Modulation of Thermoelectric Power of Individual Carbon Nanotubes

Thermoelectric power (TEP) of individual single walled carbon nanotubes (SWNTs) has been measured at mesoscopic scales using a microfabricated heater and thermometers. Gate electric field dependent TEP-modulation has been observed. The measured TEP of SWNTs is well correlated to the electrical conductance across the SWNT according to the Mott formula. At low temperatures, strong modulations of TEP were observed in the single electron conduction limit. In addition, semiconducting SWNTs exhibit large values of TEP due to the Schottky barriers at SWNT-metal junctions.Comment: to be published in Phys. Rev. Let

Detecting periodicity in experimental data using linear modeling techniques

Fourier spectral estimates and, to a lesser extent, the autocorrelation function are the primary tools to detect periodicities in experimental data in the physical and biological sciences. We propose a new method which is more reliable than traditional techniques, and is able to make clear identification of periodic behavior when traditional techniques do not. This technique is based on an information theoretic reduction of linear (autoregressive) models so that only the essential features of an autoregressive model are retained. These models we call reduced autoregressive models (RARM). The essential features of reduced autoregressive models include any periodicity present in the data. We provide theoretical and numerical evidence from both experimental and artificial data, to demonstrate that this technique will reliably detect periodicities if and only if they are present in the data. There are strong information theoretic arguments to support the statement that RARM detects periodicities if they are present. Surrogate data techniques are used to ensure the converse. Furthermore, our calculations demonstrate that RARM is more robust, more accurate, and more sensitive, than traditional spectral techniques.Comment: 10 pages (revtex) and 6 figures. To appear in Phys Rev E. Modified styl

Surrogate-assisted network analysis of nonlinear time series

The performance of recurrence networks and symbolic networks to detect weak nonlinearities in time series is compared to the nonlinear prediction error. For the synthetic data of the Lorenz system, the network measures show a comparable performance. In the case of relatively short and noisy real-world data from active galactic nuclei, the nonlinear prediction error yields more robust results than the network measures. The tests are based on surrogate data sets. The correlations in the Fourier phases of data sets from some surrogate generating algorithms are also examined. The phase correlations are shown to have an impact on the performance of the tests for nonlinearity.Comment: 9 pages, 5 figures, Chaos (http://scitation.aip.org/content/aip/journal/chaos), corrected typo

Results of an aqueous source term model for a radiological risk assessment of the Drigg LLW Site, U.K.

A radionuclide source term model has been developed which simulates the biogeochemical evolution of the Drigg low level waste (LLW) disposal site. The DRINK (DRIgg Near field Kinetic) model provides data regarding radionuclide concentrations in groundwater over a period of 100,000 years, which are used as input to assessment calculations for a groundwater pathway. The DRINK model also provides input to human intrusion and gaseous assessment calculations through simulation of the solid radionuclide inventory. These calculations are being used to support the Drigg post closure safety case. The DRINK model considers the coupled interaction of the effects of fluid flow, microbiology, corrosion, chemical reaction, sorption and radioactive decay. It represents the first direct use of a mechanistic reaction-transport model in risk assessment calculations

Dynamical modeling of collective behavior from pigeon flight data: flock cohesion and dispersion

Several models of flocking have been promoted based on simulations with qualitatively naturalistic behavior. In this paper we provide the first direct application of computational modeling methods to infer flocking behavior from experimental field data. We show that this approach is able to infer general rules for interaction, or lack of interaction, among members of a flock or, more generally, any community. Using experimental field measurements of homing pigeons in flight we demonstrate the existence of a basic distance dependent attraction/repulsion relationship and show that this rule is sufficient to explain collective behavior observed in nature. Positional data of individuals over time are used as input data to a computational algorithm capable of building complex nonlinear functions that can represent the system behavior. Topological nearest neighbor interactions are considered to characterize the components within this model. The efficacy of this method is demonstrated with simulated noisy data generated from the classical (two dimensional) Vicsek model. When applied to experimental data from homing pigeon flights we show that the more complex three dimensional models are capable of predicting and simulating trajectories, as well as exhibiting realistic collective dynamics. The simulations of the reconstructed models are used to extract properties of the collective behavior in pigeons, and how it is affected by changing the initial conditions of the system. Our results demonstrate that this approach may be applied to construct models capable of simulating trajectories and collective dynamics using experimental field measurements of herd movement. From these models, the behavior of the individual agents (animals) may be inferred

Spatial accessibility and social inclusion: The impact of Portugal's last health reform

