Editorial: Building and delivering real-world, integrated sustainability solutions: Insights, methods and case-study applications

This Research Topic aims to showcase research, development and technology (RDT) work toward devising and delivering integrated solutions that support and enhance the climate smart landscape (CSL)-based approach. This Research Topic comprises 13 articles, including 10 Original Research articles,1 Review, 1 Hypothesis and Theory article, and 1 Technology Report. State-of-the-art modeling approaches and sampling technologies are showcased. Contributed papers present new methodological/technological innovation, findings, and/or insights across four themes: (1) landscape productivity and crop suitability, (2) variable crop requirements for water and nutrients,(3) crop health status, phenology and phenotyping, (4)crop disease assessment and prediction under integrated pest management (IPM) and the CSL approach

Dynamic model to predict the association between air quality, COVID-19 cases, and level of lockdown

Studies have reported significant reductions in air pollutant levels due to the COVID-19 outbreak worldwide due to global lockdowns. Nevertheless, all of the reports are limited compared to data from the same period over the past few years, providing mainly an overview of past events, with no future predictions. Lockdown level can be directly related to the number of new COVID-19 cases, air pollution, and economic restriction. As lockdown status varies considerably across the globe, there is a window for mega-cities to determine the optimum lockdown flexibility. To that end, firstly, we employed four different Artificial Neural Networks (ANN) to examine the compatibility to the original levels of CO, O3, NO2, NO, PM2.5, and PM10, for São Paulo City, the current Pandemic epicenter in South America. After checking compatibility, we simulated four hypothetical scenarios: 10%, 30%, 70%, and 90% lockdown to predict air pollution levels. To our knowledge, ANN have not been applied to air pollution prediction by lockdown level. Using a limited database, the Multilayer Perceptron neural network has proven to be robust (with Mean Absolute Percentage Error ∼ 30%), with acceptable predictive power to estimate air pollution changes. We illustrate that air pollutant levels can effectively be controlled and predicted when flexible lockdown measures are implemented. The models will be a useful tool for governments to manage the delicate balance among lockdown, number of COVID-19 cases, and air pollution

Biological decolorization of xanthene dyes by anaerobic granular biomass

Biodegradation of a xanthene dyes was investigated for the first time using anaerobic granular sludge. On a first screening, biomass was able to decolorize, at different extents, six azo dye solutions: acid orange 7, direct black 19, direct blue 71, mordant yellow 10, reactive red 2 and reactive red 120 and two xanthene dyes—Erythrosine B and Eosin Y. Biomass concentration, type of electron donor, induction of biomass with dye and mediation with activated carbon (AC) were variables studied for Erythrosine B (Ery) as model dye. Maximum color removal efficiency was achieved with 4.71 g VSS L−1, while the process rates were independent of the biomass concentration above 1.89 g VSS L−1. No considerable effects were observed when different substrates were used as electron donors (VFA, glucose or lactose). Addition of Ery in the incubation period of biomass led to a fivefold increase of the decolorization rate. The rate of Ery decolorization almost duplicated in the presence of commercial AC (0.1 g L−1 AC0). Using different modified AC samples (from the treatment of AC0), a threefold higher rate was obtained with the most basic one, \textAC\textH2ACH2, as compared with non-mediated reaction. Higher rates were obtained at pH 6.0. Chemical reduction using Na2S confirmed the recalcitrant nature of this dye. The results attest that decolorization of Ery is essentially due to enzymatic and adsorption phenomena.This work was supported by the PTDC/AMB/69335/2006 project grants (Fundacao para a Ciencia e Technologia, FCT, Portugal), BRAIN project (ID 6681, European Social Found and Romanian Government and the grant of the Romanian National Authority for Scientific Research, CNCS-UEFISCDI, project number PN-II-ID-PCE-2011-3-0559, Contract 265/2011

Bayesian Space-Time Patterns and Climatic Determinants of Bovine Anaplasmosis

Citation: Hanzlicek, G. A., Raghavan, R. K., Ganta, R. R., & Anderson, G. A. (2016). Bayesian Space-Time Patterns and Climatic Determinants of Bovine Anaplasmosis. Plos One, 11(3), 13. doi:10.1371/journal.pone.0151924The space-time pattern and environmental drivers (land cover, climate) of bovine anaplasmosis in the Midwestern state of Kansas was retrospectively evaluated using Bayesian hierarchical spatio-temporal models and publicly available, remotely-sensed environmental covariate information. Cases of bovine anaplasmosis positively diagnosed at Kansas State Veterinary Diagnostic Laboratory (n = 478) between years 2005-2013 were used to construct the models, which included random effects for space, time and space-time interaction effects with defined priors, and fixed-effect covariates selected a priori using an univariate screening procedure. The Bayesian posterior median and 95% credible intervals for the space-time interaction term in the best-fitting covariate model indicated a steady progression of bovine anaplasmosis over time and geographic area in the state. Posterior median estimates and 95% credible intervals derived for covariates in the final covariate model indicated land surface temperature (minimum), relative humidity and diurnal temperature range to be important risk factors for bovine anaplasmosis in the study. The model performance measured using the Area Under the Curve (AUC) value indicated a good performance for the covariate model (>0.7). The relevance of climatological factors for bovine anaplasmosis is discussed

Vegan diets : practical advice for athletes and exercisers.

