Color-tunable triple state 'smart' window

Materials that rapidly change their optical properties in response to external stimuli are crucial for displays and “smart” window applications. Herein, a fluorescent red dye modified with liquid crystal (LC) side chains is described to be interactive with a LC host, resulting in a color‐tunable triple‐state smart window. The dye solubilizes in the LC matrix with increasing temperature, resulting in a red‐colored, absorbing state, recovering transparency again by reaggregation of the dye within minutes upon cooling. This dye is used to fabricate a device that can be electrically switched from a red‐colored, absorbing state to an intermediate scattering state and at greater electrical fields, a transparent state. Using a second dichroic fluorescent dye, heating the device transitions the window's color from yellow/green to red. The multiresponsive optical changes could find applications in many fields, including displays, smart windows, electricity generation, and signage

TARGET: toward a solution for the readout electronics of the Cherenkov Telescope Array

TARGET is an application specific integrated circuit (ASIC) designed to read out signals recorded by the photosensors in cameras of very-high-energy gamma-ray telescopes exploiting the imaging of Cherenkov radiation from atmospheric showers. TARGET capabilities include sampling at a high rate (typically 1 GSample/s), digitization, and triggering on the sum of four adjacent pixels. The small size, large number of channels read out per ASIC (16), low cost per channel, and deep buffer for trigger latency (~16 $\mu$s at 1 GSample/s) make TARGET ideally suited for the readout in systems with a large number of telescopes instrumented with compact photosensors like multi-anode or silicon photomultipliers combined with dual-mirror optics. The possible advantages of such systems are better sensitivity, a larger field of view, and improved angular resolution. The two latest generations of TARGET ASICs, TARGET 5 and TARGET 7, are soon to be used for the first time in two prototypes of small-sized and medium-sized dual-mirror telescopes proposed in the framework of the Cherenkov Telescope Array (CTA) project. In this contribution we report on the performance of the TARGET ASICs and discuss future developments.Comment: 8 pages, 3 figures. In Proceedings of the 34th International Cosmic Ray Conference (ICRC2015), The Hague, The Netherlands. All CTA contributions at arXiv:1508.0589

Forecasting Energy Demand in Large Commercial Buildings Using Support Vector Machine Regression

As our society gains a better understanding of how humans have negatively impacted the environment, research related to reducing carbon emissions and overall energy consumption has become increasingly important. One of the simplest ways to reduce energy usage is by making current buildings less wasteful. By improving energy efficiency, this method of lowering our carbon footprint is particularly worthwhile because it reduces energy costs of operating the building, unlike many environmental initiatives that require large monetary investments. In order to improve the efficiency of the heating, ventilation, and air conditioning (HVAC) system of a Manhattan skyscraper, 345 Park Avenue, a predictive computer model was designed to forecast the amount of energy the building will consume. This model uses Support Vector Machine Regression (SVMR), a method that builds a regression based purely on historical data of the building, requiring no knowledge of its size, heating and cooling methods, or any other physical properties. SVMR employs time-delay coordinates as a representation of the past to create the feature vectors for SVM training. This pure dependence on historical data makes the model very easily applicable to different types of buildings with few model adjustments. The SVM regression model was built to predict a week of future energy usage based on past energy, temperature, and dew point temperature data

Walks on Apollonian networks

We carry out comparative studies of random walks on deterministic Apollonian networks (DANs) and random Apollonian networks (RANs). We perform computer simulations for the mean first passage time, the average return time, the mean-square displacement, and the network coverage for unrestricted random walk. The diffusions both on DANs and RANs are proved to be sublinear. The search efficiency for walks with various strategies and the influence of the topology of underlying networks on the dynamics of walks are discussed. Contrary to one's intuition, it is shown that the self-avoiding random walk, which has been verified as an optimal strategy for searching on scale-free and small-world networks, is not the best strategy for the DAN in the thermodynamic limit.Comment: 5 pages, 4 figure

Collapse of the vortex-lattice inductance and shear modulus at the melting transition in untwinned YBa2Cu3O7\rm YBa_2Cu_3O_7

