Observation and modelling of ferromagnetic contact-induced spin relaxation in Hanle spin precession measurements

This is the author accepted manuscript. The final version is available from the American Physical Society via http://dx.doi.org/10.1103/PhysRevB.94.094431In the nonlocal spin valve (NLSV) geometry, four-terminal electrical Hanle effect measurements have the potential to provide a particularly simple determination of the lifetime (τ$_{s}$) and diffusion length (λ$_{N}$) of spins injected into nonmagnetic (N) materials. Recent papers, however, have demonstrated that traditional models typically used to fit such data provide an inaccurate measurement of τ$_{s}$ in ferromagnet (FM)/N metal devices with low interface resistance, particularly when the separation of the source and detector contacts is small. In the transparent limit, this shortcoming is due to the back diffusion and subsequent relaxation of spins within the FM contacts, which is not properly accounted for in standard models of the Hanle effect. Here we have used the separation dependence of the spin accumulation signal in NLSVs with multiple FM/N combinations, and interfaces in the diffusive limit, to determine λ$_{N}$ in traditional spin valve measurements. We then compare these results to Hanle measurements as analyzed using models that either include or exclude spin sinking. We demonstrate that differences between the spin valve and Hanle measurements of λ$_{N}$ can be quantitatively modelled provided that both the FM contact-induced isotropic spin sinking and the full three-dimensional geometry of the devices, which is particularly important at small contact separations, are accounted for. We find, however, that considerable difficulties persist, in particular due to the sensitivity of fitting to the contact interface resistance and the FM contact magnetization rotation, in precisely determining λ$_{N}$ with the Hanle technique alone, particularly at small contact separations.This work was funded by Seagate Technology Inc. and the University of Minnesota (UMN) NSF MRSEC under DMR- 1420013, as well as NSF DMR-1104951 and NSF DMR-1507048. L.O’B. acknowledges a Marie Curie International Outgoing Fellowship within the 7th European Community Framework Programme (project no. 299376).Parts of this work were carried out in the UMN Characterization Facility and Minnesota Nano Center, which receive partial support from the NSF MRSEC and NSF NNIN programs, respectively

Characterising loss and damage from climate change

Policy-makers are creating mechanisms to help developing countries cope with loss and damage from climate change, but the negotiations are largely neglecting scientific questions about what the impacts of climate change actually are. Mitigation efforts have failed to prevent the continued increase of anthropogenic greenhouse gas (GHG) emissions. Adaptation is now unlikely to be sufficient to prevent negative impacts from current and future climate change1. In this context, vulnerable nations argue that existing frameworks to promote mitigation and adaptation are inadequate, and have called for a third international mechanism to deal with residual climate change impacts, or “loss and damage”2. In 2013, the United Nations Framework Convention on Climate Change (UNFCCC) responded to these calls and established the Warsaw International Mechanism (WIM) to address loss and damage from the impacts of climate change in developing countries3. An interim Executive Committee of party representatives has been set up, and is currently drafting a two-year workplan comprising meetings, reports, and expert groups; and aiming to enhance knowledge and understanding of loss and damage, strengthen dialogue among stakeholders, and promote enhanced action and support. Issues identified as priorities for the WIM thus far include: how to deal with non-economic losses, such as loss of life, livelihood, and cultural heritage; and linkages between loss and damage and patterns of migration and displacement2. In all this, one fundamental issue still demands our attention: which losses and damages are relevant to the WIM? What counts as loss and damage from climate change

Spatial heterogeneity of habitat suitability for Rift Valley fever occurrence in Tanzania: an ecological niche modelling approach

Despite the long history of Rift Valley fever (RVF) in Tanzania, extent of its suitable habitat in the country remains unclear. In this study we investigated potential effects of temperature, precipitation, elevation, soil type, livestock density, rainfall pattern, proximity to wild animals, protected areas and forest on the habitat suitability for RVF occurrence in Tanzania. Presence-only records of 193 RVF outbreak locations from 1930 to 2007 together with potential predictor variables were used to model and map the suitable habitats for RVF occurrence using ecological niche modelling. Ground-truthing of the model outputs was conducted by comparing the levels of RVF virus specific antibodies in cattle, sheep and goats sampled from locations in Tanzania that presented different predicted habitat suitability values. Habitat suitability values for RVF occurrence were higher in the northern and central-eastern regions of Tanzania than the rest of the regions in the country. Soil type and precipitation of the wettest quarter contributed equally to habitat suitability (32.4% each), followed by livestock density (25.9%) and rainfall pattern (9.3%). Ground-truthing of model outputs revealed that the odds of an animal being seropositive for RVFV when sampled from areas predicted to be most suitable for RVF occurrence were twice the odds of an animal sampled from areas least suitable for RVF occurrence (95% CI: 1.43, 2.76, p < 0.001). The regions in the northern and central-eastern Tanzania were more suitable for RVF occurrence than the rest of the regions in the country. The modelled suitable habitat is characterised by impermeable soils, moderate precipitation in the wettest quarter, high livestock density and a bimodal rainfall pattern. The findings of this study should provide guidance for the design of appropriate RVF surveillance, prevention and control strategies which target areas with these characteristics

