Analysis of Saponins from Leaves of Aralia elata by Liquid Chromatography and Multi-stage Tandem Mass Spectrometry

Four saponins were isolated from the leaves of Aralia elata, and established using NMR and other spectroscopic methods, as well as data reported in the literature. Three Aralia saponins from the leaves of Aralia elata sharing the same structures as those isolated from the root bark suggested that the leaves would be a good substitute for the root bark of Aralia elata. These four Aralia saponins were then extensively investigated using complementarily positive and negative electrospray ionization multistage tandem mass spectrometry (ESI-MSn). Two isomers of saponins with different sugar linkages were then successfully differentiated by positive ESI-MSn and verified with different retention times and the collision-induced dissociation (CID) spectra by LC-MS. A simple and effective LC-MS method was thus developed for the rapid identification and screening of these saponins in plant extracts from leaves of Aralia elata.

Identification of herb Acanthopanax senticosus (Rupr. Et Maxim.) harms by capillary electrophoresis with electrochemical detection

In this paper, a rapid, high efficient, sensitive and inexpensive approach based on a combination of simple ultrasonic extract and capillary electrophoresis (CE) separation with electrochemical detection (ED), is described to identify herbs by comparing their CE-ED profiles (namely, CE-ED electropherograms). The proposed method takes advantage of ultrasmall sample volume, low consumption of organic solvent, simple sample pretreatment and easy cleanup procedure. It was applied to analyze the CE-ED profiles of stems of herb Acanthopanax senticosus (Rupr. Et Maxim.) Harms from different sources and different parts (roots, rhizomes, stems and leaves) of this herb. By comparing peak number, peak height and peak height ratio, we found that the CE-ED profiles showed big differences for the herbs from the different sources and the different parts of this herb. In addition, the distribution of bioactive compounds (isofraxidin, rutin and chlorogenic acid) in the different parts of this herb and their content variations affected by the source were studied with the CE-ED method. Based on their own unique CE-ED profiles, these herbs from the different sources and the different parts of this herb could be easily distinguished. Therefore, the proposed approach could be used as a rapid, high efficient and sensitive method for the identification of herbal medicines.

Using the ribosomal internal transcribed spacer (ITS) as a complement marker for species identification of red macroalgae

Barcodes based on mitochondrial cytochrome oxidase (mtDNA CO1) sequences are being used for broad taxonomic groups of animals with demonstrated success in species identification and cryptic species discovery, but it has become clear that complementation by a nuclear marker system is necessary, in particular for the barcoding of plants. Here, we propose the nuclear internal transcribed spacer (ITS) as a potentially usable and complementary marker for species identification of red macroalgae, as well as present a primary workflow for species barcoding. Data show that for most red macroalgal genera (except members of the family Delesseriaceae), the size of ITS region ranges from 600 to 1200 bp, and contains enough variation to generate unique identifiers at either the species or genus levels. Consistent with previous studies, we found that the ITS sequence can resolve closely related species with the same fidelity as mtDNA CO1. Significantly, we confirmed that length polymorphism in the ITS region (including 5.8S rRNA gene) can be utilized as a character to discriminate red macroalgal species. As a complementary marker, the verifiable nuclear ITS region can speed routine identification and the detection of species, advance ecological and taxonomic inquiry, and permit rapid and accurate analysis of red macroalgae.

Development of rRNA and rDNA-targeted probes for fluorescence in situ hybridization to detect Heterosigma akashiwo (Raphidophyceae)

Heterosigma akashiwo (Hada) is a fragile, fish-killing alga. Efforts to understand and prevent blooms due to this harmful species to mitigate the impact on aquaculture require the development of methods for rapid and precise identification and quantification, so that adequate warning of a harmful algal bloom may be given. Here, we report the development and application of rRNA and rDNA-targeted oligonucleotide probes for fluorescence in situ hybridization (FISH) to aid in the detection and enumeration of H. akashiwo. The designed probes were species specific, showing no cross-reactivity with four common HAB causative species: Prorocentrum micans Ehrenberg, P. minimum (Pavillard) Schiller, Alexandrium tarmarense (Lebour) Balech, and Skeletonema costatum (Greville) Cleve, or with four other microalgae, including Gymnodinium sp. Stein, Platy-monas cordiformis (Karter) Korsch, Skeletonema sp.1 Greville and Skeletonema sp.2. The rRNA-targeted probe hybridized to cytoplasmic rRNA, showing strong green fluorescence throughout the whole cell, while cells labeled by rDNA-targeted probe exhibited exclusively fluorescent nucleus. The detection protocols were optimized and could be completed within an hour. For rRNA and rDNA probes, about a corresponding 80% and 70% of targeted cells could be identified and quantified during the whole growth circle, despite the inapparent variability in the average probe reactivity. The established FISH was proved promising for specific, rapid, precise, and quantitative detection of H. akashiwo. (C) 2008 Elsevier B.V. All rights reserved.

