Productivity and labour demand effects of inward and outward foreign direct investment on UK industry

We relate the technological and factor price determinants of inward and outward foreign direct investment (FDI) to its potential productivity and labour market effects on both host and home economies. This allows us to distinguish clearly between technology-sourcing and technologyexploiting FDI, and to identify FDI that is linked to labour cost differentials. We then empirically examine the effects of different types of FDI into and out of the UK on domestic (i.e. UK) productivity and on the demand for skilled and unskilled labour at the industry level.

Productivity and labour demand effects of inward and outward FDI on UK industry

We relate the technological and factor price determinants of inward and outward FDI to its potential productivity and labour market effects on both host and home economies. This allows us to distinguish clearly between technology sourcing and technology exploiting FDI, and to identify FDI which is linked to labour cost differentials. We then empirically examine the effects of different types of FDI into and out of the United Kingdom on domestic (i.e. UK) productivity and on the demand for skilled and unskilled labour at the industry level. Inward investment into the UK comes overwhelmingly from sectors and countries which have a technological advantage over the corresponding UK sector. Outward FDI shows a quite different pattern, dominated by investment into foreign sectors which have lower unit labour costs than the UK. We find that different types of FDI have markedly different productivity and labour demand effects, which may in part explain the lack of consensus in the empirical literature on the effects of FDI. Our results also highlight the difficulty for policy makers of simultaneously improving employment and domestic productivity through FDI.

NEIGHBORHOOD PERCEPTION OF SAFETY AND THE MOBILITY GAP BETWEEN MEN AND WOMEN IN OLD AGE

Background and Objectives: Mobility limitations are a prevalent issue in older adult populations, and an important determinant of disability and mortality. Neighborhood conditions are key determinants of mobility and perception of safety may be one such determinant. Women have more mobility limitations than men, a phenomenon known as the gender mobility gap. The objective of this work was to validate a measure of perception of safety, examine the relationship between neighborhood perception of safety and mobility limitations in seniors, and explore if these effects vary by gender. Methods: This study was cross-sectional, using questionnaire data collected from community-dwelling older adults from four sites in Canada, Colombia, and Brazil. The exposure variable was the neighborhood aggregated Perception of Safety (PoS) scale, derived from the Physical and Social Disorder (PSD) scale by Sampson and Raudenbush. Its construct validity was verified using factor analyses and correlation with similar measures. The Mobility Assessment Tool – short form (MAT-sf), a video-based measure validated cross-culturally in the studied populations, was used to assess mobility limitations. Based on theoretical models, covariates were included in the analysis, both at the neighborhood level (SES, social capital, and built environment) and the individual level (age, gender, education, income, chronic illnesses, depression, cognitive function, BMI, and social participation). Multilevel modeling was used in order to account for neighborhood clustering. Gender specific analyses were carried out. SAS and M-plus were used in this study. Results: PoS was validated across all sites. It loaded in a single factor, after excluding two items, with a Cronbach α value of approximately 0.86. Mobility limitations were present in 22.08% of the sample, 16.32% among men and 27.41% among women. Neighborhood perception of safety was significantly associated with mobility limitations when controlling for all covariates, with an OR of 0.84 (CI 95%: 0.73-0.96), indicating lower odds of having mobility limitations as neighborhood perception of safety improves. Gender did not affect this relationship despite women being more likely to have mobility limitations and live in neighborhoods with poor perception of safety. Conclusion: Neighborhood perception of safety affected the prevalence of mobility limitations in older adults in the studied population.

NEIGHBORHOOD PERCEPTION OF SAFETY AND THE MOBILITY GAP BETWEEN MEN AND WOMEN IN OLD AGE

Thesis (Master, Community Health & Epidemiology) -- Queen's University, 2016-10-02 21:02:07.735

Determinants of China’s regional innovation capacity

This paper investigates the determinants of China’s regional innovation capacity (RIC) and variations in these determinants between different types of regions. Based on the framework of national innovation capacity (NIC) and research on innovation system, this paper develops a framework of RIC in the Chinese context. Using panel data from 1991 to 2009, clustering analysis is first employed to classify regions according to their innovation development path. Panel data regressions with fixed effect model are conducted to explore the determinants of RIC and how these vary across the different regional clusters. We find that the 30 regions can be clustered into three groups, and there are considerable differences in the drivers of RIC between these different regional groups.

