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.     

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.     

Role and distribution of different Ba-containing phases in supported Pt–Ba NSR catalysts

Pt–Ba/MeO (where MeO = Al₂O₃, CeO₂, SiO₂ and ZrO₂) NO _x storage-reduction catalysts with Ba-loading varying from 0 wt.% to 28 wt.% were investigated concerning stability of Ba phases and NO _x storage-reduction efficiency. For Pt–Ba/Al₂O₃ three different Ba-containing phases with different thermal stability are distinguished based on their interaction with the support. The relative concentration of these phases varies with the Ba-loading and NO _x storage tests indicated that the BaCO₃ phase decomposing between 400 °C and 800 °C (LT-BaCO₃) is the most efficient Ba containing phase for NO _x storage. Similar investigations of Pt–Ba catalysts supported on CeO₂, SiO₂ and ZrO₂ showed that the relative amount of LT-BaCO₃ phase depends also on the support material. NO _x storage measurements confirmed a correlation between the concentration of LT-BaCO₃ and NO _x storage efficiency. Basicity and textural properties of the support are identified as crucial parameters for efficient NO _x storage catalysts.     

Simple approach for the plasma treatment of polymeric membranes and investigation of the aging effect

The modification of the surface characteristics after treatment with plasma in polymeric materials, such as the aging phenomenon, calls the attention of research in the area of nonthermal plasma technology. In this work, a direct treatment with dielectric-barrier discharge plasma was used on the surfaces of ultrafiltration membranes. The measurements of the contact angle with water, attenuated total reflectance accessory, zeta potential, atomic force microscopy and scanning electron microscopy-MEV were performed on the surfaces to verify changes after plasma treatment and to understand the occurrence and timing of the plasma aging effect. In the analysis of the membrane performance, hydraulic permeation and protein retention tests were performed. The results showed an improvement in wettability and hydrophilic properties in the post-treated membranes. The study of reversibility/aging of the post-plasma surface is important for research that deals with the modification of polymeric membranes. Changes in surface morphology, topography and wettability of the membranes were observed up to seven days after treatment, with a tendency to return to the initial characteristics of the membranes.     

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.