Feature Matching for Object Localization in the Presence of Uncertainty

We consider the problem of matching model and sensory data features in the presence of geometric uncertainty, for the purpose of object localization and identification. The problem is to construct sets of model feature and sensory data feature pairs that are geometrically consistent given that there is uncertainty in the geometry of the sensory data features. If there is no geometric uncertainty, polynomial-time algorithms are possible for feature matching, yet these approaches can fail when there is uncertainty in the geometry of data features. Existing matching and recognition techniques which account for the geometric uncertainty in features either cannot guarantee finding a correct solution, or can construct geometrically consistent sets of feature pairs yet have worst case exponential complexity in terms of the number of features. The major new contribution of this work is to demonstrate a polynomial-time algorithm for constructing sets of geometrically consistent feature pairs given uncertainty in the geometry of the data features. We show that under a certain model of geometric uncertainty the feature matching problem in the presence of uncertainty is of polynomial complexity. This has important theoretical implications by demonstrating an upper bound on the complexity of the matching problem, an by offering insight into the nature of the matching problem itself. These insights prove useful in the solution to the matching problem in higher dimensional cases as well, such as matching three-dimensional models to either two or three-dimensional sensory data. The approach is based on an analysis of the space of feasible transformation parameters. This paper outlines the mathematical basis for the method, and describes the implementation of an algorithm for the procedure. Experiments demonstrating the method are reported.

Ubuntu, Jesus, and Earth: Integrating African Religion and Christianity in Ecological Ethics

Africa faces problems of ecological devastation caused by economic exploitation, rapid population growth, and poverty. Capitalism, residual colonialism, and corruption undermine Africa's efforts to forge a better future. The dissertation describes how in Africa the mounting ecological crisis has religious, political, and economic roots that enable and promote social and environmental harm. It presents the thesis that religious traditions, including their ethical expressions, can effectively address the crisis, ameliorate its impacts, and advocate for social and environmental betterment, now and in the future. First, it examines African traditional religion and Christian teaching, which together provide the foundation for African Christianity. Critical examination of both religious worldviews uncovers their complementary emphases on human responsibility toward planet Earth and future generations. Second, an analysis of the Gwembe Tonga of Chief Simamba explores the interconnectedness of all elements of the universe in African cosmologies. In Africa, an interdependent, participatory relationship exists between the world of animals, the world of humans, and the Creator. In discussing the annual lwiindi (rain calling) ceremony of Simamba, the study explores ecological overtones of African religions. Such rituals illustrate the involvement of ancestors and high gods in maintaining ecological integrity. Third, the foundation of the African morality of abundant life is explored. Across Sub-Saharan Africa, ancestors' teachings are the foundation of morality; ancestors are guardians of the land. A complementary teaching that Christ is the ecological ancestor of all life can direct ethical responses to the ecological crisis. Fourth, the eco-social implications of ubuntu (what it means to be fully human) are examined. Some aspects of ubuntu are criticized in light of economic inequalities and corruption in Africa. However, ubuntu can be transformed to advocate for eco-social liberation. Fifth, the study recognizes that in some cases conflicts exist between ecological values and religious teachings. This conflict is examined in terms of the contrast between awareness of socioeconomic problems caused by population growth, on the one hand, and advocacy of a traditional African morality of abundant children, on the other hand. A change in the latter religious view is needed since overpopulation threatens sustainable living and the future of Earth. The dissertation concludes that the identification of Jesus with African ancestors and theological recognition of Jesus as the ecological ancestor, woven together with ubuntu, an ethic of interconnectedness, should characterize African consciousness and promote resolution of the socio-ecological crisis.

