57 resultados para Subclassing Anomaly
Resumo:
The movement of exotic biota into native ecosystems are central to debates about the acclimatisation of plants in the settler colonies of the nineteenth century. For example, plants like lucerne from Europe and sudan grass from South Africa were transferred to Australia to support pastoral economies. The saltbush Atriplex spp. is an anomaly-it too, eventually, became the subject of acclimatisation within its native Australia because it was also deemed useful to the pastoralists of arid and semi-arid New South Wales. When settlers first came to this part of Australia, however, initial perceptions were that the plants were useless. We trace this transformation from the desert 'desperation' plant during early settlement to the 'precious' conservation species, from the 1880s, when there were changes in both management strategies and cultural responses to saltbush in Australia. This reconsideration can be seen in scientific assessments and experiments, in the way that it was commoditised by seeds and nursery traders, and in its use as a metaphor in bush poetry to connote a gendered nationalist figure in Saltbush Bill. We argue that while initial settlers were often so optimistic about European management techniques, they had nothing but contempt for indigenous plants. The later impulses to the conservation of natives arose from experiences of bitter failure and despair over attempts to impose European methods, which in turn forced this re-evaluation of Australian species.
Immunity against a Chlamydia infection and disease may be determined by a balance of IL-17 signaling
Resumo:
Most vaccines developed against Chlamydia using animal models provide partial protection against a genital tract infection. However, protection against the oviduct pathology associated with infertility is highly variable and often has no defining immunological correlate. When comparing two adjuvants (CTA1-DD and a combination of Cholera toxin plus CpG- oligodeoxynucleotide–CT/CpG) combined with the chlamydial major outer membrane protein (MOMP) antigen and delivered via the intranasal (IN), sublingual (SL) or transcutaneous (TC) routes, we identified two vaccine groups with contrasting outcomes following infection. SL immunization with MOMP/CTA1-DD induced a 70% reduction in the incidence of oviduct pathology, without significantly altering the course of infection. Conversely, IN immunization with MOMP/CT/CpG prevented an ascending infection, but not the oviduct pathology. This anomaly presented a unique opportunity to study the mechanisms by which vaccines can prevent oviduct pathology, other than by controlling the infection. The IL-17 signaling in the oviducts was found to associate with both the enhancement of immunity to infection and the development of oviduct pathology. This conflicting role of IL-17 may provide some explanation for the discordance in protection between infection and disease and suggests that controlling immunopathology, as opposed to the rapid eradication of the infection, may be essential for an effective human chlamydial vaccine that prevents infertility.
Resumo:
In this study, a machine learning technique called anomaly detection is employed for wind turbine bearing fault detection. Basically, the anomaly detection algorithm is used to recognize the presence of unusual and potentially faulty data in a dataset, which contains two phases: a training phase and a testing phase. Two bearing datasets were used to validate the proposed technique, fault-seeded bearing from a test rig located at Case Western Reserve University to validate the accuracy of the anomaly detection method, and a test to failure data of bearings from the NSF I/UCR Center for Intelligent Maintenance Systems (IMS). The latter data set was used to compare anomaly detection with SVM, a previously well-known applied method, in rapidly finding the incipient faults.
Resumo:
The momentum investment strategy, which buys recent winner stocks and sells recent loser stocks, earns returns that are simply too good to be explained by traditional finance theories. This thesis extends our understanding of the sources of momentum profits. The research shows that part of the seemingly anomalous returns can be explained by the market's reaction to public news, is affected by how delisting returns are calculated, and is biased by ignoring the time-varying risk of the trading strategy.
Resumo:
Micrometre-sized MgB2 crystals of varying quality, synthesized at low temperature and autogeneous pressure, are compared using a combination of Raman and Infra-Red (IR) spectroscopy. These data, which include new peak positions in both spectroscopies for high quality MgB2, are interpreted using DFT calculations on phonon behaviour for symmetry-related structures. Raman and IR activity additional to that predicted by point group analyses of the P6/mmm symmetry are detected. These additional peaks, as well as the overall shapes of calculated phonon dispersion (PD) models are explained by assuming a double super-lattice, consistent with a lower symmetry structure for MgB2. A 2x super-lattice in the c-direction allows a simple correlation of the pair breaking energy and the superconducting gap by activation of corresponding acoustic frequencies. A consistent physical interpretation of these spectra is obtained when the position of a phonon anomaly defines a super-lattice modulation in the a-b plane.
Resumo:
Background More individuals are now being identified with very rare genetic syndromes. We present a family with an inherited duplication of 16p11.2 to 16q12.1 in ring formation. Three of the four children, (aged 15 months to 10 years), mother, uncle, and grandmother are affected. Our aim was to provide preliminary evidence of possible phenotypic patterns of learning and behaviour associated with this chromosome anomaly. Method Psychometric assessments were undertaken with all four children. The mother and uncle also agreed to participate in the study. Measures of development (Bayley or Mullen), intellectual ability (WISC-IV or WAIS-III), academic achievement (WIAT-II), adaptive behaviour (Vinelands), and other relevant aspects of functioning (e.g., Children’s Memory Scale) were administered. Results. The first-born child is the only one who is unaffected. Her intellectual ability was assessed as being within the superior range. The second child experienced early difficulties with speech and motor skills. Although his intelligence is average, he has learning difficulties and significant auditory memory problems. The third child’s speech and motor milestones were markedly delayed. He has a complex medical history that includes a vitamin B12 deficiency. On the Mullen Scales at age 4 his scores ranged from average to very low. The development of the youngest child (aged 15 months), who also had a B12 deficiency but was treated early, was assessed as being within typical limits. Conclusions There is considerable developmental variability among the three children with this inherited 16p duplication. We discuss the intriguing similarities and differences, considering common features that may reflect phenotypic patterns and speculating about possible explanations for the variable presentations.
