Content-based and collaborative techniques for tag recommendation: an empirical evaluation

The rapid growth of the so-called Web 2.0 has changed the surfers’ behavior. A new democratic vision emerged, in which users can actively contribute to the evolution of the Web by producing new content or enriching the existing one with user generated metadata. In this context the use of tags, keywords freely chosen by users for describing and organizing resources, spread as a model for browsing and retrieving web contents. The success of that collaborative model is justified by two factors: firstly, information is organized in a way that closely reflects the users’ mental model; secondly, the absence of a controlled vocabulary reduces the users’ learning curve and allows the use of evolving vocabularies. Since tags are handled in a purely syntactical way, annotations provided by users generate a very sparse and noisy tag space that limits the effectiveness for complex tasks. Consequently, tag recommenders, with their ability of providing users with the most suitable tags for the resources to be annotated, recently emerged as a way of speeding up the process of tag convergence. The contribution of this work is a tag recommender system implementing both a collaborative and a content-based recommendation technique. The former exploits the user and community tagging behavior for producing recommendations, while the latter exploits some heuristics to extract tags directly from the textual content of resources. Results of experiments carried out on a dataset gathered from Bibsonomy show that hybrid recommendation strategies can outperform single ones and the way of combining them matters for obtaining more accurate results.     

Natural polysaccharides platforms for oral controlled release of ketoprofen lysine salt

Context: Ketoprofen lysinate (KL) is one of the most widely used non-steroidal anti-inflammatory drugs in the symptomatic treatment of some chronic inflammatory diseases. Compared to ketoprofen, KL shows better pharmacokinetics and tolerability. However, due to its short half-life of 1–2?h, a multiple dose regimen is required for oral administration. Thus, the present work deals with its encapsulation in a hydrogel-based system by prilling in order to prolong its activity.

Objective: In this paper, we propose alginate and pectin as carriers and release tailoring agent for the development of hydrogel-based beads for KL retarded and sustained release.

Materials and methods: Beads were produced by a Nisco Encapsulator® using alginate or pectin. Operative variables were optimized to produce beads with desired morphology and size. Solid state properties were analyzed by SEM and DSC. Drug release performance was studied by Pharmacopeia pH-change assay to simulate gastrointestinal environment.

Results and discussion: Prilling technique was successfully used to encapsulate high soluble drugs as KL in polysaccharides-based hydrogels. Pectin proved to be a proper polymer able to encapsulate ketoprofen lysine salt. Formulation (F8) showed good morphological properties and size, high drug content (15.6%) and encapsulation efficiency (93.5%) and promising drug release profiles. Hosting F8 in an acid-resistant capsule (DR^®caps) a delivery platform has been developed to control KL release in a delayed (90?min lag time) and prolonged way (270?min complete release).

Conclusion: The platform may be proposed as potentially useful in the oral administration of NSAIDs in chronic inflammatory diseases affected by circadian rhythm.     

Efficient energy-based embedding models for link prediction in knowledge graphs

We focus on the problem of link prediction in Knowledge Graphs, with the goal of discovering new facts. To this purpose, Energy-Based Models for Knowledge Graphs that embed entities and relations in continuous vector spaces have been largely used. The main limitation in their applicability lies in the parameter learning phase, which may require a large amount of time for converging to optimal solutions. In this article, we first propose an unified view on different Energy-Based Embedding Models. Hence, for improving the model training phase, we propose the adoption of adaptive learning rates. We show that, by adopting adaptive learning rates during training, we can improve the efficiency of the parameter learning process by an order of magnitude, while leading to more accurate link prediction models in a significantly lower number of iterations. We extensively evaluate the proposed learning procedure on a variety of new models: our result show a significant improvement over state-of-the-art link prediction methods on two large Knowledge Graphs, namely WordNet and Freebase.     

Accurate neural model identification of measurement devices

A neural approach to modeling measurement devices is presented. This approach allows the usual components of a measurement apparatus (transducers, filters, amplifiers, analog-to-digital converters, etc.) to be easily modeled by means of suitably trained artificial neural networks. Two applications regarding analog and mixed analog/digital devices are reported, highlighting the peculiarity of this approach and the accuracy that can be obtained.     

