LVM-Med: Learning Large-Scale Self-Supervised Vision Models for Medical Imaging via Second-order Graph Matching

Obtaining large pre-trained models that can be fine-tuned to new tasks with limited annotated samples has remained an open challenge for medical imaging data. While pre-trained deep networks on ImageNet and vision-language foundation models trained on web-scale data are prevailing approaches, their effectiveness on medical tasks is limited due to the significant domain shift between natural and medical images. To bridge this gap, we introduce LVM-Med, the first family of deep networks trained on large-scale medical datasets. We have collected approximately 1.3 million medical images from 55 publicly available datasets, covering a large number of organs and modalities such as CT, MRI, X-ray, and Ultrasound. We benchmark several state-of-the-art self-supervised algorithms on this dataset and propose a novel self-supervised contrastive learning algorithm using a graph-matching formulation. The proposed approach makes three contributions: (i) it integrates prior pair-wise image similarity metrics based on local and global information; (ii) it captures the structural constraints of feature embeddings through a loss function constructed via a combinatorial graph-matching objective; and (iii) it can be trained efficiently end-to-end using modern gradient-estimation techniques for black-box solvers. We thoroughly evaluate the proposed LVM-Med on 15 downstream medical tasks ranging from segmentation and classification to object detection, and both for the in and out-of-distribution settings. LVM-Med empirically outperforms a number of state-of-the-art supervised, self-supervised, and foundation models. For challenging tasks such as Brain Tumor Classification or Diabetic Retinopathy Grading, LVM-Med improves previous vision-language models trained on 1 billion masks by 6-7% while using only a ResNet-50.Comment: Update Appendi

First-Order Melting of a Moving Vortex Lattice: Effects of Disorder

We study the melting of a moving vortex lattice through numerical simulations with the current driven 3D XY model with disorder. We find that there is a first-order phase transition even for large disorder when the corresponding equilibrium transition is continuous. The low temperature phase is an anisotropic moving glass.Comment: Important changes from original version. Finite size analysis of results has been added. Figure 2 has been changed. There is a new additional Figure. To be published in Physical Review Letter

Force distributions in 3D granular assemblies: Effects of packing order and inter-particle friction

We present a systematic investigation of the distribution of normal forces at the boundaries of static packings of spheres. A new method for the efficient construction of large hexagonal-close-packed crystals is introduced and used to study the effect of spatial ordering on the distribution of forces. Under uniaxial compression we find that the form for the probability distribution of normal forces between particles does not depend strongly on crystallinity or inter-particle friction. In all cases the distribution decays exponentially at large forces and shows a plateau or possibly a small peak near the average force but does not tend to zero at small forces.Comment: 9 pages including 8 figure

Minimum information and guidelines for reporting a Multiplexed Assay of Variant Effect

Multiplexed Assays of Variant Effect (MAVEs) have emerged as a powerful approach for interrogating thousands of genetic variants in a single experiment. The flexibility and widespread adoption of these techniques across diverse disciplines has led to a heterogeneous mix of data formats and descriptions, which complicates the downstream use of the resulting datasets. To address these issues and promote reproducibility and reuse of MAVE data, we define a set of minimum information standards for MAVE data and metadata and outline a controlled vocabulary aligned with established biomedical ontologies for describing these experimental designs

Exciton bimolecular annihilation dynamics in supramolecular nanostructures of conjugated oligomers

We present femtosecond transient absorption measurements on $\pi$-conjugated supramolecular assemblies in a high pump fluence regime. Oligo(\emph{p}-phenylenevinylene) monofunctionalized with ureido-\emph{s}-triazine (MOPV) self-assembles into chiral stacks in dodecane solution below 75$^{\circ}$C at a concentration of $4\times 10^{-4}$ M. We observe exciton bimolecular annihilation in MOPV stacks at high excitation fluence, indicated by the fluence-dependent decay of $1^1$B$_{u}$-exciton spectral signatures, and by the sub-linear fluence dependence of time- and wavelength-integrated photoluminescence (PL) intensity. These two characteristics are much less pronounced in MOPV solution where the phase equilibrium is shifted significantly away from supramolecular assembly, slightly below the transition temperature. A mesoscopic rate-equation model is applied to extract the bimolecular annihilation rate constant from the excitation fluence dependence of transient absorption and PL signals. The results demonstrate that the bimolecular annihilation rate is very high with a square-root dependence in time. The exciton annihilation results from a combination of fast exciton diffusion and resonance energy transfer. The supramolecular nanostructures studied here have electronic properties that are intermediate between molecular aggregates and polymeric semiconductors

Very-High-Energy γ\gamma-Ray Observations of the Blazar 1ES 2344+514 with VERITAS