Resumo:
A long-period magnetotelluric (MT) survey, with 39 sites covering an area of 270 by 150 km, has identified melt within the thinned lithosphere of Pleistocene-Holocene Newer Volcanics Province (NVP) in southeast Australia, which has been variously attributed to mantle plume activity or edge-driven mantle convection. Two-dimensional inversions from the MT array imaged a low-resistivity anomaly (10-30Ωm) beneath the NVP at ∼40-80 km depth, which is consistent with the presence of ∼1.5-4% partial melt in the lithosphere, but inconsistent with elevated iron content, metasomatism products or a hot spot. The conductive zone is located within thin juvenile oceanic mantle lithosphere, which was accreted onto thicker Proterozoic continental mantle lithosphere. We propose that the NVP owes its origin to decompression melting within the asthenosphere, promoted by lithospheric thickness variations in conjunction with rapid shear, where asthenospheric material is drawn by shear flow at a "step" at the base of the lithosphere.
Resumo:
We show that the well-known Kohn anomaly predicts Tc for ordered AlB2-type structures. We use ab initio Density Functional Theory to calculate phonon dispersions for Mg1-xAlxB2 compositions and identify a phonon anomaly with magnitude that predicts experimental values of Tc for all x. Key features of these anomalies correlate with the electronic structure of Mg1-xAlxB2. This approach predicts Tc for other known AlB2-type structures as well as new compositions. We predict that Mg0.5Ba0.5B2 will show Tc = 63.6 ± 6.6 K. Other forms of the Mg1-xBaxB2 series will also be superconductors when successfully synthesised. Our calculations predict that the end-member composition, BaB2, is likely to show a Tc significantly higher than currently achieved by other diborides although an applied pressure ~16 GPa may be required to stabilise the structure.
Resumo:
Any kind of imbalance in the operation of a wind turbine has adverse effect on the downstream torsional components as well as tower structure. It is crucial to detect imbalance at its very inception. The identification of the type of imbalance is also required so that appropriate measures of fault accommodation can be performed in the control system. In particular, it is important to distinguish between mass and aerodynamic imbalance. While the former is gradually caused by a structural anomaly (e.g. ice deposition, moisture accumulation inside blade), the latter is generally associated to a fault in the pitch control system. This paper proposes a technique for the detection and identification of imbalance fault in large scale wind turbines. Unlike most other existing method it requires only the rotor speed signal which is readily available in existing turbines. Signature frequencies have been proposed in this work to identify imbalance type based on their physical phenomenology. The performance of this technique has been evaluated by simulations using an existing benchmark model. The effectiveness of the proposed method has been confirmed by the simulation results.
Resumo:
Video surveillance infrastructure has been widely installed in public places for security purposes. However, live video feeds are typically monitored by human staff, making the detection of important events as they occur difficult. As such, an expert system that can automatically detect events of interest in surveillance footage is highly desirable. Although a number of approaches have been proposed, they have significant limitations: supervised approaches, which can detect a specific event, ideally require a large number of samples with the event spatially and temporally localised; while unsupervised approaches, which do not require this demanding annotation, can only detect whether an event is abnormal and not specific event types. To overcome these problems, we formulate a weakly-supervised approach using Kullback-Leibler (KL) divergence to detect rare events. The proposed approach leverages the sparse nature of the target events to its advantage, and we show that this data imbalance guarantees the existence of a decision boundary to separate samples that contain the target event from those that do not. This trait, combined with the coarse annotation used by weakly supervised learning (that only indicates approximately when an event occurs), greatly reduces the annotation burden while retaining the ability to detect specific events. Furthermore, the proposed classifier requires only a decision threshold, simplifying its use compared to other weakly supervised approaches. We show that the proposed approach outperforms state-of-the-art methods on a popular real-world traffic surveillance dataset, while preserving real time performance.
Resumo:
We have shown that novel synthesis methods combined with careful evaluation of DFT phonon calculations provides new insight into boron compounds including a capacity to predict Tc for AlB2-type superconductors.
Resumo:
Identifying unusual or anomalous patterns in an underlying dataset is an important but challenging task in many applications. The focus of the unsupervised anomaly detection literature has mostly been on vectorised data. However, many applications are more naturally described using higher-order tensor representations. Approaches that vectorise tensorial data can destroy the structural information encoded in the high-dimensional space, and lead to the problem of the curse of dimensionality. In this paper we present the first unsupervised tensorial anomaly detection method, along with a randomised version of our method. Our anomaly detection method, the One-class Support Tensor Machine (1STM), is a generalisation of conventional one-class Support Vector Machines to higher-order spaces. 1STM preserves the multiway structure of tensor data, while achieving significant improvement in accuracy and efficiency over conventional vectorised methods. We then leverage the theory of nonlinear random projections to propose the Randomised 1STM (R1STM). Our empirical analysis on several real and synthetic datasets shows that our R1STM algorithm delivers comparable or better accuracy to a state-of-the-art deep learning method and traditional kernelised approaches for anomaly detection, while being approximately 100 times faster in training and testing.