Determination of organophosphorus pesticides in cucumber and potato by stir bar sorptive extraction

Organophosphorus pesticides (OPPs) in vegetables were determined by stir bar sorptive extraction (SBSE) and capillary gas chromatography with thermionic specific detection (TSD). Hydroxy-terminated polydimethylsioxane (PDMS) prepared by sol-gel method was used as extraction phase. The effects of extraction temperature, salting out, extraction time on extraction efficiency were studied. The detection limits of OPPs in water were <= 1.2 ng/l. This method was also applied to the analysis of OPPs in vegetable samples and matrix effect was studied. Linear ranges of OPPs in vegetable samples were 0.05-50 ng/g with detection limits <= 0. 15 ng/g and the repeatability of the method was less than 20% relative standard deviation. (c) 2005 Elsevier B.V. All rights reserved.

Visual Segmentation-Based Data Record Extraction From Web Documents

Li, Longzhuang, Liu, Yonghuai, Obregon, A., Weatherston, M. Visual Segmentation-Based Data Record Extraction From Web Documents. Proceedings of IEEE International Conference on Information Reuse and Integration, 2007, pp. 502-507. Sponsorship: IEEE

A survey of fingerprint classification Part I: taxonomies on feature extraction methods and learning models

This paper reviews the fingerprint classification literature looking at the problem from a double perspective. We first deal with feature extraction methods, including the different models considered for singular point detection and for orientation map extraction. Then, we focus on the different learning models considered to build the classifiers used to label new fingerprints. Taxonomies and classifications for the feature extraction, singular point detection, orientation extraction and learning methods are presented. A critical view of the existing literature have led us to present a discussion on the existing methods and their drawbacks such as difficulty in their reimplementation, lack of details or major differences in their evaluations procedures. On this account, an experimental analysis of the most relevant methods is carried out in the second part of this paper, and a new method based on their combination is presented.

Extraction of Caffeine from Energy Drinks

A simple procedure for the isolation of caffeine from energy drinks by solid phase extraction on a C18 cartridge. Quantitative analysis of the amount of caffeine by LC/MS is determined by referencing a standard curve.

Extraction and Clustering of Motion Trajectories in Video

A system is described that tracks moving objects in a video dataset so as to extract a representation of the objects' 3D trajectories. The system then finds hierarchical clusters of similar trajectories in the video dataset. Objects' motion trajectories are extracted via an EKF formulation that provides each object's 3D trajectory up to a constant factor. To increase accuracy when occlusions occur, multiple tracking hypotheses are followed. For trajectory-based clustering and retrieval, a modified version of edit distance, called longest common subsequence (LCSS) is employed. Similarities are computed between projections of trajectories on coordinate axes. Trajectories are grouped based, using an agglomerative clustering algorithm. To check the validity of the approach, experiments using real data were performed.

Biologically Inspired Approaches to Automated Feature Extraction and Target Recognition

Ongoing research at Boston University has produced computational models of biological vision and learning that embody a growing corpus of scientific data and predictions. Vision models perform long-range grouping and figure/ground segmentation, and memory models create attentionally controlled recognition codes that intrinsically cornbine botton-up activation and top-down learned expectations. These two streams of research form the foundation of novel dynamically integrated systems for image understanding. Simulations using multispectral images illustrate road completion across occlusions in a cluttered scene and information fusion from incorrect labels that are simultaneously inconsistent and correct. The CNS Vision and Technology Labs (cns.bu.edulvisionlab and cns.bu.edu/techlab) are further integrating science and technology through analysis, testing, and development of cognitive and neural models for large-scale applications, complemented by software specification and code distribution.

Rule Extraction, Fuzzy ARTMAP, and Medical Databases

This paper shows how knowledge, in the form of fuzzy rules, can be derived from a self-organizing supervised learning neural network called fuzzy ARTMAP. Rule extraction proceeds in two stages: pruning removes those recognition nodes whose confidence index falls below a selected threshold; and quantization of continuous learned weights allows the final system state to be translated into a usable set of rules. Simulations on a medical prediction problem, the Pima Indian Diabetes (PID) database, illustrate the method. In the simulations, pruned networks about 1/3 the size of the original actually show improved performance. Quantization yields comprehensible rules with only slight degradation in test set prediction performance.

3D refraction correction and extraction of clinical parameters from spectral domain optical coherence tomography of the cornea.

Capable of three-dimensional imaging of the cornea with micrometer-scale resolution, spectral domain-optical coherence tomography (SDOCT) offers potential advantages over Placido ring and Scheimpflug photography based systems for accurate extraction of quantitative keratometric parameters. In this work, an SDOCT scanning protocol and motion correction algorithm were implemented to minimize the effects of patient motion during data acquisition. Procedures are described for correction of image data artifacts resulting from 3D refraction of SDOCT light in the cornea and from non-idealities of the scanning system geometry performed as a pre-requisite for accurate parameter extraction. Zernike polynomial 3D reconstruction and a recursive half searching algorithm (RHSA) were implemented to extract clinical keratometric parameters including anterior and posterior radii of curvature, central cornea optical power, central corneal thickness, and thickness maps of the cornea. Accuracy and repeatability of the extracted parameters obtained using a commercial 859nm SDOCT retinal imaging system with a corneal adapter were assessed using a rigid gas permeable (RGP) contact lens as a phantom target. Extraction of these parameters was performed in vivo in 3 patients and compared to commercial Placido topography and Scheimpflug photography systems. The repeatability of SDOCT central corneal power measured in vivo was 0.18 Diopters, and the difference observed between the systems averaged 0.1 Diopters between SDOCT and Scheimpflug photography, and 0.6 Diopters between SDOCT and Placido topography.

