2,331 research outputs found
Fishes of the Lagunas Encadenadas (Province of Buenos Aires, Argentina), a wetland of international importance
The Lagunas Encadenadas form a large endorheic wetland. The system comprises a chain of five main lagoons (Alsina, Chochico, Del Monte, Del Venado, and Epecuen). During two recent collection trips, 13 species of fish were caught. From the collected material and available data in the literature the following points can be made: The fish fauna of this wetland comprises 18 species from 11 families and six orders. Four species (Cyprinus carpio, Hoplias malabaricus, Loricariichthys anus and Parapimelodus valenciennis) are new records for these water bodies. Fish species diversity decreases from east to west, ie from the most freshwater lagoon (Alsina, with 15 species) to the most saline (Epecuen, 1 species). A similar diversity pattern has been found in zooplankton species
Fishes of the Lagunas Encadenadas (province of Buenos Aires, Argentina), a wetland of international importance
The Lagunas Encadenadas (36° 30' - 37° 30' S, 61° 00 63° 30' W)form a large endorheic wetland, i.e. the drainage lies in an enclosedbasin. The wetland is situated in the south-west of the Province ofBuenos Aires and has a total area of nearly 58,000 hectares (Fig. 1). Thesystem comprises a chain of five main lagoons (Alsina, Chochicó, DelMonte, Del Venado, and Epecuen) (Fig. 2), distinguished by a welldefined east-west gradient in salinity from fresh water to saline
Kinematic and morphological modeling of the bipolar nebula Sa2-237
We present [OIII]500.7nm and Halpha+[NII] images and long-slit, high
resolution echelle spectra in the same spectral regions of Sa2--237, a possible
bipolar planetary nebula. The image shows a bipolar nebula of about 34" extent,
with a narrow waist, and showing strong point symmetry about the central
object, indicating it's likely binary nature. The long slit spectra were taken
over the long axis of the nebula, and show a distinct ``eight'' shaped pattern
in the velocity--space plot, and a maximum projected outflow velocity of
V=106km/s, both typical of expanding bipolar planetary nebulae. By model
fitting the shape and spectrum of the nebula simultaneously, we derive the
inclination of the long axis to be 70 degrees, and the maximum space velocity
of expansion to be 308 km/s. Due to asymmetries in the velocities we adopt a
new value for the system's heliocentric radial velocity of -30km/s. We use the
IRAS and 21cm radio fluxes, the energy distribution, and the projected size of
Sa2-237 to estimate it's distance to be 2.1+-0.37kpc. At this distance Sa2-237
has a luminosity of 340 Lsun, a size of 0.37pc, and -- assuming constant
expansion velocity -- a nebular age of 624 years. The above radial velocity and
distance place Sa2--237 in the disk of the Galaxy at z=255pc, albeit with
somewhat peculiar kinematics.Comment: 10pp, 4 fig
Federated learning for medical imaging radiology
Federated learning (FL) is gaining wide acceptance across the medical AI domains. FL promises to provide a fairly acceptable clinical-grade accuracy, privacy, and generalisability of machine learning models across multiple institutions. However, the research on FL for medical imaging AI is still in its early stages. This paper presents a review of recent research to outline the difference between state-of-the-art [SOTA] (published literature) and state-of-the-practice [SOTP] (applied research in realistic clinical environments). Furthermore, the review outlines the future research directions considering various factors such as data, learning models, system design, governance, and human-in-loop to translate the SOTA into SOTP and effectively collaborate across multiple institutions
Can segmentation models be trained with fully synthetically generated data?
