Oceanic biogeochemical characteristic maps identified with holistic use of satellite, model and data

This is the final published version.Ocean province level plankton community exhibit heterogeneity across Arctic, Nordic, Atlantic Gyre and Southern Ocean provinces. GreenSeas research is an international FP7 consortium that includes Arctic, Atlantic and Southern Ocean based research teams who are analysing the planktonic ecosystem. We are looking at how the planktonic ecosystem responds to environmental and climate change. Using Earth Observation monitoring data we report new results on identifying generic plankton characteristics observable at a province level, and also touch on spatial and temporal trends that are evident using a holistic analysis framework. Using advanced statistical methods this framework compares and combines Earth Observation information together with an in-situ Oceanic plankton Analytical Database and up to 40 year ocean general circulation biogeochemical model (OGCBM) time series of the equivalent plankton and sea-state measures of this system. Specifically, we outline the use of the GreenSeas Analytical Database, which is a harmonised set of Oceanic in-situ plankton and sea-state measures covering different cruises and time periods. The Analytical Database information ranges from plankton community, primary production, nutrient cycling to physical sea state temperature and salinity measures. The combined analysis utilises current, 10 year+ Earth Observations of ocean colour and sea surface temperature metrics and interprets these together with biogeochemical model outputs from PELAGOS, ERSEM & NORWECOM model runs to help identify planktonic based biomes. Generic planktonic characteristic maps that are equivalently observable in both the Earth Observations and numerical models are reported on. Both ocean surface and sub-surface signals are analysed together with relevant Analytical Database biome extracts. We present the current results of this inter-comparison & discuss challenges of identifying the province level plankton dominance with the satellite, model and data. In particular we discuss the strategic importance of systematically analysing the knowledge present in the existing key long term Oceanic observation platforms through such holistic analysis frameworks. These maps help to enhance and improve current biogeochemical models, our understanding of the plankton community structure and predictions used for future assessment of climate change

Desempenho de cultivares de milho para produção de forragem no Estado de Minas Gerais.

Em decorrencia da grande quantidade de cultivares de milho disponiveis no mercado e da variabilidade de suas caracteristicas agronomicas, existe a necessidade de informacoes adequadas para a escolha da cultivar mais adaptadas aos diferentes sistemas de producao das regioes produtoras. Tres variedades, tres hibridos duplos, tres hibridos triplos e tres hibridos simples foram avaliados para a producao de forragem em Sete Lagoas, Uberlandia, Curvelo, Lavras e Sao Sebastiao do Paraiso, no Estado de Minas Gerais. Foi utilizado o delineamento em blocos casualizados, com doze tratamentos e quatro repeticoes em cada local. Foram avaliadas a producao de massa verde e a de materia seca, a percentagem de espigas na materia seca e a percentagem de proteina bruta em colmos, folhas e espigas. Foram efetuadas analises de variancia conjuntas para todas as caracteristicas. As variedades e os hibridos duplos apresentaram maiores producoes de materia seca total do que os hibridos triplos e hibridos simples. Entretanto, as maiores percentagens de espigas na materia seca dos hibridos simples e hibridos triplos indicam que esses deverao produzir forragem de melhor qualidade

