Schema-based Web wrapping

An effective solution to automate information extraction from Web pages is represented by wrappers. A wrapper associates a Web page with an XML document that represents part of the information in that page in a machine-readable format. Most existing wrapping approaches have traditionally focused on how to generate extraction rules, while they have ignored potential benefits deriving from the use of the schema of the information being extracted in the wrapper evaluation. In this paper, we investigate how the schema of extracted information can be effectively used in both the design and evaluation of a Web wrapper. We define a clean declarative semantics for schema-based wrappers by introducing the notion of (preferred) extraction model, which is essential to compute a valid XML document containing the information extracted from a Web page. We developed the SCRAP (SChema-based wRAPper for web data) system for the proposed schema-based wrapping approach, which also provides visual support tools to the wrapper designer. Moreover, we present a wrapper generalization framework to profitably speed up the design of schema-based wrappers. Experimental evaluation has shown that SCRAP wrappers are not only able to successfully extract the required data, but also they are robust to changes that may occur in the source Web pages.     

The volatile fraction profiling of fresh tomatoes and triple concentrate tomato pastes as parameter for the determination of geographical origin

Two unsupervised pattern recognition techniques such as stepwise linear discriminant analysis (SLDA) and Soft Independent Modeling of Class Analogy (SIMCA) were used to classify tomato samples in categories corresponding to the cultivation areas. The same approach was used for triple concentrated pastes for discrimination between two different Italian production areas. Accordingly, HS-SPME-GC-MS with 85 ??m carboxen/polydimethylsiloxane fiber was used for the determination of the volatile fraction in tomatoes and triple concentrate tomato pastes samples. Ethyl isobututanoate was used as internal standard for semiquantitative analysis and the concentration data (??g/kg) of 38 compounds for tomatoes and of 32 compounds for triple concentrates were used in following chemometric analysis. Sixteen and three variables were selected by forward stepwise LDA for tomatoes and pastes, respectively. SLDA and SIMCA models showed respectively 96% and 94% in term of prediction ability for tomatoes. The two supervised techniques provided 100% and 97% in prediction of the production areas of tomato pastes, respectively.     

The use of multi element profiling to differentiate between cowand buffalo milk

The multi element profile of milk from 12 cows and 6 water buffaloes was investigated, to establish whether dairy products derived from the two species could be distinguished. Multi-element data were obtained using ICP-MS. Following assessment against the team’s QA/QC criteria, or where the levels were below the LOD for the procedure, 16 elements (P, S, K, Ca, V, Cr, Mn, Fe, Co, Zn, Ga, Rb, Sr, Mo, Cs and Ba) were submitted for statistical analysis. Using linear discriminant analysis (LDA) it was possible to differentiate between milk from the two species, produced under identical environmental and animal husbandry conditions, on one farm. The sources of food and water available for consumption by the animals were also analysed and the results showed that there was no correlation between the elemental composition of the dietary components and the profiles observed in the milk.     

The defensive secretion of Carabus lefebvrei Dejean 1826 pupa (Coleoptera,Carabidae): Gland ultrastructure and chemical identification

This study documents the defensive function of flavored humor secreted by the abdominal glands of Carabus lefebvrei pupae. The morphology and the ultrastructure of these glands were described and the volatile compounds of glands secretion were identified by gas chromatography/mass spectrometry. The ultrastructure analysis shows an acinose complex formed by about 50 clusters. Each cluster has 20 glandular units and the unit—composed of one secretory and one canal cell lying along a duct—belongs to the class 3 cell type of Quennedey (1998). In the cytoplasm, the secretory cell contains abundant rough endoplasmatic reticula, glycogen granules, numerous mitochondria, and many well-developed Golgi complexes producing electron-dense secretory granules. Mitochondria are large, elongated, and often adjoining electronlucent vesicles. The kind and the origin of secretory granules varying in size and density were discussed. The chemical analysis of the gland secretion revealed the presence of a mixture of low molecular weight terpenes, ketones, aldehydes, alcohols, esters, and carboxylic acids. Monoterpenes, especially linalool, were the major products. We supposed that ketones, aldehydes, alcohols, esters, and carboxylic acids have a deterrent function against the predators and monoterpenes provide a prophylaxis function against pathogens. Microsc. Res. Tech., 2009. © 2008 Wiley-Liss, Inc.     

