Total analytical method for Radix astragali extract using two-binary multi-segment gradient elution liquid chromatography

There is an urgent need for thorough analysis of Radix astragali, a widely used Chinese herb, for quality control purposes. This paper describes the development of a total analytical method for Radix astragali extract, a multi-component complex mixture. Twenty-four components were separated step by step from the extract using a series of isocratic isopropanol-methanol elutions, and then 42 components were separated similarly using methanol-water elutions. Based on the log k(w) and -S of the 66 components obtained from the above procedure and the optimization software developed in our laboratory, an optimum elution program consisting of seven methanol-water segments and four isopropanol-methanol segments was developed to finish the task of analyzing the total components in a single run. Under optimized gradient conditions, the sample of Radix astragali extract was analyzed. As expected, most of the components were well separated and the experimental chromatogram was in a good agreement with the predicted one.

Parallel Networks for Machine Vision

The amount of computation required to solve many early vision problems is prodigious, and so it has long been thought that systems that operate in a reasonable amount of time will only become feasible when parallel systems become available. Such systems now exist in digital form, but most are large and expensive. These machines constitute an invaluable test-bed for the development of new algorithms, but they can probably not be scaled down rapidly in both physical size and cost, despite continued advances in semiconductor technology and machine architecture. Simple analog networks can perform interesting computations, as has been known for a long time. We have reached the point where it is feasible to experiment with implementation of these ideas in VLSI form, particularly if we focus on networks composed of locally interconnected passive elements, linear amplifiers, and simple nonlinear components. While there have been excursions into the development of ideas in this area since the very beginnings of work on machine vision, much work remains to be done. Progress will depend on careful attention to matching of the capabilities of simple networks to the needs of early vision. Note that this is not at all intended to be anything like a review of the field, but merely a collection of some ideas that seem to be interesting.

Restructuring Sparse High Dimensional Data for Effective Retrieval

The task in text retrieval is to find the subset of a collection of documents relevant to a user's information request, usually expressed as a set of words. Classically, documents and queries are represented as vectors of word counts. In its simplest form, relevance is defined to be the dot product between a document and a query vector--a measure of the number of common terms. A central difficulty in text retrieval is that the presence or absence of a word is not sufficient to determine relevance to a query. Linear dimensionality reduction has been proposed as a technique for extracting underlying structure from the document collection. In some domains (such as vision) dimensionality reduction reduces computational complexity. In text retrieval it is more often used to improve retrieval performance. We propose an alternative and novel technique that produces sparse representations constructed from sets of highly-related words. Documents and queries are represented by their distance to these sets. and relevance is measured by the number of common clusters. This technique significantly improves retrieval performance, is efficient to compute and shares properties with the optimal linear projection operator and the independent components of documents.

Inferring 3D Structure with a Statistical Image-Based Shape Model

We present an image-based approach to infer 3D structure parameters using a probabilistic "shape+structure'' model. The 3D shape of a class of objects may be represented by sets of contours from silhouette views simultaneously observed from multiple calibrated cameras. Bayesian reconstructions of new shapes can then be estimated using a prior density constructed with a mixture model and probabilistic principal components analysis. We augment the shape model to incorporate structural features of interest; novel examples with missing structure parameters may then be reconstructed to obtain estimates of these parameters. Model matching and parameter inference are done entirely in the image domain and require no explicit 3D construction. Our shape model enables accurate estimation of structure despite segmentation errors or missing views in the input silhouettes, and works even with only a single input view. Using a dataset of thousands of pedestrian images generated from a synthetic model, we can perform accurate inference of the 3D locations of 19 joints on the body based on observed silhouette contours from real images.

The Role of SoTL in Classroom Innovation.

The Scholarship of Teaching and Learning (SoTL) is being promoted as an activity for teaching-focused academics in the UK. However, support for SoTL is not a priority for most institutions, and formal provision for such support may not extend beyond the postgraduate certificate in higher education that is offered for new academic staff. This paper examines the experiences of SoTL of a group of twenty-one Life Sciences academics from a range of UK universities. It explores the role that SoTL has to play in developing classroom innovation in a structured and scholarly manner, and the consequences to both teaching staff and students, if SoTL is not supported as an academic activity throughout the careers of teaching-focused academics.

Niemieckie lotnictwo myśliwskie. Koncepcja i realizacja w latach 1939-1945

Wydział Historyczny

Análise Biográfica, do Estilo de Vinculação e da Personalidade, em Indivíduos com História de Abuso de Substâncias e Condutas Delinquentes

Tese de Doutoramento apresentada à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Doutor em Ciências Sociais.

