A column method for determination of soil organic partition coefficients of eight pesticides

A column method was developed to conveniently and reliably determine the soil organic partition coefficients (K-oc) of three insecticides (methiocarb, azinphos-methyl, fenthion), four fungicides (triadimenol, fuberidazole, tebuconazole, pencycuron), and one herbicide (atrazine), in which real soil acted as a stationary phase and the water solution of pesticide as an eluent. The processes of sorption equilibrium were directly shown through a breakthrough curve(BTC). The log K-oc values are 1.69, 1.95, 2.25, 2.55, 2.69, 2.67, 3.10, and 3.33 for atrazine, triadimenol, methiocarb, fuberidazole, azinphos-methyl, tebuconazole, fenthion and pencycuron, respectively.

Soil column chromatography for correlation between capacity factors and soil organic partition coefficients for eight pesticides

A soil column chromatographic method was developed to measure the capacity factors (k') of pesticides, in which soil acted as a stationary phase and methanol-water mixture as an eluent. The k' values of eight pesticides, including three insecticides (methiocarb, azinphos-methyl, fenthion), four fungicides (triadimenol, fuberidazole, tebuconazole, pencycuron), and one herbicide (atrazine), were found to be well fitted to a retention equation, ln k'=ln k(w)'-S-phi. Due to similar interactions of solutes with soil and solvent in both sorption determination and retention experiment, log k' has a good linear correlation with log K-oc for the eight pesticides from different classes, in contrast with poor correlation between log k' from C-18 column and log K-oc. So the method provides a tool for rapid estimation of K-oc from experimental k'. (C) 1999 Elsevier Science Ltd. All rights reserved.

Visual Tracking

A typical robot vision scenario might involve a vehicle moving with an unknown 3D motion (translation and rotation) while taking intensity images of an arbitrary environment. This paper describes the theory and implementation issues of tracking any desired point in the environment. This method is performed completely in software without any need to mechanically move the camera relative to the vehicle. This tracking technique is simple an inexpensive. Furthermore, it does not use either optical flow or feature correspondence. Instead, the spatio-temporal gradients of the input intensity images are used directly. The experimental results presented support the idea of tracking in software. The final result is a sequence of tracked images where the desired point is kept stationary in the images independent of the nature of the relative motion. Finally, the quality of these tracked images are examined using spatio-temporal gradient maps.

Range Segmentation Using Visibility Constraints

Visibility constraints can aid the segmentation of foreground objects observed with multiple range images. In our approach, points are defined as foreground if they can be determined to occlude some {em empty space} in the scene. We present an efficient algorithm to estimate foreground points in each range view using explicit epipolar search. In cases where the background pattern is stationary, we show how visibility constraints from other views can generate virtual background values at points with no valid depth in the primary view. We demonstrate the performance of both algorithms for detecting people in indoor office environments.

Shape-Time Photography

We introduce a new method to describe, in a single image, changes in shape over time. We acquire both range and image information with a stationary stereo camera. From the pictures taken, we display a composite image consisting of the image data from the surface closest to the camera at every pixel. This reveals the 3-d relationships over time by easy-to-interpret occlusion relationships in the composite image. We call the composite a shape-time photograph. Small errors in depth measurements cause artifacts in the shape-time images. We correct most of these using a Markov network to estimate the most probable front surface, taking into account the depth measurements, their uncertainties, and layer continuity assumptions.

An Analog VLSI Chip for Estimating the Focus of Expansion

For applications involving the control of moving vehicles, the recovery of relative motion between a camera and its environment is of high utility. This thesis describes the design and testing of a real-time analog VLSI chip which estimates the focus of expansion (FOE) from measured time-varying images. Our approach assumes a camera moving through a fixed world with translational velocity; the FOE is the projection of the translation vector onto the image plane. This location is the point towards which the camera is moving, and other points appear to be expanding outward from. By way of the camera imaging parameters, the location of the FOE gives the direction of 3-D translation. The algorithm we use for estimating the FOE minimizes the sum of squares of the differences at every pixel between the observed time variation of brightness and the predicted variation given the assumed position of the FOE. This minimization is not straightforward, because the relationship between the brightness derivatives depends on the unknown distance to the surface being imaged. However, image points where brightness is instantaneously constant play a critical role. Ideally, the FOE would be at the intersection of the tangents to the iso-brightness contours at these "stationary" points. In practice, brightness derivatives are hard to estimate accurately given that the image is quite noisy. Reliable results can nevertheless be obtained if the image contains many stationary points and the point is found that minimizes the sum of squares of the perpendicular distances from the tangents at the stationary points. The FOE chip calculates the gradient of this least-squares minimization sum, and the estimation is performed by closing a feedback loop around it. The chip has been implemented using an embedded CCD imager for image acquisition and a row-parallel processing scheme. A 64 x 64 version was fabricated in a 2um CCD/ BiCMOS process through MOSIS with a design goal of 200 mW of on-chip power, a top frame rate of 1000 frames/second, and a basic accuracy of 5%. A complete experimental system which estimates the FOE in real time using real motion and image scenes is demonstrated.

