Method of making encapsulated solar cell modules

Electrical connections to solar cells in a module are made at the same time the cells are encapsulated for protection. The encapsulating material is embossed to facilitate the positioning of the cells during assembly

Preliminary results of accelerated exposure testing of solar cell system components

Plastic samples and solar cell sub modules were exposed to an accelerated outdoor environment in Arizona and an accelerated simulated environment in a cyclic ultraviolet exposure tester which included humidity exposure. These tests were for preliminary screening of materials suitable for use in the manufacture of solar cell modules which are to have a 20-year lifetime. The samples were exposed for various times up to six months, equivalent to a real time exposure of four years. Suitable materials were found to be FEP-A, FEP-C, PFA, acrylic, silicone compounds and adhesives and possibly parylene. The method of packaging the sub modules was also found to be important to their performance

Real time outdoor exposure testing of solar cell modules and component materials

Plastic samples, solar cell modules, and sub-modules were exposed at test sites in Florida, Arizona, Puerto Rico, and Cleveland, Ohio, in order to determine materials suitable for use in solar cell modules with a proposed 20-year lifetime. Various environments were encountered including subtropical, subtropical with a sea air atmosphere, desert, rain forest, normal urban, and urban-polluted. The samples were exposed for periods up to six months. Materials found not suitable were polyurethane, polyester, Kapton, Mylar, and UV-stabilized Lexan. Suitable materials were acrylic, FEP-A, and glass. The results of exposure of polyvinylidene fluoride were dependent on the specific formulation, but several types appear suitable. RTV silicone rubber (clear) appears to pick up and hold dirt both as a free film and as a potting medium for modules. The results indicate that dirt accumulation and cleanability are important factors in the selection of solar cell module covers and encapsulants

The Random Bit Complexity of Mobile Robots Scattering

We consider the problem of scattering $n$ robots in a two dimensional continuous space. As this problem is impossible to solve in a deterministic manner, all solutions must be probabilistic. We investigate the amount of randomness (that is, the number of random bits used by the robots) that is required to achieve scattering. We first prove that $n \log n$ random bits are necessary to scatter $n$ robots in any setting. Also, we give a sufficient condition for a scattering algorithm to be random bit optimal. As it turns out that previous solutions for scattering satisfy our condition, they are hence proved random bit optimal for the scattering problem. Then, we investigate the time complexity of scattering when strong multiplicity detection is not available. We prove that such algorithms cannot converge in constant time in the general case and in $o(\log \log n)$ rounds for random bits optimal scattering algorithms. However, we present a family of scattering algorithms that converge as fast as needed without using multiplicity detection. Also, we put forward a specific protocol of this family that is random bit optimal ($n \log n$ random bits are used) and time optimal ($\log \log n$ rounds are used). This improves the time complexity of previous results in the same setting by a $\log n$ factor. Aside from characterizing the random bit complexity of mobile robot scattering, our study also closes its time complexity gap with and without strong multiplicity detection (that is, $O(1)$ time complexity is only achievable when strong multiplicity detection is available, and it is possible to approach it as needed otherwise)

A non-linear and stochastic response surface method for Bayesian estimation of uncertainty in soil moisture simulation from a land surface model

International audienceThis study presents a simple and efficient scheme for Bayesian estimation of uncertainty in soil moisture simulation by a Land Surface Model (LSM). The scheme is assessed within a Monte Carlo (MC) simulation framework based on the Generalized Likelihood Uncertainty Estimation (GLUE) methodology. A primary limitation of using the GLUE method is the prohibitive computational burden imposed by uniform random sampling of the model's parameter distributions. Sampling is improved in the proposed scheme by stochastic modeling of the parameters' response surface that recognizes the non-linear deterministic behavior between soil moisture and land surface parameters. Uncertainty in soil moisture simulation (model output) is approximated through a Hermite polynomial chaos expansion of normal random variables that represent the model's parameter (model input) uncertainty. The unknown coefficients of the polynomial are calculated using limited number of model simulation runs. The calibrated polynomial is then used as a fast-running proxy to the slower-running LSM to predict the degree of representativeness of a randomly sampled model parameter set. An evaluation of the scheme's efficiency in sampling is made through comparison with the fully random MC sampling (the norm for GLUE) and the nearest-neighborhood sampling technique. The scheme was able to reduce computational burden of random MC sampling for GLUE in the ranges of 10%-70%. The scheme was also found to be about 10% more efficient than the nearest-neighborhood sampling method in predicting a sampled parameter set's degree of representativeness. The GLUE based on the proposed sampling scheme did not alter the essential features of the uncertainty structure in soil moisture simulation. The scheme can potentially make GLUE uncertainty estimation for any LSM more efficient as it does not impose any additional structural or distributional assumptions

A 10-Year Climatology of Amazonian Rainfall Derived from Passive Microwave Satellite Observations

