Monotone first‐order weighted schemes for scalar conservation laws

In this work, we present a monotone first‐order weighted (FORWE) method for scalar conservation laws using a variational formulation. We prove theoretical properties as consistency, monotonicity, and convergence of the proposed scheme for the one‐dimensional (1D) Cauchy problem. These convergence results are extended to multidimensional scalar conservation laws by a dimensional splitting technique. For the validation of the FORWE method, we consider some standard bench‐mark tests of bidimensional and 1D conservation law equations. Finally, we analyze the accuracy of the method with L¹ and L^∞ error estimates. © 2013 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq, 2013     

On k-symmetries of hyperbolic spaces

We determine all the possible pointwise k-symmetric spaces of negative constant curvature. In general, such spaces are not k-symmetric.In fact we show that, for all $n?3$, $k\ne 2$, $H^n$ is not k-symmetric, i.e., for any set of selected k-symmetries, one for each point of $H^n$, the regularity condition does not hold.     

Latent variable models for ordinal data by using the adaptive quadrature approximation

Latent variable models for ordinal data represent a useful tool in different fields of research in which the constructs of interest are not directly observable so that one or more latent variables are required to reduce the complexity of the data. In these cases problems related to the integration of the likelihood function of the model can arise. Indeed analytical solutions do not exist and in presence of several latent variables the most used classical numerical approximation, the Gauss Hermite quadrature, cannot be applied since it requires several quadrature points per dimension in order to obtain quite accurate estimates and hence the computational effort becomes not feasible. Alternative solutions have been proposed in the literature, like the Laplace approximation and the adaptive quadrature. Different studies demonstrated the superiority of the latter method particularly in presence of categorical data. In this work we present a simulation study for evaluating the performance of the adaptive quadrature approximation for a general class of latent variable models for ordinal data under different conditions of study. A real data example is also illustrated.     

New Collections of p-Subgroups and Homology Decompositions for Classifying Spaces of Finite Groups

We define new collections of p-subgroups for a finite group G and p a prime dividing its order. We study the homotopy relations among them and with the standard collections of p-subgroups and determine their ampleness and sharpness properties.     

Optimal advertising strategies with age-structured goodwill

The problem of a firm willing to optimally promote and sell a single product on the market is here undertaken. The awareness of such product is modeled by means of a Nerlove–Arrow goodwill as a state variable, differentiated jointly by means of time and of age of the segments in which the consumers are clustered. The problem falls into the class of infinite horizon optimal control problems of PDEs with age structure that have been studied in various papers either in cases when explicit solutions can be found or using Maximum Principle techniques. Here, assuming an infinite time horizon, we use some dynamic programming techniques in infinite dimension to characterize both the optimal advertising effort and the optimal goodwill path in the long run. An interesting feature of the optimal advertising effort is an anticipation effect with respect to the segments considered in the target market, due to time evolution of the segmentation. We analyze this effect in two different scenarios: in the first, the decision-maker can choose the advertising flow directed to different age segments at different times, while in the second she/he can only decide the activation level of an advertising medium with a given age-spectrum.     

Non-standard Lagrange–Burman methods for the numerical integration of differential equations

We present new non-standard methods based on Mickens' ideas for constructing numerical schemes for differential equations. By analysing his schemes, we were able to give generalized versions by means of Lagrange–Burman expansions. Our generalization provides a theoretical frame to understand non-standard finite difference methods and also to analyse the errors in the approximations. We apply the new non-standard methods to several examples.     

