Trans-dimensional inversion of modal dispersion data on the New England Mud Patch

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Bonnel, J., Dosso, S. E., Eleftherakis, D., & Chapman, N. R. Trans-dimensional inversion of modal dispersion data on the New England Mud Patch. IEEE Journal of Oceanic Engineering, 45(1), (2020): 116-130, doi:10.1109/JOE.2019.2896389.This paper presents single receiver geoacoustic inversion of two independent data sets recorded during the 2017 seabed characterization experiment on the New England Mud Patch. In the experimental area, the water depth is around 70 m, and the seabed is characterized by an upper layer of fine grained sediments with clay (i.e., mud). The first data set considered in this paper is a combustive sound source signal, and the second is a chirp emitted by a J15 source. These two data sets provide differing information on the geoacoustic properties of the seabed, as a result of their differing frequency content, and the dispersion properties of the environment. For both data sets, source/receiver range is about 7 km, and modal time-frequency dispersion curves are estimated using warping. Estimated dispersion curves are then used as input data for a Bayesian trans-dimensional inversion algorithm. Subbottom layering and geoacoustic parameters (sound speed and density) are thus inferred from the data. This paper highlights important properties of the mud, consistent with independent in situ measurements. It also demonstrates how information content differs for two data sets collected on reciprocal tracks, but with different acoustic sources and modal content.10.13039/100000006-Office of Naval Research 10.13039/100007297-Office of Naval Research Globa

A Bayesian spatial random effects model characterisation of tumour heterogeneity implemented using Markov chain Monte Carlo (MCMC) simulation

The focus of this study is the development of a statistical modelling procedure for characterising intra-tumour heterogeneity, motivated by recent clinical literature indicating that a variety of tumours exhibit a considerable degree of genetic spatial variability. A formal spatial statistical model has been developed and used to characterise the structural heterogeneity of a number of supratentorial primitive neuroecto-dermal tumours (PNETs), based on diffusionweighted magnetic resonance imaging. Particular attention is paid to the spatial dependence of diffusion close to the tumour boundary, in order to determine whether the data provide statistical evidence to support the proposition that water diffusivity in the boundary region of some tumours exhibits a deterministic dependence on distance from the boundary, in excess of an underlying random 2D spatial heterogeneity in diffusion. Tumour spatial heterogeneity measures were derived from the diffusion parameter estimates obtained using a Bayesian spatial random effects model. The analyses were implemented using Markov chain Monte Carlo (MCMC) simulation. Posterior predictive simulation was used to assess the adequacy of the statistical model. The main observations are that the previously reported relationship between diffusion and boundary proximity remains observable and achieves statistical significance after adjusting for an underlying random 2D spatial heterogeneity in the diffusion model parameters. A comparison of the magnitude of the boundary-distance effect with the underlying random 2D boundary heterogeneity suggests that both are important sources of variation in the vicinity of the boundary. No consistent pattern emerges from a comparison of the boundary and core spatial heterogeneity, with no indication of a consistently greater level of heterogeneity in one region compared with the other. The results raise the possibility that DWI might provide a surrogate marker of intra-tumour genetic regional heterogeneity, which would provide a powerful tool with applications in both patient management and in cancer research

Labor Mobility across the Formal/Informal Divide in Turkey: Evidence from Individual Level Data

Informality has long been a salient phenomenon in developing country labor markets, thus has been addressed in several theoretical and empirical research. Turkey, given its economic and demographic dynamics, provides rich evidence for a growing, heterogeneous and multifaceted informal labor market. However, the existing evidence on labor informality in Turkey is mixed and scant. Along these lines, we aim to extend the existing literature by providing a diagnosis of dynamic worker flows across distinct labor market states and identifying the effects of certain individual and job characteristics on variant mobility patterns. More specifically, we first develop and discuss a set of probability statistics based on annual worker transitions across distinct employment states utilizing Markov transition processes. As Bosch and Maloney (2007:3) argue: “labor status mobility can be assumed as a process in which changes in the states occur randomly through time, and probabilities of moves between particular states are governed by Markov transition matrices”. Towards this end, we will use the novel Income and Living Conditions Survey (SILC) panel data set to compute the transition probabilities of individuals moving across the labor market states of formal-salaried, informal-salaried, formal self-employed, informal self-employed, unemployed and inactive. The transitions analysis is conducted separately for two, three and four year panels pertaining to 2006 to 2007, 2006 to 2008 and 2006 to 2009 transitions; for total, male and female samples; and lastly for total and non-agricultural samples. In this way, we aim to contribute to the limited body of stylized facts available on mobility and informality in the Turkish labor market. Next, we conduct multinomial logit regressions individually for each set of panel to identify the impact of individual characteristics (i.e. gender, age, education level, work experience, sector of economic activity, firm size, number of other household members, having/not having children, rural/urban) underlying worker transitions. The results reveal several relationships between the covariates and likelihood of variant transitions, and are of remarkable importance for designing policy to address labor informality and reduce its negative externalities.Labor market dynamics, informality, Markov processes, multinomial logit, Turkey

