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