Stochastic Analysis of the Seismic Response of Secondary Systems

This thesis is concerned with the earthquake response of light equipment in structures. The motion of the ground during an earthquake is represented as a stochastic process in order to reflect uncertainty in the prediction of such motion. A number of different stochastic earthquake models are considered, and analytical methods are described for these models. The response of equipment in a structure to stochastic ground motion is derived, in the case of a single-degree-of-freedom secondary system (equipment) attached to a single-degree-of-freedom structure. The distribution of the envelope of the secondary system displacement is obtained for general transient ground motion. Closed form expressions are computed for the transient response to stationary ground motion. The effect of the interaction of equipment with the structure is described by the introduction of an equivalent non-interacting system. However, this method applies only to classically damped systems. The results are applied in a simple way to the problem of the computation of floor spectra. It is found that the ground spectrum is amplified in a simple way, except near resonance, where special considerations must be addressed.</p

Motor Controller System For Large Dynamic Range of Motor Operation

A motor controller system uses a rotary sensor with a plurality of signal conditioning units, coupled to the rotary sensor. Each of these units, which is associated with a particular range of motor output shaft rotation rates, generate a feedback signal indicative of the position of the motor s output shaft. A controller (i) converts a selected motor output shaft rotation rate to a corresponding incremental amount of rotational movement for a selected fixed time period, (ii) selects, at periodic completions of the selected fixed time period, the feedback signal from one of the signal conditioning units for which the particular range of motor output shaft rotation rates associated therewith encompasses the selected motor output shaft rotation rate, and (iii) generates a motor drive signal based on a difference between the incremental amount of rotational movement and the feedback signal from the selected one of the signal conditioning Units

Water Withdrawals in Illinois, 2011

This report summarizes data collected by the Illinois Water Inventory Program for calendar year 2011. Water use data are presented for public water supply and self-supplied industry facilities within Illinois. The data are further categorized by county, township, Illinois priority planning areas, and within two major Illinois withdrawal areas: Chicago and central Illinois. Illinois water withdrawals during 2011 were 53,428.6 million gallons per day (mgd), of which groundwater supplied 513.4 mgd and surface water supplied 52,915.2 mgd. Public water supply (PWS) withdrew 1,508.3 mgd and self-supplied-industry (SSI) withdrew 51,920.3 mdg. Electric power generation is the largest water use in Illinois with 96.3 percent of the total water withdrawal. Excluding electric power withdrawals, 2011 groundwater use was 508.5 mgd, and surface water use was 1,489.8 mgd.Ope

Automatic segmentation of intravital fluorescence microscopy images by K-means clustering of FLIM phasors

Fluorescence lifetime imaging microscopy (FLIM) provides additional contrast for fluorophores with overlapping emission spectra. The phasor approach to FLIM greatly reduces the complexity of FLIM analysis and enables a useful image segmentation technique by selecting adjacent phasor points and labeling their corresponding pixels with different colors. This phasor labeling process, however, is empirical and could lead to biased results. In this Letter, we present a novel and unbiased approach to automate the phasor labeling process using an unsupervised machine learning technique, i.e., K-means clustering. In addition, we provide an open-source, user-friendly program that enables users to easily employ the proposed approach. We demonstrate successful image segmentation on 2D and 3D FLIM images of fixed cells and living animals acquired with two different FLIM systems. Finally, we evaluate how different parameters affect the segmentation result and provide a guideline for users to achieve optimal performance

Convolutional Neural Network Denoising in Fluorescence Lifetime Imaging Microscopy (FLIM)

Fluorescence lifetime imaging microscopy (FLIM) systems are limited by their slow processing speed, low signal-to-noise ratio (SNR), and expensive and challenging hardware setups. In this work, we demonstrate applying a denoising convolutional network to improve FLIM SNR. The network will be integrated with an instant FLIM system with fast data acquisition based on analog signal processing, high SNR using high-efficiency pulse-modulation, and cost-effective implementation utilizing off-the-shelf radio-frequency components. Our instant FLIM system simultaneously provides the intensity, lifetime, and phasor plots \textit{in vivo} and \textit{ex vivo}. By integrating image denoising using the trained deep learning model on the FLIM data, provide accurate FLIM phasor measurements are obtained. The enhanced phasor is then passed through the K-means clustering segmentation method, an unbiased and unsupervised machine learning technique to separate different fluorophores accurately. Our experimental \textit{in vivo} mouse kidney results indicate that introducing the deep learning image denoising model before the segmentation effectively removes the noise in the phasor compared to existing methods and provides clearer segments. Hence, the proposed deep learning-based workflow provides fast and accurate automatic segmentation of fluorescence images using instant FLIM. The denoising operation is effective for the segmentation if the FLIM measurements are noisy. The clustering can effectively enhance the detection of biological structures of interest in biomedical imaging applications.Comment: SPIE Proceedings Volume 11648, Multiphoton Microscopy in the Biomedical Sciences XXI; 116481C (2021