Estimation of the daily global solar radiation; Nepal experience

This work focuses on estimation of global solar radiation and, in particular, it explores the effect of precipitation and temperature on solar radiation profile of Kathmandu (Nepal). An accurate knowledge of solar radiation distribution in each particular geographical location is crucial for the promotion of solar energy technology. The best way of knowing the amount of global solar radiation is to install quality instruments at many locations in the given region. This requires their day to day maintenance, recording and calibration, which is very costly in developing countries like Nepal. Thus, the alternative approach is to correlate meteorological measurements with appropriate models and investigate the key parameters. For the research activities the RadEst program has been used. It includes, for evaluating the daily global solar radiation values at a given latitudes, four models which estimate the atmospheric transmissivity by measurements of daily temperature range and precipitations. The model parameters are fitted in 2 years data by iterative procedures. The values obtained by these models are, then, compared with measured radiation data. The paper reports graphical and statistical evaluations suggesting that among the four models, the Modular DCBB is the best model for Kathmandu area. This result is useful for designing solar panels able to maximize the harvesting of solar energy and to reduce the chronic shortage of hydrocarbon fuel that Nepal imports in a significant amount each year.     

Characterization of human skin impedance after electrical treatment for transdermal drug delivery

A measurement technique based on Electrical Impedance Spectroscopy (EIS) aimed at discriminating electrical effects of the electrical treatment from the electrical characteristics of drug delivery in human skin is presented. The technique turns out to be useful as the first and most crucial step in determining the drug delivered into the skin after electrical treatment. After recalling the background of electrical measurements principle and electrical modeling of biological tissues, the proposed measurement procedure is illustrated. Then, experimental tests of in vivo characterization of the procedure are reported, and the obtained results are discussed.     

Modeling the flexural fatigue behavior of glass-fiber-reinforced thermoplastic matrices

A two-parameter model explicitly accounting for the cyclic as well as the mean stress was proposed and tested on the basis of static and fatigue data obtained in four-point bending on a random continuous glass-fiber-reinforced polypropylene. The model is based on residual strength degradation and captures the effect of stress ratio (i.e. the ratio between the minimal and the maximal stress). The experimental data were in excellent agreement with the theoretical predictions, indicating that a fatigue characterization can be achieved with a minimum of experimental tests. Further, the reasonable agreement between the static strength data and the theoretical predictions highlighted the potential and reliability of the model in view of its statistical implementation     

Spectrograph based on a single diffractive element for real-time measurement of circular dichroism

In this study, a novel and simple diffractive spectrographic method for real-time measurements of circular dichroism (CD) is considered from a theoretical and experimental approach. A demonstrator prototype of the CD spectrograph has been developed and its performance has been compared with a commercial phase-modulation CD spectrometer. The main element of the device is a polarization holographic grating, recorded in a thin photosensitive organic film, by two interfering opposite circularly polarized beams. A peculiarity of this grating is that the amplitude of the +1 (-1) order of diffraction is proportional to the right (left) circular polarization component of the incoming beam. Here we demonstrate that the CD spectrum of a specimen can be easily evaluated from the intensities of the diffracted beams. A white light beam passing through the specimen is diffracted from the grating and the intensities of the +/-1 orders of diffraction are measured. Due to the spectral selectivity of the grating, the CD at each wavelength can be evaluated at the same time using two linear array detectors.     

Beta-glucans improve growth, viability and colonization of probiotic microorganisms

Probiotics, prebiotics and synbiotics are frequently-used components for the elaboration of functional food. Currently, most of the commercialized probiotics are limited to a few strains of the genera Bifidobacteria, Lactobacillus and Streptococcus, most of which produce exopolysaccharides (EPS). This suggests that the beneficial properties of these microorganisms may be related to the biological activities of these biopolymers. In this work we report that a 2-substituted-(1,3)-β-d-glucan of non-dairy bacterial origin has a prebiotic effect on three probiotic strains. Moreover, the presence of this β-d-glucan potentiates in vitro adhesion of the probiotic Lactobacillus plantarum WCFS1 to human intestinal epithelial cells.     

Giant vesicles "colonies": a model for primitive cell communities

Current research on the origin of life typically focuses on the self-organisation of molecular components in individual cell-like compartments, thereby bringing about the emergence of self-sustaining minimal cells. This is justified by the fact that single cells are the minimal forms of life. No attempts have been made to investigate the cooperative mechanisms that could derive from the assembly of individual compartments. Here we present a novel experimental approach based on vesicles "colonies" as a model of primitive cell communities. Experiments show that several advantages could have favoured primitive cell colonies when compared with isolated primitive cells. In fact there are two novel unexpected features typical of vesicle colonies, namely solute capture and vesicle fusion, which can be seen as the basic physicochemical mechanisms at the origin of life.