An integrated system to remote monitor and control anaerobic wastewater treatment plants through the internet.

The TELEMAC project brings new methodologies from the Information and Science Technologies field to the world of water treatment. TELEMAC offers an advanced remote management system which adapts to most of the anaerobic wastewater treatment plants that do not benefit from a local expert in wastewater treatment. The TELEMAC system takes advantage of new sensors to better monitor the process dynamics and to run automatic controllers that stabilise the treatment plant, meet the depollution requirements and provide a biogas quality suitable for cogeneration. If the automatic system detects a failure which cannot be solved automatically or locally by a technician, then an expert from the TELEMAC Control Centre is contacted via the internet and manages the problem.     

Physical attractiveness and self-perception of mental disorder.

Prior research has reported a relation between physical attractiveness and severity of mental disorder, with less attractive people being more maladjusted. However, because these two variables have been measured simultaneously, it has not been possible to separate cause from effect. To clarify this question, in this study we first measured physical attractiveness, social competence, and perceived risk of developing a mental disorder in 280 college women. Seven months later, we measured the subjects' self-perception of having a mental disorder. Women who were more attractive were higher in social competence and lower in perceived risk of mental disorder. More attractive women were also lower in self-perception of mental disorder 7 months later. This relation between attractiveness and self-perception of mental disorder remained significant even after controlling for the Time 1 measures (social competence, perceived risk of mental disorder, and age). The implications of these findings for the hypothesized role of attractiveness in the determination of adjustment are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Broadband frequency-domain electromagnetic analysis and automatic extraction of Spice-compatible equivalent circuits

A very simple and effective algorithm able to predict the frequency response of a multiport device over a wide band, starting from the electromagnetic analysis at some spot frequencies, is derived. Data obtained by the proposed procedure are further processed to extract a Foster's type, lumped element, equivalent circuit, suitable for use as a Spice model of the device.     

Dual three-phase induction motor drive with digital current control in the stationary reference frame

Among different multiphase motor drive solutions, one of the most widely discussed is the voltage source inverter (VSI) fed dual three-phase induction machine. Over the years, various topics pertinent to this specific motor drive system have been investigated in considerable depth and, more recently, various reports on real-world applications have emerged. In this paper, a drive system that has been developed specifically for electrical vehicles is described. For vector control purposes, the drive was modeled using an approach that is based on the vector space decomposition technique since it directly leads to the proposed current control method in the stationary reference frame.     

Forecasting peak air pollution levels using NARX models

Air pollution has a negative impact on human health. For this reason, it is important to correctly forecast over-threshold events to give timely warnings to the population. Nonlinear models of the nonlinear autoregressive with exogenous variable (NARX) class have been extensively used to forecast air pollution time series, mainly using artificial neural networks (NNs) to model the nonlinearities. This work discusses the possible advantages of using polynomial NARX instead, in combination with suitable model structure selection methods. Furthermore, a suitably weighted mean square error (MSE) (one-step-ahead prediction) cost function is used in the identification/learning process to enhance the model performance in peak estimation, which is the final purpose of this application. The proposed approach is applied to ground-level ozone concentration time series. An extended simulation analysis is provided to compare the two classes of models on a selected case study (Milan metropolitan area) and to investigate the effect of different weighting functions in the identification performance index. Results show that polynomial NARX are able to correctly reconstruct ozone concentrations, with performances similar to NN-based NARX models, but providing additional information, as, e.g., the best set of regressors to describe the studied phenomena. The simulation analysis also demonstrates the potential benefits of using the weighted cost function, especially in increasing the reliability in peak estimation.     

Tartaglia-Pascal’s triangle: a historical perspective with applications

The aim of this paper is to provide a historical perspective of Tartaglia-Pascal’s triangle with its relations to physics, finance, and statistical signal processing. We start by introducing Tartaglia’s triangle and its numerous properties. We then consider its relationship with a number of topics: the Newton binomial, probability theory (in particular with the Gaussian probability density function, pdf), the Fibonacci sequence, the heat equation, the Schrödinger equation, the Black–Scholes equation of mathematical finance and stochastic filtering theory. Thus, the main contribution of this paper is to present a systematic review of the triangle properties, its connection to statistical theory, and its numerous applications. The paper has mostly a scientific-educational character and is addressed to a wide circle of readers. Sections 7 and 8 are more technical; thus, they may be of interest to more expert readers.     

A Comparison of Network-Based Methods for Drug Repurposing along with an Application to Human Complex Diseases

Drug repurposing strategy, proposing a therapeutic switching of already approved drugs with known medical indications to new therapeutic purposes, has been considered as an efficient approach to unveil novel drug candidates with new pharmacological activities, significantly reducing the cost and shortening the time of de novo drug discovery. Meaningful computational approaches for drug repurposing exploit the principles of the emerging field of Network Medicine, according to which human diseases can be interpreted as local perturbations of the human interactome network, where the molecular determinants of each disease (disease genes) are not randomly scattered, but co-localized in highly interconnected subnetworks (disease modules), whose perturbation is linked to the pathophenotype manifestation. By interpreting drug effects as local perturbations of the interactome, for a drug to be on-target effective against a specific disease or to cause off-target adverse effects, its targets should be in the nearby of disease-associated genes. Here, we used the network-based proximity measure to compute the distance between the drug module and the disease module in the human interactome by exploiting five different metrics (minimum, maximum, mean, median, mode), with the aim to compare different frameworks for highlighting putative repurposable drugs to treat complex human diseases, including malignant breast and prostate neoplasms, schizophrenia, and liver cirrhosis. Whilst the standard metric (that is the minimum) for the network-based proximity remained a valid tool for efficiently screening off-label drugs, we observed that the other implemented metrics specifically predicted further interesting drug candidates worthy of investigation for yielding a potentially significant clinical benefit.     

Optimization of spray drying process of Sargassum muticum color extract

ABSTRACT

Sargassum muticum is categorized as a brown seaweed species which has been used as a dye fabric colorant in certain regions of Asia. The brown extracts of S. muticum also have antioxidant properties, which could enhance the color and nutrients in food products. However, the color extract is unstable, and also limits the application. This study was performed to encapsulate the color extract with maltodextrin and stabilize the color extract by spray drying technique using combinations of various levels of inlet temperature and feed flow rate. Initially, S. muticum powder was analyzed for moisture content, water activity, solubility, and color properties for optimization purposes. This study showed that the optimum inlet temperature and feed flow rate of the spray drying process to produce good-quality, stable, and acceptable powder properties were at 140°C and 3?rpm, respectively, with 4% of maltodextrin. Then, the powder was analyzed for density, compressibility index, hygroscopicity, particle size, and antioxidant properties. This study represents an interesting food additive to be incorporated in functional food due to the attractive brown colorant and the presence of antioxidants.     

Corrosion of zinc in simulated carbonated concrete pore solutions

The electrochemical behaviour of pure Zn and galvanized steel in solutions simulating the pore solution of carbonated concrete has been studied by means of potentiodynamic polarization tests and polarization resistance measurements. Pure Zn was chosen because it simulates well the behaviour of galvanized steel, yielding more reproducible results. The effect of different degrees of carbonation and the presence of different chloride contents in the simulated pore solutions was investigated. Results show that at a given pH (about 9.5) the corrosion susceptibility of Zn depends on anions concentration (carbonate and bicarbonate). The results obtained in simulated carbonated concrete pore solutions show that with low anion concentration Zn does not passivate while in presence of high levels of carbonate and bicarbonate the corrosion resistance is improved. Besides, the presence of chloride increases the corrosion susceptibility.