Periodic Motion Detection and Estimation via Space-Time Sampling

A novel technique to detect and localize periodic movements in video is presented. The distinctive feature of the technique is that it requires neither feature tracking nor object segmentation. Intensity patterns along linear sample paths in space-time are used in estimation of period of object motion in a given sequence of frames. Sample paths are obtained by connecting (in space-time) sample points from regions of high motion magnitude in the first and last frames. Oscillations in intensity values are induced at time instants when an object intersects the sample path. The locations of peaks in intensity are determined by parameters of both cyclic object motion and orientation of the sample path with respect to object motion. The information about peaks is used in a least squares framework to obtain an initial estimate of these parameters. The estimate is further refined using the full intensity profile. The best estimate for the period of cyclic object motion is obtained by looking for consensus among estimates from many sample paths. The proposed technique is evaluated with synthetic videos where ground-truth is known, and with American Sign Language videos where the goal is to detect periodic hand motions.

Color Region Grouping and Shape Recognition with Deformable Models

A new deformable shape-based method for color region segmentation is described. The method includes two stages: over-segmentation using a traditional color region segmentation algorithm, followed by deformable model-based region merging via grouping and hypothesis selection. During the second stage, region merging and object identification are executed simultaneously. A statistical shape model is used to estimate the likelihood of region groupings and model hypotheses. The prior distribution on deformation parameters is precomputed using principal component analysis over a training set of region groupings. Once trained, the system autonomously segments deformed shapes from the background, while not merging them with similarly colored adjacent objects. Furthermore, the recovered parametric shape model can be used directly in object recognition and comparison. Experiments in segmentation and image retrieval are reported.

Improved Tracking of Multiple Humans with Trajectory Prediction and Occlusion Modeling

A combined 2D, 3D approach is presented that allows for robust tracking of moving bodies in a given environment as observed via a single, uncalibrated video camera. Tracking is robust even in the presence of occlusions. Low-level features are often insufficient for detection, segmentation, and tracking of non-rigid moving objects. Therefore, an improved mechanism is proposed that combines low-level (image processing) and mid-level (recursive trajectory estimation) information obtained during the tracking process. The resulting system can segment and maintain the tracking of moving objects before, during, and after occlusion. At each frame, the system also extracts a stabilized coordinate frame of the moving objects. This stabilized frame is used to resize and resample the moving blob so that it can be used as input to motion recognition modules. The approach enables robust tracking without constraining the system to know the shape of the objects being tracked beforehand; although, some assumptions are made about the characteristics of the shape of the objects, and how they evolve with time. Experiments in tracking moving people are described.

Foreground Object Segmentation from Binocular Stereo Video

Moving cameras are needed for a wide range of applications in robotics, vehicle systems, surveillance, etc. However, many foreground object segmentation methods reported in the literature are unsuitable for such settings; these methods assume that the camera is fixed and the background changes slowly, and are inadequate for segmenting objects in video if there is significant motion of the camera or background. To address this shortcoming, a new method for segmenting foreground objects is proposed that utilizes binocular video. The method is demonstrated in the application of tracking and segmenting people in video who are approximately facing the binocular camera rig. Given a stereo image pair, the system first tries to find faces. Starting at each face, the region containing the person is grown by merging regions from an over-segmented color image. The disparity map is used to guide this merging process. The system has been implemented on a consumer-grade PC, and tested on video sequences of people indoors obtained from a moving camera rig. As can be expected, the proposed method works well in situations where other foreground-background segmentation methods typically fail. We believe that this superior performance is partly due to the use of object detection to guide region merging in disparity/color foreground segmentation, and partly due to the use of disparity information available with a binocular rig, in contrast with most previous methods that assumed monocular sequences.

A Neural Theory of Attentive Visual Search: Interactions of Boundary, Surface, Spatial, and Object Representations

Visual search data are given a unified quantitative explanation by a model of how spatial maps in the parietal cortex and object recognition categories in the inferotemporal cortex deploy attentional resources as they reciprocally interact with visual representations in the prestriate cortex. The model visual representations arc organized into multiple boundary and surface representations. Visual search in the model is initiated by organizing multiple items that lie within a given boundary or surface representation into a candidate search grouping. These items arc compared with object recognition categories to test for matches or mismatches. Mismatches can trigger deeper searches and recursive selection of new groupings until a target object io identified. This search model is algorithmically specified to quantitatively simulate search data using a single set of parameters, as well as to qualitatively explain a still larger data base, including data of Aks and Enns (1992), Bravo and Blake (1990), Chellazzi, Miller, Duncan, and Desimone (1993), Egeth, Viri, and Garbart (1984), Cohen and Ivry (1991), Enno and Rensink (1990), He and Nakayarna (1992), Humphreys, Quinlan, and Riddoch (1989), Mordkoff, Yantis, and Egeth (1990), Nakayama and Silverman (1986), Treisman and Gelade (1980), Treisman and Sato (1990), Wolfe, Cave, and Franzel (1989), and Wolfe and Friedman-Hill (1992). The model hereby provides an alternative to recent variations on the Feature Integration and Guided Search models, and grounds the analysis of visual search in neural models of preattentive vision, attentive object learning and categorization, and attentive spatial localization and orientation.

