The Digital Anatomist Foundational Model Server

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Localization Recall Precision (LRP): A New Performance Metric for Object Detection

Average precision (AP), the area under the recall-precision (RP) curve, is the standard performance measure for object detection. Despite its wide acceptance, it has a number of shortcomings, the most important of which are (i) the inability to distinguish very different RP curves, and (ii) the lack of directly measuring bounding box localization accuracy. In this paper, we propose 'Localization Recall Precision (LRP) Error', a new metric which we specifically designed for object detection. LRP Error is composed of three components related to localization, false negative (FN) rate and false positive (FP) rate. Based on LRP, we introduce the 'Optimal LRP', the minimum achievable LRP error representing the best achievable configuration of the detector in terms of recall-precision and the tightness of the boxes. In contrast to AP, which considers precisions over the entire recall domain, Optimal LRP determines the 'best' confidence score threshold for a class, which balances the trade-off between localization and recall-precision. In our experiments, we show that, for state-of-the-art object (SOTA) detectors, Optimal LRP provides richer and more discriminative information than AP. We also demonstrate that the best confidence score thresholds vary significantly among classes and detectors. Moreover, we present LRP results of a simple online video object detector which uses a SOTA still image object detector and show that the class-specific optimized thresholds increase the accuracy against the common approach of using a general threshold for all classes. At https://github.com/cancam/LRP we provide the source code that can compute LRP for the PASCAL VOC and MSCOCO datasets. Our source code can easily be adapted to other datasets as well.Comment: to appear in ECCV 201

Star-Forming Brightest Cluster Galaxies at 0.25 < z < 1.25: A Transitioning Fuel Supply

We present a multi-wavelength study of 90 brightest cluster galaxies (BCGs) in a sample of galaxy clusters selected via the Sunyaev Zel'dovich effect by the South Pole Telescope, utilizing data from various ground- and space-based facilities. We infer the star formation rate (SFR) for the BCG in each cluster, based on the UV and IR continuum luminosity, as well as the [O II] emission line luminosity in cases where spectroscopy is available, finding 7 systems with SFR > 100 Msun/yr. We find that the BCG SFR exceeds 10 Msun/yr in 31 of 90 (34%) cases at 0.25 < z < 1.25, compared to ~1-5% at z ~ 0 from the literature. At z > 1, this fraction increases to 92(+6)(-31)%, implying a steady decrease in the BCG SFR over the past ~9 Gyr. At low-z, we find that the specific star formation rate in BCGs is declining more slowly with time than for field or cluster galaxies, most likely due to the replenishing fuel from the cooling ICM in relaxed, cool core clusters. At z > 0.6, the correlation between cluster central entropy and BCG star formation - which is well established at z ~ 0 - is not present. Instead, we find that the most star-forming BCGs at high-z are found in the cores of dynamically unrelaxed clusters. We investigate the rest-frame near-UV morphology of a subsample of the most star-forming BCGs using data from the Hubble Space Telescope, finding complex, highly asymmetric UV morphologies on scales as large as ~50-60 kpc. The high fraction of star-forming BCGs hosted in unrelaxed, non-cool core clusters at early times suggests that the dominant mode of fueling star formation in BCGs may have recently transitioned from galaxy-galaxy interactions to ICM cooling.Comment: 20 pages, 10 figures. Submitted for publication in ApJ. Comments welcom

Universality in metallic nanocohesion: a quantum chaos approach

Convergent semiclassical trace formulae for the density of states and cohesive force of a narrow constriction in an electron gas, whose classical motion is either chaotic or integrable, are derived. It is shown that mode quantization in a metallic point contact or nanowire leads to universal oscillations in its cohesive force: the amplitude of the oscillations depends only on a dimensionless quantum parameter describing the crossover from chaotic to integrable motion, and is of order 1 nano-Newton, in agreement with recent experiments. Interestingly, quantum tunneling is shown to be described quantitatively in terms of the instability of the classical periodic orbits.Comment: corrects spelling of one author name on abstract page (paper is unchanged

SPT-CL J0205–5829: A z = 1.32 Evolved Massive Galaxy Cluster in the South Pole Telescope Sunyaev-Zel'dovich Effect Survey

