HardIDX: Practical and Secure Index with SGX

Software-based approaches for search over encrypted data are still either challenged by lack of proper, low-leakage encryption or slow performance. Existing hardware-based approaches do not scale well due to hardware limitations and software designs that are not specifically tailored to the hardware architecture, and are rarely well analyzed for their security (e.g., the impact of side channels). Additionally, existing hardware-based solutions often have a large code footprint in the trusted environment susceptible to software compromises. In this paper we present HardIDX: a hardware-based approach, leveraging Intel's SGX, for search over encrypted data. It implements only the security critical core, i.e., the search functionality, in the trusted environment and resorts to untrusted software for the remainder. HardIDX is deployable as a highly performant encrypted database index: it is logarithmic in the size of the index and searches are performed within a few milliseconds rather than seconds. We formally model and prove the security of our scheme showing that its leakage is equivalent to the best known searchable encryption schemes. Our implementation has a very small code and memory footprint yet still scales to virtually unlimited search index sizes, i.e., size is limited only by the general - non-secure - hardware resources

Geodesic Information Flows: Spatially-Variant Graphs and Their Application to Segmentation and Fusion

Clinical annotations, such as voxel-wise binary or probabilistic tissue segmentations, structural parcellations, pathological regionsof- interest and anatomical landmarks are key to many clinical studies. However, due to the time consuming nature of manually generating these annotations, they tend to be scarce and limited to small subsets of data. This work explores a novel framework to propagate voxel-wise annotations between morphologically dissimilar images by diffusing and mapping the available examples through intermediate steps. A spatially-variant graph structure connecting morphologically similar subjects is introduced over a database of images, enabling the gradual diffusion of information to all the subjects, even in the presence of large-scale morphological variability. We illustrate the utility of the proposed framework on two example applications: brain parcellation using categorical labels and tissue segmentation using probabilistic features. The application of the proposed method to categorical label fusion showed highly statistically significant improvements when compared to state-of-the-art methodologies. Significant improvements were also observed when applying the proposed framework to probabilistic tissue segmentation of both synthetic and real data, mainly in the presence of large morphological variability

Accurate multimodal probabilistic prediction of conversion to Alzheimer's disease in patients with mild cognitive impairment

Accurately identifying the patients that have mild cognitive impairment (MCI) who will go on to develop Alzheimer's disease (AD) will become essential as new treatments will require identification of AD patients at earlier stages in the disease process. Most previous work in this area has centred around the same automated techniques used to diagnose AD patients from healthy controls, by coupling high dimensional brain image data or other relevant biomarker data to modern machine learning techniques. Such studies can now distinguish between AD patients and controls as accurately as an experienced clinician. Models trained on patients with AD and control subjects can also distinguish between MCI patients that will convert to AD within a given timeframe (MCI-c) and those that remain stable (MCI-s), although differences between these groups are smaller and thus, the corresponding accuracy is lower. The most common type of classifier used in these studies is the support vector machine, which gives categorical class decisions. In this paper, we introduce Gaussian process (GP) classification to the problem. This fully Bayesian method produces naturally probabilistic predictions, which we show correlate well with the actual chances of converting to AD within 3 years in a population of 96 MCI-s and 47 MCI-c subjects. Furthermore, we show that GPs can integrate multimodal data (in this study volumetric MRI, FDG-PET, cerebrospinal fluid, and APOE genotype with the classification process through the use of a mixed kernel). The GP approach aids combination of different data sources by learning parameters automatically from training data via type-II maximum likelihood, which we compare to a more conventional method based on cross validation and an SVM classifier. When the resulting probabilities from the GP are dichotomised to produce a binary classification, the results for predicting MCI conversion based on the combination of all three types of data show a balanced accuracy of 74%. This is a substantially higher accuracy than could be obtained using any individual modality or using a multikernel SVM, and is competitive with the highest accuracy yet achieved for predicting conversion within three years on the widely used ADNI dataset

Altered visual and haptic verticality perception in posterior cortical atrophy and Alzheimer's disease