QUANTITATIVE THREE DIMENSIONAL ELASTICITY IMAGING

Neoplastic tissue is typically highly vascularized, contains abnormal concentrations of extracellular proteins (e.g. collagen, proteoglycans) and has a high interstitial fluid pres- sure compared to most normal tissues. These changes result in an overall stiffening typical of most solid tumors. Elasticity Imaging (EI) is a technique which uses imaging systems to measure relative tissue deformation and thus noninvasively infer its mechanical stiffness. Stiffness is recovered from measured deformation by using an appropriate mathematical model and solving an inverse problem. The integration of EI with existing imaging modal- ities can improve their diagnostic and research capabilities. The aim of this work is to develop and evaluate techniques to image and quantify the mechanical properties of soft tissues in three dimensions (3D). To that end, this thesis presents and validates a method by which three dimensional ultrasound images can be used to image and quantify the shear modulus distribution of tissue mimicking phantoms. This work is presented to motivate and justify the use of this elasticity imaging technique in a clinical breast cancer screening study. The imaging methodologies discussed are intended to improve the specificity of mammography practices in general. During the development of these techniques, several issues concerning the accuracy and uniqueness of the result were elucidated. Two new algorithms for 3D EI are designed and characterized in this thesis. The first provides three dimensional motion estimates from ultrasound images of the deforming ma- terial. The novel features include finite element interpolation of the displacement field, inclusion of prior information and the ability to enforce physical constraints. The roles of regularization, mesh resolution and an incompressibility constraint on the accuracy of the measured deformation is quantified. The estimated signal to noise ratio of the measured displacement fields are approximately 1800, 21 and 41 for the axial, lateral and eleva- tional components, respectively. The second algorithm recovers the shear elastic modulus distribution of the deforming material by efficiently solving the three dimensional inverse problem as an optimization problem. This method utilizes finite element interpolations, the adjoint method to evaluate the gradient and a quasi-Newton BFGS method for optimiza- tion. Its novel features include the use of the adjoint method and TVD regularization with piece-wise constant interpolation. A source of non-uniqueness in this inverse problem is identified theoretically, demonstrated computationally, explained physically and overcome practically. Both algorithms were test on ultrasound data of independently characterized tissue mimicking phantoms. The recovered elastic modulus was in all cases within 35% of the reference elastic contrast. Finally, the preliminary application of these techniques to tomosynthesis images showed the feasiblity of imaging an elastic inclusion.

Recognition of Human Action Using Moment-Based Feature

The performance of different classification approaches is evaluated using a view-based approach for motion representation. The view-based approach uses computer vision and image processing techniques to register and process the video sequence. Two motion representations called Motion Energy Images and Motion History Image are then constructed. These representations collapse the temporal component in a way that no explicit temporal analysis or sequence matching is needed. Statistical descriptions are then computed using moment-based features and dimensionality reduction techniques. For these tests, we used 7 Hu moments, which are invariant to scale and translation. Principal Components Analysis is used to reduce the dimensionality of this representation. The system is trained using different subjects performing a set of examples of every action to be recognized. Given these samples, K-nearest neighbor, Gaussian, and Gaussian mixture classifiers are used to recognize new actions. Experiments are conducted using instances of eight human actions (i.e., eight classes) performed by seven different subjects. Comparisons in the performance among these classifiers under different conditions are analyzed and reported. Our main goals are to test this dimensionality-reduced representation of actions, and more importantly to use this representation to compare the advantages of different classification approaches in this recognition task.

Searching the Sky with CONFIGR-STARS

SyNAPSE program of the Defense Advanced Projects Research Agency (HRL Laboratories LLC, subcontract #801881-BS under DARPA prime contract HR0011-09-C-0001); CELEST, a National Science Foundation Science of Learning Center (SBE-0354378)

Sugar matrices in stabilization of bioactives by dehydration

Development of functional foods with bioactive components requires component stability in foods and ingredients. Stabilization of sensitive bioactive components can be achieved by entrapment or encapsulation of these components in solid food matrices. Lactose or trehalose was used as the structure-forming material for the entrapment of hydrophilic ascorbic acid and thiamine hydrochloride or the encapsulation of oil particles containing hydrophobic α-tocopherol. In the delivery of hydrophobic components, milk protein isolate, soy protein isolate, or whey protein isolate were used as emulsifiers and, in some cases, applied in excess amount to form matrices together with sugars. Dehydrated amorphous structures with bioactives were produced by freezing and freeze-drying. Experimental results indicated that: (i) lactose and trehalose showed similar water sorption and glass transition but very different crystallization behavior as pure sugars; (ii) the glass transition of sugar-based systems was slightly affected by the presence of other components in anhydrous systems but followed closely that of sugar after water plasticization; (iii) sugar crystallization in mixture systems was composition-dependent; (iv) the stability of bioactives was better retained in the amorphous matrices, although small losses of stability were observed for hydrophilic components above glass transition and for hydrophobic components as a function of water activity; (v) sugar crystallization caused significant loss of hydrophilic bioactives as a result of the exclusion from the continuous crystalline phase; (vi) loss of hydrophobic bioactives upon sugar crystallization was a result of dramatic change of emulsion properties and the exclusion of oil particles from the protecting structure; (vii) the double layers at the hydrophilic-hydrophobic interfaces improved the stability of hydrophobic bioactives in dehydrated systems. The present study provides information on the physical and chemical stability of sugar-based dehydrated delivery systems, which could be helpful in designing foods and ingredients containing bioactive components with improved storage stability.