3-D Vision and Figure-Ground Separation by Visual Cortex

A neural network theory of :3-D vision, called FACADE Theory, is described. The theory proposes a solution of the classical figure-ground problem for biological vision. It does so by suggesting how boundary representations and surface representations are formed within a Boundary Contour System (BCS) and a Feature Contour System (FCS). The BCS and FCS interact reciprocally to form 3-D boundary and surface representations that arc mutually consistent. Their interactions generate 3-D percepts wherein occluding and occluded object completed, and grouped. The theory clarifies how preattentive processes of 3-D perception and figure-ground separation interact reciprocally with attentive processes of spatial localization, object recognition, and visual search. A new theory of stereopsis is proposed that predicts how cells sensitive to multiple spatial frequencies, disparities, and orientations are combined by context-sensitive filtering, competition, and cooperation to form coherent BCS boundary segmentations. Several factors contribute to figure-ground pop-out, including: boundary contrast between spatially contiguous boundaries, whether due to scenic differences in luminance, color, spatial frequency, or disparity; partially ordered interactions from larger spatial scales and disparities to smaller scales and disparities; and surface filling-in restricted to regions surrounded by a connected boundary. Phenomena such as 3-D pop-out from a 2-D picture, DaVinci stereopsis, a 3-D neon color spreading, completion of partially occluded objects, and figure-ground reversals are analysed. The BCS and FCS sub-systems model aspects of how the two parvocellular cortical processing streams that join the Lateral Geniculate Nucleus to prestriate cortical area V4 interact to generate a multiplexed representation of Form-And-Color-And-Depth, or FACADE, within area V4. Area V4 is suggested to support figure-ground separation and to interact. with cortical mechanisms of spatial attention, attentive objcect learning, and visual search. Adaptive Resonance Theory (ART) mechanisms model aspects of how prestriate visual cortex interacts reciprocally with a visual object recognition system in inferotemporal cortex (IT) for purposes of attentive object learning and categorization. Object attention mechanisms of the What cortical processing stream through IT cortex are distinguished from spatial attention mechanisms of the Where cortical processing stream through parietal cortex. Parvocellular BCS and FCS signals interact with the model What stream. Parvocellular FCS and magnocellular Motion BCS signals interact with the model Where stream. Reciprocal interactions between these visual, What, and Where mechanisms arc used to discuss data about visual search and saccadic eye movements, including fast search of conjunctive targets, search of 3-D surfaces, selective search of like-colored targets, attentive tracking of multi-element groupings, and recursive search of simultaneously presented targets.

Rapid separation of biologically important low molecular weight compounds by microchip electrophoresis and ultra-fast performance liquid chromatography

The research work in this thesis reports rapid separation of biologically important low molecular weight compounds by microchip electrophoresis and ultrahigh liquid chromatography. Chapter 1 introduces the theory and principles behind capillary electrophoresis separation. An overview of the history, different modes and detection techniques coupled to CE is provided. The advantages of microchip electrophoresis are highlighted. Some aspects of metal complex analysis by capillary electrophoresis are described. Finally, the theory and different modes of the liquid chromatography technology are presented. Chapter 2 outlines the development of a method for the capillary electrophoresis of (R, S) Naproxen. Variable parameters of the separation were optimized (i.e. buffer concentration and pH, concentration of chiral selector additives, applied voltage and injection condition).The method was validated in terms of linearity, precision, and LOD. The optimized method was then transferred to a microchip electrophoresis system. Two different types of injection i.e. gated and pinched, were investigated. This microchip method represents the fastest reported chiral separation of Naproxen to date. Chapter 3 reports ultra-fast separation of aromatic amino acid by capillary electrophoresis using the short-end technique. Variable parameters of the separation were optimized and validated. The optimized method was then transferred to a microchip electrophoresis system where the separation time was further reduced. Chapter 4 outlines the use of microchip electrophoresis as an efficient tool for analysis of aluminium complexes. A 2.5 cm channel with linear imaging UV detection was used to separate and detect aluminium-dopamine complex and free dopamine. For the first time, a baseline, separation of aluminium dopamine was achieved on a 15 seconds timescale. Chapter 5 investigates a rapid, ultra-sensitive and highly efficient method for quantification of histamine in human psoriatic plaques using microdialysis and ultrahigh performance liquid chromatography with fluorescence detection. The method utilized a sub-two-micron packed C18 stationary phase. A fluorescent reagent, 4-(1-pyrene) butyric acid N-hydroxysuccinimide ester was conjugated to the primary and secondary amino moieties of histamine. The dipyrene-labeled histamine in human urine was also investigated by ultrahigh pressure liquid chromatography using a C18 column with 1.8 μm particle diameter. These methods represent one of the fastest reported separations to date of histamine using fluorescence detection.