The complex resistivity $\hat{\rho}(\omega)$ of the vortex lattice in an untwinned crystal of 93-K $\rm YBa_2Cu_3O_7$ has been measured at frequencies $\omega/2\pi$ from 100 kHz to 20 MHz in a 2-Tesla field $\bf H\parallel c$, using a 4-probe RF transmission technique that enables continuous measurements versus $\omega$ and temperature $T$. As $T$ is increased, the inductance ${\cal L}_s(\omega) ={\rm Im} \hat{\rho}(\omega)/ \omega$ increases steeply to a cusp at the melting temperature $T_m$, and then undergoes a steep collapse consistent with vanishing of the shear modulus $c_{66}$. We discuss in detail the separation of the vortex-lattice inductance from the `volume' inductance, and other skin-depth effects. To analyze the spectra, we consider a weakly disordered lattice with a low pin density. Close fits are obtained to $\rho_1(\omega)$ over 2 decades in $\omega$. Values of the pinning parameter $\kappa$ and shear modulus $c_{66}$ obtained show that $c_{66}$ collapses by over 4 decades at $T_m$, whereas $\kappa$ remains finite.Comment: 11 pages, 8 figures, Phys. Rev. B, in pres

Estimation of System Reliability Using a Semiparametric Model

An important problem in reliability engineering is to predict the failure rate, that is, the frequency with which an engineered system or component fails. This paper presents a new method of estimating failure rate using a semiparametric model with Gaussian process smoothing. The method is able to provide accurate estimation based on historical data and it does not make strong a priori assumptions of failure rate pattern (e.g., constant or monotonic). Our experiments of applying this method in power system failure data compared with other models show its efficacy and accuracy. This method can be used in estimating reliability for many other systems, such as software systems or components

Improving Efficiency and Reliability of Building Systems Using Machine Learning and Automated Online Evaluation

A high percentage of newly-constructed commercial office buildings experience energy consumption that exceeds specifications and system failures after being put into use. This problem is even worse for older buildings. We present a new approach, 'predictive building energy optimization', which uses machine learning (ML) and automated online evaluation of historical and real-time building data to improve efficiency and reliability of building operations without requiring large amounts of additional capital investment. Our ML approach uses a predictive model to generate accurate energy demand forecasts and automated analyses that can guide optimization of building operations. In parallel, an automated online evaluation system monitors efficiency at multiple stages in the system workflow and provides building operators with continuous feedback. We implemented a prototype of this application in a large commercial building in Manhattan. Our predictive machine learning model applies Support Vector Regression (SVR) to the building's historical energy use and temperature and wet-bulb humidity data from the building's interior and exterior in order to model performance for each day. This predictive model closely approximates actual energy usage values, with some seasonal and occupant-specific variability, and the dependence of the data on day-of-the-week makes the model easily applicable to different types of buildings with minimal adjustment. In parallel, an automated online evaluator monitors the building's internal and external conditions, control actions and the results of those actions. Intelligent real-time data quality analysis components quickly detect anomalies and automatically transmit feedback to building management, who can then take necessary preventive or corrective actions. Our experiments show that this evaluator is responsive and effective in further ensuring reliable and energyefficient operation of building systems

Intrinsic Absorption Lines in Seyfert 1 Galaxies. I. Ultraviolet Spectra from the Hubble Space Telescope

We present a study of the intrinsic absorption lines in the ultraviolet spectra of Seyfert 1 galaxies. We find that the fraction of Seyfert 1 galaxies that show absorption associated with their active nuclei is more than one-half (10/17), which is much higher than previous estimates (3 - 10%) . There is a one-to-one correspondence between Seyferts that show intrinsic UV absorption and X-ray ``warm absorbers''. The intrinsic UV absorption is generally characterized by high ionization: C IV and N V are seen in all 10 Seyferts with detected absorption (in addition to Ly-alpha), whereas Si IV is present in only four of these Seyferts, and Mg II absorption is only detected in NGC 4151. The absorption lines are blueshifted (or in a few cases at rest) with respect to the narrow emission lines, indicating that the absorbing gas is undergoing net radial outflow. At high resolution, the absorption often splits into distinct kinematic components that show a wide range in widths (20 - 400 km/s FWHM), indicating macroscopic motions (e.g., radial velocity subcomponents or turbulence) within a component. The strong absorption components have cores that are much deeper than the continuum flux levels, indicating that the regions responsible for these components lie completely outside of the broad emission-line regions. The covering factor of the absorbing gas in the line of sight, relative to the total underlying emission, is C > 0.86, on average. The global covering factor, which is the fraction of emission intercepted by the absorber averaged over all lines of sight, is C > 0.5.Comment: 56 pages, Latex, includes 4 figures (encapsulated postscript), Fig. 1 has 2 parts and Fig. 2 has 3 parts, to appear in the Astrophysical Journa