Transport parameters in neutron stars from in-medium N N cross sections

We present a numerical study of shear viscosity and thermal conductivity of symmetric nuclear matter, pure neutron matter, and beta-stable nuclear matter, in the framework of the Brueckner theory. The calculation of in-medium cross sections and nucleon effective masses is performed with a consistent two- and three-body interaction. The investigation covers a wide baryon density range as needed in the applications to neutron stars. The results for the transport coefficients in beta-stable nuclear matter are used to make preliminary predictions on the damping time scales of nonradial modes in neutron stars.

Emittance estimation by an ion optical element with variable focusing strength and a viewing target

The emittance of an extracted ion beam can be estimated to first order by a series of three linear independent profile measurements. This estimation is restricted to the evaluation of an upper limit of the emittance value for a homogeneous, nonfilamented beam. The beam is assumed to be round, respectively elliptical, without any structure of the intensity distribution, no space charge has been assumed for the drifting beam, and the optics is assumed to be linear. Instead of using three different drift sections, a linear focusing element with three different focusing strengths can be used. Plotting the beam radius as function of focusing strength, three independent solutions can be used to calculate the Twiss parameters alpha, beta, and gamma and furthermore the emittance epsilon. Here we describe the measurements which have been performed with the SECRAL ion source at Institute of Modern Physics Lanzhou.

Supervised Gaussian Process Latent Variable Model for Dimensionality Reduction

The Gaussian process latent variable model (GP-LVM) has been identified to be an effective probabilistic approach for dimensionality reduction because it can obtain a low-dimensional manifold of a data set in an unsupervised fashion. Consequently, the GP-LVM is insufficient for supervised learning tasks (e. g., classification and regression) because it ignores the class label information for dimensionality reduction. In this paper, a supervised GP-LVM is developed for supervised learning tasks, and the maximum a posteriori algorithm is introduced to estimate positions of all samples in the latent variable space. We present experimental evidences suggesting that the supervised GP-LVM is able to use the class label information effectively, and thus, it outperforms the GP-LVM and the discriminative extension of the GP-LVM consistently. The comparison with some supervised classification methods, such as Gaussian process classification and support vector machines, is also given to illustrate the advantage of the proposed method.

Comparison of different methods for variable selection

In chemistry for chemical analysis of a multi-component sample or quantitative structure-activity/property relationship (QSAR/QSPR) studies, variable selection is a key step. In this study, comparisons between different methods were performed. These methods include three classical methods such as forward selection, backward elimination and stepwise regression; orthogonal descriptors; leaps-and-bounds regression and genetic algorithm. Thirty-five nitrobenzenes were taken as the data set. From these structures quantum chemical parameters, topological indices and indicator variable were extracted as the descriptors for the comparisons of variable selections. The interesting results have been obtained. (C) 2001 Elsevier Science B.V. All rights reserved.

Variable selection by orthogonal descriptors and prediction of R-f value of phenol and aniline derivatives

Orthogonal descriptors is a viable method for variable selection, but this method strongly depend on the orthogonalisation ordering of the descriptors. In this paper, we compared the different methods used for order the descriptors. It showed that better results could be achieved with the use of backward elimination ordering. We predicted R-f value of phenol and aniline derivatives by this method, and compared it with classical algorithms such as forward selection, backward elimination, and stepwise procedure. Some interesting hints were obtained.

Tip-induced dynamic characterization of multilayers and variable morphologies of cytochrome c molecules on highly oriented pyrolytic graphite revealed by in-situ scanning tunnelling microscopy

The dynamic states of cytochrome c multilayers on electrochemically pretreated highly oriented pyrolytic graphite (HOPG) have been studied by in-situ scanning tunnelling microscopy (STM) under potential control of both the tip and the substrate in cytochrome c and phosphate buffer solution. The dynamic characterization of cytochrome c multilayers and relatively stable adsorbed single cytochrome c molecules scattered on HOPG imply that physically adsorbed multilayers were more easily influenced by the STM tip than those of chemically adsorbed single molecules. In-situ STM images of chemically adsorbed cytochrome c molecules with discernible internal structures on HOPG revealed that morphologies of cytochrome c molecules also suffered tip influence; possible tip-sample-substrate interactions have been discussed.

SYNTHESIS AND VARIABLE-TEMPERATURE FTIR STUDY OF 5 CHIRAL LIQUID-CRYSTALS INDUCED BY INTERMOLECULAR HYDROGEN-BONDING

Five new chiral liquid crystal systems induced by intermolecular hydrogen bonding between 4-[(S)-2-chloro-3-methyl]butyroyloxy-4'-stilbazole (MBSB, proton acceptor) and 4-alkoxybenzoic acids (nBA, proton donors) were prepared. Their liquid crystalline properties were investigated by DSC and polarized optical microscopy. Chiral nematic and chiral smectic phases were observed, and the thermal stability of one complex was studied through temperature dependent infrared spectroscopy.

An extended variable-grid global ocean circulation model and its preliminary results of the equatorial Pacific circulation

To investigate the interaction between the tropical Pacific and China seas a variable-grid global ocean circulation model with fine grid[(1/6)degrees] covering the area from 20degreesS to 50degreesN and from 99degrees to 150degreesE is developed. Numerical computation of the annually cyclic circulation fields is performed. The results of the annual mean zonal currents and deep to abyssal western boundary currents in the equatorial Pacific Ocean are reported. The North Equatorial Current,the North Equatorial Countercurrent, the South Equatorial Current and the Equatorial Undercurrent are fairly well simulated. The model well reproduces the northward flowing abyssal western boundary current. From the model results a lower deep western boundary current east of the Bismarck-Solomon-New Hebrides Island chain at depths around 2 000 in has been found. The model results also show that the currents in the equatorial Pacific Ocean have multi-layer structures both in zonal currents and western boundary currents, indicating that the global ocean overturning thermohaline circulation appears of multi-layer pattern.

