201 resultados para Atrioventricular node
Resumo:
Real-world environments such as houses and offices change over time, meaning that a mobile robot’s map will become out of date. In previous work we introduced a method to update the reference views in a topological map so that a mobile robot could continue to localize itself in a changing environment using omni-directional vision. In this work we extend this longterm updating mechanism to incorporate a spherical metric representation of the observed visual features for each node in the topological map. Using multi-view geometry we are then able to estimate the heading of the robot, in order to enable navigation between the nodes of the map, and to simultaneously adapt the spherical view representation in response to environmental changes. The results demonstrate the persistent performance of the proposed system in a long-term experiment.
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Real-world environments such as houses and offices change over time, meaning that a mobile robot’s map will become out of date. In this work, we introduce a method to update the reference views in a hybrid metrictopological map so that a mobile robot can continue to localize itself in a changing environment. The updating mechanism, based on the multi-store model of human memory, incorporates a spherical metric representation of the observed visual features for each node in the map, which enables the robot to estimate its heading and navigate using multi-view geometry, as well as representing the local 3D geometry of the environment. A series of experiments demonstrate the persistence performance of the proposed system in real changing environments, including analysis of the long-term stability.
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Knowledge of CT anatomy is increasingly vital in daily radiotherapy practice, especially with more widespread use of cross-sectional image-guided radiotherapy (IGRT) techniques. Existing CT anatomy texts are predominantly written for the diagnostic practitioner and do not always address the radiotherapy issues while emphasising structures that are not common to radiotherapy practice. CT Anatomy for Radiotherapy is a new radiotherapy-specific text that is intended to prepare the reader for CT interpretation for both IGRT and treatment planning. It is suitable for undergraduate students, qualified therapy radiographers, dosimetrists and may be of interest to oncologists and registrars engaged in treatment planning. All essential structures relevant to radiotherapy are described and depicted on 3D images generated from radiotherapy planning systems. System-based labelled CT images taken in relevant imaging planes and patient positions build up understanding of relational anatomy and CT interpretation. Images are accompanied by comprehensive commentary to aid with interpretation. This simplified approach is used to empower the reader to rapidly gain image interpretation skills. The book pays special attention to lymph node identification as well as featuring a unique section on Head and Neck Deep Spaces to help understanding of common pathways of tumour spread. Fully labelled CT images using radiotherapy-specific views and positioning are complemented where relevant by MR and fusion images. A brief introduction to image interpretation using IGRT devices is also covered. The focus of the book is on radiotherapy and some images of common tumour pathologies are utilised to illustrate some relevant abnormal anatomy. Short self-test questions help to keep the reader engaged throughout.
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Similar to the focus on training in the technical, physical and artistic areas of dance, dance professionals, students and educators alike appear to be developing an increased awareness of how important training in psychology is to their success within dance. Over the past 4 years, lectures in performance psychology have been incorporated as part of a compulsory professional skills subject for second and third year students within a University dance program. The following presentation aims to share practitioner experience and learnings regarding the implementation of this subject within this context, its perceived effectiveness, and recommendations for future use.
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We propose a topological localization method based on optical flow information. We analyse the statistical characteristics of the optical flow signal and demonstrate that the flow vectors can be used to identify and describe key locations in the environment. The key locations (nodes) correspond to significant scene changes and depth discontinuities. Since optical flow vectors contain position, magnitude and angle information, for each node, we extract low and high order statistical moments of the vectors and use them as descriptors for that node. Once a database of nodes and their corresponding optical flow features is created, the robot can perform topological localization by using the Mahalanobis distance between the current frame and the database. This is supported by field trials, which illustrate the repeatability of the proposed method for detecting and describing key locations in indoor and outdoor environments in challenging and diverse lighting conditions.
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Published information on the incidence of pathogens in the field and laboratory infections of Hypsipyla spp. with entomopathogens is reviewed. In addition, some preliminary results of field collections from Ghana and Costa Rica are presented. Fungal pathogens from the Deuteromycetes have been isolated from both H. robusta Moore and H. grandella Zeller. Mermithid nematodes, Hexamermis spp., have been frequently isolated from larvae in the field and incidence of infection with these pathogens can reach significant levels. Microsporidia have been found in cadavers of larvae collected in the field but none have been identified so far. A number of pathogens of other Lepidoptera have been shown to be infectious to H. grandella , including Bacillus thuringiensis , Deuteromycete fungi and a nucleopolyhedrovirus (NPV) from Autographa californica . Hypsipyla spp. are difficult targets for microbial control, since the larvae are cryptic, occur at low density and occur sporadically. In addition, there is a low damage threshold, the plant is susceptible for a number of years and the susceptible part of the plant will rapidly outgrow any surface application. Key features of the biology of entomopathogens with relevance to the control of low density and cryptic pests are discussed. In the light of this experience, we discuss strategies to improve the possibilities of microbial control of this pest and suggest areas for research.
