Actual and Reference Evaporative Losses and Surface Coefficients of a Maize Field during Nongrowing (Dormant) Periods

Effective water resources planning, allocation, management, and use in agroecosystems require accurate quantification of actual evapotranspiration (ETc) during growing and nongrowing (dormant) periods. Prediction of ETc for a variety of vegetation surfaces during the growing season has been researched extensively, but relatively little information exists on evaporative losses during nongrowing periods for different surfaces. The objectives of this research were to evaluate ETc in relation to available energy, precipitation, and grass and alfalfa-reference ET (ETo and ETr) for a maize (Zea mays L.) field and to analyze the dynamics of surface coefficients (Kc) during the nongrowing period (October 15–April 30). The evaporative losses were measured using a Bowen ratio energy balance system (BREBS) on an hourly basis and averaged over 24 h for three consecutive nongrowing periods: 2004–2005 (Season I), 2005–2006 (Season II), and 2006–2007 (Season III). BREBS-measured ETc was approximately 50% of available energy (Rn – G; Rn is net radiation and G is soil heat flux density) during normal and wet seasons (Seasons I and III) and 41% of available energy during a dry season (Season II). Cumulative ETc ranged from 133 mm in Season II to 167 mm in Season III and exceeded precipitation by 21% during the dry season. The ratio of ETc to precipitation was 0.85 in Season I, 1.21 in Season II, and 0.41 in Season III. ETc was approximately 50% of ETo and 36% of ETr in both Seasons I and III, whereas in Season II, ETc was 32% of ETo and 23% of ETr. Overall, measured ETc during the dormant season was generally most strongly correlated with radiation terms, particularly Rn, albedo, incoming shortwave radiation, and outgoing longwave radiation. Average surface coefficients over the three seasons were 0.44 and 0.33 for grass and alfalfa-reference surfaces, respectively. Using geometric mean Kc values to calculate ETc using a Kc ETref approach over the entire nongrowing season yielded adequate predictions with overall root mean square deviations of 0.64 and 0.67 mm day–1 for ETo and ETr, respectively. Estimates of ETc using a dual crop coefficient approach were good on a seasonal basis, but performed less well on a daily basis. Regression equations that were developed (accounting for serial autocorrelation in the ETc and ETref time series) yielded good estimates of ETc. Considering nongrowing period evaporative losses in water budget calculations would enable water regulatory agencies to better account for water use in hydrologic balance calculations over the entire year rather than only for the growing season and to better assess the progression and availability of water resources for the next growing season

Actual and Reference Evaporative Losses and Surface Coefficients of a Maize Field during Nongrowing (Dormant) Periods

Effective water resources planning, allocation, management, and use in agroecosystems require accurate quantification of actual evapotranspiration (ETc) during growing and nongrowing (dormant) periods. Prediction of ETc for a variety of vegetation surfaces during the growing season has been researched extensively, but relatively little information exists on evaporative losses during nongrowing periods for different surfaces. The objectives of this research were to evaluate ETc in relation to available energy, precipitation, and grass and alfalfa-reference ET (ETo and ETr) for a maize (Zea mays L.) field and to analyze the dynamics of surface coefficients (Kc) during the nongrowing period (October 15–April 30). The evaporative losses were measured using a Bowen ratio energy balance system (BREBS) on an hourly basis and averaged over 24 h for three consecutive nongrowing periods: 2004–2005 (Season I), 2005–2006 (Season II), and 2006–2007 (Season III). BREBS-measured ETc was approximately 50% of available energy (Rn – G; Rn is net radiation and G is soil heat flux density) during normal and wet seasons (Seasons I and III) and 41% of available energy during a dry season (Season II). Cumulative ETc ranged from 133 mm in Season II to 167 mm in Season III and exceeded precipitation by 21% during the dry season. The ratio of ETc to precipitation was 0.85 in Season I, 1.21 in Season II, and 0.41 in Season III. ETc was approximately 50% of ETo and 36% of ETr in both Seasons I and III, whereas in Season II, ETc was 32% of ETo and 23% of ETr. Overall, measured ETc during the dormant season was generally most strongly correlated with radiation terms, particularly Rn, albedo, incoming shortwave radiation, and outgoing longwave radiation. Average surface coefficients over the three seasons were 0.44 and 0.33 for grass and alfalfa-reference surfaces, respectively. Using geometric mean Kc values to calculate ETc using a Kc ETref approach over the entire nongrowing season yielded adequate predictions with overall root mean square deviations of 0.64 and 0.67 mm day–1 for ETo and ETr, respectively. Estimates of ETc using a dual crop coefficient approach were good on a seasonal basis, but performed less well on a daily basis. Regression equations that were developed (accounting for serial autocorrelation in the ETc and ETref time series) yielded good estimates of ETc. Considering nongrowing period evaporative losses in water budget calculations would enable water regulatory agencies to better account for water use in hydrologic balance calculations over the entire year rather than only for the growing season and to better assess the progression and availability of water resources for the next growing season

