On the potential of assimilating meteorological analyses in a global climate model for the purpose of model validation

A simple four-dimensional assimilation technique, called Newtonian relaxation, has been applied to the Hamburg climate model (ECHAM), to enable comparison of model output with observations for short periods of time. The prognostic model variables vorticity, divergence, temperature, and surface pressure have been relaxed toward European Center for Medium-Range Weather Forecasts (ECMWF) global meteorological analyses. Several experiments have been carried out, in which the values of the relaxation coefficients have been varied to find out which values are most usable for our purpose. To be able to use the method for validation of model physics or chemistry, good agreement of the model simulated mass and wind field is required. In addition, the model physics should not be disturbed too strongly by the relaxation forcing itself. Both aspects have been investigated. Good agreement with basic observed quantities, like wind, temperature, and pressure is obtained for most simulations in the extratropics. Derived variables, like precipitation and evaporation, have been compared with ECMWF forecasts and observations. Agreement for these variables is smaller than for the basic observed quantities. Nevertheless, considerable improvement is obtained relative to a control run without assimilation. Differences between tropics and extratropics are smaller than for the basic observed quantities. Results also show that precipitation and evaporation are affected by a sort of continuous spin-up which is introduced by the relaxation: the bias (ECMWF-ECHAM) is increasing with increasing relaxation forcing. In agreement with this result we found that with increasing relaxation forcing the vertical exchange of tracers by turbulent boundary layer mixing and, in a lesser extent, by convection, is reduced.

Content validation for level of use of feature rich systems: a Delphi study of electronic medical records systems

Introduction. Feature usage is a pre-requisite to realising the benefits of investments in feature rich systems. We propose that conceptualising the dependent variable 'system use' as 'level of use' and specifying it as a formative construct has greater value for measuring the post-adoption use of feature rich systems. We then validate the content of the construct as a first step in developing a research instrument to measure it. The context of our study is the post-adoption use of electronic medical records (EMR) by primary care physicians. Method. Initially, a literature review of the empirical context defines the scope based on prior studies. Having identified core features from the literature, they are further refined with the help of experts in a consensus seeking process that follows the Delphi technique. Results.The methodology was successfully applied to EMRs, which were selected as an example of feature rich systems. A review of EMR usage and regulatory standards provided the feature input for the first round of the Delphi process. A panel of experts then reached consensus after four rounds, identifying ten task-based features that would be indicators of level of use. Conclusions. To study why some users deploy more advanced features than others, theories of post-adoption require a rich formative dependent variable that measures level of use. We have demonstrated that a context sensitive literature review followed by refinement through a consensus seeking process is a suitable methodology to validate the content of this dependent variable. This is the first step of instrument development prior to statistical confirmation with a larger sample.

Development and validation of a parent report measure for detection of cognitive delay in infancy

Aim To develop a brief, parent-completed instrument (‘ERIC’) for detection of cognitive delay in 10-24 month-olds born preterm, or with low birth weight, or with perinatal complications, and to establish its diagnostic properties. Method Scores were collected from parents of 317 children meeting ≥1 inclusion criteria (birth weight <1500g; gestational age <34 completed weeks; 5-minute Apgar <7; presence of hypoxic-ischemic encephalopathy) and meeting no exclusion criteria. Children were assessed for cognitive delay using a criterion score on the Bayley Scales of Infant and Toddler Development Cognitive Scale III1 <80. Items were retained according to their individual associations with delay. Sensitivity, specificity, Positive and Negative Predictive Values were estimated and a truncated ERIC was developed for use <14 months. Results ERIC detected 17 out of 18 delayed children in the sample, with 94.4% sensitivity (95% CI [confidence interval] 83.9-100%), 76.9% specificity (72.1-81.7%), 19.8% positive predictive value (11.4-28.2%); 99.6% negative predictive value (98.7-100%); 4.09 likelihood ratio positive; and 0.07 likelihood ratio negative; the associated Area under the Curve was .909 (.829-.960). Interpretation ERIC has potential value as a quickly-administered diagnostic instrument for the absence of early cognitive delay in preterm or premature infants of 10-24 months, and as a screen for cognitive delay. Further research may be needed before ERIC can be recommended for wide-scale use.