Hybrid organic-inorganic phenyl monolithic column for capillary electrochromatography

A novel hybrid organic-inorganic silica-based monolithic column possessing phenyl ligands for reversed-phase (RP) capillary electrochromatography (CEC) is described. The monolithic stationary phase was prepared by in situ co-condensation of tetraethoxysilane (TEOS) with phenyltriethoxysilane (PTES) via a two-step catalytic sol-gel procedure to introduce phenyl groups distributed throughout the silica matrix for chromatographic interaction. The hydrolysis and condensation reactions of precursors were chemically controlled through pH variation by adding hydrochloric acid and dodecylamine, respectively. The structural property of the monolithic column can be easily tailored through adjusting the composition of starting sol solution. The effect of PTES/TEOS ratios on the morphology of the created stationary phases was investigated. A variety of neutral and basic analytes were used to evaluate the column performance. The CEC columns exhibited typical RP chromatographic retention mechanism for neutral compounds and had improved peak shape for basic solutes.

Methanol steam reforming in a compact plate-fin reformer for fuel-cell systems

A compact plate-fin reformer (PFR) consisting of closely spaced plate-fins, in which endothermic and exothermic reactions take place in alternate chambers, has been studied. In the PFR, which was based on a plate-fin heat exchanger, catalytic combustion of the reforming gas, as a simulation of the fuel cell anode off gas (AOG), supplied the necessary heat for the reforming reaction. One reforming chamber, which was for hydrogen production, was integrated with two vaporization chambers and two combustion chambers to constitute a single unit of PFR. The PFR is very compact, easy to be placed and scaled up. The effect of the ratio of H2O/CH3OH on the performance of the PFR has been investigated, and temperature distributions in different chambers were studied. Besides, the stationary behavior of the PFR was also investigated. Heat transfer of the reformer was enhanced by internal plate-fins as well as by external catalytic combustion, which offer both high methanol conversion ratio and low CO concentration. In addition, the fully integrated reformer exhibited good test stability. Based on the PFR, a scale-up reformer was designed and operated continuously for 1000 h, with high methanol conversion ratio and low CO concentration. (c) 2004 International Association for Hydrogen Energy. Published by Elsevier Ltd. All rights reserved.

Separation of compounds interacting with liposome membrane in combined prescription of traditional Chinese medicines with immobilized liposome chromatography

Immobilized liposome chromatography (ILC), the stationary phase of which has been regarded as a mimic biomembranes system was used to separate and analyze compounds interacting with liposome membrane in Danggui Buxue decoction, a combined prescription of traditional Chinese medicines (CPTCMs), and its compositions Radix Astragli and Radix Angelica Sinensis. More than 10 main peaks in the extract of Danggui Buxue decoction were resolved on the ILC column, suggesting that more than 10 components in the prescription have significant retention on ILC column. Ligustilide, astragaloside, TV and formononetin, three main bioactive ingredients in Danggui Buxue decoction, were found to have relatively significant, while ferulic acid, another bioactive ingredient in the prescription, relatively weak retention on ILC column. Effects of the eluent pH and amount of immobilized phosphatidylcholine (PC) on separation of interactional compounds in the extract of Danggui Buxue decoction were also investigated. It was found that these two factors strongly affected the retention of some interactional compounds. In addition, the fractions partitioned with different solvents from water extract of this combined prescription were evaluated with this ILC column system. (c) 2005 Elsevier B.V. All rights reserved.

Segmenting Foreground Objects from a Dynamic Textured Background via a Robust Kalman Filter

The algorithm presented in this paper aims to segment the foreground objects in video (e.g., people) given time-varying, textured backgrounds. Examples of time-varying backgrounds include waves on water, clouds moving, trees waving in the wind, automobile traffic, moving crowds, escalators, etc. We have developed a novel foreground-background segmentation algorithm that explicitly accounts for the non-stationary nature and clutter-like appearance of many dynamic textures. The dynamic texture is modeled by an Autoregressive Moving Average Model (ARMA). A robust Kalman filter algorithm iteratively estimates the intrinsic appearance of the dynamic texture, as well as the regions of the foreground objects. Preliminary experiments with this method have demonstrated promising results.

A Bayesian Approach for TCP to Distinguish Congestion from Wireless Losses

(This Technical Report revises TR-BUCS-2003-011) The Transmission Control Protocol (TCP) has been the protocol of choice for many Internet applications requiring reliable connections. The design of TCP has been challenged by the extension of connections over wireless links. In this paper, we investigate a Bayesian approach to infer at the source host the reason of a packet loss, whether congestion or wireless transmission error. Our approach is "mostly" end-to-end since it requires only one long-term average quantity (namely, long-term average packet loss probability over the wireless segment) that may be best obtained with help from the network (e.g. wireless access agent).Specifically, we use Maximum Likelihood Ratio tests to evaluate TCP as a classifier of the type of packet loss. We study the effectiveness of short-term classification of packet errors (congestion vs. wireless), given stationary prior error probabilities and distributions of packet delays conditioned on the type of packet loss (measured over a larger time scale). Using our Bayesian-based approach and extensive simulations, we demonstrate that congestion-induced losses and losses due to wireless transmission errors produce sufficiently different statistics upon which an efficient online error classifier can be built. We introduce a simple queueing model to underline the conditional delay distributions arising from different kinds of packet losses over a heterogeneous wired/wireless path. We show how Hidden Markov Models (HMMs) can be used by a TCP connection to infer efficiently conditional delay distributions. We demonstrate how estimation accuracy is influenced by different proportions of congestion versus wireless losses and penalties on incorrect classification.

