Behavioural context of multi-scale species distribution models assessed by radio-tracking

Incorporating ecological processes and animal behaviour into Species Distribution Models (SDMs) is difficult. In species with a central resting or breeding place, there can be conflict between the environmental requirements of the 'central place' and foraging habitat. We apply a multi-scale SDM to examine habitat trade-offs between the central place, roost sites, and foraging habitat in . Myotis nattereri. We validate these derived associations using habitat selection from behavioural observations of radio-tracked bats. A Generalised Linear Model (GLM) of roost occurrence using land cover variables with mixed spatial scales indicated roost occurrence was positively associated with woodland on a fine scale and pasture on a broad scale. Habitat selection of radio-tracked bats mirrored the SDM with bats selecting for woodland in the immediate vicinity of individual roosts but avoiding this habitat in foraging areas, whilst pasture was significantly positively selected for in foraging areas. Using habitat selection derived from radio-tracking enables a multi-scale SDM to be interpreted in a behavioural context. We suggest that the multi-scale SDM of . M. nattereri describes a trade-off between the central place and foraging habitat. Multi-scale methods provide a greater understanding of the ecological processes which determine where species occur and allow integration of behavioural processes into SDMs. The findings have implications when assessing the resource use of a species at a single point in time. Doing so could lead to misinterpretation of habitat requirements as these can change within a short time period depending on specific behaviour, particularly if detectability changes depending on behaviour. © 2011 Gesellschaft für ökologie.

Luce Irigaray: Back to the Beginning

In 2014 it will be 40 years since Luce Irigaray’s (second) doctoral thesis Speculum de l'autre femme was first published. That book, widely recognized as the most important text in feminist philosophy, was to introduce Irigaray’s critique of western philosophy and psychoanalysis and her ethics of sexual difference for which she was to become so well known. Irigaray, well into her eighties now, has published continuously since Speculum, despite her exclusion from French academic life after her expulsion in 1974 from the Université de Paris VIII Vincennes. That her latest book In the Beginning, She Was, released on the eve of Speculum’s anniversary, is perhaps the most personally revelatory of her works and revisits many of the same themes and issues that concerned her in Speculum cannot be coincidental. In this critical notice we examine Irigaray’s latest offering arguing that her contribution is twofold as she combines with new clarity her longstanding critique of phallocratic culture and her transformative vision of humanity as a culture of sexuate difference. There are a number of important themes addressed in the six chapters of the book, but for the purposes of this discussion our analysis will focus mostly on elaborating her critique of Western culture, on the usefulness of her work for rethinking masculine subject formation and on the figure of Antigone, as a feminine subject on her own terms, as a way of imagining a possible relation between two subjects within a culture of sexuate difference. We argue that this book continues to illustrate Irigaray’s importance as one of the most radical and prophetic philosophers of our time.

Establishing optimal quantitative-polymerase chain reaction assays for routine diagnosis and tracking of minimal residual disease in JAK2-V617F-associated myeloproliferative neoplasms:a joint European LeukemiaNet/MPN&MPNr-EuroNet (COST action BM0902) study

Reliable detection of JAK2-V617F is critical for accurate diagnosis of myeloproliferative neoplasms (MPNs); in addition, sensitive mutation-specific assays can be applied to monitor disease response. However, there has been no consistent approach to JAK2-V617F detection, with assays varying markedly in performance, affecting clinical utility. Therefore, we established a network of 12 laboratories from seven countries to systematically evaluate nine different DNA-based quantitative PCR (qPCR) assays, including those in widespread clinical use. Seven quality control rounds involving over 21,500 qPCR reactions were undertaken using centrally distributed cell line dilutions and plasmid controls. The two best-performing assays were tested on normal blood samples (n=100) to evaluate assay specificity, followed by analysis of serial samples from 28 patients transplanted for JAK2-V617F-positive disease. The most sensitive assay, which performed consistently across a range of qPCR platforms, predicted outcome following transplant, with the mutant allele detected a median of 22 weeks (range 6-85 weeks) before relapse. Four of seven patients achieved molecular remission following donor lymphocyte infusion, indicative of a graft vs MPN effect. This study has established a robust, reliable assay for sensitive JAK2-V617F detection, suitable for assessing response in clinical trials, predicting outcome and guiding management of patients undergoing allogeneic transplant.

