Using maximal spanning trees and word similarity to generate hierarchical clusters of non-redundant RSS news articles

RSS news articles that are either partially or completely duplicated in content are easily found on the Internet these days, which require Web users to sort through the articles to identify non-redundant information. This manual-filtering process is time-consuming and tedious. In this paper, we present a new filtering and clustering approach, called FICUS, which starts with identifying and eliminating redundant RSS news articles using a fuzzy set information retrieval approach and then clusters the remaining non-redundant RSS news articles according to their degrees of resemblance. FICUS uses a tree hierarchy to organize clusters of RSS news articles. The contents of the respective clusters are captured by the representative keywords from RSS news articles in the clusters so that searching and retrieval of similar RSS news articles is fast and efficient. FICUS is simple, since it uses the pre-defined word-correlation factors to determine related (words in) RSS news articles and filter redundant ones, and is supported by well-known and yet simple mathematical models, such as the standard deviation, vector space model, and probability theory, to generate clusters of non-redundant RSS news articles. Experiments performed on (test sets of) RSS news articles on various topics, which were downloaded from different online sources, verify the accuracy of FICUS on eliminating redundant RSS news articles, clustering similar RSS news articles together, and segregating different RSS news articles in terms of their?contents. In addition, further empirical studies show that FICUS outperforms well-known approaches adopted for clustering RSS news articles.     

Engagement in the course of programming in higher education through the use of gamification

Universal Access in the Information Society - Programming learning in college education is hard for students. Consequently, strategies are required to boost significant learning as well as...     

Changes in body composition in lactating adolescent mothers

We assessed changes in body composition in lactating adolescent mothers living under unfavorable socioeconomic and sanitary conditions. A total of 17 healthy primiparous adolescents under 17 years of age attending the Maternity Hospital of the city of La Plata, Argentina, were followed at 4 time points (15 days and 3, 6 and 12 months postpartum) to assess, a) dietary intake, b) practice of physical activity, c) nutritional condition (weight, height, body mass index [BMI] according to age, and body composition by the sum of skinfold measurements), d) characteristics of lactation, and e) growth parameters of the child. The mean age of adolescents was 15.06 +/- 0.66 years (mean menarchal age, 11.59 +/- 0.80 years). All adolescents breastfed up to 12 months postpartum, and maternal milk covered above 80% the baby intake (mean 7.06 +/- 2.54 breast feeds/day). While the daily intake of nutrients by adolescent mothers was constant up to 6 months postpartum, there was a modest decrease in that of proteins, carbohydrates and lipids 15 days and 12 months postpartum. The decrease in energetic intake during the same period was significant (p < 0.05). The practice of physical activity was classified as moderate during the follow-up period. Whereas mean basal percent of fat body mass (FBM) was 29.85 +/- 2.87, and decreased significantly at 6 (27.2% +/- 3.9%; p = 0.02) and 12 (26.1% +/- 3.9%; p = 0.002) months postpartum, changes in lean body mass (LBM) were not significant. In conclusion, lactating adolescents maintained LBM, whereas weight, FBM and BMI decreased markedly from 3 months postpartum.     

Exploiting the wisdom of social connections to make personalized recommendations on scholarly articles

Existing scholarly publication recommenders were designed to aid researchers, as well as ordinary users, in discovering pertinent literature in diverse academic fields. These recommenders, however, often (i) depend on the availability of users’ historical data in the form of ratings or access patterns, (ii) generate recommendations pertaining to users’ (articles included in their) profiles, as oppose to their current research interests, or (iii) fail to analyze valuable user-generated data at social sites that can enhance their performance. To address these design issues, we propose PReSA, a personalized recommender on scholarly articles. PReSA recommends articles bookmarked by the connections of a user U on a social bookmarking site that are not only similar in content to a target publication P currently of interest to U but are also popular among U’s connections. PReSA (i) relies on the content-similarity measure to identify potential academic publications to be recommended and (ii) uses only information readily available on popular social bookmarking sites to make recommendations. Empirical studies conducted using data from CiteULike have verified the efficiency and effectiveness of (the recommendation and ranking strategies of) PReSA, which outperforms a number of existing (scholarly publication) recommenders.     