Dyslexia detection from EEG signals using SSA component correlation and Convolutional Neural Networks

Objective dyslexia diagnosis is not a straighforward task since it is traditionally performed by means of the intepretation of different behavioural tests. Moreover, these tests are only applicable to readers. This way, early diagnosis requires the use of specific tasks not only related to reading. Thus, the use of Electroencephalography (EEG) constitutes an alternative for an objective and early diagnosis that can be used with pre-readers. In this way, the extraction of relevant features in EEG signals results crucial for classification. However, the identification of the most relevant features is not straighforward, and predefined statistics in the time or frequency domain are not always discriminant enough. On the other hand, classical processing of EEG signals based on extracting EEG bands frequency descriptors, usually make some assumptions on the raw signals that could cause indormation loosing. In this work we propose an alternative for analysis in the frequency domain based on Singluar Spectrum Analysis (SSA) to split the raw signal into components representing different oscillatory modes. Moreover, correlation matrices obtained for each component among EEG channels are classfied using a Convolutional Neural network.Comment: 11 pages, 7 figures. Submitted to conferenc

The LSST DESC data challenge 1: Generation and analysis of synthetic images for next-generation surveys

Data Challenge 1 (DC1) is the first synthetic data set produced by the Rubin Observatory Legacy Survey of Space and Time (LSST) Dark Energy Science Collaboration (DESC). DC1 is designed to develop and validate data reduction and analysis and to study the impact of systematic effects that will affect the LSST data set. DC1 is comprised of r-band observations of 40 deg2 to 10 yr LSST depth. We present each stage of the simulation and analysis process: (a) generation, by synthesizing sources from cosmological N-body simulations in individual sensor-visit images with different observing conditions; (b) reduction using a development version of the LSST Science Pipelines; and (c) matching to the input cosmological catalogue for validation and testing. We verify that testable LSST requirements pass within the fidelity of DC1. We establish a selection procedure that produces a sufficiently clean extragalactic sample for clustering analyses and we discuss residual sample contamination, including contributions from inefficiency in star-galaxy separation and imperfect deblending. We compute the galaxy power spectrum on the simulated field and conclude that: (i) survey properties have an impact of 50 per cent of the statistical uncertainty for the scales and models used in DC1; (ii) a selection to eliminate artefacts in the catalogues is necessary to avoid biases in the measured clustering; and (iii) the presence of bright objects has a significant impact (2-6) in the estimated power spectra at small scales (&gt; 1200), highlighting the impact of blending in studies at small angular scales in LSST

The impact of predation by marine mammals on Patagonian toothfish longline fisheries

Predatory interaction of marine mammals with longline fisheries is observed globally, leading to partial or complete loss of the catch and in some parts of the world to considerable financial loss. Depredation can also create additional unrecorded fishing mortality of a stock and has the potential to introduce bias to stock assessments. Here we aim to characterise depredation in the Patagonian toothfish (Dissostichus eleginoides) fishery around South Georgia focusing on the spatio-temporal component of these interactions. Antarctic fur seals (Arctocephalus gazella), sperm whales (Physeter macrocephalus), and orcas (Orcinus orca) frequently feed on fish hooked on longlines around South Georgia. A third of longlines encounter sperm whales, but loss of catch due to sperm whales is insignificant when compared to that due to orcas, which interact with only 5% of longlines but can take more than half of the catch in some cases. Orca depredation around South Georgia is spatially limited and focused in areas of putative migration routes, and the impact is compounded as a result of the fishery also concentrating in those areas at those times. Understanding the seasonal behaviour of orcas and the spatial and temporal distribution of “depredation hot spots” can reduce marine mammal interactions, will improve assessment and management of the stock and contribute to increased operational efficiency of the fishery. Such information is valuable in the effort to resolve the human-mammal conflict for resources

The complex interplay between endoplasmic reticulum stress and the NLRP3 inflammasome: a potential therapeutic target for inflammatory disorders.

Inflammation is the result of a complex network of cellular and molecular interactions and mechanisms that facilitate immune protection against intrinsic and extrinsic stimuli, particularly pathogens, to maintain homeostasis and promote tissue healing. However, dysregulation in the immune system elicits excess/abnormal inflammation resulting in unintended tissue damage and causes major inflammatory diseases including asthma, chronic obstructive pulmonary disease, atherosclerosis, inflammatory bowel diseases, sarcoidosis and rheumatoid arthritis. It is now widely accepted that both endoplasmic reticulum (ER) stress and inflammasomes play critical roles in activating inflammatory signalling cascades. Notably, evidence is mounting for the involvement of ER stress in exacerbating inflammasome-induced inflammatory cascades, which may provide a new axis for therapeutic targeting in a range of inflammatory disorders. Here, we comprehensively review the roles, mechanisms and interactions of both ER stress and inflammasomes, as well as their interconnected relationships in inflammatory signalling cascades. We also discuss novel therapeutic strategies that are being developed to treat ER stress- and inflammasome-related inflammatory disorders