Estimating Sensor Motion from Wide-Field Optical Flow on a Log-Dipolar Sensor

Log-polar image architectures, motivated by the structure of the human visual field, have long been investigated in computer vision for use in estimating motion parameters from an optical flow vector field. Practical problems with this approach have been: (i) dependence on assumed alignment of the visual and motion axes; (ii) sensitivity to occlusion form moving and stationary objects in the central visual field, where much of the numerical sensitivity is concentrated; and (iii) inaccuracy of the log-polar architecture (which is an approximation to the central 20°) for wide-field biological vision. In the present paper, we show that an algorithm based on generalization of the log-polar architecture; termed the log-dipolar sensor, provides a large improvement in performance relative to the usual log-polar sampling. Specifically, our algorithm: (i) is tolerant of large misalignmnet of the optical and motion axes; (ii) is insensitive to significant occlusion by objects of unknown motion; and (iii) represents a more correct analogy to the wide-field structure of human vision. Using the Helmholtz-Hodge decomposition to estimate the optical flow vector field on a log-dipolar sensor, we demonstrate these advantages, using synthetic optical flow maps as well as natural image sequences.

Modeling Financial Time Series with Artificial Neural Networks

Financial time series convey the decisions and actions of a population of human actors over time. Econometric and regressive models have been developed in the past decades for analyzing these time series. More recently, biologically inspired artificial neural network models have been shown to overcome some of the main challenges of traditional techniques by better exploiting the non-linear, non-stationary, and oscillatory nature of noisy, chaotic human interactions. This review paper explores the options, benefits, and weaknesses of the various forms of artificial neural networks as compared with regression techniques in the field of financial time series analysis.

Statistical properties of first-order bang-bang Pll with nonzero loop delay

A method to solve the stationary state probability is presented for the first-order bang-bang phase-locked loop (BBPLL) with nonzero loop delay. This is based on a delayed Markov chain model and a state How diagram for tracing the state history due to the loop delay. As a result, an eigenequation is obtained, and its closed form solutions are derived for some cases. After obtaining the state probability, statistical characteristics such as mean gain of the binary phase detector and timing error variance are calculated and demonstrated.

Investigation of catalyst effects in enantioselective copper- and rhodium-mediated transformations of α-diazocarbonyl compounds

This thesis describes the synthesis and reactivity of a series of α-diazocarbonyl compounds with particular emphasis on the use of copper-bis(oxazoline)-mediated enantioselective C–H insertion reactions leading to enantioenriched cyclopentanone derivatives. Through the use of additives, the enantioselectivity achieved with the copper catalysts for the first time reaches synthetically useful levels (up to 91% ee). Chapter one provides a comprehensive overview of enantioselective C–H insertions with α-diazocarbonyl compounds from the literature. The majority of reports in this section involve rhodium-catalysed systems with limited reports to date of asymmetric C–H insertion reactions in the presence of copper catalysts. Chapter two focuses on the synthesis and C–H insertion reactions of α-diazo-β-keto sulfones leading to α-sulfonyl cyclopentanones as the major product. Detailed investigation of the impact of substrate structure (both the sulfonyl substitutent and the substituent at the site of insertion), the copper source, ligand, counterion, additive and solvent was undertaken to provide an insight into the mechanistic basis for enantiocontrol in the synthetically powerful C–H insertion process and to enable optimisation of enantiocontrol and ligand design. Perhaps the most significant outcome of this work is the enhanced enantioselection achieved through use of additives, substantially improving the synthetic utility of the asymmetric C–H insertion process. In addition to the C–H insertion reaction, mechanistically interesting competing reaction pathways involving hydride transfer are observed. Chapter three reports the extension of the catalyst-additive systems, developed for C–H insertions with α-diazo-β-keto sulfones in chapter two, to C–H insertion in analogous α-diazo-β-keto phosphonate and α-diazo-β-keto ester systems. While similar patterns were seen in terms of ligand effects, the enantiopurities achieved for these reactions were lower than those in the cyclisations with analogous α-diazo-β-keto sulfones. Extension of this methodology to cyclopropanation and oxium ylide formation/[2,3]-sigmatropic rearrangement was also explored. Chapter four contains the full experimental details and spectral characterisation of all novel compounds synthesised in this project, while details of chiral stationary phase HPLC analysis and X-ray crystallography are included in the appendix.