Age and Season Affect Chemical Discrimination of Liolaemus bellii Own Space

We explored chemical discrimination of own vs. novel space by different age classes (neonates, juveniles, and adults) of the lizard Liolaemus bellii, during pre- and post-hibernation seasons. We recorded the number of tongue flicks (TF) lizards produced during 10 min in their own or a novel enclosure. Age class and season affected chemical discrimination. Only adults and neonates discriminated their own space, albeit using different strategies: while adults made fewer TF in their own enclosure, neonates made more TF in their own enclosure. This difference was interpreted in terms of different requirements for discrimination of individuals during their lives. Increased chemical exploration by juveniles and adults at the onset of the post-hibernation season was associated with food-searching and reproductive behaviors.     

Modification of titanium surfaces by adding antibiotic-loaded PHB spheres and PEG for biomedical applications

Novel researches are focused on the prevention and management of post-operative infections. To avoid this common complication of implant surgery, it is preferable to use new biomaterials with antibacterial properties. Therefore, the aim of this work is to develop a method of combining the antibacterial properties of antibiotic-loaded poly(3-hydroxybutyrate) (PHB) nano- and micro-spheres and poly(ethylene glycol) (PEG) as an antifouling agent, with titanium (Ti), as the base material for implants, in order to obtain surfaces with antibacterial activity. The Ti surfaces were linked to both PHB particles and PEG by a covalent bond. This attachment was carried out by firstly activating the surfaces with either Oxygen plasma or Sodium hydroxide. Further functionalization of the activated surfaces with different alkoxysilanes allows the reaction with PHB particles and PEG. The study confirms that the Ti surfaces achieved the antibacterial properties by combining the antibiotic-loaded PHB spheres, and PEG as an antifouling agent.     

Accelerating oil reservoir simulations using POD on the fly

A reduced order model (ROM) is presented for the long‐term calculation of subsurface oil/water flows. As in several previous ROMs in the field, the Newton iterations in the full model (FM) equations, which are implicit in time, are projected onto a set of modes obtained by applying proper orthogonal decomposition (POD) to a set of snapshots computed by the FM itself. The novelty of the present ROM is that the POD modes are (i) first calculated from snapshots computed by the FM in a short initial stage, and then (ii) updated on the fly along the simulation itself, using new sets of snapshots computed by the FM in even shorter additional runs. Thus, the POD modes adapt themselves to the local dynamics along the simulation, instead of being completely calculated at the outset, which requires a computationally expensive preprocess. This strategy is robust and computationally efficient, which is tested in 10‐ and 30‐year simulations for a realistic reservoir model taken from the SAIGUP project. Copyright © 2016 John Wiley & Sons, Ltd.     

Changes produced in the aroma compounds and structural integrity of basil (Ocimum basilicum L) during drying

The influence of drying on the aroma compounds, from a chemical and sensory standpoint, and on the structural integrity of basil (Ocimum basilicum L) was evaluated. The drying methods tested were oven drying at 45 °C, air drying at room temperature and freeze‐drying. The volatile compounds of fresh and dried basil were extracted and concentrated by simultaneous distillation/extraction and analysed by gas chromatography/mass spectrometry. In all, 27 volatile components were identified, linalool being the major component, followed by eugenol. The total quantity of volatiles of fresh basil decreased considerably during oven drying and freeze‐drying, whereas air drying of basil at room temperature brought about only small losses of volatile components. The cell damage produced on basil leaves during drying was evaluated by scanning electron microscopy. From a sensory standpoint, fresh basil was described as having a fresh, herbaceous and floral odour, while the dried samples had a mentholated, spicy, hay‐like and earthy odour. Copyright © 2004 Society of Chemical Industry