Zhong Chen

Bio: Zhong Chen is an academic researcher from Nanyang Technological University. The author has contributed to research in topics: Medicine & Chemistry. The author has an hindex of 80, co-authored 1000 publications receiving 28171 citations. Previous affiliations of Zhong Chen include Institute of High Performance Computing Singapore & National Institute of Education.

Amplitude Estimation and Source Separation for Harmonics Within Two Mixtures Based on a Min-Rank Criterion

Abstract: Exponentially decaying sinusoidal signal model is generally applied in a wide range of engineering and research fields. In order to analyze the signal components quantitatively, we need to extract the important parameters, i.e., amplitudes, frequencies, and damping factors, from the signals. In some practical applications, we can obtain multiple signals from multiple sensors or with multiple procedures. In such a way, the acquired signals are composed of similar sources or components but with different intensities. How to separate different sources and estimate the intensities of each source within the signals is essential for further analysis. In this paper, we separated different sources within two mixtures by estimating the relative intensities of the sources within mixtures. First, to evaluate a “clean” separation result, we proposed a minimum rank criterion, i.e., the Hankel matrices of the isolated sources should have the minimum rank, which corresponds to a simplified signal composition. Second, in order to minimize the rank of the Hankel matrices, we reformulated the objective function as a generalized eigenvalue decomposition problem, which can be solved based on the minimum perturbation theory. By this method, we can detect the number and intensities of common harmonic components within two mixtures, and isolate two complicated source signals with highly overlapped spectra from the mixtures. The proposed method can be applied for signal simplification or component quantification in a wide range of areas, such as biomedical or electrical engineering, where the signals are usually modeled as a sum of sinusoidal components.

Observation of intermolecular double-quantum coherence signal dips in nuclear magnetic resonance

Abstract: National Natural Science Foundation of China [10875101, 11074209]; Research Fund for the Doctoral Program of Higher Education of China [20090121110030]

Single-Scan High-Resolution 2-D $J$ -Resolved Spectroscopy in Inhomogeneous Magnetic Fields

Abstract: Objective: A method is proposed to obtain high-resolution 2-D $J$ -resolved nuclear magnetic resonance (NMR) spectra in inhomogeneous magnetic fields. Methods: The proposed experiment enables the acquisition of an entire 2-D spectrum in a single scan by utilizing intermolecular double-quantum coherences and the spatial encoding of NMR observables. Results: Chemical shifts, $J$ coupling constants, and multiplet patterns are recovered even when field inhomogeneities are severe enough to completely obscure conventional NMR spectra. After intentional deshimming to yield inhomogeneous magnetic fields, the method was demonstrated on ethyl 3-bromoproprionate in acetone and on a complex mixture of organic compounds. To illustrate the technique's applicability to biological samples with intrinsic magnetic field inhomogeneities arising from macroscopic magnetic susceptibility variations, we performed the experiment on a pig bone marrow sample. Conclusion: Our results show that the new method is a fast and effective tool for studying complex chemical mixtures and biological tissues. Significance: The method could potentially be useful for real-time in vivo NMR studies.

I and i

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

Fast parallel algorithms for short-range molecular dynamics

Abstract: Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Principles of Neural Science

Abstract: I have developed "tennis elbow" from lugging this book around the past four weeks, but it is worth the pain, the effort, and the aspirin. It is also worth the (relatively speaking) bargain price. Including appendixes, this book contains 894 pages of text. The entire panorama of the neural sciences is surveyed and examined, and it is comprehensive in its scope, from genomes to social behaviors. The editors explicitly state that the book is designed as "an introductory text for students of biology, behavior, and medicine," but it is hard to imagine any audience, interested in any fragment of neuroscience at any level of sophistication, that would not enjoy this book. The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or

Graphitic Carbon Nitride (g-C3N4)-Based Photocatalysts for Artificial Photosynthesis and Environmental Remediation: Are We a Step Closer To Achieving Sustainability?

Abstract: As a fascinating conjugated polymer, graphitic carbon nitride (g-C3N4) has become a new research hotspot and drawn broad interdisciplinary attention as a metal-free and visible-light-responsive photocatalyst in the arena of solar energy conversion and environmental remediation. This is due to its appealing electronic band structure, high physicochemical stability, and “earth-abundant” nature. This critical review summarizes a panorama of the latest progress related to the design and construction of pristine g-C3N4 and g-C3N4-based nanocomposites, including (1) nanoarchitecture design of bare g-C3N4, such as hard and soft templating approaches, supramolecular preorganization assembly, exfoliation, and template-free synthesis routes, (2) functionalization of g-C3N4 at an atomic level (elemental doping) and molecular level (copolymerization), and (3) modification of g-C3N4 with well-matched energy levels of another semiconductor or a metal as a cocatalyst to form heterojunction nanostructures. The constructi...