Variability of echo state network prediction horizon for partially observed dynamical systems

Study of dynamical systems using partial state observation is an important problem due to its applicability to many real-world systems. We address the problem by proposing an echo state network (ESN) framework with partial state input with partial or full state output. Application to the Lorenz system and Chua's oscillator (both numerically simulated and experimental systems) demonstrate the effectiveness of our method. We show that the ESN, as an autonomous dynamical system, is capable of making short-term predictions up to a few Lyapunov times. However, the prediction horizon has high variability depending on the initial condition - an aspect that we explore in detail using the distribution of the prediction horizon. Further, using a variety of statistical metrics to compare the long-term dynamics of the ESN predictions with numerically simulated or experimental dynamics and observed similar results, we show that the ESN can effectively learn the system's dynamics even when trained with noisy numerical or experimental datasets. Thus, we demonstrate the potential of ESNs to serve as cheap surrogate models for simulating the dynamics of systems where complete observations are unavailable

Improving Automatic Speech Recognition by Co-embedding Voice Queries and Voice Query Refinements

Automatic speech recognition (ASR) models are used to recognize voice commands or queries from users in hardware products such as smartphones, smart speakers/displays, as well as applications that enable speech interaction, e.g., virtual assistant applications. However, the query abandonment rates for voice queries continue to be much higher than text queries which is often due to incorrect interpretation of the spoken query. This disclosure describes techniques to improve the performance of recognition of spoken queries by combining user specific phonetic variations and session specific contextual signals, obtained with specific user permission

Effect of aerosol composition on the performance of low-cost optical particle counter correction factors

There is considerable interest in using low-cost optical particle counters (OPCs) to supplement existing routine air quality networks that monitor particle mass concentrations. In order to do this, low-cost OPC data need to be comparable with particle mass reference instrumentation; however, there is currently no widely agreed upon methodology to accomplish this. Aerosol hygroscopicity is known to be a key parameter to consider when correcting particle mass concentrations derived from low-cost OPCs, particularly at high ambient relative humidity (RH). Correction factors have been developed that apply κ-Köhler theory to correct for the influence of water uptake by hygroscopic aerosols. We have used datasets of co-located reference particle measurements and low-cost OPC (OPC-N2, Alphasense) measurements, collected in four cities on three continents, to explore the performance of this correction factor. We provide evidence that the elevated particle mass concentrations, reported by the low-cost OPC relative to reference instrumentation, are due to bulk aerosol hygroscopicity under different RH conditions, which is determined by aerosol composition and, in particular, the levels of hygroscopic aerosols (sulfate and nitrate). We exploit measurements made in volcanic plumes in Nicaragua, which are predominantly composed of sulfate aerosol, as a natural experiment to demonstrate this behaviour in the ambient atmosphere; the observed humidogram from these measurements closely resembles the calculated pure sulfuric acid humidogram. The results indicate that the particle mass concentrations derived from low-cost OPCs during periods of high RH (>60 %) need to be corrected for aerosol hygroscopic growth. We employed a correction factor based on κ-Köhler theory and observed that the corrected OPC-N2 PM2.5 mass concentrations were within 33 % of reference measurements at all sites. The results indicated that a κ value derived in situ (using suitable reference instrumentation) would lead to the most accurate correction relative to co-located reference instruments. Applying a κ values from the literature in the correction factor also resulted in improved OPC-N2 performance, with the measurements being within 50 % of the reference values. Therefore, for areas where suitable reference instrumentation for developing a local correction factor is lacking, using a literature κ value can result in a reasonable correction. For locations with low levels of hygroscopic aerosols and low RH values, a simple calibration against gravimetric measurements (using suitable reference instrumentation) would likely be sufficient. Whilst this study generated correction factors specific for the Alphasense OPC-N2 sensor, the calibration methodology developed is likely amenable to other low-cost PM sensors

Visual Acuity and Associated Factors. The Central India Eye and Medical Study

Visual acuity is a major parameter for quality of vision and quality of life. Information on visual acuity and its associated factors in rural societies almost untouched by any industrialization is mostly non-available. It was, therefore, the purpose of our study to determine the distribution of visual acuity and its associated factors in a rural population not marked influenced by modern lifestyle. The population-based Central India Eye and Medical Study included 4711 subjects (aged 30+ years), who underwent a detailed ophthalmologic examination including visual acuity measurement. Visual acuity measurements were available for 4706 subjects with a mean age of 49.5±13.4 years (range: 30–100 years). BCVA decreased significantly (P<0.001) from the moderately hyperopic group (0.08±0.15 logMAR) to the emmetropic group (0.16±0.52 logMAR), the moderately myopic group (0.28±0.33 logMAR), the highly hyperopic group (0.66±0.62 logMAR) and finally the highly myopic group (1.32±0.92 logMAR). In multivariate analysis, BCVA was significantly associated with the systemic parameters of lower age (P<0.001), higher level of education (P<0.001), higher body stature (P<0.001) and higher body mass index (P<0.001), and with the ophthalmic parameters of more hyperopic refractive error (spherical equivalent) (P<0.001), shorter axial length (P<0.001), lower degree of nuclear cataract (P<0.001), and lower intraocular pressure (P = 0.006). The results suggest that in the rural population of Central India, major determinants of visual acuity were socioeconomic background, body stature and body mass index, age, refractive error, cataract and intraocular pressure

Emerging Applications of Elemental 2D Materials.

