Efficient spectrum scheduling and power management for opportunistic users

International audienceIn this paper, we study the centralized spectrum access and power management for several opportunistic users, secondary users (SUs), without hurting the primary users (PUs). The radio resource manager's objective is to minimize the overall power consumption of the opportunistic system over several orthogonal frequency bands under constraints on the minimum quality of service (QoS) and maximum peak and average interference to the PUs. Given the opposing nature of these constraints, we first study the problem of feasibility, and we provide sufficient conditions and necessary conditions for the existence of a solution. The main challenge lies in the non-convexity of this problem because of the discrete spectrum scheduling: one band can be allocated to at most one SU to avoid interference impairments. To overcome this issue, we use a Lagrangian relaxation technique, and we prove that the discrete solutions of the relaxed problem are the solutions to the initial problem. We propose a projected sub-gradient algorithm to compute the solution, when it exists. Assuming that the channels are drawn randomly from a continuous distribution, this algorithm converges to the optimal solution. We also study a specific symmetric system for which we provide the analytical solution. Our numerical results compare the energy-efficiency of the proposed algorithm with other spectrum allocation solutions and show the optimality of our approach

Online Power Allocation for Opportunistic Radio Access in Dynamic OFDM Networks

International audienceUser mobility has become a key attribute in the design of optimal resource allocation policies for future wireless networks. This has become increasingly apparent in cognitive radio (CR) systems where the licensed, primary users (PUs) of the network must be protected from harmful interference by the network's opportunistic, secondary users (SUs): here, unpre-dictability due to mobility requires the implementation of safety net mechanisms that are provably capable of adapting to changes in the users' wireless environment. In this context, we propose a distributed learning algorithm that allows SUs to adjust their power allocation profile (over the available frequency carriers) " on the fly " , relying only on strictly causal channel state information. To account for the interference caused to the network's PUs, we incorporate a penalty function in the rate-driven objectives of the SUs, and we show that the proposed scheme matches asymptoti-cally the performance of the best fixed power allocation policy in hindsight. Specifically, in a system with S orthogonal subcarriers and transmission horizon T , this performance gap (known as the algorithm's average regret) is bounded from above as O(T −1 log S). We also validate our theoretical analysis with numerical simulations which confirm that the network's SUs rapidly achieve a " no-regret " state under realistic wireless cellular conditions. Moreover, by finetuning the choice of penalty function, the interference induced by the SUs can be kept at a sufficiently low level, thus guaranteeing the PUs' requirements

Online Power Allocation for Opportunistic Radio Access in Dynamic OFDM Networks

International audienceUser mobility has become a key attribute in the design of optimal resource allocation policies for future wireless networks. This has become increasingly apparent in cognitive radio (CR) systems where the licensed, primary users (PUs) of the network must be protected from harmful interference by the network's opportunistic, secondary users (SUs): here, unpre-dictability due to mobility requires the implementation of safety net mechanisms that are provably capable of adapting to changes in the users' wireless environment. In this context, we propose a distributed learning algorithm that allows SUs to adjust their power allocation profile (over the available frequency carriers) " on the fly " , relying only on strictly causal channel state information. To account for the interference caused to the network's PUs, we incorporate a penalty function in the rate-driven objectives of the SUs, and we show that the proposed scheme matches asymptoti-cally the performance of the best fixed power allocation policy in hindsight. Specifically, in a system with S orthogonal subcarriers and transmission horizon T , this performance gap (known as the algorithm's average regret) is bounded from above as O(T −1 log S). We also validate our theoretical analysis with numerical simulations which confirm that the network's SUs rapidly achieve a " no-regret " state under realistic wireless cellular conditions. Moreover, by finetuning the choice of penalty function, the interference induced by the SUs can be kept at a sufficiently low level, thus guaranteeing the PUs' requirements

High Pressure Effects on Thermal Properties of MgO

Using the non-empirical Variational Induced Breathing (VIB) model, the thermal properties of periclase (MgO) under high pressures and temperatures are investigated using molecular dynamics, which includes all anharmonic effects. Equations of state for temperatures up to 3000K and pressures up to 310 GPa were calculated. Bulk modulus, thermal expansivity, Anderson-Gruneisen parameter, thermal pressure, Gruneisen parameter and their pressure and temperature dependencies are studied in order to better understand high pressure effects on thermal properties. The results agree very well with experiments and show that the thermal expansivity decreases with pressure up to about 100 GPa ($\eta$=0.73), and is almost pressure and temperature independent above this compression. It is also effected by anharmonicity at zero pressure and temperatures above 2500K. The thermal pressure changes very little with increasing pressures and temperatures, and the Gruneisen parameter is temperature independent and decreases slightly with pressure.Comment: Geophys. Res. Lett., in press, 7 pages, 4 figures, uuencoded ps fil

Whole genome sequencing of experimental hybrids supports meiosis-like sexual recombination in Leishmania