Expression in aneuploid Drosophila S2 cells.

Extensive departures from balanced gene dose in aneuploids are highly deleterious. However, we know very little about the relationship between gene copy number and expression in aneuploid cells. We determined copy number and transcript abundance (expression) genome-wide in Drosophila S2 cells by DNA-Seq and RNA-Seq. We found that S2 cells are aneuploid for >43 Mb of the genome, primarily in the range of one to five copies, and show a male genotype ( approximately two X chromosomes and four sets of autosomes, or 2X;4A). Both X chromosomes and autosomes showed expression dosage compensation. X chromosome expression was elevated in a fixed-fold manner regardless of actual gene dose. In engineering terms, the system "anticipates" the perturbation caused by X dose, rather than responding to an error caused by the perturbation. This feed-forward regulation resulted in precise dosage compensation only when X dose was half of the autosome dose. Insufficient compensation occurred at lower X chromosome dose and excessive expression occurred at higher doses. RNAi knockdown of the Male Specific Lethal complex abolished feed-forward regulation. Both autosome and X chromosome genes show Male Specific Lethal-independent compensation that fits a first order dose-response curve. Our data indicate that expression dosage compensation dampens the effect of altered DNA copy number genome-wide. For the X chromosome, compensation includes fixed and dose-dependent components.

Improvement in visual search with practice: mapping learning-related changes in neurocognitive stages of processing.

Practice can improve performance on visual search tasks; the neural mechanisms underlying such improvements, however, are not clear. Response time typically shortens with practice, but which components of the stimulus-response processing chain facilitate this behavioral change? Improved search performance could result from enhancements in various cognitive processing stages, including (1) sensory processing, (2) attentional allocation, (3) target discrimination, (4) motor-response preparation, and/or (5) response execution. We measured event-related potentials (ERPs) as human participants completed a five-day visual-search protocol in which they reported the orientation of a color popout target within an array of ellipses. We assessed changes in behavioral performance and in ERP components associated with various stages of processing. After practice, response time decreased in all participants (while accuracy remained consistent), and electrophysiological measures revealed modulation of several ERP components. First, amplitudes of the early sensory-evoked N1 component at 150 ms increased bilaterally, indicating enhanced visual sensory processing of the array. Second, the negative-polarity posterior-contralateral component (N2pc, 170-250 ms) was earlier and larger, demonstrating enhanced attentional orienting. Third, the amplitude of the sustained posterior contralateral negativity component (SPCN, 300-400 ms) decreased, indicating facilitated target discrimination. Finally, faster motor-response preparation and execution were observed after practice, as indicated by latency changes in both the stimulus-locked and response-locked lateralized readiness potentials (LRPs). These electrophysiological results delineate the functional plasticity in key mechanisms underlying visual search with high temporal resolution and illustrate how practice influences various cognitive and neural processing stages leading to enhanced behavioral performance.

Elucidating the Molecular Composition of Cartilage by Proteomics.

Articular cartilage consists of chondrocytes and two major components, a collagen-rich framework and highly abundant proteoglycans. Most prior studies defining the zonal distribution of cartilage have extracted proteins with guanidine-HCl. However, an unextracted collagen-rich residual is left after extraction. In addition, the high abundance of anionic polysaccharide molecules extracted from cartilage adversely affects the chromatographic separation. In this study, we established a method for removing chondrocytes from cartilage sections with minimal extracellular matrix protein loss. The addition of surfactant to guanidine-HCl extraction buffer improved protein solubility. Ultrafiltration removed interference from polysaccharides and salts. Almost four-times more collagen peptides were extracted by the in situ trypsin digestion method. However, as expected, proteoglycans were more abundant within the guanidine-HCl extraction. These different methods were used to extract cartilage sections from different cartilage layers (superficial, intermediate, and deep), joint types (knee and hip), and disease states (healthy and osteoarthritic), and the extractions were evaluated by quantitative and qualitative proteomic analyses. The results of this study led to the identifications of the potential biomarkers of osteoarthritis (OA), OA progression, and the joint specific biomarkers.

Case-based retrieval of 3-dimensional shapes for the design of metal castings

This paper describes research into retrieval based on 3-dimensional shapes for use in the metal casting industry. The purpose of the system is to advise a casting engineer on the design aspects of a new casting by reference to similar castings which have been prototyped and tested in the past. The key aspects of the system are the orientation of the shape within the mould, the positions of feeders and chills, and particular advice concerning special problems and solutions, and possible redesign. The main focus of this research is the effectiveness of similarity measures based on 3-dimensional shapes. The approach adopted here is to construct similarity measures based on a graphical representation deriving from a shape decomposition used extensively by experienced casting design engineers. The paper explains the graphical representation and discusses similarity measures based on it. Performance measures for the CBR system are given, and the results for trials of the system are presented. The competence of the current case-base is discussed, with reference to a representation of cases as points in an n-dimensional feature space, and its principal components visualization. A refinement of the case base is performed as a result of the competence analysis and the performance of the case-base before and after refinement is compared.