Влияние состояния TiO2 на окислительную делигнификацию древесины осины и соломы пшеницы

The influence of preparation methods on structural characteristics of TiO2 catalysts was studied by the XRD, SEM, BET, DTA-DSC, FTIR techniques. Catalytic activity of obtained titanium dioxide samples was compared in reaction of oxidative delignification of aspen wood and wheat straw by hydrogen peroxide in acetic acid- water medium. The use of titanium dioxide in rutile modification allows to produce a cellulose product with lower content of a residual lignin, as compared to TiO2 in anatase modification. The increase of surface area of the TiO2 catalyst reduces its activity in wood and wheat straw delignificationМетодами РФА, СЭМ, БЭТ, ДТА-ДСК, ИКС изучено влияние способов получения катализаторов TiO2 на их структурные характеристики. Сопоставлена каталитическая активность полученных образцов диоксида титана в реакции окислительной делигнификации древесины осины и соломы пшеницы пероксидом водорода в среде «уксусная кислота–вода». Использование диоксида титана в модификации рутил позволяет получить целлюлозный продукт с более низким содержанием остаточного лигнина, чем при использовании TiO2 в модификации анатаз. Увеличение удельной поверхности катализатора приводит к уменьшению степени делигнификации древесины осины и соломы пшениц

A Novel Sparse Graphical Approach for Multimodal Brain Connectivity Inference

International audienceDespite the clear potential benefits of combining fMRI and diffusion MRI in learning the neural pathways that underlie brain functions, little methodological progress has been made in this direction. In this paper, we propose a novel multimodal integration approach based on sparse Gaussian graphical model for estimating brain connectivity. Casting functional connectivity estimation as a sparse inverse covariance learning problem, we adapt the level of sparse penalization on each connection based on its anatomical capacity for functional interactions. Functional connections with little anatomical support are thus more heavily penalized. For validation, we showed on real data collected from a cohort of 60 subjects that additionally modeling anatomical capacity significantly increases subject consistency in the detected connection patterns. Moreover, we demonstrated that incorporating a connectivity prior learned with our multimodal connectivity estimation approach improves activation detection

Sources of experimental errors in the observation of nanoscale magnetism

It has been recently reported that some non-magnetic materials in bulk state, exhibit magnetic behavior at the nanscale due to surface and size effects. The experimental observation of these effects is based on the measurement of very small magnetic signals. Thus, some spurious effects that are not critical for bulk materials with large magnetic signals may become important when measuring small signals (typically below 0.0001 emu). Here, we summarize some sources of these small magnetic signals that should be considered when studying this new nanomagnetismComment: 16 pages, 10 figure

Effective connectivity reveals strategy differences in an expert calculator

Mathematical reasoning is a core component of cognition and the study of experts defines the upper limits of human cognitive abilities, which is why we are fascinated by peak performers, such as chess masters and mental calculators. Here, we investigated the neural bases of calendrical skills, i.e. the ability to rapidly identify the weekday of a particular date, in a gifted mental calculator who does not fall in the autistic spectrum, using functional MRI. Graph-based mapping of effective connectivity, but not univariate analysis, revealed distinct anatomical location of “cortical hubs” supporting the processing of well-practiced close dates and less-practiced remote dates: the former engaged predominantly occipital and medial temporal areas, whereas the latter were associated mainly with prefrontal, orbitofrontal and anterior cingulate connectivity. These results point to the effect of extensive practice on the development of expertise and long term working memory, and demonstrate the role of frontal networks in supporting performance on less practiced calculations, which incur additional processing demands. Through the example of calendrical skills, our results demonstrate that the ability to perform complex calculations is initially supported by extensive attentional and strategic resources, which, as expertise develops, are gradually replaced by access to long term working memory for familiar material

Ecology and abundance of zooplankton in Karanja reservoir

The present work aims to study the Zooplankton seasonal distribution and diversity in Karanja reservoir, Bidar district for the period of two years from October 2001 to September 2003. We have recorded 36 species of which, 15 species belongs to rotifera, 11 species belongs to cladocera, nine species belongs to copepoda and ostracoda three species. Among zooplankton, particularly rotifera was the dominant group throughout the study period and highest count was recorded in the month of March 2003. Cluster analysis was also revealed by dendrogram and Shannon diversity index is also presented. Zooplankton community is also correlated with physicochemical parameters

