Survival time of random walk in random environment among soft obstacles

We consider a Random Walk in Random Environment (RWRE) moving in an i.i.d. random field of obstacles. When the particle hits an obstacle, it disappears with a positive probability. We obtain quenched and annealed bounds on the tails of the survival time in the general d-dimensional case. We then consider a simplified one-dimensional model (where transition probabilities and obstacles are independent and the RWRE only moves to neighbour sites), and obtain finer results for the tail of the survival time. In addition, we study also the ""mixed"" probability measures (quenched with respect to the obstacles and annealed with respect to the transition probabilities and vice-versa) and give results for tails of the survival time with respect to these probability measures. Further, we apply the same methods to obtain bounds for the tails of hitting times of Branching Random Walks in Random Environment (BRWRE).

Multiclass Hammersley-Aldous-Diaconis process and multiclass-customer queues

In the Hammersley-Aldous-Diaconis process, infinitely many particles sit in R and at most one particle is allowed at each position. A particle at x, whose nearest neighbor to the right is at y, jumps at rate y - x to a position uniformly distributed in the interval (x, y). The basic coupling between trajectories with different initial configuration induces a process with different classes of particles. We show that the invariant measures for the two-class process can be obtained as follows. First, a stationary M/M/1 queue is constructed as a function of two homogeneous Poisson processes, the arrivals with rate, and the (attempted) services with rate rho > lambda Then put first class particles at the instants of departures (effective services) and second class particles at the instants of unused services. The procedure is generalized for the n-class case by using n - 1 queues in tandem with n - 1 priority types of customers. A multi-line process is introduced; it consists of a coupling (different from Liggett's basic coupling), having as invariant measure the product of Poisson processes. The definition of the multi-line process involves the dual points of the space-time Poisson process used in the graphical construction of the reversed process. The coupled process is a transformation of the multi-line process and its invariant measure is the transformation described above of the product measure.

Laser-induced breakdown spectroscopy and chemometrics for classification of toys relying on toxic elements

Quality control of toys for avoiding children exposure to potentially toxic elements is of utmost relevance and it is a common requirement in national and/or international norms for health and safety reasons. Laser-induced breakdown spectroscopy (LIBS) was recently evaluated at authors` laboratory for direct analysis of plastic toys and one of the main difficulties for the determination of Cd. Cr and Pb was the variety of mixtures and types of polymers. As most norms rely on migration (lixiviation) protocols, chemometric classification models from LIBS spectra were tested for sampling toys that present potential risk of Cd, Cr and Pb contamination. The classification models were generated from the emission spectra of 51 polymeric toys and by using Partial Least Squares - Discriminant Analysis (PLS-DA), Soft Independent Modeling of Class Analogy (SIMCA) and K-Nearest Neighbor (KNN). The classification models and validations were carried out with 40 and 11 test samples, respectively. Best results were obtained when KNN was used, with corrected predictions varying from 95% for Cd to 100% for Cr and Pb. (C) 2011 Elsevier B.V. All rights reserved.

Analytical calculation of the transition to complete phase synchronization in coupled oscillators

Here we present a system of coupled phase oscillators with nearest neighbors coupling, which we study for different boundary conditions. We concentrate at the transition to the total synchronization. We are able to develop exact solutions for the value of the coupling parameter when the system becomes completely synchronized, for the case of periodic boundary conditions as well as for a chain with fixed ends. We compare the results with those calculated numerically.

Exploring the emission intensities of ICP OES aided by chemometrics in the geographical discrimination of mineral waters

A rapid method for classification of mineral waters is proposed. The discrimination power was evaluated by a novel combination of chemometric data analysis and qualitative multi-elemental fingerprints of mineral water samples acquired from different regions of the Brazilian territory. The classification of mineral waters was assessed using only the wavelength emission intensities obtained by inductively coupled plasma optical emission spectrometry (ICP OES), monitoring different lines of Al, B, Ba, Ca, Cl, Cu, Co, Cr, Fe, K, Mg, Mn, Na, Ni, P, Pb, S, Sb, Si, Sr, Ti, V, and Zn, and Be, Dy, Gd, In, La, Sc and Y as internal standards. Data acquisition was done under robust (RC) and non-robust (NRC) conditions. Also, the combination of signal intensities of two or more emission lines for each element were evaluated instead of the individual lines. The performance of two classification-k-nearest neighbor (kNN) and soft independent modeling of class analogy (SIMCA)-and preprocessing algorithms, autoscaling and Pareto scaling, were evaluated for the ability to differentiate between the various samples in each approach tested (combination of robust or non-robust conditions with use of individual lines or sum of the intensities of emission lines). It was shown that qualitative ICP OES fingerprinting in combination with multivariate analysis is a promising analytical tool that has potential to become a recognized procedure for rapid authenticity and adulteration testing of mineral water samples or other material whose physicochemical properties (or origin) are directly related to mineral content.

