946 research outputs found
Attribute reduction approaches for general relation decision systems
No full textThis paper proposes the concept of general relation decision systems and studies attribute reduction algorithms for relation decision systems, which are generalization of decision tables. In our relation decision systems, both condition and decision attribute sets consist of general binary relations. Novel attribute reduction algorithms for consistent and inconsistent relation decision systems are derived, respectively. A data set from the UCI machine learning databases is used in the empirical study, the experimental results verify the effectiveness of the proposed algorithms. The results unify the earlier attribute reduction algorithms for decision tables
Visible light induced oxidative hydroxylation of boronic acids
No full textWe report herein a visible light-induced aerobic oxidative hydroxylation of boronic acids. The reaction employed 7H-benzo[c]thioxanthen-7-one as metal-free catalyst and dimethyl carbonate as green solvent. Scale-up experiment was achieved using 0.1 mol% catalyst in a good yield with column-free purification. This reaction showed great green chemistry features and potential in synthetic applications.</p
Developing force field parameters for water interacting with graphene and graphene-like materials
No full textConfined water can have properties dramatically different from bulk water, and these properties can be used to develop unique functionality at the nanoscale. For example, fast water transport, rotation-translation coupling, and fast rotationalmotion have been observed in graphitic carbon-based nano structures, which enables various applications like energy storage and seawater desalination. The explosive studies on graphene have sparked new interests towards graphene-analogous materials including hexagonal boron nitride (hBN) and molybdenum disulfide (MoS2). Compared to graphene, the graphene-analogous materials possess non-zero bandgap, chemical inertness, and biological compatibility. The graphene-analogous materials are promising materials, complementary to graphene, for high-temperature, biomedical and nanofluidic applications. We would like to understand and optimize graphene and graphene-analogous materials in these applications.
The study of graphene and graphene-analogous materials at the atomic level requires accurate force field parameters to describe the water-surface interaction. We begin with benchmark quality first principles quantum Monte Carlo (QMC) calculations on the interaction energy between water and surface, which are used to validate random phase approximation (RPA) calculations. We then proceed with RPA to derive force field parameters, which are used to simulate properties like water contact angle on the surface, attaining a value within the experimental uncertainties. This work demonstrates that end-to-end multiscale modeling, starting at detailed many-body quantum mechanics, and ending with macroscopic properties, with the approximations controlled along the way, is feasible for these systems.Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2018-08-01The student, Yanbin Wu, accepted the attached license on 2016-07-01 at 11:25.The student, Yanbin Wu, submitted this Dissertation for approval on 2016-07-01 at 11:32.This Dissertation was approved for publication on 2016-07-05 at 09:40.DSpace SAF Submission Ingestion Package generated from Vireo submission #9740 on 2016-11-10 at 12:24:48Made available in DSpace on 2016-11-10T18:39:15Z (GMT). No. of bitstreams: 3
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Previous issue date: 2016-07-05Embargo set by: Seth Robbins for item 95447
Lift date: 2018-11-10T18:39:22Z
Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD systemEmbargo set by: Seth Robbins for item 95447
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Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD systemU of I Only Restriction Lifted for Item 95447 on 2018-11-11T10:15:28Z
Evaluation of a redox-initiated in situ hydrogel as vitreous substitute
No full textCurrently there is no material clinically available as a long-term vitreous substitute. In this study, an insitu gelation system based on alpha-poly(ethylene glycol) methacrylate (alpha-PEG-MA) and a redox-initiated radical polymerization/crosslinking reaction was evaluated for this purpose. Ammonium persulfate CAPS) and N,N,N',N'-tetramethyl ethylene diamine (TMEDA) were used as initiators. The gelation time, rheological properties, reaction kinetics and swelling profiles were studied in detail and the system with 10 wt% of alpha-PEG-MA and 8 mM APS/TMEDA was chosen as the optimal material for in vivo studies. Using the rabbit as the animal model, we showed that the system did form a space-filling and transparent gel in the vitreous cavity, and the inflammation response could be controlled to an acceptable level. (C) 2014 Elsevier Ltd. All rights reserved.Polymer ScienceSCI(E)[email protected]; [email protected]; [email protected]
A data-driven crop model for maize yield prediction
No full textAccurate estimation of crop yield predictions is of great importance for food security under the impact of climate change. We propose a data-driven crop model that combines the knowledge advantage of process-based modeling and the computational advantage of data-driven modeling. The proposed model tracks the daily biomass accumulation process during the maize growing season and uses daily produced biomass to estimate the final grain yield. Computational studies using crop yield, field location, genotype and corresponding environmental data were conducted in the US Corn Belt region from 1981 to 2020. The results suggest that the proposed model can achieve an accurate prediction performance with a 7.16% relative root-mean-square-error of average yield in 2020 and provide scientifically explainable results. The model also demonstrates its ability to detect and separate interactions between genotypic parameters and environmental variables. Additionally, this study demonstrates the potential value of the proposed model in helping farmers achieve higher yields by optimizing seed selection.This article is published as Chang, Yanbin, Jeremy Latham, Mark Licht, and Lizhi Wang. "A data-driven crop model for maize yield prediction." Communications Biology 6, no. 1 (2023): 439.
