Predicting Spatio-Temporal Time Series Using Dimension Reduced Local States

We present a method for both cross estimation and iterated time series prediction of spatio temporal dynamics based on reconstructed local states, PCA dimension reduction, and local modelling using nearest neighbour methods. The effectiveness of this approach is shown for (noisy) data from a (cubic) Barkley model, the Bueno-Orovio-Cherry-Fenton model, and the Kuramoto-Sivashinsky model

Predicting Spatio-Temporal Time Series Using Dimension Reduced Local States

We present a method for both cross estimation and iterated time series prediction of spatio temporal dynamics based on reconstructed local states, PCA dimension reduction, and local modelling using nearest neighbour methods. The effectiveness of this approach is shown for (noisy) data from a (cubic) Barkley model, the Bueno-Orovio-Cherry-Fenton model, and the Kuramoto-Sivashinsky model

Detection of nitrous oxide (N2O) at sub-ppmv using intracavity absorption spectroscopy

We demonstrate a fiber laser system for the detection of the greenhouse gas, nitrous oxide (N2O), at sub-ppmv concentration levels. The fiber laser is stabilized by a saturable absorber. The sensitivity is enhanced by multiple circulations of amplified spontaneous emission light under threshold conditions, and multi-longitudinal mode oscillation of the laser. An intra-cavity Herriott cell of an effective path length of 30 m was used to detect the P (12) rotational line of N2O at ∼1522.20 nm

Board Gender Diversity and Dividend Policy in SMEs: Moderating Role of Capital Structure in Emerging Market

Given the mix findings in literature regarding gender diversity and dividend policy, we suspected that capital structure is an intervening variable to moderate the relationship.  This paper therefore examines the joint role of board gender diversity and capital structure of a firm; does it improve or weaken dividend policy. The study analyzed 2015 year data from 1,011 unlisted firms from Ghana. Structured questionnaire and published annual reports were used to obtain the required data for the study. The results indicate that the relationship between the interaction term and dividend policy is insignificant, hence capital structure does not moderate the relationship between board gender diversity and dividend policy. Policy makers should not blindly adopt initiative of gender equality from another country; instead they should carefully examine the influence of capital structure and the causality of relation before appointing more or less of females on corporate boards

High System-Code Security with Low Overhead

Security vulnerabilities plague modern systems because writing secure systems code is hard. Promising approaches can retrofit security automatically via runtime checks that implement the desired security policy; these checks guard critical operations, like memory accesses. Alas, the induced slowdown usually exceeds by a wide margin what system users are willing to tolerate in production, so these tools are hardly ever used. As a result, the insecurity of real-world systems persists. We present an approach in which developers/operators can specify what level of overhead they find acceptable for a given workload (e.g., 5%); our proposed tool ASAP then automatically instruments the program to maximize its security while staying within the specified "overhead budget." Two insights make this approach effective: most overhead in existing tools is due to only a few "hot" checks, whereas the checks most useful to security are typically "cold" and cheap. We evaluate ASAP on programs from the Phoronix and SPEC benchmark suites. It can precisely select the best points in the security-performance spectrum. Moreover, we analyzed existing bugs and security vulnerabilities in RIPE, OpenSSL, and the Python interpreter, and found that the protection level offered by the ASAP approach is sufficient to protect against all of them

Lanthanide-assisted deposition of strongly electro-optic PZT thin films on silicon: toward integrated active nanophotonic devices

The electro-optical properties of lead zirconate titanate (PZT) thin films depend strongly on the quality and crystallographic orientation of the thin films. We demonstrate a novel method to grow highly textured PZT thin films on silicon using the chemical solution deposition (CSD) process. We report the use of ultrathin (5–15 nm) lanthanide (La, Pr, Nd, Sm) based intermediate layers for obtaining preferentially (100) oriented PZT thin films. X-ray diffraction measurements indicate preferentially oriented intermediate Ln2O2CO3 layers providing an excellent lattice match with the PZT thin films grown on top. The XRD and scanning electron microscopy measurements reveal that the annealed layers are dense, uniform, crack-free and highly oriented (>99.8%) without apparent defects or secondary phases. The EDX and HRTEM characterization confirm that the template layers act as an efficient diffusion barrier and form a sharp interface between the substrate and the PZT. The electrical measurements indicate a dielectric constant of ∼650, low dielectric loss of ∼0.02, coercive field of 70 kV/cm, remnant polarization of 25 μC/cm2, and large breakdown electric field of 1000 kV/cm. Finally, the effective electro-optic coefficients of the films are estimated with a spectroscopic ellipsometer measurement, considering the electric field induced variations in the phase reflectance ratio. The electro-optic measurements reveal excellent linear effective pockels coefficients of 110 to 240 pm/V, which makes the CSD deposited PZT thin film an ideal candidate for Si-based active integrated nanophotonic devices

Deep Cardiac MRI Reconstruction with ADMM

Cardiac magnetic resonance imaging is a valuable non-invasive tool for identifying cardiovascular diseases. For instance, Cine MRI is the benchmark modality for assessing the cardiac function and anatomy. On the other hand, multi-contrast (T1 and T2) mapping has the potential to assess pathologies and abnormalities in the myocardium and interstitium. However, voluntary breath-holding and often arrhythmia, in combination with MRI's slow imaging speed, can lead to motion artifacts, hindering real-time acquisition image quality. Although performing accelerated acquisitions can facilitate dynamic imaging, it induces aliasing, causing low reconstructed image quality in Cine MRI and inaccurate T1 and T2 mapping estimation. In this work, inspired by related work in accelerated MRI reconstruction, we present a deep learning (DL)-based method for accelerated cine and multi-contrast reconstruction in the context of dynamic cardiac imaging. We formulate the reconstruction problem as a least squares regularized optimization task, and employ vSHARP, a state-of-the-art DL-based inverse problem solver, which incorporates half-quadratic variable splitting and the alternating direction method of multipliers with neural networks. We treat the problem in two setups; a 2D reconstruction and a 2D dynamic reconstruction task, and employ 2D and 3D deep learning networks, respectively. Our method optimizes in both the image and k-space domains, allowing for high reconstruction fidelity. Although the target data is undersampled with a Cartesian equispaced scheme, we train our model using both Cartesian and simulated non-Cartesian undersampling schemes to enhance generalization of the model to unseen data. Furthermore, our model adopts a deep neural network to learn and refine the sensitivity maps of multi-coil k-space data. Lastly, our method is jointly trained on both, undersampled cine and multi-contrast data.Comment: 12 pages, 3 figures, 2 tables. CMRxRecon Challenge, MICCAI 202