Dynamics of Overhauser Field under nuclear spin diffusion in a quantum dot

The coherence of electron spin can be significantly enhanced by locking the Overhauser field from nuclear spins using the nuclear spin preparation. We propose a theoretical model to calculate the long time dynamics of the Overhauser field under intrinsic nuclear spin diffusion in a quantum dot. We obtain a simplified diffusion equation that can be numerically solved and show quantitatively how the Knight shift and the electron-mediated nuclear spin flip-flop affect the nuclear spin diffusion. The results explain several recent experimental observations, where the decay time of Overhauser field is measured under different configurations, including variation of the external magnetic field, the electron spin configuration in a double dot, and the initial nuclear spin polarization rate.Comment: 6 pages, 5 figure

A Dispersive Analysis on the f0(600)f_0(600) and f0(980)f_0(980) Resonances in γγ→π+π−,π0π0\gamma\gamma\to\pi^+\pi^-, \pi^0\pi^0 Processes

We estimate the di-photon coupling of $f_0(600)$, $f_0(980)$ and $f_2(1270)$ resonances in a coupled channel dispersive approach. The $f_0(600)$ di-photon coupling is also reinvestigated using a single channel $T$ matrix for $\pi\pi$ scattering with better analyticity property, and it is found to be significantly smaller than that of a $\bar qq$ state. Especially we also estimate the di-photon coupling of the third sheet pole located near $\bar KK$ threshold, denoted as $f_0^{III}(980)$. It is argued that this third sheet pole may be originated from a coupled channel Breit-Wigner description of the $f_0(980)$ resonance.Comment: 24 pages and 13 eps figures. A nuerical bug in previous version is fixed. Some results changed. References and new figures added. Version to appear in Phys. Rev.

Spectroscopic properties and antimicrobial activity of dioxomolybdenum(VI) complexes with heterocyclic S,S’-ligands

Five new dioxomolybdenum(VI) complexes of the general formula[MoO2(Rdtc)2], 1-5, where Rdtc-refer to piperidine- (Pipdtc), 4-morpholine-(Morphdtc), 4-thiomorpholine-(Timdtc), piperazine- (Pzdtc) or Nmethylpiperazine- (N-Mepzdtc) dithiocarbamates, respectively, have been prepared. Elemental analysis, conductometric measurements, electronic, IR and NMR spectroscopy have been employed to characterize them. Complexes 1-5 contain a cis-MoO2 group and are of an octahedral geometry. Two dithiocarbamato ions join as bidentates with both the sulphur atoms to the molybdenum atom. The presence of different heteroatom in the piperidinо moiety influences the v(C----N) and v(C----S) vibrations, which decrease in the order of the complexes with: Pipdtc > N-Mepipdtc > Morphdtc > Pzdtc > Timdtc ligands. On the basis of spectral data, molecular structures of complexes 1-5 were optimized on semiempirical molecular-orbital level, and the geometries, as obtained from calculations, described. Antimicrobial activity was tested against nine different laboratory control strains of bacteria and two strains of yeast Candida albicans. All tested strains were sensitive. Complexes bearing heteroatom in position 4 of piperidine moiety are significantly more potent against bacteria tested comparing to corresponding ligands

Towards the digitalisation of porous energy materials: evolution of digital approaches for microstructural design

Porous energy materials are essential components of many energy devices and systems, the development of which have been long plagued by two main challenges. The first is the ‘curse of dimensionality’, i.e. the complex structure–property relationships of energy materials are largely determined by a high-dimensional parameter space. The second challenge is the low efficiency of optimisation/discovery techniques for new energy materials. Digitalisation of porous energy materials is currently being considered as one of the most promising solutions to tackle these issues by transforming all material information into the digital space using reconstruction and imaging data and fusing this with various computational methods. With the help of material digitalisation, the rapid characterisation, the prediction of properties, and the autonomous optimisation of new energy materials can be achieved by using advanced mathematical algorithms. In this paper, we review the evolution of these computational and digital approaches and their typical applications in studying various porous energy materials and devices. Particularly, we address the recent progress of artificial intelligence (AI) in porous energy materials and highlight the successful application of several deep learning methods in microstructural reconstruction and generation, property prediction, and the performance optimisation of energy materials in service. We also provide a perspective on the potential of deep learning methods in achieving autonomous optimisation and discovery of new porous energy materials based on advanced computational modelling and AI techniques

