Consortia Focused on Photovoltaic R&D, Manufacturing, and Testing: A Review of Existing Models and Structures

As the U.S. Department of Energy\u27s (DOE\u27s) Solar Energy Technologies Program prepares to initiate a new cost-shared research and development (R&D) effort on photovoltaic (PV) manufacturing, it is useful to review the experience to date with consortia focused on PV R&D, manufacturing, and testing. Information was gathered for this report by conducting interviews and accessing Web sites of 14 U.S. consortia and four European consortia, each with either a primary focus on or an emerging interest in PV technology R&D, manufacturing, or testing. Additional input was collected from several workshops held by the DOE and National Academy of Sciences (NAS) in 2009, which examined the practical steps -- including public-private partnerships and policy support -- necessary to enhance the United States\u27 capacity to competitively manufacture photovoltaics. This report categorizes the 18 consortia into three groups: university-led consortia, industry-led consortia, and manufacturing and testing facilities consortia. The first section summarizes the organizations within the different categories, with a particular focus on the key benefits and challenges for each grouping. The second section provides a more detailed overview of each consortium, including the origins, goals, organization, membership, funding sources, and key contacts. This survey is a useful resource for stakeholders interested in PV manufacturing R&D, but should not imply endorsement of any of these groups

Basic Forest Cover Mapping Using Digitized Remote Sensor Data and Automatic Data Processing Techniques

Increasing demands on the forest resource will necessitate increasingly more intensive management in the future. In order to achieve this goal, reliable and timely information over large geographic areas will be required. Remote sensing techniques offer much potential for the procurement of such information. This research, then, was pointed toward study of that potential. Four objectives were established as follows: 1) to determine the optimum number of the available twelve multispectral scanner (MSS) wavelength bands to use for forest cover mapping with automatic data processing (ADP) techniques; 2) to determine the current capability to map basic forest cover using MSS data and ADP techniques; 3) to determine the relative utility, to forest cover mapping, of the four spectral regions available in the twelve-channel MSS data (i.e. visible, and near, middle and thermal infrared); and 4) to compare the accuracy of digitized color infrared photography with that of MSS data for forest cover mapping using ADP techniques. In attaining the first objective, statistics defining the six cover type classes of interest (deciduous forest, coniferous forest, water, forage, corn, and soybeans) were calculated and used by the computer as a basis for the selection of best wavelength band combinations ranging in size from one through ten wavelength bands each. With the spectral information contained in each of these combinations, and with all twelve channels, the entire test area was classified into the six defined classes, using the LARSYS programs. Tests of the computer\u27s performance indicated that the use of five wavelength bands would fulfill the dual requirements of adequate accuracy and moderate computer time. In fulfilling the second objective, the automatically selected best combination of five channels (one each from the green and red visible wavelengths, and the near, middle and thermal infrared wavelengths) produced classification accuracies in excess of 90 percent for deciduous and coniferous forest. When these two classes were grouped, the accuracy for combined forest was in excess of 95 percent. The use of all twelve channels caused only a slight increase in overall accuracy. In satisfying the third objective, the LARSYS feature selection processor was allowed to consider wavelength bands constituting only various subsets of the four spectral regions. On this basis, it selected a number of five-channel combinations. Classifications performed by these various channel combinations indicate that the visible wavelengths are sufficiently accurate for classifying combined forest, but inadequate for differentiating between deciduous and coniferous forest. The infrared channels separated the two forest classes with reasonable accuracy, but allowed confusion between forest and the agricultural classes. The deletion of either the near or the middle infrared individually, did not reduce accuracies, but, when both were deleted, accuracies dropped drastically. The deletion of the thermal infrared had little effect on forest cover mapping but did allow considerable confusion among the agricultural cover types. These results indicate that the thermal infrared is desirable, but not necessary, for basic forest cover mapping, and that accurate classification of deciduous and coniferous forest cover can be achieved with the visible plus either the near or middle infrared spectral regions. To meet the fourth objective, small-scale color infrared photography, acquired the same day over the test site, was color separated, digitized in three wavelength bands and, automatically classified. In general, the digitized photography was inadequate for automatic forest cover mapping and compared poorly to the MSS data results when similar wavelength bands were used. These results were apparently caused by the narrower dynamic range, poorer spectral resolution, and uneven illumination (due to vignetting and the anti-solar point) of the photographic data

