Returns to scale in food preparation and the Deaton–Paxson puzzle

We consider returns to scale in food preparation as a potential resolution of a puzzle raised by Deaton and Paxson (Journal of Political Economy, 106(5), 897–930, 1998). We clarify the conditions under which returns to scale in food preparation can resolve the puzzle. The key requirement is that foods are heterogeneous in time costs. We then show that detailed food expenditure and time use data are consistent with larger households shifting to more time intensive foods

Treatment of Linear and Nonlinear Dielectric Property of Molecular Monolayer and Submonolayer with Microscopic Dipole Lattice Model: I. Second Harmonic Generation and Sum-Frequency Generation

In the currently accepted models of the nonlinear optics, the nonlinear radiation was treated as the result of an infinitesimally thin polarization sheet layer, and a three layer model was generally employed. The direct consequence of this approach is that an apriori dielectric constant, which still does not have a clear definition, has to be assigned to this polarization layer. Because the Second Harmonic Generation (SHG) and the Sum-Frequency Generation vibrational Spectroscopy (SFG-VS) have been proven as the sensitive probes for interfaces with the submonolayer coverage, the treatment based on the more realistic discrete induced dipole model needs to be developed. Here we show that following the molecular optics theory approach the SHG, as well as the SFG-VS, radiation from the monolayer or submonolayer at an interface can be rigorously treated as the radiation from an induced dipole lattice at the interface. In this approach, the introduction of the polarization sheet is no longer necessary. Therefore, the ambiguity of the unaccounted dielectric constant of the polarization layer is no longer an issue. Moreover, the anisotropic two dimensional microscopic local field factors can be explicitly expressed with the linear polarizability tensors of the interfacial molecules. Based on the planewise dipole sum rule in the molecular monolayer, crucial experimental tests of this microscopic treatment with SHG and SFG-VS are discussed. Many puzzles in the literature of surface SHG and SFG spectroscopy studies can also be understood or resolved in this framework. This new treatment may provide a solid basis for the quantitative analysis in the surface SHG and SFG studies.Comment: 23 pages, 3 figure

The association of cold weather and all-cause and cause-specific mortality in the island of Ireland between 1984 and 2007

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.This article has been made available through the Brunel Open Access Publishing Fund.Background This study aimed to assess the relationship between cold temperature and daily mortality in the Republic of Ireland (ROI) and Northern Ireland (NI), and to explore any differences in the population responses between the two jurisdictions. Methods A time-stratified case-crossover approach was used to examine this relationship in two adult national populations, between 1984 and 2007. Daily mortality risk was examined in association with exposure to daily maximum temperatures on the same day and up to 6 weeks preceding death, during the winter (December-February) and cold period (October-March), using distributed lag models. Model stratification by age and gender assessed for modification of the cold weather-mortality relationship. Results In the ROI, the impact of cold weather in winter persisted up to 35 days, with a cumulative mortality increase for all-causes of 6.4% (95%CI=4.8%-7.9%) in relation to every 1oC drop in daily maximum temperature, similar increases for cardiovascular disease (CVD) and stroke, and twice as much for respiratory causes. In NI, these associations were less pronounced for CVD causes, and overall extended up to 28 days. Effects of cold weather on mortality increased with age in both jurisdictions, and some suggestive gender differences were observed. Conclusions The study findings indicated strong cold weather-mortality associations in the island of Ireland; these effects were less persistent, and for CVD mortality, smaller in NI than in the ROI. Together with suggestive differences in associations by age and gender between the two Irish jurisdictions, the findings suggest potential contribution of underlying societal differences, and require further exploration. The evidence provided here will hope to contribute to the current efforts to modify fuel policy and reduce winter mortality in Ireland

IEEE Access Special Section Editorial: Advanced Signal Processing Methods in Medical Imaging

Medical Imaging is a technique to create visual representations of the interior of the body, with the aim of making accurate diagnoses and optimized treatments. Many medical imaging techniques are widely used to produce images, such as computer tomography (CT), ultrasound (US), positron emission tomography (PET), single photon emission computed tomography (SPECT), and magnetic resonance imaging (MRI)/functional MRI (fMRI)

Generalized alignment-based trace clustering of process behavior

Process mining techniques use event logs containing real process executions in order to mine, align and extend process models. The partition of an event log into trace variants facilitates the understanding and analysis of traces, so it is a common pre-processing in process mining environments. Trace clustering automates this partition; traditionally it has been applied without taking into consideration the availability of a process model. In this paper we extend our previous work on process model based trace clustering, by allowing cluster centroids to have a complex structure, that can range from a partial order, down to a subnet of the initial process model. This way, the new clustering framework presented in this paper is able to cluster together traces that are distant only due to concurrency or loop constructs in process models. We show the complexity analysis of the different instantiations of the trace clustering framework, and have implemented it in a prototype tool that has been tested on different datasets.Peer ReviewedPostprint (author's final draft

Experimental observations that simulated active-layer deepening drives deeper rock fracture