Attenuated total reflection infrared microspectroscopy combined with multivariate analysis: a novel tool to study the presence of cocoa polyphenol metabolites in urine samples

The detection and quantification of polyphenols in biological samples is mainly performed by liquid chromatography in tandem with mass spectrometry (HPLC-MS/MS). This technique requires the use of organic solvents and needs control and maintenance of several MS/MS parameters, which makes the method expensive and time consuming. The main objective of this study was to evaluate, for the first time, the potential of using attenuated total reflection infrared microspectroscopy (ATR-IRMS) coupled with multivariate analysis to detect and quantify phenolic compounds excreted in human urine. Samples were collected from 5 healthy volunteers before and 6, 12 and 24 h after ingestion of 40 g cocoa powder with 250 mL of water or whole milk, and stored at -80 °C. Each sample was centrifuged at 5000 rpm for 10 min and at 4 °C and applied onto grids of a hydrophobic membrane. Spectra were collected in the attenuated total reflection (ATR) mode in the mid-infrared region (4000-800 cm(-1)) and were analyzed by a multivariate analysis technique, soft independent modeling of class analogy (SIMCA). Spectral models showed that IR bands responsible for chemical differences among samples were related to aromatic rings. Therefore, ATR-IRMS could be an interesting and straightforward technique for the detection of phenolic compounds excreted in urine. Moreover, it could be a valuable tool in studies aimed to identify biomarkers of consumption of polyphenol-rich diets.     

Meta-heuristic improvements applied for steel sheet incremental cold shaping

In previous studies, a wrapper feature selection method for decision support in steel sheet incremental cold shaping process (SSICS) was proposed. The problem included both regression and classification, while the learned models were neural networks and support vector machines, respectively. SSICS is the type of problem for which the number of features is similar to the number of instances in the data set, this represents many of real world decision support problems found in the industry. This study focuses on several questions and improvements that were left open, suggesting proposals for each of them. More specifically, this study evaluates the relevance of the different cross validation methods in the learned models, but also proposes several improvements such as allowing the number of chosen features as well as some of the parameters of the neural networks to evolve, accordingly. Well-known data sets have been use in this experimentation and an in-depth analysis of the experiment results is included. 5 $\times $ 2 CV has been found the more interesting cross validation method for this kind of problems. In addition, the adaptation of the number of features and, consequently, the model parameters really improves the performance of the approach. The different enhancements have been applied to the real world problem, an several conclusions have been drawn from the results obtained.     

Removal of sulfonamide antibiotics upon conventional activated sludge and advanced membrane bioreactor treatment

This work reports the removal efficiencies of nine sulfonamides (SAs) and one of their acetylated metabolites during conventional activated sludge (CAS) and membrane bioreactor (MBR) treatments. Two different types of membranes were studied, hollow-fiber membranes and flat-sheet membranes, in two separate pilot plants operating in parallel to a full-scale CAS treatment. A total of 48 water samples and 16 sewage sludge samples were analyzed by liquid chromatography-tandem mass spectrometry. We obtained 100% elimination in the MBR effluents for three SAs (sulfadiazine, sulfadimethoxine, and sulfamethoxypyridazine) and the metabolite. For the rest of the SAs, the removal efficiencies during CAS and MBR treatments were similar and usually below 55%. Sulfamethizole was the most recalcitrant SA, exhibiting negative removal efficiencies in all the treatments investigated. The concentrations of SAs in the different sewage sludge types were also calculated and ranged from 0.01 to 11 ng g(-1). Furthermore, adsorption and biodegradation of SAs in activated sludge were investigated in two sets of batch reactors, which were spiked at high and low concentration (1,000 and 50 ng mL(-1), respectively). All SAs followed a similar trend and, with the exception of sulfathiazole, were not fully eliminated after 25 days of treatment.     

Collagen‐Reinforced Electrospun Silk Fibroin Tubular Construct as Small Calibre Vascular Graft

None of the replacements proposed in the literature for small‐calibre blood vessels (SCBV) fully satisfies the stringent requirements that these grafts have to fulfil. Here, an electrospun silk fibroin tubular construct is hybridized with type I collagen gel to produce a biomimetic SCBV graft with physiologically relevant compliance and burst pressure and optimal cytocompatibility. The hybridization of the two polymers results in the formation of a nanofibrillar hydrated matrix, where the collagen gel enhances the mechanical properties of the SF tubular construct and improves the early response of the material to in vitro cell adhesion and proliferation.