906 resultados para DENDRITIC BRANCHING FEATURES
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A new optimal control model of the interactions between a growing tumour and the host immune system along with an immunotherapy treatment strategy is presented. The model is based on an ordinary differential equation model of interactions between the growing tu- mour and the natural killer, cytotoxic T lymphocyte and dendritic cells of the host immune system, extended through the addition of a control function representing the application of a dendritic cell treat- ment to the system. The numerical solution of this model, obtained from a multi species Runge–Kutta forward-backward sweep scheme, is described. We investigate the effects of varying the maximum al- lowed amount of dendritic cell vaccine administered to the system and find that control of the tumour cell population is best effected via a high initial vaccine level, followed by reduced treatment and finally cessation of treatment. We also found that increasing the strength of the dendritic cell vaccine causes an increase in the number of natural killer cells and lymphocytes, which in turn reduces the growth of the tumour.
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This paper presents practical vision-based collision avoidance for objects approximating a single point feature. Using a spherical camera model, a visual predictive control scheme guides the aircraft around the object along a conical spiral trajectory. Visibility, state and control constraints are considered explicitly in the controller design by combining image and vehicle dynamics in the process model, and solving the nonlinear optimization problem over the resulting state space. Importantly, range is not required. Instead, the principles of conical spiral motion are used to design an objective function that simultaneously guides the aircraft along the avoidance trajectory, whilst providing an indication of the appropriate point to stop the spiral behaviour. Our approach is aimed at providing a potential solution to the See and Avoid problem for unmanned aircraft and is demonstrated through a series.
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Osteocyte cells are the most abundant cells in human bone tissue. Due to their unique morphology and location, osteocyte cells are thought to act as regulators in the bone remodelling process, and are believed to play an important role in astronauts’ bone mass loss after long-term space missions. There is increasing evidence showing that an osteocyte’s functions are highly affected by its morphology. However, changes in an osteocyte’s morphology under an altered gravity environment are still not well documented. Several in vitro studies have been recently conducted to investigate the morphological response of osteocyte cells to the microgravity environment, where osteocyte cells were cultured on a two-dimensional flat surface for at least 24 hours before microgravity experiments. Morphology changes of osteocyte cells in microgravity were then studied by comparing the cell area to 1g control cells. However, osteocyte cells found in vivo are with a more 3D morphology, and both cell body and dendritic processes are found sensitive to mechanical loadings. A round shape osteocyte’s cells support a less stiff cytoskeleton and are more sensitive to mechanical stimulations compared with flat cellular morphology. Thus, the relative flat and spread shape of isolated osteocytes in 2D culture may greatly hamper their sensitivity to a mechanical stimulus, and the lack of knowledge on the osteocyte’s morphological characteristics in culture may lead to subjective and noncomprehensive conclusions of how altered gravity impacts on an osteocyte’s morphology. Through this work empirical models were developed to quantitatively predicate the changes of morphology in osteocyte cell lines (MLO-Y4) in culture, and the response of osteocyte cells, which are relatively round in shape, to hyper-gravity stimulation has also been investigated. The morphology changes of MLO-Y4 cells in culture were quantified by measuring cell area and three dimensionless shape features including aspect ratio, circularity and solidity by using widely accepted image analysis software (ImageJTM). MLO-Y4 cells were cultured at low density (5×103 per well) and the changes in morphology were recorded over 10 hours. Based on the data obtained from the imaging analysis, empirical models were developed using the non-linear regression method. The developed empirical models accurately predict the morphology of MLO-Y4 cells for different culture times and can, therefore, be used as a reference model for analysing MLO-Y4 cell morphology changes within various biological/mechanical studies, as necessary. The morphological response of MLO-Y4 cells with a relatively round morphology to hyper-gravity environment has been investigated using a centrifuge. After 2 hours culture, MLO-Y4 cells were exposed to 20g for 30mins. Changes in the morphology of MLO-Y4 cells are quantitatively analysed by measuring the average value of cell area and dimensionless shape factors such as aspect ratio, solidity and circularity. In this study, no significant morphology changes were detected in MLO-Y4 cells under a hyper-gravity environment (20g for 30 mins) compared with 1g control cells.