Health policies seek to promote access to health care and should provide appropriate geographical accessibility to each demographical functional group. The dispersal demand of health‐careservices and the provision for such services atfixed locations contribute to the growth of inequality intheir access. Therefore, the optimal distribution of health facilities over the space/area can lead toaccessibility improvements and to the mitigation of the social exclusion of the groups considered mostvulnerable. Requiring for such, the use of planning practices joined with accessibility measures. However,the capacities of Geographic Information Systems in determining and evaluating spatial accessibility inhealth system planning have not yet been fully exploited. This paper focuses on health‐care services planningbased on accessibility measures grounded on the network analysis. The case study hinges on mainlandPortugal. Different scenarios were developed to measure and compare impact on the population'saccessibility. It distinguishes itself from other studies of accessibility measures by integrating network data ina spatial accessibility measure: the enhanced two‐stepfloating catchment area. The convenient location forhealth‐care facilities can increase the accessibility standards of the population and consequently reducethe economic and social costs incurred. Recently, the Portuguese government implemented a reform thataimed to improve, namely, the access and equity in meeting with the most urgent patients. It envisaged,in terms of equity, the allocation of 89 emergency network points that ensured more than 90% of thepopulation be within 30 min from any one point in the network. Consequently, several emergency serviceswere closed, namely, in rural areas. This reform highlighted the need to improve the quality of the emergencycare, accessibility to each care facility, and equity in their access. Hence, accessibility measures becomean efficient decision‐making tool, despite its absence in effective practice planning. According to anapplication of this type of measure, it was possible to verify which levels of accessibility were decreased,including the most disadvantaged people, with a larger time of dislocation of 12 min between 2001 and 2011

Overcoming the risk of inaction from emissions uncertainty in smallholder agriculture

The potential for improving productivity and increasing the resilience of smallholder agriculture, while also contributing to climate change mitigation, has recently received considerable political attention (Beddington et al 2012). Financial support for improving smallholder agriculture could come from performance-based funding including sale of carbon credits or certified commodities, payments for ecosystem services, and nationally appropriate mitigation action (NAMA) budgets, as well as more traditional sources of development and environment finance. Monitoring the greenhouse gas fluxes associated with changes to agricultural practice is needed for performance-based mitigation funding, and efforts are underway to develop tools to quantify mitigation achieved and assess trade-offs and synergies between mitigation and other livelihood and environmental priorities (Olander 2012)

Accommodating error analysis in comparison and clustering of molecular fingerprints.

Molecular epidemiologic studies of infectious diseases rely on pathogen genotype comparisons, which usually yield patterns comprising sets of DNA fragments (DNA fingerprints). We use a highly developed genotyping system, IS6110-based restriction fragment length polymorphism analysis of Mycobacterium tuberculosis, to develop a computational method that automates comparison of large numbers of fingerprints. Because error in fragment length measurements is proportional to fragment length and is positively correlated for fragments within a lane, an align-and-count method that compensates for relative scaling of lanes reliably counts matching fragments between lanes. Results of a two-step method we developed to cluster identical fingerprints agree closely with 5 years of computer-assisted visual matching among 1,335 M. tuberculosis fingerprints. Fully documented and validated methods of automated comparison and clustering will greatly expand the scope of molecular epidemiology

A \u3cem\u3eMycobacterium ulcerans\u3c/em\u3e Toxin, Mycolactone, Causes Apoptosis in Guinea Pig Ulcers and Tissue Culture Cells

Mycobacterium ulcerans is the causative agent of Buruli ulcer, a tropical ulcerative skin disease. One of the most intriguing aspects of this disease is the presence of extensive tissue damage in the absence of an acute inflammatory response. We recently purified and characterized a macrolide toxin, mycolactone, from M. ulcerans. Injection of this molecule into guinea pig skin reproduced cell death and lack of acute inflammatory response similar to that seen following the injection of viable bacteria. We also showed that mycolactone causes a cytopathic effect on mouse fibroblast L929 cells that is characterized by cytoskeletal rearrangements and growth arrest within 48 h. However, these results could not account for the extensive cell death which occurs in Buruli ulcer. The results presented here demonstrate that L929 and J774 mouse macrophage cells die via apoptosis after 3 to 5 days of exposure to mycolactone. Treatment of cells with a pan-caspase inhibitor can inhibit mycolactone-induced apoptosis. We demonstrate that injection of mycolactone into guinea pig skin results in cell death via apoptosis and that the extent of apoptosis increases as the lesion progresses. These results may help to explain why tissue damage in Buruli ulcer is not accompanied by an acute inflammatory response