Chandra studies of the globular cluster 47 Tucanae: A deeper X-ray source catalogue, five new X-ray counterparts to millisecond radio pulsars, and new constraints to r-mode instability window

We combined Chandra ACIS observations of the globular cluster 47 Tucanae (hereafter, 47 Tuc) from 2000, 2002, and 2014-15 to create a deeper X-ray source list, and study some of the faint radio millisecond pulsars (MSPs) present in this cluster. We have detected 370 X-ray sources within the half-mass radius (2$'$.79) of the cluster, 81 of which are newly identified, by including new data and using improved source detection techniques. The majority of the newly identified sources are in the crowded core region, indicating cluster membership. We associate five of the new X-ray sources with chromospherically active BY Dra or W UMa variables identified by Albrow et al. (2001). We present alternative positions derived from two methods, centroiding and image reconstruction, for faint, crowded sources. We are able to extract X-ray spectra of the recently discovered MSPs 47 Tuc aa, 47 Tuc ab, the newly timed MSP 47 Tuc Z, and the newly resolved MSPs 47 Tuc S and 47 Tuc F. Generally, they are well fit by black body or neutron star atmosphere models, with temperatures, luminosities and emitting radii similar to those of other known MSPs in 47 Tuc, though 47 Tuc aa and 47 Tuc ab reach lower X-ray luminosities. We limit X-ray emission from the full surface of the rapidly spinning (542 Hz) MSP 47 Tuc aa, and use this limit to put an upper bound for amplitude of r-mode oscillations in this pulsar as $\alpha<2.5\times 10^{-9}$ and constrain the shape of the r-mode instability window.Comment: 17 pages, 11 figures, 6 tables, Accepted for publication in MNRA

Stochastic description of waterlogging and hydroperiods in wetlands

Wetlands are found at the interface between aquatic and terrestrial ecosystems, where different hydrologic factors and ecosystem processes interact to generate unique characteristics and a delicate balance between biotic and abiotic factors. The main hydrologic driver of wetland ecosystems is the water level, whose position above or below the ground level, determines the submergence or non-submergence of soil. When the water level lies above the soil surface, soil is saturated and hypoxic conditions affect all biochemical processes, inducing anaerobic microorganism functioning, variation of redox potential, and anoxic stress in plants, that might lead to the death of non-adapted organisms. When the water level is below the soil surface, the soil water balance is similar to that of groundwater-dependent ecosystems, which allows for both oxygen and water supply to the plant roots. Therefore, the succession of the submerged-unsubmerged conditions plays a fundamental role on the ecosystem. Shallow or above-ground water level fluctuations, at the daily time scale, are driven by stochastic precipitation; using a simple process-based model for soil water balance, the dynamics of groundwater level is here described as a function of evapotranspiration, lateral flow to/from an external water body and random precipitation, modeled as a marked Poisson process. This simple model provides the analytical long-term probability distribution of water table depth and the crossing properties of water table dynamics, which are used to study the timing of waterlogging. The interval of time during which a wetland remains flooded, often called “hydroperiod”, is represented by the first passage time of water table in down-crossing the soil surface; here we calculate the mean hydroperiod as the Mean First Passage Time of the process, that is a function of the model parameters, and we verify this result with numerical simulations. Focusing on the statistical properties of hydroperiods, we also propose to describe their long term probability distribution with a parametric distribution, whose parameters are linked to the model parameters through simple analytical relations. Numerical simulations again confirm the validity of the approach, and its capability of describing the properties of hydroperiods as a function of the climatic, pedological, and ecological characteristics of wetlands

