A time-series prediction approach for feature extraction in a brain-computer interface.

This paper presents a feature extraction procedure (FEP) for a brain-computer interface (BCI) application where features are extracted from the electroencephalogram (EEG) recorded from subjects performing right and left motor imagery. Two neural networks (NNs) are trained to perform one-step-ahead predictions for the EEG time-series data, where one NN is trained on right motor imagery and the other on left motor imagery. Features are derived from the power (mean squared) of the prediction error or the power of the predicted signals. All features are calculated from a window through which all predicted signals pass. Separability of features is achieved due to the morphological differences of the EEG signals and each NNs specialization to the type of data on which it is trained. Linear discriminant analysis (LDA) is used for classification. This FEP is tested on three subjects off-line and classification accuracy (CA) rates range between 88% and 98%. The approach compares favorably to a well-known adaptive autoregressive (AAR) FEP and also a linear AAR model based prediction approach.     

Adding Federated Identity Management to OpenStack

OpenStack is an open source cloud computing project that is enjoying wide. While many cloud deployments may be stand-alone, it is clear that secure federated community clouds, i.e., inter-clouds, are needed. Hence, there must be methods for federated identity management (FIM) that enable authentication and authorisation to be flexibly enforced across federated environments. Since there are many different FIM protocols either in use or in development today, this paper addresses the goal of adding protocol independent federated identity management to the OpenStack services. After giving a motivating example for secure cloud federation, and describing the conceptual design for protocol independent federated access, a detailed federated identity protocol sequence is presented. The paper then describes the implementation of the protocol independent system components, along with the incorporation of two different FIM protocols, namely SAML and Keystone proprietary. Finally performance measurements of the protocol independent components, and the two different protocols dependent components are presented, before the paper concludes with the current limitations.     

Confinement Effects on the Structure of Entropy-Induced Supercrystals

Depletion-induced self-assembly is routinely used to separate plasmonic nanoparticles (NPs) of different shapes, but less often for its ability to create supercrystals (SCs) in suspension. Therefore, these plasmonic assemblies have not yet reached a high level of maturity and their in-depth characterization by a combination of in situ techniques is still very much needed. In this work, gold triangles (AuNTs) and silver nanorods (AgNRs) are assembled by depletion-induced self-assembly. Small Angle X-ray Scattering (SAXS) and scanning electron microscopy (SEM) analysis shows that the AuNTs and AgNRs form 3D and 2D hexagonal lattices in bulk, respectively. The colloidal crystals are also imaged by in situ Liquid-Cell Transmission Electron Microscopy. Under confinement, the affinity of the NPs for the liquid cell windows reduces their ability to stack perpendicularly to the membrane and lead to SCs with a lower dimensionality than their bulk counterparts. Moreover, extended beam irradiation leads to disassembly of the lattices, which is well described by a model accounting for the desorption kinetics highlighting the key role of the NP-membrane interaction in the structural properties of SCs in the liquid-cell. The results shed light on the reconfigurability of NP superlattices obtained by depletion-induced self-assembly, which can rearrange under confinement.     

Robust Pointset Denoising of Piecewise-Smooth Surfaces through Line Processes

Denoising is a common, yet critical operation in geometry processing aiming at recovering high-fidelity models of piecewise-smooth objects from noise-corrupted pointsets. Despite a sizable literature on the topic, there is a dearth of approaches capable of processing very noisy and outlier-ridden input pointsets for which no normal estimates and no assumptions on the underlying geometric features or noise type are provided. In this paper, we propose a new robust-statistics approach to denoising pointsets based on line processes to offer robustness to noise and outliers while preserving sharp features possibly present in the data. While the use of robust statistics in denoising is hardly new, most approaches rely on prescribed filtering using data-independent blending expressions based on the spatial and normal closeness of samples. Instead, our approach deduces a geometric denoising strategy through robust and regularized tangent plane fitting of the initial pointset, obtained numerically via alternating minimizations for efficiency and reliability. Key to our variational approach is the use of line processes to identify inliers vs. outliers, as well as the presence of sharp features. We demonstrate that our method can denoise sampled piecewise-smooth surfaces for levels of noise and outliers at which previous works fall short.     

Solubility and diffusivity of hydrogen and its isotopes in the BeO system

This work revisits hydrogen insertion in the wurtzite beryllium oxide in order to fill the gap in scientific knowledge regarding the diffusion coefficients of the different chemical states of hydrogen (neutral, charged, or molecular). Both first-principle and macroscopic models were used to this end. In the former, two exchange-correlation functionals (PBE and SCAN) were used to compute the properties of interest and accuracy was then discussed. Regarding the behavior of interstitial insertion of hydrogen, this work is slightly different from previous works; hydrogen was mainly found in the form of charged H⁻ or H⁺ ions, depending on experimental conditions. In regard to diffusivity properties, a complex migration pathway was found for hydrogen cation. Finally, the present study succeeded in producing a reliable set of diffusion coefficients for neutral, charged, and molecular hydrogen.     