In order to achieve good performance and generalisability, medical image
segmentation models should be trained on sizeable datasets with sufficient
variability. Due to ethics and governance restrictions, and the costs
associated with labelling data, scientific development is often stifled, with
models trained and tested on limited data. Data augmentation is often used to
artificially increase the variability in the data distribution and improve
model generalisability. Recent works have explored deep generative models for
image synthesis, as such an approach would enable the generation of an
effectively infinite amount of varied data, addressing the generalisability and
data access problems. However, many proposed solutions limit the user's control
over what is generated. In this work, we propose brainSPADE, a model which
combines a synthetic diffusion-based label generator with a semantic image
generator. Our model can produce fully synthetic brain labels on-demand, with
or without pathology of interest, and then generate a corresponding MRI image
of an arbitrary guided style. Experiments show that brainSPADE synthetic data
can be used to train segmentation models with performance comparable to that of
models trained on real data.Comment: 12 pages, 2 (+2 App.) figures, 3 tables. Accepted at Simulation and
Synthesis in Medical Imaging workshop (MICCAI 2022
Alterations in Mesenteric Lymph Node T Cell Phenotype and Cytokine Secretion are Associated with Changes in Thymocyte Phenotype after LP-BM5 Retrovirus Infection
In this study, mouse MLN cells and thymocytes from advanced stages of
LP-BM5 retrovirus infection were studied. A decrease in
the percentage of IL-7+
cells and an increase in the percentage of IL-16+ cells in the MLN
indicated that
secretion of these cytokines was also altered after LP-BM5 infection. The
percentage of MLN T cells expressing IL-7 receptors was significantly reduced,
while the percentage of MLN T cells expressing TNFR-p75 and of B cells
expressing TNFR-p55 increased. Simultaneous analysis of surface markers and
cytokine secretion was done in an attempt to understand whether the deregulation
of IFN-Υ secretion could be ascribed to a defined cell phenotype, concluding
that
all T cell subsets studied increased IFN-Υ secretion after retrovirus infection.
Finally,
thymocyte phenotype was further analyzed trying to correlate changes in thymocyte
phenotype with MLN cell phenotype. The results indicated that the increase in
single positive either CD4+CD8- or CD4-
CD8+ cells was due to accumulation of
both immature (CD3- ) and mature (CD3+) single
positive thymocytes. Moreover,
single positive mature thymocytes presented a phenotype similar to the phenotype
previously seen on MLN T cells. In summary, we can conclude that LP-BM5 uses
the immune system to reach the thymus where it interferes with the generation of
functionally mature T cells, favoring the development of T cells with an abnormal
phenotype. These new T cells are activated to secrete several cytokines that in turn
will favor retrovirus
replication and inhibit any attempt of the immune system to control infection
Ultrafast Dynamics of Nitro−Nitrite Rearrangement and Dissociation in Nitromethane Cation
We report new insights into the ultrafast rearrange- ment and dissociation dynamics of nitromethane cation (NM+) using pump−probe measurements, electronic structure calculations, and ab initio molecular dynamics simulations. The “roaming” nitro−nitrite rearrangement (NNR) pathway involving large- amplitude atomic motion, which has been previously described for neutral nitromethane, is demonstrated for NM+. Excess energy resulting from initial population of the electronically excited D2 state of NM+ upon strong-field ionization provides the necessary energy to initiate NNR and subsequent dissociation into NO+. Both pump−probe measurements and molecular dynamics simulations are consistent with the completion of NNR within 500 fs of ionization with dissociation into NO+ and OCH3 occurring ∼30 fs later. Pump−probe measurements indicate that NO+ formation is in competition with the direct dissociation of NM+ to CH3+ and NO2. Electronic structure calculations indicate that a strong D0 → D1 transition can be excited at 650 nm when the C−N bond is stretched from its equilibrium value (1.48 Å) to 1.88 Å. On the other hand, relaxation of the NM+ cation after ionization into D0 occurs in less than 50 fs and results in observation of intact NM+. Direct dissociation of the equilibrium NM+ to produce NO2+ and CH3 can be induced with 650 nm excitation via a weakly allowed D0 → D2 transition
High-velocity collimated outflows in planetary nebulae: NGC 6337, He 2-186, and K 4-47
We have obtained narrow-band images and high-resolution spectra of the
