scholarly journals Reversing “drift”: Innovation and diffusion in the London diphthong system

2008 ◽  
Vol 20 (3) ◽  
pp. 451-491 ◽  
Author(s):  
Paul Kerswill ◽  
Eivind Nessa Torgersen ◽  
Susan Fox

AbstractThis study contributes to innovation and diffusion models by examining phonetic changes in London English. It evaluates Sapir's notion of “drift,” which involves “natural,” unconscious change, in relation to these changes. Investigating parallel developments in two related varieties of English enables drift to be tested in terms of the effect of extralinguistic factors. The diphthongs ofprice,mouth,face, andgoatin both London and New Zealand English are characterized by “Diphthong Shift,” a process that continued unabated in New Zealand. A new, large data set of London speech shows Diphthong Shift reversal, providing counterevidence for drift. We discuss Diphthong Shift and its “reversal” in relation to innovation, diffusion, leveling, and supralocalization, arguing that sociolinguistic factors and dialect contact override natural Diphthong Shift. Studying dialect change in a metropolis, with its large and linguistically innovative minority ethnic population, is of the utmost importance in understanding the dynamics of change.

2019 ◽  
Vol 191 (1) ◽  
pp. 1-17 ◽  
Author(s):  
Matt H Buys ◽  
Richard C Winkworth ◽  
Peter J de Lange ◽  
Peter G Wilson ◽  
Nora Mitchell ◽  
...  

Abstract Leptospermum scoparium (Myrtaceae) is a morphologically highly variable species found in mainland Australia, Tasmania and New Zealand. For example, in New Zealand up to six morphologically distinct varieties of this species have been described, although only two (var. scoparium and var. incanum) are now formally recognized. In the present study we provide a first examination of genetic diversity in this culturally and commercially important species with the aim of gaining insights into its origins and evolution. We used anchored hybrid enrichment to acquire sequence data from 485 orthologous low-copy nuclear loci for 27 New Zealand and three Australian accessions of L. scoparium and representatives of several other Leptospermum spp. The final concatenated data matrix contained 421 687 nucleotide positions of which 55 102 were potentially informative. Despite the relative large data set, our analyses suggest that a combination of low and incompatible data signal limits the resolution of relationships among New Zealand populations of L. scoparium. Nevertheless, our analyses are consistent with genetic diversity being geographically structured, with three groups of L. scoparium recovered. We discuss the evolutionary and taxonomic implications of our findings.


2008 ◽  
Vol 2 (1) ◽  
pp. 89-106
Author(s):  
Joshua Cohen ◽  
Laura Faden ◽  
Kenneth Getz

In the US, there is a vigorous public debate on the merits of biopharmaceutical innovations and their diffusion. There is virtual unanimity about the importance of maintaining a steady stream of biopharmaceutical innovations, to which patients should have timely access. However, the debate’s participants are cognizant that the effects of innovation and diffusion on health outcomes, health care spending, and incentives for future innovation, must be weighed against one another. First, we performed a Medline literature review to map the innovation diffusion process, combining the search terms “innovation,” “diffusion,” and “pharmaceutical.” Second, we conducted a survey of 190 physicians to examine their valuation of the innovativeness and rate of diffusion of 20 new molecular entities (NMEs). Third, we collected data from the Centers for Medicare and Medicaid Services (CMS) Formulary Finder to assess payers’ valuation of the innovativeness of the 20 NMEs in question. Based on our literature review, we identified the key stakeholders involved in the innovation diffusion process. Furthermore, we highlighted the changing landscape of translational movers and shakers, tracing the emergence of T2 barriers, emanating largely from third party payer formulary management. Our empirical analysis suggests payers are exerting influence on physicians’ prescribing decisions, while the role of patients and pharmaceutical firms has diminished somewhat. Payers directly affect prescribing decisions through the use of formularies, and indirectly by funding evidence-based continuing medical education. On average, across the 20 drugs we sampled, the time from approval to first prescription was 33 months, which indicates a slow diffusion process. Our data analysis shows a gap in perception of innovativeness between physicians and payers, with physicians ranking drugs as more innovative on average than payers. And, our findings suggest the more innovative a drug is perceived by physicians and payers the higher market share it has. Striking an appropriate balance on access to and cost of biopharmaceuticals will require policy adjustments on the part of payers. In cases in which there is a large degree of uncertainty or the fiscal impact is particularly high, coverage could be made subject to a policy of coverage with evidence development (CED). Here, coverage would be conditional on development and capture of outcome data. A CED policy could be combined with a risk-sharing arrangement in which financial risk is shared between payers and the biopharmaceutical industry.


