Ex-ante measure of patent quality reveals intrinsic fitness for citation-network growth

We have constructed a fitness parameter, characterizing the intrinsic attractiveness for patents to be cited, from attributes of the associated inventions known at the time a patent is granted. This exogenously obtained fitness is shown to determine the temporal growth of the citation network in conjunction with mechanisms of preferential attachment and obsolescence-induced ageing that operate without reference to characteristics of individual patents. Our study opens a window on understanding quantitatively the interplay of the rich-gets-richer and fit-gets-richer paradigms that have been suggested to govern the growth dynamics of real-world complex networks.Comment: 6 pages, 3 figures, RevTex4.1, v2: minor changes, version to appear as a Rapid Communication in Phys. Rev.

Unraveling the dynamics of growth, aging and inflation for citations to scientific articles from specific research fields

We analyze the time evolution of citations acquired by articles from journals of the American Physical Society (PRA, PRB, PRC, PRD, PRE and PRL). The observed change over time in the number of papers published in each journal is considered an exogenously caused variation in citability that is accounted for by a normalization. The appropriately inflation-adjusted citation rates are found to be separable into a preferential-attachment-type growth kernel and a purely obsolescence-related (i.e., monotonously decreasing as a function of time since publication) aging function. Variations in the empirically extracted parameters of the growth kernels and aging functions associated with different journals point to research-field-specific characteristics of citation intensity and knowledge flow. Comparison with analogous results for the citation dynamics of technology-disaggregated cohorts of patents provides deeper insight into the basic principles of information propagation as indicated by citing behavior.Comment: 13 pages, 6 figures, Elsevier style, v2: revised version to appear in J. Informetric

When, what and how image transformation techniques should be used to reduce error in Particle Image Velocimetry data?

© 2019 Elsevier Ltd Particle Image Velocimetry is commonly used to compute velocity fields in several areas including fluid mechanics, hydraulics and geophysics. However, acquired images often contain deformations caused either by camera lenses or placement. In this work the most popular digital transformation methods used to remove/reduce these deformations are benchmarked and suggestions tailoring specific transformations to different types of deformations are made. This article also shows the reduction of the error associated to the first and second order statistics, in the case of two-dimensional Particle Image Velocimetry, when the transformation techniques are applied to the computed velocity fields, and not the raw images, a common option in available commercial software

A Rapid, Empirical Method for Detection and Estimation of Outlier Frames in Particle Imaging Velocimetry Data using Proper Orthogonal Decomposition

This paper develops a method for detection and removal of outlier images from digital Particle Image Velocimetry data using Proper Orthogonal De-composition (POD). The outlier is isolated in the leading POD modes, removed and a replacement value re-estimated. The method is used to estimate and replace whole images within the sequence. This is particularly useful, if a single PIV image is suddenly heavily contaminated with background noise, or to estimate a dropped frame within a sequence. The technique is tested on a synthetic dataset that permits the effective acquisition frequency to be varied systematically, before application to flow field frames obtained from a large-eddy simulation. As expected, outlier re-estimation becomes more difficult when the integral time scale for the flow is long relative to the sampling period. However, the method provides a systematic improvement in predicting frames compared to interpolating from neighbouring(1) frames

Community structure in co-inventor networks affects time to first citation for patents

We have investigated community structure in the co-inventor network of a given cohort of patents and related this structure to the dynamics of how these patents acquire their first citation. A statistically significant difference in the time lag until first citation is linked to whether or not this citation comes from a patent whose listed inventors share membership in the same communities as the inventors of the cited patent. Although the inventor-community structures identified by different community-detection algorithms differ in several aspects, including the community-size distribution, the magnitude of the difference in time to first citation is robustly exhibited. Our work is able to quantify the expected acceleration of knowledge flow within inventor communities and thereby further establishes the utility of network-analysis tools for studying innovation dynamics.Comment: 16 pages, 4 figures, BioMedCentral article style, to appear in Applied Network Science - special issue 'Community structure in networks

Hydropyrolysis: implications for radiocarbon pre-treatment and characterization of Black Carbon

Charcoal is the result of natural and anthropogenic burning events, when biomass is exposed to elevated temperatures under conditions of restricted oxygen. This process produces a range of materials, collectively known as pyrogenic carbon, the most inert fraction of which is known as Black Carbon (BC). BC degrades extremely slowly, and is resistant to diagenetic alteration involving the addition of exogenous carbon making it a useful target substance for radiocarbon dating particularly of more ancient samples, where contamination issues are critical. We present results of tests using a new method for the quantification and isolation of BC, known as hydropyrolysis (hypy). Results show controlled reductive removal of non-BC organic components in charcoal samples, including lignocellulosic and humic material. The process is reproducible and rapid, making hypy a promising new approach not only for isolation of purified BC for 14C measurement but also in quantification of different labile and resistant sample C fractions

