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https://www.readbyqxmd.com/read/28651043/visualizing-the-contributions-of-virtual-states-to-two-photon-absorption-cross-sections-by-natural-transition-orbitals-of-response-transition-density-matrices
#1
Kaushik D Nanda, Anna I Krylov
Observables such as two-photon absorption cross-sections cannot be computed from the wave functions of the initial and final states alone because of their nonlinear nature. Rather, they depend on the entire manifold of the excited states, which follows from the familiar sum-over-states expressions of second- and higher-order properties. Consequently, the interpretation of the computed nonlinear optical properties in terms of molecular orbitals is not straightforward and usually relies on approximate few-states models...
June 26, 2017: Journal of Physical Chemistry Letters
https://www.readbyqxmd.com/read/28650814/multi-label-classification-by-semi-supervised-singular-value-decomposition
#2
Liping Jing, Chenyang Shen, Liu Yang, Jian Yu, Michael K Ng
Multi-label problems arise in various domains including automatic multimedia data categorization, and have generated significant interest in computer vision and machine learning community. However, existing methods do not adequately address two key challenges: exploiting correlations between labels and making up for the lack of labeled data or even missing labeled data. In this paper, we proposed to use a semi-supervised singular value decomposition to handle these two challenges. The proposed model takes advantage of the nuclear norm regularization on the singular value decomposition to effectively capture the label correlations...
June 26, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28650442/magnetic-brightening-and-control-of-dark-excitons-in-monolayer-wse2
#3
Xiao-Xiao Zhang, Ting Cao, Zhengguang Lu, Yu-Chuan Lin, Fan Zhang, Ying Wang, Zhiqiang Li, James C Hone, Joshua A Robinson, Dmitry Smirnov, Steven G Louie, Tony F Heinz
Monolayer transition metal dichalcogenide crystals, as direct-gap materials with strong light-matter interactions, have attracted much recent attention. Because of their spin-polarized valence bands and a predicted spin splitting at the conduction band edges, the lowest-lying excitons in WX2 (X = S, Se) are expected to be spin-forbidden and optically dark. To date, however, there has been no direct experimental probe of these dark excitons. Here, we show how an in-plane magnetic field can brighten the dark excitons in monolayer WSe2 and permit their properties to be observed experimentally...
June 26, 2017: Nature Nanotechnology
https://www.readbyqxmd.com/read/28644871/predicting-the-bounds-of-large-chaotic-systems-using-low-dimensional-manifolds
#4
Asger M Haugaard
Predicting extrema of chaotic systems in high-dimensional phase space remains a challenge. Methods, which give extrema that are valid in the long term, have thus far been restricted to models of only a few variables. Here, a method is presented which treats extrema of chaotic systems as belonging to discretised manifolds of low dimension (low-D) embedded in high-dimensional (high-D) phase space. As a central feature, the method exploits that strange attractor dimension is generally much smaller than parent system phase space dimension...
2017: PloS One
https://www.readbyqxmd.com/read/28644806/discriminative-deep-metric-learning-for-face-and-kinship-verification
#5
Jiwen Lu, Junlin Hu, Yap-Peng Tan
This paper presents a new discriminative deep metric learning (DDML) method for face and kinship verification in wild conditions. While metric learning has achieved reasonably good performance in face and kinship verification, most existing metric learning methods aim to learn a single Mahalanobis distance metric to maximize the inter-class variations and minimize the intra-class variations, which cannot capture the nonlinear manifold where face images usually lie on. To address this, we propose a DDML method to train a deep neural network to learn a set of hierarchical nonlinear transformations to project face pairs into the same latent feature space, under which the distance of each positive pair is reduced and that of each negative pair is enlarged, respectively...