The impact of changes in active-layer thickness on the depth of pervasive macrofracture (brecciation) in frost-susceptible bedrock is unclear but important to understanding its physical properties and geohazard potential. Here we report results from a laboratory experiment to test the hypothesis that active-layer deepening drives an increase in the depth of brecciation. The experiment simulated active-layer deepening in 300 mm cubic blocks of limestone (chalk) and sandstone. Temperature, surface heave and strain at depth were measured during 16 freeze–thaw cycles. Macrocracks photographed at intervals were digitally analysed to visualise crack growth and to quantify crack inclination and length. In chalk, an upper horizon of macrocracks developed first at about 100 mm depth in a shallow thaw active layer during cycles 1–8, followed by a lower horizon at about 175‒225 mm depth in a deeper thaw active layer during cycles 9–16. The longest cracks (>35 mm) were most common at inclinations of 0–30° from horizontal, and numerous cracks <5 to 15 mm long developed at inclinations of 40–50°, with some longer vertical to subvertical cracks linking the two brecciated horizons. Overall, the observations support the hypothesis that a thickening active layer drives deeper rock fracture by ice segregation

Robust Detection of Hierarchical Communities from Escherichia coli Gene Expression Data

Determining the functional structure of biological networks is a central goal of systems biology. One approach is to analyze gene expression data to infer a network of gene interactions on the basis of their correlated responses to environmental and genetic perturbations. The inferred network can then be analyzed to identify functional communities. However, commonly used algorithms can yield unreliable results due to experimental noise, algorithmic stochasticity, and the influence of arbitrarily chosen parameter values. Furthermore, the results obtained typically provide only a simplistic view of the network partitioned into disjoint communities and provide no information of the relationship between communities. Here, we present methods to robustly detect coregulated and functionally enriched gene communities and demonstrate their application and validity for Escherichia coli gene expression data. Applying a recently developed community detection algorithm to the network of interactions identified with the context likelihood of relatedness (CLR) method, we show that a hierarchy of network communities can be identified. These communities significantly enrich for gene ontology (GO) terms, consistent with them representing biologically meaningful groups. Further, analysis of the most significantly enriched communities identified several candidate new regulatory interactions. The robustness of our methods is demonstrated by showing that a core set of functional communities is reliably found when artificial noise, modeling experimental noise, is added to the data. We find that noise mainly acts conservatively, increasing the relatedness required for a network link to be reliably assigned and decreasing the size of the core communities, rather than causing association of genes into new communities.Comment: Due to appear in PLoS Computational Biology. Supplementary Figure S1 was not uploaded but is available by contacting the author. 27 pages, 5 figures, 15 supplementary file

Physical activity to improve cognition in older adults: can physical activity programs enriched with cognitive challenges enhance the effects? A systematic review and meta-analysis

: EPHPP quality rating scores (DOCX 38 kb

Options for early breast cancer follow-up in primary and secondary care : a systematic review

Background Both incidence of breast cancer and survival have increased in recent years and there is a need to review follow up strategies. This study aims to assess the evidence for benefits of follow-up in different settings for women who have had treatment for early breast cancer. Method A systematic review to identify key criteria for follow up and then address research questions. Key criteria were: 1) Risk of second breast cancer over time - incidence compared to general population. 2) Incidence and method of detection of local recurrence and second ipsi and contra-lateral breast cancer. 3) Level 1–4 evidence of the benefits of hospital or alternative setting follow-up for survival and well-being. Data sources to identify criteria were MEDLINE, EMBASE, AMED, CINAHL, PSYCHINFO, ZETOC, Health Management Information Consortium, Science Direct. For the systematic review to address research questions searches were performed using MEDLINE (2011). Studies included were population studies using cancer registry data for incidence of new cancers, cohort studies with long term follow up for recurrence and detection of new primaries and RCTs not restricted to special populations for trials of alternative follow up and lifestyle interventions. Results Women who have had breast cancer have an increased risk of a second primary breast cancer for at least 20 years compared to the general population. Mammographically detected local recurrences or those detected by women themselves gave better survival than those detected by clinical examination. Follow up in alternative settings to the specialist clinic is acceptable to women but trials are underpowered for survival. Conclusions Long term support, surveillance mammography and fast access to medical treatment at point of need may be better than hospital based surveillance limited to five years but further large, randomised controlled trials are needed

Detection of regulator genes and eQTLs in gene networks

Genetic differences between individuals associated to quantitative phenotypic traits, including disease states, are usually found in non-coding genomic regions. These genetic variants are often also associated to differences in expression levels of nearby genes (they are "expression quantitative trait loci" or eQTLs for short) and presumably play a gene regulatory role, affecting the status of molecular networks of interacting genes, proteins and metabolites. Computational systems biology approaches to reconstruct causal gene networks from large-scale omics data have therefore become essential to understand the structure of networks controlled by eQTLs together with other regulatory genes, and to generate detailed hypotheses about the molecular mechanisms that lead from genotype to phenotype. Here we review the main analytical methods and softwares to identify eQTLs and their associated genes, to reconstruct co-expression networks and modules, to reconstruct causal Bayesian gene and module networks, and to validate predicted networks in silico.Comment: minor revision with typos corrected; review article; 24 pages, 2 figure