997 resultados para SUBSET


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Plants are capable of recognizing phytopathogens through the perception of pathogen-derived molecules or plant cell-wall degradation products due to the activities of pathogen-secreted enzymes. Such elicitor recognition events trigger an array of inducible defense responses involving signal transduction networks and massive transcriptional re-programming. The outcome of a pathogen infection relies on the balance between different signaling pathways, which are integrated by regulatory proteins. This thesis characterized two key regulatory components: a damage control enzyme, chlorophyllase 1 (AtCHL1), and a transcription factor, WRKY70. Their roles in defense signaling were then investigated. The Erwinia-derived elicitors rapidly activated the expression of AtCLH1 and WRKY70 through different signaling pathways. The expression of the AtCHL1 gene was up-regulated by jasmonic acid (JA) but down-regulated by salicylic acid (SA), whereas WRKY70 was activated by SA and repressed by JA. In order to elucidate the functions of AtCLH1 and WRKY70 in plant defense, stable transgenic lines were produced where these genes were overexpressed or silenced. Additionally, independent knockout lines were also characterized. Bacterial and fungal pathogens were then used to assess the contribution of these genes to the Arabidopsis disease resistance. The transcriptional modulation of AtCLH1 by either the constitutive over-expression or RNAi silencing caused alterations in the chlorophyll-to-chlorophyllide ratio, supporting the claim that chlorophyllase 1 has a role in the chlorophyll degradation pathway. Silencing of this gene led to light-dependent over-accumulation of the reactive oxygen species (ROS) in response to infection by Erwinia carotovora subsp. carotovora SCC1. This was followed by an enhanced induction of SA-dependent defense genes and an increased resistance to this pathogen. Interestingly, little effect on the pathogen-induced SA accumulation at the early infection was observed, suggesting that action of ROS might potentiate SA signaling. In contrast, the pathogen-induced JA production was significantly reduced in the RNAi silenced plants. Moreover, JA signaling and resistance to Alternaria brassicicola were impaired. These observations provide support for the argument that the ROS generated in chloroplasts might have a negative impact on JA signaling. The over-expression of WRKY70 resulted in an enhanced resistance to E. carotovora subsp. carotovora SCC1, Pseudomonas syringae pv. tomato DC3000 and Erysiphe cichoracearum UCSC1, whilst an antisense suppression or an insertional inactivation of WRKY70 led to a compromised resistance to E. carotovora subsp. carotovora SCC1 and to E. cichoracearum UCSC1 but not to P. syringae pv. tomato DC3000. Gene expression analysis revealed that WRKY70 activated many known defense-related genes associated with the SAR response but suppressed a subset of the JA-responsive genes. In particular, I was able to show that both the basal and the induced expression of AtCLH1 was enhanced by the antisense silencing or the insertional inactivation of WRKY70, whereas a reduction in AtCLH1 expression was observed in the WRKY70 over-expressors following an MeJA application or an A. brassicicola infection. Moreover, the SA-induced suppression of AtCLH1 was relieved in wrky70 mutants. These results indicate that WRKY70 down-regulates AtCLH1. An epistasis analysis suggested that WRKY70 functions downstream of the NPR1 in an SA-dependent signaling pathway. When challenged with A. brassicicola, WRKY70 over-expressing plants exhibited a compromised disease resistance while wrky70 mutants had the opposite effect. These results confirmed the WRKY70-mediated inhibitory effects on JA signaling. Furthermore, the WRKY70-controlled suppression of A. brassicicola resistance was mainly through an NPR1-dependent mechanism. Taking all the data together, I suggest that the pathogen-responsive transcription factor WRKY70 is a common component in both SA- and JA-dependent pathways and plays a crucial role in the SA-mediated suppression of JA signaling.