Abstract: There is increasing theoretical and empirical support for the brain combining multisensory information to determine the direction of gravity and hence uprightness. A fundamental part of the process is the spatial transformation of sensory signals between reference frames: eye-centred, head-centred, body-centred, etc. The question ‘Am I the right way up?’ posed by a patient with posterior cortical atrophy (PCA) suggests disturbances in upright perception, subsequently investigated in PCA and typical Alzheimer's disease (tAD) based on what looks or feels upright. Participants repeatedly aligned to vertical a rod presented either visually (visual-vertical) or haptically (haptic-vertical). Visual-vertical involved orienting a projected rod presented without or with a visual orientation cue (circle, tilted square (±18°)). Haptic-vertical involved orientating a grasped rod with eyes closed using a combination of side (left, right) and hand (unimanual, bimanual) configurations. Intraindividual uncertainty and bias defined verticality perception. Uncertainty was consistently greater in both patient groups than in control groups, and greater in PCA than tAD. Bias in the frontal plane was strongly directionally affected by visual cue tilt (visual-vertical) and grip side (haptic-vertical). A model was developed that assumed verticality information from multiple sources is combined in a statistically optimal way to produce observed uncertainties and biases. Model results suggest the mechanism that spatially transforms graviceptive information between body parts is disturbed in both patient groups. Despite visual dysfunction being typically considered the primary feature of PCA, disturbances were greater in PCA than tAD particularly for haptic-vertical, and are considered in light of posterior parietal vulnerability. (Figure presented.). Key points: The perception of upright requires accurate and precise estimates of orientation based on multiple noisy sensory signals. The question ‘Am I the right way up?’ posed by a patient with posterior cortical atrophy (PCA; purported ‘visual variant Alzheimer's’) suggests disturbances in the perception of upright. What looks or feels upright in PCA and typical Alzheimer's disease (tAD) was investigated by asking participants to repeatedly align to vertical a rod presented visually (visual-vertical) or haptically (haptic-vertical). PCA and tAD groups exhibited not only greater perceptual uncertainty than controls, but also exaggerated bias induced by tilted visual orientation cues (visual-vertical) and grip side (haptic-vertical). When modelled, these abnormalities, which were particularly evident in PCA haptic-vertical performance, were compatible with disruption of a mechanism that spatially transforms verticality information between body parts. The findings suggest an important role of posterior parietal cortex in verticality perception, and have implications for understanding spatial disorientation in dementia. © 2021 The Authors. The Journal of Physiology published by John Wiley & Sons Ltd on behalf of The Physiological Society

The Discovery of Argon in Comet C/1995 O1 (Hale-Bopp)

On 30.14 March 1997 we observed the EUV spectrum of the bright comet C/1995 O1 (Hale-Bopp) at the time of its perihelion, using our EUVS sounding rocket telescope/spectrometer. The spectra reveal the presence H Ly beta, O+, and, most notably, Argon. Modelling of the retrieved Ar production rates indicates that comet Hale-Bopp is enriched in Ar relative to cosmogonic expectations. This in turn indicates that Hale-Bopp's deep interior has never been exposed to the 35-40 K temperatures necessary to deplete the comet's primordial argon supply.Comment: 9 pages, 2 figures. ApJ, 545, in press (2000

Spatial Correlation Function of X-ray Selected AGN

We present a detailed description of the first direct measurement of the spatial correlation function of X-ray selected AGN. This result is based on an X-ray flux-limited sample of 219 AGN discovered in the contiguous 80.7 deg^2 region of the ROSAT North Ecliptic Pole (NEP) Survey. Clustering is detected at the 4 sigma level at comoving scales in the interval r = 5-60 h^-1 Mpc. Fitting the data with a power law of slope gamma=1.8, we find a correlation length of r_0 = 7.4 (+1.8, -1.9) h^-1 Mpc (Omega_M=0.3, Omega_Lambda=0.7). The median redshift of the AGN contributing to the signal is z_xi=0.22. This clustering amplitude implies that X-ray selected AGN are spatially distributed in a manner similar to that of optically selected AGN. Furthermore, the ROSAT NEP determination establishes the local behavior of AGN clustering, a regime which is poorly sampled in general. Combined with high-redshift measures from optical studies, the ROSAT NEP results argue that the AGN correlation strength essentially does not evolve with redshift, at least out to z~2.2. In the local Universe, X-ray selected AGN appear to be unbiased relative to galaxies and the inferred X-ray bias parameter is near unity, b_X~1. Hence X-ray selected AGN closely trace the underlying mass distribution. The ROSAT NEP AGN catalog, presented here, features complete optical identifications and spectroscopic redshifts. The median redshift, X-ray flux, and X-ray luminosity are z=0.41, f_X=1.1*10^-13 cgs, and L_X=9.2*10^43 h_70^-2 cgs (0.5-2.0 keV), respectively. Unobscured, type 1 AGN are the dominant constituents (90%) of this soft X-ray selected sample of AGN.Comment: 17 pages, 8 figures, accepted for publication in ApJ, a version with high-resolution figures is available at http://www.eso.org/~cmullis/papers/Mullis_et_al_2004b.ps.gz, a machine-readable version of the ROSAT NEP AGN catalog is available at http://www.eso.org/~cmullis/research/nep-catalog.htm

Detachable force sensor for an ultrasound probe to improve rotator cuff injury diagnosis