Coarse grained description of the protein folding

We consider two- and three-dimensional lattice models of proteins which were characterized previously. We coarse grain their folding dynamics by reducing it to transitions between effective states. We consider two methods of selection of the effective states. The first method is based on the steepest descent mapping of states to underlying local energy minima and the other involves an additional projection to maximally compact conformations. Both methods generate connectivity patterns that allow to distinguish between the good and bad folders. Connectivity graphs corresponding to the folding funnel have few loops and are thus tree-like. The Arrhenius law for the median folding time of a 16-monomer sequence is established and the corresponding barrier is related to easily identifiable kinetic trap states.Comment: REVTeX, 9 pages, 15 EPS figures, to appear in Phys. Rev.

Energy landscapes, supergraphs, and "folding funnels" in spin systems

Dynamical connectivity graphs, which describe dynamical transition rates between local energy minima of a system, can be displayed against the background of a disconnectivity graph which represents the energy landscape of the system. The resulting supergraph describes both dynamics and statics of the system in a unified coarse-grained sense. We give examples of the supergraphs for several two dimensional spin and protein-related systems. We demonstrate that disordered ferromagnets have supergraphs akin to those of model proteins whereas spin glasses behave like random sequences of aminoacids which fold badly.Comment: REVTeX, 9 pages, two-column, 13 EPS figures include

Changes in mangrove vegetation area and character in a war and land use change affected region of Vietnam (Mui Ca Mau) over six decades

Aerial photographs and satellite images have been used to determine land cover changes during the period 1953 to 2011 in the Mui Ca Mau, Vietnam, especially in relation to changes in the mangrove area. The mangrove area declined drastically from approximately 71,345 ha in 1953 to 33,083 ha in 1992, then rose to 46,712 ha in 2011. Loss due to herbicide attacks during the Vietnam War, overexploitation, and conversion into agriculture and aquaculture encouraged by land management policies are being partially counteracted by natural regeneration and replanting, especially a gradual increase in plantations as part of integrated mangrove-shrimp farming systems. The nature of the mangrove vegetation has markedly been transformed over this period. The results are valuable for management planning to understand and improve the contribution of mangrove forests to the provision of ecosystem services and resources, local livelihood and global interest

Scaling of folding properties in simple models of proteins

Scaling of folding properties of proteins is studied in a toy system -- the lattice Go model with various two- and three- dimensional geometries of the maximally compact native states. Characteristic folding times grow as power laws with the system size. The corresponding exponents are not universal. Scaling of the thermodynamic stability also indicates size-related deterioration of the folding properties.Comment: REVTeX, 4 pages, 4 EPS figures, PRL (in press

Models for Minimax Stochastic Linear Optimization Problems with Risk Aversion

We propose a semidefinite optimization (SDP) model for the class of minimax two-stage stochastic linear optimization problems with risk aversion. The distribution of second-stage random variables belongs to a set of multivariate distributions with known first and second moments. For the minimax stochastic problem with random objective, we provide a tight SDP formulation. The problem with random right-hand side is NP-hard in general. In a special case, the problem can be solved in polynomial time. Explicit constructions of the worst-case distributions are provided. Applications in a production-transportation problem and a single facility minimax distance problem are provided to demonstrate our approach. In our experiments, the performance of minimax solutions is close to that of data-driven solutions under the multivariate normal distribution and better under extremal distributions. The minimax solutions thus guarantee to hedge against these worst possible distributions and provide a natural distribution to stress test stochastic optimization problems under distributional ambiguity.Singapore-MIT Alliance for Research and TechnologyNational University of Singapore. Dept. of Mathematic