Edge-sharing bioctahedral diruthenium(III) complexes containing methoxy and carboxylate bridges:x-ray structures, redox behavior, and core stability

Edge-sharing bioctahedral (ESBO) complexes [Ru-2(OMe)(O2CC6H4-p-X)3(1-MeIm)(4)](ClO4)2 (X = OMe (1a), Me (1b)) and [Ru-2(O2CC6H4-P-X)(4)(1-MeIm)(4)](ClO4)(2) (X = OMe (2a), Me (2b)) are prepared by reacting Ru2Cl(O(2)CR)(4) with 1-methylimidazole (1-MeIm) in methanol followed by treatment with NaClO4. Complex 2a and the PF6- salt (1a') of 1a have been structurally characterized. Crystal data for 1a.1.5MeCN. 0.5Et(2)O: triclinic, P (1) over bar, a = 13.125(2) Angstrom, b = 15.529(3) Angstrom, c 17.314(5) Angstrom, a; 67.03(2)degrees, beta 68.05(2)degrees, gamma = 81.38(1)degrees, V 3014(1) Angstrom(3), Z = 2. Crystal data for 2a: triclinic, P (1) over bar, a 8.950(1) Angstrom, b = 12.089(3) Angstrom, c = 13.735(3) Angstrom, alpha 81.09(2)degrees, beta = 72.27(1)degrees, gamma = 83.15(2)degrees, V = 1394(1) Angstrom(3), Z = 1. The complexes consist of a diruthenium(III) unit held by two monoatomic and two three-atom bridging ligands. The 1-MeIm ligands are at the terminal sites of the [Ru-2(mu-L)(eta(1):mu-O(2)CR)(eta(1):eta(1):mu-O(2)CR)(2)](2+) core having a Ru-Ru single bond (L = OMe or eta(1)-O(2)CR). The Ru-Ru distance and the Ru-O-Ru angle in the core of 1a' and 2a are 2.49 Angstrom and similar to 76 degrees. The complexes undergo one-electron oxidation and reduction processes in MeCN-0.1 M TBAP to form mixed-valence diruthenium species with Ru-Ru bonds of orders 1.5 and 0.5, respectively.

Chance constrained uncertain classification via robust optimization

This paper studies the problem of constructing robust classifiers when the training is plagued with uncertainty. The problem is posed as a Chance-Constrained Program (CCP) which ensures that the uncertain data points are classified correctly with high probability. Unfortunately such a CCP turns out to be intractable. The key novelty is in employing Bernstein bounding schemes to relax the CCP as a convex second order cone program whose solution is guaranteed to satisfy the probabilistic constraint. Prior to this work, only the Chebyshev based relaxations were exploited in learning algorithms. Bernstein bounds employ richer partial information and hence can be far less conservative than Chebyshev bounds. Due to this efficient modeling of uncertainty, the resulting classifiers achieve higher classification margins and hence better generalization. Methodologies for classifying uncertain test data points and error measures for evaluating classifiers robust to uncertain data are discussed. Experimental results on synthetic and real-world datasets show that the proposed classifiers are better equipped to handle data uncertainty and outperform state-of-the-art in many cases.

Combining Bayes Classification and Point Group Symmetry under Boolean Framework for Enhanced Protein Quaternary Structure Inference

Our ability to infer the protein quaternary structure automatically from atom and lattice information is inadequate, especially for weak complexes, and heteromeric quaternary structures. Several approaches exist, but they have limited performance. Here, we present a new scheme to infer protein quaternary structure from lattice and protein information, with all-around coverage for strong, weak and very weak affinity homomeric and heteromeric complexes. The scheme combines naive Bayes classifier and point group symmetry under Boolean framework to detect quaternary structures in crystal lattice. It consistently produces >= 90% coverage across diverse benchmarking data sets, including a notably superior 95% coverage for recognition heteromeric complexes, compared with 53% on the same data set by current state-of-the-art method. The detailed study of a limited number of prediction-failed cases offers interesting insights into the intriguing nature of protein contacts in lattice. The findings have implications for accurate inference of quaternary states of proteins, especially weak affinity complexes.

Two-mode quantum systems: Invariant classification of squeezing transformations and squeezed states

A general analysis of squeezing transformations for two-mode systems is given based on the four-dimensional real symplectic group Sp(4, R). Within the framework of the unitary (metaplectic) representation of this group, a distinction between compact photon-number-conserving and noncompact photon-number-nonconserving squeezing transformations is made. We exploit the U(2) invariant squeezing criterion to divide the set of all squeezing transformations into a two-parameter family of distinct equivalence classes with representative elements chosen for each class. Familiar two-mode squeezing transformations in the literature are recognized in our framework and seen to form a set of measure zero. Examples of squeezed coherent and thermal states are worked out. The need to extend the heterodyne detection scheme to encompass all of U(2) is emphasized, and known experimental situations where all U(2) elements can be reproduced are briefly described.