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Generating discriminative input features is a key requirement for achieving highly accurate classifiers. The process of generating features from raw data is known as feature engineering and it can take significant manual effort. In this paper we propose automated feature engineering to derive a suite of additional features from a given set of basic features with the aim of both improving classifier accuracy through discriminative features, and to assist data scientists through automation. Our implementation is specific to HTTP computer network traffic. To measure the effectiveness of our proposal, we compare the performance of a supervised machine learning classifier built with automated feature engineering versus one using human-guided features. The classifier addresses a problem in computer network security, namely the detection of HTTP tunnels. We use Bro to process network traffic into base features and then apply automated feature engineering to calculate a larger set of derived features. The derived features are calculated without favour to any base feature and include entropy, length and N-grams for all string features, and counts and averages over time for all numeric features. Feature selection is then used to find the most relevant subset of these features. Testing showed that both classifiers achieved a detection rate above 99.93% at a false positive rate below 0.01%. For our datasets, we conclude that automated feature engineering can provide the advantages of increasing classifier development speed and reducing development technical difficulties through the removal of manual feature engineering. These are achieved while also maintaining classification accuracy.

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Background Several prospective studies have suggested that gait and plantar pressure abnormalities secondary to diabetic peripheral neuropathy contributes to foot ulceration. There are many different methods by which gait and plantar pressures are assessed and currently there is no agreed standardised approach. This study aimed to describe the methods and reproducibility of three-dimensional gait and plantar pressure assessments in a small subset of participants using pre-existing protocols. Methods Fourteen participants were conveniently sampled prior to a planned longitudinal study; four patients with diabetes and plantar foot ulcers, five patients with diabetes but no foot ulcers and five healthy controls. The repeatability of measuring key biomechanical data was assessed including the identification of 16 key anatomical landmarks, the measurement of seven leg dimensions, the processing of 22 three-dimensional gait parameters and the analysis of four different plantar pressures measures at 20 foot regions. Results The mean inter-observer differences were within the pre-defined acceptable level (<7 mm) for 100 % (16 of 16) of key anatomical landmarks measured for gait analysis. The intra-observer assessment concordance correlation coefficients were > 0.9 for 100 % (7 of 7) of leg dimensions. The coefficients of variations (CVs) were within the pre-defined acceptable level (<10 %) for 100 % (22 of 22) of gait parameters. The CVs were within the pre-defined acceptable level (<30 %) for 95 % (19 of 20) of the contact area measures, 85 % (17 of 20) of mean plantar pressures, 70 % (14 of 20) of pressure time integrals and 55 % (11 of 20) of maximum sensor plantar pressure measures. Conclusion Overall, the findings of this study suggest that important gait and plantar pressure measurements can be reliably acquired. Nearly all measures contributing to three-dimensional gait parameter assessments were within predefined acceptable limits. Most plantar pressure measurements were also within predefined acceptable limits; however, reproducibility was not as good for assessment of the maximum sensor pressure. To our knowledge, this is the first study to investigate the reproducibility of several biomechanical methods in a heterogeneous cohort.

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Predicting temporal responses of ecosystems to disturbances associated with industrial activities is critical for their management and conservation. However, prediction of ecosystem responses is challenging due to the complexity and potential non-linearities stemming from interactions between system components and multiple environmental drivers. Prediction is particularly difficult for marine ecosystems due to their often highly variable and complex natures and large uncertainties surrounding their dynamic responses. Consequently, current management of such systems often rely on expert judgement and/or complex quantitative models that consider only a subset of the relevant ecological processes. Hence there exists an urgent need for the development of whole-of-systems predictive models to support decision and policy makers in managing complex marine systems in the context of industry based disturbances. This paper presents Dynamic Bayesian Networks (DBNs) for predicting the temporal response of a marine ecosystem to anthropogenic disturbances. The DBN provides a visual representation of the problem domain in terms of factors (parts of the ecosystem) and their relationships. These relationships are quantified via Conditional Probability Tables (CPTs), which estimate the variability and uncertainty in the distribution of each factor. The combination of qualitative visual and quantitative elements in a DBN facilitates the integration of a wide array of data, published and expert knowledge and other models. Such multiple sources are often essential as one single source of information is rarely sufficient to cover the diverse range of factors relevant to a management task. Here, a DBN model is developed for tropical, annual Halophila and temperate, persistent Amphibolis seagrass meadows to inform dredging management and help meet environmental guidelines. Specifically, the impacts of capital (e.g. new port development) and maintenance (e.g. maintaining channel depths in established ports) dredging is evaluated with respect to the risk of permanent loss, defined as no recovery within 5 years (Environmental Protection Agency guidelines). The model is developed using expert knowledge, existing literature, statistical models of environmental light, and experimental data. The model is then demonstrated in a case study through the analysis of a variety of dredging, environmental and seagrass ecosystem recovery scenarios. In spatial zones significantly affected by dredging, such as the zone of moderate impact, shoot density has a very high probability of being driven to zero by capital dredging due to the duration of such dredging. Here, fast growing Halophila species can recover, however, the probability of recovery depends on the presence of seed banks. On the other hand, slow growing Amphibolis meadows have a high probability of suffering permanent loss. However, in the maintenance dredging scenario, due to the shorter duration of dredging, Amphibolis is better able to resist the impacts of dredging. For both types of seagrass meadows, the probability of loss was strongly dependent on the biological and ecological status of the meadow, as well as environmental conditions post-dredging. The ability to predict the ecosystem response under cumulative, non-linear interactions across a complex ecosystem highlights the utility of DBNs for decision support and environmental management.