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The genesis of ferruginous nodules and pisoliths in soils and weathering profiles of coastal southern and eastern Australia has long been debated. It is not clear whether iron (Fe) nodules are redox accumulations, residues of Miocene laterite duricrust, or the products of contemporary weathering of Fe-rich sedimentary rocks. This study combines a catchment-wide survey of Fe nodule distribution in Poona Creek catchment (Fraser Coast, Queensland) with detailed investigations of a representative ferric soil profile to show that Fe nodules are derived from Fe-rich sandstones. Where these crop out, they are broken down, transported downslope by colluvial processes, and redeposited. Chemical and physical weathering transforms these eroded rock fragments into non-magnetic Fe nodules. Major features of this transformation include lower hematite/goethite and kaolinite/gibbsite ratios, increased porosity, etching of quartz grains, and development of rounded morphology and a smooth outer cortex. Iron nodules are commonly concentrated in ferric horizons. We show that these horizons form as the result of differential biological mixing of the soil. Bioturbation gradually buries nodules and rock fragments deposited at the surface of the soil, resulting in a largely nodule-free 'biomantle' over a ferric 'stone line'. Maghemite-rich magnetic nodules are a prominent feature of the upper half of the profile. These are most likely formed by the thermal alteration of non-magnetic nodules located at the top of the profile during severe bushfires. They are subsequently redistributed through the soil profile by bioturbation. Iron nodules occurring in the study area are products of contemporary weathering of Fe-rich rock units. They are not laterite duricrust residues nor are they redox accumulations, although redox-controlled dissolution/re-precipitation is an important component of post-depositional modification of these Fe nodules.
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This paper investigates the characteristics of ventures which have the potential to reach high growth and compares this with ‘everyday’ new ventures. Findings of interest in this paper include: • HP firms are characterised by higher human capital, are more likely to have a team of founders, are more likely to be product based. • HP firms are more likely to achieve more extreme levels of growth (both positive and negative). • HP ventures that make a loss are more likely to do so early in the venture process. Those that do hold on show that there can higher levels of loss made later on in firm development. HP firms have higher resource needs, in terms of seeking external finance, but are no more likely to receive external finance than regular firms.
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Background Viral and bacterial respiratory tract infections in early-life are linked to the development of allergic airway inflammation and asthma. However, the mechanisms involved are not well understood. We have previously shown that neonatal and infant, but not adult, chlamydial lung infections in mice permanently alter inflammatory phenotype and physiology to increase the severity of allergic airway disease by increasing lung interleukin (IL)-13 expression, mucus hyper-secretion and airway hyper-responsiveness. This occurred through different mechanisms with infection at different ages. Neonatal infection suppressed inflammatory responses but enhanced systemic dendritic cell:T-cell IL-13 release and induced permanent alterations in lung structure (i.e., increased the size of alveoli). Infant infection enhanced inflammatory responses but had no effect on lung structure. Here we investigated the role of hematopoietic cells in these processes using bone marrow chimera studies. Methodology/Principal Findings Neonatal (<24-hours-old), infant (3-weeks-old) and adult (6-weeks-old) mice were infected with C. muridarum. Nine weeks after infection bone marrow was collected and transferred into recipient age-matched irradiated naïve mice. Allergic airway disease was induced (8 weeks after adoptive transfer) by sensitization and challenge with ovalbumin. Reconstitution of irradiated naïve mice with bone marrow from mice infected as neonates resulted in the suppression of the hallmark features of allergic airway disease including mucus hyper-secretion and airway hyper-responsiveness, which was associated with decreased IL-13 levels in the lung. In stark contrast, reconstitution with bone marrow from mice infected as infants increased the severity of allergic airway disease by increasing T helper type-2 cell cytokine release (IL-5 and IL-13), mucus hyper-secretion, airway hyper-responsiveness and IL-13 levels in the lung. Reconstitution with bone marrow from infected adult mice had no effects. Conclusions These results suggest that an infant chlamydial lung infection results in long lasting alterations in hematopoietic cells that increases the severity of allergic airway disease in later-life.
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Highly sensitive infrared cameras can produce high-resolution diagnostic images of the temperature and vascular changes of breasts. Wavelet transform based features are suitable in extracting the texture difference information of these images due to their scale-space decomposition. The objective of this study is to investigate the potential of extracted features in differentiating between breast lesions by comparing the two corresponding pectoral regions of two breast thermograms. The pectoral regions of breastsare important because near 50% of all breast cancer is located in this region. In this study, the pectoral region of the left breast is selected. Then the corresponding pectoral region of the right breast is identified. Texture features based on the first and the second sets of statistics are extracted from wavelet decomposed images of the pectoral regions of two breast thermograms. Principal component analysis is used to reduce dimension and an Adaboost classifier to evaluate classification performance. A number of different wavelet features are compared and it is shown that complex non-separable 2D discrete wavelet transform features perform better than their real separable counterparts.