The importance of 1,5-oxygen-chalcogen interactions in enantioselective isochalcogenourea catalysis

Syngenta (Case Award to DJP) and a Philip Leverhulme Prize for funding (SLC, AE). RKM and PHW are grateful to the American Chemical Society Petroleum Research Fund and National Science Foundation (NSF-MRI: CHE-1429616).The importance of 1,5-O···chalcogen (Ch) interactions in isochalcogenourea catalysis (Ch = O, S, Se) is investigated. Conformational analyses of N-acyl isochalcogenouronium species and comparison with kinetic data demonstrate the significance of 1,5-O···Ch interactions in enantioselective catalysis. Importantly, the selenium analogue demonstrates enhanced rate and selectivity profiles across a range of reaction processes including nitronate conjugate addition and formal [4+2] cycloadditions. A gram-scale synthesis of the most active selenium analogue was developed using a previously unreported seleno-Hugerschoff reaction, allowing the challenging kinetic resolutions of tertiary alcohols to be performed at 500 ppm catalyst loading. Density Functional Theory (DFT) and natural bond orbital (NBO) calculations support the role of orbital delocalization (occurring by intramolecular chalcogen bonding) in determining the conformation, equilibrium population, and reactivity of N-acylated intermediates.PostprintPeer reviewe

An approach for verifying biogenic greenhouse gas emissions inventories with atmospheric CO₂ concentration data

Verifying national greenhouse gas (GHG) emissions inventories is a critical step to ensure that reported emissions data to the United Nations Framework Convention on Climate Change (UNFCCC) are accurate and representative of a country\u27s contribution to GHG concentrations in the atmosphere. Furthermore, verifying biogenic fluxes provides a check on estimated emissions associated with managing lands for carbon sequestration and other activities, which often have large uncertainties. We report here on the challenges and results associated with a case study using atmospheric measurements of CO₂ concentrations and inverse modeling to verify nationally-reported biogenic CO₂ emissions. The biogenic CO₂ emissions inventory was compiled for the Mid-Continent region of United States based on methods and data used by the US government for reporting to the UNFCCC, along with additional sources and sinks to produce a full carbon balance. The biogenic emissions inventory produced an estimated flux of −408 ± 136 Tg CO₂ for the entire study region, which was not statistically different from the biogenic flux of −478 ± 146 Tg CO₂ that was estimated using the atmospheric CO₂concentration data. At sub-regional scales, the spatial density of atmospheric observations did not appear sufficient to verify emissions in general. However, a difference between the inventory and inversion results was found in one isolated area of West-central Wisconsin. This part of the region is dominated by forestlands, suggesting that further investigation may be warranted into the forest C stock or harvested wood product data from this portion of the study area. The results suggest that observations of atmospheric CO₂ concentration data and inverse modeling could be used to verify biogenic emissions, and provide more confidence in biogenic GHG emissions reporting to the UNFCCC

Sharpening the predictions of big-bang nucleosynthesis

Motivated by the recent measurement of the primeval abundance of deuterium, we re-examine the nuclear inputs to big-bang nucleosynthesis (BBN). Using Monte-Carlo realization of the nuclear cross-section data to directly estimate the theoretical uncertainties for the yields of D, 3-He and 7-Li, we show that previous estimates were a factor of 2 too large. We sharpen the BBN determination of the baryon density based upon deuterium, rho_B = (3.6 +/- 0.4) * 10^{-31} g/cm^3 (Omega_B h^2 = 0.019 +/- 0.0024), which leads to a predicted 4-He abundance, Y_P = 0.246 +/- 0.0014 and a stringent limit to the equivalent number of light neutrino species: N_nu < 3.20 (all at 95% cl). The predicted 7-Li abundance, 7-Li/H = (3.5 + 1.1 - 0.9) * 10^{-10}, is higher than that observed in pop II stars, (1.7 +/- 0.3) * 10^{-10} (both, 95% cl). We identify key reactions and the energies where further work is needed.Comment: 5 pages, 4 figures (epsfig), REVTeX; submitted to Phys. Rev. Let