Equitability revisited: why the “equitable threat score” is not equitable

In the forecasting of binary events, verification measures that are “equitable” were defined by Gandin and Murphy to satisfy two requirements: 1) they award all random forecasting systems, including those that always issue the same forecast, the same expected score (typically zero), and 2) they are expressible as the linear weighted sum of the elements of the contingency table, where the weights are independent of the entries in the table, apart from the base rate. The authors demonstrate that the widely used “equitable threat score” (ETS), as well as numerous others, satisfies neither of these requirements and only satisfies the first requirement in the limit of an infinite sample size. Such measures are referred to as “asymptotically equitable.” In the case of ETS, the expected score of a random forecasting system is always positive and only falls below 0.01 when the number of samples is greater than around 30. Two other asymptotically equitable measures are the odds ratio skill score and the symmetric extreme dependency score, which are more strongly inequitable than ETS, particularly for rare events; for example, when the base rate is 2% and the sample size is 1000, random but unbiased forecasting systems yield an expected score of around −0.5, reducing in magnitude to −0.01 or smaller only for sample sizes exceeding 25 000. This presents a problem since these nonlinear measures have other desirable properties, in particular being reliable indicators of skill for rare events (provided that the sample size is large enough). A potential way to reconcile these properties with equitability is to recognize that Gandin and Murphy’s two requirements are independent, and the second can be safely discarded without losing the key advantages of equitability that are embodied in the first. This enables inequitable and asymptotically equitable measures to be scaled to make them equitable, while retaining their nonlinearity and other properties such as being reliable indicators of skill for rare events. It also opens up the possibility of designing new equitable verification measures.

A unique example of structural and magnetic diversity in four interconvertible copper(II)−azide complexes with the same Schiff base ligand: a monomer, a dimer, a chain, and a layer

Four new Cu(II)-azido complexes of formula [CuL(N-3)] (1), [CuL(N-3)](2) (2), [Cu7L2(N-3)(12)](n) (3), and [Cu2L(dmen)-(N-3)(3)](n) (4) (dmen = N,N-dimethylethylenediamine) have been synthesized using the same tridentate Schiff base ligand HL (2-[1-(2-dimethylaminoethylimino)ethyl]phenol, the condensation product of dmen and 2-hydroxyacetophenone). The four compounds have been characterized by X-ray structural analyses and variable-temperature magnetic susceptibility measurements. Complex 1 is mononuclear, whereas 2 is a single mu-1,1 azido-bridged dinuclear compound. The polymeric compound 3 possesses a 2D structure in which the Cu(II) ions are linked by phenoxo oxygen atoms and two different azide bridges (mu-1,1 and mu-1,1,3). The structure of complex 4 is a double helix in which two mu-1,3-azido-bridged alternating one-dimensional helical chains of CuL(N-3) and Cu(dmen)(N-3)(2) are joined together by weak mu-1,1 azido bridges and H-bonds. The complexes interconvert in solution and can be obtained in pure form by carefully controlling the conditions. The magnetic properties of compounds 1 and 2 show the presence of very weak antiferromagnetic exchange interactions mediated by a ligand pi overlap (J = -1.77) and by an asymmetric 1,1-N-3 bridge (J = -1.97 cm(-1)), respectively. Compound 3 presents, from the magnetic point of view, a decorated chain structure with both ferro- and antiferromagnetic interactions. Compound 4 is an alternating helicoidal chain with two weak antiferromagnetic exchange interactions (J -1.35 and -2.64 cm(-1)).

A simple, coherent framework for partitioning uncertainty in climate predictions

A simple and coherent framework for partitioning uncertainty in multi-model climate ensembles is presented. The analysis of variance (ANOVA) is used to decompose a measure of total variation additively into scenario uncertainty, model uncertainty and internal variability. This approach requires fewer assumptions than existing methods and can be easily used to quantify uncertainty related to model-scenario interaction - the contribution to model uncertainty arising from the variation across scenarios of model deviations from the ensemble mean. Uncertainty in global mean surface air temperature is quantified as a function of lead time for a subset of the Coupled Model Intercomparison Project phase 3 ensemble and results largely agree with those published by other authors: scenario uncertainty dominates beyond 2050 and internal variability remains approximately constant over the 21st century. Both elements of model uncertainty, due to scenario-independent and scenario-dependent deviations from the ensemble mean, are found to increase with time. Estimates of model deviations that arise as by-products of the framework reveal significant differences between models that could lead to a deeper understanding of the sources of uncertainty in multi-model ensembles. For example, three models are shown diverging pattern over the 21st century, while another model exhibits an unusually large variation among its scenario-dependent deviations.

