Chemiotropic behavior of female olive fly (Bactrocera oleae GMEL.) onOlea europaea L

An interpretation is given of a number of observations on the chemiotropic behavior ofBactrocera oleae in connection with olive maceration water and the fly's return to the olive groves after the first summer rains. To this end, the headspace of both maceration water and leaf leaching water, simulating rainfall, were examined. In both cases, the presence of ammonia, which is generally known to attract fruit flies (Diptera, Tephritidae), was detected and, for the first time, in addition to other compounds that are inert for the fly, the presence of styrene was also detected. This aromatic hydrocarbon was found to be a strong attractant. It is shown that both ammonia and styrene are products of the metabolism of microbial flora present on the olive and leaf surface.     

Smooth migration from the GSM system to UMTS for multimedia services

Third generation of mobile systems is now entering the operational phase; European Community ACTS (RACE follow-on) programme just aims at finalizing the plenty of solutions resulting from the European Community RACE programme as well as from several other studies and researches. European manufactures, also deeply involved in the ACTS programme, seem to show a preference for solutions which gradually upgrade the present pan-European GSM successful standard. The underlying concept is the one of asmooth migration from the GSM network to the third generation system, in order to reuse, at least in the first phases of the transition, most of the existing technologies and infrastructures already implemented for the GSM network. In this respect, this paper, by referring to radio interface aspects, proposes a two step evolution: in the first step, a Dynamic Channel Allocation (DCA) strategy with distributed control should be implemented for coping with the high variance of traffic entailed by the reduction of cell dimensions; in the second step, a gradual upgrading of the GSM Base Stations should allow a smooth transition towards the third generation Packet Reservation Multiple Access (PRMA) technique and the provision of broadband services. The paper is partly based upon the work performed by the author in the framework of the RACE project Satellite Integration in the Future Mobile Network (SAINT) and of the European Community ACTS Projects MEDIAN. The opinions herewith reported are not necessarily those of the European Community.     

Excited states of alkali atoms in liquid4He from density functional calculations

Calculations are presented, based on a Density Functional approach, of the first excited states (l=1) of alkali metal atoms (Cs and Na) in liquid ⁴He. We find large departures from the spherical bubble in the liquid⁴He structure when the alkali atom is excited. The shifts from the free atom values of the excitation and emission transition lines are calculated and compared with the experimental results. According to our calculations, the so far unseen radiative deexcitation transition for light alkalis in⁴He may lie in an unexplored infrared region of the spectrum.     

In vivo characterization of renal auto-antigens involved in human auto-immune diseases: the case of membranous glomerulonephritis

Renal auto-immune diseases represent a major source of morbidity in humans. For many years the knowledge on mechanisms of auto-immunity involving the kidney has been uniquely based on animal models. However, these findings often could not be readily translated to humans owing to notably difference in antigen expression by human podocytes. One example is Heymann nephritis (HN), the experimental model of human membranous glomerulonephritis (MGN), which is obtained in rats by injecting antibodies against megalin, a protein that is not present in human glomeruli. Human studies could not be done in the past since sequencing required too much material exceeding what obtainable from tissue biopsies in vivo. Research is now on the way to identify auto-antigens and isolate specific auto-antibodies in humans. New technology developments based on tissue microdissection and proteomical analysis have facilitated the recent discoveries, allowing direct analysis of human tissue in vivo. Major advances on the pathogenesis of MGN, the prototype for the formation and glomerular deposition of auto-antibodies, are now in progress. Two independent groups have, in fact, demonstrated the existence of specific IgG(4) against phospholipase A2 receptor, aldose reductase and Mn-superoxide dismutase in glomerular eluates and in plasma of a prominent part of patients with MGN, suggesting a major role of these proteins as auto-antigens in human MGN. This review will focalize these aspects outlining the contribution of proteomics in most recent developments.     