Analysis of Dependence Tracking Algorithms for Task Dataflow Execution

Processor architectures has taken a turn towards many-core processors, which integrate multiple processing cores on a single chip to increase overall performance, and there are no signs that this trend will stop in the near future. Many-core processors are harder to program than multi-core and single-core processors due to the need of writing parallel or concurrent programs with high degrees of parallelism. Moreover, many-cores have to operate in a mode of strong scaling because of memory bandwidth constraints. In strong scaling increasingly finer-grain parallelism must be extracted in order to keep all processing cores busy.

Task dataflow programming models have a high potential to simplify parallel program- ming because they alleviate the programmer from identifying precisely all inter-task de- pendences when writing programs. Instead, the task dataflow runtime system detects and enforces inter-task dependences during execution based on the description of memory each task accesses. The runtime constructs a task dataflow graph that captures all tasks and their dependences. Tasks are scheduled to execute in parallel taking into account dependences specified in the task graph.

Several papers report important overheads for task dataflow systems, which severely limits the scalability and usability of such systems. In this paper we study efficient schemes to manage task graphs and analyze their scalability. We assume a programming model that supports input, output and in/out annotations on task arguments, as well as commutative in/out and reductions. We analyze the structure of task graphs and identify versions and generations as key concepts for efficient management of task graphs. Then, we present three schemes to manage task graphs building on graph representations, hypergraphs and lists. We also consider a fourth edge-less scheme that synchronizes tasks using integers. Analysis using micro-benchmarks shows that the graph representation is not always scalable and that the edge-less scheme introduces least overhead in nearly all situations.

Generalized Laplacian Eigenmaps for Modeling and Tracking Human Motions

This paper presents generalized Laplacian eigenmaps, a novel dimensionality reduction approach designed to address stylistic variations in time series. It generates compact and coherent continuous spaces whose geometry is data-driven. This paper also introduces graph-based particle filter, a novel methodology conceived for efficient tracking in low dimensional space derived from a spectral dimensionality reduction method. Its strengths are a propagation scheme, which facilitates the prediction in time and style, and a noise model coherent with the manifold, which prevents divergence, and increases robustness. Experiments show that a combination of both techniques achieves state-of-the-art performance for human pose tracking in underconstrained scenarios.

Tracking down the cause of proteinuria in primary care

Proteinuria originates from the kidney and occurs as a result of injury to either the glomerulus or the renal tubule or both. It is relatively common in the general population with reported point prevalence of up to 8% but the prevalence falls to around 2% on repeated testing. Chronic glomerular injury resulting in proteinuria may be secondary to prolonged duration of diabetes or hypertension. A tubular origin of proteinuria may be associated with inflammation of renal tubules triggered by prescribed drugs or ingested toxins. In the absence of obvious clues to the cause of persistent proteinuria on history or clinical examination it is worthwhile reviewing the patient's prescribed drugs to identify any potentially nephrotoxic agents e.g. NSAIDs. NICE guidelines recommend screening for proteinuria in individuals at higher risk for chronic kidney disease (CKD). These include patients with diabetes, hypertension, cardiovascular disease, connective tissue disorders, a family history of renal disease and those prescribed potentially nephrotoxic drugs. Patients with sudden onset of lower limb oedema and associated proteinuria should have a serum albumin level measured to exclude the nephrotic syndrome. Renal tract ultrasound will measure kidney size, and detect scarring associated with chronic pyelonephritis or prior renal stone disease which can cause proteinuria.

Adaptive Fusion Of Particle Filtering And Spatio-Temporal Motion Energy For Human Tracking

Object tracking is an active research area nowadays due to its importance in human computer interface, teleconferencing and video surveillance. However, reliable tracking of objects in the presence of occlusions, pose and illumination changes is still a challenging topic. In this paper, we introduce a novel tracking approach that fuses two cues namely colour and spatio-temporal motion energy within a particle filter based framework. We conduct a measure of coherent motion over two image frames, which reveals the spatio-temporal dynamics of the target. At the same time, the importance of both colour and motion energy cues is determined in the stage of reliability evaluation. This determination helps maintain the performance of the tracking system against abrupt appearance changes. Experimental results demonstrate that the proposed method outperforms the other state of the art techniques in the used test datasets.

