Large‐Scale, Long‐Range‐Ordered Patterning of Nanocrystals via Capillary‐Bridge Manipulation

2017 ◽  
Vol 29 (46) ◽  
pp. 1703143 ◽  
Author(s):  
Jiangang Feng ◽  
Qian Song ◽  
Bo Zhang ◽  
Yuchen Wu ◽  
Tie Wang ◽  
...  
Keyword(s):  
Long Range ◽  
Large Scale ◽  
Capillary Bridge

scholarly journals TransMed: Transformers Advance Multi-Modal Medical Image Classification

Diagnostics ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1384
Author(s):  
Yin Dai ◽  
Yifan Gao ◽  
Fayu Liu
Keyword(s):  
Image Analysis ◽  
Image Classification ◽  
Long Range ◽  
Medical Image ◽  
Large Scale ◽  
Medical Images ◽  
Medical Image Analysis ◽  
Lesion Detection ◽  
Tumor Segmentation ◽  
Medical Image Classification

Over the past decade, convolutional neural networks (CNN) have shown very competitive performance in medical image analysis tasks, such as disease classification, tumor segmentation, and lesion detection. CNN has great advantages in extracting local features of images. However, due to the locality of convolution operation, it cannot deal with long-range relationships well. Recently, transformers have been applied to computer vision and achieved remarkable success in large-scale datasets. Compared with natural images, multi-modal medical images have explicit and important long-range dependencies, and effective multi-modal fusion strategies can greatly improve the performance of deep models. This prompts us to study transformer-based structures and apply them to multi-modal medical images. Existing transformer-based network architectures require large-scale datasets to achieve better performance. However, medical imaging datasets are relatively small, which makes it difficult to apply pure transformers to medical image analysis. Therefore, we propose TransMed for multi-modal medical image classification. TransMed combines the advantages of CNN and transformer to efficiently extract low-level features of images and establish long-range dependencies between modalities. We evaluated our model on two datasets, parotid gland tumors classification and knee injury classification. Combining our contributions, we achieve an improvement of 10.1% and 1.9% in average accuracy, respectively, outperforming other state-of-the-art CNN-based models. The results of the proposed method are promising and have tremendous potential to be applied to a large number of medical image analysis tasks. To our best knowledge, this is the first work to apply transformers to multi-modal medical image classification.

TrafficBERT: Pre-trained model with large-scale data for long-range traffic flow forecasting

2021 ◽  
pp. 115738
Author(s):  
KyoHoon Jin ◽  
JeongA Wi ◽  
EunJu Lee ◽  
ShinJin Kang ◽  
SooKyun Kim ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Long Range ◽  
Large Scale ◽  
Traffic Flow Forecasting ◽  
Large Scale Data ◽  
Scale Data

The Finale of Mahler's Fifth Symphony: Long-Range Musical Thought

1987 ◽  
Vol 112 (2) ◽  
pp. 257-279
Author(s):  
Carolyn Baxendale
Keyword(s):  
Long Range ◽  
Large Scale ◽  
New Technique ◽  
Musical Thought ◽  
Musical Concepts ◽  
A New Technique

It is clear that all the experience I had gained in writing the first four symphonies completely let me down in this one- for a completely new style demanded a new technique.Twenty-Five years ago a prominent Mahler enthusiast could describe the finale of Mahler's Fifth Symphony as ‘a windy, uninspired stretch of note-spinning, literally scraping the barrel in search of music’. Few people nowadays would subscribe to this view: indeed the upsurge of interest in the work of other ‘late Romantic’ composers has perhaps served to sharpen our admiration for Mahler's exceptional powers of invention and his no less extraordinary mastery of large-scale form. Yet we are not really any closer to explaining just how such extended works are held together and given shape, particularly in the absence of specific extra-musical concepts such as those of the ‘Wunderhorn’ symphonies.

scholarly journals Lagrangian formation pathways of moist anomalies in the trade-wind region during the dry season: two case studies from EUREC<sup>4</sup>A

2021 ◽  
Author(s):  
Leonie Villiger ◽  
Heini Wernli ◽  
Maxi Boettcher ◽  
Martin Hagen ◽  
Franziska Aemisegger
Keyword(s):  
Long Range ◽  
North Atlantic ◽  
Large Scale ◽  
Cold Front ◽  
Trade Wind ◽  
Long Range Transport ◽  
The North ◽  
Range Transport ◽  
The North Atlantic ◽  
The Tropics