Rotator cuff disease, common in elderly persons and athletes, is resultant of repetitive use of shoulder muscles or sudden impact to the area. The spectrum of injury ranges from tendonitis to a complete tear of the rotator cuff tendon which results in a myriad of treatments. Even though ultrasound is one of the most frequently used imaging techniques to diagnose this disease, it lacks contextual information and consistency needed for an accurate treatment plan. We are creating an ultrasound probe attachment using pressure sensing pads to measure force applied during imaging. Using our pads, we measured the change in resistance across the pad which can be used with pre-existing ultrasound imaging data to calculate the Young\u27s Modulus of the tissue. We hope this will provide more consistency in characterizing the rotator cuff. For the clinician, having this additional information may help to determine the extent of the injury and be beneficial in determining the appropriate treatment

A Complete Catalog of Swift GRB Spectra and Durations: Demise of a Physical Origin for Pre-Swift High-Energy Correlations

We calculate durations and spectral paramaters for 218 Swift bursts detected by the BAT instrument between and including GRBs 041220 and 070509, including 77 events with measured redshifts. Incorporating prior knowledge into the spectral fits, we are able to measure the characteristic $\nu F_{\nu}$ spectral peak energy $E_{\rm pk,obs}$ and the isotropic equivalent energy $E_{\rm iso}$ (1--$10^4$ keV) for all events. This complete and rather extensive catalog, analyzed with a unified methodology, allows us to address the persistence and origin of high-energy correlations suggested in pre-Swift observations. We find that the $E_{\rm pk,obs}$-$E_{\rm iso}$ correlation is present in the Swift sample; however, the best-fit powerlaw relation is inconsistent with the best-fit pre-Swift relation at >5 sigma significance. Moreover, it has a factor >~ 2 larger intrinsic scatter, after accounting for large errors on $E_{\rm pk,obs}$. A large fraction of the Swift events are hard and subluminous relative to (and inconsistent with) the pre-Swift relation, in agreement with indications from BATSE GRBs without redshift. Moreover, we determine an experimental threshold for the BAT detector and show how the $E_{\rm pk,obs}$--$E_{\rm iso}$ correlation arises artificially due to partial correlation with the threshold. We show that pre-Swift correlations found by Amati et al.(2002), Yonetoku et al. (2004), Firmani et al.(2006) (and independently by others) are likely unrelated to the physical properties of GRBs and are likely useless for tests of cosmology. Also, an explanation of these correlations in terms of a detector threshold provides a natural and quantitative explanation for why short-duration GRBs and events at low redshift tend to be outliers to the correlations.Comment: 25 pages, 9 figures, 2 tables, Accepted to Ap

A comprehensive analysis of methods for assessing polygenic burden on Alzheimer’s disease pathology and risk beyond APOE

Genome-wide association studies have identified dozens of loci that alter the risk to develop Alzheimer’s disease. However, with the exception of the APOE-ε4 allele, most variants bear only little individual effect and have, therefore, limited diagnostic and prognostic value. Polygenic risk scores aim to collate the disease risk distributed across the genome in a single score. Recent works have demonstrated that polygenic risk scores designed for Alzheimer’s disease are predictive of clinical diagnosis, pathology confirmed diagnosis and changes in imaging biomarkers. Methodological innovations in polygenic risk modelling include the polygenic hazard score, which derives effect estimates for individual single nucleotide polymorphisms from survival analysis, and methods that account for linkage disequilibrium between genomic loci. In this work, using data from the Alzheimer’s disease neuroimaging initiative, we compared different approaches to quantify polygenic disease burden for Alzheimer’s disease and their association (beyond the APOE locus) with a broad range of Alzheimer’s disease-related traits: cross-sectional CSF biomarker levels, cross-sectional cortical amyloid burden, clinical diagnosis, clinical progression, longitudinal loss of grey matter and longitudinal decline in cognitive function. We found that polygenic scores were associated beyond APOE with clinical diagnosis, CSF-tau levels and, to a minor degree, with progressive atrophy. However, for many other tested traits such as clinical disease progression, CSF amyloid, cognitive decline and cortical amyloid load, the additional effects of polygenic burden beyond APOE were of minor nature. Overall, polygenic risk scores and the polygenic hazard score performed equally and given the ease with which polygenic risk scores can be derived; they constitute the more practical choice in comparison with polygenic hazard scores. Furthermore, our results demonstrate that incomplete adjustment for the APOE locus, i.e. only adjusting for APOE-ε4 carrier status, can lead to overestimated effects of polygenic scores due to APOE-ε4 homozygous participants. Lastly, on many of the tested traits, the major driving factor remained the APOE locus, with the exception of quantitative CSF-tau and p-tau measures