Global, Regional, and National Life Expectancy, All-Cause Mortality, and Cause-Specific Mortality for 249 Causes of Death, 1980-2015: A Systematic Analysis for the Global Burden of Disease Study 2015

Background Improving survival and extending the longevity of life for all populations requires timely, robust evidence on local mortality levels and trends. The Global Burden of Disease 2015 Study (GBD 2015) provides a comprehensive assessment of all-cause and cause-specific mortality for 249 causes in 195 countries and territories from 1980 to 2015. These results informed an in-depth investigation of observed and expected mortality patterns based on sociodemographic measures. Methods We estimated all-cause mortality by age, sex, geography, and year using an improved analytical approach originally developed for GBD 2013 and GBD 2010. Improvements included refinements to the estimation of child and adult mortality and corresponding uncertainty, parameter selection for under-5 mortality synthesis by spatiotemporal Gaussian process regression, and sibling history data processing. We also expanded the database of vital registration, survey, and census data to 14 294 geography-year datapoints. For GBD 2015, eight causes, including Ebola virus disease, were added to the previous GBD cause list for mortality. We used six modelling approaches to assess cause-specific mortality, with the Cause of Death Ensemble Model (CODEm) generating estimates for most causes. We used a series of novel analyses to systematically quantify the drivers of trends in mortality across geographies. First, we assessed observed and expected levels and trends of cause-specific mortality as they relate to the Socio-demographic Index (SDI), a summary indicator derived from measures of income per capita, educational attainment, and fertility. Second, we examined factors affecting total mortality patterns through a series of counterfactual scenarios, testing the magnitude by which population growth, population age structures, and epidemiological changes contributed to shifts in mortality. Finally, we attributed changes in life expectancy to changes in cause of death. We documented each step of the GBD 2015 estimation processes, as well as data sources, in accordance with Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER). Findings Globally, life expectancy from birth increased from 61.7 years (95% uncertainty interval 61.4-61.9) in 1980 to 71.8 years (71.5-72.2) in 2015. Several countries in sub-Saharan Africa had very large gains in life expectancy from 2005 to 2015, rebounding from an era of exceedingly high loss of life due to HIV/AIDS. At the same time, many geographies saw life expectancy stagnate or decline, particularly for men and in countries with rising mortality from war or interpersonal violence. From 2005 to 2015, male life expectancy in Syria dropped by 11.3 years (3.7-17.4), to 62.6 years (56.5-70.2). Total deaths increased by 4.1% (2.6-5.6) from 2005 to 2015, rising to 55.8 million (54.9 million to 56.6 million) in 2015, but age-standardised death rates fell by 17.0% (15.8-18.1) during this time, underscoring changes in population growth and shifts in global age structures. The result was similar for non-communicable diseases (NCDs), with total deaths from these causes increasing by 14.1% (12.6-16.0) to 39.8 million (39.2 million to 40.5 million) in 2015, whereas age-standardised rates decreased by 13.1% (11.9-14.3). Globally, this mortality pattern emerged for several NCDs, including several types of cancer, ischaemic heart disease, cirrhosis, and Alzheimer\u27s disease and other dementias. By contrast, both total deaths and age-standardised death rates due to communicable, maternal, neonatal, and nutritional conditions significantly declined from 2005 to 2015, gains largely attributable to decreases in mortality rates due to HIV/AIDS (42.1%, 39.1-44.6), malaria (43.1%, 34.7-51.8), neonatal preterm birth complications (29.8%, 24.8-34.9), and maternal disorders (29.1%, 19.3-37.1). Progress was slower for several causes, such as lower respiratory infections and nutritional deficiencies, whereas deaths increased for others, including dengue and drug use disorders. Age-standardised death rates due to injuries significantly declined from 2005 to 2015, yet interpersonal violence and war claimed increasingly more lives in some regions, particularly in the Middle East. In 2015, rotaviral enteritis (rotavirus) was the leading cause of under-5 deaths due to diarrhoea (146 000 deaths, 118 000-183 000) and pneumococcal pneumonia was the leading cause of under-5 deaths due to lower respiratory infections (393 000 deaths, 228 000-532 000), although pathogen-specific mortality varied by region. Globally, the effects of population growth, ageing, and changes in age-standardised death rates substantially differed by cause. Our analyses on the expected associations between cause-specific mortality and SDI show the regular shifts in cause of death composition and population age structure with rising SDI. Country patterns of premature mortality (measured as years of life lost [YLLs]) and how they differ from the level expected on the basis of SDI alone revealed distinct but highly heterogeneous patterns by region and country or territory. Ischaemic heart disease, stroke, and diabetes were among the leading causes of YLLs in most regions, but in many cases, intraregional results sharply diverged for ratios of observed and expected YLLs based on SDI. Communicable, maternal, neonatal, and nutritional diseases caused the most YLLs throughout sub-Saharan Africa, with observed YLLs far exceeding expected YLLs for countries in which malaria or HIV/AIDS remained the leading causes of early death. Interpretation At the global scale, age-specific mortality has steadily improved over the past 35 years; this pattern of general progress continued in the past decade. Progress has been faster in most countries than expected on the basis of development measured by the SDI. Against this background of progress, some countries have seen falls in life expectancy, and age-standardised death rates for some causes are increasing. Despite progress in reducing age-standardised death rates, population growth and ageing mean that the number of deaths from most non-communicable causes are increasing in most countries, putting increased demands on health systems. Copyright (C) The Author(s). Published by Elsevier Ltd

