AGRICULTURAL LAND CONVERSION IN THE TWIN CITIES: PART II, THE NATIONAL RESOURCES INVENTORY

We divided the thirteen-county Twin Cities Metropolitan Statistical Area into a core and a fringe of seven and six counties, respectively. The National Resources Inventory estimates that 170 thousand acres of the Core were converted from agriculture to other uses between 1982 and 1987, while only about 46 thousand acres of the Fringe were so converted. The conversion rate was much greater in the Core than on the Fringe according to the NRIbut not according to the Census of Agriculture. The number of acres of agricultural land converted for each new resident ranged from 0.15 in Sherburne County to 2.49 in Pierce County. Viewed another way, the increase in urban land to house new residents ranged from 0.28 in Ramsey County to 1.23 acres per person in Isanti County.Land Economics/Use,

Assessing the quality of home detection from mobile phone data for official statistics

Mobile phone data are an interesting new data source for official statistics. However, multiple problems and uncertainties need to be solved before these data can inform, support or even become an integral part of statistical production processes. In this paper, we focus on arguably the most important problem hindering the application of mobile phone data in official statistics: detecting home locations. We argue that current efforts to detect home locations suffer from a blind deployment of criteria to define a place of residence and from limited validation possibilities. We support our argument by analysing the performance of five home detection algorithms (HDAs) that have been applied to a large, French, Call Detailed Record (CDR) dataset (~18 million users, 5 months). Our results show that criteria choice in HDAs influences the detection of home locations for up to about 40% of users, that HDAs perform poorly when compared with a validation dataset (the 35{\deg}-gap), and that their performance is sensitive to the time period and the duration of observation. Based on our findings and experiences, we offer several recommendations for official statistics. If adopted, our recommendations would help in ensuring a more reliable use of mobile phone data vis-\`a-vis official statistics

Raman-induced Kerr-effect dual-comb spectroscopy

We report on the first demonstration of nonlinear dual-frequency-comb spectroscopy. In multi-heterodyne femtosecond Raman-induced Kerr-effect spectroscopy, the Raman gain resulting from the coherent excitation of molecular vibrations by a spectrally-narrow pump is imprinted onto the femtosecond laser frequency comb probe spectrum. The birefringence signal induced by the nonlinear interaction of these beams and the sample is heterodyned against a frequency comb local oscillator with a repetition frequency slightly different from that of the comb probe. Such time-domain interference provides multiplex access to the phase and amplitude Raman spectra over a broad spectral bandwidth within a short measurement time. Experimental demonstration, at a spectral resolution of 200 GHz, a measurement time of 293 {\mu}s and a sensitivity of 10^-6, is given on liquid samples exhibiting a C-H stretch Raman shift.Comment: 7 pages, 4 figure

Comparing Regional Patterns of Individual Movement Using Corrected Mobility Entropy

In this paper, we propose a correction of the Mobility Entropy indicator (ME) used to describe the diversity of individual movement patterns as can be captured by data from mobile phones. We argue that a correction is necessary because standard calculations of ME show a structural dependency on the geographical density of observation points, rendering results biased and comparisons between regions incorrect. As a solution, we propose the Corrected Mobility Entropy (CME). We apply our solution to a French mobile phone dataset with ∼18.5 million users. Results show CME to be less correlated to cell-tower density (r = –0.17 instead of –0.59 for ME). As a spatial pattern of mobility diversity, we find CME values to be higher in suburban regions compared to their related urban centers, while both decrease considerably with lowering urban center sizes. Based on regression models, we find mobility diversity to relate to factors like income and employment. Additionally, using CME reveals the role of car use in relation to land use, which was not recognized when using ME values. Our solution enables a better description of individual mobility at a large scale, which has applications in official statistics, urban planning and policy, and mobility research

A study of wrist-worn activity measurement as a potential real-world biomarker for late-life depression.

BACKGROUND: Late-life depression (LLD) is associated with a decline in physical activity. Typically this is assessed by self-report questionnaires and, more recently, with actigraphy. We sought to explore the utility of a bespoke activity monitor to characterize activity profiles in LLD more precisely. METHOD: The activity monitor was worn for 7 days by 29 adults with LLD and 30 healthy controls. Subjects underwent neuropsychological assessment and quality of life (QoL) (36-item Short-Form Health Survey) and activities of daily living (ADL) scales (Instrumental Activities of Daily Living Scale) were administered. RESULTS: Physical activity was significantly reduced in LLD compared with controls (t = 3.63, p < 0.001), primarily in the morning. LLD subjects showed slower fine motor movements (t = 3.49, p < 0.001). In LLD patients, activity reductions were related to reduced ADL (r = 0.61, p < 0.001), lower QoL (r = 0.65, p < 0.001), associative learning (r = 0.40, p = 0.036), and higher Montgomery-Åsberg Depression Rating Scale score (r = -0.37, p < 0.05). CONCLUSIONS: Patients with LLD had a significant reduction in general physical activity compared with healthy controls. Assessment of specific activity parameters further revealed the correlates of impairments associated with LLD. Our study suggests that novel wearable technology has the potential to provide an objective way of monitoring real-world function.This study was funded by an award from the UK Medical Research Council (G1001828/1)