The galaxy cluster SPT-CL J0205–5829 currently has the highest spectroscopically confirmed redshift, z = 1.322, in the South Pole Telescope Sunyaev-Zel'dovich (SPT-SZ) survey. XMM-Newton observations measure a core-excluded temperature of T_X = 8.7^(+1.0)_(–0.8) keV producing a mass estimate that is consistent with the Sunyaev-Zel'dovich-derived mass. The combined SZ and X-ray mass estimate of M_(500) = (4.8 ± 0.8) × 10^(14) h^(–1)_(70) M_☉ makes it the most massive known SZ-selected galaxy cluster at z > 1.2 and the second most massive at z > 1. Using optical and infrared observations, we find that the brightest galaxies in SPT-CL J0205–5829 are already well evolved by the time the universe was <5 Gyr old, with stellar population ages ≳3 Gyr, and low rates of star formation (<0.5 M_☉ yr^(–1)). We find that, despite the high redshift and mass, the existence of SPT-CL J0205–5829 is not surprising given a flat ΛCDM cosmology with Gaussian initial perturbations. The a priori chance of finding a cluster of similar rarity (or rarer) in a survey the size of the 2500 deg^2 SPT-SZ survey is 69%

Observations of the GRB afterglow ATLAS17aeu and its possible association with GW170104

We report the discovery and multi-wavelength data analysis of the peculiar optical transient, ATLAS17aeu. This transient was identified in the skymap of the LIGO gravitational wave event GW170104 by our ATLAS and Pan-STARRS coverage. ATLAS17aeu was discovered 23.1hrs after GW170104 and rapidly faded over the next 3 nights, with a spectrum revealing a blue featureless continuum. The transient was also detected as a fading x-ray source by Swift and in the radio at 6 and 15 GHz. A gamma ray burst GRB170105A was detected by 3 satellites 19.04hrs after GW170104 and 4.10hrs before our first optical detection. We analyse the multi-wavelength fluxes in the context of the known GRB population and discuss the observed sky rates of GRBs and their afterglows. We find it statistically likely that ATLAS17aeu is an afterglow associated with GRB170105A, with a chance coincidence ruled out at the 99\% confidence or 2.6$\sigma$. A long, soft GRB within a redshift range of $1 \lesssim z \lesssim 2.9$ would be consistent with all the observed multi-wavelength data. The Poisson probability of a chance occurrence of GW170104 and ATLAS17aeu is $p=0.04$. This is the probability of a chance coincidence in 2D sky location and in time. These observations indicate that ATLAS17aeu is plausibly a normal GRB afterglow at significantly higher redshift than the distance constraint for GW170104 and therefore a chance coincidence. However if a redshift of the faint host were to place it within the GW170104 distance range, then physical association with GW170104 should be considered.Comment: 16 pages, 6 figures, accepted to Ap

Managing pregnancy of unknown location based on initial serum progesterone and serial serum hCG: development and validation of a two-step triage protocol.

A uniform rationalized management protocol for pregnancies of unknown location (PUL) is lacking. We developed a two-step triage protocol based on presenting serum progesterone (step 1) and hCG ratio two days later (step 2) to select PUL at high-risk of ectopic pregnancy (EP).Cohort study of 2753 PUL (301 EP), involving a secondary analysis of prospectively and consecutively collected PUL at two London-based university teaching hospitals. Using a chronological split we used 1449 PUL for development and 1304 for validation. We aimed to select PUL as low-risk with high confidence (high negative predictive value, NPV) while classifying most EP as high-risk (high sensitivity). The first triage step selects low-risk PUL at presentation using a serum progesterone threshold. The remaining PUL are triaged using a novel logistic regression risk model based on hCG ratio and initial serum progesterone (second step), defining low-risk as an estimated EP risk <5%.On validation, initial serum progesterone ≤2nmol/l (step 1) selected 16.1% PUL as low-risk. Second step classification with the risk model M6P selected an additional 46.0% of all PUL as low-risk. Overall, the two-step protocol classified 62.1% of PUL as low-risk, with an NPV of 98.6% and a sensitivity of 92.0%. When the risk model was used in isolation (i.e. without the first step), 60.5% of PUL were classified as low-risk with 99.1% NPV and 94.9% sensitivity.The two-step protocol can efficiently classify PUL into being at high or low risk of complications