919 resultados para Byrsonima intermedia extract


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Traditional nearest points methods use all the samples in an image set to construct a single convex or affine hull model for classification. However, strong artificial features and noisy data may be generated from combinations of training samples when significant intra-class variations and/or noise occur in the image set. Existing multi-model approaches extract local models by clustering each image set individually only once, with fixed clusters used for matching with various image sets. This may not be optimal for discrimination, as undesirable environmental conditions (eg. illumination and pose variations) may result in the two closest clusters representing different characteristics of an object (eg. frontal face being compared to non-frontal face). To address the above problem, we propose a novel approach to enhance nearest points based methods by integrating affine/convex hull classification with an adapted multi-model approach. We first extract multiple local convex hulls from a query image set via maximum margin clustering to diminish the artificial variations and constrain the noise in local convex hulls. We then propose adaptive reference clustering (ARC) to constrain the clustering of each gallery image set by forcing the clusters to have resemblance to the clusters in the query image set. By applying ARC, noisy clusters in the query set can be discarded. Experiments on Honda, MoBo and ETH-80 datasets show that the proposed method outperforms single model approaches and other recent techniques, such as Sparse Approximated Nearest Points, Mutual Subspace Method and Manifold Discriminant Analysis.

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Existing multi-model approaches for image set classification extract local models by clustering each image set individually only once, with fixed clusters used for matching with other image sets. However, this may result in the two closest clusters to represent different characteristics of an object, due to different undesirable environmental conditions (such as variations in illumination and pose). To address this problem, we propose to constrain the clustering of each query image set by forcing the clusters to have resemblance to the clusters in the gallery image sets. We first define a Frobenius norm distance between subspaces over Grassmann manifolds based on reconstruction error. We then extract local linear subspaces from a gallery image set via sparse representation. For each local linear subspace, we adaptively construct the corresponding closest subspace from the samples of a probe image set by joint sparse representation. We show that by minimising the sparse representation reconstruction error, we approach the nearest point on a Grassmann manifold. Experiments on Honda, ETH-80 and Cambridge-Gesture datasets show that the proposed method consistently outperforms several other recent techniques, such as Affine Hull based Image Set Distance (AHISD), Sparse Approximated Nearest Points (SANP) and Manifold Discriminant Analysis (MDA).

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Background Southeast Asia has been at the epicentre of recent epidemics of emerging and re-emerging zoonotic diseases. Community-based surveillance and control interventions have been heavily promoted but the most effective interventions have not been identified. Objectives This review evaluated evidence for the effectiveness of community-based surveillance interventions at monitoring and identifying emerging infectious disease; the effectiveness of community-based control interventions at reducing rates of emerging infectious disease; and contextual factors that influence intervention effectiveness. Inclusion criteria Participants Communities in Brunei, Cambodia, Indonesia, Laos, Malaysia, Myanmar, the Philippines, Singapore, Thailand and Viet Nam. Types of intervention(s) Non-pharmaceutical, non-vaccine, and community-based surveillance or prevention and control interventions targeting rabies, Nipah virus , dengue, SARS or avian influenza. Types of outcomes Primary outcomes: measures: of infection or disease; secondary outcomes: measures of intervention function. Types of studies Original quantitative studies published in English. Search strategy Databases searched (1980 to 2011): PubMed, CINAHL, ProQuest, EBSCOhost, Web of Science, Science Direct, Cochrane database of systematic reviews, WHOLIS, British Development Library, LILACS, World Bank (East Asia), Asian Development Bank. Methodological quality Two independent reviewers critically appraised studies using standard Joanna Briggs Institute instruments. Disagreements were resolved through discussion. Data extraction A customised tool was used to extract quantitative data on intervention(s), populations, study methods, and primary and secondary outcomes; and qualitative contextual information or narrative evidence about interventions. Data synthesis Data was synthesised in a narrative summary with the aid of tables. Meta-analysis was used to statistically pool quantitative results. Results Fifty-seven studies were included. Vector control interventions using copepods, environmental cleanup and education are effective and sustainable at reducing dengue in rural and urban communities, whilst insecticide spraying is effective in urban outbreak situations. Community-based surveillance interventions can effectively identify avian influenza in backyard flocks, but have not been broadly applied. Outbreak control interventions for Nipah virus and SARS are effective but may not be suitable for ongoing control. Canine vaccination and education is more acceptable than culling, but still fails to reach coverage levels required to effectively control rabies. Contextual factors were identified that influence community engagement with, and ultimately effectiveness of, interventions. Conclusion Despite investment in community-based disease control and surveillance in Southeast Asia, published evidence evaluating interventions is limited in quantity and quality. Nonetheless this review identified a number of effective interventions, and several contextual factors influencing effectiveness. Identification of the best programs will require comparative evidence of effectiveness acceptability, cost-effectiveness and sustainability.

