Wet hydrogen peroxide catalytic oxidation (WHPCO) of organic waste in agro-food and industrial streams

This review discusses the use of iron- or copper-based solid catalysts in the wet oxidation using H₂O₂ as oxidant of organic molecules present in agro-food and industrial waste aqueous streams. After an introduction on the advantages and limits of using wet hydrogen peroxide catalytic oxidation (WHPCO) as opposite to wet air catalytic oxidation (WACO), the contribution shortly analyses recent results in the field in order to evidence new trends and open issues. More specific examples discussed regard the performances of Fe/zeolite and Fe-containing pillared clays in the oxidation of selected molecules (p-coumaric acid, propionic acid) of relevance for the treatment of organic waste from agro-food production (with reference especially to olive oil milling wastewater). The application of WHPCO in the treatment of complex effluents from electronic industry is also shortly discussed.     

Homogeneous versus heterogeneous catalytic reactions to eliminate organics from waste water using H2O2

Homogeneous (Cu²⁺ ions) and heterogeneous (Cu²⁺-pillared clay) Fenton-like catalysts have been compared in the conversion of p-coumaric acid. The performances of the two classes of catalysts are similar for an analogous amount of copper, but there are some relevant differences in terms of (i) the presence of an induction time, (ii) the turnover frequency, (iii) the efficiency in the use of H₂O₂, (iv) the initial attack of p-coumaric acid (hydroxylation on the aromatic ring or oxidative attack on the double bond of the lateral chain), and (v) the effect of dissolved oxygen on the removal of total organic carbon (TOC). These differences were interpreted in terms of reaction network of generation of radical oxygen species and of organics conversion. The possible formation of a surface peroxo adduct coordinated to a copper binulcear site was also evidenced for the solid heterogeneous catalyst.     

On the correspondence between abstract dialectical frameworks and nonmonotonic conditional logics

Annals of Mathematics and Artificial Intelligence - The exact relationship between formal argumentation and nonmonotonic logics is a research topic that keeps on eluding researchers despite recent...     

How the risk of failure in lifetime of tempered glass depends on the size of NiS inclusions and heat soak test duration

The probability of breakage in service lifetime of heat-tempered glass panes contaminated by nickel sulfide inclusions is estimated with a multiscale micromechanically motivated statistical theory, which considers the effects of the heat soak test (HST). Short and long HSTs differently affect the phase transformation of NiS of diverse chemical composition, whose increase in volume can break the glass. The main hypothesis, corroborated by experiments, is that there is a lower limit for the size of NiS stones below which no crack can be initiated from the volumetric expansion. The catastrophic propagation of nucleated fractures in the long term is modeled through a rescaled critical stress intensity factor, which accounts for the subcritical crack propagation and the slow phase transformation of NiS. A parametric analysis evidences how the failure probability is strongly affected by these parameters, depending on the holding time in the HST. Tailored experimental activity is suggested for the proper calibration of the model.     

Collaborative learning in the clouds

Cloud computing has emerged as one of the most highly discussed topics both in the academic community and in the computing industry. While most of the work that has been conducted to explore this field focuses either on establishing the basis for cloud computing or almost exclusively on the issues surrounding security and data privacy, this paper takes the first exploratory step into exploring the actual internal working of cloud computing and demonstrates its viability for organizations, more specifically educational establishments . The paper starts by introducing the most important key clouds computing concepts, including virtualization technologies, Web services and Service Oriented Architectures (SOA), and distributed computing. Light will be then shed on the impact and potential benefits of cloud computing on teaching and learning in educational institutions. The paper closes by describing building a private cloud inside educational institution and highlights its offerings for students, staff and lecturers.     

Landscape-aware location-privacy protection in location-based services

Mobile network providers have developed a variety of location-based services (LBSs), such as friend-finder, point of interest services, emergency rescue and many other safety and security services. The protection of location-privacy has consequently become a key aspect to the success of LBSs, since users consider their own physical location and movements highly privacy-sensitive, and demand for solutions able to protect such an information in a variety of environments. The idea behind location-privacy protection is that the individual should be able to set the level at which the location information is released to avoid undesired exploitation by a potential attacker: one of the approaches to this problem is given by the application of spatial obfuscation techniques, actuated by a trusted agent, and consisting in artificial perturbations of the location information collected by sensing technologies, before its disclosure to third parties. In many situations, however, landscape/map information can help a third party to perform Bayesian inference over spatially obfuscated data and to refine the user’s location estimate up to a violation of the original user’s location-privacy requirements. The goal of this paper is to provide a map-dependent obfuscation procedure that enables the release of the maximum possible user’s location information, that does not lead to a violation of the original user’s location-privacy requirements, even when refined through map-based inference.     

A graph-based framework for model-driven optimization facilitating impact analysis of mutation operator properties

Optimization problems in software engineering typically deal with structures as they occur in the design and maintenance of software systems. In model-driven optimization (MDO), domain-specific models are used to represent these structures while evolutionary algorithms are often used to solve optimization problems. However, designing appropriate models and evolutionary algorithms to represent and evolve structures is not always straightforward. Domain experts often need deep knowledge of how to configure an evolutionary algorithm. This makes the use of model-driven meta-heuristic search difficult and expensive. We present a graph-based framework for MDO that identifies and clarifies core concepts and relies on mutation operators to specify evolutionary change. This framework is intended to help domain experts develop and study evolutionary algorithms based on domain-specific models and operators. In addition, it can help in clarifying the critical factors for conducting reproducible experiments in MDO. Based on the framework, we are able to take a first step toward identifying and studying important properties of evolutionary operators in the context of MDO. As a showcase, we investigate the impact of soundness and completeness at the level of mutation operator sets on the effectiveness and efficiency of evolutionary algorithms.