Seasonal water level fluctuations: Implications for reservoir limnology and management

With the purpose of finding out whether seasonal water level fluctuations could affect water quality in a reservoir subjected to those changes, trends in environmental variables and in phytoplankton and zooplankton assemblages were analysed. The reservoir’s hydrological cycle was characterized by three regimes. The maximum level phase lasted from January to the beginning of June, the emptying phase existed between mid-June to the beginning of September and the minimum level phase lasted from mid-September to the beginning of the first autumn/winter rain events. The highest values of total phosphorus, soluble reactive phosphorus, nitrate, water colour and chlorophyll a were found during the minimum level phase. The phytoplankton assemblage was dominated by taxa typical of meso-eutrophic environments during the emptying and minimum level phases. However, during the maximum level phase, taxa generally found in more oligotrophic systems were observed here also. Similar to other disturbed systems, the zooplankton assemblage was dominated by Rotifera, except in summer and autumn when the cladoceran Ceriodaphnia quadrangula and/or the copepod Tropocyclops prasinus became dominant. Although those shifts seem to be related to water level variations, further research is needed to evaluate to what extent they might also be induced by other seasonal factors acting independently of water fluctuations. Based upon the obtained data, suggestions for reservoir management are proposed

Fast reproducible identification and large-scale databasing of individual functional cognitive networks

<p>Abstract</p> <p>Background</p> <p>Although cognitive processes such as reading and calculation are associated with reproducible cerebral networks, inter-individual variability is considerable. Understanding the origins of this variability will require the elaboration of large multimodal databases compiling behavioral, anatomical, genetic and functional neuroimaging data over hundreds of subjects. With this goal in mind, we designed a simple and fast acquisition procedure based on a 5-minute functional magnetic resonance imaging (fMRI) sequence that can be run as easily and as systematically as an anatomical scan, and is therefore used in every subject undergoing fMRI in our laboratory. This protocol captures the cerebral bases of auditory and visual perception, motor actions, reading, language comprehension and mental calculation at an individual level.</p> <p>Results</p> <p>81 subjects were successfully scanned. Before describing inter-individual variability, we demonstrated in the present study the reliability of individual functional data obtained with this short protocol. Considering the anatomical variability, we then needed to correctly describe individual functional networks in a voxel-free space. We applied then non-voxel based methods that automatically extract main features of individual patterns of activation: group analyses performed on these individual data not only converge to those reported with a more conventional voxel-based random effect analysis, but also keep information concerning variance in location and degrees of activation across subjects.</p> <p>Conclusion</p> <p>This collection of individual fMRI data will help to describe the cerebral inter-subject variability of the correlates of some language, calculation and sensorimotor tasks. In association with demographic, anatomical, behavioral and genetic data, this protocol will serve as the cornerstone to establish a hybrid database of hundreds of subjects suitable to study the range and causes of variation in the cerebral bases of numerous mental processes.</p

The 2014–2015 eruption of Fogo volcano: Geodetic modeling of Sentinel-1 TOPS interferometry

After 20 years of quiescence, Fogo volcano erupted in November 2014. The eruption produced fast-moving lava flows that traveled for several kilometers and destroyed two villages. This event represents the first episode of significant surface deformation imaged by the new European Space Agency's Sentinel-1 satellite in its standard acquisition mode, Terrain Observation by Progressive Scans (TOPS), which differs from that of previous synthetic aperture radar (SAR) missions. We perform a Bayesian inversion of Sentinel-1 TOPS SAR interferograms spanning the eruption and accurately account for variations in the TOPS line-of-sight vector when modeling displacements. Our results show that magma ascended beneath the Pico do Fogo cone and then moved laterally toward its southwestern flank, where the eruptive fissure opened. This study provides important insights into the inner workings of Fogo volcano and shows the potential of Sentinel-1 TOPS interferometry for geophysical (e.g., volcano monitoring) applications