Application of the novel Droplet digital PCR technology for identification of meat species

The authenticity and traceability of meat products are issues of primary importance to ensure food safety. Unfortunately, food adulteration (e.g. the addition of inexpensive cuts to minced meat products) and mislabelling (e.g. the inclusion of meat from species other than those declared) happens frequently worldwide. The aim of this study was to apply a droplet digital PCR assay for the detection and quantification (copies μL⁻¹) of the beef, pork, horse, sheep, chicken and turkey in meat products. The analysis conducted on commercial meat showed the presence of traces of DNA from other animal species than those declared. We show that the method is highly sensitive, specific and accurate (accuracy = 100%). This method could be adopted by competent food safety authorities to verify compliance with the labelling of meat products and to ensure quality and safety throughout the meat supply chain, from primary production to consumption.     

Automated Parallelization of Discrete State-Space Generation

We consider the problem of generating a large state-space in a distributed fashion. Unlike previously proposed solutions that partition the set of reachable states according to a hashing function provided by the user, we explore heuristic methods that completely automate the process. The first step is an initial random walk through the state space to initialize a search tree, duplicated in each processor. Then, the reachability graph is built in a distributed way, using the search tree to assign each newly found state to classes assigned to the available processors. Furthermore, we explore two remapping criteria that attempt to balance memory usage or future workload, respectively. We show how the cost of computing the global snapshot required for remapping will scale up for system sizes in the foreseeable future. An extensive set of results is presented to support our conclusions that remapping is extremely beneficial.     

A method for the preparation of PMMA-SiO2 nanocomposites with high homogeneity

It is possible to optimize the performance of the inorganic-organic composites dispersing the inorganic component in the organic matrix on a nanomiter length scale. If dry the inorganic phase cannot be intimately dispersed during the incorporation in the matrix. When the particle surface is organically modified, and the incorporation is made starting from a liquid dispersion (particles in polymer solution), the resulting composites exhibit an excellent homogeneity. Here, monolithic [poly(methyl methacrylate)/monodisperse silica particles] nanocomposites have been prepared and characterized by scanning electron microscopy (SEM), transmission electron microscopy (TEM), dynamic light scattering (DLS), micro-hardness, and differential scanning calorimetry (DSC).     

Hybrid photocatalytic membranes embedding decatungstate for heterogeneous photooxygenation

The incorporation of decatungstate in polymeric membranes provides new heterogeneous photocatalysts for the oxidation of organic substrates under oxygen atmosphere at 25 °C. Photocatalytic membranes have been prepared yielding polymeric films with a high thermal, chemical and mechanical stability (PVDF, PDMS, Hyflon). Surface spectroscopy techniques including transmittance and reflectance UV-Vis and FT-IR have been used to assess the photocatalyst integrity within the polymeric support. Catalyst screening has been performed under both homogeneous and heterogeneous photooxygenation conditions. The photocatalyst activity has been evaluated in terms of the substrate conversion, turnover numbers, and recycling experiments. A membrane induced selectivity behavior has been evidenced by comparison with homogeneous oxidations.     

PROPAGATION OF GASLESS COMBUSTION FRONTS: NONZERO REACTION RATE IN THE WHOLE DOMAIN

This paper deals with the gasless combustion problem in an infinite one-dimensional medium. The possibility of the existence of steadily propagating reaction waves is stated for system models with nonzero reaction rates everywhere but at the boundaries. Two forms for the chemical reaction rate dependence on the temperature are considered: the classical Arrhenius, and a modified Arrhenius incorporating and ignition temperature. The equations for the steadily propagating waves are studied in the phase-plane of the temperature and its derivative. The analysis first addresses the question of whether steadily propagating waves are admissible. Then bounds for the propagation velocity are sought and found. The results of the closed-form analysis are successfully tested against numerical experiments. Non-steady propagation regimes are also found, and regions in the parameter space associated with different asymptotic dynamical behaviour are identified.     

Post-Event Site Investigation,Monitoring, Stability Analysis,and Modeling of a Gas Pipeline Explosion

This paper describes the results of site investigations, monitoring, stability analyses, and soil-pipe interaction modeling of a built-up slope located near Pineto (Abruzzo Province, Central Italy), where a gas pipeline exploded on March 6th, 2015, due to heavy rains inducing slope movements. The slope is formed by OC clay, covered with an upper 10- to 14-m-thick clayey-sandy silt colluvial layer. The explosion in the upper portion of the slope caused extensive damage to existing buildings and threatened human lives. Soon after the event, a site investigation and monitoring program was carried out. A detailed topographic survey and hydrological data were analyzed in order to characterize possible critical rainfall events. The stability of the slope was analyzed both in pre- and in post-explosion conditions. The profiles of the DMT horizontal stress index K _D helped to identify multiple slip surfaces. Then, the results of the site investigation and stability analyses were used to implement a simplified finite element model aimed to describe the soil-pipeline interaction, taking into account the role of the observed wrinkle in the pipeline. The numerical simulations reveal the crucial role played by the slope movements, and by the wrinkle as well, in inducing the collapse of the pipe.     

Symbolic computation of strongly connected components and fair cycles using saturation

The computation of strongly connected components (SCCs) in discrete-state models is a critical step in formal verification of LTL and fair CTL properties, but the potentially huge number of reachable states and SCCs constitutes a formidable challenge. We consider the problem of computing the set of states in SCCs or terminal SCCs in an asynchronous system. We employ the idea of saturation, which has shown clear advantages in symbolic state-space exploration (Ciardo et al. in Softw Tools Technol Transf 8(1):4–25, 2006; Zhao and Ciardo in Proceedings of 7th international symposium on automated technology for verification and analysis, pp 368–381, 2009), to improve two previously proposed approaches. We use saturation to speed up state exploration when computing each SCC in the Xie-Beerel algorithm, and we compute the transitive closure of the transition relation using a novel algorithm based on saturation. Furthermore, we show that the techniques we developed are also applicable to the computation of fair cycles. Experimental results indicate that the improved algorithms using saturation achieve a substantial speedup over previous BFS algorithms. In particular, with the new transitive closure computation algorithm, up to 10¹⁵⁰ SCCs can be explored within a few seconds.     

Models and Simulations for Portfolio Rebalancing

In 1950 Markowitz first formalized the portfolio optimization problem in terms of mean return and variance. Since then, the mean-variance model has played a crucial role in single-period portfolio optimization theory and practice. In this paper we study the optimal portfolio selection problem in a multi-period framework, by considering fixed and proportional transaction costs and evaluating how much they affect a re-investment strategy. Specifically, we modify the single-period portfolio optimization model, based on the Conditional Value at Risk (CVaR) as measure of risk, to introduce portfolio rebalancing. The aim is to provide investors and financial institutions with an effective tool to better exploit new information made available by the market. We then suggest a procedure to use the proposed optimization model in a multi-period framework. Extensive computational results based on different historical data sets from German Stock Exchange Market (XETRA) are presented.