planetary nebulae NGC 6337, He 2-186, and K 4-47, with the aim of investigating
the relation between their main morphological components and several
low-ionization features present in these nebulae. The data suggest that NGC
6337 is a bipolar PN seen almost pole on, with polar velocities higher than 200
km/s. The bright inner ring of the nebula is interpreted to be the "equatorial"
density enhancement. It contains a number of low-ionization knots and outward
tails that we ascribe to dynamical instabilities leading to fragmentation of
the ring or transient density enhancements due to the interaction of the
ionization front with previous density fluctuations in the ISM. The lobes show
a pronounced point-symmetric morphology and two peculiar low-ionization
filaments whose nature remains unclear. The most notable characteristic of He
2-186 is the presence of two high-velocity (higher than 135 km/s) knots from
which an S-shaped lane of emission departs toward the central star. K 4-47 is
composed of a compact core and two high-velocity, low-ionization blobs. We
interpret the substantial broadening of line emission from the blobs as a
signature of bow shocks, and using the modeling of Hartigan, Raymond, & Hartman
(1987), we derive a shock velocity of 150 km/s and a mild inclination of the
outflow on the plane of the sky. We discuss possible scenarios for the
formation of these nebulae and their low-ionization features. In particular,
the morphology of K 4-47 hardly fits into any of the usually adopted mass-loss
geometries for single AGB stars. Finally, we discuss the possibility that
point-symmetric morphologies in the lobes of NGC 6337 and the knots of He 2-186
are the result of precessing outflows from the central stars.Comment: 16 pages plus 7 figures, ApJ accepted. Also available at
http://www.iac.es/publicaciones/preprints.htm
The effect of accretion temperature on microstructure and bending strength of atmospheric ice
Accurate determination of the mechanical response of atmospheric ice is key to understanding the risks associated with ice impact on aircraft during flight. Two types of atmospheric ice which are of particular interest to the aerospace industry are studied. Rime and Glaze ice are each manufactured in an icing wind tunnel facility under controlled conditions. Rime ice is accreted at a temperature of −20◦C, and Glaze ice is accreted at −5 ◦C. Quasi-static threepoint bend tests are performed on both types of ice to understand the effect of accretion temperature, and therefore microstructure, on strength. The results indicate that the ice accretion temperature, and thus microstructure, has a significant influence on the bending strength. On average, the bending strength of Rime ice is 9.0 ± 0.18 MPa compared to 4.4 ± 0.093 MPa for Glaze. The comparatively lower accretion temperature of Rime results in smaller grain sizes and higher bending strength. In contrast, the effective modulus appears insensitive to ice microstructure, with an average value of 3.5±0.12 GPa for Rime compared to 3.6±0.098 GPa for Glaze. Furthermore, the results indicate that both the bending strength and effective modulus are insensitive to the ice storage time.Innovate UK: 113155
Rolls-Royce pl
Transformer-based out-of-distribution detection for clinically safe segmentation
In a clinical setting it is essential that deployed image processing systems are robust to the full range of inputs they might encounter and, in particular, do not make confidently wrong predictions. The most popular approach to safe processing is to train networks that can provide a measure of their uncertainty, but these tend to fail for inputs that are far outside the training data distribution. Recently, generative modelling approaches have been proposed as an alternative; these can quantify the likelihood of a data sample explicitly, filtering out any out-of-distribution (OOD) samples before further processing is performed. In this work, we focus on image segmentation and evaluate several approaches to network uncertainty in the far-OOD and near-OOD cases for the task of segmenting haemorrhages in head CTs. We find all of these approaches are unsuitable for safe segmentation as they provide confidently wrong predictions when operating OOD. We propose performing full 3D OOD detection using a VQ-GAN to provide a compressed latent representation of the image and a transformer to estimate the data likelihood. Our approach successfully identifies images in both the far- and near-OOD cases. We find a strong relationship between image likelihood and the quality of a model’s segmentation, making this approach viable for filtering images unsuitable for segmentation. To our knowledge, this is the first time transformers have been applied to perform OOD detection on 3D image data.</p
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