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.

Apparent diffusion behaviors of spins in the presence of distant dipolar field in two-component solution NMR

Abstract: NNSF of China[10875101, 11074209]; Research Fund for the Doctoral Program of Higher Education of China[20090121110030]

Process control for the tea baking

Abstract: The tea baking process is usually controlled by experience. It may leads to the instability of product quality. A new process control scheme for tea baking is proposed in this paper. Varied intelligent meters and concentrative controllers are used to construct the control system. A mathematic model is built to simplify the various factors, such as growth zone, breed tea-picking season, baking temperature, surrounding humidity, moisture of tea leaves, and consumer's desire. Furthermore, a novel interface software is designed to make the communication between controller and intelligent meters more agile, stable, and extensible. The proposed controlling scheme has been adopted by tea manufactories, and the result shows that the process control is effective and feasible, and the quality of tea is greatly improved.

High-resolution heteronuclear correlation spectroscopy based on spatial encoding and coherence transfer in inhomogeneous fields

Abstract: Two-dimensional (2D) nuclear magnetic resonance (NMR) spectroscopy has been proven to be a powerful technique for chemical, biological, and medical studies. Heteronuclear single quantum correlation (HSQC) and heteronuclear multiple bond correlation (HMBC) are two frequently used 2D NMR methods. In combination with spatially encoded techniques, a heteronuclear 2D NMR spectrum can be acquired in several seconds and may be applied to monitoring chemical reactions. However, it is difficult to obtain high-resolution NMR spectra in inhomogeneous fields. Inspired by the idea of tracing the difference of precession frequencies between two different spins to yield high-resolution spectra, we propose a method with correlation acquisition option and J-resolved-like acquisition option to ultrafast obtain high-resolution HSQC/HMBC spectra and heteronuclear J-resolved-like spectra in inhomogeneous fields.

Revealing Different Lung Metastatic Potentials Induced Metabolic Alterations of Hepatocellular Carcinoma Cells via Proton Nuclear Magnetic Resonance Spectroscopy.

Abstract: Background: Hepatocellular carcinoma (HCC) causes death mainly by disseminated metastasis progression and major challenge of clinical management is to distinguish lethal metastatic stage from indolent stage. It is shown that metastatic progression is closely related to cellular metabolism. But detailed metabolic alterations and molecular mechanisms still kept unclear between subtypes of different lung metastatic potentials. Methods: The current work used NMR-based metabolomics in the study of HCC cells with high malignancy but differed in lung metastatic potentials. Cell extracts and cultured media from MHCC97L and MHCC97H were utilized to reveal metabolic alterations related to metastatic potentials. Multivariate analyses were performed to identify characteristic metabolites which were used subsequently to draw the map of relative biochemical pathways by combining KEGG database. Results: The NMR spectra of both MHCC97L and MHCC97H include various signals from necessary nutritional components and metabolic intermediates. A series of characteristic metabolites were determined from both cell extracts and media. The ability on nutrient uptake varied from cell lines. Most of amino acids decreased in high metastatic cell line, so altered amino acid metabolisms and energy metabolism were revealed in high metastatic MHCC97H cell line. The majority pathways involved six essential amino acids in which the observed branched-chain amino acids together with lysine contributed to biosynthesis or degradation. Basically MHCC97H cell line could induce more active events than that of MHCC97L to progress to high metastasis with certain molecular events. Characteristic metabolites-derived classifiers performed robustly during prediction and confirmed their critical role in supporting metastasis progression. Conclusions: Our results provide evidence that NMR-metabolomics analyses of cells are able to understand metastatic characteristics accountable for biological properties. The proposed characteristic metabolites will help to understand HCC metastatic characterizations and may be filtered as potential biomarkers.

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...