Virtual Hyperspectral Images Using Symmetric Autoencoders

Spectral data acquired through remote sensing are invaluable for environmental and resource studies. However, these datasets are often marred by nuisance phenomena such as atmospheric interference and other complexities, which pose significant challenges for accurate analysis. We show that an autoencoder architecture, called symmetric autoencoder (SymAE), which leverages symmetry under reordering of the pixels, can learn to disentangle the influence of these nuisance from surface reflectance features on a pixel-by-pixel basis. The disentanglement provides an alternative to atmospheric correction, without relying on radiative transfer modelling, through a purely data-driven process. More importantly, SymAE can generate virtual hyperspectral images by manipulating the nuisance effects of each pixel. We demonstrate using AVIRIS instrument data that these virtual images are valuable for subsequent image analysis tasks. We also show SymAE's ability to extract intra-class invariant features, which is very useful in clustering and classification tasks, delivering state-of-the-art classification performance for a purely spectral method

Learning earthquake sources using symmetric autoencoders

We introduce Symmetric Autoencoder (SymAE), a neural-network architecture designed to automatically extract earthquake information from far-field seismic waves. SymAE represents the measured displacement field using a code that is partitioned into two interpretable components: source and path-scattering information. We achieve this source-path representation using the scale separation principle and stochastic regularization, which traditional autoencoding methods lack. According to the scale separation principle, the variations in far-field band-limited seismic measurements resulting from finite faulting occur across two spatial scales: a slower scale associated with the source processes and a faster scale corresponding to path effects. Once trained, SymAE facilitates the generation of virtual seismograms, engineered to not contain subsurface scattering effects. We present time-reversal imaging of virtual seismograms to accurately infer the kinematic rupture parameters without knowledge of empirical Green's function. SymAE is an unsupervised learning method that can efficiently scale with large amounts of seismic data and does not require labeled seismograms, making it the first framework that can learn from all available previous earthquakes to accurately characterize a given earthquake. The paper presents the results of an analysis of nearly thirty complex earthquake events, revealing differences between earthquakes in energy rise times, stopping phases, and providing insights into their rupture complexity

Enhancing core-diffracted arrivals by supervirtual interferometry

A supervirtual interferometry (SVI) method is presented that can enhance the signal-to-noise ratio (SNR) of core diffracted waveforms by as much as $O(\sqrt{N})$, where N is the number of inline receivers that record the core-mantle boundary (CMB) diffractions from more than one event. Here, the events are chosen to be approximately inline with the receivers along the same great circle. Results with synthetic and teleseismic data recorded by USArray stations demonstrate that formerly unusable records with low SNR can be transformed to high SNR records with clearly visible CMB diffractions. Another benefit is that SVI allows for the recording of a virtual earthquake at stations not deployed during the time of the earthquake. This means that portable arrays such as USArray can extend the aperture of one recorded earthquake from the West coast to the East coast, even though the teleseism might have only been recorded during the West coast deployment. In summary, SVI applied to teleseismic data can significantly enlarge the catalogue of usable records both in SNR and available aperture for analysing CMB diffractions. A potential drawback of this method is that it generally provides the correct kinematics of CMB diffractions, but does not necessarily preserve correct amplitude informatio

Characterization of protective epitopes in a highly conserved Plasmodium falciparum antigenic protein containing repeats of acidic and basic residues

The delineation of putatively protective and immunogenic epitopes in vaccine candidate proteins constitutes a major research effort towards the development of an effective malaria vaccine. By virtue of its role in the formation of the immune clusters of merozoites, its location on the surface of merozoites, and its highly conserved nature both at the nucleotide sequence level and the amino acid sequence level, the antigen which contains repeats of acidic and basic residues (ABRA) of the human malaria parasite Plasmodium falciparum represents such an antigen. Based upon the predicted amino acid sequence of ABRA, we synthesized eight peptides, with six of these (AB-1 to AB-6) ranging from 12 to 18 residues covering the most hydrophilic regions of the protein, and two more peptides (AB-7 and AB-8) representing its repetitive sequences. We found that all eight constructs bound an appreciable amount of antibody in sera from a large proportion of P. falciparum malaria patients; two of these peptides (AB-1 and AB-3) also elicited a strong proliferation response in peripheral blood mononuclear cells from all 11 human subjects recovering from malaria. When used as carrier-free immunogens, six peptides induced a strong, boostable, immunoglobulin G-type antibody response in rabbits, indicating the presence of both B-cell determinants and T-helper-cell epitopes in these six constructs. These antibodies specifically cross-reacted with the parasite protein(s) in an immunoblot and in an immunofluorescence assay. In another immunoblot, rabbit antipeptide sera also recognized recombinant fragments of ABRA expressed in bacteria. More significantly, rabbit antibodies against two constructs (AB-1 and AB-5) inhibited the merozoite reinvasion of human erythrocytes in vitro up to ~90%. These results favor further studies so as to determine possible inclusion of these two constructs in a multicomponent subunit vaccine against asexual blood stages of P. falciparum

Characterization of protective epitopes in a highly conserved Plasmodium falciparum antigenic protein containing repeats of acidic and basic residues