June 20, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28643880/effects-of-discrete-bioactive-microbial-volatiles-on-plants-and-fungi
#6
REVIEW
Birgit Piechulla, Marie-Chantal Lemfack, Marco Kai
Plants live in association with microorganisms, which are well known as a rich source of specialized metabolits, including volatile compounds. The increasing numbers of described plant microbiomes allowed manifold phylogenetic tree deductions, but less emphasis is presently put on the metabolic capacities of plant-associated microorganisms. With the focus on small volatile metabolites we summarize i) the knowledge of prominent bacteria of plant microbiomes, ii) present the state-of-the-art of individual (discrete) microbial organic and inorganic volatiles affecting plants and fungi, and iii) emphasize the high potential of microbial volatiles in mediating microbe-plant interactions...
June 23, 2017: Plant, Cell & Environment
https://www.readbyqxmd.com/read/28641259/face-hallucination-using-linear-models-of-coupled-sparse-support
#7
Reuben A Farrugia, Christine Guillemot
Most face super-resolution methods assume that low- and high-resolution manifolds have similar local geometrical structure, hence learn local models on the low-resolution manifold (e.g. sparse or locally linear embedding models), which are then applied on the high- resolution manifold. However, the low-resolution manifold is distorted by the one-to-many relationship between low- and high- resolution patches. This paper presents the Linear Model of Coupled Sparse Support (LM-CSS) method which learns linear models based on the local geometrical structure on the high-resolution manifold rather than on the low-resolution manifold...
June 19, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28641245/data-visualization-with-structural-control-of-global-cohort-and-local-data-neighborhoods
#8
Tingting Mu, Yannis John Goulermas, Sophia Ananiadou
A typical objective of data visualization is to generate low-dimensional plots that maximally convey the information within the data. The visualization output should help the user to not only identify the local neighborhood structure of individual samples, but also obtain a global view of the relative positioning and separation between cohorts. Here, we propose a very novel visualization framework designed to satisfy these needs. By incorporating additional cohort positioning and discriminative constraints into local neighbor preservation models through the use of computed cohort prototypes, effective control over the arrangements and proximities of data cohorts can be obtained...
June 15, 2017: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/28641242/arrhythmia-mechanism-and-scaling-effect-on-the-spectral-properties-of-electroanatomical-maps-with-manifold-harmonics
#9
Margarita Sanroman-Junquera, Inmaculada Mora-Jimenez, Arcadi Garcia-Alberola, Antonio J Caamano, Beatriz Trenor, Jose Luis Rojo-Alvarez
Spatial and temporal processing of intracardiac electrograms provides relevant information to support the arrhythmia ablation during electrophysiological studies. Current Cardiac Navigation Systems (CNS) and Electrocardiographic Imaging (ECGI) build detailed three-dimensional electroanatomical maps (EAM), which represent the spatial anatomical distribution of bioelectrical features, such as activation time or voltage. We present a principled methodology for spectral analysis of both EAM geometry and bioelectrical feature in CNS or ECGI, including their spectral representation, cut-off frequency, or spatial sampling rate (SSR)...
June 15, 2017: IEEE Transactions on Bio-medical Engineering
https://www.readbyqxmd.com/read/28640756/single-lead-f-wave-extraction-using-diffusion-geometry
#10
John Malik, Neil Reed, Chun-Li Wang, Hau-Tieng Wu
OBJECTIVE: A novel single-lead f-wave extraction algorithm based on the modern diffusion geometry data analysis framework is proposed. APPROACH: The algorithm is essentially an averaged beat subtraction algorithm, where the ventricular activity template is estimated by combining a newly designed metric, the 'diffusion distance', and the non-local Euclidean median based on the non-linear manifold setup. We coined the algorithm [Formula: see text]. MAIN RESULTS: Two simulation schemes are considered, and the new algorithm [Formula: see text] outperforms traditional algorithms, including the average beat subtraction, principal component analysis, and adaptive singular value cancellation, in different evaluation metrics with statistical significance...
