40 research outputs found

    EFFECT OF MULTI-WALLED CARBON NANOTUBES ON THE STABILITY OF DYE SENSITIZED SOLAR CELLS

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    We report the improvement of the operational stability of dye-sensitized solar cells (DSSCs) by incorporating multi-wall carbon nanotubes (MWCNTs) in conventional nanostructured semiconducting TiO2 photoanodes. DSSCs were prepared by adding various concentrations of MWCNTs (up to 1.0% wt.) to TiO2 anatase nanoparticles. Optimization of MWCNT concentration leads to photoconversion efficiency as high as 4.1% as opposed to 3.7% for pure TiO2 photoanodes. The performance of the solar cells was measured for 10 consecutive days of continuous ambient light exposure. MWCNT addition results in the decrease of efficiency from 4.1% to 3.7%, while a decrease from 3.7% to 2.4% was recorded in pure TiO2 photoanodes. These results are encouraging toward the commercial exploitation of DSSCs

    Gap-filling of daily streamflow time series using Direct Sampling in various hydroclimatic settings

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    Complete hydrological time series are necessary for water resources management and modeling. This can be challenging in data scarce environments where data gaps are ubiquitous. In many applications, repetitive gaps can have unfortunate consequences including ineffective model calibration, unreliable timing of peak flows, and biased statistics. Here, Direct Sampling (DS) is used as a non-parametric stochastic method for infilling gaps in daily streamflow records. A thorough gap-filling framework including the selection of predictor stations and the optimization of the DS parameters is developed and applied to data collected in the Volta River basin, West Africa. Various synthetic missing data scenarios are developed to assess the performance of the method, followed by a real-case application to the existing gaps in the flow records. The contribution of this study includes the assessment of the method for different climatic zones and hydrological regimes and for different upstream-downstream relations among the gauging stations used for gap filling. Tested in various missing data conditions, the method allows a precise and reliable simulation of the missing data by using the data patterns available in other stations as predictor variables. The developed gap-filling framework is transferable to other hydrological applications, and it is promising for environmental modeling.Accepted Author ManuscriptWater Resource

    Explicit Serre weights for GL_2 via Kummer theory

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    We give an explicit formulation of the weight part of Serre's conjecture for GL_2 using Kummer theory. This avoids any reference to p-adic Hodge theory. The key inputs are a description of the reduction modulo p of crystalline extensions in terms of certain "G_K-Artin-Scheier cocycles" and a result of Abrashkin which describes these cocycles in terms of Kummer theory. An alternative explicit formulation in terms of local class field theory was previously given by Dembele-Diamond-Roberts in the unramified case and by the second author in general. We show that the description of Dembele-Diamond-Roberts can be recovered directly from ours using the explicit reciprocity laws of Brueckner-Shaferevich-Vostokov. These calculations illustrate how our use of Kummer theory eliminates certain combinatorial complications appearing in these two papers

    Explicit Serre weights for two-dimensional Galois representations

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    We prove the explicit version of the Buzzard–Diamond–Jarvis conjecture formulated by Dembele et al. (Serre weights and wild ramification in two-dimensional Galois representations, Preprint (2016), arXiv:1603.07708 [math.NT]). More precisely, we prove that it is equivalent to the original Buzzard–Diamond–Jarvis conjecture, which was proved for odd primes (under a mild Taylor–Wiles hypothesis) in earlier work of the third author and coauthors

    Africa’s Developmental Impasse: Some Perspectives and Recommendations

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    Africa is among the “poorest” regions of the world. The reality is thatAfrica is not poor but rather impoverished. This impoverishment datesback to the dawn of capitalism when slavery was one of the key elementsof capitalism’s “original accumulation”, as demonstrated par Karl Marxin The Capital.Colonial administration replaced slavery as from the 19th Century withthe occupation of Africa by Western powers. This has led to a systematiclooting of its natural resources and the exploitation of its cheap labourwhich served to industrialise Western countries.Thus, slavery and colonisation constituted the main causes of Africa’simpoverishment. With its accession to independence from the 1960s,one may have thought that looting Africa would have come to an endand its development stepped up. It was the contrary that occurredbecause in many countries, foreign domination had been reinforced inconnivance with the new African leaders.The failure of the neo-colonial management of African countries wasillustrated by the external debt crisis which started from the end of the1970s and led to the World Bank and IMF’s intervention. Theseinstitutions forced upon African countries the notoriously sadadjustment programmes which contributed to worsening the crisis intheir economies, taking poverty to an unprecedented level.The international financial crisis that occurred in 2008 illustrated thefailure of market fundamentalism of which adjustment programmes arethe forerunners. This crisis which has shaken the very bases of thecapitalistic system affords African leaders and thinkers the opportunityto break loose of the neoliberal yoke and explore a development paththat is more in tune with Africa. The author underscores that such apath should be non-capitalistic because the heavy toll that Africa haspaid since the birth of capitalism until now is a proof that the capitalisticdevelopment model is bound to fail

    Improving the Predictive Skill of a Distributed Hydrological Model by Calibration on Spatial Patterns With Multiple Satellite Data Sets

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    Hydrological model calibration combining Earth observations and in situ measurements is a promising solution to overcome the limitations of the traditional streamflow-only calibration. However, combining multiple data sources in model calibration requires a meaningful integration of the data sets, which should harness their most reliable contents to avoid accumulation of their uncertainties and mislead the parameter estimation procedure. This study analyzes the improvement of model parameter selection by using only the spatial patterns of satellite remote sensing data, thereby ignoring their absolute values. Although satellite products are characterized by uncertainties, their most reliable key feature is the representation of spatial patterns, which is a unique and relevant source of information for distributed hydrological models. We propose a novel multivariate calibration framework exploiting spatial patterns and simultaneously incorporating streamflow and three satellite products (i.e., Global Land Evaporation Amsterdam Model [GLEAM] evaporation, European Space Agency Climate Change Initiative [ESA CCI] soil moisture, and Gravity Recovery and Climate Experiment [GRACE] terrestrial water storage). The Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature data set is used for model evaluation. A bias-insensitive and multicomponent spatial pattern matching metric is developed to formulate a multiobjective function. The proposed multivariate calibration framework is tested with the mesoscale Hydrologic Model (mHM) and applied to the poorly gauged Volta River basin located in a predominantly semiarid climate in West Africa. Results of the multivariate calibration show that the decrease in performance for streamflow (−7%) and terrestrial water storage (−6%) is counterbalanced with an increase in performance for soil moisture (+105%) and evaporation (+26%). These results demonstrate that there are benefits in using satellite data sets, when suitably integrated in a robust model parametrization scheme.Water Resource
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