Durum wheat plays a central role for Italy, a country characterized by an historical tradition of pasta making. This crop is one of the major sources of starch in the Mediterranean diet, also providing substantial amounts of nutrients, either essential or healthy, such as minerals and phytochemicals. In this study, the effect of cropping system (organic (ORG) and conventional (CONV)) on the content of proteins, wet gluten, minerals, and total polyphenols (TPC), as well as on the antioxidant activity (AA) and yield characteristics were evaluated in nine genotypes of whole durum wheat. The analysis of variance confirmed the key role of cropping system, which explained more than 50% of the total variation for some minerals (Na, K, and Fe), and more than 80% for proteins, wet gluten, and TPC. The CONV reported the highest levels of proteins, wet gluten, and ash, whereas the TPC and AA were statistically higher in the ORG ones. The quality traits under study were also genotype dependent. For instance, ‘Ramirez’ had a higher ash content under ORG than CONV, while ‘Core’ had an opposite behavior. This study provides a better understanding about the effect of both cropping system (ORG vs. CONV) and genotype on the yield and qualitative traits of the whole grain durum wheat.

Abstract:This paper examines benefits of using concavity-based structural features in recognition of handwritten digits. An overview of existing concavity features is presented and a new method is introduced. These features are used as complementary features to gradient and chaincode features, both among the best performing features in handwritten digit recognition. Two support vector classifiers (SVCs) are chosen for classification task as the top performers in previous works; SVC with radial basis function (RBF) kernel and the SVC with polynomial kernel. For reference, we also used the k-nearest neighbor (k-NN) classifier. Results are obtained on MNIST, USPS and DIGITS datasets. We also tested dataset independency of various feature vectors by combining different datasets. The introduced feature extraction method gives the best results in majority of tests.

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Multiple sporadic servers as a mechanism for rescheduling aperiodic tasks are applicable to today's computer environments. A developed simulation tool enables evaluation of its performance for various task sets and server parameters. By increasing the number of servers, aperiodic task response time is reduced; system utilization and the number of reschedulings are increased whereas periodic task execution is disrupted insignificantly. Proper selection of server parameters improves task response time, and decreases the number of unnecessary reschedulings. Simulation results prove model correctness and simulation accuracy. The simulator is applicable to developing rescheduling algorithms and their implementation into real environments.

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