Avaliação citopatológica da medula óssea e perfil hematológico de cães naturalmente infectados por Leishmania (Leishmania) chagasiCarla de Oliveira Honse

Foram avaliados quarenta e um cães adultos, machos e fêmeas, sem raça definida, provenientes de inquéritos sorológicos para leishmaniose visceral canina realizados pela Secretaria Municipal de Saúde do Rio de Janeiro. O objetivo deste estudo foi descrever as alterações citopatológicas da medula óssea e o perfil hematológico de cães naturalmente infectados por Leishmania (Leishmania) chagasi. A avaliação citológica da medula óssea incluiu a análise qualitativa e quantitativa. O perfil hematológico foi avaliado através de contador automático de células e esfregaços sanguíneos. Adicionalmente, foram realizadas a imunofenotipagem de linfócitos medulares, pesquisa de formas amastigotas na medula óssea e avaliação dos estoques de ferro medular. De acordo com os resultados obtidos, cães naturalmente infectados por L. (L.) chagasi apresentaram hiperplasia das séries mieloide, linfoide e monocítica, onde frequentemente foram observadas formas amastigotas, anemia normocítica normocrômica e aumento dos estoques de ferro medular Não foram observadas diferenças estatisticamente significativas entre as populações de linfócitos T e linfócitos B medulares. Em conclusão, os cães naturalmente infectados por L. (L.) chagasi apresentaram alterações na medula óssea e no perfil hematológico independentemente da manifestação clínica apresentada pelo animal. Hiperplasia das linhagens hematopoiéticas, anemia, eritrofagocitose e aumento dos estoques de ferro medular possibilitaram uma melhor compreensão dos mecanismos fisiopatológicos envolvidos na doença e a pesquisa de formas amastigotas na medula óssea contribuiu como uma importante ferramenta diagnóstica da leishmaniose visceral canina

Avaliação dos produtos da degradação da hemoglobina na lesão cerebral e mecanismos de proteção encefálica após a hemorragia intracraniana

Introdução: O acidente vascular encefálico hemorrágico e a hemorragia subaracnóide são doenças de elevada morbi-mortalidade. Os produtos da degradação da hemoglobina são implicados em diversos estudos experimentais como elementoschave na fisiopatologia da lesão secundária após a hemorragia intracraniana. Entretanto, há poucos dados em humanos que possam corroborar as observações experimentais. Objetivo: Avaliar o papel dos produtos da degradação da hemoglobina e dos mecanismos de proteção contra a hemoglobina e o heme na fisiopatologia do dano secundário à hemorragia intracraniana. Métodos: Estudo prospectivo realizado nas unidades neurointensivas de três hospitais. Foi coletado sangue e líquor (pela DVE) de pacientes internados com AVEh ou HSA e hemoventrículo durante os primeiros três dias após o ictus. Foram dosadas sequencialmente as concentrações de ferro, heme, hemopexina, haptoglobina, enolase e S100-\03B2 além de um painel de citocinas. O desfecho primário era mortalidade em 7 dias Resultados: Quinze pacientes foram incluídos, 10 com HSA e 5 com AVEh. Após a hemorragia intracraniana, ocorreu o desencadeamento da resposta inflamatória no sistema nervoso central (SNC), com níveis de IL-8 e GM-CSF no líquor cerca de 20x superiores ao do plasma. Foi observada a correlação entre a concentração de ferro e IP-10 no líquor (r=0,97; p=0,03) e heme e MIP-1b no líquor (r=0,76; p=0,01). Os níveis de hemopexina e haptoglobina foram consistentemente inferiores no líquor em relação ao plasma, ao longo dos três dias de estudo. Tanto o ferro e heme plasmáticos, quanto o grau de resposta inflamatória sistêmica e no SNC foram preditores de mortalidade nos primeiros 7 dias após o evento. Conclusão: Os resultados desse estudo mostram que tanto o ferro quanto o heme estão correlacionados ao desencadeamento da lesão secundária após a hemorragia intracraniana e estão associados ao pior prognóstico neste grupo de pacientes. Além disso, os mecanismos de proteção cerebral contra a hemoglobina e o heme são insuficientes. Mais estudos são necessários para elucidar o papel dos produtos da degradação da hemoglobina na fisiopatologia da hemorragia intracraniana em humanos