Stochastic water table dynamics in groundwater-dependent ecosystems

Humidlands are environments where the groundwater plays a key role on the ecosystem function. Contrary to water limited ecosystems, where water table is mostly out of reach for the vegetation, groundwater-dependent ecosystems exhibit important interactions between the water table and vegetation dynamics. We propose here an analytical model to study the interactions between rainfall, water table and vegetation in humidland ecosystems. The groundwater dynamics is studied as a random process, stochastically driven by a marked Poisson noise representing rainfall events. Infiltration, root water uptake, water flow to/from an external water body, and capillary rise are accounted for in a probabilistic description of water table fluctuations. We obtain analytical expressions for the steady-state probability distribution of water table depth, which allows us to investigate the long term behavior of water table dynamics, and their sensitivity to changes in climate, vegetation cover, and water managemen

Ecohydrology of groundwater-dependent ecosystems: a stochastic framework for plant transpiration

Groundwater-dependent ecosystems are found in areas with a shallow water table, where the groundwater plays a key role on the ecosystem functions. In these areas, the water table depth, the capillary fluxes, and the soil moisture content exert a major control on most ecohydrologic processes, such as infiltration, surface runoff, aquifer recharge, land-atmosphere feedbacks, vegetation dynamics, nutrient cycling, and pollutant transport. Understanding and modeling the soil water balance and its relationships with climate, soil, and vegetation is therefore a crucial aspect for geosciences such as hydrology and ecology. The ecohydrology of groundwater-dependent ecosystems can be described with a modeling framework based on a stochastic process-based water balance. The model is driven by a compound marked Poisson noise representing the rainfall events and, under some simplifying, yet realistic, assumptions, it includes rainfall infiltration, root water uptake, capillary flux, and subsurface flow to/from an external water body. The framework provides the long-term probability distribution of water table depth and of soil moisture vertical profiles, enabling a quantitative study of the local hydrology with a limited number of parameters. We here apply this framework to investigate plant transpiration and root water uptake. The probability distributions of water uptake are derived from those of the soil water content and are investigated for different scenarios of climate, soil, and vegetation. The results of this approach allow for interesting speculations about the groundwater contribution to root uptake, the soil water available for plant transpiration, and the optimal strategies of root growth and plant competition. This information is useful to assess the impact of climate changes, vegetation modification, and water management operation

Progress in the Neural Network Determination of Polarized Parton Distributions

We review recent progress towards a determination of a set of polarized parton distributions from a global set of deep-inelastic scattering data based on the NNPDF methodology, in analogy with the unpolarized case. This method is designed to provide a faithful and statistically sound representation of parton distributions and their uncertainties. We show how the FastKernel method provides a fast and accurate method for solving the polarized DGLAP equations. We discuss the polarized PDF parametrizations and the physical constraints which can be imposed. Preliminary results suggest that the uncertainty on polarized PDFs, most notably the gluon, has been underestimated in previous studies.Comment: 5 pages, 2 figures; to appear in the proceedings of DIS 2010, Firenz

Stochastic water table dynamics in groundwater-dependent ecosystems

Humidlands are environments where the groundwater plays a key role on the ecosystem function. Contrary to water limited ecosystems, where water table is mostly out of reach for the vegetation, groundwater-dependent ecosystems exhibit important interactions between the water table and vegetation dynamics. We propose here an analytical model to study the interactions between rainfall, water table and vegetation in humidland ecosystems. The groundwater dynamics is studied as a random process, stochastically driven by a marked Poisson noise representing rainfall events. Infiltration, root water uptake, water flow to/from an external water body, and capillary rise are accounted for in a probabilistic description of water table fluctuations. We obtain analytical expressions for the steady-state probability distribution of water table depth, which allows us to investigate the long term behavior of water table dynamics, and their sensitivity to changes in climate, vegetation cover, and water managemen

Ecohydrology of groundwater-dependent ecosystems: a stochastic framework for plant transpiration