Mantle flow, volatiles, slab-surface temperatures and melting dynamics in the north Tonga arc-Lau back-arc basin

The Fonualei Spreading Center affords an excellent opportunity to evaluate geochemical changes with increasing depth to the slab in the Lau back-arc basin. We present H2O and CO2 concentrations and Sr, Nd, Pb, Hf and U-Th-Ra isotope data for selected glasses as well as new Hf isotope data from boninites and seamounts to the north of the Tonga arc. The Pb and Hf isotope data are used to show that mantle flow is oriented to the southwest and that the tear in the northern end of the slab may not extend east as far as the boninite locality. Along the Fonualei Spreading Center, key geochemical parameters change smoothly with increasing distance from the arc front and increasing slab surface temperatures. The latter may range from 720 to 866 degrees C, based on decreasing H2O/Ce ratios. Consistent with experimental data, the geochemical trends are interpreted to reflect changes in the amount and composition of wet pelite melts or super-critical fluids and aqueous fluids derived from the slab. With one exception, all of the lavas preserve both U-238 excesses and Ra-226 excesses. We suggest that lavas from the Fonualei Spreading Center and Valu Fa Ridge are dominated by fluid-fluxed melting whereas those from the East and Central Lau Spreading Centers, where slab surface temperatures exceed similar to 850-900 degrees C, are largely derived through decompression. A similar observation is found for the Manus and East Scotia back-arc basins and may reflect the expiry of a key phase such as lawsonite in the subducted basaltic crust.

Tracking magnetic bright point motions through the solar atmosphere

High-cadence, multiwavelength observations and simulations are employed for the analysis of solar photospheric magnetic bright points (MBPs) in the quiet Sun. The observations were obtained with the Rapid Oscillations in the Solar Atmosphere (ROSA) imager and the Interferometric Bidimensional Spectrometer at the Dunn Solar Telescope. Our analysis reveals that photospheric MBPs have an average transverse velocity of approximately 1 km s-1, whereas their chromospheric counterparts have a slightly higher average velocity of 1.4 km s-1. Additionally, chromospheric MBPs were found to be around 63 per cent larger than the equivalent photospheric MBPs. These velocity values were compared with the output of numerical simulations generated using the muram code. The simulated results were similar, but slightly elevated, when compared to the observed data. An average velocity of 1.3 km s-1 was found in the simulated G-band images and an average of 1.8 km s-1 seen in the velocity domain at a height of 500 km above the continuum formation layer. Delays in the change of velocities were also analysed. Average delays of ˜4 s between layers of the simulated data set were established and values of ˜29 s observed between G-band and Ca ii K ROSA observations. The delays in the simulations are likely to be the result of oblique granular shock waves, whereas those found in the observations are possibly the result of a semi-rigid flux tube.

Dense Multiperson Tracking with Robust Hierarchical Linear Assignment

We introduce a novel dual-stage algorithm for online multi-target tracking in realistic conditions. In the first stage, the problem of data association between tracklets and detections, given partial occlusion, is addressed using a novel occlusion robust appearance similarity method. This is used to robustly link tracklets with detections without requiring explicit knowledge of the occluded regions. In the second stage, tracklets are linked using a novel method of constraining the linking process that removes the need for ad-hoc tracklet linking rules. In this method, links between tracklets are permitted based on their agreement with optical flow evidence. Tests of this new tracking system have been performed using several public datasets.

Adaptive NormalHedge for robust visual tracking

In this paper, we propose a novel visual tracking framework, based on a decision-theoretic online learning algorithm namely NormalHedge. To make NormalHedge more robust against noise, we propose an adaptive NormalHedge algorithm, which exploits the historic information of each expert to perform more accurate prediction than the standard NormalHedge. Technically, we use a set of weighted experts to predict the state of the target to be tracked over time. The weight of each expert is online learned by pushing the cumulative regret of the learner towards that of the expert. Our simulation experiments demonstrate the effectiveness of the proposed adaptive NormalHedge, compared to the standard NormalHedge method. Furthermore, the experimental results of several challenging video sequences show that the proposed tracking method outperforms several state-of-the-art methods.