DOI: 10.1038/s42003-023-04833-y.
Copyright 2023 The Author(s).
Attribution 4.0 International (CC BY 4.0).
Posted with permission
Detrital zircon evidence from Burma for reorganization of the eastern Himalayan river system
No full textTowards a complete understanding of the Magellanic Clouds and Stream
No full textThe origin of Magellanic Clouds (MCs) and Stream have kept challenging to explain. Moreover, the recent discoveries of a huge amounts of ionized gas associated with the Stream and the extraordinary elongated 3D structure of SMC stars make them more enigmatic. Illustrating with fully-resolved hydrodynamical simulations, I will present comprehensive studies on this system, giving a overall and physical view on their formation history in a "ram-pressure plus collision" scenario. Carefully analyzed the deepest HI survey, we found that the overall Stream is actually structured into two ram-pressure tails. The ram pressure is induced by the diffused multiphase gas in the MW halo. Kelvin-Helmholtz instability in the mixing phase of the stripped gas provides sufficient efficiency to explain the huge amounts ionized gas in the Stream. The collision between the two clouds at 200-300 Myr ago has completely reshaped the system, i.e., radically changed the motion of LMC making it largely offset from the trace of its ram-pressure tail; helped to expel more gas from the Clouds; destroyed SMC stellar system stretching it into 30-kpc long along line of sight but only 5x3 kpc^2 in sky projection
基于光纤陀螺的转台周期性误差抑制方法
No full text
In order to suppress the periodic angle measuring error's fluctuation on gimbals and the imaging effect of photoelectric tracking, a measuring error model and an error control algorithm were established. Firstly, the mechanism of the measurement error of angular measuring system was analyzed, and a mathematical model for the periodic error was established in this paper. Secondly, a measuring error acquisition system based on the high precision fiber optic gyroscope and Fourier was established, and a specific expression of angle measurement error model was established through seven experimental procedures. Then, the periodic system error was compensated according to the measured angle error expressions through four steps. Finally, the effectiveness of control compensation was verified by tracking imaging experiments, and the experimental results show that speed error is reduced to 0.04 (°)/s, is reduced 8 times. The error meets the requirement of the imaging system less than 0.1 (°)/s, and the stripe imaging effect is greatly improved. ©, 2015, Chinese Society of Astronautics. All right reserved.</p
Adaptive Graph Partition Methods for Structured Graphs
No full textGraphs can be models for many real-world systems, where nodes indicate the entities and edges indicate the pairwise connections in between. In various cases, it is important to detect informative subsets of nodes such that the nodes within the subsets are ’closer’ to each other. For example, in a cellular network, determining appropriate node subsets can reduce the operation costs. A subset is usually called a cluster. This leads to the graph clustering problem. Furthermore, plenty of systems in the real world are changing over time, and consequently, graphs as models vary with time as well. It is thus also important to update the clusters when the graph changes.In this thesis work, we studied two problems from the cellular network background. We needed to partition graphs that have certain structures and cluster their nodes to minimize certain cost functions. In the first problem, we partitioned a bipartite graph by minimizing the so-called MinMaxCut cost function, while in the second problem, we partitioned a structured graph by minimizing the so-called Modified-MinMaxCut cost function. The structural property of the graph is incorporated in defining this new cost function. The solutions we proposed are under the framework of spectral clustering, where one relies on the eigenvectors of the graph matrices, e.g., the Laplacian matrix or the adjacency matrix, and any clustering algorithm, e.g., K-means, to partition nodes into disjoint clusters.Furthermore, for the time-variant graph, we decomposed the problem into two steps. First, we transformed the variations in the graph topology into perturbations to the graph matrices. Then we transformed the update of the clusters into an update of the (generalized) eigenvectors of these graph matrices. We utilized matrix perturbation theory to update the generalized eigenvectors and then update the clusters. Our simulations showed that on synthetic data, the proposed method can efficiently track the eigenvectors and the clusters generated by the updated eigenvectors have almost the same cost function value as that of exact computation.Electrical Engineering | Wireless Communication and Sensin
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