As elemental main group materials (i.e., silicon and germanium) have dominated the field of modern electronics, their monolayer 2D analogues have shown great promise for next-generation electronic materials as well as potential game-changing properties for optoelectronics, energy, and beyond. These atomically thin materials composed of single atomic variants of group III through group VI elements on the periodic table have already demonstrated exciting properties such as near-room-temperature topological insulation in bismuthene, extremely high electron mobilities in phosphorene and silicone, and substantial Li-ion storage capability in borophene. Isolation of these materials within the postgraphene era began with silicene in 2010 and quickly progressed to the experimental identification or theoretical prediction of 15 of the 18 main group elements existing as solids at standard pressure and temperatures. This review first focuses on the significance of defects/functionalization, discussion of different allotropes, and overarching structure-property relationships of 2D main group elemental materials. Then, a complete review of emerging applications in electronics, sensing, spintronics, plasmonics, photodetectors, ultrafast lasers, batteries, supercapacitors, and thermoelectrics is presented by application type, including detailed descriptions of how the material properties may be tailored toward each specific application

Emerging Applications of Elemental 2D Materials

As elemental main group materials (i.e., silicon and germanium) have dominated the field of modern electronics, their monolayer 2D analogues have shown great promise for next‐generation electronic materials as well as potential game‐changing properties for optoelectronics, energy, and beyond. These atomically thin materials composed of single atomic variants of group III through group VI elements on the periodic table have already demonstrated exciting properties such as near‐room‐temperature topological insulation in bismuthene, extremely high electron mobilities in phosphorene and silicone, and substantial Li‐ion storage capability in borophene. Isolation of these materials within the postgraphene era began with silicene in 2010 and quickly progressed to the experimental identification or theoretical prediction of 15 of the 18 main group elements existing as solids at standard pressure and temperatures. This review first focuses on the significance of defects/functionalization, discussion of different allotropes, and overarching structure–property relationships of 2D main group elemental materials. Then, a complete review of emerging applications in electronics, sensing, spintronics, plasmonics, photodetectors, ultrafast lasers, batteries, supercapacitors, and thermoelectrics is presented by application type, including detailed descriptions of how the material properties may be tailored toward each specific application

Validation of a Genome-Wide Polygenic Score for Coronary Artery Disease in South Asians.

BACKGROUND: Genome-wide polygenic scores (GPS) integrate information from many common DNA variants into a single number. Because rates of coronary artery disease (CAD) are substantially higher among South Asians, a GPS to identify high-risk individuals may be particularly useful in this population. OBJECTIVES: This analysis used summary statistics from a prior genome-wide association study to derive a new GPSCAD for South Asians. METHODS: This GPSCAD was validated in 7,244 South Asian UK Biobank participants and tested in 491 individuals from a case-control study in Bangladesh. Next, a static ancestry and GPSCAD reference distribution was built using whole-genome sequencing from 1,522 Indian individuals, and a framework was tested for projecting individuals onto this static ancestry and GPSCAD reference distribution using 1,800 CAD cases and 1,163 control subjects newly recruited in India. RESULTS: The GPSCAD, containing 6,630,150 common DNA variants, had an odds ratio (OR) per SD of 1.58 in South Asian UK Biobank participants and 1.60 in the Bangladeshi study (p < 0.001 for each). Next, individuals of the Indian case-control study were projected onto static reference distributions, observing an OR/SD of 1.66 (p < 0.001). Compared with the middle quintile, risk for CAD was most pronounced for those in the top 5% of the GPSCAD distribution-ORs of 4.16, 2.46, and 3.22 in the South Asian UK Biobank, Bangladeshi, and Indian studies, respectively (p < 0.05 for each). CONCLUSIONS: The new GPSCAD has been developed and tested using 3 distinct South Asian studies, and provides a generalizable framework for ancestry-specific GPS assessment.Dr. Patel is supported by grant T32HL007208 from the National Heart, Lung, and Blood Institute; Dr. Kathiresan is supported by the Ofer and Shelly Nemirovsky Research Scholar Award from Massachusetts General Hospital and the National Human Genome Research Institute under award number 5UM1HG008895; Dr. Khera is supported by an institutional grant from the Broad Institute of MIT and Harvard (BroadIgnite), award numbers 1K08HG010155 and 5UM1HG008895 from the National Human Genome Research Institute, a Hassenfeld Scholar Award from Massachusetts General Hospital, and a sponsored research agreement from IBM Research