A verification framework for interannual-to-decadal predictions experiments

Decadal predictions have a high profile in the climate science community and beyond, yet very little is known about their skill. Nor is there any agreed protocol for estimating their skill. This paper proposes a sound and coordinated framework for verification of decadal hindcast experiments. The framework is illustrated for decadal hindcasts tailored to meet the requirements and specifications of CMIP5 (Coupled Model Intercomparison Project phase 5). The chosen metrics address key questions about the information content in initialized decadal hindcasts. These questions are: (1) Do the initial conditions in the hindcasts lead to more accurate predictions of the climate, compared to un-initialized climate change projections? and (2) Is the prediction model’s ensemble spread an appropriate representation of forecast uncertainty on average? The first question is addressed through deterministic metrics that compare the initialized and uninitialized hindcasts. The second question is addressed through a probabilistic metric applied to the initialized hindcasts and comparing different ways to ascribe forecast uncertainty. Verification is advocated at smoothed regional scales that can illuminate broad areas of predictability, as well as at the grid scale, since many users of the decadal prediction experiments who feed the climate data into applications or decision models will use the data at grid scale, or downscale it to even higher resolution. An overall statement on skill of CMIP5 decadal hindcasts is not the aim of this paper. The results presented are only illustrative of the framework, which would enable such studies. However, broad conclusions that are beginning to emerge from the CMIP5 results include (1) Most predictability at the interannual-to-decadal scale, relative to climatological averages, comes from external forcing, particularly for temperature; (2) though moderate, additional skill is added by the initial conditions over what is imparted by external forcing alone; however, the impact of initialization may result in overall worse predictions in some regions than provided by uninitialized climate change projections; (3) limited hindcast records and the dearth of climate-quality observational data impede our ability to quantify expected skill as well as model biases; and (4) as is common to seasonal-to-interannual model predictions, the spread of the ensemble members is not necessarily a good representation of forecast uncertainty. The authors recommend that this framework be adopted to serve as a starting point to compare prediction quality across prediction systems. The framework can provide a baseline against which future improvements can be quantified. The framework also provides guidance on the use of these model predictions, which differ in fundamental ways from the climate change projections that much of the community has become familiar with, including adjustment of mean and conditional biases, and consideration of how to best approach forecast uncertainty.

Increasing influence of heat stress on French maize yields from the 1960s to the 2030s

Improved crop yield forecasts could enable more effective adaptation to climate variability and change. Here, we explore how to combine historical observations of crop yields and weather with climate model simulations to produce crop yield projections for decision relevant timescales. Firstly, the effects on historical crop yields of improved technology, precipitation and daily maximum temperatures are modelled empirically, accounting for a nonlinear technology trend and interactions between temperature and precipitation, and applied specifically for a case study of maize in France. The relative importance of precipitation variability for maize yields in France has decreased significantly since the 1960s, likely due to increased irrigation. In addition, heat stress is found to be as important for yield as precipitation since around 2000. A significant reduction in maize yield is found for each day with a maximum temperature above 32 °C, in broad agreement with previous estimates. The recent increase in such hot days has likely contributed to the observed yield stagnation. Furthermore, a general method for producing near-term crop yield projections, based on climate model simulations, is developed and utilized. We use projections of future daily maximum temperatures to assess the likely change in yields due to variations in climate. Importantly, we calibrate the climate model projections using observed data to ensure both reliable temperature mean and daily variability characteristics, and demonstrate that these methods work using retrospective predictions. We conclude that, to offset the projected increased daily maximum temperatures over France, improved technology will need to increase base level yields by 12% to be confident about maintaining current levels of yield for the period 2016–2035; the current rate of yield technology increase is not sufficient to meet this target.

Simple uncertainty frameworks for selecting weighting schemes and interpreting multimodel ensemble climate change experiments

Future climate change projections are often derived from ensembles of simulations from multiple global circulation models using heuristic weighting schemes. This study provides a more rigorous justification for this by introducing a nested family of three simple analysis of variance frameworks. Statistical frameworks are essential in order to quantify the uncertainty associated with the estimate of the mean climate change response. The most general framework yields the “one model, one vote” weighting scheme often used in climate projection. However, a simpler additive framework is found to be preferable when the climate change response is not strongly model dependent. In such situations, the weighted multimodel mean may be interpreted as an estimate of the actual climate response, even in the presence of shared model biases. Statistical significance tests are derived to choose the most appropriate framework for specific multimodel ensemble data. The framework assumptions are explicit and can be checked using simple tests and graphical techniques. The frameworks can be used to test for evidence of nonzero climate response and to construct confidence intervals for the size of the response. The methodology is illustrated by application to North Atlantic storm track data from the Coupled Model Intercomparison Project phase 5 (CMIP5) multimodel ensemble. Despite large variations in the historical storm tracks, the cyclone frequency climate change response is not found to be model dependent over most of the region. This gives high confidence in the response estimates. Statistically significant decreases in cyclone frequency are found on the flanks of the North Atlantic storm track and in the Mediterranean basin.