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Existing evidence for successful silvicultural control of Hypsipyla spp. is conflicting and to a large extent anecdotal. Levels of attack have been correlated with factors such as shade, planting density, species mixtures, site characteristics, etc. These factors have often been poorly defined and are usually interdependent. The actual mechanisms that determine whether or not Hypsipyla spp. adversely affects plants we define as host-finding, host suitability, host recovery and natural enemies. These mechanisms can be influenced by the silvicultural techniques applied to a stand. Success of silvicultural techniques can usually be attributed to more than one mechanism and it is difficult to assess which is most the important for minimising the impact of Hypsipyla as these analytical data are lacking. This highlights the need for further research on silvicultural methods for controlling Hypsipyla spp. However, several silvicultural techniques that are briefly described show promise for improving the performance of future plantations. Examples of silvicultural control are reviewed with reference to these mechanisms.
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Hypsipyla grandella (Zeller) is the most important insect pest of the Meliaceae in the Neotropics. This paper reviews the information on H. grandella parasitoids in Latin America and the Caribbean. Preliminary data on the parasitoid complex in Turrialba, Costa Rica, are presented, where apparent parasitisation of H. grandella during 1995–1996 reached 36%. The lowest level of parasitisation occurred during the dry season. The parasitoid Apanteles sp. (= Hypomicrogaster hypsipylae de Santis?) (Hymenoptera: Braconidae) was the most abundant larval parasitoid with a mean of 22 parasitoids per parasitised larva and a sex ratio of 3:1 females to males. Brachymeria conica Ashmead (Hymenoptera: Chalcididae) was found parasitising pupae, but at low frequency
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The biological function of inhibin-a subunit (INHa) in prostate cancer (PCa) is currently unclear. A recent study associated elevated levels of INHa in PCa patients with a higher risk of recurrence. This prompted us to use clinical specimens and functional studies to investigate the pro-tumourigenic and pro-metastatic function of INHa. We conducted a cross-sectional study to determine a link between INHa expression and a number of clinicopathological parameters including Gleason score, surgical margin, extracapsular spread, lymph node status and vascular endothelial growth factor receptor-3 expression, which are well-established prognostic factors of PCa. In addition, using two human PCa cell lines (LNCaP and PC3) representing androgen-dependent and -independent PCa respectively, we investigated the biological function of elevated levels of INHa in advanced cancer. Elevated expression of INHa in primary PCa tissues showed a higher risk of PCa patients being positive for clinicopathological parameters outlined above. Overexpressing INHa in LNCaP and PC3 cells demonstrated two different and cell-type-specific responses. INHa-positive LNCaP demonstrated reduced tumour growth whereas INHa-positive PC3 cells demonstrated increased tumour growth and metastasis through the process of lymphangiogenesis. This study is the first to demonstrate a pro-tumourigenic and pro-metastatic function for INHa associated with androgen-independent stage of metastatic prostate disease. Our results also suggest that INHa expression in the primary prostate tumour can be used as a predictive factor for prognosis of PCa.
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Background Dysfunctional lymphatic vessel formation has been implicated in a number of pathological conditions including cancer metastasis, lymphedema, and impaired wound healing. The vascular endothelial growth factor (VEGF) family is a major regulator of lymphatic endothelial cell (LEC) function and lymphangiogenesis. Indeed, dissemination of malignant cells into the regional lymph nodes, a common occurrence in many cancers, is stimulated by VEGF family members. This effect is generally considered to be mediated via VEGFR-2 and VEGFR-3. However, the role of specific receptors and their downstream signaling pathways is not well understood. Methods and Results Here we delineate the VEGF-C/VEGF receptor (VEGFR)-3 signaling pathway in LECs and show that VEGF-C induces activation of PI3K/Akt and MEK/Erk. Furthermore, activation of PI3K/Akt by VEGF-C/VEGFR-3 resulted in phosphorylation of P70S6K, eNOS, PLCc1, and Erk1/2. Importantly, a direct interaction between PI3K and VEGFR-3 in LECs was demonstrated both in vitro and in clinical cancer specimens. This interaction was strongly associated with the presence of lymph node metastases in primary small cell carcinoma of the lung in clinical specimens. Blocking PI3K activity abolished VEGF-C-stimulated LEC tube formation and migration. Conclusions Our findings demonstrate that specific VEGFR-3 signaling pathways are activated in LECs by VEGF-C. The importance of PI3K in VEGF-C/VEGFR-3-mediated lymphangiogenesis provides a potential therapeutic target for the inhibition of lymphatic metastasis.