Theoretical analysis of x-ray-absorption near-edge fine structure at the O and metal K edges of LaFeO3 and LaCoO3

We present experimental x-ray-absorption spectra at the oxygen and 3d transition-metal K edges of LaFeO3 and LaCoO3. We interpret the experimental results in terms of detailed theoretical calculations based on multiple-scattering theory. Along with providing an understanding of the origin of various experimental features, we investigate the effects of structural distortions and the core-hole potential in determining the experimental spectral shape. The results indicate that the core-hole potential as well as many-body effects within the valence electrons do not have any strong effect on the spectra suggesting that the spectral features can be directly interpreted in terms of the electronic structure of such compounds.

Classification of microwatersheds based on morphological characteristics

Three classification techniques, namely, K-means Cluster Analysis (KCA), Fuzzy Cluster Analysis (FCA), and Kohonen Neural Networks (KNN) were employed to group 25 microwatersheds of Kherthal watershed, Rajasthan into homogeneous groups for formulating the basis for suitable conservation and management practices. Ten parameters, mainly, morphological, namely, drainage density (D-d), bifurcation ratio (R-b), stream frequency (F-u), length of overland flow (L-o), form factor (R-f), shape factor (B-s), elongation ratio (R-e), circulatory ratio (R-c), compactness coefficient (C-c) and texture ratio (T) are used for the classification. Optimal number of groups is chosen, based on two cluster validation indices Davies-Bouldin and Dunn's. Comparative analysis of various clustering techniques revealed that 13 microwatersheds out of 25 are commonly suggested by KCA, FCA and KNN i.e., 52%; 17 microwatersheds out of 25 i.e., 68% are commonly suggested by KCA and FCA whereas these are 16 out of 25 in FCA and KNN (64%) and 15 out of 25 in KNN and CA (60%). It is observed from KNN sensitivity analysis that effect of various number of epochs (1000, 3000, 5000) and learning rates (0.01, 0.1-0.9) on total squared error values is significant even though no fixed trend is observed. Sensitivity analysis studies revealed that microwatershecls have occupied all the groups even though their number in each group is different in case of further increase in the number of groups from 5 to 6, 7 and 8. (C) 2010 International Association of Hydro-environment Engineering and Research, Asia Pacific Division. Published by Elsevier B.V. All rights reserved.

Nonresonant edge slot antenna for phased array applications: Theory and experiment

The design and development of nonresonant edge slot antenna for phased array applications has been presented. The radiating element is a slot cut on the narrow wall of rectangular waveguide (edge slot). The admittance characteristics of the edge slot have been rigorously studied using a novel hybrid method. Nonresonant arrays have been fabricated using the present slot characterization data and the earlier published data. The experimentally measured electrical characteristics of the antenna are presented which clearly brings out the accuracy of the present method.

Video coding mode decision as a classification problem

In this paper, we show that it is possible to reduce the complexity of Intra MB coding in H.264/AVC based on a novel chance constrained classifier. Using the pairs of simple mean-variances values, our technique is able to reduce the complexity of Intra MB coding process with a negligible loss in PSNR. We present an alternate approach to address the classification problem which is equivalent to machine learning. Implementation results show that the proposed method reduces encoding time to about 20% of the reference implementation with average loss of 0.05 dB in PSNR.

Acyclic Edge-Coloring of Planar Graphs

A proper edge-coloring with the property that every cycle contains edges of at least three distinct colors is called an acyclic edge-coloring. The acyclic chromatic index of a graph G, denoted. chi'(alpha)(G), is the minimum k such that G admits an acyclic edge-coloring with k colors. We conjecture that if G is planar and Delta(G) is large enough, then chi'(alpha) (G) = Delta (G). We settle this conjecture for planar graphs with girth at least 5. We also show that chi'(alpha) (G) <= Delta (G) + 12 for all planar G, which improves a previous result by Fiedorowicz, Haluszczak, and Narayan Inform. Process. Lett., 108 (2008), pp. 412-417].