Validation of Canopy Height Profile methodology for small-footprint full-waveform airborne LiDAR data in a discontinuous canopy environment

A Canopy Height Profile (CHP) procedure presented in Harding et al. (2001) for large footprint LiDAR data was tested in a closed canopy environment as a way of extracting vertical foliage profiles from LiDAR raw-waveform. In this study, an adaptation of this method to small-footprint data has been shown, tested and validated in an Australian sparse canopy forest at plot- and site-level. Further, the methodology itself has been enhanced by implementing a dataset-adjusted reflectance ratio calculation according to Armston et al. (2013) in the processing chain, and tested against a fixed ratio of 0.5 estimated for the laser wavelength of 1550nm. As a by-product of the methodology, effective leaf area index (LAIe) estimates were derived and compared to hemispherical photography-derived values. To assess the influence of LiDAR aggregation area size on the estimates in a sparse canopy environment, LiDAR CHPs and LAIes were generated by aggregating waveforms to plot- and site-level footprints (plot/site-aggregated) as well as in 5m grids (grid-processed). LiDAR profiles were then compared to leaf biomass field profiles generated based on field tree measurements. The correlation between field and LiDAR profiles was very high, with a mean R2 of 0.75 at plot-level and 0.86 at site-level for 55 plots and the corresponding 11 sites. Gridding had almost no impact on the correlation between LiDAR and field profiles (only marginally improvement), nor did the dataset-adjusted reflectance ratio. However, gridding and the dataset-adjusted reflectance ratio were found to improve the correlation between raw-waveform LiDAR and hemispherical photography LAIe estimates, yielding the highest correlations of 0.61 at plot-level and of 0.83 at site-level. This proved the validity of the approach and superiority of dataset-adjusted reflectance ratio of Armston et al. (2013) over a fixed ratio of 0.5 for LAIe estimation, as well as showed the adequacy of small-footprint LiDAR data for LAIe estimation in discontinuous canopy forests.

Towards pain-free diagnosis of skin diseases through multiplexed microneedles: biomarker extraction and detection using a highly sensitive blotting method

Immunodiagnostic microneedles provide a novel way to extract protein biomarkers from the skin in a minimally invasive manner for analysis in vitro. The technology could overcome challenges in biomarker analysis specifically in solid tissue, which currently often involves invasive biopsies. This study describes the development of a multiplex immunodiagnostic device incorporating mechanisms to detect multiple antigens simultaneously, as well as internal assay controls for result validation. A novel detection method is also proposed. It enables signal detection specifically at microneedle tips and therefore may aid the construction of depth profiles of skin biomarkers. The detection method can be coupled with computerised densitometry for signal quantitation. The antigen specificity, sensitivity and functional stability of the device were assessed against a number of model biomarkers. Detection and analysis of endogenous antigens (interleukins 1α and 6) from the skin using the device was demonstrated. The results were verified using conventional enzyme-linked immunosorbent assays. The detection limit of the microneedle device, at ≤10 pg/mL, was at least comparable to conventional plate-based solid-phase enzyme immunoassays.

KPIs and their properties defined with the EXTREME method

Key Performance Indicators (KPIs) are the main instruments of Business Performance Management. KPIs are the measures that are translated to both the strategy and the business process. These measures are often designed for an industry sector with the assumptions about business processes in organizations. However, the assumptions can be too incomplete to guarantee the required properties of KPIs. This raises the need to validate the properties of KPIs prior to their application to performance measurement. This paper applies the method called EXecutable Requirements Engineering Management and Evolution (EXTREME) for validation of the KPI definitions. EXTREME semantically relates the goal modeling, conceptual modeling and protocol modeling techniques into one methodology. The synchronous composition built into protocol modeling enables raceability of goals in protocol models and constructive definitions of a KPI. The application of the method clarifies the meaning of KPI properties and procedures of their assessment and validation.