Hybrid genotypes have been repeatedly described among natural isolates of Leishmania, and the recovery of experimental hybrids from sand flies co-infected with different strains or species of Leishmania has formally demonstrated that members of the genus possess the machinery for genetic exchange. As neither gamete stages nor cell fusion events have been directly observed during parasite development in the vector, we have relied on a classical genetic analysis to determine if Leishmania has a true sexual cycle. Here, we used whole genome sequencing to follow the chromosomal inheritance patterns of experimental hybrids generated within and between different strains of L. major and L. infantum. We also generated and sequenced the first experimental hybrids in L. tropica. We found that in each case the parental somy and allele contributions matched the inheritance patterns expected under meiosis 97–99% of the time. The hybrids were equivalent to F1 progeny, heterozygous throughout most of the genome for the markers that were homozygous and different between the parents. Rare, non-Mendelian patterns of chromosomal inheritance were observed, including a gain or loss of somy, and loss of heterozygosity, that likely arose during meiosis or during mitotic divisions of the progeny clones in the fly or culture. While the interspecies hybrids appeared to be sterile, the intraspecies hybrids were able to produce backcross and outcross progeny. Analysis of 5 backcross and outcross progeny clones generated from an L. major F1 hybrid, as well as 17 progeny clones generated from backcrosses involving a natural hybrid of L. tropica, revealed genome wide patterns of recombination, demonstrating that classical crossing over occurs at meiosis, and allowed us to construct the first physical and genetic maps in Leishmania. Altogether, the findings provide strong evidence for meiosis-like sexual recombination in Leishmania, presenting clear opportunities for forward genetic analysis and positional cloning of important genes.</div

Andean Land Use And Biodiversity: Humanized Landscapes In A Time Of Change

Some landscapes Cannot be understood without reference., to the kinds. degrees, kinds, degrees, and history of human-caused modifications to the Earth's surface. The tropical latitudes of the Andes represent one such place, with agricultural land-use systems appearing in the Early Holocene. Current land use includes both intensive and extensive grazing and crop- or tree-based agricultural systems found across virtually the, entire range of possible elevations and humidity regimes. Biodiversity found in or adjacent to such humanized landscapes will have been altered in abundance. composition, and distribution in relation to the resiliency of the native Species to harvest, hold cover modifications, and other deliberate or inadvertent human land uses. In addition, the geometries of land cover, resulting flout difference among the shapes, sizes, connectivities, and physical structures of the patches, corridors, and matrices that compose landscape mosaics, will constrain biodiversity, often in predictable ways. This article proposes a conceptual model that alter ins that the Continued persistence of native species may depend as much oil the shifting Of Andean landscape mosaics as on species characteristics, themselves. Furthermore, mountains such as the Andes display long gradients of environmental Conditions that after in relation to latitude, soil moisture, aspect, and elevation. Global environmental change will shift these, especially temperature and humidity regimes along elevational gradients, causing Changes outside the historical range of variation for some species. Both land-use systems and Conservation efforts will need to respond spatially to these shifts in the future, at both landscape and regional scales.Geography and the Environmen

Online Interference Mitigation via Learning in Dynamic IoT Environments

International audienceA key challenge for ensuring self-organization capabilities in the Internet of things (IoT) is that wireless devices must be able to adapt to the network's unpredictable dynamics. In the lower layers of network design, this means the deployment of highly adaptive protocols capable of supporting large numbers of wireless " things " via intelligent interference mitigation and online power control. In view of this, we propose an exponential learning policy for throughput maximization in time-varying, dynamic IoT environments where interference must be kept at very low levels. The proposed policy is provably capable of adapting quickly and efficiently to changes in the network and relies only on locally available and strictly causal information. Specifically, if the transmission horizon T of a device is known ahead of time, the algorithm under study matches the performance of the best possible fixed policy in hindsight within an error margin of O(T −1/2); otherwise, if the horizon is not known in advance, the algorithm still achieves a O(T −1/2 log T) worst-case margin. In practice, our numerical results show that the interference induced by the connected devices can be mitigated effectively and – more importantly – in a highly adaptive, distributed way

Self-hybridization in Leishmania major

Genetic exchange between differen

Effects of pressure on diffusion and vacancy formation in MgO from non-empirical free-energy integrations

The free energies of vacancy pair formation and migration in MgO were computed via molecular dynamics using free-energy integrations and a non-empirical ionic model with no adjustable parameters. The intrinsic diffusion constant for MgO was obtained at pressures from 0 to 140 GPa and temperatures from 1000 to 5000 K. Excellent agreement was found with the zero pressure diffusion data within experimental error. The homologous temperature model which relates diffusion to the melting curve describes well our high pressure results within our theoretical framework.Comment: 4 pages, latex, 1 figure, revtex, submitted to PR

Mother-infant bonding is not associated with feeding type: a community study sample

Abstract Background Bonding refers to emotions and cognitions towards one’s infant. Breastfeeding is believed to facilitate bonding, yet only a handful of studies have empirically tested this assertion. This study aimed to confirm whether a positive association between breastfeeding and bonding exists and whether breastfeeding may be protective against the negative consequences of mood and sleep disturbances on bonding. Method A cross-sectional survey was administered to a convenience sample of Israeli mothers of infants ages 1–9 months. The main outcome measures were breastfeeding history, bonding (Postpartum Bonding Questionnaire, PBQ), mood (Edinburgh Postnatal Depression Scale, EPDS) and sleep (Pittsburgh Sleep Quality Index, PSQI). Results Two hundred seventy-one mothers (21–46 years) completed the survey. 65.7% reported current breastfeeding, 22.1% past breastfeeding, 12.2% never nursed. The PBQ correlated with both the EPDS and PSQI. Breastfeeding was associated with greater daytime fatigue, but not with any other sleep problem, and was not associated with bonding. This negative result was confirmed with Bayesian analysis demonstrating that the probability for the null hypothesis was 4.5 times greater than the hypothesized effect. Further, hierarchical regression revealed a positive relationship between bonding, daytime fatigue and depression symptoms only among women who were currently breastfeeding. Conclusions These findings suggest that among healthy mothers, breastfeeding may not be a central factor in mother-infant bonding, nor is it protective against the negative impact of mood symptoms and bonding difficulties. Theoretical and methodological bases of these findings are discussed.https://deepblue.lib.umich.edu/bitstream/2027.42/148570/1/12884_2019_Article_2264.pd