Hierarchical mapping of Northern Eurasian land cover using MODIS data

The Northern Eurasian land mass encompasses a diverse array of land cover types including tundra, boreal forest, wetlands, semi-arid steppe, and agricultural land use. Despite the well-established importance of Northern Eurasia in the global carbon and climate system, the distribution and properties of land cover in this region are not well characterized. To address this knowledge and data gap, a hierarchical mapping approach was developed that encompasses the study area for the Northern Eurasia Earth System Partnership Initiative (NEESPI). The Northern Eurasia Land Cover (NELC) database developed in this study follows the FAO-Land Cover Classification System and provides nested groupings of land cover characteristics, with separate layers for land use, wetlands, and tundra. The database implementation is substantially different from other large-scale land cover datasets that provide maps based on a single set of discrete classes. By providing a database consisting of nested maps and complementary layers, the NELC database provides a flexible framework that allows users to tailor maps to suit their needs. The methods used to create the database combine empirically derived climate–vegetation relationships with results from supervised classifications based on Moderate Resolution Imaging Spectroradiometer (MODIS) data. The hierarchical approach provides an effective framework for integrating climate–vegetation relationships with remote sensing-based classifications, and also allows sources of error to be characterized and attributed to specific levels in the hierarchy. The cross-validated accuracy was 73% for the land cover map and 73% and 91% for the agriculture and wetland classifications, respectively. These results support the use of hierarchical classification and climate–vegetation relationships for mapping land cover at continental scales.     

Robust Control Using Interval Analysis

The synthesis procedure of a control law that guarantees properties of robust stability with respect to structured parameter perturbations is proposed. The solution of the considered problem is based on the Razumikhin's method for functional differential equations generalized for parameter perturbation systems with time delay. The extension is obtained by using interval Lyapunov functions. The robust control law is represented through a solution of an interval matrix Riccati type equation.     

Suboptimal filter for continuous‐time linear systems with unknown parameters

The filtering problem for continuous‐time linear systems with unknown parameters is considered. A new suboptimal filter is herein proposed. It is based on the optimal mean‐square linear combination of the local Kalman filters. In contrast to the optimal weights, the suboptimal weights do not depend on current observations; thus, the proposed filter can easily be implemented in real‐time. Examples demonstrate high accuracy and efficiency of the suboptimal filter. Copyright © 2008 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Proteomic expression profiling of thyroid neoplasms

Thyroid cancer is the most common endocrine neoplasm with multiple histologic subtypes, each associated with different treatments and outcomes. Differentiating benign neoplasms such as follicular adenomas from malignant entities such as follicular carcinomas and papillary carcinoma can be challenging. To define the proteomic profile of different thyroid tumors, we screened an antibody array of 330 features against five thyroid neoplasms: follicular adenoma, follicular carcinoma, papillary carcinoma, anaplastic carcinoma, and medullary carcinoma as well as normal thyroid epithelium. Eight candidate biomarkers; c-erbB-2, Stat5a, Annexin IV, IL-11, RARα, FGF7, Caspase 9, and phospho-c-myc were identified as differentially expressed on the antibody array, and validated with immunohistochemistry on tissue microarrays, with a total of 144 samples of the same variety of thyroid neoplasms. Analysis revealed c-erbB-2, Annexin IV, and Stat5a have potential clinical utility to differentiate follicular adenoma, follicular carcinoma, and papillary carcinoma from each other. By using an antibody array as a discovery platform and a tissue microarray as a first step in validation on a large number of specimens, we have identified new markers that have potential utility in the diagnosis of thyroid neoplasms.     

