imageseg: An R package for deep learning-based image segmentation

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2022 The Authors. Methods in Ecology and Evolution published by John Wiley & Sons Ltd on behalf of British Ecological SocietyConvolutional neural networks (CNNs) and deep learning are powerful and robust tools for ecological applications and are particularly suited for image data. Image segmentation (the classification of all pixels in images) is one such application and can, for example, be used to assess forest structural metrics. While CNN-based image segmentation methods for such applications have been suggested, widespread adoption in ecological research has been slow, likely due to technical difficulties in implementation of CNNs and lack of toolboxes for ecologists. Here, we present R package imageseg which implements a CNN-based workflow for general purpose image segmentation using the U-Net and U-Net++ architectures in R. The workflow covers data (pre)processing, model training and predictions. We illustrate the utility of the package with image recognition models for two forest structural metrics: tree canopy density and understorey vegetation density. We trained the models using large and diverse training datasets from a variety of forest types and biomes, consisting of 2877 canopy images (both canopy cover and hemispherical canopy closure photographs) and 1285 understorey vegetation images. Overall segmentation accuracy of the models was high with a Dice score of 0.91 for the canopy model and 0.89 for the understorey vegetation model (assessed with 821 and 367 images respectively). The image segmentation models performed significantly better than commonly used thresholding methods and generalized well to data from study areas not included in training. This indicates robustness to variation in input images and good generalization strength across forest types and biomes. The package and its workflow allow simple yet powerful assessments of forest structural metrics using pretrained models. Furthermore, the package facilitates custom image segmentation with single or multiple classes and based on colour or grayscale images, for example, for applications in cell biology or for medical images. Our package is free, open source and available from CRAN. It will enable easier and faster implementation of deep learning-based image segmentation within R for ecological applications and beyond.publishedVersio

Shifting up a gear with iDNA: From mammal detection events to standardised surveys

Invertebrate-derived DNA (iDNA), in combination with high throughput sequencing, has been proposed as a cost-efficient and powerful tool to survey vertebrate species. Previous studies, however, have only provided evidence that vertebrates can be detected using iDNA, but have not taken the next step of placing these detection events within a statistical framework that allows for robust biodiversity assessments. Here, we compare concurrent iDNA and camera-trap surveys. Leeches were repeatedly collected in close vicinity to 64 camera-trap stations in Sabah, Malaysian Borneo. We analyse iDNA-derived mammalian detection events in a modern occupancy model that accounts for imperfect detection and compare the results with those from occupancy models parameterised with camera-trap-derived detection events. We also combine leech-iDNA and camera-trap data in a single occupancy model. We found consistent estimates of occupancy probabilities produced by our camera-trap and leech datasets. This indicates that the metabarcoding of leech-iDNA method provides reasonable estimates of occupancy and may be a suitable method for studying and monitoring mammal species in tropical rainforests. However, we also show that a more extensive collection of leeches would be needed to assess mammal biodiversity with a robustness similar to that of camera traps. As certain taxa were only detected in leeches, we see great potential in complementing camera-trap studies with the iDNA approach, as long as the collection of leeches follows a robust and standardised sampling scheme. Synthesis and applications. Here, we describe an approach to analyse detection records of mammals derived from leech samples using an occupancy framework that accounts for leech-specific factors influencing the detection probability. We further combined camera trap and leech data, which lead to increased confidence in occupancy estimates. Our approach is not restricted to the processing of leech samples, but can be used for the analysis of other invertebrate DNA and environmental DNA data. Our study is the first step to shift the application of invertebrate DNA studies from opportunistic ad-hoc collections to the systematic surveys required for long-term management of wildlife populations

X(3872): Hadronic Molecules in Effective Field Theory

We consider the implications from the possibility that the recently observed state X(3872) is a meson-antimeson molecule. We write an effective Lagrangian consistent with the heavy-quark and chiral symmetries needed to describe X(3872). We claim that if X(3872) is a molecular bound state of D^*0 and anti-D^0 mesons, the heavy-quark symmetry requires the existence of the molecular bound state X_b of B^*0 and anti-B^0 with the mass of 10604 MeV.Comment: 12 pages, 1 figure, 1 table, RevTe

MHCII-mediated dialog between group 2 innate lymphoid cells and CD4+ T cells potentiates type 2 immunity and promotes parasitic helminth expulsion

Group 2 innate lymphoid cells (ILC2s) release interleukin-13 (IL-13) during protective immunity to helminth infection and detrimentally during allergy and asthma. Using two mouse models to deplete ILC2s in vivo, we demonstrate that T helper 2 (Th2) cell responses are impaired in the absence of ILC2s. We show that MHCII-expressing ILC2s interact with antigen-specific T cells to instigate a dialog in which IL-2 production from T cells promotes ILC2 proliferation and IL-13 production. Deletion of MHCII renders IL-13-expressing ILC2s incapable of efficiently inducing Nippostrongylus brasiliensis expulsion. Thus, during transition to adaptive T cell-mediated immunity, the ILC2 and T cell crosstalk contributes to their mutual maintenance, expansion and cytokine production. This interaction appears to augment dendritic-cell-induced T cell activation and identifies a previously unappreciated pathway in the regulation of type-2 immunity

The Hubble Space Telescope Wide Field Camera 3 Early Release Science data: Panchromatic Faint Object Counts for 0.2-2 microns wavelength

