Managing Software Reuse Economics: An Integrated ROI-based Model

Several cost models have been proposed in the past for estimating, predicting, and analyzing the costs of software reuse. In this paper we propose an integrated ROI-based cost model which attempts to encompass existing models. Our approach is to analyze existing models, identify their dimensions of variance, classify the models along these dimensions, then provide an integrated cost model that makes explicit provisions for these dimensions of variance. In this paper, we also discuss in what sense our model encompasses existing models, present a prototype that supports the cost model, and illustrate the model with a sample example.     

Derivative-based band clustering and multi-agent PSO optimization for optimal band selection of hyper-spectral images

The Journal of Supercomputing - Images (HSIs) are popular in diversified applications, such as geosciences, biomedical imaging, molecular biology, agriculture, astronomy, food quality and safety...     

In vitro evaluation of red and green lettuce (Lactuca sativa) for functional food properties

Lettuce (Lactuca sativa) is an important leafy vegetable consumed fresh or in salad mixes. We have compared the functional food properties of selected commercial red and green lettuce varieties grown under field conditions. Both lettuce cultivars were extracted with water at biological (38 °C) and room temperatures (22 °C) at pH 2. The residues from each extraction were further extracted, sequentially with methanol and ethyl acetate. The extracts were evaluated for their in vitro lipid peroxidation (LPO) and cyclooxygenase enzyme (COX) inhibitory activities. Amongst the extracts tested, all three extracts of red lettuce showed higher LPO and COX-1 and -2 enzyme inhibitory activities than did the green lettuce extracts. Red lettuce contained a single anthocyanin, cyanidin-3-O-(6″-malonyl-β-glucopyranoside) (1), which immediately converted to cyanidin-3-O-(6″-malonyl-β-glucopyranoside methyl ester) (2) and cyanidin-3-O-β-glucopyranoside (3) under laboratory conditions. Anthocyanins 1 and 2 inhibited LPO by 88% and 91.5%, respectively, at 0.25 μM concentration. Also, they inhibited COX-2 enzyme by 78.9% and 84.3% and COX-1 by 64% and 65.8%, respectively, at 5 μM. The chicoric acid (4), amongst other phenolics, such as quercetin glucoside, ferulic and caffeic acids, isolated from both green and red lettuce, showed 85.6%, 45.6% and 94% of LPO, COX-1 and -2 enzyme inhibitions at 50 μM, respectively. This is the first report of the LPO, COX-1 and -2 enzyme inhibitory activities of compounds 1, 2 and 4. The variation of phenolics in the red and green lettuces, and specifically the lack of anthocyanins in green lettuce, might account for the higher biological activity obtained with the red variety in our study.     

Aqueous Oxidative Heck Reaction as a Protein‐Labeling Strategy

An increasing number of chemical reactions are being employed for bio‐orthogonal ligation of detection labels to protein‐bound functional groups. Several of these strategies, however, are limited in their application to pure proteins and are ineffective in complex biological samples such as cell lysates. Here we present the palladium‐catalyzed oxidative Heck reaction as a new and robust bio‐orthogonal strategy for linking functionalized arylboronic acids to protein‐bound alkenes in high yields and with excellent chemoselectivity even in the presence of complex protein mixtures from living cells. Advantageously, this reaction proceeds under aerobic conditions, whereas most other metal‐catalyzed reactions require inert atmosphere.     

River Stage Forecasting using Enhanced Partial Correlation Graph

Various time series forecasting methods have been successfully applied for the water-stage forecasting problem. Graphical time series models are a class of multivariate time series to model the spatio-temporal dependencies between the sensors. Constructing graph-based models involve data pre-processing and correlation analysis to capture the dynamics of different water flow scenarios, which is not scalable for a large network of sensors. This paper presents a novel approach to model spatio-temporal dependencies across river network stations using a partial correlation graph. We also provide a method to enrich this partial correlation graph by eliminating the spurious correlations. We demonstrate the utility of enriched partial correlation graphs in multivariate forecasting for various scenarios and state-of-the-art multivariate forecasting models. We observe that the forecasting techniques that use information from the enriched partial correlation graph outperform standard time series forecasting approaches for river network forecasting.