A rate adaptive bit-loading algorithm for in-building power-line communications based on DMT-modulated systems

This paper deals with a variable rate discrete multitone modulation system for broadband power-line communications, based on the bit-loading algorithm proposed by Leke and Cioffi. In the proposed system a suitable least mean square channel estimator is considered, which is based on the insertion of a training sequence (TS). The proposed approach will be compared with the ideal channel estimates, showing its effectiveness. Moreover, different TS lengths will be compared. The system performance, expressed in terms of bit rate and bit-error rate, is derived by simulation with and without estimation errors. The propagation environment has been assumed as a frequency-selective multipath fading channel with additive colored Gaussian noise, according to the in-building networks model.     

In vivo roles of receptor tyrosine kinases and cytokine receptors in early thymocyte development

The early phases of T-cell development require both cell-cell interactions and soluble factors provided by stromal cells within the thymic microenvironment. Still, the precise nature of the signals delivered in vivo by cytokines (resulting in survival, proliferation or differentiation) remains unclear. Recent studies using mice deficient in cytokines or in their receptors have helped to identify essential signaling pathways required for the development of intrathymic precursors to mature alpha beta and gamma delta T cells. In addition, cytokine requirements for the development of natural killer cells were revealed in such mutants. The results obtained demonstrate that the development of all classes of lymphocytes (natural killer, gamma delta T cells and alpha beta T cells) is cytokine dependent, but the specific requirements differ for each lineage.     

Robust Algorithms for Preemptive Scheduling

Preemptive scheduling problems on parallel machines are classic problems. Given the goal of minimizing the makespan, they are polynomially solvable even for the most general model of unrelated machines. In these problems, a set of jobs is to be assigned to run on a set of m machines. A job can be split into parts arbitrarily and these parts are to be assigned to time slots on the machines without parallelism, that is, for every job, at most one of its parts can be processed at each time. Motivated by sensitivity analysis and online algorithms, we investigate the problem of designing robust algorithms for constructing preemptive schedules. Robust algorithms receive one piece of input at a time. They may change a small portion of the solution as an additional part of the input is revealed. The capacity of change is based on the size of the new piece of input. For scheduling problems, the supremum ratio between the total size of the jobs (or parts of jobs) which may be re-scheduled upon the arrival of a new job j, and the size of j, is called migration factor. We design a strongly optimal algorithm with the migration factor $1-\frac{1}{m}$ for identical machines. Strongly optimal algorithms avoid idle time and create solutions where the (non-increasingly) sorted vector of completion times of the machines is lexicographically minimal. In the case of identical machines this results not only in makespan minimization, but the created solution is also optimal with respect to any ? _p norm (for p>1). We show that an algorithm of a smaller migration factor cannot be optimal with respect to makespan or any other ? _p norm, thus the result is best possible in this sense as well. We further show that neither uniformly related machines nor identical machines with restricted assignment admit an optimal algorithm with a constant migration factor. This lower bound holds both for makespan minimization and for any ? _p norm. Finally, we analyze the case of two machines and show that in this case it is still possible to maintain an optimal schedule with a small migration factor in the cases of two uniformly related machines and two identical machines with restricted assignment.     

Occurrence patterns of alien freshwater turtles in a large urban pond ‘Archipelago’ (Rome,Italy): Suggesting hypotheses on root causes

The patterns of the occurrence and distribution of alien freshwater turtle species in an urban pond archipelago (Rome, Italy) were analysed, with the aim of exploring the role of a set of factors (type of ponds, landscape context, size area, distance from the nearest road) with a generalized linear model approach. A total of 311 ponds subdivided in three types (fountains, small basins, lakes) embedded in different landscape contexts (public parks, private parks, urban areas) at differing distances from the nearest road were sampled. Six non‐native freshwater turtle species in 31 sites were recorded (9.97%). Lakes exhibited the highest occurrence rates of alien freshwater turtles, compared to small basins and fountains. Freshwater turtle species in urbanized areas were only observed in parks (both public and private). In both the public and private parks, the lakes exhibited the highest percentage of occupied sites, with fountains being the lowest. A direct and significant relationship was observed between pond size and species richness. The distance from the nearest road did not appear to affect species richness. A first interpretation of the data from this study facilitated the postulation of two a posteriori hypotheses that should be tested, as follows: (i) the causal process of turtle release is random, and the rate of extinction (and recapture) is higher in smaller ponds, thus producing the observed pattern; and (ii) the turtle release is not random, and people actively select the ponds they consider more suitable for their pet animals. In this study, it appears the lakes were perceived by those who abandon their pets as the most ecologically suitable habitats among other pond types to accommodate the different species of turtles. Knowledge of people's attitudes in regard to releasing pet animals also might assist managers of public green spaces to develop strategies aimed to preserve local biodiversity, and to educate the public about the conservation issue represented by the alien species.     

A large-displacement 65Pb(Mg1/3Nb2/3)O3–35PbTiO3/Pt bimorph actuator prepared by screen printing

In this paper we present a novel approach to preparing large-displacement 65Pb(Mg_1/3Nb_2/3)O₃–35PbTiO₃/Pt (65/35 PMN–PT/Pt) bimorph actuators. These “substrate-free”, bending-type actuators were prepared by screen-printing the 65/35 PMN–PT and Pt thick-film pastes as the electrodes on alumina substrates. After this screen printing and the subsequent firing the 65/35 PMN–PT/Pt composites were peeled off from the substrates. Displacements of nearly 100 μm at 18 V were achieved for actuators with dimensions of 1.8 cm × 2.5 mm × 50 μm for the 65/35 PMN–PT layer. The normalized displacement (the displacement per unit length) was 40 μm/cm at 18 V. The experimental results together with a computation procedure were used to obtain the material parameters for a finite-element analysis of the 65/35 PMN–PT/Pt bimorph actuators.     

Intrusion detection for mobile devices using the knowledge-based, temporal abstraction method

In this paper, a new approach for detecting previously unencountered malware targeting mobile device is proposed. In the proposed approach, time-stamped security data is continuously monitored within the target mobile device (i.e., smartphones, PDAs) and then processed by the knowledge-based temporal abstraction (KBTA) methodology. Using KBTA, continuously measured data (e.g., the number of sent SMSs) and events (e.g., software installation) are integrated with a mobile device security domain knowledge-base (i.e., an ontology for abstracting meaningful patterns from raw, time-oriented security data), to create higher level, time-oriented concepts and patterns, also known as temporal abstractions. Automatically-generated temporal abstractions are then monitored to detect suspicious temporal patterns and to issue an alert. These patterns are compatible with a set of predefined classes of malware as defined by a security expert (or the owner) employing a set of time and value constraints. The goal is to identify malicious behavior that other defensive technologies (e.g., antivirus or firewall) failed to detect. Since the abstraction derivation process is complex, the KBTA method was adapted for mobile devices that are limited in resources (i.e., CPU, memory, battery). To evaluate the proposed modified KBTA method a lightweight host-based intrusion detection system (HIDS), combined with central management capabilities for Android-based mobile phones, was developed. Evaluation results demonstrated the effectiveness of the new approach in detecting malicious applications on mobile devices (detection rate above 94% in most scenarios) and the feasibility of running such a system on mobile devices (CPU consumption was 3% on average).