June 22, 2017: Physiological Measurement
https://www.readbyqxmd.com/read/28640601/initiation-of-the-electrochemical-reduction-of-co2-by-a-singly-reduced-ruthenium-ii-bipyridine-complex
#11
Srinivasan Ramakrishnan, Christopher E D Chidsey
The one-electron reduction of [CpRu(bpy)NCCH3]PF6 (Cp = cyclopentadienyl; bpy = 2,2'-bipyridine), abbreviated as [Ru-S](+), where S = CH3CN, in CO2-saturated acetonitrile initiates a cascade of rapid electrochemical and chemical steps (ECEC) at an electrode potential of ca. 100 mV positive of the first reduction of the ruthenium complex. The overall two-electron process leads to the generation of a CO-bound ruthenium complex, [Ru-CO](+), and carbonate, as independently confirmed by NMR spectroscopy. Simulations of the cyclic voltammograms using DigiElch together with density functional theory based calculations reveal that the singly reduced ruthenium complex [Ru-S](0) binds CO2 at a rate of ca...
June 22, 2017: Inorganic Chemistry
https://www.readbyqxmd.com/read/28634293/intrinsic-map-dynamics-exploration-for-uncharted-effective-free-energy-landscapes
#12
Eliodoro Chiavazzo, Roberto Covino, Ronald R Coifman, C William Gear, Anastasia S Georgiou, Gerhard Hummer, Ioannis G Kevrekidis
We describe and implement a computer-assisted approach for accelerating the exploration of uncharted effective free-energy surfaces (FESs). More generally, the aim is the extraction of coarse-grained, macroscopic information from stochastic or atomistic simulations, such as molecular dynamics (MD). The approach functionally links the MD simulator with nonlinear manifold learning techniques. The added value comes from biasing the simulator toward unexplored phase-space regions by exploiting the smoothness of the gradually revealed intrinsic low-dimensional geometry of the FES...
June 20, 2017: Proceedings of the National Academy of Sciences of the United States of America
https://www.readbyqxmd.com/read/28632170/current-research-in-lidar-technology-used-for-the-remote-sensing-of-atmospheric-aerosols
#13
REVIEW
Adolfo Comerón, Constantino Muñoz-Porcar, Francesc Rocadenbosch, Alejandro Rodríguez-Gómez, Michaël Sicard
Lidars are active optical remote sensing instruments with unique capabilities for atmospheric sounding. A manifold of atmospheric variables can be profiled using different types of lidar: concentration of species, wind speed, temperature, etc. Among them, measurement of the properties of aerosol particles, whose influence in many atmospheric processes is important but is still poorly stated, stands as one of the main fields of application of current lidar systems. This paper presents a review on fundamentals, technology, methodologies and state-of-the art of the lidar systems used to obtain aerosol information...
June 20, 2017: Sensors
https://www.readbyqxmd.com/read/28630971/2-thiouracil-intersystem-crossing-photodynamics-studied-by-wavelength-dependent-photoelectron-and-transient-absorption-spectroscopies
#14
José A Sánchez-Rodríguez, Abed Mohamadzade, Sebastian Mai, Brennan Ashwood, Marvin Pollum, Philipp Marquetand, Leticia González, Carlos E Crespo-Hernández, Susanne Ullrich
Single-atom substitution within a natural nucleobase-such as replacing oxygen by sulfur in uracil-can result in drastic changes in the relaxation dynamics after UV excitation. While the photodynamics of natural nucleobases like uracil are dominated by pathways along singlet excited states, the photodynamics of thiobases like 2-thiouracil populate the triplet manifold with near unity quantum yield. In the present study, a synergistic approach based on time-resolved photoelectron spectroscopy (TRPES), time-resolved absorption spectroscopy (TRAS), and ab initio computations has been particularly successful at unraveling the underlying photophysical principles and describing the dissimilarities between the natural and substituted nucleobases...
June 20, 2017: Physical Chemistry Chemical Physics: PCCP
https://www.readbyqxmd.com/read/28630026/what-have-we-learned-on-aging-from-omics-studies
#15
REVIEW
Alessandro Cellerino, Alessandro Ori
Aging is a complex process. Transcriptomic studies of the last decade have identified genes and pathways that are regulated during aging in multiple species and organs. Yet, since a manifold of pathways are regulated and the amplitude of regulation is often small, reproducibility across studies is moderate and disentangling cause-consequence relationships has proven challenging. Here, we review a number of consistent findings in the light of more recent, longitudinal studies and of studies combining transcriptomics and proteomics that identified deregulation of protein biosynthetic pathways as an early event and likely driver of aging...
