Beyond social graphs: mining patterns underlying social interactions

This work aims at discovering and extracting relevant patterns underlying social interactions. To do so, some knowledge extracted from Facebook, a social networking site, is formalised by means of an Extended Social Graph, a data structure which goes beyond the original concept of a social graph by also incorporating information on interests. When the Extended Social Graph is built, state-of-the-art techniques are applied over it in order to discover communities. Once these social communities are found, statistical techniques will look for relevant patterns common to each of those, in such a way that each cluster of users is characterised by a set of common features. The resulting knowledge will be used to develop and evaluate a social recommender system, which aims at suggesting users in a social network with possible friends or interests.     

Analysis of the HLA class I associated peptide repertoire in a hepatocellular carcinoma cell line reveals tumor-specific peptides as putative targets for immunotherapy

HLA class I molecules present peptides on the cell surface to CD8(+) T cells. The repertoire of peptides that associate to class I molecules represents the cellular proteome. Therefore, cells expressing different proteomes could generate different class I-associated peptide repertoires. A large number of peptides have been sequenced from HLA class I alleles, mostly from lymphoid cells. On the other hand, T cell immunotherapy is a goal in the fight against cancer, but the identification of T cell epitopes is a laborious task. Proteomic techniques allow the definition of putative T cell epitopes by the identification of HLA natural ligands in tumor cells. In this study, we have compared the HLA class I-associated peptide repertoire from the hepatocellular carcinoma (HCC) cell line SK-Hep-1 with that previously described from lymphoid cells. The analysis of the peptide pool confirmed that, as expected, the peptides from SK-Hep-1 derive from proteins localized in the same compartments as in lymphoid cells. Within this pool, we have identified 12 HLA class I peptides derived from HCC-related proteins. This confirms that tumor cell lines could be a good source of tumor associated antigens to be used, together with MS, to define putative epitopes for cytotoxic T cells from cancer patients.     

Influence diagnostics in regression with complex designs through conditional bias

One of the areas of Statistics in which the influence analysis has been widely studied is the multiple linear regression model. Nevertheless, the influence diagnostics proposed in this context cannot be applied to regression in complex survey, under randomized inference, since the i.i.d. case does not incorporate any probability weighting or population structure, such as clustering, stratification or measures of size into the analysis. In this paper we introduce some influence diagnostics in regression in complex survey. They are built on the conditional bias concept (Moreno-Rebollo et al., 1999). We emphasize the similarities and differences of the proposed measures with respect to the existing ones for the i.i.d. case. Research partly supported by the Spanish MCYT grant BFM2001-3844 and Spanish MEC grant MTM2004-0111433.     

Characterisation of chickpea flour‐based gluten‐free batters and muffins with added biopolymers: rheological,physical and sensory properties

Chickpea flour (CF)‐based muffin formulations were made with CF alone and with added biopolymers [whey protein (WP), xanthan gum (XG) and inulin (INL)] to evaluate their suitability to be a wheat flour (WF) substitute in muffins. Structural characteristics of the batters and muffins were studied by means of rheometry, microscopy, physicochemical properties, and texture and sensory analysis. Partial replacement of CF with XG, alone (at 0.5 and 1%) or blended with either WP or INL, significantly increased the batter viscoelasticity as denser matrices developed; moreover, the muffins with XG added at 1% had similar hardness to wheat gluten muffins. The replacement of WF decreased the springiness, cohesiveness, chewiness, resilience and specific volume of the muffin. However, baked muffins with added XG also showed higher sensory sponginess and moisture associated with numerous air bubbles in the batter and were perceived to be easier to swallow and to have better general appearance.     

How much nitrogen is fixed by biological symbiosis in tropical dry forests? 2. Herbs

Although biological nitrogen fixation (BNF) is considered the main input of N in mature and regenerating native tropical vegetation, it has seldom been quantified. Biomass and N accumulation and fixation were determined for spontaneously occurring herbaceous species in caatinga areas in four regeneration stages (2, 17, 39 and >50?years after abandonment from agricultural use). BNF was estimated using the ¹⁵N natural-abundance method. The 2-year regeneration area had the highest total herb (6,355?kg?ha^?1) and legume (262?kg?ha^?1) biomass production, N stocks (82?kg?ha^?1) and fixed N (5.0?kg?ha^?1). N₂-fixing legumes (nine species in the sampled area) contributed over 97?% of legume biomass in all areas. Macroptilium gracile added the largest amount of N (3.9?kg?ha^?1 in the 2-year regeneration area) because of its large biomass production (205?kg?ha^?1), although it was not the species with the highest proportion of fixed N (76?%). All of the N₂-fixing species obtained large proportions of their N from symbiosis, most of them more than 50?%.However, the amounts of fixed N per unit area were relatively low (0.22?C5.00?kg?ha^?1) because the biomass of N₂-fixing species was always less than 5?% of the total herb biomass.     