A haplotype-resolved chromosome-scale genome for Quercus rubra L. provides insights into the genetics of adaptive traits for red oak species

Northern red oak (Quercus rubra L.) is an ecologically and economically important forest tree native to North America. We present a chromosome-scale genome of Q. rubra generated by the combination of PacBio sequences and chromatin conformation capture (Hi-C) scaffolding. This is the first reference genome from the red oak clade (section Lobatae). The Q. rubra assembly spans 739 Mb with 95.27% of the genome in 12 chromosomes and 33,333 protein-coding genes. Comparisons to the genomes of Quercus lobata and Quercus mongolica revealed high collinearity, with intrachromosomal structural variants present. Orthologous gene family analysis with other tree species revealed that gene families associated with defense response were expanding and contracting simultaneously across the Q. rubra genome. Quercus rubra had the most CC-NBS-LRR and TIR-NBS-LRR resistance genes out of the 9 species analyzed. Terpene synthase gene family comparisons further reveal tandem gene duplications in TPS-b subfamily, similar to Quercus robur. Phylogenetic analysis also identified 4 subfamilies of the IGT/LAZY gene family in Q. rubra important for plant structure. Single major QTL regions were identified for vegetative bud break and marcescence, which contain candidate genes for further research, including a putative ortholog of the circadian clock constituent cryptochrome (CRY2) and 8 tandemly duplicated genes for serine protease inhibitors, respectively. Genome–environment associations across natural populations identified candidate abiotic stress tolerance genes and predicted performance in a common garden. This high-quality red oak genome represents an essential resource to the oak genomic community, which will expedite comparative genomics and biological studies in Quercus species

Single hadron response measurement and calorimeter jet energy scale uncertainty with the ATLAS detector at the LHC

The uncertainty on the calorimeter energy response to jets of particles is derived for the ATLAS experiment at the Large Hadron Collider (LHC). First, the calorimeter response to single isolated charged hadrons is measured and compared to the Monte Carlo simulation using proton-proton collisions at centre-of-mass energies of sqrt(s) = 900 GeV and 7 TeV collected during 2009 and 2010. Then, using the decay of K_s and Lambda particles, the calorimeter response to specific types of particles (positively and negatively charged pions, protons, and anti-protons) is measured and compared to the Monte Carlo predictions. Finally, the jet energy scale uncertainty is determined by propagating the response uncertainty for single charged and neutral particles to jets. The response uncertainty is 2-5% for central isolated hadrons and 1-3% for the final calorimeter jet energy scale.Comment: 24 pages plus author list (36 pages total), 23 figures, 1 table, submitted to European Physical Journal