The delineation of putatively protective and immunogenic epitopes in vaccine candidate proteins constitutes a major research effort towards the development of an effective malaria vaccine. By virtue of its role in the formation of the immune clusters of merozoites, its location on the surface of merozoites, and its highly conserved nature both at the nucleotide sequence level and the amino acid sequence level, the antigen which contains repeats of acidic and basic residues (ABRA) of the human malaria parasite Plasmodium falciparum represents such an antigen. Based upon the predicted amino acid sequence of ABRA, we synthesized eight peptides, with six of these (AB-1 to AB-6) ranging from 12 to 18 residues covering the most hydrophilic regions of the protein, and two more peptides (AB-7 and AB-8) representing its repetitive sequences. We found that all eight constructs bound an appreciable amount of antibody in sera from a large proportion of P. falciparum malaria patients; two of these peptides (AB-1 and AB-3) also elicited a strong proliferation response in peripheral blood mononuclear cells from all 11 human subjects recovering from malaria. When used as carrier-free immunogens, six peptides induced a strong, boostable, immunoglobulin G-type antibody response in rabbits, indicating the presence of both B-cell determinants and T-helper-cell epitopes in these six constructs. These antibodies specifically cross-reacted with the parasite protein(s) in an immunoblot and in an immunofluorescence assay. In another immunoblot, rabbit antipeptide sera also recognized recombinant fragments of ABRA expressed in bacteria. More significantly, rabbit antibodies against two constructs (AB-1 and AB-5) inhibited the merozoite reinvasion of human erythrocytes in vitro up to ∼90%. These results favor further studies so as to determine possible inclusion of these two constructs in a multicomponent subunit vaccine against asexual blood stages of P. falciparum

Case Reports1. A Late Presentation of Loeys-Dietz Syndrome: Beware of TGFβ Receptor Mutations in Benign Joint Hypermobility

Background: Thoracic aortic aneurysms (TAA) and dissections are not uncommon causes of sudden death in young adults. Loeys-Dietz syndrome (LDS) is a rare, recently described, autosomal dominant, connective tissue disease characterized by aggressive arterial aneurysms, resulting from mutations in the transforming growth factor beta (TGFβ) receptor genes TGFBR1 and TGFBR2. Mean age at death is 26.1 years, most often due to aortic dissection. We report an unusually late presentation of LDS, diagnosed following elective surgery in a female with a long history of joint hypermobility. Methods: A 51-year-old Caucasian lady complained of chest pain and headache following a dural leak from spinal anaesthesia for an elective ankle arthroscopy. CT scan and echocardiography demonstrated a dilated aortic root and significant aortic regurgitation. MRA demonstrated aortic tortuosity, an infrarenal aortic aneurysm and aneurysms in the left renal and right internal mammary arteries. She underwent aortic root repair and aortic valve replacement. She had a background of long-standing joint pains secondary to hypermobility, easy bruising, unusual fracture susceptibility and mild bronchiectasis. She had one healthy child age 32, after which she suffered a uterine prolapse. Examination revealed mild Marfanoid features. Uvula, skin and ophthalmological examination was normal. Results: Fibrillin-1 testing for Marfan syndrome (MFS) was negative. Detection of a c.1270G > C (p.Gly424Arg) TGFBR2 mutation confirmed the diagnosis of LDS. Losartan was started for vascular protection. Conclusions: LDS is a severe inherited vasculopathy that usually presents in childhood. It is characterized by aortic root dilatation and ascending aneurysms. There is a higher risk of aortic dissection compared with MFS. Clinical features overlap with MFS and Ehlers Danlos syndrome Type IV, but differentiating dysmorphogenic features include ocular hypertelorism, bifid uvula and cleft palate. Echocardiography and MRA or CT scanning from head to pelvis is recommended to establish the extent of vascular involvement. Management involves early surgical intervention, including early valve-sparing aortic root replacement, genetic counselling and close monitoring in pregnancy. Despite being caused by loss of function mutations in either TGFβ receptor, paradoxical activation of TGFβ signalling is seen, suggesting that TGFβ antagonism may confer disease modifying effects similar to those observed in MFS. TGFβ antagonism can be achieved with angiotensin antagonists, such as Losartan, which is able to delay aortic aneurysm development in preclinical models and in patients with MFS. Our case emphasizes the importance of timely recognition of vasculopathy syndromes in patients with hypermobility and the need for early surgical intervention. It also highlights their heterogeneity and the potential for late presentation. Disclosures: The authors have declared no conflicts of interes

Deblending random seismic sources via independent component analysis

We consider the question of deblending for seismic shot records generated from simultaneous random sources at different locations, i.e., how to decompose them into isolated records involving one source at a time. As an example, seismic-while-drilling experiments use active drill-string sources and receivers to look around and ahead of the borehole, but these receivers also record noise from the operation of the drill bit. A conventional method for deblending is independent component analysis (ICA), which assumes a “cocktail-party” mixing model where each receiver records a linear combination of source signals assumed to be statistically independent, and where only one source can have a Gaussian distribution. In this note, we extend the applicability of ICA to seismic shot records with markedly more complex mixing models with unknown wave kinematics, provided the following assumptions are met. 1. The active source is fully controllable, which means that it can be used to input a wide range of non-Gaussian random signals into the subsurface. 2. The waves are a linear function of the source, have a finite speed of propagation, and follow finite-length paths. The last assumption implies a scale separation, in frequency, between the mixing matrix elements (Green’s functions) and the random input signals. In this regime, we show that the key to the success of ICA is careful windowing to frequency bands over which the Green’s functions are approximately constant.Statoil ASAUnited States. Air Force. Office of Scientific Research (Grant FA9550- 12-1-0328)United States. Air Force. Office of Scientific Research (Grant FA9550-15-1-0078)National Science Foundation (U.S.) (Grant DMS-1255203)United States. Office of Naval Research (Grant N00014-16-1- 2122