Nutrient enrichment effects on mangrove sediments from differing tree height zones in Bocas del Toro, Panama

Red mangrove (Rhizophora mangle L.) forests have distinct tree-height zones, with tall trees fringing the ocean and shorter trees in interior stands. A long-term nitrogen (N) and phosphorus (P) fertilization experiment in Almirante Bay, Bocas del Toro Province, Panama has shown that tree-height zonation is primarily related to nutrient limitation. This experiment was used to test the effects of in-situ nutrient additions and tree zonation on mangrove sediments. The sediments underlying the experimental R. mangle trees were sampled and N₂ fixation, ¹⁵N, chlorophyll a, percent N and P, and percent organic biomass were quantified. Both N and P additions significantly affected almost every parameter measured in both zones within this experiment. These results are likely to have implications for management since N and P inputs are predicted to increase throughout the tropics and subtropics worldwide.

Interaction between 3’,5’-cyclic monophosphate, volume-regulated anion channels and the Na+-HCO3- cotransporter NBCe1 in the regulation of nutrient- and hypotonicity-induced insulin release from rat pancreatic islets and tumoral insulin-producing BRIN-BD11 cells

info:eu-repo/semantics/published

Nutrient- and hypotonicity-induced insulin secretion: effects of cyclic AMP analogs, IBMX, tenidap and 5-nitro-2-(3-phenylpropylamino)benzoic acid

info:eu-repo/semantics/published

Analysis of ocean power extraction capabilites of a rotary wave energy conversion system

Gemstone Team WAVES (Water and Versatile Energy Systems)

A range-wide experiment to investigate nutrient and soil moisture interactions in loblolly pine plantations

© 2015 by the authors.The future climate of the southeastern USA is predicted to be warmer, drier and more variable in rainfall, which may increase drought frequency and intensity. Loblolly pine (Pinus taeda) is the most important commercial tree species in the world and is planted on ~11 million ha within its native range in the southeastern USA. A regional study was installed to evaluate effects of decreased rainfall and nutrient additions on loblolly pine plantation productivity and physiology. Four locations were established to capture the range-wide variability of soil and climate. Treatments were initiated in 2012 and consisted of a factorial combination of throughfall reduction (approximate 30% reduction) and fertilization (complete suite of nutrients). Tree and stand growth were measured at each site. Results after two growing seasons indicate a positive but variable response of fertilization on stand volume increment at all four sites and a negative effect of throughfall reduction at two sites. Data will be used to produce robust process model parameterizations useful for simulating loblolly pine growth and function under future, novel climate and management scenarios. The resulting improved models will provide support for developing management strategies to increase pine plantation productivity and carbon sequestration under a changing climate.

Different Mechanisms Confer Gradual Control and Memory at Nutrient- and Stress-Regulated Genes in Yeast.

Cells respond to environmental stimuli by fine-tuned regulation of gene expression. Here we investigated the dose-dependent modulation of gene expression at high temporal resolution in response to nutrient and stress signals in yeast. The GAL1 activity in cell populations is modulated in a well-defined range of galactose concentrations, correlating with a dynamic change of histone remodeling and RNA polymerase II (RNAPII) association. This behavior is the result of a heterogeneous induction delay caused by decreasing inducer concentrations across the population. Chromatin remodeling appears to be the basis for the dynamic GAL1 expression, because mutants with impaired histone dynamics show severely truncated dose-response profiles. In contrast, the GRE2 promoter operates like a rapid off/on switch in response to increasing osmotic stress, with almost constant expression rates and exclusively temporal regulation of histone remodeling and RNAPII occupancy. The Gal3 inducer and the Hog1 mitogen-activated protein (MAP) kinase seem to determine the different dose-response strategies at the two promoters. Accordingly, GAL1 becomes highly sensitive and dose independent if previously stimulated because of residual Gal3 levels, whereas GRE2 expression diminishes upon repeated stimulation due to acquired stress resistance. Our analysis reveals important differences in the way dynamic signals create dose-sensitive gene expression outputs.

Evaluating Alternative Nutrient Sources in Subsistence-Level Aquaponic Systems

Many food production methods are both economically and environmentally unsustainable. Our project investigated aquaponics, an alternative method of agriculture that could address these issues. Aquaponics combines fish and plant crop production in a symbiotic, closed-loop system. We aimed to reduce the initial and operating costs of current aquaponic systems by utilizing alternative feeds. These improvements may allow for sustainable implementation of the system in rural or developing regions. We conducted a multi-phase process to determine the most affordable and effective feed alternatives for use in an aquaponic system. At the end of two preliminary phases, soybean meal was identified as the most effective potential feed supplement. In our final phase, we constructed and tested six full-scale aquaponic systems of our own design. Data showed that soybean meal can be used to reduce operating costs and reliance on fishmeal. However, a more targeted investigation is needed to identify the optimal formulation of alternative feed blends.