Synthesis of Oligosaccharides Derived from Lactulose (OsLu) Using Soluble and Immobilized Aspergillus oryzae β-Galactosidase

β-Galactosidase from Aspergillus oryzae offers a high yield for the synthesis of oligosaccharides derived from lactulose (OsLu) by transgalactosylation. Oligosaccharides with degree of polymerization (DP) ≥ 3 have shown to possess higher in vitro bifidogenic effect than di- and tetrasaccharides. Thus, in this work, an optimization of reaction conditions affecting the specific selectivity of A. oryzae β-galactosidase for synthesis of OsLu has been carried out to enhance OsLu with DP ≥ 3 production. Assays with β-galactosidase immobilized onto a glutaraldehyde–agarose support were also carried out with the aim of making the process cost-effective and industrially viable. Optimal conditions with both soluble and immobilized enzyme for the synthesis of OsLu with DP ≥ 3 were 50 °C, pH 6.5, 450 g/L of lactulose, and 8 U/mL of enzyme, reaching yields of ca. 50% (w/v) of total OsLu and ca. 20% (w/v) of OsLu with DP 3, being 6′-galactosyl-lactulose the major one, after a short reaction time. Selective formation of disaccharides, however, was favored at 60 °C, pH 4.5, 450 g/L of lactulose and 8 U/mL of enzyme. Immobilization increased the enzymatic stability to temperature changes and allowed to reuse the enzyme. We can conclude that the use, under determined optimal conditions, of the A. oryzae β-galactosidase immobilized on a support of glutaraldehyde–agarose constitutes an efficient and cost-effective alternative to the use of soluble β-galactosidases for the synthesis of prebiotic OsLu mixturesThis work has been supported by projects AGL2014-53445-R from Ministerio de Economía y Competitividad; ALIBIRD-CM S-2013/ABI-2728 from Comunidad Autónoma de Madrid and COOPB20099 from CSI

A Spatially Enhanced Data‐Driven Multimodel to Improve Semiseasonal Groundwater Forecasts in the High Plains Aquifer, USA

The aim of this paper is to improve semiseasonal forecast of groundwater availability in response to climate variables, surface water availability, groundwater level variations, and human water management using a two‐step data‐driven modeling approach. First, we implement an ensemble of artificial neural networks (ANNs) for the 300 wells across the High Plains aquifer (USA). The modeling framework includes a method to choose the most relevant input variables and time lags; an assessment of the effect of exogenous variables on the predictive capabilities of models; and the estimation of the forecast skill based on the Nash‐Sutcliffe efficiency (NSE) index, the normalized root mean square error, and the coefficient of determination (R2). Then, for the ANNs with low‐ accuracy, a MultiModel Combination (MuMoC) based on a hybrid of ANN and an instance‐based learning method is applied. MuMoC uses forecasts from neighboring wells to improve the accuracy of ANNs. An exhaustive‐search optimization algorithm is employed to select the best neighboring wells based on the cross correlation and predictive accuracy criteria. The results show high average ANN forecasting skills across the aquifer (average NSE \u3e 0.9). Spatially distributed metrics of performance showed also higher error in areas of strong interaction between hydrometeorological forcings, irrigation intensity, and the aquifer. In those areas, the integration of the spatial information into MuMoC leads to an improvement of the model accuracy (NSE increased by 0.12), with peaks higher than 0.3 when the optimization objectives for selecting the neighbors were maximized.t

Extreme precipitation and extreme streamflow in the Dongjiang River Basin in southern China

International audienceExtreme hydro-meteorological events have become the focus of more and more studies in the last decade. Due to the complexity of the spatial pattern of changes in precipitation processes, it is still hard to establish a clear view of how precipitation has changed and how it will change in the future. In the present study, changes in extreme precipitation and streamflow processes in the Dongjiang River Basin in southern China are investigated. It was shown that little change is observed in annual extreme precipitation in terms of various indices, but some significant changes are found in the precipitation processes on a monthly basis. The result indicates that when detecting climate changes, besides annual indices, seasonal variations in extreme events should be considered as well. Despite of little change in annual extreme precipitation series, significant changes are detected in several annual extreme flood flow and low-flow series, mainly at the stations along the main channel of Dongjiang River, which are affected significantly by the operation of several major reservoirs. The result highlights the importance of evaluating the impacts of human activities in assessing the changes of extreme streamflows. In addition, three non-parametric methods that are not-commonly used by hydro-meteorology community, i.e., Kolmogorov?Smirnov test, Levene's test and quantile test, are introduced and assessed by Monte Carlo simulation in the present study to test for changes in the distribution, variance and the shift of tails of different groups of dataset. Monte Carlo simulation result shows that, while all three methods work well for detecting changes in two groups of data with large data size (e.g., over 200 points in each group) and big difference in distribution parameters (e.g., over 100% increase of scale parameter in Gamma distribution), none of them are powerful enough for small data sets (e.g., less than 100 points) and small distribution parameter difference (e.g., 50% increase of scale parameter in Gamma distribution)