Anomalous Temperature dependence of Fermi-edge Singularity in Modulation-doped AlGaAs/InGaAs/GaAs hetero-structures

The temperature and power dependence of Fermi-edge singularity (FES) in high-density two-dimensional electron gas, specific to pseudomorphic AlxGa1-xAs/InyGa1-yAs/GaAs heterostructures is studied by photoluminescence (PL). In all these structures, there are two prominent transitions E11 and E21 considered to be the result of electron-hole recombination from first and second electron sub-bands with that of first heavy-hole sub-band. FES is observed approximately 5 -10 meV below the E21 transition. At 4.2 K, FES appears as a lower energy shoulder to the E21 transition. The PL intensity of all the three transitions E11, FES and E21 grows linearly with excitation power. However, we observe anomalous behavior of FES with temperature. While PL intensity of E11 and E21 decrease with increasing temperature, FES transition becomes stronger initially and then quenches-off slowly (till 40K). Though it appears as a distinct peak at about 20 K, its maximum is around 7 - 13 K.

Solving a part classification problem using simulated annealing-like hybrid

Part classification and coding is still considered as laborious and time-consuming exercise. Keeping in view, the crucial role, which it plays, in developing automated CAPP systems, the attempts have been made in this article to automate a few elements of this exercise using a shape analysis model. In this study, a 24-vector directional template is contemplated to represent the feature elements of the parts (candidate and prototype). Various transformation processes such as deformation, straightening, bypassing, insertion and deletion are embedded in the proposed simulated annealing (SA)-like hybrid algorithm to match the candidate part with their prototype. For a candidate part, searching its matching prototype from the information data is computationally expensive and requires large search space. However, the proposed SA-like hybrid algorithm for solving the part classification problem considerably minimizes the search space and ensures early convergence of the solution. The application of the proposed approach is illustrated by an example part. The proposed approach is applied for the classification of 100 candidate parts and their prototypes to demonstrate the effectiveness of the algorithm. (C) 2003 Elsevier Science Ltd. All rights reserved.

Fast edge splitting and Edmonds' arborescence construction for unweighted graphs

Given an unweighted undirected or directed graph with n vertices, m edges and edge connectivity c, we present a new deterministic algorithm for edge splitting. Our algorithm splits-off any specified subset S of vertices satisfying standard conditions (even degree for the undirected case and in-degree ≥ out-degree for the directed case) while maintaining connectivity c for vertices outside S in Õ(m+nc2) time for an undirected graph and Õ(mc) time for a directed graph. This improves the current best deterministic time bounds due to Gabow [8], who splits-off a single vertex in Õ(nc2+m) time for an undirected graph and Õ(mc) time for a directed graph. Further, for appropriate ranges of n, c, |S| it improves the current best randomized bounds due to Benczúr and Karger [2], who split-off a single vertex in an undirected graph in Õ(n2) Monte Carlo time. We give two applications of our edge splitting algorithms. Our first application is a sub-quadratic (in n) algorithm to construct Edmonds' arborescences. A classical result of Edmonds [5] shows that an unweighted directed graph with c edge-disjoint paths from any particular vertex r to every other vertex has exactly c edge-disjoint arborescences rooted at r. For a c edge connected unweighted undirected graph, the same theorem holds on the digraph obtained by replacing each undirected edge by two directed edges, one in each direction. The current fastest construction of these arborescences by Gabow [7] takes Õ(n2c2) time. Our algorithm takes Õ(nc3+m) time for the undirected case and Õ(nc4+mc) time for the directed case. The second application of our splitting algorithm is a new Steiner edge connectivity algorithm for undirected graphs which matches the best known bound of Õ(nc2 + m) time due to Bhalgat et al [3]. Finally, our algorithm can also be viewed as an alternative proof for existential edge splitting theorems due to Lovász [9] and Mader [11].

Soft classification based Sub-pixel allocation model

Land cover (LC) refers to what is actually present on the ground and provide insights into the underlying solution for improving the conditions of many issues, from water pollution to sustainable economic development. One of the greatest challenges of modeling LC changes using remotely sensed (RS) data is of scale-resolution mismatch: that the spatial resolution of detail is less than what is required, and that this sub-pixel level heterogeneity is important but not readily knowable. However, many pixels consist of a mixture of multiple classes. The solution to mixed pixel problem typically centers on soft classification techniques that are used to estimate the proportion of a certain class within each pixel. However, the spatial distribution of these class components within the pixel remains unknown. This study investigates Orthogonal Subspace Projection - an unmixing technique and uses pixel-swapping algorithm for predicting the spatial distribution of LC at sub-pixel resolution. Both the algorithms are applied on many simulated and actual satellite images for validation. The accuracy on the simulated images is ~100%, while IRS LISS-III and MODIS data show accuracy of 76.6% and 73.02% respectively. This demonstrates the relevance of these techniques for applications such as urban-nonurban, forest-nonforest classification studies etc.