Author(s):  
Yongqiang Chu

Abstract Objectives Utilizing policy innovation and diffusion theory, this study aims to explain why city governments adopt housing adaptation policies that primarily benefit older people based on the case of China. Methods The data are drawn from an event history data set of a housing adaptation policy for older people collected from 283 Chinese cities from 2010 to 2018. Piecewise constant exponential models are utilized. Results The results indicate that cities facing greater internal pressure and a higher political status are more likely to adopt a housing adaptation policy for older people. Policy adoption by neighboring cities could further facilitate this process. Discussion Policy innovation and diffusion theory provide a useful framework for this study. That is, the Chinese city government’s adoption of housing adaptation policy for older adults is initially driven by local needs and then accelerated by interactions among neighboring governments.


2020 ◽  
Vol 39 (5) ◽  
pp. 6419-6430
Author(s):  
Dusan Marcek

To forecast time series data, two methodological frameworks of statistical and computational intelligence modelling are considered. The statistical methodological approach is based on the theory of invertible ARIMA (Auto-Regressive Integrated Moving Average) models with Maximum Likelihood (ML) estimating method. As a competitive tool to statistical forecasting models, we use the popular classic neural network (NN) of perceptron type. To train NN, the Back-Propagation (BP) algorithm and heuristics like genetic and micro-genetic algorithm (GA and MGA) are implemented on the large data set. A comparative analysis of selected learning methods is performed and evaluated. From performed experiments we find that the optimal population size will likely be 20 with the lowest training time from all NN trained by the evolutionary algorithms, while the prediction accuracy level is lesser, but still acceptable by managers.


2018 ◽  
Author(s):  
Barton Hamilton ◽  
Andrés Hincapié ◽  
Robert Miller ◽  
Nicholas Papageorge

2019 ◽  
Vol 21 (9) ◽  
pp. 662-669 ◽  
Author(s):  
Junnan Zhao ◽  
Lu Zhu ◽  
Weineng Zhou ◽  
Lingfeng Yin ◽  
Yuchen Wang ◽  
...  

Background: Thrombin is the central protease of the vertebrate blood coagulation cascade, which is closely related to cardiovascular diseases. The inhibitory constant Ki is the most significant property of thrombin inhibitors. Method: This study was carried out to predict Ki values of thrombin inhibitors based on a large data set by using machine learning methods. Taking advantage of finding non-intuitive regularities on high-dimensional datasets, machine learning can be used to build effective predictive models. A total of 6554 descriptors for each compound were collected and an efficient descriptor selection method was chosen to find the appropriate descriptors. Four different methods including multiple linear regression (MLR), K Nearest Neighbors (KNN), Gradient Boosting Regression Tree (GBRT) and Support Vector Machine (SVM) were implemented to build prediction models with these selected descriptors. Results: The SVM model was the best one among these methods with R2=0.84, MSE=0.55 for the training set and R2=0.83, MSE=0.56 for the test set. Several validation methods such as yrandomization test and applicability domain evaluation, were adopted to assess the robustness and generalization ability of the model. The final model shows excellent stability and predictive ability and can be employed for rapid estimation of the inhibitory constant, which is full of help for designing novel thrombin inhibitors.


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