Lambda production in central Pb+Pb collisions at CERN-SPS energies

In this paper we present recent results from the NA49 experiment for $\Lambda$ and $\bar{\Lambda}$ hyperons produced in central Pb+Pb collisions at 40, 80 and 158 A$\cdot$GeV. Transverse mass spectra and rapidity distributions for $\Lambda$ are shown for all three energies. The shape of the rapidity distribution becomes flatter with increasing beam energy. The multiplicities at mid-rapidity as well as the total yields are studied as a function of collision energy including AGS measurements. The ratio $\Lambda/\pi$ at mid-rapidity and in 4$\pi$ has a maximum around 40 A$\cdot$GeV. In addition, $\bar{\Lambda}$ rapidity distributions have been measured at 40 and 80 A$\cdot$GeV, which allows to study the $\bar{\Lambda}$/$\Lambda$ ratio.Comment: SQM proceedings. J. Phys. G: Nucl. Part. Phys.: submitte

Strangeness from 20 AGeV to 158 AGeV

New results from the energy scan programme of NA49, in particular kaon production at 30 AGeV and phi production at 40 and 80 AGeV are presented. The K+/pi+ ratio shows a pronounced maximum at 30 AGeV; the kaon slope parameters are constant at SPS energies. Both findings support the scenario of a phase transition at about 30 AGeV beam energy. The phi/pi ratio increases smoothly with beam energy, showing an energy dependence similar to K-/pi-. The measured particle yields can be reproduced by a hadron gas model, with chemical freeze-out parameters on a smooth curve in the T-muB plane. The transverse spectra can be understood as resulting from a rapidly expanding, locally equilibrated source. No evidence for an earlier kinetic decoupling of heavy hyperons is found.Comment: Contribution to the proceedings of "Strangeness in Quark Matter 2003" (March 2003, Atlantic Beach NC, USA), to be published in Journal of Physics G. 11 pages, 14 figure

Errors and uncertainties in a gridded carbon dioxide emissions inventory

Emission inventories (EIs) are the fundamental tool to monitor compliance with greenhouse gas (GHG) emissions and emission reduction commitments. Inventory accounting guidelines provide the best practices to help EI compilers across different countries and regions make comparable, national emission estimates regardless of differences in data availability. However, there are a variety of sources of error and uncertainty that originate beyond what the inventory guidelines can define. Spatially explicit EIs, which are a key product for atmospheric modeling applications, are often developed for research purposes and there are no specific guidelines to achieve spatial emission estimates. The errors and uncertainties associated with the spatial estimates are unique to the approaches employed and are often difficult to assess. This study compares the global, high-resolution (1 km), fossil fuel, carbon dioxide (CO2), gridded EI Open-source Data Inventory for Anthropogenic CO2 (ODIAC) with the multi-resolution, spatially explicit bottom-up EI geoinformation technologies, spatio-temporal approaches, and full carbon account for improving the accuracy of GHG inventories (GESAPU) over the domain of Poland. By taking full advantage of the data granularity that bottom-up EI offers, this study characterized the potential biases in spatial disaggregation by emission sector (point and non-point emissions) across different scales (national, subnational/regional, and urban policy-relevant scales) and identified the root causes. While two EIs are in agreement in total and sectoral emissions (2.2% for the total emissions), the emission spatial patterns showed large differences (10~100% relative differences at 1 km) especially at the urban-rural transitioning areas (90–100%). We however found that the agreement of emissions over urban areas is surprisingly good compared with the estimates previously reported for US cities. This paper also discusses the use of spatially explicit EIs for climate mitigation applications beyond the common use in atmospheric modeling. We conclude with a discussion of current and future challenges of EIs in support of successful implementation of GHG emission monitoring and mitigation activity under the Paris Climate Agreement from the United Nations Framework Convention on Climate Change (UNFCCC) 21st Conference of the Parties (COP21). We highlight the importance of capacity building for EI development and coordinated research efforts of EI, atmospheric observations, and modeling to overcome the challenges

Ranking of Fuzzy Similar Faces Using Relevance Matrix and Aggregation Operators

AbstractIn perception based imaging, Sketching With Words (SWW) is a well-established methodology in which the objects of computation are fuzzy geometric objects (f-objects).The problem of facial imaging of criminal on the basis of onlooker statement is not lack of method and measures but the modeling of onlooker(s) mind set. Because the onlooker has to give statements about different human face parts like forehead, eyes, nose, and chin etc.The concept of fuzzy similarity (f-similarity) and proper aggregation of components of face may provide more flexibility to onlooker(s). In proposed work onlooker(s) statement is recorded. Thereafter it is compared with existing statements. The f-similarity with different faces in database is estimated by using ‘as many as possible’ linguistic quantifier. Three types of constraints over size of parts of face ‘small’, ‘medium’, and ‘large’ are considered. Possibilistic constraints with linguistic hedges and negation operator like ‘very long’, ‘not long’, ‘not very long’ etc. are used. Moreover we have generated ranking of alike faces in decreasing order by using the concepts of f-similarity and relevance matrix

The impact of customer-specific marketing expenses on customer retention and customer profitability

We study the effects of customer-specific marketing expenses on customer retention and customer profitability in a business-to-business setting. Using data from a company providing hygiene services, we look at the impact of a hitherto unstudied type of expense targeted at individual customer relationships: the offering of free equipment to customers. The data allow tracking the activities performed in more than 4,500 customer relationships over a period of 4 years. Retention rates are higher for customers targeted with free equipment, but this effect results from an interaction with customer size. First-order dynamic panel data analyses show that the impact of targeted marketing expenses on customer dollar profit is positive for large customers, but there is no effect for smaller customers. Thus, targeted marketing expenses seem to be a tool for relationship maintenance rather than customer development: they help in retaining large customers that generate more profit, but they do not seem to work in developing new customers into larger, more profitable ones

The Use of Gridded Fossil Fuel CO2 Emissions (FFCO2) Inventory for Climate Mitigation Applications: Errors, Uncertainties, and Current and Future Challenges

Emission Inventory (EI) is a fundamental tool to monitor global compliance of greenhouse gases (GHGs) emissions reduction actions. Inventory guidelines provide a best practice to help EI compilers to make comparable national emission estimates, in spite of the differences in data availability across countries and regions. There are a variety of sources of errors and uncertainties, however, that originate beyond what the inventory guidelines define. For example, spatially-explicit EIs, which are a key product for atmospheric modeling applications, are often developed for research purposes, and there are no specific guidelines to disaggregate emission estimates from country scale. On top of that, EIs are fundamentally prone to systematic biases due to the simple calculation methodology and thus an objective evaluation (e.g. atmospheric top-down estimates) is needed to assure the accuracy of the estimates. ODIAC is a global high-resolution (1x1 km) fossil fuel carbon dioxide (CO2) gridded EI that is now often used in atmospheric CO2 modeling. ODIAC is based on disaggregation of national emission estimates made by CDIAC, which is the well accepted standard in the community. The ODIAC emission data product is updated on an annual basis using best available statistical data. Subnational spatial emission patterns are estimated using power plant profiles and satellite-observations of nighttime lights. In addition to the conventional CDIAC gridded data product, ODIAC carries international bunker emissions (shipping and aviation), which allows flux inversion modelers to accurately impose the global total fossil fuel emissions and their horizontal and vertical distribution. We have extensively evaluated ODIAC emissions using fine-grained EIs as well as a high-resolution atmospheric model simulation across different scales (national, subnational/regional, and urban policy relevant) with a focus on the uncertainties associated with the emission disaggregation. We have examined the use of NASA's Black Marble Suomi-NPP/VIIRS nightlight data