On cooling rate dependent spallation of α-alumina films grown by oxidation [Abstract]

On cooling rate dependent spallation of α-alumina films grown by oxidation [Abstract

On cooling rate dependent spallation behavior of α-alumina scale grown by oxidation

It is hypothesized that dynamic and non-uniform plastic relaxation occurs in α-Al2O3 scale on Fe-Cr-Al substrate during cooling from high temperature, and furthermore, that the non-uniformity of plastic relaxation is related to (1) the variation of residual stress with respect to cooling rate; and (2) the rate of stress relaxation. Based on this hypothesis, a mechanical model is developed which gives accurate predictions for the cooling dependent spallation behavior of α-Al2O3 grown by oxidation

Prioritising Infectious Disease Mapping.

BACKGROUND: Increasing volumes of data and computational capacity afford unprecedented opportunities to scale up infectious disease (ID) mapping for public health uses. Whilst a large number of IDs show global spatial variation, comprehensive knowledge of these geographic patterns is poor. Here we use an objective method to prioritise mapping efforts to begin to address the large deficit in global disease maps currently available. METHODOLOGY/PRINCIPAL FINDINGS: Automation of ID mapping requires bespoke methodological adjustments tailored to the epidemiological characteristics of different types of diseases. Diseases were therefore grouped into 33 clusters based upon taxonomic divisions and shared epidemiological characteristics. Disability-adjusted life years, derived from the Global Burden of Disease 2013 study, were used as a globally consistent metric of disease burden. A review of global health stakeholders, existing literature and national health priorities was undertaken to assess relative interest in the diseases. The clusters were ranked by combining both metrics, which identified 44 diseases of main concern within 15 principle clusters. Whilst malaria, HIV and tuberculosis were the highest priority due to their considerable burden, the high priority clusters were dominated by neglected tropical diseases and vector-borne parasites. CONCLUSIONS/SIGNIFICANCE: A quantitative, easily-updated and flexible framework for prioritising diseases is presented here. The study identifies a possible future strategy for those diseases where significant knowledge gaps remain, as well as recognising those where global mapping programs have already made significant progress. For many conditions, potential shared epidemiological information has yet to be exploited

Estimation of the global prevalence of dementia in 2019 and forecasted prevalence in 2050: an analysis for the Global Burden of Disease Study 2019

