Time dependent correlations in marine stratocumulus cloud base height records

The scaling ranges of time correlations in the cloud base height records of marine boundary layer stratocumulus are studied applying the Detrended Fluctuation Analysis statistical method. We have found that time dependent variations in the evolution of the $\alpha$ exponent reflect the diurnal dynamics of cloud base height fluctuations in the marine boundary layer. In general, a more stable structure of the boundary layer corresponds to a lower value of the $\alpha$ - indicator, i.e. larger anti-persistence, thus a set of fluctuations tending to induce a greater stability of the stratocumulus. In contrast, during periods of higher instability in the marine boundary, less anti-persistent (more persistent like) behavior of the system drags it out of equilibrium, corresponding to larger $\alpha$ values. From an analysis of the frequency spectrum, the stratocumulus base height evolution is found to be a non-stationary process with stationary increments. The occurrence of these statistics in cloud base height fluctuations suggests the usefulness of similar studies for the radiation transfer dynamics modeling.Comment: 12 pages, 6 figures; to appear in Int. J. Mod. Phys. C, Vol. 13, No. 2 (2002

Long term persistence in the sea surface temperature fluctuations

We study the temporal correlations in the sea surface temperature (SST) fluctuations around the seasonal mean values in the Atlantic and Pacific oceans. We apply a method that systematically overcome possible trends in the data. We find that the SST persistence, characterized by the correlation $C(s)$ of temperature fluctuations separated by a time period $s$, displays two different regimes. In the short-time regime which extends up to roughly 10 months, the temperature fluctuations display a nonstationary behavior for both oceans, while in the asymptotic regime it becomes stationary. The long term correlations decay as $C(s) \sim s^{-\gamma}$ with $\gamma \sim 0.4$ for both oceans which is different from $\gamma \sim 0.7$ found for atmospheric land temperature.Comment: 14 pages, 5 fiure

МЕТОД МАШИН ОПОРНЫХ ВЕКТОРОВ ДЛЯ ПРОГНОЗИРОВАНИЯ ПОКАЗАТЕЛЕЙ ИНВЕСТИЦИЙ

Possibilities of applying intelligent machine learning technique based on support vectors for predicting investment measures are considered in the article. The base features of support vector method over traditional econometric techniques for improving the forecast quality are described. Computer modeling results in terms of tuning support vector machine models developed with programming language Python for predicting some investment measures are shown.В статье рассматриваются возможности применения интеллектуального метода машинного обучения на основе опорных векторов для прогнозирования показателей инвестиций. Описываются основные преимущества метода над традиционными методами прогнозирования, что позволяет улучшать качество прогноза. Приводятся результаты компьютерных экспериментов по адаптации моделей на основе машин опорных векторов, реализованных с использованием языка программирования Python, к прогнозированию отдельных показателей инвестиций

Predictors of pathological hyperbilirubinemia in newborns

The article discusses the likely causes that can affect the degree of increase in the level of bilirubin in a newborn. The significance of such factors as infectious diseases and metabolic diseases of the mother is shownВ статье рассмотрены вероятные причины, которые могут влиять на степень повышения билирубина у новорожденного. Показана значимость таких факторов, как инфекционные заболевания и метаболические расстройства у матер

<i>Pseudomonas aeruginosa</i> AlgF is a protein-protein interaction mediator required for acetylation of the alginate exopolysaccharide

Enzymatic modifications of bacterial exopolysaccharides enhance immune evasion and persistence during infection. In the Gram-negative opportunistic pathogen Pseudomonas aeruginosa, acetylation of alginate reduces opsonic killing by phagocytes and improves reactive oxygen species scavenging. Although it is well-known that alginate acetylation in P. aeruginosa requires AlgI, AlgJ, AlgF, and AlgX, how these proteins coordinate polymer modification at a molecular level remains unclear. Here, we describe the structural characterization of AlgF and its protein interaction network. We characterize direct interactions between AlgF and both AlgJ and AlgX in vitro, and demonstrate an association between AlgF and AlgX, as well as AlgJ and AlgI, in P. aeruginosa. We determine that AlgF does not exhibit acetylesterase activity and is unable to bind to polymannuronate in vitro. Therefore, we propose that AlgF functions to mediate protein-protein interactions between alginate acetylation enzymes, forming the periplasmic AlgJFXK (AlgJ-AlgF-AlgX-AlgK) acetylation and export complex required for robust biofilm formation.</p

Structural and biochemical characterization of the exopolysaccharide deacetylase Agd3 required for Aspergillus fumigatus biofilm formation

The exopolysaccharide galactosaminogalactan (GAG) is an important virulence factor of the fungal pathogen Aspergillus fumigatus. Deletion of a gene encoding a putative deacetylase, Agd3, leads to defects in GAG deacetylation, biofilm formation, and virulence. Here, we show that Agd3 deacetylates GAG in a metal-dependent manner, and is the founding member of carbohydrate esterase family CE18. The active site is formed by four catalytic motifs that are essential for activity. The structure of Agd3 includes an elongated substrate-binding cleft formed by a carbohydrate binding module (CBM) that is the founding member of CBM family 87. Agd3 homologues are encoded in previously unidentified putative bacterial exopolysaccharide biosynthetic operons and in other fungal genomes. The exopolysaccharide galactosaminogalactan (GAG) is an important virulence factor of the fungal pathogen Aspergillus fumigatus. Here, the authors study an A. fumigatus enzyme that deacetylates GAG in a metal-dependent manner and constitutes a founding member of a new carbohydrate esterase family.Bio-organic Synthesi

Stone Age Yersinia pestis genomes shed light on the early evolution, diversity, and ecology of plague

The bacterial pathogenYersinia pestisgave rise to devastating outbreaks throughouthuman history, and ancient DNA evidence has shown it afflicted human populations asfar back as the Neolithic.Y. pestisgenomes recovered from the Eurasian Late Neolithic/Early Bronze Age (LNBA) period have uncovered key evolutionary steps that led to itsemergence from aYersinia pseudotuberculosis-like progenitor; however, the number ofreconstructed LNBA genomes are too few to explore its diversity during this criticalperiod of development. Here, we present 17Y. pestisgenomes dating to 5,000 to 2,500y BP from a wide geographic expanse across Eurasia. This increased dataset enabled usto explore correlations between temporal, geographical, and genetic distance. Ourresults suggest a nonflea-adapted and potentially extinct single lineage that persistedover millennia without significant parallel diversification, accompanied by rapid dis-persal across continents throughout this period, a trend not observed in other pathogensfor which ancient genomes are available. A stepwise pattern of gene loss provides fur-ther clues on its early evolution and potential adaptation. We also discover the presenceof theflea-adapted form ofY. pestisin Bronze Age Iberia, previously only identified inin the Caucasus and the Volga regions, suggesting a much wider geographic spread ofthis form ofY. pestis. Together, these data reveal the dynamic nature of plague’s forma-tive years in terms of its early evolution and ecology