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Dispersing a data object into a set of data shares is an elemental stage in distributed communication and storage systems. In comparison to data replication, data dispersal with redundancy saves space and bandwidth. Moreover, dispersing a data object to distinct communication links or storage sites limits adversarial access to whole data and tolerates loss of a part of data shares. Existing data dispersal schemes have been proposed mostly based on various mathematical transformations on the data which induce high computation overhead. This paper presents a novel data dispersal scheme where each part of a data object is replicated, without encoding, into a subset of data shares according to combinatorial design theory. Particularly, data parts are mapped to points and data shares are mapped to lines of a projective plane. Data parts are then distributed to data shares using the point and line incidence relations in the plane so that certain subsets of data shares collectively possess all data parts. The presented scheme incorporates combinatorial design theory with inseparability transformation to achieve secure data dispersal at reduced computation, communication and storage costs. Rigorous formal analysis and experimental study demonstrate significant cost-benefits of the presented scheme in comparison to existing methods.

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Background: Recent studies have implicated aberrant Notch signaling in breast cancers. Yet, relatively little is known about the pattern of expression of various components of the Notch pathway, or its mechanism of action. To better understand the role of the Notch pathway in breast cancer, we have undertaken a detailed expression analysis of various Notch receptors, their ligands, and downstream targets at different stages of breast cancer progression. Results: We report here that there is a general increase in the expression levels of Notch 1, 2, 4, Jagged1, Jagged2, and Delta-like 4 proteins in breast cancers, with simultaneous upregulation of multiple Notch receptors and ligands in a given cancer tissue. While Notch3 and Delta-like1 were undetectable in normal tissues, moderate to high expression was detected in several cancers. We detected the presence of active, cleaved Notch1, along with downstream targets of the Notch pathway, Hes1/Hes5, in similar to 75% of breast cancers, clearly indicating that in a large proportion of breast cancers Notch signaling is aberrantly activated. Furthermore, we detected cleaved Notch1 and Hes1/5 in early precursors of breast cancers - hyperplasia and ductal carcinoma in situ suggesting that aberrant Notch activation may be an early event in breast cancer progression. Mechanistically, while constitutively active Notch1 alone failed to transform immortalized breast cells, it synergized with the Ras/MAPK pathway to mediate transformation. This cooperation is reflected in vivo, as a subset of cleaved Notch positive tumors additionally expressed phopsho-Erk1/2 in the nuclei. Such cases exhibited high node positivity, suggesting that Notch-Ras cooperation may lead to poor prognosis. Conclusions: High level expression of Notch receptors and ligands, and its increased activation in several breast cancers and early precursors, places Notch signaling as a key player in breast cancer pathogenesis. Its cooperation with the Ras/MAPK pathway in transformation offers combined inhibition of the two pathways as a new modality for breast cancer treatment.