Multilabeled classification approach to find a plaint source for terpenoids

Recently, we have built a classification model that is capable of assigning a given sesquiterpene lactone (STL) into exactly one tribe of the plant family Asteraceae from which the STL has been isolated. Although many plant species are able to biosynthesize a set of peculiar compounds, the occurrence of the same secondary metabolites in more than one tribe of Asteraceae is frequent. Building on our previous work, in this paper, we explore the possibility of assigning an STL to more than one tribe (class) simultaneously. When an object may belong to more than one class simultaneously, it is called multilabeled. In this work, we present a general overview of the techniques available to examine multilabeled data. The problem of evaluating the performance of a multilabeled classifier is discussed. Two particular multilabeled classification methods-cross-training with support vector machines (ct-SVM) and multilabeled k-nearest neighbors (M-L-kNN)were applied to the classification of the STLs into seven tribes from the plant family Asteraceae. The results are compared to a single-label classification and are analyzed from a chemotaxonomic point of view. The multilabeled approach allowed us to (1) model the reality as closely as possible, (2) improve our understanding of the relationship between the secondary metabolite profiles of different Asteraceae tribes, and (3) significantly decrease the number of plant sources to be considered for finding a certain STL. The presented classification models are useful for the targeted collection of plants with the objective of finding plant sources of natural compounds that are biologically active or possess other specific properties of interest.

A chemometric study on the analgesic activity of cannabinoid compounds using SDA, KNN and SIMCA methods

The supervised pattern recognition methods K-Nearest Neighbors (KNN), stepwise discriminant analysis (SDA), and soft independent modelling of class analogy (SIMCA) were employed in this work with the aim to investigate the relationship between the molecular structure of 27 cannabinoid compounds and their analgesic activity. Previous analyses using two unsupervised pattern recognition methods (PCA-principal component analysis and HCA-hierarchical cluster analysis) were performed and five descriptors were selected as the most relevants for the analgesic activity of the compounds studied: R (3) (charge density on substituent at position C(3)), Q (1) (charge on atom C(1)), A (surface area), log P (logarithm of the partition coefficient) and MR (molecular refractivity). The supervised pattern recognition methods (SDA, KNN, and SIMCA) were employed in order to construct a reliable model that can be able to predict the analgesic activity of new cannabinoid compounds and to validate our previous study. The results obtained using the SDA, KNN, and SIMCA methods agree perfectly with our previous model. Comparing the SDA, KNN, and SIMCA results with the PCA and HCA ones we could notice that all multivariate statistical methods classified the cannabinoid compounds studied in three groups exactly in the same way: active, moderately active, and inactive.

XAS characterization of the RuO(2)-Ta(2)O(5) system local (crystal) structure

The influence of the preparation method on the structural properties of the RuO(2)-Ta(2)O(5) system was investigated. Both thin films on Ti substrates and powder samples of nominal composition Ti/RuO(2)-Ta(2)O(5) (Ru:Ta = 100:0, 90:10, 80:20, 30:70, and 0:100 at.%) were prepared through thermal decomposition of polymeric precursors (DPP). The thin films and powder samples were investigated using X-ray absorption spectroscopy (XAS). XANES analyses showed that Ru and Ta are present in the Ru(IV) and Ta(V) oxidation states. EXAFS signals of all the samples were analyzed, to obtain the average bond length (r), coordination number, and the Debye-Waller factor (sigma(2)) for each Ru-O, Ru-Ru, Ta-O nearest-neighbor. The first shell Ru-O distance was found at 1.91-1.92 angstrom with coordination number of 1.8-2.1, and at 2.01-2.02 angstrom with coordination number of 3.9-4.1. The Ta-O distance obtained for all the samples and in both modes (transmission and fluorescence) had significantly different values from the theoretical ones. The results revealed that the local structure around both the Ru and Ta sites are similar, and that they consist of distorted M-O(6) octahedra (where M = Ru or Ta). (C) 2010 Elsevier B.V. All rights reserved.

