Investigation of space radiation effects in polymeric film-forming materials

The literature search in the field of ultraviolet radiation effects that was conducted during the previous program, Contract No. NAS1-12549, has been expanded to include the effects of charged particle radiation and high energy electromagnetic radiation. The literature from 1958 to 1969 was searched manually, while the literature from 1969 to present was searched by using a computerized keyword system. The information generated from this search was utilized for the design of an experimental program aimed at the development of materials with improved resistance to the vacuum-radiation environment of space. Preliminary irradiation experiments were performed which indicate that the approaches and criteria employed are very promising and may provide a solution to the challenging problem of polymer stability to combined ultraviolet/high energy radiation

MEDIATOR: TOWARDS A NEGOTIATION SUPPORT SYSTEM

MEDIATOR is a negotiation support system (NSS) based on evolutionary systems design (ESD) and database-centered implementation. It supports negotiations by consensus seeking through exchange of information and, where consensus is incomplete, by compromise. The negotiation problem is shown --graphically or as relational data in matrix form-- in three spaces as a mapping from control space to goal space (and through marginal utility functions) to utility space. Within each of these spaces the negotiation process is characterized by adaptive change, i.e., mappings of group target and feasible sets by which these sets are redefined in seeking a solution characterized by a single-point intersection between them. This concept is being implemented in MEDIATOR, a data-based micro-mainframe NSS intended to support the players and a human mediator in multi-player decision situations. Each player employs private and shared database views, using his/her own micro-computer decision support system enhanced with a communications manager to interact with the mediator DSS. Sharing of views constitutes exchange of information which can lead towards consensus. The human mediator can support compromise, as needed, through use of solution concepts and/or concession-making procedures in the NSS model base. As a concrete example, we demonstrate the use of the system for group car buying decisions.Information Systems Working Papers Serie

MEDIATOR: TOWARDS A NEGOTIATION SUPPORT SYSTEM

MEDIATOR is a negotiation support system (NSS) based on evolutionary systems design (ESD) and database-centered implementation. It supports negotiations by consensus seeking through exchange of information and, where consensus is incomplete, by compromise. The negotiation problem is shown --graphically or as relational data in matrix form-- in three spaces as a mapping from control space to goal space (and through marginal utility functions) to utility space. Within each of these spaces the negotiation process is characterized by adaptive change, i.e., mappings of group target and feasible sets by which these sets are redefined in seeking a solution characterized by a single-point intersection between them. This concept is being implemented in MEDIATOR, a data-based micro-mainframe NSS intended to support the players and a human mediator in multi-player decision situations. Each player employs private and shared database views, using his/her own micro-computer decision support system enhanced with a communications manager to interact with the mediator DSS. Sharing of views constitutes exchange of information which can lead towards consensus. The human mediator can support compromise, as needed, through use of solution concepts and/or concession-making procedures in the NSS model base. As a concrete example, we demonstrate the use of the system for group car buying decisions.Information Systems Working Papers Serie

Designing data warehouses for geographic OLAP querying by using MDA

Data aggregation in Geographic Information Systems (GIS) is a desirable feature, spatial data are integrated in OLAP engines for this purpose. However, the development and operation of those systems is still a complex task due to methodologies followed. There are some ad hoc solutions that deal only with isolated aspects and do not provide developer and analyst with an intuitive, integrated and standard framework for designing all relevant parts. To overcome these problems, we have defined a model driven approach to accomplish Geographic Data Warehouse (GDW) development. Then, we have defined a data model required to implement and query spatial data. Its modeling is defined and implemented by using an extension of UML metamodel and it is also formalized by using OCL language. In addition, the proposal has been verified against a example scenario with sample data sets. For this purpose, we have accomplished a developing tool based on Eclipse platform and MDA standard. The great advantage of this solution is that developers can directly include spatial data at conceptual level, while decision makers can also conceptually make geographic queries without being aware of logical details.This work has been partially supported by the ESPIA project (TIN2007-67078) from the Spanish Ministry of Education and Science and by the QUASIMODO project (PAC08-0157-0668) from the Castilla-La Mancha Ministry of Education and Science (Spain). Octavio Glorio is funded by the University of Alicante under the 11th Latin American grant program

Dagstuhl-Manifest zur Strategischen Bedeutung des Software Engineering in Deutschland