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Type 1 diabetes (T1D) is considered to be an autoimmune disease. In T1D insulin producing pancreatic β cells are destroyed. The disease process begins years before the clinical diagnosis of T1D. During the pathogenesis of T1D, pancreatic islets are infiltrated by cells of the immune system and T-lymphocytes are considered to be the main mediators of the β-cell destruction. In children with an active β-cell destruction process, autoantibodies against β-cell antigens appear in the blood. Individuals at increased risk of developing T1D can often be identified by detecting serum autoantibodies against β-cell antigens. Immunological aberrancies associated with T1D are related to defects in the polarization of T cells and in the function of regulatory mechanisms. T1D has been considered as an organ-specific autoimmune disease mediated by uncontrolled Th1-responses. In human T1D, the evidence for the role of over-expression of cytokines promoting cytotoxicity is controversial. For the past 15 years, regulatory T cells (Tregs) have been recognized as having a key role in the initiation and maintenance of tolerance, limiting harmful autoantigen-specific inflammation processes. It is possible that, if regulatory mechanisms fail to be initiated, the subtle inflammation targeting β cells lead to insulitis and eventually to overt T1D in some individuals. In the present thesis, we studied the induction of Tregs during the generation of T-cell responses in T1D. The results suggest that the generation of regulatory mechanisms and effector mechanisms upon T-cell activation is aberrant in children with T1D. In our studies, an in vitro cytotoxic environment inhibited the induction of genes associated with regulatory functions upon T-cell activation. We also found T1D patients to have an impaired cytotoxic response against coxsackievirus B4. Ineffective virus clearance may increase the apoptosis of β cells, and thus the risk of β-cell specific autoimmunity, due to the increased presentation of β-cell-derived peptides by APCs to T cells in pancreatic lymph nodes. Recently, a novel T helper cell subset called Th17 has been discovered. Animal models have associated Th17 cells and especially co-producers of IL-17 and IFN-γ with the pathogenesis of T1D. We aimed to characterize the role of Th17 immunity in human T1D. We demonstrated IL-17 activation to be a major alteration in T1D patients in comparison to healthy children. Moreover, alterations related to the FOXP3-mediated regulatory mechanisms were associated with the IL-17 up-regulation seen in T1D patients. These findings may have therapeutic implications for the treatment and prevention of T1D.

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The issue raised in this Letter is classical, not only in the sense of being nonquantum, but also in the sense of being quite ancient: which subset of 4 X 4 real matrices should be accepted as physical Mueller matrices in polarization optics? Nonquantum entanglement or inseparability between the polarization and spatial degrees of freedom of an electromagnetic beam whose polarization is not homogeneous is shown to provide the physical basis to resolve this issue in a definitive manner.

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The delivery of products and services for construction-based businesses is increasingly becoming knowledge-driven and information-intensive. The proliferation of building information modelling (BIM) has increased business opportunities as well as introduced new challenges for the architectural, engineering and construction and facilities management (AEC/FM) industry. As such, the effective use, sharing and exchange of building life cycle information and knowledge management in building design, construction, maintenance and operation assumes a position of paramount importance. This paper identifies a subset of construction management (CM) relevant knowledge for different design conditions of building components through a critical, comprehensive review of synthesized literature and other information gathering and knowledge acquisition techniques. It then explores how such domain knowledge can be formalized as ontologies and, subsequently, a query vocabulary in order to equip BIM users with the capacity to query digital models of a building for the retrieval of useful and relevant domain-specific information. The formalized construction knowledge is validated through interviews with domain experts in relation to four case study projects. Additionally, retrospective analyses of several design conditions are used to demonstrate the soundness (realism), completeness, and appeal of the knowledge base and query-based reasoning approach in relation to the state-of-the-art tools, Solibri Model Checker and Navisworks. The knowledge engineering process and the methods applied in this research for information representation and retrieval could provide useful mechanisms to leverage BIM in support of a number of knowledge intensive CM/FM tasks and functions.

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In this paper, we present a new feature-based approach for mosaicing of camera-captured document images. A novel block-based scheme is employed to ensure that corners can be reliably detected over a wide range of images. 2-D discrete cosine transform is computed for image blocks defined around each of the detected corners and a small subset of the coefficients is used as a feature vector A 2-pass feature matching is performed to establish point correspondences from which the homography relating the input images could be computed. The algorithm is tested on a number of complex document images casually taken from a hand-held camera yielding convincing results.