Identification and validation of candidate genes associated with domesticated and improved traits in soybean

Soybean, an important source of vegetable oils and proteins for humans, has undergone significant phenotypic changes during domestication and improvement. However, there is limited knowledge about genes related to these domesticated and improved traits, such as flowering time, seed development, alkaline-salt tolerance, and seed oil content (SOC). In this study, more than 106,000 single nucleotide polymorphisms (SNPs) were identified by restriction site associated DNA sequencing of 14 wild, 153 landrace, and 119 bred soybean accessions, and 198 candidate domestication regions (CDRs) were identified via multiple genetic diversity analyses. Of the 1489 candidate domestication genes (CDGs) within these CDRs, a total of 330 CDGs were related to the above four traits in the domestication, gene ontology (GO) enrichment, gene expression, and pathway analyses. Eighteen, 60, 66, and 10 of the 330 CDGs were significantly associated with the above four traits, respectively. Of 134 traitassociated CDGs, 29 overlapped with previous CDGs, 11 were consistent with candidate genes in previous trait association studies, and 66 were covered by the domesticated and improved quantitative trait loci or their adjacent regions, having six common CDGs, such as one functionally characterized gene Glyma15 g17480 (GmZTL3). Of the 68 seed size (SS) and SOC CDGs, 37 were further confirmed by gene expression analysis. In addition, eight genes were found to be related to artificial selection during modern breeding. Therefore, this study provides an integrated method for efficiently identifying CDGs and valuable information for domestication and genetic research.

Validation of a food frequency questionnaire for women with osteoporosis

The importance of nutrient intakes in osteoporosis prevention in treatment is widely recognized. The objective of the present study was to develop and validate a FFQ for women with osteoporosis. The questionnaire was composed of 60 items, separated into 10 groups. The relative validation was accomplished through comparison of the 3-Day Food Record (3DR) with the FFQ. The 3DR was applied to 30 elderly women with confirmed osteoporosis, and after 45 days the FFQ was administrated. Statistical analysis comprised the Kolmogorov-Smirnov, Student T test and Pearson correlation coefficient. The agreement between two methods was evaluated by the frequency of similar classification into quartiles, and by the Bland-Altman method. No significant differences between methods were observed for the mean evaluated nutrients, except for carbohydrate and magnesium. Pearson correlation coefficients were positive and statistically significant for all nutrients. The overall proportion of subjects classified in the same quartile by the two methods was on average 50.01% and in the opposite quartile 0.47%. For calcium intake, only 3% of subjects were classified in opposite extreme quartiles by the two methods. The Bland-Altman analysis demonstrated that the differences obtained by the two methods in each subject were well distributed around the mean of the difference, and the disagreement increases as the mean intake increases. These results indicates that the FFQ for elderly women with osteoporosis presented here is highly acceptable and is an accurate method that can be used in large-scale or clinical studies for evaluation of nutrient intakes in a similar population.

Sequence-specific reconstruction from fragmentary databases using seed sequences: implementation and validation on SAGE, proteome and generic sequencing data

Motivation: DNA assembly programs classically perform an all-against-all comparison of reads to identify overlaps, followed by a multiple sequence alignment and generation of a consensus sequence. If the aim is to assemble a particular segment, instead of a whole genome or transcriptome, a target-specific assembly is a more sensible approach. GenSeed is a Perl program that implements a seed-driven recursive assembly consisting of cycles comprising a similarity search, read selection and assembly. The iterative process results in a progressive extension of the original seed sequence. GenSeed was tested and validated on many applications, including the reconstruction of nuclear genes or segments, full-length transcripts, and extrachromosomal genomes. The robustness of the method was confirmed through the use of a variety of DNA and protein seeds, including short sequences derived from SAGE and proteome projects.

