On model selection criteria for climate change impact studies

Climate change impact studies inform policymakers on the estimated damages of future climate change on economic, health and other outcomes. In most studies, an annual outcome variable is observed, e.g. annual mortality rate, along with higher-frequency regressors, e.g. daily temperature and precipitation. Practitioners use summaries of the higher-frequency regressors in fixed effects panel models. The choice over summary statistics amounts to model selection. Some practitioners use Monte Carlo cross-validation (MCCV) to justify a particular specification. However, conventional implementation of MCCV with fixed testing-to-full sample ratios tends to select over-fit models. This paper presents conditions under which MCCV, and also information criteria, can deliver consistent model selection. Previous work has established that the Bayesian information criterion (BIC) can be inconsistent for non-nested selection. We illustrate that the BIC can also be inconsistent in our framework, when all candidate models are misspecified. Our results have practical implications for empirical conventions in climate change impact studies. Specifically, they highlight the importance of a priori information provided by the scientific literature to guide the models considered for selection. We emphasize caution in interpreting model selection results in settings where the scientific literature does not specify the relationship between the outcome and the weather variables.Comment: Additional simulation results available from authors by reques

Boundary interpolation for slice hyperholomorphic Schur functions

A boundary Nevanlinna-Pick interpolation problem is posed and solved in the quaternionic setting. Given nonnegative real numbers $\kappa_1, \ldots, \kappa_N$, quaternions $p_1, \ldots, p_N$ all of modulus $1$, so that the $2$-spheres determined by each point do not intersect and $p_u \neq 1$ for $u = 1,\ldots, N$, and quaternions $s_1, \ldots, s_N$, we wish to find a slice hyperholomorphic Schur function $s$ so that $$\lim_{\substack{r\rightarrow 1\\ r\in(0,1)}} s(r p_u) = s_u\quad {\rm for} \quad u=1,\ldots, N,$$ and $$\lim_{\substack{r\rightarrow 1\\ r\in(0,1)}}\frac{1-s(rp_u)\overline{s_u}}{1-r}\le\kappa_u,\quad {\rm for} \quad u=1,\ldots, N.$$ Our arguments relies on the theory of slice hyperholomorphic functions and reproducing kernel Hilbert spaces

Thermal performance of High-Efficiency Vortex (HEV) variants: reversed arrays configuration

Convective heat transfer in the Reversed Arrays configuration of the High-Efficiency Vortex (HEV) multifunctional heat exchanger is investigated. An experimental test section constituted of a tube equipped with inclined trapezoidal vortex generators with a constant-flux heating system is designed and constructed. In this configuration, the tab inclination is opposite to the flow direction. Interactions between the tabs and the flow generate coherent structures in the form of longitudinal counter-rotating streamwise vortices enhancing radial particle dispersion, mixing, and ultimately heat transport. The original configuration in which the tabs are inclined in the flow direction is also examined. Recent in-house hydrodynamic and thermal studies have been conducted showing the interest of these configurations in mixing and heat transfer applications. The experimental data are in good agreement with the numerical results. Local Nusselt numbers show an increasing tendency in the longitudinal direction with remarkable cross-sectional variations. Global analysis of convective heat transfer reveals the superiority of the Reversed Arrays. Energy expenditures are assessed through total pressure drop measurements. A comparative analysis based on the thermal enhancement factor and Colburn factor shows that the HEV is energetically less costly than other heat exchangers with similar heat transfer capacity

Transport phenomena in chaotic flows: flux recombination HEX reactors

Rapid transport of heat and mass is required in many industrial processes. Mixing is a fundamental issue in chemical engineering applications and when exothermic reactions are involved, heat transfer capabilities of reactors and static mixers become an advantage and a necessity to ensure stable operating conditions and security standards. Enhancement of mixing and heat exchange is possible through turbulence, but vortical structures are often not feasible for highly viscous, non-Newtonian or shear sensitive fluids such as emulsions, pastes and slurries common in pharmaceutical, cosmetic and food industries. An alternative to improve transport within such materials is chaotic advection, where Lagrangian chaotic structures are induced by physical means in low-Reynolds laminar flows. Microfluidics is an increasingly active domain in which small dimensions and velocities render turbulent mixing extremely hard. Mixing by diffusion is one solution where topological mixing schemes exploiting the laminarity the flow to repeatedly fold the flow and exponentially increase the concentration gradients to obtain fast and efficient mixing by diffusion. This paper presents the first results of a study investigating laminar and turbulent mixing qualities of a Flux Recombination Hex reactor by using the chemical probe method. The geometry, exploiting a three-dimensional, steady flow configuration intended to mimic the baker’s map and enhance mixing by chaotic advection. First proposed by Chen & Meiners [1] for a microfluidic chip, it is here reproduced for investigation purposes using a stratified multiple plate manufacturing technique on a mini-scale where laminar and slightly turbulent regimes can be assessed

