91 research outputs found

    Ideal E/IMRI vs Real E/IMRI system : Observable signature in LISA

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    Real extreme/intermediate mass ratio inspiral(E/IMRI) systems are likely to contain large accretion disks which could be as massive as the central supermassive black hole. Therefore, contrary to its ideal model, a real E/IMRI system contains a third important component: the accretion disk. We study the influence of these disks on the emitted GW profile and its detectability through proposed LISA observation. We use a semi-relativistic formalism in the Kerr background (Gair & Glampedakis 2006; Barausse & Rezzolla 2008) for the case of transonic accretion flow which is a potential candidate to describe the accretion flows around AGN. The hydrodynamic drag of the disks modified the motion of the companion as a result the emitted wave changes in amplitude and phase. We found that these changes are detectable through the last few years of observation by LISA (in some cases as small as six months) for EMRIs residing within 3 GPc from the detector and for the accretion rate of the primary black hole of the order of M˙=1M˙Edd\dot{M}=1 \dot{M}_{Edd}. These choices of parameter values are consistent with real systems. The drag effect and hence the detectability of the emitted GW is sensitive to the hydrodynamical model of the disk. Therefore such observations will help one to identify the nature of the accretion flow and verify various paradigms of accretion physics.Comment: 17 pages, 17 figure

    Room temperature multiferroicity in orthorhombic LuFeO3_3

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    From the measurement of dielectric, ferroelectric, and magnetic properties we observe simultaneous ferroelectric and magnetic transitions around ∼\sim600 K in orthorhombic LuFeO3_3. We also observe suppression of the remanent polarization by ∼\sim95\% under a magnetic field of ∼\sim15 kOe at room temperature. The extent of suppression of the polarization under magnetic field increases monotonically with the field. These results show that even the orthorhombic LuFeO3_3 is a room temperature multiferroic of type-II variety exhibiting quite a strong coupling between magnetization and polarization.Comment: 5 pages with 5 figures; published in Appl. Phys. Let

    FocusMAE: Gallbladder Cancer Detection from Ultrasound Videos with Focused Masked Autoencoders

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    In recent years, automated Gallbladder Cancer (GBC) detection has gained the attention of researchers. Current state-of-the-art (SOTA) methodologies relying on ultrasound sonography (US) images exhibit limited generalization, emphasizing the need for transformative approaches. We observe that individual US frames may lack sufficient information to capture disease manifestation. This study advocates for a paradigm shift towards video-based GBC detection, leveraging the inherent advantages of spatiotemporal representations. Employing the Masked Autoencoder (MAE) for representation learning, we address shortcomings in conventional image-based methods. We propose a novel design called FocusMAE to systematically bias the selection of masking tokens from high-information regions, fostering a more refined representation of malignancy. Additionally, we contribute the most extensive US video dataset for GBC detection. We also note that, this is the first study on US video-based GBC detection. We validate the proposed methods on the curated dataset, and report a new state-of-the-art (SOTA) accuracy of 96.4% for the GBC detection problem, against an accuracy of 84% by current Image-based SOTA - GBCNet, and RadFormer, and 94.7% by Video-based SOTA - AdaMAE. We further demonstrate the generality of the proposed FocusMAE on a public CT-based Covid detection dataset, reporting an improvement in accuracy by 3.3% over current baselines. The source code and pretrained models are available at: https://gbc-iitd.github.io/focusmaeComment: To Appear at CVPR 202

    RadFormer: Transformers with Global-Local Attention for Interpretable and Accurate Gallbladder Cancer Detection

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    We propose a novel deep neural network architecture to learn interpretable representation for medical image analysis. Our architecture generates a global attention for region of interest, and then learns bag of words style deep feature embeddings with local attention. The global, and local feature maps are combined using a contemporary transformer architecture for highly accurate Gallbladder Cancer (GBC) detection from Ultrasound (USG) images. Our experiments indicate that the detection accuracy of our model beats even human radiologists, and advocates its use as the second reader for GBC diagnosis. Bag of words embeddings allow our model to be probed for generating interpretable explanations for GBC detection consistent with the ones reported in medical literature. We show that the proposed model not only helps understand decisions of neural network models but also aids in discovery of new visual features relevant to the diagnosis of GBC. Source-code and model will be available at https://github.com/sbasu276/RadFormerComment: To Appear in Elsevier Medical Image Analysi

    Gall Bladder Cancer Detection from US Images with Only Image Level Labels

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    Automated detection of Gallbladder Cancer (GBC) from Ultrasound (US) images is an important problem, which has drawn increased interest from researchers. However, most of these works use difficult-to-acquire information such as bounding box annotations or additional US videos. In this paper, we focus on GBC detection using only image-level labels. Such annotation is usually available based on the diagnostic report of a patient, and do not require additional annotation effort from the physicians. However, our analysis reveals that it is difficult to train a standard image classification model for GBC detection. This is due to the low inter-class variance (a malignant region usually occupies only a small portion of a US image), high intra-class variance (due to the US sensor capturing a 2D slice of a 3D object leading to large viewpoint variations), and low training data availability. We posit that even when we have only the image level label, still formulating the problem as object detection (with bounding box output) helps a deep neural network (DNN) model focus on the relevant region of interest. Since no bounding box annotations is available for training, we pose the problem as weakly supervised object detection (WSOD). Motivated by the recent success of transformer models in object detection, we train one such model, DETR, using multi-instance-learning (MIL) with self-supervised instance selection to suit the WSOD task. Our proposed method demonstrates an improvement of AP and detection sensitivity over the SOTA transformer-based and CNN-based WSOD methods. Project page is at https://gbc-iitd.github.io/wsod-gbcComment: Accepted at MICCAI 202