PD disease state assessment in naturalistic environments using deep learning

Management of Parkinson's Disease (PD) could be improved significantly if reliable, objective information about fluctuations in disease severity can be obtained in ecologically valid surroundings such as the private home. Although automatic assessment in PD has been studied extensively, so far no approach has been devised that is useful for clinical practice. Analysis approaches common for the field lack the capability of exploiting data from realistic environments, which represents a major barrier towards practical assessment systems. The very unreliable and infrequent labelling of ambiguous, low resolution movement data collected in such environments represents a very challenging analysis setting, where advances would have significant societal impact in our ageing population. In this work we propose an assessment system that abides practical usability constraints and applies deep learning to differentiate disease state in data collected in naturalistic settings. Based on a large data-set collected from 34 people with PD we illustrate that deep learning outperforms other approaches in generalisation performance, despite the unreliable labelling characteristic for this problem setting, and how such systems could improve current clinical practice

Fluctuation solution theory of pure fluids

Citation: Ploetz, E. A., Pallewela, G. N., & Smith, P. E. (2017). Fluctuation solution theory of pure fluids. Journal of Chemical Physics, 146(9), 13. doi:10.1063/1.4977040Fluctuation Solution Theory (FST) provides an alternative view of fluid thermodynamics in terms of pair fluctuations in the particle number and excess energy observed for an equivalent open system. Here we extend the FST approach to provide a series of triplet and quadruplet particle and excess energy fluctuations that can also be used to help understand the behavior of fluids. The fluctuations for the gas, liquid, and supercritical regions of three fluids (H2O, CO2, and SF6) are then determined from accurate equations of state. Many of the fluctuating quantities change sign on moving from the gas to liquid phase and, therefore, we argue that the fluctuations can be used to characterize gas and liquid behavior. Further analysis provides an approach to isolate contributions to the excess energy fluctuations arising from just the intermolecular interactions and also indicates that the triplet and quadruplet particle fluctuations are related to the pair particle fluctuations by a simple power law for large regions of the phase diagram away from the critical point. Published by AIP Publishing

Experimental triplet and quadruplet fluctuation densities and spatial distribution function integrals for pure liquids

Citation: Ploetz, E. A., Karunaweera, S., & Smith, P. E. (2015). Experimental triplet and quadruplet fluctuation densities and spatial distribution function integrals for pure liquids. Journal of Chemical Physics, 142(4), 14. doi:10.1063/1.4905562Fluctuation solution theory has provided an alternative view of many liquid mixture properties in terms of particle number fluctuations. The particle number fluctuations can also be related to integrals of the corresponding two body distribution functions between molecular pairs in order to provide a more physical picture of solution behavior and molecule affinities. Here, we extend this type of approach to provide expressions for higher order triplet and quadruplet fluctuations, and thereby integrals over the corresponding distribution functions, all of which can be obtained from available experimental thermodynamic data. The fluctuations and integrals are then determined using the International Association for the Properties of Water and Steam Formulation 1995 (IAPWS-95) equation of state for the liquid phase of pure water. The results indicate small, but significant, deviations from a Gaussian distribution for the molecules in this system. The pressure and temperature dependence of the fluctuations and integrals, as well as the limiting behavior as one approaches both the triple point and the critical point, are also examined. (C) 2015 AIP Publishing LLC

Climate change impacts on banana yields around the world

This is the author accepted manuscript. The final version is available from Nature Research via the DOI in this r4ecordData availability: All data used are publicly available and open access. All banana production data sources are listed in Supplementary Table 1. All climatic and topographic data sources are listed in the Methods.Nutritional diversity is a key element of food security1,2,3. However, research on the effects of climate change on food security has, thus far, focused on the main food grains4,5,6,7,8, while the responses of other crops, particularly those that play an important role in the developing world, are poorly understood. Bananas are a staple food and a major export commodity for many tropical nations9. Here, we show that for 27 countries—accounting for 86% of global dessert banana production—a changing climate since 1961 has increased annual yields by an average of 1.37 t ha−1. Past gains have been largely ubiquitous across the countries assessed and African producers will continue to see yield increases in the future. However, global yield gains could be dampened or disappear, reducing to 0.59 t ha−1 and 0.19 t ha−1 by 2050 under the climate scenarios for Representative Concentration Pathways 4.5 and 8.5, respectively, driven by declining yields in the largest producers and exporters. By quantifying climate-driven and technology-driven influences on yield, we also identify countries at risk from climate change and those capable of mitigating its effects or capitalizing on its benefits.Biotechnology and Biological Sciences Research Council (BBSRC)European Union Horizon 202