Comparison of Methods for Analyzing Left-Censored Occupational Exposure Data

The National Institute for Environmental Health Sciences (NIEHS) is conducting an epidemiologic study (GuLF STUDY) to investigate the health of the workers and volunteers who participated from April to December of 2010 in the response and cleanup of the oil release after the Deepwater Horizon explosion in the Gulf of Mexico. The exposure assessment component of the study involves analyzing thousands of personal monitoring measurements that were collected during this effort. A substantial portion of these data has values reported by the analytic laboratories to be below the limits of detection (LOD). A simulation study was conducted to evaluate three established methods for analyzing data with censored observations to estimate the arithmetic mean (AM), geometric mean (GM), geometric standard deviation (GSD), and the 95th percentile (X0.95) of the exposure distribution: the maximum likelihood (ML) estimation, the β-substitution, and the Kaplan–Meier (K-M) methods. Each method was challenged with computer-generated exposure datasets drawn from lognormal and mixed lognormal distributions with sample sizes (N) varying from 5 to 100, GSDs ranging from 2 to 5, and censoring levels ranging from 10 to 90%, with single and multiple LODs. Using relative bias and relative root mean squared error (rMSE) as the evaluation metrics, the β-substitution method generally performed as well or better than the ML and K-M methods in most simulated lognormal and mixed lognormal distribution conditions. The ML method was suitable for large sample sizes (N ≥ 30) up to 80% censoring for lognormal distributions with small variability (GSD = 2–3). The K-M method generally provided accurate estimates of the AM when the censoring was <50% for lognormal and mixed distributions. The accuracy and precision of all methods decreased under high variability (GSD = 4 and 5) and small to moderate sample sizes (N < 20) but the β-substitution was still the best of the three methods. When using the ML method, practitioners are cautioned to be aware of different ways of estimating the AM as they could lead to biased interpretation. A limitation of the β-substitution method is the absence of a confidence interval for the estimate. More research is needed to develop methods that could improve the estimation accuracy for small sample sizes and high percent censored data and also provide uncertainty intervals

Adaptabilidade e estabilidade de produção de cultivares de milho no Nordeste brasileiro.

Vinte e cinco cultivares de milho (Zea mays L.) foram avaliadas, em 1994, em doze ambientes, na Regiao Nordeste do Brasil, em blocos ao acaso, com tres repeticoes, objetivando conhecer sua adaptabilidade e estabilidade de producao, em diferentes condicoes ambientais. Foram detectados efeitos significativos quanto a ambientes, cultivares e interacao cultivares x ambientes, na analise de variancia conjunta, e foram evidenciadas diferentes marcantes entre os ambientes, as cultivares e respostas das cultivares com relacao as variacoes ambientais. Os hibridos mostraram melhor desempenho produtivo que as variedades, produzindo, em media, 22,5% mais em relacao a media das variedades. Apenas os hibridos Cargill 505 e AG 510 mostraram baixa adaptabilidade a ambientes desfavoraveis, com respostas positivas a melhoria do ambiente. Considerando a media das variedades, a CMS 39 ajustou-se mais ao genotipo ideal proposto pelo modelo. Nenhum dos materiais estudados mostrou coeficiente de determinacao (R2) inferior a 80%, o que confere a todos eles uma boa estabilidade de producao

Selective P2X7 receptor antagonists for chronic inflammation and pain

ATP, acting on P2X7 receptors, stimulates changes in intracellular calcium concentrations, maturation, and release of interleukin-1β (IL-1β), and following prolonged agonist exposure, cell death. The functional effects of P2X7 receptor activation facilitate several proinflammatory processes associated with arthritis. Within the nervous system, these proinflammatory processes may also contribute to the development and maintenance of chronic pain. Emerging data from genetic knockout studies have indicated specific roles for P2X7 receptors in inflammatory and neuropathic pain states. The discovery of multiple distinct chemical series of potent and highly selective P2X7 receptor antagonists have enhanced our understanding of P2X7 receptor pharmacology and the diverse array of P2X7 receptor signaling mechanisms. These antagonists have provided mechanistic insight into the role(s) P2X7 receptors play under pathophysiological conditions. In this review, we integrate the recent discoveries of novel P2X7 receptor-selective antagonists with a brief update on P2X7 receptor pharmacology and its therapeutic potential

External validation of prognostic models to predict stillbirth using the International Prediction of Pregnancy Complications (IPPIC) Network database: an individual participant data meta-analysis

