91 research outputs found
Ideal E/IMRI vs Real E/IMRI system : Observable signature in LISA
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 . 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 LuFeO
From the measurement of dielectric, ferroelectric, and magnetic properties we
observe simultaneous ferroelectric and magnetic transitions around 600 K
in orthorhombic LuFeO. We also observe suppression of the remanent
polarization by 95\% under a magnetic field of 15 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 LuFeO 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
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
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
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–TiO composite beads driven hybrid process of photocatalysis and photo-Fenton for the degradation of isoproturon
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 mgL-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–TiO composite beads driven hybrid process of photocatalysis and photo-Fenton for the degradation of isoproturon
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 mgL-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
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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