In this study we present and describe a satellite-derived precipitation climatology over northern South America using a passive microwave technique, the Goddard Profiling Algorithm. A period of data slightly longer than 10 years is examined. The climatologies take the form of the mean estimated (adjusted) rainfall for a 10-year (+) period, with sub-divisions by month and meteorological season. For the six-year period 1992-1997, when two satellites were in operation, diurnal variability (to the extent it is discerned by four unequally spaced observations) is presented. We find an alternating pattern of morning and maxima stretching from the northeast (Atlantic coast) clear across the continent to the Pacific. The effects of topography, coastlines and geography (river valleys) on the rainfall patterns are clear. Interannual variability is examined by computing the deviations of yearly and warm season (DJF) rainfall from their respective long-term means. Interannual variability of the diurnal nature of the rainfall is presented, and the strong El Nino event of 1997-1998 is discussed

Multiregional Satellite Precipitation Products Evaluation over Complex Terrain

An extensive evaluation of nine global-scale high-resolution satellite-based rainfall (SBR) products is performed using a minimum of 6 years (within the period of 2000-13) of reference rainfall data derived from rain gauge networks in nine mountainous regions across the globe. The SBR products are compared to a recently released global reanalysis dataset from the European Centre for Medium-Range Weather Forecasts (ECMWF). The study areas include the eastern Italian Alps, the Swiss Alps, the western Black Sea of Turkey, the French Cévennes, the Peruvian Andes, the Colombian Andes, the Himalayas over Nepal, the Blue Nile in East Africa, Taiwan, and the U.S. Rocky Mountains. Evaluation is performed at annual, monthly, and daily time scales and 0.25° spatial resolution. The SBR datasets are based on the following retrieval algorithms: Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis (TMPA), the NOAA/Climate Prediction Center morphing technique (CMORPH), Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN), and Global Satellite Mapping of Precipitation (GSMaP). SBR products are categorized into those that include gauge adjustment versus unadjusted. Results show that performance of SBR is highly dependent on the rainfall variability. Many SBR products usually underestimate wet season and overestimate dry season precipitation. The performance of gauge adjustment to the SBR products varies by region and depends greatly on the representativeness of the rain gauge network

Detecting Genetic Isolation in Human Populations: A Study of European Language Minorities

The identification of isolation signatures is fundamental to better understand the genetic structure of human populations and to test the relations between cultural factors and genetic variation. However, with current approaches, it is not possible to distinguish between the consequences of long-term isolation and the effects of reduced sample size, selection and differential gene flow. To overcome these limitations, we have integrated the analysis of classical genetic diversity measures with a Bayesian method to estimate gene flow and have carried out simulations based on the coalescent. Combining these approaches, we first tested whether the relatively short history of cultural and geographical isolation of four "linguistic islands" of the Eastern Alps (Lessinia, Sauris, Sappada and Timau) had left detectable signatures in their genetic structure. We then compared our findings to previous studies of European population isolates. Finally, we explored the importance of demographic and cultural factors in shaping genetic diversity among the groups under study. A combination of small initial effective size and continued genetic isolation from surrounding populations seems to provide a coherent explanation for the diversity observed among Sauris, Sappada and Timau, which was found to be substantially greater than in other groups of European isolated populations. Simulations of micro-evolutionary scenarios indicate that ethnicity might have been important in increasing genetic diversity among these culturally related and spatially close populations. © 2013 Capocasa et al

Ethnic fragmentation and degree of urbanization strongly affect the discrimination power of Y-STR haplotypes in central Sahel

Y chromosome short tandem repeats (Y-STRs) are commonly used to identify male lineages for investigative and judicial purposes and could represent the only source of male-specific genetic information from unbalanced female-male mixtures. The Yfiler Plus multiplex, which includes twenty conventional and seven rapidly-mutating Y-STRs, represents the most discriminating patrilineal system commercially available to date. Over the past five years, this multiplex has been used to analyze several Eurasian populations, with a reported discrimination capacity (DC) approaching or corresponding to the highest possible value. However, despite the inclusion of rapidly mutating Y-STRs, extensive haplotype sharing was still reported for some African populations due to a number of different factors affecting the effective population size. In the present study, we analyzed 27 Y-STRs included in the Yfiler Plus multiplex and 82 Y-SNPs in central Sahel (northern Cameroon and western Chad), an African region characterized by a strong ethnic fragmentation and linguistic diversity. We evaluated the effects of population sub-structuring on genetic diversity by stratifying a sample composed of 431 males according to their ethnicity (44 different ethnic groups) and urbanization degree (four villages and four towns). Overall, we observed a low discrimination capacity (DC = 0.90), with 71 subjects (16.5 %) sharing 27 Y-STR haplotypes. Haplotype sharing was essentially limited to subjects with the same binary haplogroup, coming from the same location and belonging to the same ethnic group. Haplotype sharing was much higher in rural areas (average DC = 0.83) than urban settlements (average DC = 0.96) with a significant correlation between DC and census size (r = 0.89; p = 0.003). Notably, we found that genetic differentiation between villages from the same country (ΦST = 0.14) largely exceeded that found among countries (ΦST = 0.02). These findings have important implications for the choice of the appropriate reference population database to evaluate the statistical relevance of forensic Y-haplotype matches