Im Rahmen des Dagstuhl Perspektiven Workshop 05402 "Challenges for Software Engineering Research" haben führende Software Engineering Professoren den derzeitigen Stand der Softwaretechnik in Deutschland charakterisiert und Handlungsempfehlungen für Wirtschaft, Forschung und Politik abgeleitet. Das Manifest fasst die diese Empfehlungen und die Bedeutung und Entwicklung des Fachgebiets prägnant zusammen

Improved clinical investigation and evaluation of high-risk medical devices: the rationale and objectives of CORE-MD (Coordinating Research and Evidence for Medical Devices)

: In the European Union (EU) the delivery of health services is a national responsibility but there are concerted actions between member states to protect public health. Approval of pharmaceutical products is the responsibility of the European Medicines Agency, whereas authorizing the placing on the market of medical devices is decentralized to independent 'conformity assessment' organizations called notified bodies. The first legal basis for an EU system of evaluating medical devices and approving their market access was the medical device directives, from the 1990s. Uncertainties about clinical evidence requirements, among other reasons, led to the EU Medical Device Regulation (2017/745) that has applied since May 2021. It provides general principles for clinical investigations but few methodological details-which challenges responsible authorities to set appropriate balances between regulation and innovation, pre- and post-market studies, and clinical trials and real-world evidence. Scientific experts should advise on methods and standards for assessing and approving new high-risk devices, and safety, efficacy, and transparency of evidence should be paramount. The European Commission recently awarded a Horizon 2020 grant to a consortium led by the European Society of Cardiology and the European Federation of National Associations of Orthopaedics and Traumatology, that will review methodologies of clinical investigations, advise on study designs, and develop recommendations for aggregating clinical data from registries and other real-world sources. The CORE-MD project (Coordinating Research and Evidence for Medical Devices) will run until March 2024; here we describe how it may contribute to the development of regulatory science in Europe

A synthesis of evidence for policy from behavioural science during COVID-19

Scientific evidence regularly guides policy decisions1, with behavioural science increasingly part of this process2. In April 2020, an influential paper3 proposed 19 policy recommendations ('claims') detailing how evidence from behavioural science could contribute to efforts to reduce impacts and end the COVID-19 pandemic. Here we assess 747 pandemic-related research articles that empirically investigated those claims. We report the scale of evidence and whether evidence supports them to indicate applicability for policymaking. Two independent teams, involving 72 reviewers, found evidence for 18 of 19 claims, with both teams finding evidence supporting 16 (89%) of those 18 claims. The strongest evidence supported claims that anticipated culture, polarization and misinformation would be associated with policy effectiveness. Claims suggesting trusted leaders and positive social norms increased adherence to behavioural interventions also had strong empirical support, as did appealing to social consensus or bipartisan agreement. Targeted language in messaging yielded mixed effects and there were no effects for highlighting individual benefits or protecting others. No available evidence existed to assess any distinct differences in effects between using the terms 'physical distancing' and 'social distancing'. Analysis of 463 papers containing data showed generally large samples; 418 involved human participants with a mean of 16,848 (median of 1,699). That statistical power underscored improved suitability of behavioural science research for informing policy decisions. Furthermore, by implementing a standardized approach to evidence selection and synthesis, we amplify broader implications for advancing scientific evidence in policy formulation and prioritization

A synthesis of evidence for policy from behavioural science during COVID-19

Scientific evidence regularly guides policy decisions1, with behavioural science increasingly part of this process2. In April 2020, an influential paper3 proposed 19 policy recommendations (‘claims’) detailing how evidence from behavioural science could contribute to efforts to reduce impacts and end the COVID-19 pandemic. Here we assess 747 pandemic-related research articles that empirically investigated those claims. We report the scale of evidence and whether evidence supports them to indicate applicability for policymaking. Two independent teams, involving 72 reviewers, found evidence for 18 of 19 claims, with both teams finding evidence supporting 16 (89%) of those 18 claims. The strongest evidence supported claims that anticipated culture, polarization and misinformation would be associated with policy effectiveness. Claims suggesting trusted leaders and positive social norms increased adherence to behavioural interventions also had strong empirical support, as did appealing to social consensus or bipartisan agreement. Targeted language in messaging yielded mixed effects and there were no effects for highlighting individual benefits or protecting others. No available evidence existed to assess any distinct differences in effects between using the terms ‘physical distancing’ and ‘social distancing’. Analysis of 463 papers containing data showed generally large samples; 418 involved human participants with a mean of 16,848 (median of 1,699). That statistical power underscored improved suitability of behavioural science research for informing policy decisions. Furthermore, by implementing a standardized approach to evidence selection and synthesis, we amplify broader implications for advancing scientific evidence in policy formulation and prioritization