With the growth of social media as a platform to share information, veganism is becoming more visible, and could be becoming more accepted in sports and in the health and fitness industry. However, to date, there appears to be a lack of literature that discusses how to manage vegan diets for athletic purposes. This article attempted to review literature in order to provide recommendations for how to construct a vegan diet for athletes and exercisers. While little data could be found in the sports nutrition literature specifically, it was revealed elsewhere that veganism creates challenges that need to be accounted for when designing a nutritious diet. This included the sufficiency of energy and protein; the adequacy of vitamin B12, iron, zinc, calcium, iodine and vitamin D; and the lack of the long-chain n-3 fatty acids EPA and DHA in most plant-based sources. However, via the strategic management of food and appropriate supplementation, it is the contention of this article that a nutritive vegan diet can be designed to achieve the dietary needs of most athletes satisfactorily. Further, it was suggested here that creatine and β-alanine supplementation might be of particular use to vegan athletes, owing to vegetarian diets promoting lower muscle creatine and lower muscle carnosine levels in consumers. Empirical research is needed to examine the effects of vegan diets in athletic populations however, especially if this movement grows in popularity, to ensure that the health and performance of athletic vegans is optimised in accordance with developments in sports nutrition knowledge

Global patient outcomes after elective surgery: prospective cohort study in 27 low-, middle- and high-income countries.

BACKGROUND: As global initiatives increase patient access to surgical treatments, there remains a need to understand the adverse effects of surgery and define appropriate levels of perioperative care. METHODS: We designed a prospective international 7-day cohort study of outcomes following elective adult inpatient surgery in 27 countries. The primary outcome was in-hospital complications. Secondary outcomes were death following a complication (failure to rescue) and death in hospital. Process measures were admission to critical care immediately after surgery or to treat a complication and duration of hospital stay. A single definition of critical care was used for all countries. RESULTS: A total of 474 hospitals in 19 high-, 7 middle- and 1 low-income country were included in the primary analysis. Data included 44 814 patients with a median hospital stay of 4 (range 2-7) days. A total of 7508 patients (16.8%) developed one or more postoperative complication and 207 died (0.5%). The overall mortality among patients who developed complications was 2.8%. Mortality following complications ranged from 2.4% for pulmonary embolism to 43.9% for cardiac arrest. A total of 4360 (9.7%) patients were admitted to a critical care unit as routine immediately after surgery, of whom 2198 (50.4%) developed a complication, with 105 (2.4%) deaths. A total of 1233 patients (16.4%) were admitted to a critical care unit to treat complications, with 119 (9.7%) deaths. Despite lower baseline risk, outcomes were similar in low- and middle-income compared with high-income countries. CONCLUSIONS: Poor patient outcomes are common after inpatient surgery. Global initiatives to increase access to surgical treatments should also address the need for safe perioperative care. STUDY REGISTRATION: ISRCTN5181700

Methods, fluxes and sources of gas phase alkyl nitrates in the coastal air

The daily and seasonal atmospheric concentrations, deposition fluxes and emission sources of a few C3-C9 gaseous alkyl nitrates (ANs) at the Belgian coast (De Haan) on the Southern North Sea were determined. An adapted sampler design for low- and high-volume air-sampling, optimized sample extraction and clean-up, as well as identification and quantification of ANs in air samples by means of gas chromatography mass spectrometry, are reported. The total concentrations of ANs ranged from 0.03 to 85 pptv and consisted primarily of the nitro-butane and nitro-pentane isomers. Air mass backward trajectories were calculated by the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model to determine the influence of main air masses on AN levels in the air. The shorter chain ANs have been the most abundant in the Atlantic/Channel/UK air masses, while longer chain ANs prevailed in continental air. The overall mean N fluxes of the ANs were slightly higher for summer than those for winter-spring, although their contributions to the total nitrogen flux were low. High correlations between AN and HNO2 levels were observed during winter/spring. During summer, the shorter chain ANs correlated well with precipitation. Source apportionment by means of principal component analysis indicated that most of the gas phase ANs could be attributed to traffic/combustion, secondary photochemical formation and biomass burning, although marine sources may also have been present and a contributing factor. © 2014 Springer International Publishing Switzerland