Reservoir computing and data visualisation

We consider the problem of visualisation of high dimensional multivariate time series. A data analyst in creating a two dimensional projection of such a time series might hope to gain some intuition into the structure of the original high dimensional data set. We review a method for visualising time series data using an extension of Echo State Networks (ESNs). The method uses the multidimensional scaling criterion in order to create a visualisation of the time series after its representation in the reservoir of the ESN. We illustrate the method with two dimensional maps of a financial time series. The method is then compared with a mapping which uses a fixed latent space and a novel objective function

Cost-optimized heterogeneous FPGA architecture for non-iterative hologram generation.

The generation of computer-generated holograms (CGHs) requires a significant amount of computational power. To accelerate the process, highly parallel field-programmable gate arrays (FPGAs) are deemed to be a promising computing platform to implement non-iterative hologram generation algorithms. In this paper, we present a cost-optimized heterogeneous FPGA architecture based on a one-step phase retrieval algorithm for CGH generation. The results indicate that our hardware implementation is 2.5× faster than the equivalent software implementation on a personal computer with a high-end multi-core CPU. Trade-offs between cost and performance are demonstrated, and we show that the proposed heterogeneous architecture can be used in a compact display system that is cost and size optimized

Hardware implementations of computer-generated holography: a review

Computer-generated holography (CGH) is a technique to generate holographic interference patterns. One of the major issues related to computer hologram generation is the massive computational power required. Hardware accelerators are used to accelerate this process. Previous publications targeting hardware platforms lack performance comparisons between different architectures and do not provide enough information for the evaluation of the suitability of recent hardware platforms for CGH algorithms. We aim to address these limitations and present a comprehensive review of CGH-related hardware implementations

AWPP: A New Scheme for Wireless Access Control Proportional to Traffic Priority and Rate

Cutting-edge wireless networking approaches are required to efficiently differentiate traffic and handle it according to its special characteristics. The current Medium Access Control (MAC) scheme which is expected to be sufficiently supported by well-known networking vendors comes from the IEEE 802.11e workgroup. The standardized solution is the Hybrid Coordination Function (HCF), that includes the mandatory Enhanced Distributed Channel Access (EDCA) protocol and the optional Hybrid Control Channel Access (HCCA) protocol. These two protocols greatly differ in nature and they both have significant limitations. The objective of this work is the development of a high-performance MAC scheme for wireless networks, capable of providing predictable Quality of Service (QoS) via an efficient traffic differentiation algorithm in proportion to the traffic priority and generation rate. The proposed Adaptive Weighted and Prioritized Polling (AWPP) protocol is analyzed, and its superior deterministic operation is revealed

Introducing a nonvolatile N-type dopant drastically improves electron transport in polymer and small-molecule organic transistors

KGaA, Weinheim Molecular doping is a powerful yet challenging technique for enhancing charge transport in organic semiconductors (OSCs). While there is a wealth of research on p-type dopants, work on their n-type counterparts is comparatively limited. Here, reported is the previously unexplored n-dopant (12a,18a)-5,6,12,12a,13,18,18a,19-octahydro-5,6-dimethyl- 13,18[1′,2′]-benzenobisbenzimidazo [1,2-b:2′,1′-d]benzo[i][2.5]benzodiazo-cine potassium triflate adduct (DMBI-BDZC) and its application in organic thin-film transistors (OTFTs). Two different high electron mobility OSCs, namely, the polymer poly[[N,N′-bis(2-octyldodecyl)-naphthalene-1,4,5,8- bis(dicarboximide)-2,6-diyl]-alt-5,5′-(2′-bithiophene)] and a small-molecule naphthalene diimides fused with 2-(1,3-dithiol-2-ylidene)malononitrile groups (NDI-DTYM2) are used to study the effectiveness of DMBI-BDZC as a n-dopant. N-doping of both semiconductors results in OTFTs with improved electron mobility (up to 1.1 cm2 V−1 s−1), reduced threshold voltage and lower contact resistance. The impact of DMBI-BDZC incorporation is particularly evident in the temperature dependence of the electron transport, where a significant reduction in the activation energy due to trap deactivation is observed. Electron paramagnetic resonance measurements support the n-doping activity of DMBI-BDZC in both semiconductors. This finding is corroborated by density functional theory calculations, which highlights ground-state electron transfer as the main doping mechanism. The work highlights DMBI-BDZC as a promising n-type molecular dopant for OSCs and its application in OTFTs, solar cells, photodetectors, and thermoelectrics