A network approach for managing and processing big cancer data in clouds

Translational cancer research requires integrative analysis of multiple levels of big cancer data to identify and treat cancer. In order to address the issues that data is decentralised, growing and continually being updated, and the content living or archiving on different information sources partially overlaps creating redundancies as well as contradictions and inconsistencies, we develop a data network model and technology for constructing and managing big cancer data. To support our data network approach for data process and analysis, we employ a semantic content network approach and adopt the CELAR cloud platform. The prototype implementation shows that the CELAR cloud can satisfy the on-demanding needs of various data resources for management and process of big cancer data

Kinematic mixing and heat transfer enhancement in chaotic split-and-recombine heat exchangers/reactors

Small system dimensions, low fluid velocity and high viscosity are all factors that hinder the production of turbulence. Enhancing mixing and heat transfer under these conditions, while keeping sufficient residence times and moderate pressure drops, constitutes a real challenge. Adapted to low-Reynolds flow regimes, Split-And-Recombine (SAR) static mixer and heat exchanger configurations are designed to exploit flow energy to produce chaotic advection and promote diffusion at the molecular level. The present work explores the hydrodynamic and thermal character of the SAR flow and compares, through CFD simulations, two such geometries namely SAR-1 and SAR-2, with two other reference configurations: a square three-dimensional continuous flow geometry (3D-Flow) and a plain square channel. Efficient convective heat transfer is achieved in deeply laminar creeping flow. Relative enhancements up to 1700% can be achieved compared to plain square channel flow, with a moderate increase in the pressure drop that does not exceed 17% for the SAR-2 configuration showing the better performance

A Dimension-Adaptive Multi-Index Monte Carlo Method Applied to a Model of a Heat Exchanger

We present an adaptive version of the Multi-Index Monte Carlo method, introduced by Haji-Ali, Nobile and Tempone (2016), for simulating PDEs with coefficients that are random fields. A classical technique for sampling from these random fields is the Karhunen-Lo\`eve expansion. Our adaptive algorithm is based on the adaptive algorithm used in sparse grid cubature as introduced by Gerstner and Griebel (2003), and automatically chooses the number of terms needed in this expansion, as well as the required spatial discretizations of the PDE model. We apply the method to a simplified model of a heat exchanger with random insulator material, where the stochastic characteristics are modeled as a lognormal random field, and we show consistent computational savings

Exhaustive and Efficient Constraint Propagation: A Semi-Supervised Learning Perspective and Its Applications

This paper presents a novel pairwise constraint propagation approach by decomposing the challenging constraint propagation problem into a set of independent semi-supervised learning subproblems which can be solved in quadratic time using label propagation based on k-nearest neighbor graphs. Considering that this time cost is proportional to the number of all possible pairwise constraints, our approach actually provides an efficient solution for exhaustively propagating pairwise constraints throughout the entire dataset. The resulting exhaustive set of propagated pairwise constraints are further used to adjust the similarity matrix for constrained spectral clustering. Other than the traditional constraint propagation on single-source data, our approach is also extended to more challenging constraint propagation on multi-source data where each pairwise constraint is defined over a pair of data points from different sources. This multi-source constraint propagation has an important application to cross-modal multimedia retrieval. Extensive results have shown the superior performance of our approach.Comment: The short version of this paper appears as oral paper in ECCV 201

Tip-Leakage Vortex Inception on a Ducted Rotor

The tip-leakage vortex occurring on a ducted rotor was examined using both three component Laser Doppler Velocimetry (LDV) and planar Particle Imaging Velocimetry (PIV). The vortex strength and core size were examined for different vortex cross sections downstream of the blade trailing edge. The variability of these quantities are observed with PIV and the average quantities are compared between LDV and PIV. Developed cavitation is also examined for the leakage vortex. The implication of vortex variability on cavitation inception is discussed