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In vitro analyses of basement membrane invasiveness employing Matrigel (a murine tumor extract rich in basement membrane components) have been performed on human breast cancer model systems. Constitutive invasiveness of different human breast cancer (HBC) cell lines has been examined as well as regulation by steroid hormones, growth factors, and oncogenes. Carcinoma cells exhibiting a mesenchymal-like phenotype (vimentin expression, lack of cell border associated uvomorulin) show dramatically increased motility, invasiveness, and metastatic potential in nude mice. These findings support the hypothesis that epithelial to mesenchymal transition (EMT)-like events may be instrumental in the metastatic progression of human breast cancer. The MCF-7 subline MCF-7ADR appears to have undergone such a transition. The importance of such a transition may be reflected in the emergence of vimentin expression as an indicator of poor prognosis in HBC. Matrix degradation and laminin recognition are highlighted as potential targets for antimetastatic therapy, and analyses of laminin attachment and the matrix metalloproteinase (MMP) family in HBC cell lines are summarized. Matrigel-based assays have proved useful in the study of the molecular mechanisms of basement membrane invasiveness, their regulation in HBC cells, and their potential as targets for antimetastatic therapy.

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This paper firstly presents the benefits and critical challenges on the use of Bluetooth and Wi-Fi for crowd data collection and monitoring. The major challenges include antenna characteristics, environment’s complexity and scanning features. Wi-Fi and Bluetooth are compared in this paper in terms of architecture, discovery time, popularity of use and signal strength. Type of antennas used and the environment’s complexity such as trees for outdoor and partitions for indoor spaces highly affect the scanning range. The aforementioned challenges are empirically evaluated by “real” experiments using Bluetooth and Wi-Fi Scanners. The issues related to the antenna characteristics are also highlighted by experimenting with different antenna types. Novel scanning approaches including Overlapped Zones and Single Point Multi-Range detection methods will be then presented and verified by real-world tests. These novel techniques will be applied for location identification of the MAC IDs captured that can extract more information about people movement dynamics.

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Expression of the intermediate filament protein vimentin, and loss of the cellular adhesion protein uvomorulin (E-cadherin) have been associated with increased invasiveness of established human breast cancer cell lines in vitro and in vivo. In the current study, we have further examined these relationships in oncogenically transformed human mammary epithelial cells. A normal human mammary epithelial strain, termed 184, was previously immortalized with benzo[a]pyrene, and two distinct sublines were derived (A1N4 and 184B5). These sublines were infected with retroviral vectors containing a single or two oncogenes of the nuclear, cytoplasmic, and plasma membrane-associated type (v-rasH, v-rasKi, v -mos, SV40T and c -myc). All infectants have been previously shown to exhibit some aspects of phenotypic transformation. In the current study, cellular invasiveness was determined in vitro using Matrigel, a reconstituted basement membrane extract. Lineage-specific differences were observed with respect to low constitutive invasiveness and invasive changes after infection with ras, despite similar ras-induced transformation of each line. Major effects on cellular invasiveness were observed after infection of the cells with two different oncogenes (v-rasH + SV40T and v -rasH + v -mos). In contrast, the effects of single oncogenes were only modest or negligible. All oncogenic infectants demonstrated increased attachment to laminin, but altered secretion of the 72 kDa and 92 kDa gelatinases was not associated with any aspect of malignant progression. Each of the two highly invasive double oncogene transformants were vimentinpositive and uvomorulin-negative, a phenotype indicative of the epithelial-mesenchymal transition (EMT) previously associated with invasiveness of established human breast cancer cell lines. Weakly invasive untransformed mammary epithelial cells in this study were positive for both vimentin and uvomorulin, suggesting that uvomorulin may over-ride the otherwise vimentin-associated invasiveness.

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Hindered amine light stabilisers (HALS) are the most effective antioxidants currently available for polymer systems in post-production, in-service applications, yet the mechanism of their action is still not fully understood. Structural characterisation of HALS in polymer matrices, particularly the identification of structural modifications brought about by oxidative conditions, is critical to aid mechanistic understanding of the prophylactic effects of these molecules. In this work, electrospray ionisation tandem mass spectrometry (ESI-MS/MS) was applied to the analysis of a suite of commercially available 2,2,6,6-tetramethylpiperidine-based HALS. Fragmentation mechanisms for the \[M + H](+) ions are proposed, which provide a rationale for the product ions observed in the MS/MS and MS(3) mass spectra of N-H, N-CH(3), N-C(O)CH(3) and N-OR containing HALS (where R is an alkyl substituent). A common product ion at m/z 123 was identified for the group of antioxidants containing N-H, N-CH3 or N-C(0)CH3 functionality, and this product ion was employed in precursor ion scans on a triple quadrupole mass spectrometer to identify the HALS species present in a crude extract from of a polyester-based coil coating. Using MS/MS, two degradation products were unambiguously identified. This technique provides a simple and selective approach to monitoring HALS structures within complex matrices. Copyright (C) 2010 John Wiley & Sons, Ltd.

