Illinois Institute of Technology

About: Illinois Institute of Technology is a education organization based out in Chicago, Illinois, United States. It is known for research contribution in the topics: Electric power system & Wireless network. The organization has 10188 authors who have published 21062 publications receiving 554178 citations. The organization is also known as: IIT & Illinois Tech.

Measurement of the Reactor Antineutrino Flux and Spectrum at Daya Bay

Abstract: This Letter reports a measurement of the flux and energy spectrum of electron antineutrinos from six 2.9 GWth nuclear reactors with six detectors deployed in two near (effective baselines 512 and 561 m) and one far (1579 m) underground experimental halls in the Daya Bay experiment. Using 217 days of data, 296 721 and 41 589 inverse β decay (IBD) candidates were detected in the near and far halls, respectively. The measured IBD yield is (1.55±0.04) ×10(-18) cm(2) GW(-1) day(-1) or (5.92±0.14) ×10(-43) cm(2) fission(-1). This flux measurement is consistent with previous short-baseline reactor antineutrino experiments and is 0.946±0.022 (0.991±0.023) relative to the flux predicted with the Huber-Mueller (ILL-Vogel) fissile antineutrino model. The measured IBD positron energy spectrum deviates from both spectral predictions by more than 2σ over the full energy range with a local significance of up to ∼4σ between 4-6 MeV. A reactor antineutrino spectrum of IBD reactions is extracted from the measured positron energy spectrum for model-independent predictions.

Cost of Reliability Analysis Based on Stochastic Unit Commitment

Abstract: This paper presents a model for calculating the cost of power system reliability based on the stochastic optimization of long-term security-constrained unit commitment. Random outages of generating units and transmission lines as well as load forecasting inaccuracy are modeled as scenario trees in the Monte Carlo simulation. Unlike previous reliability analyses methods in the literature which considered the solution of an economic dispatch problem, this model solves an hourly unit commitment problem, which incorporates spatial constraints of generating units and transmission lines, random component outages, and load forecast uncertainty into the reliability problem. The classical methods considered predefined reserve constraints in the deterministic solution of unit commitment. However, this study considers possible uncertainties when calculating the optimal reserve in the unit commitment solution as a tradeoff between minimizing operating costs and satisfying power system reliability requirements. Loss-of-load-expectation (LOLE) is included as a constraint in the stochastic unit commitment for calculating the cost of supplying the reserve. The proposed model can be used by a vertically integrated utility or an ISO. In the first case, the utility considers the impact of long-term fuel and emission scheduling on power system reliability studies. In the second case, fuel and emission constraints of individual generating companies are submitted as energy constraints when solving the ISO's reliability problem. Numerical simulations indicate the effectiveness of the proposed approach for minimizing the cost of reliability in stochastic power systems.

DEEPre: sequence-based enzyme EC number prediction by deep learning

Abstract: Motivation Annotation of enzyme function has a broad range of applications, such as metagenomics, industrial biotechnology, and diagnosis of enzyme deficiency-caused diseases. However, the time and resource required make it prohibitively expensive to experimentally determine the function of every enzyme. Therefore, computational enzyme function prediction has become increasingly important. In this paper, we develop such an approach, determining the enzyme function by predicting the Enzyme Commission number. Results We propose an end-to-end feature selection and classification model training approach, as well as an automatic and robust feature dimensionality uniformization method, DEEPre, in the field of enzyme function prediction. Instead of extracting manually crafted features from enzyme sequences, our model takes the raw sequence encoding as inputs, extracting convolutional and sequential features from the raw encoding based on the classification result to directly improve the prediction performance. The thorough cross-fold validation experiments conducted on two large-scale datasets show that DEEPre improves the prediction performance over the previous state-of-the-art methods. In addition, our server outperforms five other servers in determining the main class of enzymes on a separate low-homology dataset. Two case studies demonstrate DEEPre's ability to capture the functional difference of enzyme isoforms. Availability and implementation The server could be accessed freely at http://www.cbrc.kaust.edu.sa/DEEPre. Contact xin.gao@kaust.edu.sa. Supplementary information Supplementary data are available at Bioinformatics online.

Surface Modification of Colloidal Gold by Chemisorption of Alkanethiols in the Presence of a Nonionic Surfactant

Abstract: Surface modification of colloidal gold with 11-mercaptoundecanoic acid or 16-mercaptohexadecanoic acid was performed in the absence or in the presence of the nonionic surfactant polyoxyethylene (20) sorbitan monolaurate (Tween 20). The stability of the colloidal systems was assessed with optical absorption spectroscopy. The surface-modified nanoparticles were stable only within a narrow range of intermediate pH values when chemisorption of alkanethiols was performed in the absence of Tween 20. This was explained in terms of partial ionization of the surface carboxylic groups and charge neutralization at high pH values by counterions present in the buffer solutions. Formation of a physisorbed monolayer of Tween 20 onto the nanoparticles prior to chemisorption of alkanethiols resulted in surface-modified colloidal gold that was stable over a broader range of pH values. Parallel experiments demonstrated that self-assembled monolayers could form on flat substrates in the presence of Tween 20. Therefore, possi...