65 research outputs found

    Phase-field modeling of eutectic structures on the nanoscale: the effect of anisotropy

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    This is a post-peer-review, pre-copyedit version of an article published in Journal of Materials Science. The final authenticated version is available online at: https://doi.org/10.1007/s10853-017-0853-8A simple phase-field model is used to address anisotropic eutectic freezing on the nanoscale in two (2D) and three dimensions (3D). Comparing parameter-free simulations with experiments, it is demonstrated that the employed model can be made quantitative for Ag-Cu. Next, we explore the effect of material properties, and the conditions of freezing on the eutectic pattern. We find that the anisotropies of kinetic coefficient and the interfacial free energies (solid-liquid and solid-solid), the crystal misorientation relative to pulling, the lateral temperature gradient, play essential roles in determining the eutectic pattern. Finally, we explore eutectic morphologies, which form when one of the solid phases are faceted, and investigate cases, in which the kinetic anisotropy for the two solid phases are drastically different

    Can human amblyopia be treated in adulthood?

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    Amblyopia is a common visual disorder that results in a spatial acuity deficit in the affected eye. Orthodox treatment is to occlude the unaffected eye for lengthy periods, largely determined by the severity of the visual deficit at diagnosis. Although this treatment is not without its problems (poor compliance, potential to reduce binocular function, etc) it is effective in many children with moderate to severe amblyopia. Diagnosis and initiation of treatment early in life are thought to be critical to the success of this form of therapy. Occlusion is rarely undertaken in older children (more than 10 years old) as the visual benefits are considered to be marginal. Therefore, in subjects where occlusion is not effective or those missed by mass screening programs, there is no alternative therapy available later in life. More recently, burgeoning evidence has begun to reveal previously unrecognized levels of residual neural plasticity in the adult brain and scientists have developed new genetic, pharmacological, and behavioral interventions to activate these latent mechanisms in order to harness their potential for visual recovery. Prominent amongst these is the concept of perceptual learning—the fact that repeatedly practicing a challenging visual task leads to substantial and enduring improvements in visual performance over time. In the normal visual system the improvements are highly specific to the attributes of the trained stimulus. However, in the amblyopic visual system, learned improvements have been shown to generalize to novel tasks. In this paper we ask whether amblyopic deficits can be reduced in adulthood and explore the pattern of transfer of learned improvements. We also show that developing training protocols that target the deficit in stereo acuity allows the recovery of normal stereo function even in adulthood. This information will help guide further development of learning-based interventions in this clinical group

    Particulate Matter, Color, Turbidity, and Light

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    Cloud Type Identification Using Data Fusion and Ensemble Learning

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    Cloud type classification is a complex multi-class problem where total sky images are analysed to determine their category such as Stratus or Cirrus, among others. However, many properties of this domain make high classification accuracy difficult to achieve. In this paper, we design a novel fusion approach, showing that recent image classification architectures based on deep learning, such as Convolutional Neural Networks, can be improved using statistical features directly calculated from images. In this research, three powerful CNNs have been trained on a comprehensive dataset: VGG-19, Inception-ResNet V2 and Inception V3. Simultaneously, a pool of standard machine learning classifiers have been trained on 14 different statistical characteristics on each colour channel. The results evidence that a fusion approach of the predictions of an image-trained CNN and a feature-trained Random Forest classifier improves the classification ability of both methods individually, reaching 95.05% macro average weighted precision over 12 classes in a complex highly imbalanced dataset with noisy examples.Ministerio de Ciencia y Educación (TIN2014-56494-C4-4-P)Comunidad Autónoma de Madrid (S2018/TCS-4566)No data JCR 20190.427 SJR (2019) Q3, 113/393 Computer Science (miscellaneous)No data IDR 2019UE

    Rebels without a conscience: the evolution of the rogue states narrative in US security policy

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    This article examines how the foundations of the ‘rogue states’ security narrative in the United States developed prior to the declaration of the George W. Bush administration’s ‘Global War on Terror’ and President Bush’s representation of Iraq, Iran and North Korea as an ‘axis of evil’. The article argues that the puzzle of how US post-Cold War foreign and defence policy came to be focused on ‘irrational’ — but militarily inferior — adversaries can be understood through analysing how actors within the US defence community discursively constructed discrete international crises as the trigger for a major shift in US threat scenarios. This is developed through an examination of two crucial episodes in the construction of post-Cold War US national security interests: the crisis in the Persian Gulf in 1990–1 and the North Korean nuclear crisis in 1993–4. The article suggests the importance of historicizing contests over the interpretation of international crises in order to both better understand the process through which a country’s national security interests are defined and to gain greater analytical purchase on how security narratives are reconstructed during processes of systemic change
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