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Limbal stem cell deficiency leads to conjunctivalisation of the cornea and subsequent loss of vision. The recent development of transplantation of ex-vivo amplified corneal epithelium, derived from limbal stem cells, has shown promise in treating this challenging condition. The purpose of this research was to compare a variety of cell sheet carriers for their suitability in creating a confluent corneal epithelium from amplified limbal stem cells. Cadaveric donor limbal cells were cultured using an explant technique, free of 3T3 feeder cells, on a variety of cell sheet carriers, including denuded amniotic membrane, Matrigel, Myogel and stromal extract. Comparisons in rate of growth and degree of differentiation were made, using immunocytochemistry (CK3, CK19 and ABCG2). The most rapid growth was observed on Myogel and denuded amniotic membrane, these two cell carriers also provided the most reliable substrata for achieving confluence. The putative limbal stem cell marker, ABCG2, stained positively on cells grown over Myogel and Matrigel but not for those propagated on denuded amniotic membrane. In the clinical setting amniotic membrane has been demonstrated to provide a suitable carrier for limbal stem cells and the resultant epithelium has been shown to be successful in treating limbal stem cell deficiency. Myogel may provide an alternative cell carrier with a further reduction in risk as it is has the potential to be derived from an autologous muscle biopsy in the clinical setting.

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Existing techniques for automated discovery of process models from event logs largely focus on extracting flat process models. In other words, they fail to exploit the notion of subprocess, as well as structured error handling and repetition constructs provided by contemporary process modeling notations, such as the Business Process Model and Notation (BPMN). This paper presents a technique for automated discovery of BPMN models containing subprocesses, interrupting and non-interrupting boundary events, and loop and multi-instance markers. The technique analyzes dependencies between data attributes associated with events, in order to identify subprocesses and to extract their associated logs. Parent process and subprocess models are then discovered separately using existing techniques for flat process model discovery. Finally, the resulting models and logs are heuristically analyzed in order to identify boundary events and markers. A validation with one synthetic and two real-life logs shows that process models derived using the proposed technique are more accurate and less complex than those derived with flat process model discovery techniques.

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Introduction Natural product provenance is important in the food, beverage and pharmaceutical industries, for consumer confidence and with health implications. Raman spectroscopy has powerful molecular fingerprint abilities. Surface Enhanced Raman Spectroscopy’s (SERS) sharp peaks allow distinction between minimally different molecules, so it should be suitable for this purpose. Methods Naturally caffeinated beverages with Guarana extract, coffee and Red Bull energy drink as a synthetic caffeinated beverage for comparison (20 µL ea.) were reacted 1:1 with Gold nanoparticles functionalised with anti-caffeine antibody (ab15221) (10 minutes), air dried and analysed in a micro-Raman instrument. The spectral data was processed using Principle Component Analysis (PCA). Results The PCA showed Guarana sourced caffeine varied significantly from synthetic caffeine (Red Bull) on component 1 (containing 76.4% of the variance in the data). See figure 1. The coffee containing beverages, and in particular Robert Timms (instant coffee) were very similar on component 1, but the barista espresso showed minor variance on component 1. Both coffee sourced caffeine samples varied with red Bull on component 2, (20% of variance). ************************************************************ Figure 1 PCA comparing a naturally caffeinated beverage containing Guarana with coffee. ************************************************************ Discussion PCA is an unsupervised multivariate statistical method that determines patterns within data. Figure 1 shows Caffeine in Guarana is notably different to synthetic caffeine. Other researchers have revealed that caffeine in Guarana plants is complexed with tannins. Naturally sourced/ lightly processed caffeine (Monster Energy, Espresso) are more inherently different than synthetic (Red Bull) /highly processed (Robert Timms) caffeine, in figure 1, which is consistent with this finding and demonstrates this technique’s applicability. Guarana provenance is important because it is still largely hand produced and its demand is escalating with recognition of its benefits. This could be a powerful technique for Guarana provenance, and may extend to other industries where provenance / authentication are required, e.g. the wine or natural pharmaceuticals industries.

