice for measuring physical activity due to their small size, low cost, convenience and their ability to provide objective information about physical activity. However, interpreting accelerometer data once it has been collected can be challenging. In this work, we applied machine learning algorithms to the task of physical activity recognition from triaxial accelerometer data. We employed a simple but effective approach of dividing the accelerometer data into short non-overlapping windows, converting each window into a feature vector, and treating each feature vector as an i.i.d training instance for a supervised learning algorithm. In addition, we improved on this simple approach with a multi-scale ensemble method that did not need to commit to a single window size and was able to leverage the fact that physical activities produced time series with repetitive patterns and discriminative features for physical activity occurred at different temporal scales.

Trans-scale granular modelling of cytoskeleton: A mini-review

Living cells are the functional unit of organs that controls reactions to their exterior. However, the mechanics of living cells can be difficult to characterize due to the crypticity of their microscale structures and associated dynamic cellular processes. Fortunately, multiscale modelling provides a powerful simulation tool that can be used to study the mechanical properties of these soft hierarchical, biological systems. This paper reviews recent developments in hierarchical multiscale modeling technique that aimed at understanding cytoskeleton mechanics. Discussions are expanded with respects to cytoskeletal components including: intermediate filaments, microtubules and microfilament networks. The mechanical performance of difference cytoskeleton components are discussed with respect to their structural and material properties. Explicit granular simulation methods are adopted with different coarse-grained strategies for these cytoskeleton components and the simulation details are introduced in this review.

Separating grazing and rainfall effects at regional scale using remote sensing imagery: A dynamic reference-cover method

Remote detection of management-related trend in the presence of inter-annual climatic variability in the rangelands is difficult. Minimally disturbed reference areas provide a useful guide, but suitable benchmarks are usually difficult to identify. We describe a method that uses a unique conceptual framework to identify reference areas from multitemporal sequences of ground cover derived from Landsat TM and ETM+ imagery. The method does not require ground-based reference sites nor GIS layers about management. We calculate a minimum ground cover image across all years to identify locations of most persistent ground cover in years of lowest rainfall. We then use a moving window approach to calculate the difference between the window's central pixel and its surrounding reference pixels. This difference estimates ground-cover change between successive below-average rainfall years, which provides a seasonally interpreted measure of management effects. We examine the approach's sensitivity to window size and to cover-index percentiles used to define persistence. The method successfully detected management-related change in ground cover in Queensland tropical savanna woodlands in two case studies: (1) a grazing trial where heavy stocking resulted in substantial decline in ground cover in small paddocks, and (2) commercial paddocks where wet-season spelling (destocking) resulted in increased ground cover. At a larger scale, there was broad agreement between our analysis of ground-cover change and ground-based land condition change for commercial beef properties with different a priori ratings of initial condition, but there was also some disagreement where changing condition reflected pasture composition rather than ground cover. We conclude that the method is suitably robust to analyse grazing effects on ground cover across the 1.3 x 10(6) km(2) of Queensland's rangelands. Crown Copyright (c) 2012 Published by Elsevier Inc. All rights reserved.

A simple method for large-scale preparation of chick embryo tRNA

A simple method for preparing bulk quantities of tRNA from chick embryo has been developed. In this method chick embryos were homogenized in a buffer of pH 4.5, followed by deproteinization with phenol. The aqueous layer was allowed to separate under gravity. The resulting aqueous layer, after two more phenol treatments, was directly passed through a DEAE-cellulose column and the tRNA eluted therefrom with 1 Image NaCl. The tRNA prepared by this method was as active as the one prepared at neutral pH.

An FETI-preconditioned conjuerate gradient method for large-scale stochastic finite element problems

In the spectral stochastic finite element method for analyzing an uncertain system. the uncertainty is represented by a set of random variables, and a quantity of Interest such as the system response is considered as a function of these random variables Consequently, the underlying Galerkin projection yields a block system of deterministic equations where the blocks are sparse but coupled. The solution of this algebraic system of equations becomes rapidly challenging when the size of the physical system and/or the level of uncertainty is increased This paper addresses this challenge by presenting a preconditioned conjugate gradient method for such block systems where the preconditioning step is based on the dual-primal finite element tearing and interconnecting method equipped with a Krylov subspace reusage technique for accelerating the iterative solution of systems with multiple and repeated right-hand sides. Preliminary performance results on a Linux Cluster suggest that the proposed Solution method is numerically scalable and demonstrate its potential for making the uncertainty quantification Of realistic systems tractable.

Research on extracting method of micro-scale remote sensing information combination and application in coastal zone

973 Project of China [2006CB701305]; "863" Project of China [2009AA12Z148]; National Natural Science Foundation of China [40971224]

Large-scale isolation and purification of R-phycoerythrin from red alga Palmaria palmata using the expanded bed adsorption method

R-phycoerythrin, a light-harvesting protein in some marine algae, and can be widely used in medicine, was isolated and purified from a red alga, Palmaria palmata (Lannaeus) Kuntze, using the streamline column (expanded bed adsorption) combined with ion-exchange chromatography. Because the crude extract was applied to the column upwardly, the column would not be blocked by polysaccharides usually very abundant in the extract of marine alga, this kind of blockage could hardly lie overcome in ordinary chromatographic column. After applying the crude extract containing 0.5 mol/L (NH4)(2)SO4, (NH4)(2)SO4 solution of different concentrations (0.2 mol/L, 0.1 mol/L and 0.05 mol/L) was used to elute the column downwardly and the eluates were collected and desalted. The desalted eluates were then applied onto all ion-exchange chromatographic column loaded with Q-sepharose for further purification of the R-phycoerythrin. Through these two steps, the purity (OD565/OD280) of the R-phycoerythrin from P. palmata was up to 3.5, more than 3.2, the commonly accepted criterion for purity, and the yield of the purified R-phycoerythrin could reach 0.122 mg/g of frozen P. palmata, much higher than that of phycobiliproteins purified with the previous methods. The result indicated that the cost of R-phycoerythrin will drop down with the method reported in this article.