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Purpose/Objective: The basis for poor outcomes in some patients post transfusion remains largely unknown. Despite leukodepletion, there is still evidence of immunomodulatory effects of transfusion that require further study. In addition, there is evidence that the age of blood components transfused significantly affects patient outcomes. Myeloid dendritic cell (DC) and monocyte immune function were studied utilising an in vitro whole blood model of transfusion. Materials and methods: Freshly collected (‘recipient’) whole blood was cultured with ABO compatible leukodepleted PRBC at 25% blood replacement-volume (6hrs). PRBC were assayed at [Day (D) 2, 14, 28and 42 (date-of expiry)]. In parallel, LPS or Zymosan (Zy) were added to mimic infection. Recipients were maintained for the duration of the time course (2 recipients, 4 PRBC units, n = 8).Recipient DC and monocyte intracellular cytokines and chemokines (IL-6, IL-10, IL-12,TNF-a, IL-1a, IL-8, IP-10, MIP-1a, MIP-1b, MCP-1) were measured using flow cytometry. Changes in immune response were calculated by comparison to a parallel no transfusion control (Wilcoxin matched pairs). Influence of storage age was calculated using ANOVA. Results: Significant suppression of DC and monocyte inflammatory responses were evident. DC and monocyte production of IL-1a was reduced following exposure to PRBC regardless of storage age (P < 0.05 at all time points). Storage independent PRBC mediated suppression of DC and monocyte IL-1a was also evident in cultures costimulated with Zy. In cultures co-stimulated with either LPS or Zy, significant suppression of DC and monocyte TNF-a and IL-6 was also evident. PRBC storage attenuated monocyte TNF-a production when co-cultured with LPS (P < 0.01 ANOVA). DC and monocyte production of MIP-1a was significantly reduced following exposure to PRBC (DC: P < 0.05 at D2, 28, 42; Monocyte P < 0.05 all time points). In cultures co-stimulated with LPS and zymosan, a similar suppression of MIP-1a production was also evident, and production of both DC and monocyte MIP-1b and IP-10 were also significantly reduced. Conclusions: The complexity of the transfusion context was reflected in the whole blood approach utilised. Significant suppression of these key DC and monocyte immune responses may contribute to patient outcomes, such as increased risk of infection and longer hospital stay, following blood transfusion.
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Physical and chemical properties of biodiesel are influenced by structural features of the fatty acids, such as chain length, degree of unsaturation and branching of the carbon chain. This study investigated if microalgal fatty acid profiles are suitable for biodiesel characterization and species selection through Preference Ranking Organisation Method for Enrichment Evaluation (PROMETHEE) and Graphical Analysis for Interactive Assistance (GAIA) analysis. Fatty acid methyl ester (FAME) profiles were used to calculate the likely key chemical and physical properties of the biodiesel [cetane number (CN), iodine value (IV), cold filter plugging point, density, kinematic viscosity, higher heating value] of nine microalgal species (this study) and twelve species from the literature, selected for their suitability for cultivation in subtropical climates. An equal-parameter weighted (PROMETHEE-GAIA) ranked Nannochloropsis oculata, Extubocellulus sp. and Biddulphia sp. highest; the only species meeting the EN14214 and ASTM D6751-02 biodiesel standards, except for the double bond limit in the EN14214. Chlorella vulgaris outranked N. oculata when the twelve microalgae were included. Culture growth phase (stationary) and, to a lesser extent, nutrient provision affected CN and IV values of N. oculata due to lower eicosapentaenoic acid (EPA) contents. Application of a polyunsaturated fatty acid (PUFA) weighting to saturation led to a lower ranking of species exceeding the double bond EN14214 thresholds. In summary, CN, IV, C18:3 and double bond limits were the strongest drivers in equal biodiesel parameter-weighted PROMETHEE analysis.
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We demonstrate an unusual shape transformation of Ag nanospheres into {111}-oriented Au–Ag dendritic nanostructures by a galvanic replacement reaction in the ionic liquid (IL) 1-butyl-3-methylimidazolium tetrafluoroborate ([BMIM][BF4]).
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In this work a simple approach to the creation of highly dispersed electrocatalytically active silver microstructured dendrites on indium tin oxide in the absence of any surface modification or surfactant is presented. It is found that the addition of low concentrations of supporting electrolyte to the AgNO3 solution dramatically influences the morphology of electrodeposited silver which is independent of both the anion and the cation employed. The silver dendrites are characterized by SEM, XRD, XPS as well as by cyclic voltammetry under alkaline conditions. It is found that the surface oxide formation and removal processes are significantly influenced by the microstructured morphology of the silver electrodeposits compared to a smooth macrosized silver electrode. The facile formation of dendritic silver microstructures is also shown to be beneficial for the electrocatalytic oxidation of both formaldehyde and hydrazine and oxygen reduction. The formation of a continuous film of dendritic silver is also investigated for its SERS activity where the connectivity between the individual dendrites is found to be particularly important.