We present very-high-energy $\gamma$-ray observations of the BL Lac object 1ES 2344+514 taken by the Very Energetic Radiation Imaging Telescope Array System (VERITAS) between 2007 and 2015. 1ES 2344+514 is detected with a statistical significance above background of $20.8\sigma$ in $47.2$ hours (livetime) of observations, making this the most comprehensive very-high-energy study of 1ES 2344+514 to date. Using these observations the temporal properties of 1ES 2344+514 are studied on short and long times scales. We fit a constant flux model to nightly- and seasonally-binned light curves and apply a fractional variability test, to determine the stability of the source on different timescales. We reject the constant-flux model for the 2007-2008 and 2014-2015 nightly-binned light curves and for the long-term seasonally-binned light curve at the $> 3\sigma$ level. The spectra of the time-averaged emission before and after correction for attenuation by the extragalactic background light are obtained. The observed time-averaged spectrum above 200 GeV is satisfactorily fitted (${\chi^2/NDF = 7.89/6}$) by a power-law function with index $\Gamma = 2.46 \pm 0.06_{stat} \pm 0.20_{sys}$ and extends to at least 8 TeV. The extragalactic-background-light-deabsorbed spectrum is adequately fit (${\chi^2/NDF = 6.73/6}$) by a power-law function with index $\Gamma = 2.15 \pm 0.06_{stat} \pm 0.20_{sys}$ while an F-test indicates that the power-law with exponential cutoff function provides a marginally-better fit ($\chi^2/NDF$ = $2.56 / 5$) at the 2.1$\sigma$ level. The source location is found to be consistent with the published radio location and its spatial extent is consistent with a point source.Comment: 7 pages, 2 figures. Published in Monthly Notices of the Royal Astronomical Societ

Cracking in asphalt materials

This chapter provides a comprehensive review of both laboratory characterization and modelling of bulk material fracture in asphalt mixtures. For the purpose of organization, this chapter is divided into a section on laboratory tests and a section on models. The laboratory characterization section is further subdivided on the basis of predominant loading conditions (monotonic vs. cyclic). The section on constitutive models is subdivided into two sections, the first one containing fracture mechanics based models for crack initiation and propagation that do not include material degradation due to cyclic loading conditions. The second section discusses phenomenological models that have been developed for crack growth through the use of dissipated energy and damage accumulation concepts. These latter models have the capability to simulate degradation of material capacity upon exceeding a threshold number of loading cycles.Peer ReviewedPostprint (author's final draft

Design of Experiments for Screening

The aim of this paper is to review methods of designing screening experiments, ranging from designs originally developed for physical experiments to those especially tailored to experiments on numerical models. The strengths and weaknesses of the various designs for screening variables in numerical models are discussed. First, classes of factorial designs for experiments to estimate main effects and interactions through a linear statistical model are described, specifically regular and nonregular fractional factorial designs, supersaturated designs and systematic fractional replicate designs. Generic issues of aliasing, bias and cancellation of factorial effects are discussed. Second, group screening experiments are considered including factorial group screening and sequential bifurcation. Third, random sampling plans are discussed including Latin hypercube sampling and sampling plans to estimate elementary effects. Fourth, a variety of modelling methods commonly employed with screening designs are briefly described. Finally, a novel study demonstrates six screening methods on two frequently-used exemplars, and their performances are compared

Studies on Dibenzylamines as Inhibitors of Venezuelan Equine Encephalitis Virus

Alphaviruses are arthropod-transmitted members of the Togaviridae family that can cause severe disease in humans, including debilitating arthralgia and severe neurological complications. Currently, there are no approved vaccines or antiviral therapies directed against the alphaviruses, and care is limited to treating disease symptoms. A phenotypic cell-based high-throughput screen was performed to identify small molecules that inhibit the replication of Venezuelan Equine Encephalitis Virus (VEEV). The compound, 1-(2,3-dihydrobenzo[b][1,4]dioxin-6-yl)-N-(3-fluoro-4-methoxybenzyl)ethan-1-amine (1), was identified as a highly active, potent inhibitor of VEEV with an effective concentration for 90% inhibition of virus (EC90) of 0.89 μM and 7.49 log reduction in virus titers at 10 μM concentration. These data suggest that further investigation of compound 1 as an antiviral therapeutic against VEEV, and perhaps other alphaviruses, is warranted. Experiments suggested that the antiviral activity of compound 1 is directed at an early step in the VEEV replication cycle by blocking viral RNA and protein synthesis

Weight Loss after Roux-en-Y Gastric Bypass in Obese Patients Heterozygous for MC4R Mutations

BackgroundHeterozygous mutations in melanocortin-4 receptor (MC4R) are the most frequent genetic cause of obesity. Bariatric surgery is a successful treatment for severe obesity. The mechanisms of weight loss after bariatric surgery are not well understood.MethodsNinety-two patients who had Roux-en-Y gastric bypass (RYGB) surgery were screened for MC4R mutations. We compared percent excess weight loss (%EWL) in the four MC4R mutation carriers with that of two control groups: 8 matched controls and with the remaining 80 patients who underwent RYGB.ResultsFour patients were heterozygous for functionally significant MC4R mutations. In patients with MC4R mutations, the %EWL after RYGB (66% EWL) was not significantly different compared to matched controls (70% EWL) and non-matched controls (60% EWL) after 1 year of follow-up.ConclusionsThis study suggests that patients with heterozygous MC4R mutations also benefit from RYGB and that weight loss may be independent of the presence of such mutations