Unexplored documentary sources to assess climate variability in the Mediterranean sea

The CLIWOC project has recently shown the potential of 18th and 19th century logbooks to reconstruct wind climatology in the open oceans. This paper examines the availability of non-digitised logbooks covering the Mediterranean Sea during the same period. It is shown that the combination of logbooks kept in British, French and Spanish archives would provide a high density of observations which could result in a significant wind climatology for the Maditerranean Sea

Preface: Understanding dynamics and current developments of climate extremes in the Mediterranean region

There is an increasing interest of scientists on climate extremes. A progressively larger number of papers dealing with climate issues have been produced in the past 15 yr, and those dealing with extremes have increased at an even faster pace. The number of papers on extremes in the Mediterranean follows this overall trend and confirms how extremes are perceived to be important by the scientific community and by society. This special issue (which is mainly related to activities of the MedCLIVAR (Mediterranean CLImate VARiability and Predictability) and CIRCE (Climate Change and Impact Research: the Mediterranean Environment) projects), contains thirteen papers that are representative of current research on extremes in the Mediterranean region. Five have precipitation as its main target, four temperature (one paper addresses both variables), and two droughts; the remaining papers consider sea level, winds and impacts on society. Results are quite clear concerning climate evolution toward progressively hotter temperature extremes, but more controversial for precipitation, though in the published literature there are indications for a future increasing intensity of hydrological extremes (intense precipitation events and droughts). Scenario simulations suggest an attenuation of extreme storms, winds, waves and surges, but more results are requested for confirming this future change

Rigidity and Vanishing Theorems for Almost Even-Clifford Hermitian Manifolds

We prove the rigidity and vanishing of several indices of ''geometrically natural'' twisted Dirac operators on almost even-Clifford Hermitian manifolds admitting circle actions by automorphisms

The Dynamical Behaviour of Test Particles in a Quasi-Spherical Spacetime and the Physical Meaning of Superenergy

We calculate the instantaneous proper radial acceleration of test particles (as measured by a locally defined Lorentzian observer) in a Weyl spacetime, close to the horizon. As expected from the Israel theorem, there appear some bifurcations with respect to the spherically symmetric case (Schwarzschild), which are explained in terms of the behaviour of the superenergy, bringing out the physical relevance of this quantity in the study of general relativistic systems.Comment: 14 pages, Latex. 4 figures. New references added. Typos corrected. To appear in Int. J. Theor. Phy

Magnetic field dependence of the density of states in the multiband superconductor β\beta-Bi2_2Pd

We present very low temperature scanning tunneling microscopy (STM) experiments on single crystalline samples of the superconductor $\beta$-Bi$_2$Pd. We find a single fully isotropic superconducting gap. However, the magnetic field dependence of the intervortex density of states is higher than the one expected in a single gap superconductor, and the hexagonal vortex lattice is locked to the square atomic lattice. Such increase in the intervortex density of states and vortex lattice locking have been found in superconductors with multiple superconducting gaps and anisotropic Fermi surfaces. We compare the upper critical field $H_{c2}(T)$ obtained in our sample with previous measurements and explain available data within multiband supercondutivity. We propose that $\beta$-Bi$_2$Pd is a single gap multiband superconductor. We anticipate that single gap multiband superconductivity can occur in other compounds with complex Fermi surfaces.Comment: 8 pages, 7 figure

Análise multivariada de características de carcaça e qualidade da carne de ovinos.