We describe the Hubble Space Telescope (HST) Wide Field Camera 3 (WFC3) Early Release Science (ERS) observations in the Great Observatories Origins Deep Survey (GOODS) South field. The new WFC3 ERS data provide calibrated, drizzled mosaics in the UV filters F225W, F275W, and F336W, as well as in the near-IR filters F098M (Ys), F125W (J), and F160W (H) with 1-2 HST orbits per filter. Together with the existing HST Advanced Camera for Surveys (ACS) GOODS-South mosaics in the BViz filters, these panchromatic 10-band ERS data cover 40-50 square arcmin at 0.2-1.7 {\mu}m in wavelength at 0.07-0.15" FWHM resolution and 0.090" Multidrizzled pixels to depths of AB\simeq 26.0-27.0 mag (5-{\sigma}) for point sources, and AB\simeq 25.5-26.5 mag for compact galaxies. In this paper, we describe: a) the scientific rationale, and the data taking plus reduction procedures of the panchromatic 10-band ERS mosaics; b) the procedure of generating object catalogs across the 10 different ERS filters, and the specific star-galaxy separation techniques used; and c) the reliability and completeness of the object catalogs from the WFC3 ERS mosaics. The excellent 0.07-0.15" FWHM resolution of HST/WFC3 and ACS makes star- galaxy separation straightforward over a factor of 10 in wavelength to AB\simeq 25-26 mag from the UV to the near-IR, respectively.Comment: 51 pages, 71 figures Accepted to ApJS 2011.01.2

The Effect of Bound Dineutrons upon BBN

We have examined the effects of a bound dineutron, n2, upon big bang nucleosynthesis (BBN) as a function of its binding energy B_n2. We find a weakly bound dineutron has little impact but as B_n2 increases its presence begins to alter the flow of free nucleons to helium-4. Due to this disruption, and in the absence of changes to other binding energies or fundamental constants, BBN sets a reliable upper limit of B_n2 <~ 2.5 MeV in order to maintain the agreement with the observations of the primordial helium-4 mass fraction and D/H abundance

Respiratory Syncytial Virus NS1 Protein Colocalizes with Mitochondrial Antiviral Signaling Protein MAVS following Infection

Respiratory syncytial virus (RSV) nonstructural protein 1(NS1) attenuates type-I interferon (IFN) production during RSV infection; however the precise role of RSV NS1 protein in orchestrating the early host-virus interaction during infection is poorly understood. Since NS1 constitutes the first RSV gene transcribed and the production of IFN depends upon RLR (RIG-I-like receptor) signaling, we reasoned that NS1 may interfere with this signaling. Herein, we report that NS1 is localized to mitochondria and binds to mitochondrial antiviral signaling protein (MAVS). Live-cell imaging of rgRSV-infected A549 human epithelial cells showed that RSV replication and transcription occurs in proximity to mitochondria. NS1 localization to mitochondria was directly visualized by confocal microscopy using a cell-permeable chemical probe for His6-NS1. Further, NS1 colocalization with MAVS in A549 cells infected with RSV was shown by confocal laser microscopy and immuno-electron microscopy. NS1 protein is present in the mitochondrial fraction and co-immunoprecipitates with MAVS in total cell lysatesof A549 cells transfected with the plasmid pNS1-Flag. By immunoprecipitation with anti-RIG-I antibody, RSV NS1 was shown to associate with MAVS at an early stage of RSV infection, and to disrupt MAVS interaction with RIG-I (retinoic acid inducible gene) and the downstream IFN antiviral and inflammatory response. Together, these results demonstrate that NS1 binds to MAVS and that this binding inhibits the MAVS-RIG-I interaction required for IFN production

Wave Function Based Characteristics of Hybrid Mesons

We propose some extensions of the quark potential model to hybrids, fit them to the lattice data and use them for the purpose of calculating the masses, root mean square radii and wave functions at the origin of the conventional and hybrid charmonium mesons. We treat the ground and excited gluonic field between a quark and an antiquark as in the Born-Oppenheimer expansion, and use the shooting method to numerically solve the required Schr$\ddot{\textrm{o}}$dinger equation for the radial wave functions; from these wave functions we calculate the mesonic properties. For masses we also check through a Crank Nichelson discretization. For hybrid charmonium mesons, we consider the exotic quantum number states with $J^{PC} = 0^{+ -}, 1^{- +}$ and $2^{+ -}$. We also compare our results with the experimentally observed masses and theoretically predicted results of the other models. Our results have implications for scalar form factors, energy shifts, magnetic polarizabilities, decay constants, decay widths and differential cross sections of conventional and hybrid mesons.Comment: 13 pages, 6 figures, Erratum is submitted to EPJ

RIG-I, MDA5 and TLR3 Synergistically Play an Important Role in Restriction of Dengue Virus Infection

Dengue virus (DV) infection is one of the most common mosquito-borne viral diseases in the world. The innate immune system is important for the early detection of virus and for mounting a cascade of defense measures which include the production of type 1 interferon (IFN). Hence, a thorough understanding of the innate immune response during DV infection would be essential for our understanding of the DV pathogenesis. A recent application of the microarray to dengue virus type 1 (DV1) infected lung carcinoma cells revealed the increased expression of both extracellular and cytoplasmic pattern recognition receptors; retinoic acid inducible gene-I (RIG-I), melanoma differentiation associated gene-5 (MDA-5) and Toll-like receptor-3 (TLR3). These intracellular RNA sensors were previously reported to sense DV infection in different cells. In this study, we show that they are collectively involved in initiating an effective IFN production against DV. Cells silenced for these genes were highly susceptible to DV infection. RIG-I and MDA5 knockdown HUH-7 cells and TLR3 knockout macrophages were highly susceptible to DV infection. When cells were silenced for only RIG-I and MDA5 (but not TLR3), substantial production of IFN-β was observed upon virus infection and vice versa. High susceptibility to virus infection led to ER-stress induced apoptosis in HUH-7 cells. Collectively, our studies demonstrate that the intracellular RNA virus sensors (RIG-I, MDA5 and TLR3) are activated upon DV infection and are essential for host defense against the virus