A decision support system to facilitate management of patients with acute gastrointestinal bleeding

Objective: To develop a model to predict the bleeding source and identify the cohort amongst patients with acute gastrointestinal bleeding (GIB) who require urgent intervention, including endoscopy. Patients with acute GIB, an unpredictable event, are most commonly evaluated and managed by non-gastroenterologists. Rapid and consistently reliable risk stratification of patients with acute GIB for urgent endoscopy may potentially improve outcomes amongst such patients by targeting scarce health-care resources to those who need it the most. Design and methods: Using ICD-9 codes for acute GIB, 189 patients with acute GIB and all. available data variables required to develop and test models were identified from a hospital medical records database. Data on 122 patients was utilized for development of the model and on 67 patients utilized to perform comparative analysis of the models. Clinical data such as presenting signs and symptoms, demographic data, presence of co-morbidities, laboratory data and corresponding endoscopic diagnosis and outcomes were collected. Clinical data and endoscopic diagnosis collected for each patient was utilized to retrospectively ascertain optimal management for each patient. Clinical presentations and corresponding treatment was utilized as training examples. Eight mathematical models including artificial neural network (ANN), support vector machine (SVM), k-nearest neighbor, linear discriminant analysis (LDA), shrunken centroid (SC), random forest (RF), logistic regression, and boosting were trained and tested. The performance of these models was compared using standard statistical analysis and ROC curves. Results: Overall the random forest model best predicted the source, need for resuscitation, and disposition with accuracies of approximately 80% or higher (accuracy for endoscopy was greater than 75%). The area under ROC curve for RF was greater than 0.85, indicating excellent performance by the random forest model Conclusion: While most mathematical models are effective as a decision support system for evaluation and management of patients with acute GIB, in our testing, the RF model consistently demonstrated the best performance. Amongst patients presenting with acute GIB, mathematical models may facilitate the identification of the source of GIB, need for intervention and allow optimization of care and healthcare resource allocation; these however require further validation. (c) 2007 Elsevier B.V. All rights reserved.

The role of convective parameterization in the simulation of a cyclone over the South Atlantic

Numerical simulations are carried out to examine the role of the Kuo and Kain-Fritsch (KF) cumulus parameterization schemes and dry dynamics on a cyclone development, in a weak baroclinic atmosphere, over subtropical South Atlantic Ocean. The initial phase of the cyclone development is investigated with a coarse horizontal mesh (75 km) and when the cyclone reaches the mature stage two different horizontal resolutions are used (75 and 25 km). The best performance simulation for the cyclone initial phase occurs when the Kuo convective scheme is applied, and this may be attributed to a greater diabatic warming in the troposphere. On the other hand, the dry simulation is not capable of simulating the correct location and intensity of the cyclone in its initial phase. During the mature phase, a cyclone over deepening occurs in the Kuo scheme experiment associated with larger latent heat release in a deep vertical column. The presence of downdraft currents in the KF scheme, which acts to cool and dry the lower levels, is essential to stabilize the atmosphere and to reproduce the nearest observation cyclone deepening rate. The largest cyclone deepening is found in the Kuo scheme high resolution experiment. This suggests that the KF convective scheme is less sensitive to the horizontal grid resolution. It was also revealed that the diabatic processes are crucial to simulate the observed features of this marine cyclone over subtropical region.

Nuclear and extended spectra of NGC 1068-II. Near-infrared stellar population synthesis

We performed stellar population synthesis on the nuclear and extended regions of NGC 1068 by means of near-infrared spectroscopy to disentangle their spectral energy distribution components. This is the first time that such a technique is applied to the whole 0.8-2.4 mu m wavelength interval in this galaxy. NGC 1068 is one of the nearest and probably the most studied Seyfert 2 galaxy, becoming an excellent laboratory to study the interaction between black holes, the jets that they can produce and the medium in which they propagate. Our main result is that traces of young stellar population are found at similar to 100 pc south of the nucleus. The contribution of a power-law continuum in the centre is about 25 per cent, which is expected if the light is scattered from a Seyfert 1 nucleus. We find peaks in the contribution of the featureless continuum about 100-150 pc from the nucleus on both sides. They might be associated with regions where the jet encounters dense clouds. Further support to this scenario is given by the peaks of hot dust distribution found around these same regions and the H(2) emission-line profile, leading us to propose that the peaks might be associated to regions where stars are being formed. Hot dust also has an important contribution to the nuclear region, reinforcing the idea of the presence of a dense, circumnuclear torus in this galaxy. Cold dust appears mostly in the south direction, which supports the view that the south-west emission is behind the plane of the galaxy and is extinguished very likely by dust in the plane. Intermediate-age stellar population contributes significantly to the continuum, especially in the inner 200 pc.