Groundwater-dependent ecosystems are found in areas with a shallow water table, where the groundwater plays a key role on the ecosystem functions. In these areas, the water table depth, the capillary fluxes, and the soil moisture content exert a major control on most ecohydrologic processes, such as infiltration, surface runoff, aquifer recharge, land-atmosphere feedbacks, vegetation dynamics, nutrient cycling, and pollutant transport. Understanding and modeling the soil water balance and its relationships with climate, soil, and vegetation is therefore a crucial aspect for geosciences such as hydrology and ecology. The ecohydrology of groundwater-dependent ecosystems can be described with a modeling framework based on a stochastic process-based water balance. The model is driven by a compound marked Poisson noise representing the rainfall events and, under some simplifying, yet realistic, assumptions, it includes rainfall infiltration, root water uptake, capillary flux, and subsurface flow to/from an external water body. The framework provides the long-term probability distribution of water table depth and of soil moisture vertical profiles, enabling a quantitative study of the local hydrology with a limited number of parameters. We here apply this framework to investigate plant transpiration and root water uptake. The probability distributions of water uptake are derived from those of the soil water content and are investigated for different scenarios of climate, soil, and vegetation. The results of this approach allow for interesting speculations about the groundwater contribution to root uptake, the soil water available for plant transpiration, and the optimal strategies of root growth and plant competition. This information is useful to assess the impact of climate changes, vegetation modification, and water management operation

Il‐17 promotes nitric oxide production in non‐small‐cell lung cancer

Introduction: Lung cancer is the second most frequent malignancy worldwide, but its aetiology is still unclear. Inflammatory cytokines and Th cells, including Th17, are now emerging as being involved in NSCLC pathways, thus postulating a role of IL‐17 in tumour angiogenesis by stimulating the vascular endothelial growth factor and the release of nitric oxide. Despite the fact that many biomarkers are used for chest malignancy diagnosis, data on FeNO levels and inflammatory cytokines in NSCLC are still few. Our study aimed to evaluate the relationship between pulmonary nitric oxide production and VEGF and Th17‐related cytokines in the EBC of patients affected by early‐stage NSCLC. Methods: FeNO measurement and lung function tests were performed in both patients affected by NCSLC and controls; EBC samples were also taken, and Th1 (IL‐1, IL‐6, IL‐12, IFN‐g, TNF‐a), Th17 (IL‐17, IL‐23) and Th2 (IL‐4, IL‐5, IL‐13) related cytokines were measured. Results: Th1 and Th17‐related cytokines in EBC, except for IFN‐gamma and TNF-alpha, were significantly higher in patients than in healthy controls, whereas no differences were seen for Th2‐related cytokines. FeNO at the flow rate of 50 mL/s, JawNO and CalvNO levels were significantly higher in patients affected by NSCLC compared to controls. Significant correlations were found between FeNO 50 mL/s and IL‐17, IL‐1 and VEGF. JawNO levels positively correlated with IL‐6, IL‐17 and VEGF. No correlations were found between FeNO and Th2‐related cytokines. Conclusion: This is the first report assessing a relationship between FeNO levels and Th17‐related cytokines in the EBC of patients affected by early‐stage NSCLC. IL‐17, which could promote angiogenesis through the VEGF pathway, might be indirectly responsible for the increased lung production of NO in patients with NSCLC

Physics at the front-end of a neutrino factory: a quantitative appraisal

We present a quantitative appraisal of the physics potential for neutrino experiments at the front-end of a muon storage ring. We estimate the forseeable accuracy in the determination of several interesting observables, and explore the consequences of these measurements. We discuss the extraction of individual quark and antiquark densities from polarized and unpolarized deep-inelastic scattering. In particular we study the implications for the undertanding of the nucleon spin structure. We assess the determination of alpha_s from scaling violation of structure functions, and from sum rules, and the determination of sin^2(theta_W) from elastic nu-e and deep-inelastic nu-p scattering. We then consider the production of charmed hadrons, and the measurement of their absolute branching ratios. We study the polarization of Lambda baryons produced in the current and target fragmentation regions. Finally, we discuss the sensitivity to physics beyond the Standard Model.Comment: 73+1 pages, 33 figs. Report of the nuDIS Working Group for the ECFA-CERN Neutrino-Factory study, M.L. Mangano (convener