Tetrisation of triangular meshes and its application in shape blending

The As-Rigid-As-Possible (ARAP) shape deformation framework is a versatile technique for morphing, surface modelling, and mesh editing. We discuss an improvement of the ARAP framework in a few aspects: 1. Given a triangular mesh in 3D space, we introduce a method to associate a tetrahedral structure, which encodes the geometry of the original mesh. 2. We use a Lie algebra based method to interpolate local transformation, which provides better handling of rotation with large angle. 3. We propose a new error function to compile local transformations into a global piecewise linear map, which is rotation invariant and easy to minimise. We implemented a shape blender based on our algorithm and its MIT licensed source code is available online

Deep learnability: using neural networks to quantify language similarity and learnability

Learning a second language (L2) usually progresses faster if a learner's L2 is similar to their first language (L1). Yet global similarity between languages is difficult to quantify, obscuring its precise effect on learnability. Further, the combinatorial explosion of possible L1 and L2 language pairs, combined with the difficulty of controlling for idiosyncratic differences across language pairs and language learners, limits the generalisability of the experimental approach. In this study, we present a different approach, employing artificial languages and artificial learners. We built a set of five artificial languages whose underlying grammars and vocabulary were manipulated to ensure a known degree of similarity between each pair of languages. We next built a series of neural network models for each language, and sequentially trained them on pairs of languages. These models thus represented L1 speakers learning L2s. By observing the change in activity of the cells between the L1-speaker model and the L2-learner model, we estimated how much change was needed for the model to learn the new language. We then compared the change for each L1/L2 bilingual model to the underlying similarity across each language pair. The results showed that this approach can not only recover the facilitative effect of similarity on L2 acquisition, but can also offer new insights into the differential effects across different domains of similarity. These findings serve as a proof of concept for a generalisable approach that can be applied to natural languages

Effects of intradermal injection of atrial natriuretic peptide.

Abstract Atrial natriuretic peptide (ANP) causes mast cell degranulation in rats in vivo and in vitro but is bronchodilator in humans. The aim of this study was to investigate the wheal and flare dose-response to intradermal injection of alpha-human ANP in normal humans. Eight normal subjects received five 30 microliters injections containing 1, 10, 39, 78, 117 pmol ANP and one each of normal saline, histamine 675 pmol and substance P 30 pmol. Maximum ANP flare response was greater but not significantly than that to saline at 1.55 +/- 0.6 (mean +/- s.e. mean) compared with 0.42 +/- 0.17 cm2, but much less than to histamine 9.86 +/- 0.97 or to substance P 12.5 +/- 1.2. Maximum ANP wheal response was significantly greater than that to saline at 0.38 +/- 0.08 compared with 0.18 +/- 0.05 cm2 (difference between means 0.20, 95% CI 0.05, 0.35), but much less than to histamine 0.75 +/- 0.06 or to substance P 1.05 +/- 0.08 cm2. No dose-response to ANP was demonstrated, though responses to the highest dose differed significantly from those to the lowest dose studied. We conclude that human cutaneous responses to ANP differ from those of animals and that the skin is less responsive than other tissues in humans

Assessing the association between oral hygiene and preterm birth by quantitative light-induced fluorescence

The aim of this study was to investigate the purported link between oral hygiene and preterm birth by using image analysis tools to quantify dental plaque biofilm. Volunteers (η = 91) attending an antenatal clinic were identified as those considered to be “at high risk” of preterm delivery (i.e., a previous history of idiopathic preterm delivery, case group) or those who were not considered to be at risk (control group). The women had images of their anterior teeth captured using quantitative light-induced fluorescence (QLF). These images were analysed to calculate the amount of red fluorescent plaque (ΔR%) and percentage of plaque coverage. QLF showed little difference in ΔR% between the two groups, 65.00% case versus 68.70% control, whereas there was 19.29% difference with regard to the mean plaque coverage, 25.50% case versus 20.58% control. A logistic regression model showed a significant association between plaque coverage and case/control status (Ρ = 0.031), controlling for other potential predictor variables, namely, smoking status, maternal age, and body mass index (BMI)