June 16, 2017: Seminars in Cell & Developmental Biology
https://www.readbyqxmd.com/read/28628932/-european-collaboration-in-medical-device-assessment-one-step-towards-cross-border-health-care
#16
Julia Mayer, Sabine Ettinger, Anna Nachtnebel
Aim The aim of this paper was to present the legal framework as well as previous experience in transnational collaboration regarding the assessment of medical devices for reimbursement decisions. Furthermore, the possible benefit of transnational collaboration for various stakeholders will be discussed. Methods Experiences gathered with the compilation of overall 6 joint rapid assessments of medical devices within the completed European Network for Health Technology Assessment (EUnetHTA) Joint Action 2 (JA2) are summarised and discussed...
June 19, 2017: Das Gesundheitswesen
https://www.readbyqxmd.com/read/28627472/molecular-dynamics-as-a-tool-for-in-silico-screening-of-skin-permeability
#17
Paolo Rocco, Francesco Cilurzo, Paola Minghetti, Giulio Vistoli, Alessandro Pedretti
Prediction of skin permeability can have manifold applications ranging from drug delivery to toxicity prediction. Along with the semi-empirical or mechanistic models proposed in the last decades, Molecular Dynamics simulations have recently become a fruitful tool for investigating membrane permeability, in particular as they allow the involved mechanisms to be modelled at a molecular level. Despite their significant structural complexity, Molecular Dynamics simulations can also be utilized to study permeation through the lipid matrix that characterizes the stratum corneum...
June 13, 2017: European Journal of Pharmaceutical Sciences
https://www.readbyqxmd.com/read/28626276/standing-and-travelling-waves-in-a-spherical-brain-model-the-nunez-model-revisited
#18
S Visser, R Nicks, O Faugeras, S Coombes
The Nunez model for the generation of electroencephalogram (EEG) signals is naturally described as a neural field model on a sphere with space-dependent delays. For simplicity, dynamical realisations of this model either as a damped wave equation or an integro-differential equation, have typically been studied in idealised one dimensional or planar settings. Here we revisit the original Nunez model to specifically address the role of spherical topology on spatio-temporal pattern generation. We do this using a mixture of Turing instability analysis, symmetric bifurcation theory, centre manifold reduction and direct simulations with a bespoke numerical scheme...
June 15, 2017: Physica D. Nonlinear Phenomena
https://www.readbyqxmd.com/read/28621795/machine-learning-for-autonomous-crystal-structure-identification
#19
Wesley F Reinhart, Andrew W Long, Michael P Howard, Andrew L Ferguson, Athanassios Z Panagiotopoulos
We present a machine learning technique to discover and distinguish relevant ordered structures from molecular simulation snapshots or particle tracking data. Unlike other popular methods for structural identification, our technique requires no a priori description of the target structures. Instead, we use nonlinear manifold learning to infer structural relationships between particles according to the topology of their local environment. This graph-based approach yields unbiased structural information which allows us to quantify the crystalline character of particles near defects, grain boundaries, and interfaces...
June 16, 2017: Soft Matter
https://www.readbyqxmd.com/read/28621466/integrative-pericyclic-cascade-an-atom-economy-multi-c-c-bond-forming-strategy-for-the-construction-of-molecular-complexity
#20
Fernando García-Tellado, David Tejedor, Samuel Delgado-Hernández, Jesús Peyrac, Javier González-Platas
An all-pericyclic manifold is developed for the construction of topologically diverse, structurally complex and natural product-like polycyclic chemotypes. The manifold uses readily accessible tertiary propargyl vinyl ethers as substrates and an imidazole as a catalyst to form up to 2 new rings, 3 new C-C bonds, 6 stereogenic centers and one transannular oxo-bridge. The manifold is efficient, scalable and instrumentally simple to perform and entails a Propargyl Claisen rearrangement-[1,3]H-shift, an oxa-6 electrocyclization and an intramolecular Diels-Alder reaction...
June 16, 2017: Chemistry: a European Journal
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