Real-time assessment of potential seismic migration within a monitoring network using Red-flag SARA

Magma opening new fluid pathways through the crust can generate migrating seismic sources following the trail of the magma. By using Seismic Amplitude Ratio Analysis (SARA), it is possible to detect this seismic migration simply from the amplitudes of continuous data recorded at different stations in a network, without having to do any picking of seismic phases. In this study, we present a modified method – Red-flag SARA, which adapts SARA for real-time monitoring. Red-flag SARA provides a quantitative tool to analyse amplitude ratios between stations in a network and detect temporal changes in these ratios. Since such changes imply seismic source location variations, Red-flag SARA is a handy tool during seismic crises to quickly answer the question of whether seismic activity, and therefore magma, is migrating or not. We tested Red-flag SARA on synthetic data and validated it using real data from two volcanoes – Piton de la Fournaise, Reunion Island, and Gede, Indonesia, for three scenarios: 1) magma migration ending as intrusion, 2) migration leading to eruption and 3) a burst of seismicity with no magma migration

Reconstituted high-density lipoproteins promote wound repair and blood flow recovery in response to ischemia in aged mice

Background: The average population age is increasing and the incidence of age-related vascular complications is rising in parallel. Impaired wound healing and disordered ischemia-mediated angiogenesis are key contributors to age-impaired vascular complications that can lead to amputation. High-density lipoproteins (HDL) have vasculo-protective properties and augment ischemia-driven angiogenesis in young animals. We aimed to determine the effect of reconstituted HDL (rHDL) on aged mice in a murine wound healing model and the hindlimb ischemia (HLI) model. Methods: Murine wound healing model—24-month-old aged mice received topical application of rHDL (50 μg/wound/ day) or PBS (vehicle control) for 10 days following wounding. Murine HLI model—Femoral artery ligation was performed on 24-month-old mice. Mice received rHDL (40 mg/kg) or PBS, intravenously, on alternate days, 1 week pre-surgery and up to 21 days post ligation. For both models, blood flow perfusion was determined using laser Doppler perfusion imaging. Mice were sacrificed at 10 (wound healing) or 21 (HLI) days post-surgery and tissues were collected for histological and gene analyses. Results: Daily topical application of rHDL increased the rate of wound closure by Day 7 post-wounding (25 %, p < 0.05). Wound blood perfusion, a marker of angiogenesis, was elevated in rHDL treated wounds (Days 4–10 by 22–25 %, p < 0. 05). In addition, rHDL increased wound capillary density by 52.6 %. In the HLI model, rHDL infusions augmented blood flow recovery in ischemic limbs (Day 18 by 50 % and Day 21 by 88 %, p < 0.05) and prevented tissue necrosis and toe loss. Assessment of capillary density in ischemic hindlimb sections found a 90 % increase in rHDL infused animals. In vitro studies in fibroblasts isolated from aged mice found that incubation with rHDL was able to significantly increase the key pro-angiogenic mediator vascular endothelial growth factor (VEGF) protein (25 %, p < 0.05). Conclusion: rHDL can promote wound healing and wound angiogenesis, and blood flow recovery in response to ischemia in aged mice. Mechanistically, this is likely to be via an increase in VEGF. This highlights a potential role for HDL in the therapeutic modulation of age-impaired vascular complications

Graph-Regularized Manifold-Aware Conditional Wasserstein GAN for Brain Functional Connectivity Generation

Common measures of brain functional connectivity (FC) including covariance and correlation matrices are semi-positive definite (SPD) matrices residing on a cone-shape Riemannian manifold. Despite its remarkable success for Euclidean-valued data generation, use of standard generative adversarial networks (GANs) to generate manifold-valued FC data neglects its inherent SPD structure and hence the inter-relatedness of edges in real FC. We propose a novel graph-regularized manifold-aware conditional Wasserstein GAN (GR-SPD-GAN) for FC data generation on the SPD manifold that can preserve the global FC structure. Specifically, we optimize a generalized Wasserstein distance between the real and generated SPD data under an adversarial training, conditioned on the class labels. The resulting generator can synthesize new SPD-valued FC matrices associated with different classes of brain networks, e.g., brain disorder or healthy control. Furthermore, we introduce additional population graph-based regularization terms on both the SPD manifold and its tangent space to encourage the generator to respect the inter-subject similarity of FC patterns in the real data. This also helps in avoiding mode collapse and produces more stable GAN training. Evaluated on resting-state functional magnetic resonance imaging (fMRI) data of major depressive disorder (MDD), qualitative and quantitative results show that the proposed GR-SPD-GAN clearly outperforms several state-of-the-art GANs in generating more realistic fMRI-based FC samples. When applied to FC data augmentation for MDD identification, classification models trained on augmented data generated by our approach achieved the largest margin of improvement in classification accuracy among the competing GANs over baselines without data augmentation.Comment: 10 pages, 4 figure

Single-trial event-related potential extraction through one-unit ICA-with-reference.