Optimized Spectral Energy Distribution for Seyfert Galaxies

The temperature predicted by photoionization models for the Narrow Line Region of Seyfert 2 galaxies is lower than the value inferred from the observed [O III] {\lambda}4363A/{\lambda}5007A line ratio. We explore the possibility of considering a harder ionizing continuum than typically assumed. The spectral ionizing energy distribution, which can generate the observed {\lambda}4363A/{\lambda}5007A ratio, is characterized by a secondary continuum peak at 200 eV.Comment: 17 pages, 4 figures, accepted for publication in Revista Mexicana de Astronom\'ia y Astrof\'isic

Combining semi-distributed process-based and data-driven models in flow simulation: a case study of the Meuse river basin

While the United Nations Principles of Responsible Management Education (PRME) is a very positive development in the horizon of management education over the last decade, there are still many significant challenges for engaging the mind of the manager in ways that will foster the values of PRME and the UN Global Compact. Responsible management education must address three foundational challenges in business education if it is to actualize the aspirations of PRME: 1) it must confront the cognitional myth that knowing is like looking, 2) it must move beyond mere analysis to systems thinking, and 3) it must transition from a values-neutral stance to a values-driven stance. Using Developing Sustainable Strategies, an MBA practicum in the Sustainable Management Concentration at DePaul University’s Kellstadt Graduate School of Business, as a case study, this article identifies the ways in which Pragmatic Inquiry can addresses these challenges. The method of Pragmatic Inquiry prepares students to become responsible managers, to develop sustainable strategies, and to be creators of shared value. Built from the philosophical foundations of American pragmatism and Bernard Lonergan’s critical realism, Pragmatic Inquiry is an effective method and pedagogy for responsible management education. The final publication is available at http://link.springer.co

A Nonionic Alcohol Soluble Polymer Cathode Interlayer Enables Efficient Organic and Perovskite Solar Cells

The choice of interfacial materials and their properties play a critical role in determining solar cell performance and stability. For compatibility with roll-to-roll printing, it is desirable to develop stable cathode interface layers (CILs) that can be processed over the photoactive layer using orthogonal solvents. In this study, an n-type naphthalene diimide core and oligo (ethylene glycol) side-chain-based conjugated polymer is reported as a universal, efficient CIL for organic and perovskite photovoltaics. Besides good thermal stability and easy processing in alcohol/water, the new CIL is found to possess electron transport properties with an electrical conductivity of 2.3 × 10^{–6} S cm^{–1}, enabling its use as a CIL with a film thickness of up to ∼35(±2) nm. Utilizing the new CIL, 16% power conversion efficiency (PCE) is achieved for organic solar cells (OSCs) based on the PM6-Y6 photoactive layer (8.9% PCE for no CIL and 15.1% with state-of-the-art CIL, PDINO), and perovskite solar cells from methylammonium lead iodide yielded a PCE of 17.6%. Compared to the reference devices, the new CIL reduced trap-assisted carrier recombination and increased the built-in potential by 80 mV, simultaneously enhancing all photovoltaic parameters. Moreover, new CIL based devices had better photostability with no burn-in losses

Alternativas de establecimiento de praderas.

Se describen tecnologías de establecimiento de praderas en empresas ganaderas de la altillanura de los Llanos Orientales de Colombia, para intensificar la producción de carne y leche de los sistemas productivos. Se indican las fincas seleccionadas, sus características agroecológicas, las labores de establecimiento, preparación y siembra de praderas y los resultados obtenidos en términos de producción de forraje y composición botánica. Se evaluó la producción animal y se observó que la introducción y manejo adecuado de leguminosas de las praderas, aumenta los nutrientes de la dieta y mejora la ganancia de peso en los animalesPastos y forraje

Measurement of activity produced by low energy proton beam in metals using off-line PET imaging

Proceeding of: 2011 Nuclear Science Symposium and Medical Imaging Conference, Valencia, España, 23-29 October, 2011In this work, we investigate PET imaging with 68Ga and 66Ga after proton irradiation on a natural zinc foil. The nuclides 68Ga and 66Ga are ideally suited for off line PET monitoring of proton radiotherapy due to their beta decay halflives of 67.71(9) minutes and 9.49(3) hours, respectively, and suitable fl end point energy. The purpose of this work is to explore the feasibility of PET monitoring in hadrontherapy treatments, and to study how the amount of activity and the positron range affect the PET image reconstruction. Profiting from the low energy reaction threshold for production via (p,n) reactions, both 68Ga and 66Ga gallium isotopes have been produced by activation on a natural zinc target by a proton pencil beam. In this way, it is possible to create detailed patterns, such as the Derenzo inspired one employed here. The proton beam was produced by the 5 MV tandetron accelerator at CMAM in Madrid. The energy of this beam (up to 10 MeV) is similar to the residual energy of the protons used for therapy at the distal edge of their path. The activated target was imaged in an ARGUS small animal PETtCT scanner and reconstructed with a fully 3D iterative algorithm, with and without positron range corrections.This work was supported in part by Comunidad de Madrid (ARTEMIS S2009/DPI 1802), Spanish Ministry of Science and Innovation (grants FPA2010 17142 and ENTEPRASE, PSE 300000 2009 5), by European Regional Funds, by CDTI under the CENIT Programme (AMIT Project), UCM (grupos UCM, 910059) and by CPAN, CSPD 2007 [email protected]