Determinants of driver vs. second row occupant posture modelling

Digital human modeling (DHM), as a convenient and cost-effective tool, is increasingly incorporated into product and workplace design. In product design, it is predominantly used for the development of driver-vehicle systems. Most digital human modeling software tools, such as JACK, RAMSIS and DELMIA HUMANBUILDER provide functions to predict posture and positions for drivers with selected anthropometry according to SAE (Society of Automotive Engineers) Recommended Practices and other ergonomics guidelines. However, few studies have presented 2nd row passenger postural information, and digital human modeling of these passenger postures cannot be performed directly using the existing driver posture prediction functions. In this paper, the significant studies related to occupant posture and modeling were reviewed and a framework of determinants of driver vs. 2nd row occupant posture modeling was extracted. The determinants which are regarded as input factors for posture modeling include target population anthropometry, vehicle package geometry and seat design variables as well as task definitions. The differences between determinants of driver and 2nd row occupant posture models are significant, as driver posture modeling is primarily based on the position of the foot on the accelerator pedal (accelerator actuation point AAP, accelerator heel point AHP) and the hands on the steering wheel (steering wheel centre point A-Point). The objectives of this paper are aimed to investigate those differences between driver and passenger posture, and to supplement the existing parametric model for occupant posture prediction. With the guide of the framework, the associated input parameters of occupant digital human models of both driver and second row occupant will be identified. Beyond the existing occupant posture models, for example a driver posture model could be modified to predict second row occupant posture, by adjusting the associated input parameters introduced in this paper. This study combines results from a literature review and the theoretical modeling stage of a second row passenger posture prediction model project.

Functional interaction of diphenols with polyphenol oxidase - Molecular determinants of substrate/inhibitor specificity SO FEBS JOURNAL

Polyphenol oxidase (PPO) catalyzes the oxidation of o-diphenols to their respective quinones. The quinones autopolymerize to form dark pigments, an undesired effect. PPO is therefore the target for the development of antibrowning and antimelanization agents. A series of phenolic compounds experimentally evaluated for their binding affinity and inhibition constants were computationally docked to the active site of catechol oxidase. Docking studies suggested two distinct modes of binding, dividing the docked ligands into two groups. Remarkably, the first group corresponds to ligands determined to be substrates and the second group corresponds to reversible inhibitors. Analyses of the complexes provide structural explanations for correlating subtle changes in the position and nature of the substitutions on o-diphenols to their functional properties as substrates and inhibitors. Higher reaction rates and binding are reckoned by additional interactions of the substrates with key residues that line the hydrophobic cavity. The docking results suggest that inhibition of oxidation stems from an interaction between the aromatic carboxylic acid group and the apical His 109 of the four coordinates of the trigonal pyramidal coordination polyhedron of CuA. The spatial orientation of the hydroxyl in relation to the carboxylic group either allows a perfect fit in the substrate cavity, leading to inhibition, or because of a steric clash flips the molecule vertically, facilitating oxidation. This is the first study to explain, at the molecular level, the determinants Of substrate and inhibitor specificity of a catechol oxidase, thereby providing a platform for the design of selective inhibitors useful to both the food and pharmaceutical industries.

Antigenic determinants of human serum retinol binding protein as probed with monoclonal antibodies

Monoclonal antibodies raised against human serum retinol-binding protein (hRBP) were used as probes for the study of the antigenic determinants of hRBP and those shared with the same protein from other species. The antibodies could be classified into four distinct groups and react with the homologous proteins from the rat as well as the rabbit sera. Three of these antibodies recognize sequential or continuous epitopes while the remaining antibody is directed against a discontinuous or conformational epitope. By chemical cleavage with cyanogen bromide, the domains recognized by the monoclonal antibodies could be delineated. By solid-phase synthetic approach, the core sequences recognized by two of these monoclonal antibodies were identified to amino acid sequences 45–51 and 128–131 of the primary amino acid sequence of hRBP.

A study of the Hobson and Rogers volatility model

We firstly examine the model of Hobson and Rogers for the volatility of a financial asset such as a stock or share. The main feature of this model is the specification of volatility in terms of past price returns. The volatility process and the underlying price process share the same source of randomness and so the model is said to be complete. Complete models are advantageous as they allow a unique, preference independent price for options on the underlying price process. One of the main objectives of the model is to reproduce the `smiles' and `skews' seen in the market implied volatilities and this model produces the desired effect. In the first main piece of work we numerically calibrate the model of Hobson and Rogers for comparison with existing literature. We also develop parameter estimation methods based on the calibration of a GARCH model. We examine alternative specifications of the volatility and show an improvement of model fit to market data based on these specifications. We also show how to process market data in order to take account of inter-day movements in the volatility surface. In the second piece of work, we extend the Hobson and Rogers model in a way that better reflects market structure. We extend the model to take into account both first and second order effects. We derive and numerically solve the pde which describes the price of options under this extended model. We show that this extension allows for a better fit to the market data. Finally, we analyse the parameters of this extended model in order to understand intuitively the role of these parameters in the volatility surface.

