Measuring microscopic viscosity with optical tweezers as a confocal probe

We demonstrate, what is to the best our knowledge, a new method for studying the motion of a particle trapped by optical tweezers; in this method the trapping beam itself is used as a confocal probe. By studying the response of the particle to periodic motion of the tweezers, we obtain information about the medium viscosity, particle properties, and trap stiffness. We develop the mathematical model, demonstrate experimentally its validity for our system, and discuss advantages of using this method as a new form of scanning photonic force microscopy for applications in which a high spatial and temporal resolution of the medium viscosity is desired.     

Functional theory of illusory conjunctions and neon colors.

Illusory conjunctions are the incorrect perceptual combination of briefly presented colors and shapes. In the neon colors illusion, achromatic figures take on the color of an overlaid grid of colored lines. Both illusions are explained by a theory that assumes (a) poor location information or poor spatial resolution for some aspects of visual information and (b) that the spatial location of features is constrained by perceptual organization. Computer simulations demonstrate that the mechanisms suggested by the theory are useful in veridical perception and they are sufficient to produce illusory conjunctions. The theory suggests mechanisms that economically encode visual information in a way that filters noise and fills in missing data. Issues related to neural implementation are discussed. Four experiments illustrate the theory. Illusory conjunctions are shown to be affected by objective stimulus organization, by subjective organization, and by the linguistic structure of ambiguous Hebrew words. Neon colors are constrained by linguistic structure in the same way as illusory conjunctions. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

On the computation of an asymptotic bound for estimating autoregressive signals in white noise

The Cramer-Rao lower bound (CRLB) provides a useful reference for evaluating the performance of parameter estimation techniques. This paper considers the problem of estimating the parameters of an autoregressive signal corrupted by white noise. An explicit formula is derived for computing the asymptotic CRLB for the signal and noise parameters. Formulas for the asymptotic CRLB for functions of the signal and noise parameters are also presented. In particular, the center frequency, bandwidth and power of a second order process are considered. Some numerical examples are presented to illustrate the usefulness of these bounds in studying estimation accuracy.     

Performance analysis of parameter estimation algorithms based on high-order moments

Recently, there has been a considerable interest in parametric estimation of non-Gaussian processes, based on high-order moments. Several researchers have proposed algorithms for estimating the parameters of AR, MA and ARMA processes, based on the third-order and fourth-order cumulants. These algorithms are capable of handling non-minimum phase processes, and some of them provide a good trade-off between computational complexity and statistical efficiency. This paper presents some results about the performance of algorithms based on high-order moments. A general lower bound is derived for the variance of estimates based on high-order sample moments. This bound, which is shown to be asymptotically tight, is neither the Cramer-Rao bound nor a trivial extension thereof. The performance of weighted least squares estimates of the type recently proposed in the literature is investigated. An expression for the variance of such estimates is derived and the existence of an optimal weight matrix is proven. The general formulae are specialized to MA and ARMA processes and used to analyse the performance of some algorithms in detail. The analytic results are verified by Monte Carlo simulations for some specific test cases. A by-product of this paper is the derivation of asymptotic formulae for the variances and covariances of the sample third-order moments of a certain class of processes.     

Anisotropic lattice distortions in biogenic aragonite

Composite biogenic materials produced by organisms have a complicated design on a nanometre scale. An outstanding example of organic-inorganic composites is provided by mollusc seashells, whose superior mechanical properties are due to their multi-level crystalline hierarchy and the presence of a small amount (0.1-5 wt%) of organic molecules. The presence of organic molecules, among other characteristics, can influence the coherence length for X-ray scattering in biogenic crystals. Here we show the results of synchrotron high-resolution X-ray powder diffraction measurements in biogenic and non-biogenic (geological) aragonite crystals. On applying the Rietveld refinement procedure to the high-resolution diffraction spectra, we were able to extract the aragonite lattice parameters with an accuracy of 10 p.p.m. As a result, we found anisotropic lattice distortions in biogenic aragonite relative to the geological sample, maximum distortion being 0.1% along the c axis of the orthorhombic unit cell. The organic molecules could be a source of these structural distortions in biogenic crystals. This finding may be important to the general understanding of the biomineralization process and the development of bio-inspired 'smart' materials.     

The Bayesian ARTMAP.