Metacluster-based Projective Clustering Ensembles

Machine Learning - The Projective Clustering Ensemble (PCE) problem is a recent clustering advance aimed at combining the two powerful tools of clustering ensembles and projective clustering. PCE...     

Absolute method for the assay of oleuropein in olive oils by atmospheric pressure chemical ionization tandem mass spectrometry

Oleuropein (OLP, 1), the active ingredient present (i) in food integrators extracted from olive leaves, (ii) in table olives, and (iii) in extra virgin olive oils is a nutraceutical whose health benefits have been widely documented. A new analytical method for its assay, which is based on the utilization of atmospheric pressure chemical ionization tandem mass spectrometry and on the use of a synthetic labeled analogue, the 4-trideuteriocarboxyoleuropein (2), as an internal standard, is presented. The results obtained with extra virgin olive oils from different cultivars and different Italian regions are discussed.     

Collaborative clustering of XML documents

Clustering XML documents is extensively used to organize large collections of XML documents in groups that are coherent according to structure and/or content features. The growing availability of distributed XML sources and the variety of high-demand environments raise the need for clustering approaches that can exploit distributed processing techniques. Nevertheless, existing methods for clustering XML documents are designed to work in a centralized way. In this paper, we address the problem of clustering XML documents in a collaborative distributed framework. XML documents are first decomposed based on semantically cohesive subtrees, then modeled as transactional data that embed both XML structure and content information. The proposed clustering framework employs a centroid-based partitional clustering method that has been developed for a peer-to-peer network. Each peer in the network is allowed to compute a local clustering solution over its own data, and to exchange its cluster representatives with other peers. The exchanged representatives are used to compute representatives for the global clustering solution in a collaborative way. We evaluated effectiveness and efficiency of our approach on real XML document collections varying the number of peers. Results have shown that major advantages with respect to the corresponding centralized clustering setting are obtained in terms of runtime behavior, although clustering solutions can still be accurate with a moderately low number of nodes in the network. Moreover, the collaborativeness characteristic of our approach has revealed to be a convenient feature in distributed clustering as found in a comparative evaluation with a distributed non-collaborative clustering method.     

Evaluation of pervaporation process of kiwifruit juice by SPME-GC/Ion Trap Mass Spectrometry

The processing of kiwifruit for obtaining products with a higher sensory quality, to be used in the food industry, is associated with the use of techniques which can limit the physical and chemical losses of aroma compounds. Pervaporation (PV) represents an alternative to the techniques based on distillation/evaporation or partial condensation to concentrate the aroma compounds preserving the molecule integrity (mild operational conditions used), having a high selectivity towards the organic volatile compounds, and respecting also the environment. The most representative volatile compounds of the kiwifruit aroma was chosen for evaluating the pervaporation process. SPME‐GC/ion trap mass spectrometry method was exploited to determine the amounts of these compounds. The approach was based on chemical ionization acquisition with isobutane as reagent gas and 1‐heptanol and (Z)‐3‐hexen‐yl acetate as internal standards. In these conditions, the calibration curves were satisfactory as demonstrated by the R² values of the straight lines (0.9937-0.9999). A kiwifruit fresh juice was processed by pervaporation through the composite commercial membrane (GFT1070) and the one self‐prepared, made of styrene butadiene co‐styrene (SBS), at three different feed temperatures. Marked effects for both membranes were observed in the total and partial fluxes of aroma compounds as the temperature was increased. The studied aroma compounds were differently affected by the temperature changes during PV process, with the result of a change in concentration in the permeate of the aroma compounds recovered.