Probabilistic fusion of stereo with color and contrast for bilayer segmentation

This paper describes models and algorithms for the real-time segmentation of foreground from background layers in stereo video sequences. Automatic separation of layers from color/contrast or from stereo alone is known to be error-prone. Here, color, contrast, and stereo matching information are fused to infer layers accurately and efficiently. The first algorithm, layered dynamic programming (LDP), solves stereo in an extended six-state space that represents both foreground/background layers and occluded regions. The stereo-match likelihood is then fused with a contrast-sensitive color model that is learned on-the-fly and stereo disparities are obtained by dynamic programming. The second algorithm, layered graph cut (LGC), does not directly solve stereo. Instead, the stereo match likelihood is marginalized over disparities to evaluate foreground and background hypotheses and then fused with a contrast-sensitive color model like the one used in LDP. Segmentation is solved efficiently by ternary graph cut. Both algorithms are evaluated with respect to ground truth data and found to have similar performance, substantially better than either stereo or color/contrast alone. However, their characteristics with respect to computational efficiency are rather different. The algorithms are demonstrated in the application of background substitution and shown to give good quality composite video output.     

Simple Algorithm for Partial Quantum Search

Quite often in database search, we only need to extract portion of the information about the satisfying item. We consider this problem in the following form: the database of N items is separated into K blocks of size b = N / K elements each and an algorithm has just to find the block containing the item of interest. The queries are exactly the same as in the standard database search problem. We present a quantum algorithm for this problem of partial search that takes about 0.34 fewer iterations than the quantum search algorithm.     

Ion-cyclotron resonance study of elementary stages of the catalytic oxidation of CO by N2O in the presence of VIA-group metal ions

Gas phase reactions of Mo⁺ and W⁺ ions with the molecules of various oxidants (NO, O₂, N₂O, CH₂O, C₂H₄O) were studied using ion cyclotron resonance. In oxidation with N₂O the mono-, di- and trioxide metal cations are formed consecutively. The trioxide MO₃ ⁺ ions of both metals react with CO to form CO₂ and MO₂ ⁺ ions. In this way, catalytic reaction N₂O + CO N₂ + CO₂ occurs in the gas phase with MoO₃ ⁺ /MoO₂ ⁺ and WO₃ ⁺/WO₂ ⁺ couples as catalysts. The rate constants have been measured for both stages of the catalytic cycle as well as for the stages of the catalyst preparation. Metal-oxygen bond energies were estimated for MoO_x ⁺ and WO_x ⁺ species with various x. The mechanism of CO oxidation with MoO_x ⁺ and WO_x ⁺ cations as catalysts in the gas phase is discussed in comparison with that for the oxidation over classical solid oxide catalysts.     

Water productivity and water footprint: misguided concepts or useful tools in water management and policy?

Water productivity (WP) and water footprint (WFP) are popular concepts in research and discourses on water management. Yet there are concerns about their theoretical validity and practical value. This paper shows that the water production function, the concept with a sound theoretical foundation, is the basis for WP. Total WFP is the reciprocal of WP. The practical value of WP and WFP depends on the context of water use and stress. Maximizing WP, not a panacea to all water problems, mainly suits arid rainfed areas. In other regions, economic and marginal WP for increasing overall production should take precedence in water management and policy decisions.     

Probabilistic resource allocation in heterogeneous distributed systems with random failures

The problem of finding efficient workload distribution techniques is becoming increasingly important today for heterogeneous distributed systems where the availability of compute nodes may change spontaneously over time. Resource-allocation policies designed for such systems should maximize the performance and, at the same time, be robust against failure and recovery of compute nodes. Such a policy, based on the concepts of the Derman–Lieberman–Ross theorem, is proposed in this work, and is applied to a simulated model of a dedicated system composed of a set of heterogeneous image processing servers. Assuming that each image results in a “reward” if its processing is completed before a certain deadline, the goal for the resource allocation policy is to maximize the expected cumulative reward. An extensive analysis was done to study the performance of the proposed policy and compare it with the performance of some existing policies adapted to this environment. Our experiments conducted for various types of task-machine heterogeneity illustrate the potential of our method for solving resource allocation problems in a broad spectrum of distributed systems that experience high failure rates.