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  • 1
    Electronic Resource
    Electronic Resource
    Springer
    Letters in mathematical physics 30 (1994), S. 169-171 
    ISSN: 1573-0530
    Keywords: 81V10 ; 33D10
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics , Physics
    Notes: Abstract We show that a slight modification in Schwinger's method leads directly to the finite result for the Casimir energy of a massless scalar theory.
    Type of Medium: Electronic Resource
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  • 2
    Electronic Resource
    Electronic Resource
    Springer
    Letters in mathematical physics 31 (1994), S. 309-313 
    ISSN: 1573-0530
    Keywords: 81V10 ; 33D10
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics , Physics
    Notes: Abstract We apply a method recently proposed by Schwinger to the massive scalar field to calculate the Casimir effect. The method is applied with two different regularization schemes: Schwinger's original one by means of Poisson formula and another one by means of analytical continuation.
    Type of Medium: Electronic Resource
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  • 3
    Electronic Resource
    Electronic Resource
    Chichester [u.a.] : Wiley-Blackwell
    International Journal for Numerical Methods in Engineering 7 (1973), S. 479-490 
    ISSN: 0029-5981
    Keywords: Engineering ; Engineering General
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Mathematics , Technology
    Notes: FORTRAN subprograms for the solution of systems of linear algebraic equations are evaluated and compared on the basis of execution speed and accuracy. A symmetric, positive definite, banded test matrix is used in each case. The procedures considered are direct solution, iteration and matrix inversion. Both in-core schemes and those requiring the use of auxiliary data storage devices are included. Some of the techniques used require the full coefficient matrix, whereas others account for symmetry, banding, or sparseness of the system.Matrix inversion is found to be an inefficient technique, even if multiple right-hand side constant vectors are to be solved. In such cases, either Gauss elimination with multiple constant vectors treated simultaneously, or decomposition with the retention of the upper and lower triangular matrices, is recommended. Double precision arithmetic is suggested as a means of reducing round-off errors, and should always be employed when permitted by the computer's core capacity.On the basis of the results obtained with the single test system of equations, specific subprograms are recommended for each category of problem.
    Additional Material: 4 Tab.
    Type of Medium: Electronic Resource
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  • 4
    Publication Date: 2022-06-16
    Description: Abstract
    Description: As the negative impacts of hydrological extremes increase in large parts of the world, a better understanding of the drivers of change in risk and impacts is essential for effective flood and drought risk management and climate adaptation. However, there is a lack of comprehensive, empirical data about the processes, interactions and feedbacks in complex human-water systems leading to flood and drought impacts. To fill this gap, we present an IAHS Panta Rhei benchmark dataset containing socio-hydrological data of paired events, i.e. two floods or two droughts that occurred in the same area (Kreibich et al. 2017, 2019). The contained 45 paired events occurred in 42 different study areas (in three study areas we have data on two paired events), which cover different socioeconomic and hydroclimatic contexts across all continents. The dataset is unique in covering floods and droughts, in the number of cases assessed and in the amount of qualitative and quantitative socio-hydrological data contained. References to the data sources are provided in 2022-002_Kreibich-et-al_Key_data_table.xlsx where possible. Based on templates, we collected detailed, review-style reports describing the event characteristics and processes in the case study areas, as well as various semi-quantitative data, categorised into management, hazard, exposure, vulnerability and impacts. Sources of the data were classified as follows: scientific study (peer-reviewed paper and PhD thesis), report (by governments, administrations, NGOs, research organisations, projects), own analysis by authors, based on a database (e.g. official statistics, monitoring data such as weather, discharge data, etc.), newspaper article, and expert judgement. The campaign to collect the information and data on paired events started at the EGU General Assembly in April 2019 in Vienna and was continued with talks promoting the paired event data collection at various conferences. Communication with the Panta Rhei community and other flood and drought experts identified through snowballing techniques was important. Thus, data on paired events were provided by professionals with excellent local knowledge of the events and risk management practices.
    Keywords: hydrological extremes ; risk dynamics ; human-flood system ; human-drought system ; socio-hydrology ; risk management ; flood ; drought ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 ENVIRONMENTAL GOVERNANCE/MANAGEMENT 〉 WATER MANAGEMENT ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 NATURAL HAZARDS 〉 DROUGHTS ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 NATURAL HAZARDS 〉 FLOODS ; EARTH SCIENCE SERVICES 〉 DATA ANALYSIS AND VISUALIZATION ; environmental assessment 〉 environmental risk assessment
    Type: Dataset , Dataset
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  • 5
    Publication Date: 2023-04-18
    Description: Abstract
    Description: As the negative impacts of hydrological extremes increase in large parts of the world, a better understanding of the drivers of change in risk and impacts is essential for effective flood and drought risk management and climate adaptation. However, there is a lack of comprehensive, empirical data about the processes, interactions and feedbacks in complex human-water systems leading to flood and drought impacts. To fill this gap, we present an IAHS Panta Rhei benchmark dataset containing socio-hydrological data of paired events, i.e. two floods or two droughts that occurred in the same area (Kreibich et al. 2017, 2019). The contained 45 paired events occurred in 42 different study areas (in three study areas we have data on two paired events), which cover different socioeconomic and hydroclimatic contexts across all continents. The dataset is unique in covering floods and droughts, in the number of cases assessed and in the amount of qualitative and quantitative socio-hydrological data contained. References to the data sources are provided in 2023-001_Kreibich-et-al_Key_data_table.xlsx where possible. Based on templates, we collected detailed, review-style reports describing the event characteristics and processes in the case study areas, as well as various semi-quantitative data, categorised into management, hazard, exposure, vulnerability and impacts. Sources of the data were classified as follows: scientific study (peer-reviewed paper and PhD thesis), report (by governments, administrations, NGOs, research organisations, projects), own analysis by authors, based on a database (e.g. official statistics, monitoring data such as weather, discharge data, etc.), newspaper article, and expert judgement. The campaign to collect the information and data on paired events started at the EGU General Assembly in April 2019 in Vienna and was continued with talks promoting the paired event data collection at various conferences. Communication with the Panta Rhei community and other flood and drought experts identified through snowballing techniques was important. Thus, data on paired events were provided by professionals with excellent local knowledge of the events and risk management practices.
    Keywords: hydrological extremes ; risk dynamics ; human-flood system ; human-drought system ; socio-hydrology ; risk management ; flood ; drought ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 ENVIRONMENTAL GOVERNANCE/MANAGEMENT 〉 WATER MANAGEMENT ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 NATURAL HAZARDS 〉 DROUGHTS ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 NATURAL HAZARDS 〉 FLOODS ; EARTH SCIENCE SERVICES 〉 DATA ANALYSIS AND VISUALIZATION ; environmental assessment 〉 environmental risk assessment
    Type: Dataset , Dataset
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