In this paper, we modify the fuzzy ARTMAP (FA) neural network (NN) using the Bayesian framework in order to improve its classification accuracy while simultaneously reduce its category proliferation. The proposed algorithm, called Bayesian ARTMAP (BA), preserves the FA advantages and also enhances its performance by the following: (1) representing a category using a multidimensional Gaussian distribution, (2) allowing a category to grow or shrink, (3) limiting a category hypervolume, (4) using Bayes' decision theory for learning and inference, and (5) employing the probabilistic association between every category and a class in order to predict the class. In addition, the BA estimates the class posterior probability and thereby enables the introduction of loss and classification according to the minimum expected loss. Based on these characteristics and using synthetic and 20 real-world databases, we show that the BA outperformes the FA, either trained for one epoch or until completion, with respect to classification accuracy, sensitivity to statistical overlapping, learning curves, expected loss, and category proliferation.     

A novel technique to assess chromatin texture using pixel optical densitometry in oral squamous cell carcinoma

Background: The early detection of neoplasia is the prime aim of a diagnostician. Altered chromatin distribution is the earliest microscopic change observed in malignant transformation making it a valuable morphometric parameter. This study was aimed to assess and correlate the progressive changes in chromatin texture from normal to varying grades of premalignancies to malignancy of the oral cavity. Methods: Thirty‐four archival tissue specimens categorized as normal buccal mucosa (5), low‐grade epithelial dysplasia (11), high‐grade epithelial dysplasia (7), and squamous cell carcinoma (11) were stained with Feulgen reaction. Pixel optical densitometry histograms were obtained from analysis of an average of 300 cells/case using ImageJ software. Nine histogram curve characteristics (including area under the curve, area integer percentage, center, centroid) were then analyzed statistically for differences between the four groups. Results: Area integer percentage (P = 0.002), center (P = 0.038), and centroid (P = 0.021) were statistically significant within the four groups The parameters showed a dip in their value from normal to low‐grade dysplasia but showed a steady increase in high‐grade dysplasia and carcinoma. Conclusion: The optical density characteristics had the ability to differentiate the progression of neoplastic changes by extracting information of the chromatin distribution not quantifiable by routine microscopy. The early clumping of chromatin in the periphery in low‐grade dysplasia followed by progressively increasing chromatin aggregates in high‐grade dysplasia and carcinoma correlated well with the shift observed in the histogram center and centroid. The novel pixel optical densitometry technique efficiently predicted malignant transformation. Microsc. Res. Tech. 75:1119–1123, 2012. © 2012 Wiley Periodicals, Inc.     

Joint maximization of accuracy and information for learning the structure of a Bayesian network classifier

Machine Learning - Although recent studies have shown that a Bayesian network classifier (BNC) that maximizes the classification accuracy (i.e., minimizes the 0/1 loss function) is a powerful tool...     

Online Scheduling with Interval Conflicts

In the problem of Scheduling with Interval Conflicts, there is a ground set of items indexed by integers, and the input is a collection of conflicts, each containing all the items whose index lies within some interval on the real line. Conflicts arrive in an online fashion. A scheduling algorithm must select, from each conflict, at most one survivor item, and the goal is to maximize the number (or weight) of items that survive all the conflicts they are involved in. We present a centralized deterministic online algorithm whose competitive ratio is O(lgσ), where σ is the size of the largest conflict. For the distributed setting, we present another deterministic algorithm whose competitive ratio is $2\left \lceil {\lg\sigma} \right \rceil $ in the special contiguous case, in which the item indices constitute a contiguous interval of integers. Our upper bounds are complemented by two lower bounds: one that shows that even in the contiguous case, all deterministic algorithms (centralized or distributed) have competitive ratio Ω(lgσ), and that in the non-contiguous case, no deterministic oblivious algorithm (i.e., a distributed algorithm that does not use communication) can have a bounded competitive ratio.     

Merkle’s Key Agreement Protocol is Optimal: An $$O(n^2)$$ Attack on Any Key Agreement from Random Oracles

We prove that every key agreement protocol in the random oracle model in which the honest users make at most n queries to the oracle can be broken by an adversary who makes \(O(n^2)\) queries to the oracle. This improves on the previous \({\tilde{\Omega }}(n^6)\) query attack given by Impagliazzo and Rudich (STOC ’89) and resolves an open question posed by them. Our bound is optimal up to a constant factor since Merkle proposed a key agreement protocol in 1974 that can be easily implemented with n queries to a random oracle and cannot be broken by any adversary who asks \(o(n^2)\) queries.