Microhabitat Selection of three Forest Understory Birds in the Brazilian Atlantic Rainforest

When assessing fragmentation effects on species, not only habitat preferences on the landscape scale, but also microhabitat selection is an important factor to consider, as microhabitat is also affected by habitat disturbance, but nevertheless essential for species for foraging, nesting and sheltering. In the Atlantic Rainforest of Brazil we examined microhabitat selection of six Pyriglena leucoptera (white-shouldered fire-eye), 10 Sclerurus scansor (rufous-breasted leaftosser), and 30 Chiroxiphia caudata (blue manakin). We radio-tracked the individuals between May 2004 and February 2005 to gain home ranges based on individual fixed kernels. Vegetation structures in core plots and fringe plots were compared. In C. caudata, we additionally assessed the influence of behavioural traits on microhabitat selection. Further, we compared microhabitat structures in the fragmented forest with those in the contiguous, and contrasted the results with the birds` preferences. Pyriglena leucoptera preferred liana tangles that were more common in the fragmented forest, whereas S. scansor preferred woody debris, open forest floor (up to 0.5 m), and a thin closed leaf litter cover which all occurred significantly more often in the contiguous forest. Significant differences were detected in C. caudata for vegetation densities in the different strata; the distance of core plots to the nearest lek site was significantly influenced by sex and age. However, core sites of C. caudata in fragmented and contiguous forests showed no significant differences in structure. Exploring microhabitat selection and behavior may greatly support the understanding of habitat selection of species and their susceptibility to fragmentation on the landscape scale.

Screening for endophytic nitrogen-fixing bacteria in Brazilian sugar cane varieties used in organic farming and description of Stenotrophomonas pavanii sp. nov.

A Gram-negative, rod-shaped, non-spore-forming and nitrogen-fixing bacterium, designated ICB 89(T), was isolated from stems of a Brazilian sugar cane variety widely used in organic farming. 16S rRNA gene sequence analysis revealed that strain ICB 89(T) belonged to the genus Stenotrophomonas and was most closely related to Stenotrophomonas maltophilia LMG 958(T), Stenotrophomonas rhizophila LMG 22075(T), Stenotrophomonas nitritireducens L2(T), [Pseudomonas] geniculata ATCC 19374(T), [Pseudomonas] hibiscicola ATCC 19867(T) and [Pseudomonas] beteli ATCC 19861(T). DNA-DNA hybridization together with chemotaxonomic data and biochemical characteristics allowed the differentiation of strain ICB 89(T) from its nearest phylogenetic neighbours. Therefore, strain ICB 89(T) represents a novel species, for which the name Stenotrophomonas pavanii sp. nov. is proposed. The type strain is ICB 89(T) (=CBMAI 564(T) =LMG 25348(T)).

Paged similarity queries

An important feature of a database management systems (DBMS) is its client/server architecture, where managing shared memory among the clients and the server is always an tough issue. However, similarity queries are specially sensitive to this kind of architecture, since the answer sizes vary widely. Usually, the answers of similarity query are fully processed to be sent in full to the user, who often is interested in just parts of the answer, e.g. just few elements closer or farther to the query reference. Compelling the DBMS to retrieve the full answer, further ignoring its majority is at least a waste of server processing power. Paging the answer is a technique that splits the answer onto several pages, following client requests. Despite the success of paging on traditional queries, little work has been done to support it in similarity queries. In this work, we present a technique that not only provides paging in similarity range or k-nearest neighbor queries, but also supports them in two variations: the forward similarity query and the backward similarity query. They return elements either increasingly farther of increasingly closer to the query reference. The reported experiments show that, depending on the proportion of the interesting part over the full answer, both techniques allow answering queries much faster than it is obtained in the non-paged way. (C) 2010 Elsevier Inc. All rights reserved.

On the influence of imputation in classification: practical issues

The substitution of missing values, also called imputation, is an important data preparation task for many domains. Ideally, the substitution of missing values should not insert biases into the dataset. This aspect has been usually assessed by some measures of the prediction capability of imputation methods. Such measures assume the simulation of missing entries for some attributes whose values are actually known. These artificially missing values are imputed and then compared with the original values. Although this evaluation is useful, it does not allow the influence of imputed values in the ultimate modelling task (e.g. in classification) to be inferred. We argue that imputation cannot be properly evaluated apart from the modelling task. Thus, alternative approaches are needed. This article elaborates on the influence of imputed values in classification. In particular, a practical procedure for estimating the inserted bias is described. As an additional contribution, we have used such a procedure to empirically illustrate the performance of three imputation methods (majority, naive Bayes and Bayesian networks) in three datasets. Three classifiers (decision tree, naive Bayes and nearest neighbours) have been used as modelling tools in our experiments. The achieved results illustrate a variety of situations that can take place in the data preparation practice.