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A construction for a family of sequences over the 8-ary AM-PSK constellation that has maximum nontrivial correlation magnitude bounded as theta(max) less than or similar to root N is presented here. The famfly is asymptotically optimal with respect to the Welch bound on maximum magnitude of correlation. The 8-ary AM-PSK constellation is a subset of the 16-QAM constellation. We also construct two families of sequences over 16-QAM with theta(max) less than or similar to root 2 root N. These families are constructed by interleaving sets of sequences. A construction for a famBy of low-correlation sequences over QAM alphabet of size 2(2m) is presented with maximum nontrivial normalized correlation parameter bounded above by less than or similar to a root N, where N is the period of the sequences in the family and where a ranges from 1.61 in the case of 16-QAM modulation to 2.76 for large m. When used in a CDMA setting, the family will permit each user to modulate the code sequence with 2m bits of data. Interestingly, the construction permits users on the reverse link of the CDMA channel to communicate using varying data rates by switching between sequence famflies; associated to different values of the parameter m. Other features of the sequence families are improved Euclidean distance between different data symbols in comparison with PSK signaling and compatibility of the QAM sequence families with sequences belonging to the large quaternary sequence families {S(p)}.

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In this note, we point out that a large family of n x n matrix valued kernel functions defined on the unit disc D subset of C, which were constructed recently in [9], behave like the familiar Bergman kernel function on ID in several different ways. We show that a number of questions involving the multiplication operator on the corresponding Hilbert space of holomorphic functions on D can be answered using this likeness.

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Single-symbol maximum likelihood (ML) decodable distributed orthogonal space-time block codes (DOST- BCs) have been introduced recently for cooperative networks and an upper-bound on the maximal rate of such codes along with code constructions has been presented. In this paper, we introduce a new class of distributed space-time block codes (DSTBCs) called semi-orthogonal precoded distributed single-symbol decodable space-time block codes (Semi-SSD-PDSTBCs) wherein, the source performs preceding on the information symbols before transmitting it to all the relays. A set of necessary and sufficient conditions on the relay matrices for the existence of semi-SSD- PDSTBCs is proved. It is shown that the DOSTBCs are a special case of semi-SSD-PDSTBCs. A subset of semi-SSD-PDSTBCs having diagonal covariance matrix at the destination is studied and an upper bound on the maximal rate of such codes is derived. The bounds obtained are approximately twice larger than that of the DOSTBCs. A systematic construction of Semi- SSD-PDSTBCs is presented when the number of relays K ges 4 and the constructed codes are shown to have higher rates than that of DOSTBCs.

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Synchronising bushcricket males achieve synchrony by delaying their chirps in response to calling neighbours. In multi-male choruses, males that delay chirps in response to all their neighbours would remain silent most of the time and be unable to attract mates. This problem could be overcome if the afferent auditory system exhibited selective attention, and thus a male interacted only with a subset of neighbours. We investigated whether individuals of the bushcricket genus Mecopoda restricted their attention to louder chirps neurophysiologically, behaviourally and through spacing. We found that louder leading chirps were preferentially represented in the omega neuron but the representation of softer following chirps was not completely abolished. Following chirps that were 20 dB louder than leading chirps were better represented than leading chirps. During acoustic interactions, males synchronised with leading chirps even when the following chirps were 20 dB louder. Males did not restrict their attention to louder chirps during interactions but were affected by all chirps above a particular threshold. In the field, we found that males on average had only one or two neighbours whose calls were above this threshold. Selective attention is thus achieved in this bushcricket through spacing rather than neurophysiological filtering of softer signals.

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Synchronising bushcricket males achieve synchrony by delaying their chirps in response to calling neighbours. In multi-male choruses, males that delay chirps in response to all their neighbours would remain silent most of the time and be unable to attract mates. This problem could be overcome if the afferent auditory system exhibited selective attention, and thus a male interacted only with a subset of neighbours. We investigated whether individuals of the bushcricket genus Mecopoda restricted their attention to louder chirps neurophysiologically, behaviourally and through spacing. We found that louder leading chirps were preferentially represented in the omega neuron but the representation of softer following chirps was not completely abolished. Following chirps that were 20 dB louder than leading chirps were better represented than leading chirps. During acoustic interactions, males synchronised with leading chirps even when the following chirps were 20 dB louder. Males did not restrict their attention to louder chirps during interactions but were affected by all chirps above a particular threshold. In the field, we found that males on average had only one or two neighbours whose calls were above this threshold. Selective attention is thus achieved in this bushcricket through spacing rather than neurophysiological filtering of softer signals.