Electromagnetic tracking and steering for catheter navigation

This thesis explores the use of electromagnetics for both steering and tracking of medical instruments in minimally invasive surgeries. The end application is virtual navigation of the lung for biopsy of early stage cancer nodules. Navigation to the peripheral regions of the lung is difficult due to physical dimensions of the bronchi and current methods have low successes rates for accurate diagnosis. Firstly, the potential use of DC magnetic fields for the actuation of catheter devices with permanently magnetised distal attachments is investigated. Catheter models formed from various materials and magnetic tip formations are used to examine the usefulness of relatively low power and compact electromagnets. The force and torque that can be exerted on a small permanent magnet is shown to be extremely limited. Hence, after this initial investigation we turn our attention to electromagnetic tracking, in the development of a novel, low-cost implementation of a GPS-like system for navigating within a patient. A planar magnetic transmitter, formed on a printed circuit board for a low-profile and low cost manufacture, is used to generate a low frequency magnetic field distribution which is detected by a small induction coil sensor. The field transmitter is controlled by a novel closed-loop system that ensures a highly stable magnetic field with reduced interference from one transmitter coil to another. Efficient demodulation schemes are presented which utilise synchronous detection of each magnetic field component experienced by the sensor. The overall tracking accuracy of the system is shown to be less than 2 mm with an orientation error less than 1°. A novel demodulation implementation using a unique undersampling approach allows the use of reduced sample rates to sample the signals of interest without loss of tracking accuracy. This is advantageous for embedded microcontroller implementations of EM tracking systems. The EM tracking system is demonstrated in the pre-clinical environment of a breathing lung phantom. The airways of the phantom are successfully navigated using the system in combination with a 3D computer model rendered from CT data. Registration is achieved using both a landmark rigid registration method and a hybrid fiducial-free approach. The design of a planar magnetic shield structure for blocking the effects of metallic distortion from below the transmitter is presented which successfully blocks the impact of large ferromagnetic objects such as operating tables. A variety of shielding material are analysed with MuMetal and ferrite both providing excellent shieling performance and an increased signal to noise ratio. Finally, the effect of conductive materials and human tissue on magnetic field measurements is presented. Error due to induced eddy currents and capacitive coupling is shown to severely affect EM tracking accuracy at higher frequencies.

Investigating antecedents and consequences of brand identification

Purpose – This study aims to analyse the influences of prestige, satisfaction, and communication on brand identification and to show how brand identification influences word-of-mouth and brand repurchase. Design/methodology/approach – A theoretical model is developed and tested with a sample of car owners in the UK of two global car brands. Structural equation modelling was used with LISREL 8.54 and the maximum likelihood (ML) method. Findings – This paper draws mainly on the theory of social identity to provide a comprehensive understanding of conditions under which brand owners are likely to identify with their brand and the bases and consequences of such identification. It was shown that prestige, satisfaction, and communication effect brand identification. The study confirms that consumers' development of relationships via brand identification results in word of mouth about the brand and intentions to repurchase the brand. Furthermore, it was found that brand identification fully mediates the influences of prestige, satisfaction, and communication on word of mouth and brand repurchase. Research limitations/implications – The focus was on one country and one industry. Practical implications – Managers are provided with strategies that enhance the identification of their customers with their brand so that they can strengthen the customers' brand identification. Areas for future research are suggested. For instance, it could be interesting to test the model in a different industry and/or cultural context. Originality/value – Very few previous studies have looked at brand identification which is surprising considering it is such an important variable to influence word-of-mouth and brand repurchase. The study tests three antecedents to brand identification and two outcomes that have not been investigated previously. Overall, the study adds knowledge in this somewhat neglected area.