    Fe–TiO2_2 composite beads driven hybrid process of photocatalysis and photo-Fenton for the degradation of isoproturon

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    The concept of hybrid process of photo-Fenton and photocatalysis, particularly in the fixed mode, has been presented in this study for the degradation of the pesticide isoproturon with reduction at the time of treatment. For fixed-bed studies, spherical beads were prepared by combining definite proportions of clay, foundry sand, and fly ash, which were utilized as iron sources for titanium dioxide (TiO2) immobilization. The optimization of various parameters was performed by utilizing the Box–Behnken design model under response surface methodology. The process of degradation followed first-order kinetics under an optimized condition for the integrated degradation of isoproturon with a 700 mg⋅{\cdot }L-1 dose of H2O2, 42 spherical beads, and 190 mL of solution for a duration of 176 min at pH 3.7. Approximately 80.96% degradation of isoproturon was observed after inducing the optimized conditions. The integrated treatment was also carried out in a solar batch reactor under optimized conditions to expand its application to industries for treating bio-recalcitrant compounds. The mineralization of isoproturon was confirmed through the generation of nitrate, nitrite, and ammonical nitrogen with a definite chemical oxygen demand reduction. The recyclability of the catalyst was confirmed by recycling the spherical beads characterized by scanning electron microscopy–energy dispersive X-Ray analysis. For confirming the dual effect, that is, the presence of TiO2 along with Fe on the bead’s surface, various analyses including UV–diffuse reflectance spectroscopy, scanning electron microscopy–energy-dispersive spectroscopy, X-ray diffraction, and Fourier-transform infrared spectroscopy were carried out. A tentative pathway for isoproturon removal was also predicted based on intermediate analysis through gas chromatography–mass spectroscopy

    Fe–TiO2_2 composite beads driven hybrid process of photocatalysis and photo-Fenton for the degradation of isoproturon

    Get PDF
    The concept of hybrid process of photo-Fenton and photocatalysis, particularly in the fixed mode, has been presented in this study for the degradation of the pesticide isoproturon with reduction at the time of treatment. For fixed-bed studies, spherical beads were prepared by combining definite proportions of clay, foundry sand, and fly ash, which were utilized as iron sources for titanium dioxide (TiO2) immobilization. The optimization of various parameters was performed by utilizing the Box–Behnken design model under response surface methodology. The process of degradation followed first-order kinetics under an optimized condition for the integrated degradation of isoproturon with a 700 mg⋅{\cdot }L-1 dose of H2O2, 42 spherical beads, and 190 mL of solution for a duration of 176 min at pH 3.7. Approximately 80.96% degradation of isoproturon was observed after inducing the optimized conditions. The integrated treatment was also carried out in a solar batch reactor under optimized conditions to expand its application to industries for treating bio-recalcitrant compounds. The mineralization of isoproturon was confirmed through the generation of nitrate, nitrite, and ammonical nitrogen with a definite chemical oxygen demand reduction. The recyclability of the catalyst was confirmed by recycling the spherical beads characterized by scanning electron microscopy–energy dispersive X-Ray analysis. For confirming the dual effect, that is, the presence of TiO2 along with Fe on the bead’s surface, various analyses including UV–diffuse reflectance spectroscopy, scanning electron microscopy–energy-dispersive spectroscopy, X-ray diffraction, and Fourier-transform infrared spectroscopy were carried out. A tentative pathway for isoproturon removal was also predicted based on intermediate analysis through gas chromatography–mass spectroscopy

    Glutathione-induced aggregation of gold nanoparticles: electromagnetic interactions in a closely packed assembly

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    Gold nanoparticles of variable sizes have been prepared by reducing HAuCl4 with trisodium citrate by Frens' method. The synthesized gold particles show intense surface plasmon band in the visible region. The optical resonances in the visible are due to the surface plasmon oscillation, which is a function of geometry of the particles. The work reported here describes the interaction between nanoscale gold particles and a biomolecule, glutathione at low pH. Glutathione, which is a major cellular antioxidant and consists of amino acids glutamic acid, cysteine, and glycine, has been used as a molecular linker between the gold nanoparticles. In glutathione, the reactivity of the a-amines (adjacent to -COOH) is found to be pH-dependent. Linking via the a-amines are activated at low pH but suppressed at high pH due to electrostatic repulsive forces between the gold surfaces and the charged carboxylate groups. In colloidal solutions, the colour of gold nanoparticles may range from red to purple to blue, depending on the degree of aggregation as well as orientation of the individual particles within the aggregates. The citrate-functionalized gold nanoparticles with glutathione in variable acidic pH condition produce different but well-ordered aggregates. It is observed that a new peak appearing at a longer wavelength intensifies and shifts further to the red from the original peak position depending on the particle size, concentration of glutathione, and pH of the solution. The aggregates have been characterized by UV/Vis, FTIR, XRD, and TEM. On the basis of the first appearance of a clearly defined new peak at longer wavelength, a higher sensitivity of glutathione detection has been achieved with gold nanoparticles of larger dimension
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