Analysis of Air Mean Temperature Anomalies by Using Horizontal Visibility Graphs.

The last decades have been successively warmer at the Earth's surface. An increasing interest in climate variability is appearing, and many research works have investigated the main effects on different climate variables. Some of them apply complex networks approaches to explore the spatial relation between distinct grid points or stations. In this work, the authors investigate whether topological properties change over several years. To this aim, we explore the application of the horizontal visibility graph (HVG) approach which maps a time series into a complex network. Data used in this study include a 60-year period of daily mean temperature anomalies in several stations over the Iberian Peninsula (Spain). Average degree, degree distribution exponent, and global clustering coefficient were analyzed. Interestingly, results show that they agree on a lack of significant trends, unlike annual mean values of anomalies, which present a characteristic upward trend. The main conclusions obtained are that complex networks structures and nonlinear features, such as weak correlations, appear not to be affected by rising temperatures derived from global climate conditions. Furthermore, different locations present a similar behavior and the intrinsic nature of these signals seems to be well described by network parameters.

A sliding window-based algorithm for faster transformation of time series into complex networks.

A new alternative method to approximate the Visibility Graph (VG) of a time series has been introduced here. It exploits the fact that most of the nodes in the resulting network are not connected to those that are far away from them. This means that the adjacency matrix is almost empty, and its nonzero values are close to the main diagonal. This new method is called Sliding Visibility Graph (SVG). Numerical tests have been performed for several time series, showing a time efficiency that scales linearly with the size of the series [O(N)], in contrast to the original VG that does so quadratically [O(N2)]. This fact is noticeably convenient when dealing with very large time series. The results obtained from the SVG of the studied time series have been compared to the exact values of the original VG. As expected, the SVG outcomes converge very rapidly to the desired ones, especially for random and stochastic series. Also, this method can be extended to the analysis of time series that evolve in real time, since it does not require the entire dataset to perform the analysis but a shorter segment of it. The length segment can remain constant, making possible a simple analysis as the series evolves in time.

Checking complex networks indicators in search of singular episodes of the photochemical smog.

A set of indicators derived from the analysis of complex networks have been introduced to identify singularities on a time series. To that end, the Visibility Graphs (VG) from three different signals related to photochemical smog (O3, NO2 concentration and temperature) have been computed. From the resulting complex network, the centrality parameters have been obtained and compared among them. Besides, they have been contrasted to two others that arise from a multifractal point of view, that have been widely used for singularity detection in many fields: the Hölder and singularity exponents (specially the first one of them). The outcomes show that the complex network indicators give equivalent results to those already tested, even exhibiting some advantages such as the unambiguity and the more selective results. This suggest a favorable position as supplementary sources of information when detecting singularities in several environmental variables, such as pollutant concentration or temperature.

Improving graph-based detection of singular events for photochemical smog agents.

Recently, a set of graph-based tools have been introduced for the identification of singular events of O3, NO2 and temperature time series, as well as description of their dynamics. These are based on the use of the Visibility Graphs (VG). In this work, an improvement of the original approach is proposed, being called Upside-Down Visibility Graph (UDVG). It adds the possibility of investigating the singular lowest episodes, instead of the highest. Results confirm the applicability of the new method for describing the multifractal nature of the underlying O3, NO2, and temperature. Asymmetries in the NO2 degree distribution are observed, possibly due to the interaction with different chemicals. Furthermore, a comparison of VG and UDVG has been performed and the outcomes show that they describe opposite subsets of the time series (low and high values) as expected. The combination of the results from the two networks is proposed and evaluated, with the aim of obtaining all the information at once. It turns out to be a more complete tool for singularity detection in photochemical time series, which could be a valuable asset for future research.

Can complex networks describe the urban and rural tropospheric O3 dynamics?

Tropospheric ozone (O3) time series have been converted into complex networks through the recent so-called Visibility Graph (VG), using the data from air quality stations located in the western part of Andalusia (Spain). The aim is to apply this novel method to differentiate the behavior between rural and urban regions when it comes to the ozone dynamics. To do so, some centrality parameters of the resulting complex networks have been investigated: the degree, betweenness and shortest path. Some of them are expected to corroborate previous works in order to support the use of this technique; while others to supply new information. Results coincide when describing the difference that tropospheric ozone exhibits seasonally and geographically. It is seen that ozone behavior is fractal, in accordance to previous works. Also, it has been demonstrated that this methodology is able to characterize the divergence encountered between measurements in urban environments and countryside. In addition to that, the promising outcomes of this technique support the use of complex networks for the study of air pollutants dynamics. Particularly, new nuances are offered such as the identification and description of singularities in the signal.