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Background: Few patients diagnosed with lung cancer are still alive 5 years after diagnosis. The aim of the current study was to conduct a 10-year review of a consecutive series of patients undergoing curative-intent surgical resection at the largest tertiary referral centre to identify prognostic factors. Methods: Case records of all patients operated on for lung cancer between 1998 and 2008 were reviewed. The clinical features and outcomes of all patients with non-small cell lung cancer (NSCLC) stage I-IV were recorded. Results: A total of 654 patients underwent surgical resection with curative intent during the study period. Median overall survival for the entire cohort was 37 months. The median age at operation was 66 years, with males accounting for 62.7 %. Squamous cell type was the most common histological subtype, and lobectomies were performed in 76.5 % of surgical resections. Pneumonectomy rates decreased significantly in the latter half of the study (25 vs. 16.3 %), while sub-anatomical resection more than doubled (2 vs. 5 %) (p < 0.005). Clinico-pathological characteristics associated with improved survival by univariate analysis include younger age, female sex, smaller tumour size, smoking status, lobectomy, lower T and N status and less advanced pathological stage. Age, gender, smoking status and tumour size, as well as T and N descriptors have emerged as independent prognostic factors by multivariate analysis. Conclusion: We identified several factors that predicted outcome for NSCLC patients undergoing curative-intent surgical resection. Survival rates in our series are comparable to those reported from other thoracic surgery centres. © 2012 Royal Academy of Medicine in Ireland.
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This paper presents an investigation into event detection in crowded scenes, where the event of interest co-occurs with other activities and only binary labels at the clip level are available. The proposed approach incorporates a fast feature descriptor from the MPEG domain, and a novel multiple instance learning (MIL) algorithm using sparse approximation and random sensing. MPEG motion vectors are used to build particle trajectories that represent the motion of objects in uniform video clips, and the MPEG DCT coefficients are used to compute a foreground map to remove background particles. Trajectories are transformed into the Fourier domain, and the Fourier representations are quantized into visual words using the K-Means algorithm. The proposed MIL algorithm models the scene as a linear combination of independent events, where each event is a distribution of visual words. Experimental results show that the proposed approaches achieve promising results for event detection compared to the state-of-the-art.
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The huge amount of CCTV footage available makes it very burdensome to process these videos manually through human operators. This has made automated processing of video footage through computer vision technologies necessary. During the past several years, there has been a large effort to detect abnormal activities through computer vision techniques. Typically, the problem is formulated as a novelty detection task where the system is trained on normal data and is required to detect events which do not fit the learned ‘normal’ model. There is no precise and exact definition for an abnormal activity; it is dependent on the context of the scene. Hence there is a requirement for different feature sets to detect different kinds of abnormal activities. In this work we evaluate the performance of different state of the art features to detect the presence of the abnormal objects in the scene. These include optical flow vectors to detect motion related anomalies, textures of optical flow and image textures to detect the presence of abnormal objects. These extracted features in different combinations are modeled using different state of the art models such as Gaussian mixture model(GMM) and Semi- 2D Hidden Markov model(HMM) to analyse the performances. Further we apply perspective normalization to the extracted features to compensate for perspective distortion due to the distance between the camera and objects of consideration. The proposed approach is evaluated using the publicly available UCSD datasets and we demonstrate improved performance compared to other state of the art methods.
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Efficient and effective feature detection and representation is an important consideration when processing videos, and a large number of applications such as motion analysis, 3D scene understanding, tracking etc. depend on this. Amongst several feature description methods, local features are becoming increasingly popular for representing videos because of their simplicity and efficiency. While they achieve state-of-the-art performance with low computational complexity, their performance is still too limited for real world applications. Furthermore, rapid increases in the uptake of mobile devices has increased the demand for algorithms that can run with reduced memory and computational requirements. In this paper we propose a semi binary based feature detectordescriptor based on the BRISK detector, which can detect and represent videos with significantly reduced computational requirements, while achieving comparable performance to the state of the art spatio-temporal feature descriptors. First, the BRISK feature detector is applied on a frame by frame basis to detect interest points, then the detected key points are compared against consecutive frames for significant motion. Key points with significant motion are encoded with the BRISK descriptor in the spatial domain and Motion Boundary Histogram in the temporal domain. This descriptor is not only lightweight but also has lower memory requirements because of the binary nature of the BRISK descriptor, allowing the possibility of applications using hand held devices.We evaluate the combination of detectordescriptor performance in the context of action classification with a standard, popular bag-of-features with SVM framework. Experiments are carried out on two popular datasets with varying complexity and we demonstrate comparable performance with other descriptors with reduced computational complexity.