Multivariant optimization, validation, and application of capillary electrophoresis for simultaneous determination of polyphenols and phenolic acids in Brazilian wines

A method for the simultaneous determination of the stilbene resveratrol, four phenolic acids (syringic, coumaric, caffeic, and gallic acids), and five flavonoids (catechin, rutin, kaempferol, myricetin, and quercetin) in wine by CE was developed and validated. The CE electrolyte composition and instrumental conditions were optimized using 2(7-3) factorial design and response surface analysis, showing sodium tetraborate, MeOH, and their interaction as the most influential variables. The optimal electrophoretic conditions, minimizing the chromatographic resolution statistic values, consisted of 17 mmol/L sodium tetraborate with 20% methanol as electrolyte, constant voltage of 25 kV, hydrodynamic injection at 50 mbar for 3 s, and temperature of 25 degrees C. The R(2) values for linearity varied from 0.994 to 0.999; LOD and LOQ were 0.1 to 0.3 mg/L and 0.4 to 0.8 mg/L, respectively. The RSDs for migration time and peak area obtained from ten consecutive injections were less than 2% and recoveries varied from 97 to 102%. The method was applied to 23 samples of inexpensive Brazilian wines, showing wide compositional variation.

Development of a fast capillary electrophoresis method for the determination of propranolol-Total analysis time reduction strategies

The aim of this study was to develop a fast capillary electrophoresis method for the determination of propranolol in pharmaceutical preparations. In the method development the pH and constituents of the background electrolyte were selected using the effective mobility versus pH curves. Benzylamine was used as the internal standard. The background electrolyte was composed of 60 mmol L(-1) tris(hydroxymethyl)aminomethane and 30 mmol L(-1) 2-hydroxyisobutyric acid,at pH 8.1. Separation was conducted in a fused-silica capillary (32 cm total length and 8.5 cm effective length, 50 mu m I.D.) with a short-end injection configuration and direct UV detection at 214 nm. The run time was only 14 s. Three different strategies were studied in order to develop a fast CE method with low total analysis time for propranolol analysis: low flush time (Lflush) 35 runs/h, without flush (Wflush) 52 runs/h, and Invert (switched polarity) 45 runs/h. Since the three strategies developed are statistically equivalent, Mush was selected due to the higher analytical frequency in comparison with the other methods. A few figures of merit of the proposed method include: good linearity (R(2) > 0.9999); limit of detection of 0.5 mg L(-1): inter-day precision better than 1.03% (n = 9) and recovery in the range of 95.1-104.5%. (C) 2009 Elsevier B.V. All rights reserved.

Evaluation of the QuEChERS Method and Gas Chromatography-Mass Spectrometry for the Analysis Pesticide Residues in Water and Sediment

A method for the determination of pesticide residues in water and sediment was developed using the QuEChERS method followed by gas chromatography - mass spectrometry. The method was validated in terms of accuracy, specificity, linearity, detection and quantification limits. The recovery percentages obtained for the pesticides in water at different concentrations ranged from 63 to 116%, with relative standard deviations below 12%. The corresponding results from the sediment ranged from 48 to 115% with relative standard deviations below 16%. The limits of detection for the pesticides in water and sediment were below 0.003 mg L(-1) and 0.02 mg kg(-1), respectively.