Abstract. Shallow clouds in the trade-wind region over the North Atlantic contribute substantially to the global radiative budget. In the vicinity of the Caribbean island Barbados, they appear in different mesoscale organisation patterns with distinct net cloud radiative effects (CRE). Cloud formation processes in this region are typically controlled by the prevailing large-scale subsidence. However, occasionally weather systems from remote origin cause significant disturbances. This study investigates the complex cloud-circulation interactions during the field campaign EUREC4A (Elucidate the Couplings Between Clouds, Convection and Circulation) from 16 January to 20 February 2020, using a combination of Eulerian and Lagrangian diagnostics. Based on observations and ERA5 reanalyses, we identify the relevant processes and characterise the formation pathways of two moist anomalies above the Barbados Cloud Observatory (BCO), one in the lower (~1000–650 hPa) and one in the middle troposphere (~650–300 hPa). These moist anomalies are associated with strongly negative CRE values and with contrasting long-range transport processes from the extratropics and the tropics, respectively. The low-level moist anomaly is characterised by an unusually thick cloud layer, high precipitation totals and a strongly negative CRE. Its formation is connected to an “extratropical dry intrusion” (EDI) that interacts with a trailing cold front. A quasi-climatological (2010–2020) analysis reveals that EDIs lead to different conditions at the BCO depending on how they interact with the associated cold front. Based on this climatology, we discuss the relevance of the strong large-scale forcing by EDIs for the low-cloud patterns near the BCO and the related CRE. The second case study about the mid-tropospheric moist anomaly is associated with an extended and persistent mixed-phase shelf cloud and the lowest daily CRE value observed during the campaign. Its formation is linked to “tropical mid-level detrainment” (TMD), which refers to detrainment from tropical deep convection near the melting layer. The quasi-climatological analysis shows that TMDs consistently lead to mid-tropospheric moist anomalies over the BCO and that the detrainment height controls the magnitude of the anomaly. However, no systematic relationship was found between the amplitude of this mid-tropospheric moist anomaly and the CRE at the BCO. Overall, this study reveals the important impact of the long-range transport, driven by dynamical processes either in the extratropics or the tropics, on the variability of the vertical structure of moisture and clouds, and on the resulting CRE in the North Atlantic winter trades.

scholarly journals Long range predictability of atmospheric flows

2001 ◽  
Vol 8 (1/2) ◽  
pp. 55-67 ◽  
Author(s):  
R. Robert ◽  
C. Rosier
Keyword(s):  
Long Range ◽  
Degrees Of Freedom ◽  
Large Scale ◽  
Local Perturbation ◽  
Atmospheric Flow ◽  
Atmospheric Flows ◽  
2D Euler Equations ◽  
Large Scale Change ◽  
The One ◽  
Scale Motion

Abstract. In the light of recent advances in 2D turbulence, we investigate the long range predictability problem of atmospheric flows. Using 2D Euler equations, we show that the full nonlinearity acting on a large number of degrees of freedom can, paradoxically, improve the predictability of the large scale motion, giving a picture opposite to the one largely popularized by Lorenz: a small local perturbation of the atmosphere will progressively gain larger and larger scales by nonlinear interaction and will finally cause large scale change in the atmospheric flow.

scholarly journals Long-range coupling and scalable architecture for superconducting flux qubits

2008 ◽  
Vol 86 (4) ◽  
pp. 533-540
Author(s):  
A G Fowler ◽  
W F Thompson ◽  
Z Yan ◽  
A M Stephens ◽  
B L.T. Plourde ◽  
...  
Keyword(s):  
Long Range ◽  
Large Scale ◽  
Quantum Computer ◽  
Fault Tolerant ◽  
Maximum Error ◽  
Error Rates ◽  
Coupling Mechanism ◽  
Scalable Architectures ◽  
Daunting Task ◽  
Flux Qubits

Constructing a fault-tolerant quantum computer is a daunting task. Given any design, it is possible to determine the maximum error rate of each type of component that can be tolerated while still permitting arbitrarily large-scale quantum computation. It is an under-appreciated fact that including an appropriately designed mechanism enabling long-range qubit coupling or transport substantially increases the maximum tolerable error rates of all components. With this thought in mind, we take the superconducting flux qubit coupling mechanism described in Plourde et al. (Phys. Rev. B, 70, 140501(R) (2004)) and extend it to allow approximately 500~MHz coupling of square flux qubits, 50 µm a side, at a distance of up to several mm. This mechanism is then used as the basis of two scalable architectures for flux qubits taking into account crosstalk and fault-tolerant considerations such as permitting a universal set of logical gates, parallelism, measurement and initialization, and data mobility.PACS No.: 03.67.Lx

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