Software for simulating dichromatic perception of video streams

We have designed a configurable stand‐alone Matlab‐based software to simulate dichromatic perception of video streams. The algorithm used is an extension for video streams of the “corresponding pair algorithm” by Capilla and coworkers for simulation of dichromatic perception of images. The software allows the user to upload a video sequence and to process it using different dichromatic color vision models and viewing conditions. The output video may be generated in different spatial and temporal resolutions and file formats. The functions for Matlab environment and a stand‐alone application may be downloaded from the Repository of the University of Alicante. © 2013 Wiley Periodicals, Inc. Col Res Appl, 39, 486–491, 2014     

Texture Prediction in Intact Green Asparagus by Near Infrared (NIR) Spectroscopy,Assaying Linear and Non-linear Regression Strategies

Texture-related parameters were assessed in intact green asparagus at harvest and during postharvest storage using near-infrared spectroscopy combined with MPLS and LOCAL algorithms. Three spectrophotometers were evaluated for this purpose: a monochromator (range, 400–2,500 nm), a diode-array Vis–NIR spectrophotometer (range, 400–1,700 nm), and a handheld micro-electro-mechanical system (MEMS) spectrophotometer (range, 1,600–2,400 nm). Three hundred green asparagus spears (cv. “Grande”) were used to obtain calibration models based on reference data and NIR data. Results for maximum shear force showed that LOCAL algorithm improved the predictive capacity of models constructed using all three NIRS instruments, increasing r ² by 24, 16, and 56 % and reducing the SEP(c) values by 11, 8, and 14 %, respectively. For cutting energy, the LOCAL also improved the predictive capacity of the models (r ² increased by 3 % for the monochromator and the diode-array instrument and by 6 % for the MEMS device; and the SEP(c) decreased by 3 % in the three instruments). It is worth noting that while the monochromator and diode-array instruments displayed similar predictive capacity for the parameters tested, the MEMS instrument achieved slightly poorer results but has clear advantages for the measurement of texture in intact asparagus, being economical, portable, and easy to use in situ.     

Technological Implications of Modifying the Extent of Cell Wall-Proanthocyanidin Interactions Using Enzymes

The transference and reactivity of proanthocyanidins is an important issue that affects the technological processing of some fruits, such as grapes and apples. These processes are affected by proanthocyanidins bound to cell wall polysaccharides, which are present in high concentrations during the processing of the fruits. Therefore, the effective extraction of proanthocyanidins from fruits to their juices or derived products will depend on the ability to manage these associations, and, in this respect, enzymes that degrade these polysaccharides could play an important role. The main objective of this work was to test the role of pure hydrolytic enzymes (polygalacturonase and cellulose) and a commercial enzyme containing these two activities on the extent of proanthocyanidin-cell wall interactions. The results showed that the modification promoted by enzymes reduced the amount of proanthocyanidins adsorbed to cell walls since they contributed to the degradation and release of the cell wall polysaccharides, which diffused into the model solution. Some of these released polysaccharides also presented some reactivity towards the proanthocyanidins present in a model solution.     

Production of Methyl Oleate in Reactive‐Separation Systems

The esterification of oleic acid and methanol using sulfuric acid as a homogeneous catalyst is studied in reactive‐separation systems. The conversion of the free fatty acid was investigated in two different experiments with the molar ratio of methanol/oleic acid, amount of catalyst, temperature, and reaction time as variables. The conversion of the free fatty acid was found to depend strongly on the molar ratio of methanol/oleic acid. The reaction time had a direct effect on the conversion of the free fatty acid, and this conversion decreased with higher temperature. These results were valuable for a preliminary study on biodiesel production, using an acid homogeneous catalyst in a reactive dividing‐wall distillation column.     

Grading and color evolution of apples using RGB and hyperspectral imaging vision cameras

The potential of RGB digital imaging and hyperspectral imaging (900–1700 nm) was evaluated for discriminating maturity level in apples under different storage conditions along the shelf-life. Segmentation, preprocessing and partial least squares-discriminant analysis (PLS-DA) were used for hyperspectral data analysis, while illumination correction, dimensionality reduction and linear discriminant analysis (LDA) were used for RGB data analysis. The results showed that hyperspectral discrimination classified different storage regimes better than RGB, with an overall success rate of 95.83%. In addition, color evolution of apples during shelf-life under different storage regimes was modeled using RGB zero and first order regression models, fitting better to a first order kinetic model.