Interbasin freshwater, heat and salt transport through the boundaries of the East and South China Seas from a variable-grid global ocean circulation model

The monthly and annual mean freshwater, heat and salt transport through the open boundaries of the South and East China Seas derived from a variable-grid global ocean circulation model is reported. The model has 1/6degrees resolution for the seas adjacent to China and 30 resolution for the global ocean. The model results are in fairly good agreement with the existing estimates based on measurements. The computation shows that the flows passing through the South China Sea contribute volume, heat and salt transport of 5.3 Sv, 0.57 PW and 184 Ggs(-1), respectively (about 1/4) to the Indonesian Throughflow, indicating that the South China Sea is an important pathway of the Pacific to Indian Ocean throughflow. The volume, heat and salt transport of the Kuroshio in the East China Sea is 25.6 Sv, 2.32 PW and 894 Ggs(-1), respectively. Less than 1/4 of this transport passes through the passage between Iriomote and Okinawa. The calculation of heat balance indicates that the South China Sea absorbs net heat flux from the sun and atmosphere with a rate of 0.08 PW, while the atmosphere gains net heat flux from the Baohai, Yellow and East China Seas with a rate of 0.05 PW.

Sea surface height and transport stream function of the South China Sea from a variable-grid global ocean circulation model

A fine-grid model (1/6degrees) covering the South China Sea (SCS), East China Sea and Japan/East Sea, which is embedded into a coarse-grid (3degrees) global model, was established to study the SCS circulation. In the present paper, we report the model-produced monthly and annual mean transport stream functions and sea surface heights(SSH) and their anomalies of the SCS. Comparison to the TOPEX/Poseidon data shows that the model-produced monthly sea surface height anomalies (SSHA) are in good agreement with altimeter measurements. Based on the results, the circulation of the SCS, especially the upper layer circulation, is discussed. In the surface layer, the western Philippine Sea water intrudes into the SCS through the Luzon Strait in autumn, winter and spring, but not in summer. However, as far as the whole water column is concerned, the water intrudes into the SCS through the Luzon Strait all the year round. This indicates that in summer the water still intrudes into the SCS in the subsurface and intermediate layers. The area near the northern continental slope of the SCS is dominated by a cyclonic circulation all the year round. The SCS Southern Anticyclonic Gyre, SE Vietnam Off-Shore Current in summertime and SCS Southern Cyclonic Gyre in wintertime are reproduced reasonably. The difference between the monthly averaged SSH and SSHA is significant, indicating the importance of the mean SSH in the SCS circulation.

On the Emergence of Highly Variable Distributions in the Autonomous System Topology

Recent studies have noted that vertex degree in the autonomous system (AS) graph exhibits a highly variable distribution [15, 22]. The most prominent explanatory model for this phenomenon is the Barabási-Albert (B-A) model [5, 2]. A central feature of the B-A model is preferential connectivity—meaning that the likelihood a new node in a growing graph will connect to an existing node is proportional to the existing node’s degree. In this paper we ask whether a more general explanation than the B-A model, and absent the assumption of preferential connectivity, is consistent with empirical data. We are motivated by two observations: first, AS degree and AS size are highly correlated [11]; and second, highly variable AS size can arise simply through exponential growth. We construct a model incorporating exponential growth in the size of the Internet, and in the number of ASes. We then show via analysis that such a model yields a size distribution exhibiting a power-law tail. In such a model, if an AS’s link formation is roughly proportional to its size, then AS degree will also show high variability. We instantiate such a model with empirically derived estimates of growth rates and show that the resulting degree distribution is in good agreement with that of real AS graphs.

Detecting Instances of Shape Classes That Exhibit Variable Structure

This paper proposes a method for detecting shapes of variable structure in images with clutter. The term "variable structure" means that some shape parts can be repeated an arbitrary number of times, some parts can be optional, and some parts can have several alternative appearances. The particular variation of the shape structure that occurs in a given image is not known a priori. Existing computer vision methods, including deformable model methods, were not designed to detect shapes of variable structure; they may only be used to detect shapes that can be decomposed into a fixed, a priori known, number of parts. The proposed method can handle both variations in shape structure and variations in the appearance of individual shape parts. A new class of shape models is introduced, called Hidden State Shape Models, that can naturally represent shapes of variable structure. A detection algorithm is described that finds instances of such shapes in images with large amounts of clutter by finding globally optimal correspondences between image features and shape models. Experiments with real images demonstrate that our method can localize plant branches that consist of an a priori unknown number of leaves and can detect hands more accurately than a hand detector based on the chamfer distance.

Searching the Sky with CONFIGR-STARS

SyNAPSE program of the Defense Advanced Projects Research Agency (HRL Laboratories LLC, subcontract #801881-BS under DARPA prime contract HR0011-09-C-0001); CELEST, a National Science Foundation Science of Learning Center (SBE-0354378)

Variable Rate Working Memories for Phonetic Categorization and Invariant Speech Perception

Speech can be understood at widely varying production rates. A working memory is described for short-term storage of temporal lists of input items. The working memory is a cooperative-competitive neural network that automatically adjusts its integration rate, or gain, to generate a short-term memory code for a list that is independent of item presentation rate. Such an invariant working memory model is used to simulate data of Repp (1980) concerning the changes of phonetic category boundaries as a function of their presentation rate. Thus the variability of categorical boundaries can be traced to the temporal in variance of the working memory code.