Surveying adjustment datum and relative deformation accuracy analysis

In the surveying adjustment, unknown parameters are usually not direct observations, but the elements related to these direct observations. In order to determine the unknown parameters adequate known data should be provided, and these necessarily required known data are used to form the adjustment datum. Under different datums, different results will be obtained even with the same direct observations. However, in the practical adjustment calculation, the datum and its effect on the results are always ignored. In this paper, the adjustment datum is firstly discussed and defined as datum equations. Then an adjustment method based on the datum equations and least squares is presented. This method is a generic one, not only suited for the case in an ordinary datum but also in the gravity centre datum or a quasi-datum, and can be easily used to analyse different deformations. Based on this method, the transformation between different reference frames is derived. It shows that the calculation results, deformation and positioning accuracy under one kind of datum are relative and generic. A case study is further introduced and used to test this new method. Based on the case study, the conclusions are reached. It is found that the relative positional root mean square error of each point becomes bigger as the distance between the point and the datum increases, and the relative deformation offsets under different kinds of datum are helpful for reliable deformation analysis

In situ evidence for the structure of the magnetic null in a 3D reconnection event in the Earth's magnetotail

Magnetic reconnection is one of the most important processes in astrophysical, space and laboratory plasmas. Identifying the structure around the point at which the magnetic field lines break and subsequently reform, known as the magnetic null point, is crucial to improving our understanding reconnection. But owing to the inherently three-dimensional nature of this process, magnetic nulls are only detectable through measurements obtained simultaneously from at least four points in space. Using data collected by the four spacecraft of the Cluster constellation as they traversed a diffusion region in the Earth's magnetotail on 15 September, 2001, we report here the first in situ evidence for the structure of an isolated magnetic null. The results indicate that it has a positive-spiral structure whose spatial extent is of the same order as the local ion inertial length scale, suggesting that the Hall effect could play an important role in 3D reconnection dynamics.Comment: 14 pages, 4 figure

Biomimetic intrafibrillar mineralization of type I collagen with intermediate precursors-loaded mesoporous carriers

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Causal-Aware Generative Imputation for Automated Underwriting

Underwriting is an important process in insurance and is concerned with accepting individuals into insurance policy with tolerable claim risk. Underwriting is a tedious and labor intensive process relying on underwriters' domain knowledge and experience, thus is labor intensive and prone to error. Machine learning models are recently applied to automate the underwriting process and thus to ease the burden on the underwriters as well as improve underwriting accuracy. However, observational data used for underwriting modelling is high dimensional, sparse and incomplete, due to the dynamic evolving nature (e.g., upgrade) of business information systems. Simply applying traditional supervised learning methods e.g., logistic regression or Gradient boosting on such highly incomplete data usually leads to the unsatisfactory underwriting result, thus requiring practical data imputation for training quality improvement. In this paper, rather than choosing off-the-shelf solutions tackling the complex data missing problem, we propose an innovative Generative Adversarial Nets (GAN) framework that can capture the missing pattern from a causal perspective. Specifically, we design a structural causal model to learn the causal relations underlying the missing pattern of data. Then, we devise a Causality-aware Generative network (CaGen) using the learned causal relationship prior to generating missing values, and correct the imputed values via the adversarial learning. We also show that CaGen significantly improves the underwriting prediction in real-world insurance applications

Regulation of Gdf5 expression in joint remodelling, repair and osteoarthritis

Funding: Arthritis Research UK (grants no. 20775, 19667, 20865, 21156); European Union’s Horizon 2020 research and innovation programme under Marie Sklodowska Curie grant agreement no. 642414; Medical Research Council (grant MR/L022893/1); A.H.K.R. was supported by the Wellcome Trust through the Scottish Translational Medicine and Therapeutics Initiative (grant no. WT 085664). The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.Peer reviewedPublisher PD