Motion estimation with object based regularisation

A dynamic programming based matching method for motion estimation, that optimises a Bayesian maximum likelihood function in a 3-D optimisation space, is presented. The Bayesian function consists of a matching cost and an object based 2-D regularisation cost. The method gives results more accurate than block-based matching since the motion boundaries are close to the actual object boundaries

Microsimulations in the Presence of Heterogeneity

This paper develops a method that improves researchers’ ability to account for behavioral responses to policy change in microsimulation models. Current microsimulation models are relatively simple, in part because of the technical difficulty of accounting for unobserved heterogeneity. This is all the more problematic because data constraints typically force researchers to limit their forecasting models to relatively few, mostly time-invariant explanatory covariates, so that much of the variation across individuals is unobserved. Furthermore, failure to account for unobservables often leads to biased estimates of structural parameters, which are critically important for measuring behavioral responses. This paper develops a theoretical approach to incorporate (univariate and multivariate) unobserved heterogeneity into microsimulation models; illustrates computer algorithms to efficiently implement heterogeneity in continuous and limited dependent models; and evaluates the importance of unobserved heterogeneity by conducting Monte Carlo simulations.

A high resolution spatiotemporal model for in-vehicle black carbon exposure : quantifying the in-vehicle exposure reduction due to the Euro 5 particulate matter standard legislation

Several studies have shown that a significant amount of daily air pollution exposure is inhaled during trips. In this study, car drivers assessed their own black carbon exposure under real-life conditions (223 h of data from 2013). The spatiotemporal exposure of the car drivers is modeled using a data science approach, referred to as microscopic land-use regression (mu LUR). In-vehicle exposure is highly dynamical and is strongly related to the local traffic dynamics. An extensive set of potential covariates was used to model the in-vehicle black carbon exposure in a temporal resolution of 10 s. Traffic was retrieved directly from traffic databases and indirectly by attributing the trips through a noise map as an alternative traffic source. Modeling by generalized additive models (GAM) shows non-linear effects for meteorology and diurnal traffic patterns. A fitted diurnal pattern explains indirectly the complex diurnal variability of the exposure due to the non-linear interaction between traffic density and distance to the preceding vehicles. Comparing the strength of direct traffic attribution and indirect noise map-based traffic attribution reveals the potential of noise maps as a proxy for traffic-related air pollution exposure. An external validation, based on a dataset gathered in 2010-2011, quantifies the exposure reduction inside the vehicles at 33% (mean) and 50% (median). The EU PM Euro 5 PM emission standard (in force since 2009) explains the largest part of the discrepancy between the measurement campaign in 2013 and the validation dataset. The mu LUR methodology provides a high resolution, route-sensitive, seasonal and meteorology-sensitive personal exposure estimate for epidemiologists and policy makers

System approach to disparity estimation

A system approach to disparity estimation using dynamic programming is presented. The four step system can calculate a dense correspondence map between a stereo pair with parallel or nonparallel camera geometry. Results are presented with CCIR 601 format stereo images

Stem Cells Intended for Cosmetic Use Only: Regulation in Belgium, Europe and the United States

The central question in this paper is whether it is wise to assume that cosmetics are not hazardous, especially in the light of the stem cell hype. Some cosmetics contain stem cell extracts or claim to influence the stem cells in the skin. This paper examines the issue of these “stem cell creams” in three jurisdictions: Belgium, Europe and the United States. The paper approaches the issues raised by the advent of such products in the following manner: first, the classification problem is discussed. Stem cell creams sometimes fall in a grey area between cosmetics and drugs. When the categorization is only based on claims made of the products, manufacturers can easily evade their responsibilities by manipulating the claims. The applicable regulations are then analyzed. Although the requirements for drugs are similar in the three jurisdictions, this is not the case with respect to cosmetics. Cosmetics are clearly regulated more strictly in Europe. Finally, a clear overview of the loopholes in the current regulations is offered and some recommendations for change are proposed. The conclusion of the paper is that the discussed stem cell creams might be hazardous and therefore, should be rigorously regulated. Moreover, something as superficial as claims by manufacturer should not be determinative so as to alter the classification of a product. The European model could thus arguably be an inspiration for FDA to base future reforms upon

The Size and Composition of Wealth Holdings in the United States, Italy, and the Netherlands

This paper analyzes retirement saving and portfolio choice in the United States, Italy, and the Netherlands. While these countries enjoy roughly the same standard of living, they vary widely in their institutional organization of retirement income provisions. Building on extensions of the life cycle model, we derive hypotheses on the implications of institutional differences for wealth accumulation and portfolio composition. Examples of implications are that the ratio of net worth and gross wealth should be highest in Italy, that Dutch households should hold the lowest wealth levels at retirement and that the ownership of risky assets should be highest in the U.S. We investigate these and other hypotheses at both the macro and micro level and find that the data are generally consistent with the hypotheses.

Evaluation of four different strategies to characterize plasma membrane proteins from banana roots

Plasma membrane proteins constitute a very important class of proteins. They are involved in the transmission of external signals to the interior of the cell and selective transport of water, nutrients and ions across the plasma membrane. However, the study of plasma membrane proteins is challenging because of their poor solubility in aqueous media and low relative abundance. In this work, we evaluated four different strategies for the characterization of plasma membrane proteins from banana roots: (i) the aqueous-polymer two-phase system technique (ATPS) coupled to gelelectrophoresis (gel-based), and (ii) ATPS coupled to LC-MS/MS (gel free), (iii) a microsomal fraction and (iv) a full proteome, both coupled to LC-MS/ MS. Our results show that the gel-based strategy is useful for protein visualization but has major limitations in terms of time reproducibility and efficiency. From the gel-free strategies, the microsomal-based strategy allowed the highest number of plasma membrane proteins to be identified, followed by the full proteome strategy and by the ATPS based strategy. The high yield of plasma membrane proteins provided by the microsomal fraction can be explained by the enrichment of membrane proteins in this fraction and the high throughput of the gel-free approach combined with the usage of a fast high-resolution mass spectrometer for the identification of proteins