Evaluation of biological production of lactic acid in a synthetic medium and in Aloe vera (L.) Burm. f. processing by-products / Evaluation of biological production of lactic acid in a synthetic medium and in Aloe vera (L.) Burm. f. processing by-products / Avaliação da produção biológica de ácido lático em um meio sintético e no processamento de subprodutos de Aloe vera (L.) Burm. f.

This study evaluated lactic acid production through batch fermentation in a bioreactor with Thermoanaerobacter sp. strain USBA-018 and a chemically defined culture medium and with hydrolyzed pressed extract of Aloe vera peel (AHE). The strain USBA-018 fermented various sugars, but its primary end-product was L-lactic acid. Factors which influenced L- lactic acid production were pH, addition of yeast extract (YE) and manganese chloride. Under the most favorable growing conditions for the production of lactic acid, yield (Yp/s) increased from 0.66 to 0.96 g/g with a productivity (Qp) of 0.62 g.l-1.h and a maximum lactic acid concentration of 178 mM at 26 hours of fermentation. When AHE was used, 93.3 mM, or 0.175 g.l-1.h, was obtained. These results show the potential for transformation of sugars that strain USBA-018 offers, but additional studies are needed to find out if different strategies using AHE as carbon source can produce large enough quantities of lactic acid to allow AHE to become a low-cost alternative substrate.

Este estudio evaluó la producción de ácido láctico de la cepa de Thermoanaerobacter sp. USBA-018 en un biorreactor de fermentación por lotes, utilizando como medios de cultivo una formulación químicamente definida y un extracto prensado e hidrolizado de cáscara de Aloe vera (AHE). La cepa USBA-018 fermentó varios azúcares, pero su principal producto final fue L-ácido láctico. Los factores que influyeron en la producción de L-ácido láctico fueron pH, adición de extracto de levadura (YE) y de cloruro de manganeso. Bajo las condiciones más favorables de crecimiento para la producción de ácido láctico el rendimiento (Yp/s) aumentó de 0.66 a 0.96 g/g, con una productividad (Qp) de 0.62 g.l-1.h y una máxima concentración de ácido láctico de 178 mM a las 26 horas de fermentación. Cuando se usó AHE, se obtuvieron 93.3 mM, o 0.175 g.l-1.h. Estos resultados muestran el potencial de transformación de azúcares que ofrece la cepa USBA-018, pero se requieren estudios adicionales para determinar si diferentes estrategias de uso de AHE como fuente de carbono producen cantidades suficientemente grandes de ácido láctico como para permitir que el AHE se convierta en un sustrato alternativo de bajo costo.

Este estudo avaliou a produção de ácido lático por meio de fermentação descontinua em um biorreator com Thermoanaerobacter sp. cepa USBA-018 e um meio de cultura químicamente definido e com extrato hidrolisado de casca de Aloe vera (AHE). A cepa USBA-018 fermentou vários acucares, mas seu produto final primàrio foi L-ácido lático. Os fatores que influenciaram a produção de L-ácido lático foram o pH, adição de extrato de levedura (YE) e cloreto de manganès. Sob as condicoes de crescimento mais favoráveis para a produção de ácido lático, o rendimento (Yp/S) aumentou de 0,66 a 0,96 g/g com uma produtividade (Q) de 0,62 g.L4.h e um máximo de concentração de ácido lático de 178 mM em 26 horas de fermentação. Quando o AHE foi utilizado, se obteve 93,3 mM ou 0,175 g.L-1.h. Estes resultados mostram o potencial para transformação de acucares que a cepa USBA-018 oferece, entretanto estudos adicionais sáo necessários para descobrir se diferentes estrategias utilizando o AHE como fonte de carbonos podem produzir quantidades de ácido lático grandes o suficiente para permitir que AHE se converta em um substrato alternativo de baixo custo.