Background Given the projected trends in population ageing and population growth, the number of people with dementia is expected to increase. In addition, strong evidence has emerged supporting the importance of potentially modifiable risk factors for dementia. Characterising the distribution and magnitude of anticipated growth is crucial for public health planning and resource prioritisation. This study aimed to improve on previous forecasts of dementia prevalence by producing country-level estimates and incorporating information on selected risk factors. Methods We forecasted the prevalence of dementia attributable to the three dementia risk factors included in the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 (high body-mass index, high fasting plasma glucose, and smoking) from 2019 to 2050, using relative risks and forecasted risk factor prevalence to predict GBD risk-attributable prevalence in 2050 globally and by world region and country. Using linear regression models with education included as an additional predictor, we then forecasted the prevalence of dementia not attributable to GBD risks. To assess the relative contribution of future trends in GBD risk factors, education, population growth, and population ageing, we did a decomposition analysis. Findings We estimated that the number of people with dementia would increase from 57·4 (95% uncertainty interval 50·4–65·1) million cases globally in 2019 to 152·8 (130·8–175·9) million cases in 2050. Despite large increases in the projected number of people living with dementia, age-standardised both-sex prevalence remained stable between 2019 and 2050 (global percentage change of 0·1% [–7·5 to 10·8]). We estimated that there were more women with dementia than men with dementia globally in 2019 (female-to-male ratio of 1·69 [1·64–1·73]), and we expect this pattern to continue to 2050 (female-to-male ratio of 1·67 [1·52–1·85]). There was geographical heterogeneity in the projected increases across countries and regions, with the smallest percentage changes in the number of projected dementia cases in high-income Asia Pacific (53% [41–67]) and western Europe (74% [58–90]), and the largest in north Africa and the Middle East (367% [329–403]) and eastern sub-Saharan Africa (357% [323–395]). Projected increases in cases could largely be attributed to population growth and population ageing, although their relative importance varied by world region, with population growth contributing most to the increases in sub-Saharan Africa and population ageing contributing most to the increases in east Asia. Interpretation Growth in the number of individuals living with dementia underscores the need for public health planning efforts and policy to address the needs of this group. Country-level estimates can be used to inform national planning efforts and decisions. Multifaceted approaches, including scaling up interventions to address modifiable risk factors and investing in research on biological mechanisms, will be key in addressing the expected increases in the number of individuals affected by dementia.F Carvalho and E F Fernandes acknowledge support from the University of Porto (UID/MULTI/04378/2019 and UID/QUI/50006/2019 with funding from FCT/MCTES through national funds). L F S Castro-de-Araujo acknowledges support from the Medical Research Council (London; grant number MC_PC_MR/T03355X/1). V M Costa acknowledges her grant (SFRH/BHD/110001/2015), received by Portuguese national funds through Fundação para a Ciência e Tecnologia (FCT), IP, under the Norma Transitória (DL57/2016/CP1334/CT0006). A Douiri acknowledges support from the NIHR Applied Research Collaboration (ARC) South London at King's College Hospital NHS Foundation Trust and the Royal College of Physicians, as well as the support from the NIHR Biomedical Research Centre based at Guy's and St Thomas' NHS Foundation Trust and King's College London. N Ghith acknowledges her salary as a postdoc is covered by a grant to her research group provided by Novo Nordisk Foundation. V K Gupta and V B Gupta acknowledge funding support from National Health and Medical Research Council (NHMRC), Australia. S Haque acknowledges support from Jazan University, Saudi Arabia, for providing access to the Saudi Digital Library for this study. C Herteliu is partially supported by a grant of the Romanian National Authority for Scientific Research and Innovation (CNDS-UEFISCDI, project number PN-III-P4-ID-PCCF-2016-0084). Y J Kim was supported by the Research Management Centre, Xiamen University, Malaysia (No. XMUMRF/2020-C6/ITCM/0004). M Kivimäki was supported by the MRC (S011676) and the Wellcome Trust (221854/Z/20/Z). M Kumar acknowledges support from Fogarty International Center (K43 TW010716-04). S Lorkowski acknowledges institutional support from the Competence Cluster for Nutrition and Cardiovascular Health (nutriCARD) Halle-Jena-Leipzig (Germany; German Federal Ministry of Education and Research, grant agreement number 01EA1808A). S Mondello was supported by the Italian Ministry of Health (GR-2013-02354960). A Raggi acknowledges support from a grant from the Italian Ministry of Health (Ricerca Corrente, Fondazione Istituto Neurologico C. Besta, Linea – Outcome Research: dagli Indicatori alle Raccomandazioni Cliniche). D A S Silva acknowledges support from Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Brasil (CAPES; Finance Code 001 / CAPES-PRINT). J P Silva acknowledges support from the Applied Molecular Biosciences Unit (UCIBIO; grant number UIDB/04378/2020), supported through Portuguese national funds via FCT/MCTES.publishedVersio

Prioritising Infectious Disease Mapping.

BACKGROUND: Increasing volumes of data and computational capacity afford unprecedented opportunities to scale up infectious disease (ID) mapping for public health uses. Whilst a large number of IDs show global spatial variation, comprehensive knowledge of these geographic patterns is poor. Here we use an objective method to prioritise mapping efforts to begin to address the large deficit in global disease maps currently available. METHODOLOGY/PRINCIPAL FINDINGS: Automation of ID mapping requires bespoke methodological adjustments tailored to the epidemiological characteristics of different types of diseases. Diseases were therefore grouped into 33 clusters based upon taxonomic divisions and shared epidemiological characteristics. Disability-adjusted life years, derived from the Global Burden of Disease 2013 study, were used as a globally consistent metric of disease burden. A review of global health stakeholders, existing literature and national health priorities was undertaken to assess relative interest in the diseases. The clusters were ranked by combining both metrics, which identified 44 diseases of main concern within 15 principle clusters. Whilst malaria, HIV and tuberculosis were the highest priority due to their considerable burden, the high priority clusters were dominated by neglected tropical diseases and vector-borne parasites. CONCLUSIONS/SIGNIFICANCE: A quantitative, easily-updated and flexible framework for prioritising diseases is presented here. The study identifies a possible future strategy for those diseases where significant knowledge gaps remain, as well as recognising those where global mapping programs have already made significant progress. For many conditions, potential shared epidemiological information has yet to be exploited