Objective Stillbirth is a potentially preventable complication of pregnancy. Identifying women at high risk of stillbirth can guide decisions on the need for closer surveillance and timing of delivery in order to prevent fetal death. Prognostic models have been developed to predict the risk of stillbirth, but none has yet been validated externally. In this study, we externally validated published prediction models for stillbirth using individual participant data (IPD) meta-analysis to assess their predictive performance. Methods MEDLINE, EMBASE, DH-DATA and AMED databases were searched from inception to December 2020 to identify studies reporting stillbirth prediction models. Studies that developed or updated prediction models for stillbirth for use at any time during pregnancy were included. IPD from cohorts within the International Prediction of Pregnancy Complications (IPPIC) Network were used to validate externally the identified prediction models whose individual variables were available in the IPD. The risk of bias of the models and cohorts was assessed using the Prediction study Risk Of Bias ASsessment Tool (PROBAST). The discriminative performance of the models was evaluated using the C-statistic, and calibration was assessed using calibration plots, calibration slope and calibration-in-the-large. Performance measures were estimated separately in each cohort, as well as summarized across cohorts using random-effects meta-analysis. Clinical utility was assessed using net benefit. Results Seventeen studies reporting the development of 40 prognostic models for stillbirth were identified. None of the models had been previously validated externally, and the full model equation was reported for only one-fifth (20%, 8/40) of the models. External validation was possible for three of these models, using IPD from 19 cohorts (491 201 pregnant women) within the IPPIC Network database. Based on evaluation of the model development studies, all three models had an overall high risk of bias, according to PROBAST. In the IPD meta-analysis, the models had summary C-statistics ranging from 0.53 to 0.65 and summary calibration slopes ranging from 0.40 to 0.88, with risk predictions that were generally too extreme compared with the observed risks. The models had little to no clinical utility, as assessed by net benefit. However, there remained uncertainty in the performance of some models due to small available sample sizes. Conclusions The three validated stillbirth prediction models showed generally poor and uncertain predictive performance in new data, with limited evidence to support their clinical application. The findings suggest methodological shortcomings in their development, including overfitting. Further research is needed to further validate these and other models, identify stronger prognostic factors and develop more robust prediction models. (c) 2021 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.Peer reviewe

Ευρετικές προσεγγίσεις του μοναδιάστατου προβλήματος πακετοποίησης

Article 59.1, of the International Code of Nomenclature for Algae, Fungi, and Plants (ICN; Melbourne Code), which addresses the nomenclature of pleomorphic fungi, became effective from 30 July 2011. Since that date, each fungal species can have one nomenclaturally correct name in a particular classification. All other previously used names for this species will be considered as synonyms. The older generic epithet takes priority over the younger name. Any widely used younger names proposed for use, must comply with Art. 57.2 and their usage should be approved by the Nomenclature Committee for Fungi (NCF). In this paper, we list all genera currently accepted by us in Dothideomycetes (belonging to 23 orders and 110 families), including pleomorphic and non-pleomorphic genera. In the case of pleomorphic genera, we follow the rulings of the current ICN and propose single generic names for future usage. The taxonomic placements of 1261 genera are listed as an outline. Protected names and suppressed names for 34 pleomorphic genera are listed separately. Notes and justifications are provided for possible proposed names after the list of genera. Notes are also provided on recent advances in our understanding of asexual and sexual morph linkages in Dothideomycetes. A phylogenetic tree based on four gene analyses supported 23 orders and 75 families, while 35 families still lack molecular data

Stability of equilibrium states in a simple system with unilateral contact and Coulomb friction

International audienceThe aim of this paper is to study the stability of equilibrium states in a mechanical system involving unilateral contact with Coulomb friction. Since the assumptions made in classical stability theorems are not satisfied with this class of systems, we return to the basic definitions of stability by studying the time evolution of the distance between a given equilibrium and the solution of a Cauchy problem where the initial conditions are in a neighborhood of the equilibrium. It was recently established that the dynamics is well posed in the case of analytical data. In the present study, we focus in particular on the stability of the equilibrium states under a constant force and deal only with a simple mass-spring system in $\mathbb{R}^2$