Boundary condition effects in the simulation study of equilibrium properties of magnetic dipolar fluids

In this paper we investigate the equilibrium properties of magnetic dipolar (ferro-) fluids and discuss finite-size effects originating from the use of different boundary conditions in computer simulations. Both periodic boundary conditions and a finite spherical box are studied. We demonstrate that periodic boundary conditions and subsequent use of Ewald sum to account for the long-range dipolar interactions lead to a much faster convergence (in terms of the number of investigated dipolar particles) of the magnetization curve and the initial susceptibility to their thermodynamic limits. Another unwanted effect of the simulations in a finite spherical box geometry is a considerable sensitivity to the container size. We further investigate the influence of the surface term in the Ewald sum-that is, due to the surrounding continuum with magnetic permeability mu(BC)-on the convergence properties of our observables and on the final results. The two different ways of evaluating the initial susceptibility, i.e., (1) by the magnetization response of the system to an applied field and (2) by the zero-field fluctuation of the mean-square dipole moment of the system, are compared in terms of speed and accuracy.

Molecular dynamics study on the equilibrium magnetization properties and structure of ferrofluids

We investigate in detail the initial susceptibility, magnetization curves, and microstructure of ferrofluids in various concentration and particle dipole moment ranges by means of molecular dynamics simulations. We use the Ewald summation for the long-range dipolar interactions, take explicitly into account the translational and rotational degrees of freedom, coupled to a Langevin thermostat. When the dipolar interaction energy is comparable with the thermal energy, the simulation results on the magnetization properties agree with the theoretical predictions very well. For stronger dipolar couplings, however, we find systematic deviations from the theoretical curves. We analyze in detail the observed microstructure of the fluids under different conditions. The formation of clusters is found to enhance the magnetization at weak fields and thus leads to a larger initial susceptibility. The influence of the particle aggregation is isolated by studying ferro-solids, which consist of magnetic dipoles frozen in at random locations but which are free to rotate. Due to the artificial suppression of clusters in ferrosolids the observed susceptibility is considerably lowered when compared to ferrofluids.

On judging the credibility of climate predictions

Incorporating a prediction into future planning and decision making is advisable only if we have judged the prediction’s credibility. This is notoriously difficult and controversial in the case of predictions of future climate. By reviewing epistemic arguments about climate model performance, we discuss how to make and justify judgments about the credibility of climate predictions. We propose a new bounding argument that justifies basing such judgments on the past performance of possibly dissimilar prediction problems. This encourages a more explicit use of data in making quantitative judgments about the credibility of future climate predictions, and in training users of climate predictions to become better judges of credibility. We illustrate the approach using decadal predictions of annual mean, global mean surface air temperature.

Hemiparkinsonian rats rotate toward the side with the weaker dopaminergic neurotransmission

Rats with unilateral lesion of the substantia nigra pars compacta (SNpc) have been used as a model of Parkinson`s disease. Depending on the lesion protocol and on the drug challenge, these rats rotate in opposite directions. The aim of the present study was to propose a model to explain how critical factors determine the direction of these turns. Unilateral lesion of the SNpc was induced with 6-hydroxydopamine (6-OHDA) or 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP). Separate analysis showed that neither the type of neurotoxin nor the site of lesion along the nigrostriatal. pathway was able to predict the direction of the turns these rats made after they were challenged with apomorphine. However, the combination of these two factors determined the magnitude of the lesion estimated by tyrosine-hydroxylase immunohistochemistry and HPLC-ED measurement of striatal dopamine. Very small lesions did Dot cause turns, medium-size lesions caused ipsiversive turns, and large lesions caused contraversive turns. Large-size SNpc lesions resulted in an increased binding of [H-3] raclopride to D2 receptors, while medium-size lesions reduced the binding of [H-3]SCH-23390 D1 receptors in the ipsilateral striatum. These results are coherent with the model proposing that after challenged with a dopamine receptor agonist, unilaterally SNpc-lesioned rats rotate toward the side with the weaker activation of dopamine receptors. This activation is weaker on the lesioned side in animals with small SNpc lesions due to the loss of dopamine, but stronger in animals with large lesions due to dopamine receptor supersensitivity. (C) 2008 Elsevier B.V. All rights reserved.