Finite-time control of discrete-time linear systems: Analysis and design conditions

In this paper we deal with some finite-time control problems for discrete-time, time-varying linear systems. First we provide necessary and sufficient conditions for finite-time stability; these conditions require either the computation of the state transition matrix of the system or the solution of a certain difference Lyapunov inequality. Then we address the design problem. The proposed conditions allow us to find output feedback controllers which stabilize the closed loop system in the finite-time sense; all these conditions can be expressed in terms of LMIs and therefore are numerically tractable, as shown in the example included in the paper.     

Enabling energy-efficient and lossy-aware data compression in wireless sensor networks by multi-objective evolutionary optimization

Nodes of wireless sensor networks (WSNs) are typically powered by batteries with a limited capacity. Thus, energy is a primary constraint in the design and deployment of WSNs. Since radio communication is in general the main cause of power consumption, the different techniques proposed in the literature to improve energy efficiency have mainly focused on limiting transmission/reception of data, for instance, by adopting data compression and/or aggregation. The limited resources available in a sensor node demand, however, the development of specifically designed algorithms. To this aim, we propose an approach to perform lossy compression on single node based on a differential pulse code modulation scheme with quantization of the differences between consecutive samples. Since different combinations of the quantization process parameters determine different trade-offs between compression performance and information loss, we exploit a multi-objective evolutionary algorithm to generate a set of combinations of these parameters corresponding to different optimal trade-offs. The user can therefore choose the combination with the most suitable trade-off for the specific application. We tested our lossy compression approach on three datasets collected by real WSNs. We show that our approach can achieve significant compression ratios despite negligible reconstruction errors. Further, we discuss how our approach outperforms LTC, a lossy compression algorithm purposely designed to be embedded in sensor nodes, in terms of compression rate and complexity.     

Logic based methods for SNPs tagging and reconstruction

SNPs are positions of the DNA sequences where the differences among individuals are embedded. The knowledge of such SNPs is crucial for disease association studies, but even if the number of such positions is low (about 1% of the entire sequence), the cost to extract the complete information is actually very high. Recent studies have shown that DNA sequences are structured into blocks of positions, that are conserved during evolution, where there is strong correlation among values (alleles) of different loci. To reduce the cost of extracting SNPs information, the block structure of the DNA has suggested to limit the process to a subset of SNPs, the so-called Tag SNPs, that are able to maintain the most of the information contained in the whole sequence. In this paper, we apply a technique for feature selection based on integer programming to the problem of Tag SNP selection. Moreover, to test the quality of our approach, we consider also the problem of SNPs reconstruction, i.e. the problem of deriving unknown SNPs from the value of Tag SNPs and propose two reconstruction methods, one based on a majority vote and the other on a machine learning approach. We test our algorithm on two public data sets of different nature, providing results that are, when comparable, in line with the related literature. One of the interesting aspects of the proposed method is to be found in its capability to deal simultaneously with very large SNPs sets, and, in addition, to provide highly informative reconstruction rules in the form of logic formulas.     

Anonymization of moving objects databases by clustering and perturbation

Preserving individual privacy when publishing data is a problem that is receiving increasing attention. Thanks to its simplicity the concept of k-anonymity, introduced by Samarati and Sweeney [1], established itself as one fundamental principle for privacy preserving data publishing. According to the k-anonymity principle, each release of data must be such that each individual is indistinguishable from at least k−1 other individuals.     

A query expansion and user profile enrichment approach to improve the performance of recommender systems operating on a folksonomy

In this paper we propose a query expansion and user profile enrichment approach to improve the performance of recommender systems operating on a folksonomy, storing and classifying the tags used to label a set of available resources. Our approach builds and maintains a profile for each user. When he submits a query (consisting of a set of tags) on this folksonomy to retrieve a set of resources of his interest, it automatically finds further “authoritative” tags to enrich his query and proposes them to him. All “authoritative” tags considered interesting by the user are exploited to refine his query and, along with those tags directly specified by him, are stored in his profile in such a way to enrich it. The expansion of user queries and the enrichment of user profiles allow any content-based recommender system operating on the folksonomy to retrieve and suggest a high number of resources matching with user needs and desires. Moreover, enriched user profiles can guide any collaborative filtering recommender system to proactively discover and suggest to a user many resources relevant to him, even if he has not explicitly searched for them.