Method for large-scale isolation and purification of R-phycoerythrin from red alga Polysiphonia urceolata Grev

R-phycoerythrin was isolated and purified from a red alga, Polysiphonia urceolata Grev, using Streamline column combined with ion-exchange chromatography or hydroxyapatite chromatography. The purity of R-phycoerythrin isolated by Streamline column was up to 1.66 and the yield of R-phycoerythrin could be as high as 0.68 mg/g frozen P. urceolata. All the eluates from Streamline column were divided into two equivalent parts, respectively. One part was pumped into the ion-exchange column loaded with Q-Sepharose and the other was applied to the adsorption column loaded with hydroxyapatite. The purities of R-phycoerythrin purified using these two methods were both up to 3.26, more than 3.2 the commonly accepted criterion. The yield of purified R-phycoerythrin from the ion-exchange chromatography was 0.40 mg/g frozen P. urceolata and that from the hydroxyapatite chromatography could reach 0.34 mg/g frozen P. urceolata. The purified protein had three absorption peaks at 498, 535, and 565 nm and displayed a fluorescence maximum at 580 nm, which was consistent with the typical spectrum of R-phycoerythrin. The purified R-PE was also identified with electrophoresis. Only one single protein band appeared on native-PAGE with silver staining. SDS-PAGE demonstrated the presence of one 20 kDa major subunit, and one low intensity band corresponding to 33 kDa subunit. The results indicate that using the expanded bed adsorption combined with ion-exchange chromatography or hydroxyapatite chromatography, R-phycoerythrin can be purified from frozen P. urceolata on large scale. (c) 2006 Elsevier Inc. All rights reserved.

A method for semi-automated objective quantification of linear bedforms from multi-scale Digital Elevation Models

The increasing availability of large, detailed digital representations of the Earth’s surface demands the application of objective and quantitative analyses. Given recent advances in the understanding of the mechanisms of formation of linear bedform features from a range of environments, objective measurement of their wavelength, orientation, crest and trough positions, height and asymmetry is highly desirable. These parameters are also of use when determining observation-based parameters for use in many applications such as numerical modelling, surface classification and sediment transport pathway analysis. Here, we (i) adapt and extend extant techniques to provide a suite of semi-automatic tools which calculate crest orientation, wavelength, height, asymmetry direction and asymmetry ratios of bedforms, and then (ii) undertake sensitivity tests on synthetic data, increasingly complex seabeds and a very large-scale (39 000km2) aeolian dune system. The automated results are compared with traditional, manually derived,measurements at each stage. This new approach successfully analyses different types of topographic data (from aeolian and marine environments) from a range of sources, with tens of millions of data points being processed in a semi-automated and objective manner within minutes rather than hours or days. The results from these analyses show there is significant variability in all measurable parameters in what might otherwise be considered uniform bedform fields. For example, the dunes of the Rub’ al Khali on the Arabian peninsula are shown to exhibit deviations in dimensions from global trends. Morphological and dune asymmetry analysis of the Rub’ al Khali suggests parts of the sand sea may be adjusting to a changed wind regime from that during their formation 100 to 10 ka BP.

Depression associates with Mini Nutritional Assessment (MNA), Vitamin B12 and Folate status::Findings from Belfast Elderly Longitudinal Free-Living Ageing STudy (BELFAST)

Introduction: An association between depression and folate has been found in clinical studies. Depression and dementia can contribute to nutritional deficiency. This study clinical depression in in octo/nonagenarians from the BELFAST study.
Method: In the BELFAST study, 38 free-living octo/nonagenarians (mean age 82 years), who apparently well and cognitively intact were followed up at 5 years and assessed using the Geriatric Depression Scale (GDS), Folstein (30 point), Mini Nutritional Assessment Tool (MNA) together with serum folate and vitamin B12 levels.
Results: Mean GDS was 3.4 (SD 2.5), serum folate 7.1 umol/l (SD 5.3) and B12 553 umol/l (458). With mean MNA and Folstein -25.8 (SD 2.7) and 27.6 (SD 2.7) respectively with no sex difference (p = 0.78; p = 0.36). 25% of subjects showed a GDS >5 indicating risk of mild depression and 21% had compromised nutritional status. MNA associated with GDS in male (r2 = 0.56 p = 0.01), but not in female elderly subjects (r2 = 0.01; p = 0.44). GDS score and lower serum folate were associated (r2 = -0.23; p = 0.01).
Conclusion: Overall there was the suggestion that nutritional status and depression might be linked in male subjects at 5 year follow-up in octo/nonagenarians from the BEFLAST study. The lower folate in subjects categorised at risk of mild depression might suggest vitamin supplementation could be useful.