A Multifrequency Analysis of the Polarized Diffuse Galactic Radio Emission at Degree Scales

The polarized diffuse Galactic radio emission, mainly synchrotron emission, is expected to be one of the most relevant source of astrophysical contamination at low and moderate multipoles in cosmic microwave background polarization anisotropy experiments at frequencies lower then 50 to 100 GHz. We present here preliminary results based on a recent analysis of the Leiden surveys covering about 50% of the sky at low as well as at middle and high Galactic latitudes. By implementing specific interpolation methods to deal with these data, which show a large variation of the sampling across the sky, we produce maps of the polarized diffuse Galactic synchrotron component at frequencies between 408 and 1411 MHz with pixel sizes larger or equal to about 0.92 degrees. We derive the angular power spectrum of this component for the whole covered region and for three patches in the sky significantly oversampled with respect to the average and at different Galactic latitudes. We find multipole spectral indices typically ranging between about -3 and about -1, according to the considered frequency and sky region. At frequencies higher or equal to 610 MHz, the frequency spectral indices observed in the considered sky regions are about -3.5, compatible with an intrinsic frequency spectral index of about -5.8 and a depolarization due to Faraday rotation with a rotation measure RM of about 15 radians per square meter. This implies that the observed angular power spectrum of the polarized signal is about 85% or 20% of the intrinsic one at 1411 MHz or 820 MHz respectively.Comment: 6 pages, 5 figures. to appear in S.Cecchini et al., Astrophysical Polarized Backgrounds, AIP Conf. Proceeding

Complexity in cancer stem cells and tumor evolution: towards precision medicine

In this review, we discuss recent advances on the plasticity of cancer stem cells and highlight their relevance to understand the metastatic process and to guide therapeutic interventions. Recent results suggest that the strict hierarchical structure of cancer cell populations advocated by the cancer stem cell model must be reconsidered since the depletion of cancer stem cells leads the other tumor cells to switch back into the cancer stem cell phenotype. This plasticity has important implications for metastasis since migrating cells do not need to be cancer stem cells in order to seed a metastasis. We also discuss the important role of the immune system and the microenvironment in modulating phenotypic switching and suggest possible avenues to exploit our understanding of this process to develop an effective strategy for precision medicine.Comment: 2 Figures, to appear in Seminars in Cancer Biology, Available online 23 February 201

Self-Adaptive resource allocation for event monitoring with uncertainty in Sensor Networks

Event monitoring is an important application of sensor networks. Multiple parties, with different surveillance targets, can share the same network, with limited sensing resources, to monitor their events of interest simultaneously. Such a system achieves profit by allocating sensing resources to missions to collect event related information (e.g., videos, photos, electromagnetic signals). We address the problem of dynamically assigning resources to missions so as to achieve maximum profit with uncertainty in event occurrence. We consider timevarying resource demands and profits, and multiple concurrent surveillance missions. We model each mission as a sequence of monitoring attempts, each being allocated with a certain amount of resources, on a specific set of events that occurs as a Markov process. We propose a Self-Adaptive Resource Allocation algorithm (SARA) to adaptively and efficiently allocate resources according to the results of previous observations. By means of simulations we compare SARA to previous solutions and show SARA’s potential in finding higher profit in both static and dynamic scenarios

Progressive damage assessment and network recovery after massive failures

After a massive scale failure, the assessment of damages to communication networks requires local interventions and remote monitoring. While previous works on network recovery require complete knowledge of damage extent, we address the problem of damage assessment and critical service restoration in a joint manner. We propose a polynomial algorithm called Centrality based Damage Assessment and Recovery (CeDAR) which performs a joint activity of failure monitoring and restoration of network components. CeDAR works under limited availability of recovery resources and optimizes service recovery over time. We modified two existing approaches to the problem of network recovery to make them also able to exploit incremental knowledge of the failure extent. Through simulations we show that CeDAR outperforms the previous approaches in terms of recovery resource utilization and accumulative flow over time of the critical service

Energy-Efficient selective activation in Femtocell Networks

Provisioning the capacity of wireless networks is difficult when peak load is significantly higher than average load, for example, in public spaces like airports or train stations. Service providers can use femtocells and small cells to increase local capacity, but deploying enough femtocells to serve peak loads requires a large number of femtocells that will remain idle most of the time, which wastes a significant amount of power. To reduce the energy consumption of over-provisioned femtocell networks, we formulate a femtocell selective activation problem, which we formalize as an integer nonlinear optimization problem. Then we introduce GREENFEMTO, a distributed femtocell selective activation algorithm that deactivates idle femtocells to save power and activates them on-the-fly as the number of users increases. We prove that GREENFEMTO converges to a locally Pareto optimal solution and demonstrate its performance using extensive simulations of an LTE wireless system. Overall, we find that GREENFEMTO requires up to 55% fewer femtocells to serve a given user load, relative to an existing femtocell power-saving procedure, and comes within 15% of a globally optimal solution

On the vulnerabilities of voronoi-based approaches to mobile sensor deployment

Mobile sensor networks are the most promising solution to cover an Area of Interest (AoI) in safety critical scenarios. Mobile devices can coordinate with each other according to a distributed deployment algorithm, without resorting to human supervision for device positioning and network configuration. In this paper, we focus on the vulnerabilities of the deployment algorithms based on Voronoi diagrams to coordinate mobile sensors and guide their movements. We give a geometric characterization of possible attack configurations, proving that a simple attack consisting of a barrier of few compromised sensors can severely reduce network coverage. On the basis of the above characterization, we propose two new secure deployment algorithms, named SecureVor and Secure Swap Deployment (SSD). These algorithms allow a sensor to detect compromised nodes by analyzing their movements, under different and complementary operative settings. We show that the proposed algorithms are effective in defeating a barrier attack, and both have guaranteed termination. We perform extensive simulations to study the performance of the two algorithms and compare them with the original approach. Results show that SecureVor and SSD have better robustness and flexibility and excellent coverage capabilities and deployment time, even in the presence of an attac