Therapist Adherence in the Strong Without Anorexia Nervosa (SWAN) Study: A Randomized Controlled Trial of Three Treatments for Adults with Anorexia Nervosa

The Authors. International Journal of Eating Disorders Published by Wiley Periodicals, Inc. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.Objective: To develop a psychotherapy rating scale to measure therapist adherence in the Strong Without Anorexia Nervosa (SWAN) study, a multi-center randomized controlled trial comparing three different psychological treatments for adults with anorexia nervosa. The three treatments under investigation were Enhanced Cognitive Behavioural Therapy (CBT-E), the Maudsley Anorexia Nervosa Treatment for Adults (MANTRA), and Specialist Supportive Clinical Management (SSCM). Method: The SWAN Psychotherapy Rating Scale (SWAN-PRS) was developed, after consultation with the developers of the treatments, and refined. Using the SWANPRS, two independent raters initially rated 48 audiotapes of treatment sessions to yield inter-rater reliability data. One rater proceeded to rate a total of 98 audiotapes from 64 trial participants. Results: The SWAN-PRS demonstrated sound psychometric properties, and was considered a reliable measure of therapist adherence. The three treatments were highly distinguishable by independent raters, with therapists demonstrating significantly more behaviors consistent with the actual allocated treatment compared to the other two treatment modalities. There were no significant site differences in therapist adherence observed. Discussion: The findings provide support for the internal validity of the SWAN study. The SWAN-PRS was deemed suitable for use in other trials involving CBT-E, MANTRA, or SSCM. VC 2015 The Authors. International Journal of Eating Disorders Published by Wiley Periodicals, Inc

Effectiveness of Denitrifying Bioreactors on Water Pollutant Reduction from Agricultural Areas

HighlightsDenitrifying woodchip bioreactors treat nitrate-N in a variety of applications and geographies.This review focuses on subsurface drainage bioreactors and bed-style designs (including in-ditch).Monitoring and reporting recommendations are provided to advance bioreactor science and engineering. Denitrifying bioreactors enhance the natural process of denitrification in a practical way to treat nitrate-nitrogen (N) in a variety of N-laden water matrices. The design and construction of bioreactors for treatment of subsurface drainage in the U.S. is guided by USDA-NRCS Conservation Practice Standard 605. This review consolidates the state of the science for denitrifying bioreactors using case studies from across the globe with an emphasis on full-size bioreactor nitrate-N removal and cost-effectiveness. The focus is on bed-style bioreactors (including in-ditch modifications), although there is mention of denitrifying walls, which broaden the applicability of bioreactor technology in some areas. Subsurface drainage denitrifying bioreactors have been assessed as removing 20% to 40% of annual nitrate-N loss in the Midwest, and an evaluation across the peer-reviewed literature published over the past three years showed that bioreactors around the world have been generally consistent with that (N load reduction median: 46%; mean ±SD: 40% ±26%; n = 15). Reported N removal rates were on the order of 5.1 g N m-3 d-1 (median; mean ±SD: 7.2 ±9.6 g N m-3 d-1; n = 27). Subsurface drainage bioreactor installation costs have ranged from less than $5,000 to$27,000, with estimated cost efficiencies ranging from less than $2.50 kg-1 N year-1 to roughly$20 kg-1 N year-1 (although they can be as high as $48 kg-1 N year-1). A suggested monitoring setup is described primarily for the context of conservation practitioners and watershed groups for assessing annual nitrate-N load removal performance of subsurface drainage denitrifying bioreactors. Recommended minimum reporting measures for assessing and comparing annual N removal performance include: bioreactor dimensions and installation date; fill media size, porosity, and type; nitrate-N concentrations and water temperatures; bioreactor flow treatment details; basic drainage system and bioreactor design characteristics; and N removal rate and efficiency