Labor Mobility Across The Formal/Informal Divide in Turkey: Evidence From Individual Level Data

Informality has long been a salient phenomenon in developing country labor markets, thus has been addressed in several theoretical and empirical research. Turkey, given its economic and demographic dynamics, provides rich evidence for a growing, heterogeneous and multifaceted informal labor market. However, the existing evidence on labor informality in Turkey is mixed and scant. Along these lines, we aim to extend the existing literature by providing a diagnosis of dynamic worker flows across distinct labor market states and identifying the effects of certain individual and job characteristics on variant mobility patterns. More specifically, we first develop and discuss a set of probability statistics based on annual worker transitions across distinct employment states utilizing Markov transition processes. As Bosch and Maloney (2007:3) argue: “labor status mobility can be assumed as a process in which changes in the states occur randomly through time, and probabilities of moves between particular states are governed by Markov transition matrices”. Towards this end, we will use the novel Income and Living Conditions Survey (SILC) panel data set to compute the transition probabilities of individuals moving across the labor market states of formal-salaried, informal-salaried, formal self-employed, informal self-employed, unemployed and inactive. The transitions analysis is conducted separately for two, three and four year panels pertaining to 2006 to 2007, 2006 to 2008 and 2006 to 2009 transitions; for total, male and female samples; and lastly for total and non-agricultural samples. In this way, we aim to contribute to the limited body of stylized facts available on mobility and informality in the Turkish labor market. Next, we conduct multinomial logit regressions individually for each set of panel to identify the impact of individual characteristics (i.e. gender, age, education level, work experience, sector of economic activity, firm size, number of other household members, having/not having children, rural/urban) underlying worker transitions. The results reveal several relationships between the covariates and likelihood of variant transitions, and are of remarkable importance for designing policy to adress labor informality and reduce its negative externalities.Labor market dynamics, informality, Markov processes, multinomial logit, Turkey

Labor Mobility across the Formal/Informal Divide in Turkey: Evidence from Individual Level Data

Informality has long been a salient phenomenon in developing country labor markets, thus has been addressed in several theoretical and empirical research. Turkey, given its economic and demographic dynamics, provides rich evidence for a growing, heterogeneous and multifaceted informal labor market. However, the existing evidence on labor informality in Turkey is mixed and scant. Along these lines, we aim to extend the existing literature by providing a diagnosis of dynamic worker flows across distinct labor market states and identifying the effects of certain individual and job characteristics on variant mobility patterns. More specifically, we first develop and discuss a set of probability statistics based on annual worker transitions across distinct employment states utilizing Markov transition processes. As Bosch and Maloney (2007:3) argue: "labor status mobility can be assumed as a process in which changes in the states occur randomly through time, and probabilities of moves between particular states are governed by Markov transition matrices". Towards this end, we will use the novel Income and Living Conditions Survey (SILC) panel data set to compute the transition probabilities of individuals moving across the labor market states of formal-salaried, informal-salaried, formal self-employed, informal self-employed, unemployed and inactive. The transitions analysis is conducted separately for two, three and four year panels pertaining to 2006 to 2007, 2006 to 2008 and 2006 to 2009 transitions; for total, male and female samples; and lastly for total and non-agricultural samples. In this way, we aim to contribute to the limited body of stylized facts available on mobility and informality in the Turkish labor market. Next, we conduct multinomial logit regressions individually for each set of panel to identify the impact of individual characteristics (i.e. gender, age, education level, work experience, sector of economic activity, firm size, number of other household members, having/not having children, rural/urban) underlying worker transitions. The results reveal several relationships between the covariates and likelihood of variant transitions, and are of remarkable importance for designing policy to address labor informality and reduce its negative externalities.labor market dynamics, informality, Markov processes, multinomial logit, Turkey