Selective Display of a Chemoattractant Agonist on Cancer Cells Activates the Formyl Peptide Receptor 1 on Immune Cells**

Current immunotherapeutics often work by directing components of the immune system to recognize biomarkers on the surface of cancer cells to generate an immune response. However, variable changes in biomarker distribution and expression can result in inconsistent patient response. The development of a more universal tumor-homing strategy has the potential to improve selectivity and extend therapy to cancers with decreased expression or absence of specific biomarkers. Here, we designed a bifunctional agent that exploits the inherent acidic microenvironment of most solid tumors to selectively graft the surface of cancer cells with a formyl peptide receptor ligand (FPRL). Our approach is based on the pH(Low) insertion peptide (pHLIP), a unique peptide that selectively targets tumors in vivo by anchoring to cancer cells in a pH-dependent manner. We establish that selectively remodeling cancer cells with a pHLIP-based FPRL activates formyl peptide receptors on recruited immune cells, potentially initiating an immune response towards tumors.     

Spin-Orbit Readout Using Thin Films of Topological Insulator Sb2Te3 Deposited by Industrial Magnetron Sputtering

Driving a spin-logic circuit requires the production of a large output signal by spin-charge interconversion in spin-orbit readout devices. This should be possible by using topological insulators, which are known for their high spin-charge interconversion efficiency. However, high-quality topological insulators have so far only been obtained on a small scale, or with large scale deposition techniques that are not compatible with conventional industrial deposition processes. The nanopatterning and electrical spin injection into these materials have also proven difficult due to their fragile structure and low spin conductance. The fabrication of a spin-orbit readout device from the topological insulator Sb₂Te₃ deposited by large-scale industrial magnetron sputtering on SiO₂ is presented. Despite a modification of the Sb₂Te₃ layer structural properties during the device nanofabrication, a sizeable output voltage is measured that can be unambiguously ascribed to a spin-charge interconversion process. The results pave the way for the integration of layered van der Waals materials in spin-logic devices.     

Data-driven coordination of subproblems in enterprise-wide optimization under organizational considerations

While decomposition techniques in mathematical programming are usually designed for numerical efficiency, coordination problems within enterprise-wide optimization are often limited by organizational rather than numerical considerations. We propose a “data-driven” coordination framework which manages to recover the same optimum as the equivalent centralized formulation while allowing coordinating agents to retain autonomy, privacy, and flexibility over their own objectives, constraints, and variables. This approach updates the coordinated, or shared, variables based on derivative-free optimization (DFO) using only coordinated variables to agent-level optimal subproblem evaluation “data.” We compare the performance of our framework using different DFO solvers (CUATRO, Py-BOBYQA, DIRECT-L, GPyOpt) against conventional distributed optimization (ADMM) on three case studies: collaborative learning, facility location, and multiobjective blending. We show that in low-dimensional and nonconvex subproblems, the exploration-exploitation trade-offs of DFO solvers can be leveraged to converge faster and to a better solution than in distributed optimization.     

Formation and Etching of the Insulating Sr-Rich V5+ Phase at the Metallic SrVO3 Surface Revealed by Operando XAS Spectroscopy Characterizations

In the search of low cost and more efficient electronic devices, here the properties of SrVO₃ transparent conductor oxide (TCO) thin film are investigated, both visible-range optically transparent and highly conductive, it stands as a promising candidate to substitute the standard indium-tin-oxide (ITO) in applications. Its surface stability under water (both liquid and vapor) and other gaseous atmospheres is especially addressed. Through the use of spectroscopy characterizations, X-ray photoemission and operando X-ray absorption measurements, the formation of a thin Sr-rich V⁵⁺ layer located at the surface of the polycrystalline SrVO₃ film with aging is observed, and for the first time how it can be removed from the surface by solvating in water atmosphere. The surface recovery is associated to an etching process, here spectroscopically characterized in operando conditions, allowing to follow the stoichiometric modification under reaction. Once exposed in oxygen atmosphere, the Sr-rich V⁵⁺ layer forms again. The findings improve the understanding of aging effects in perovskite oxides, allowing for the development of functionalized films in which it is possible to control or to avoid an insulating surface layer. This constitutes an important step towards the large-scale use of V-based TCOs, with possible implementations in oxide-based electronics.