Combining Satellite And Gauge Precipitation Data With Co-Kriging Method For Jakarta Region

Jakarta is vulnerable to flooding mainly caused by prolonged and heavy rainfall and thus a robust hydrological modeling is called for. A good quality of spatial precipitation data is therefore desired so that a good hydrological model could be achieved. Two types of rainfall sources are available: satellite and gauge station observations. At-site rainfall is considered to be a reliable and accurate source of rainfall. However, the limited number of stations makes the spatial interpolation not very much appealing. On the other hand, the gridded rainfall nowadays has high spatial resolution and improved accuracy, but still, relatively less accurate than its counterpart. To achieve a better precipitation data set, the study proposes cokriging method, a blending algorithm, to yield the blended satellite-gauge gridded rainfall at approximately 10-km resolution. The Global Satellite Mapping of Precipitation (GSMaP, 0.1⁰×0.1⁰) and daily rainfall observations from gauge stations are used. The blended product is compared with satellite data by cross-validation method. The newly-yield blended product is then utilized to re-calibrate the hydrological model. Several scenarios are simulated by the hydrological models calibrated by gauge observations alone and blended product. The performance of two calibrated hydrological models is then assessed and compared based on simulated and observed runoff.

The Potential Of Kohonen Method For Classifying Rivers Focused On Regional Environmental Flow Determination With ELOHA

This article highlights the potential benefits that the Kohonen method has for the classification of rivers with similar characteristics by determining regional ecological flows using the ELOHA (Ecological Limits of Hydrologic Alteration) methodology. Currently, there are many methodologies for the classification of rivers, however none of them include the characteristics found in Kohonen method such as (i) providing the number of groups that actually underlie the information presented, (ii) used to make variable importance analysis, (iii) which in any case can display two-dimensional classification process, and (iv) that regardless of the parameters used in the model the clustering structure remains. In order to evaluate the potential benefits of the Kohonen method, 174 flow stations distributed along the great river basin “Magdalena-Cauca” (Colombia) were analyzed. 73 variables were obtained for the classification process in each case. Six trials were done using different combinations of variables and the results were validated against reference classification obtained by Ingfocol in 2010, whose results were also framed using ELOHA guidelines. In the process of validation it was found that two of the tested models reproduced a level higher than 80% of the reference classification with the first trial, meaning that more than 80% of the flow stations analyzed in both models formed invariant groups of streams.

New method for determination of (E)resveratrol in wine based on microextraction using packed sorbent and ultra-performance liquid chromatography

An ultra-fast and improved analytical methodology based on microextraction by packed sorbent (MEPS) combined with ultra-performance LC (UPLC) was developed and validated for determination of (E)-resveratrol in wines. Important factors affecting the performance of MEPS such as the type of sorbent material (C2, C8, C18, SIL, and M1), number of extraction cycles, and sample volume were studied. The optimal conditions of MEPS extraction were obtained using C8 sorbent and small sample volumes (50–250mL) in one extraction cycle (extract–discard) and in a short time period (about 3 min for the entire sample preparation step). (E)-Resveratrol was eluted by 1 250mL of the mixture containing 95% methanol and 5% water, and the separation was carried out on a highstrength silica HSS T3 analytical column (100 mm 2.1 mm, 1.8mm particle size) using a binary mobile phase composed of aqueous 0.1% formic acid (eluent A) and methanol (eluent B) in the gradient elution mode (10 min of total analysis). The method was fully validated in terms of linearity, detection (LOD) and quantification (LOQ) limits, extraction yield, accuracy, and inter/intra-day precision, using a Madeira wine sample (ET) spiked with (E)-resveratrol at concentration levels ranging from 5 to 60mg/mL. Validation experiments revealed very good recovery rate of 9575.8% RSD, good linearity with r2 values 40.999 within the established concentration range, excellent repeatability (0.52%), and reproducibility (1.67%) values (expressed as RSD), thus demonstrating the robustness and accuracy of the MEPSC8/UPLC-photodiode array (PDA) method. The LOD of the method was 0.21mg/mL, whereas the LOQ was 0.68mg/mL. The validated methodology was applied to 30 commercial wines (24 red wines and six white wines) from different grape varieties, vintages, and regions. On the basis of the analytical validation, the MEPSC8/UPLC-PDA methodology shows to be an improved, sensitive, and ultra-fast approach for determination of (E)-resveratrol in wines with high resolving power within 6 min.