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Adipose tissue forms when basement membrane extract (Matrigel™) and fibroblast growth factor-2 (FGF-2) are added to our mouse tissue engineering chamber model. A mouse tumor extract, Matrigel is unsuitable for human clinical application, and finding an alternative to Matrigel is essential. In this study we generated adipose tissue in the chamber model without using Matrigel by controlled release of FGF-2 in a type I collagen matrix. FGF-2 was impregnated into biodegradable gelatin microspheres for its slow release. The chambers were filled with these microspheres suspended in 60 μL collagen gel. Injection of collagen containing free FGF-2 or collagen containing gelatin microspheres with buffer alone served as controls. When chambers were harvested 6 weeks after implantation, the volume and weight of the tissue obtained were higher in the group that received collagen and FGF-2 impregnated microspheres than in controls. Histologic analysis of tissue constructs showed the formation of de novo adipose tissue accompanied by angiogenesis. In contrast, control groups did not show extensive adipose tissue formation. In conclusion, this study has shown that de novo formation of adipose tissue can be achieved through controlled release of FGF-2 in collagen type I in the absence of Matrigel.

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Digital forensics concerns the analysis of electronic artifacts to reconstruct events such as cyber crimes. This research produced a framework to support forensic analyses by identifying associations in digital evidence using metadata. It showed that metadata based associations can help uncover the inherent relationships between heterogeneous digital artifacts thereby aiding reconstruction of past events by identifying artifact dependencies and time sequencing. It also showed that metadata association based analysis is amenable to automation by virtue of the ubiquitous nature of metadata across forensic disk images, files, system and application logs and network packet captures. The results prove that metadata based associations can be used to extract meaningful relationships between digital artifacts, thus potentially benefiting real-life forensics investigations.

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Invasion of extracellular matrices is crucial to a number of physiological and pathophysiological states, including tumor cell metastasis, arthritis, embryo implantation, wound healing, and early development. To isolate invasion from the additional complexities of these scenarios a number of in vitro invasion assays have been developed over the years. Early studies employed intact tissues, like denuded amniotic membrane (1) or embryonic chick heart fragments (2), however recently, purified matrix components or complex matrix extracts have been used to provide more uniform and often more rapid analyses (for examples, see the following integrin studies). Of course, the more holistic view of invasion offered in the earlier assays is valuable and cannot be fully reproduced in these more rapid assays, but advantages of reproducibility among replicates, ease of preparation and analysis, and overall high throughput favor the newer assays. In this chapter, we will focus on providing detailed protocols for Matrigel-based assays (Matrigel=reconstituted basement membrane; reviewed in ref. (3)). Matrigel is an extract from the transplantable Engelbreth-Holm-Swarm murine sarcoma that deposits a multilammelar basement membrane. Matrigel is available commercially (Becton Dickinson, Bedford, MA), and can be manipulated as a liquid at 4°C into a variety of different formats. Alternatively, cell culture inserts precoated with Matrigel can be purchased for even greater simplicity.

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Acoustic recordings of the environment are an important aid to ecologists monitoring biodiversity and environmental health. However, rapid advances in recording technology, storage and computing make it possible to accumulate thousands of hours of recordings, of which, ecologists can only listen to a small fraction. The big-data challenge addressed in this paper is to visualize the content of long-duration audio recordings on multiple scales, from hours, days, months to years. The visualization should facilitate navigation and yield ecologically meaningful information. Our approach is to extract (at one minute resolution) acoustic indices which reflect content of ecological interest. An acoustic index is a statistic that summarizes some aspect of the distribution of acoustic energy in a recording. We combine indices to produce false-color images that reveal acoustic content and facilitate navigation through recordings that are months or even years in duration.

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Service mismatches involve the adaptation of structural and behavioural interfaces of services, which in practice incurs long lead times through manual, coding e ort. We propose a framework, complementary to conventional service adaptation, to extract comprehensive and seman- tically normalised service interfaces, useful for interoperability in large business networks and the Internet of Services. The framework supports introspection and analysis of large and overloaded operational signa- tures to derive focal artefacts, namely the underlying business objects of services. A more simpli ed and comprehensive service interface layer is created based on these, and rendered into semantically normalised in- terfaces, given an ontology accrued through the framework from service analysis history. This opens up the prospect of supporting capability comparisons across services, and run-time request backtracking and ad- justment, as consumers discover new features of a service's operations through corresponding features of similar services. This paper provides a rst exposition of the service interface synthesis framework, describing patterns having novel requirements for unilateral service adaptation, and algorithms for interface introspection and business object alignment. A prototype implementation and analysis of web services drawn from com- mercial logistic systems are used to validate the algorithms and identify open challenges and future research directions.