Resumo: Técnicas de análise multivariada foram utilizadas para avaliação de características de carcaça e qualidade da carne de cordeiros: Morada Nova (MN), Somalis Brasileira (SB), Santa Inês (SI) e ½ Dorper x ½ Morada Nova (F1). Na análise fatorial, os cinco primeiros fatores extraídos por componentes principais explicaram 80 % da variância total dos dados. Os escores calculados para cada fator foram utilizados na análise de variância. Houve efeito significativo do grupo genético para os fatores 1, 3 e 4. O primeiro fator é o processo que representa às características morfométricas da carcaça, os pesos ao abate e da carcaça, os pesos dos cortes comerciais e a área de olho de lombo, sendo a raça SI superior às raças SB e MN, porém similar ao genótipo F1. Esse fator explica 52,65 % da variância total dos dados. Quanto ao terceiro (espessura de gordura e intensidade de vermelho da carne) e ao quarto fator (índice de quebra por resfriamento e perda de peso por cocção) a raça SB apresentou maior especificidade, diferindo dos demais grupos. Para o segundo fator (pH medido 24 horas post mortem, luminosidade da carne e intensidade de amarelo) e para o quinto (força de cisalhamento) não houve diferença entre os grupos genéticos. Através da análise exploratória dos dados foi possível reduzir a dimensionalidade do conjunto de informações e identificar diferenças entre grupos considerando o processo formado pelas combinações lineares das características mais associadas entre si (fatores). [Multivariate analysis of carcass and meat quality traits in sheep]. Abstract: Multivariate analyzes were used for evaluation of carcass and meat quality traits of lambs: Morada Nova (MN), Brazilian Somalis (BS), Santa Inês (SI) and ½Dorper x ½Morada Nova (F1). In the factor analysis, the first five factors extracted by principal components explained 80 % of total variance. The factor scores were used in the analysis of variance. The first factor is the process that represents the carcass morphometric traits, to slaughter weights and commercial cuts weights and loin eye area, and SI breed similar to genotype F1, but higher than the races SB and MN. This factor explained 52.65% of the total variance. The third (fat thickness and redness of meat) and the fourth factor (drip loss and cooking loss), SB genotype showed higher specificity, differing from other groups. For the second factor (pH measured 24 hours post mortem, lightness of meat and yellowness of meat) and the fifth factor (shear force) there was no difference between genotypes. Through exploratory analysis of the data was possible to reduce the dimensionality of the information and identify differences among genotypes considering the process formed by linear combinations of the traits more associated with each other (factors)

Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI

In the last few years, Artificial Intelligence (AI) has achieved a notable momentum that, if harnessed appropriately, may deliver the best of expectations over many application sectors across the field. For this to occur shortly in Machine Learning, the entire community stands in front of the barrier of explainability, an inherent problem of the latest techniques brought by sub-symbolism (e.g. ensembles or Deep Neural Networks) that were not present in the last hype of AI (namely, expert systems and rule based models). Paradigms underlying this problem fall within the so-called eXplainable AI (XAI) field, which is widely acknowledged as a crucial feature for the practical deployment of AI models. The overview presented in this article examines the existing literature and contributions already done in the field of XAI, including a prospect toward what is yet to be reached. For this purpose we summarize previous efforts made to define explainability in Machine Learning, establishing a novel definition of explainable Machine Learning that covers such prior conceptual propositions with a major focus on the audience for which the explainability is sought. Departing from this definition, we propose and discuss about a taxonomy of recent contributions related to the explainability of different Machine Learning models, including those aimed at explaining Deep Learning methods for which a second dedicated taxonomy is built and examined in detail. This critical literature analysis serves as the motivating background for a series of challenges faced by XAI, such as the interesting crossroads of data fusion and explainability. Our prospects lead toward the concept of Responsible Artificial Intelligence, namely, a methodology for the large-scale implementation of AI methods in real organizations with fairness, model explainability and accountability at its core. Our ultimate goal is to provide newcomers to the field of XAI with a thorough taxonomy that can serve as reference material in order to stimulate future research advances, but also to encourage experts and professionals from other disciplines to embrace the benefits of AI in their activity sectors, without any prior bias for its lack of interpretability

A microalgal-based preparation with synergistic cellulolytic and detoxifying action towards chemical-treated lignocellulose

High-temperature bioconversion of lignocellulose into fermentable sugars has drawn attention for efficient production of renewable chemicals and biofuels, because competing microbial activities are inhibited at elevated temperatures and thermostable cell wall degrading enzymes are superior to mesophilic enzymes. Here, we report on the development of a platform to produce four different thermostable cell wall degrading enzymes in the chloroplast of Chlamydomonas reinhardtii. The enzyme blend was composed of the cellobiohydrolase CBM3GH5 from C. saccharolyticus, the β-glucosidase celB from P. furiosus, the endoglucanase B and the endoxylanase XynA from T. neapolitana. In addition, transplastomic microalgae were engineered for the expression of phosphite dehydrogenase D from Pseudomonas stutzeri, allowing for growth in non-axenic media by selective phosphite nutrition. The cellulolytic blend composed of the glycoside hydrolase (GH) domain GH12/GH5/GH1 allowed the conversion of alkaline-treated lignocellulose into glucose with efficiencies ranging from 14% to 17% upon 48h of reaction and an enzyme loading of 0.05% (w/w). Hydrolysates from treated cellulosic materials with extracts of transgenic microalgae boosted both the biogas production by methanogenic bacteria and the mixotrophic growth of the oleaginous microalga Chlorella vulgaris. Notably, microalgal treatment suppressed the detrimental effect of inhibitory by-products released from the alkaline treatment of biomass, thus allowing for efficient assimilation of lignocellulose-derived sugars by C. vulgaris under mixotrophic growth