Investment using evolutionary learning methods and technical rules

In this paper, I propose a genetic learning approach to generate technical trading systems for stock timing. The most informative technical indicators are selected from a set of almost 5000 signals by a multi-objective genetic algorithm with variable string length. Successively, these signals are combined into a unique trading signal by a learning method. I test the expert weighting solution obtained by the plurality voting committee, the Bayesian model averaging and Boosting procedures with data from the S&P 500 Composite Index, in three market phases, up-trend, down-trend and sideways-movements, covering the period 2000–2006. Computational results indicate that the near-optimal set of rules varies among market phases but presents stable results and is able to reduce or eliminate losses in down-trend periods.     

Information-disturbance tradeoff in estimating a maximally entangled state

We derive the amount of information retrieved by a quantum measurement in estimating an unknown maximally entangled state, along with the pertaining disturbance on the state itself. The optimal tradeoff between information and disturbance is obtained, and a corresponding optimal measurement is provided.     

The Ontology of Products

We speak of products in two senses: in one, we speak of types of products, in the other we speak of the particular objects that are instances of those types. I argue that types of products have the same ontological status as that of material stuffs, like water and gold, which have a non-particular level of existence. I also argue that the relationship between types of products and their instances is logically similar to the relation of constitution, which holds between, say, gold and a ring made of gold. In my approach, types of products are concrete entities, having spatiotemporal properties. This picture fits our commonplace conception of types of products better than alternative approaches according to which types of products are universal, abstract, or mereological entities.     

Quantum dice

In a letter to Born, Einstein wrote  [42]: “Quantum mechanics is certainly imposing. But an inner voice tells me that it is not yet the real thing. The theory says a lot, but does not really bring us any closer to the secret of the ‘old one.’ I, at any rate, am convinced that He does not throw dice.” In this paper we take seriously Einstein’s famous metaphor, and show that we can gain considerable insight into quantum mechanics by doing something as simple as rolling dice. More precisely, we show how to perform measurements on a single die, to create typical quantum interference effects, and how to connect (entangle) two identical dice, to maximally violate Bell’s inequality.     

The rate matching effect: A hidden property of aperiodic stochastic resonance

We study a system S generating Poisson events, and a corresponding dichotomous signal as well, perturbed by a system P, also generating Poisson events and a corresponding dichotomous signal. The rates of events productions for system and perturbation are gS and gP, respectively. We call S events the events produced by the system S and P events those produced by the perturbation P. We show that this simple model reproduces the essence of recent experimental and theoretical results on aperiodic stochastic resonance. More remarkably, this simplified version of aperiodic stochastic resonance allows us to discover a property that has been overlooked by the earlier research work. The rate matching condition gS=gP is the border between two distinctly different conditions: For gS<gP, the P events are attractors of the S events and for gS>gP they become repellers of the S events. The transition from the former to the latter condition is very marked and takes place in a short region of either gS or gP, depending on which is the parameter changed, thereby resulting in a discontinuous transition.     

Colloidal Surface Active Maghemite Nanoparticles for Biologically Safe CrVI Remediation: from Core‐Shell Nanostructures to Pilot Plant Development

The present study is aimed at the exploration of achievable improvements for Cr^VI ex situ and in situ water remediation by using novel naked colloidal maghemite (γ‐Fe₂O₃) nanoparticles (surface active maghemite nanoparticles, SAMNs). The reliability of SAMNs for Cr^VI binding and removal was demonstrated, and SAMN@Cr^VI complex was characterized, as well as the covalent nature of the absorption was unequivocally proved. SAMNs were structurally and magnetically well conserved after Cr^VI binding. Thus, in consideration of their affinity for Cr^VI, SAMNs were exploited in a biological model system, mimicking a real in situ application. The assay evidenced a progressive reduction of revertant colonies of Salmonella typhimurium TA100 strain, as maghemite nanoparticles concentration increased, till the complete suppression of Cr^VI mutagen effect. Finally, an automatic modular pilot system for continuous magnetic removal and recovery of Cr^VI from water is proposed. SAMNs, thanks to their colloidal, binding, and catalytic properties, represent a promising tool as a reliable nanomaterial for water remediation by Cr^VI.     

Spatio-Temporal Variation of the Bacterial Communities along a Salinity Gradient within a Thalassohaline Environment (Saline di Tarquinia Salterns,Italy)

The “Saline di Tarquinia” salterns have been scarcely investigated regarding their microbiological aspects. This work studied the structure and composition of their bacterial communities along the salinity gradient (from the nearby sea through different ponds). The communities showed increasing simplification of pond bacterial diversity along the gradient (particularly if compared to those of the sea). Among the 38 assigned phyla, the most represented were Proteobacteria, Actinobacteria and Bacteroidetes. Differently to other marine salterns, where at the highest salinities Bacteroidetes dominated, preponderance of Proteobacteria was observed. At the genus level the most abundant taxa were Pontimonas, Marivita, Spiribacter, Bordetella, GpVII and Lentibacter. The α-diversity analysis showed that the communities were highly uneven, and the Canonical Correspondence Analysis indicated that they were structured by various factors (sampling site, sampling year, salinity, and sampling month). Moreover, the taxa abundance variation in relation to these significant parameters were investigated by Generalized Linear Models. This work represents the first investigation of a marine saltern, carried out by a metabarcoding approach, which permitted a broad vision of the bacterial diversity, covering both a wide temporal span (two years with monthly sampling) and the entire salinity gradient (from the nearby sea up to the crystallisation ponds).     

Parameters influencing the capacitive behavior of carbon composite electrodes: composition,morphology, electrical conductivity,and surface chemistry

Journal of Solid State Electrochemistry - The interplay and overlapping of several factors determine the capacitive behavior of carbon composite electrodes for capacitive energy storage...     

Ordered mesoporous Co3O4 as highly active catalyst for low temperature CO-oxidation

Cubic ordered mesoporous Co(3)O(4), prepared via the nanocasting pathway using KIT-6 as hard template, was found to be an excellent catalyst for low temperature CO oxidation, with the activity clearly depending on surface area and pore systems of the catalysts.