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Rapid development of plug-in hybrid electric vehicles (PHEVs) brings new challenges and opportunities to the power industry. A large number of idle PHEVs can potentially be employed to form a distributed energy storage system for supporting renewable generation. To reduce the negative effects of unsteady renewable generation outputs, a stochastic optimization-based dispatch model capable of handling uncertain outputs of PHEVs and renewable generation is formulated in this paper. The mathematical expectations, second-order original moments, and variances of wind and photovoltaic (PV) generation outputs are derived analytically. Incorporated all the derived uncertainties, a novel generation shifting objective is proposed. The cross-entropy (CE) method is employed to solve this optimal dispatch model. Multiple patterns of renewable generation depending on seasons and renewable market shares are investigated. The feasibility and efficiency of the developed optimal dispatch model, as well as the CE method, are demonstrated with a 33-node distribution system.
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Heart rate variability (HRV) refers to the regulation of the sinoatrial node, the natural pacemaker of the heart by the sympathetic and parasympathetic branches of the autonomic nervous system. HRV analysis is an important tool to observe the heart’s ability to respond to normal regulatory impulses that affect its rhythm. Like many bio-signals, HRV signals are non-linear in nature. Higher order spectral analysis (HOS) is known to be a good tool for the analysis of non-linear systems and provides good noise immunity. A computer-based arrhythmia detection system of cardiac states is very useful in diagnostics and disease management. In this work, we studied the identification of the HRV signals using features derived from HOS. These features were fed to the support vector machine (SVM) for classification. Our proposed system can classify the normal and other four classes of arrhythmia with an average accuracy of more than 85%.
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Weak cell-surface adhesion of cell lines to tissue culture surfaces is a common problem and presents technical limitations to the design of experiments. To overcome this problem, various surface coating protocols have been developed. However, a comparative and precise real-time measurement of their impact on cell behavior has not been conducted. The prostate cancer cell line LNCaP, derived from a patient lymph node metastasis, is a commonly used model system in prostate cancer research. However, the cells’ characteristically weak attachment to the surface of tissue culture vessels and cover slips has impeded their manipulation and analysis and use in high throughput screening. To improve the adherence of LNCaP cells to the culture surface, we compared different coating reagents (poly-L-lysine, poly-L-ornithine, collagen type IV, fibronectin, and laminin) and culturing conditions and analyzed their impact on cell proliferation, adhesion, morphology, mobility and gene expression using real-time technologies. The results showed that fibronectin, poly-L-lysine and poly-L-ornithine improved LNCaP cells adherence and provoked cell morphology alterations, such as increase of nuclear and cellular area. These coating reagents also induced a higher expression of F-actin and reduced cell mobility. In contrast, laminin and collagen type IV did not improve adherence but promoted cell aggregation and affected cell morphology. Cells cultured in the presence of laminin displayed higher mobility than control cells. All the coating conditions significantly affected cell viability; however, they did not affect the expression of androgen receptor-regulated genes. Our comparative findings provide important insight for the selection of the ideal coating reagent and culture conditions for the cancer cell lines with respect to their effect on proliferation rate, attachment, morphology, migration, transcriptional response and cellular cytoskeleton arrangement.
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Bayesian networks (BNs) are graphical probabilistic models used for reasoning under uncertainty. These models are becoming increasing popular in a range of fields including ecology, computational biology, medical diagnosis, and forensics. In most of these cases, the BNs are quantified using information from experts, or from user opinions. An interest therefore lies in the way in which multiple opinions can be represented and used in a BN. This paper proposes the use of a measurement error model to combine opinions for use in the quantification of a BN. The multiple opinions are treated as a realisation of measurement error and the model uses the posterior probabilities ascribed to each node in the BN which are computed from the prior information given by each expert. The proposed model addresses the issues associated with current methods of combining opinions such as the absence of a coherent probability model, the lack of the conditional independence structure of the BN being maintained, and the provision of only a point estimate for the consensus. The proposed model is applied an existing Bayesian Network and performed well when compared to existing methods of combining opinions.