Objective: In recent years, ICA has been one of the more popular methods for extracting event-related potential (ERP) at the single-trial level. It is a blind source separation technique that allows the extraction of an ERP without making strong assumptions on the temporal and spatial characteristics of an ERP. However, the problem with traditional ICA is that the extraction is not direct and is time-consuming due to the need for source selection processing. In this paper, the application of an one-unit ICA-with-Reference (ICA-R), a constrained ICA method, is proposed. Approach: In cases where the time-region of the desired ERP is known a priori, this time information is utilized to generate a reference signal, which is then used for guiding the one-unit ICA-R to extract the source signal of the desired ERP directly. Main results: Our results showed that, as compared to traditional ICA, ICA-R is a more effective method for analysing ERP because it avoids manual source selection and it requires less computation thus resulting in faster ERP extraction. Significance: In addition to that, since the method is automated, it reduces the risks of any subjective bias in the ERP analysis. It is also a potential tool for extracting the ERP in online application

A survey of cost-sensitive decision tree induction algorithms

The past decade has seen a significant interest on the problem of inducing decision trees that take account of costs of misclassification and costs of acquiring the features used for decision making. This survey identifies over 50 algorithms including approaches that are direct adaptations of accuracy based methods, use genetic algorithms, use anytime methods and utilize boosting and bagging. The survey brings together these different studies and novel approaches to cost-sensitive decision tree learning, provides a useful taxonomy, a historical timeline of how the field has developed and should provide a useful reference point for future research in this field

Stokes' first problem for some non-Newtonian fluids: Results and mistakes

The well-known problem of unidirectional plane flow of a fluid in a half-space due to the impulsive motion of the plate it rests upon is discussed in the context of the second-grade and the Oldroyd-B non-Newtonian fluids. The governing equations are derived from the conservation laws of mass and momentum and three correct known representations of their exact solutions given. Common mistakes made in the literature are identified. Simple numerical schemes that corroborate the analytical solutions are constructed.Comment: 10 pages, 2 figures; accepted for publication in Mechanics Research Communications; v2 corrects a few typo

Inducing safer oblique trees without costs

Decision tree induction has been widely studied and applied. In safety applications, such as determining whether a chemical process is safe or whether a person has a medical condition, the cost of misclassification in one of the classes is significantly higher than in the other class. Several authors have tackled this problem by developing cost-sensitive decision tree learning algorithms or have suggested ways of changing the distribution of training examples to bias the decision tree learning process so as to take account of costs. A prerequisite for applying such algorithms is the availability of costs of misclassification. Although this may be possible for some applications, obtaining reasonable estimates of costs of misclassification is not easy in the area of safety. This paper presents a new algorithm for applications where the cost of misclassifications cannot be quantified, although the cost of misclassification in one class is known to be significantly higher than in another class. The algorithm utilizes linear discriminant analysis to identify oblique relationships between continuous attributes and then carries out an appropriate modification to ensure that the resulting tree errs on the side of safety. The algorithm is evaluated with respect to one of the best known cost-sensitive algorithms (ICET), a well-known oblique decision tree algorithm (OC1) and an algorithm that utilizes robust linear programming

Towards Efficient Detection of Small Near-Earth Asteroids Using the Zwicky Transient Facility (ZTF)

We describe ZStreak, a semi-real-time pipeline specialized in detecting small, fast-moving near-Earth asteroids (NEAs) that is currently operating on the data from the newly-commissioned Zwicky Transient Facility (ZTF) survey. Based on a prototype originally developed by Waszczak et al. (2017) for the Palomar Transient Factory (PTF), the predecessor of ZTF, ZStreak features an improved machine-learning model that can cope with the $10\times$ data rate increment between PTF and ZTF. Since its first discovery on 2018 February 5 (2018 CL), ZTF/ZStreak has discovered $45$ confirmed new NEAs over a total of 232 observable nights until 2018 December 31. Most of the discoveries are small NEAs, with diameters less than $\sim100$ m. By analyzing the discovery circumstances, we find that objects having the first to last detection time interval under 2 hr are at risk of being lost. We will further improve real-time follow-up capabilities, and work on suppressing false positives using deep learning.Comment: PASP in pres

Hysteresis of Electronic Transport in Graphene Transistors

Graphene field effect transistors commonly comprise graphene flakes lying on SiO2 surfaces. The gate-voltage dependent conductance shows hysteresis depending on the gate sweeping rate/range. It is shown here that the transistors exhibit two different kinds of hysteresis in their electrical characteristics. Charge transfer causes a positive shift in the gate voltage of the minimum conductance, while capacitive gating can cause the negative shift of conductance with respect to gate voltage. The positive hysteretic phenomena decay with an increase of the number of layers in graphene flakes. Self-heating in helium atmosphere significantly removes adsorbates and reduces positive hysteresis. We also observed negative hysteresis in graphene devices at low temperature. It is also found that an ice layer on/under graphene has much stronger dipole moment than a water layer does. Mobile ions in the electrolyte gate and a polarity switch in the ferroelectric gate could also cause negative hysteresis in graphene transistors. These findings improved our understanding of the electrical response of graphene to its surroundings. The unique sensitivity to environment and related phenomena in graphene deserve further studies on nonvolatile memory, electrostatic detection and chemically driven applications.Comment: 13 pages, 6 Figure