Constraining the age of Lateglacial and early Holocene pollen zones and tephra horizons in southern Sweden with Bayesian probability methods

The sediment sequence from Hasseldala port in southeastern Sweden provides a unique Lateglacial/early Holocene record that contains five different tephra layers. Three of these have been geochemically identified as the Borrobol Tephra, the Hasseldalen Tephra and the 10-ka Askja Tephra. Twenty-eight high-resolution C-14 measurements have been obtained and three different age models based on Bayesian statistics are employed to provide age estimates for the five different tephra layers. The chrono- and pollen stratigraphic framework supports the stratigraphic position of the Borrobol Tephra as found in Sweden at the very end of the Older Dryas pollen zone and provides the first age estimates for the Askja and Hasseldalen tephras. Our results, however, highlight the limitations that arise in attempting to establish a robust, chronologically independent lacustrine sequence that can be correlated in great detail to ice core or marine records. Radiocarbon samples are prone to error and sedimentation rates in lake basins may vary considerably due to a number of factors. Any type of valid and 'realistic' age model, therefore, has to take these limitations into account and needs to include this information in its prior assumptions. As a result, the age ranges for the specific horizons at Hasseldala port are large and calendar year estimates differ according to the assumptions of the age-model. Not only do these results provide a cautionary note for overdependence on one age-model for the derivation of age estimates for specific horizons, but they also demonstrate that precise correlations to other palaeoarchives to detect leads or lags is problematic. Given the uncertainties associated with establishing age-depth models for sedimentary sequences spanning the Lateglacial period, however, this exercise employing Bayesian probability methods represents the best possible approach and provides the most statistically significant age estimates for the pollen zone boundaries and tephra horizons. Copyright (C) 2006 John Wiley & Sons, Ltd.

The competition–performance relation: a meta-analytic review and test of the opposing processes model of competition and performance

What is the relation between competition and performance? The present research addresses this important multidisciplinary question by conducting a meta-analysis of existing empirical work and by proposing a new conceptual model—the opposing processes model of competition and performance. This model was tested by conducting an additional meta-analysis and 3 new empirical studies. The first meta-analysis revealed that there is no noteworthy relation between competition and performance. The second meta-analysis showed, in accord with the opposing processes model, that the absence of a direct effect is the result of inconsistent mediation via achievement goals: Competition prompts performance-approach goals which, in turn, facilitate performance; and competition also prompts performance-avoidance goals which, in turn, undermine performance. These same direct and mediational findings were also observed in the 3 new empirical studies (using 3 different conceptualizations of competition and attending to numerous control variables). Our findings provide both interpretational clarity regarding past research and conceptual guidance regarding future research on the competition–performance relation.

SECC: simultaneous extraction of context and community from pervasive signals

Understanding user contexts and group structures plays a central role in pervasive computing. These contexts and community structures are complex to mine from data collected in the wild due to the unprecedented growth of data, noise, uncertainties and complexities. Typical existing approaches would first extract the latent patterns to explain the human dynamics or behaviors and then use them as the way to consistently formulate numerical representations for community detection, often via a clustering method. While being able to capture high-order and complex representations, these two steps are performed separately. More importantly, they face a fundamental difficulty in determining the correct number of latent patterns and communities. This paper presents an approach that seamlessly addresses these challenges to simultaneously discover latent patterns and communities in a unified Bayesian nonparametric framework. Our Simultaneous Extraction of Context and Community (SECC) model roots in the nested Dirichlet process theory which allows nested structure to be built to explain data at multiple levels. We demonstrate our framework on three public datasets where the advantages of the proposed approach are validated.

Dinamicity and unpredictability of emerging markets: an implementation of Goetzamnn and Jorion (1999)

This research is to be considered as an implementation of Goetzmann and Jorion (1999). In order to provide a more realistic scenario, we have implemented a Garch (1,1) approach for the residuals of returns and a multifactor model thus to better replicate the systematic risk of a market. The new simulations reveal some new aspects of emerging markets’ expected returns: the unpredictability of the emerging markets’ returns with the global factor does not depend on the year of emergence and that the unsystematic risk explains the returns of emerging markets for a much larger period of time. The results also reveal the high impact of Exchange rate, Commodities index and of the Global factor in emerging markets’ expected return.

Determination of labile inorganic and organic species of Al and Cu in river waters using the diffusive gradients in thin films technique

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A simultaneous extraction of context and community from pervasive signals using nested dirichlet process

Understanding user contexts and group structures plays a central role in pervasive computing. These contexts and community structures are complex to mine from data collected in the wild due to the unprecedented growth of data, noise, uncertainties and complexities. Typical existing approaches would first extract the latent patterns to explain human dynamics or behaviors and then use them as a way to consistently formulate numerical representations for community detection, often via a clustering method. While being able to capture high-order and complex representations, these two steps are performed separately. More importantly, they face a fundamental difficulty in determining the correct number of latent patterns and communities. This paper presents an approach that seamlessly addresses these challenges to simultaneously discover latent patterns and communities in a unified Bayesian nonparametric framework. Our Simultaneous Extraction of Context and Community (SECC) model roots in the nested Dirichlet process theory which allows a nested structure to be built to summarize data at multiple levels. We demonstrate our framework on five datasets where the advantages of the proposed approach are validated.