A growing number of older patients undergo cardiac surgery. Some of these patients are at increased risk of post-operative functional decline, potentially leading to reduced quality of life and autonomy, and other negative health outcomes. First step in prevention is to identify patients at risk of functional decline. There are no current published tools available to predict functional decline following cardiac surgery. The objective was to validate the identification of seniors at risk—hospitalised patients (ISAR-HP), in older patients undergoing cardiac surgery. A multicenter cohort study was performed in cardiac surgery wards of two university hospitals with follow-up 3 months after hospital admission. Inclusion criteria: consecutive cardiac surgery patients, aged ≥65. Functional decline was defined as a decline of at least one point on the Katz ADL Index at follow-up compared with preadmission status.
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Purpose: Intellectual capital theory and practice predominantly focus on measuring and managing intangible assets. However, if we want to balance the intellectual capital books (Harvey and Lusch, 1999), we should recognize both intellectual assets and intellectual liabilities (Caddy, 2000). Therefore, the purpose of this article is to present a theoretical framework for measuring intellectual liabilities. Design: Identifying intangible liabilities is identifying the risk of decline and fall of organizations. One of the first extensive studies related to causes of decline and fall is Gibbon‟s Decline and Fall of the Roman Empire (Gibbon, 2003 [original publication 1776]). It seems as if the main lessons that were drawn from this study are also applicable to today‟s business environment. Therefore, the framework that is developed in this article is not only based on intellectual capital literature, but also on Gibbon‟s study into the causes of decline and fall of the Roman Empire. Findings: The findings are combined in a framework for measuring intellectual liabilities. The main distinction within the proposed framework is the distinction between internal and external liabilities. Internal liabilities refer to the causes of deterioration that arise from the sources of value creation within the organization. External liabilities refer to the causes of deterioration that come from outside and are beyond control of the organization. Originality: This article explores a relatively new topic (intellectual liabilities) from a perspective (historical sciences) that is hardly used in management science.
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Population decline, welfare state reforms and austerity measures pressurise the liveability of rural areas in the Netherlands and call upon local governments and communities to adapt and renew their mode of governance. This paper reports on three Dutch experimental governance arrangements which are analysed through the lens of Evolutionary Governance Theory. The study focuses on how decision-making roles change while these arrangements unfold and how the three municipalities institutionalise these changes in the course of time. The study produces three main conclusions. First, the readiness and preparedness of local governments to shift decision-making roles with citizens proved to be of main influence on governance change. Second, local residents’ commitment importantly affected the progress of the experiments, while social cohesion and tangible outputs strongly influenced the extent and continuity of such commitment. Third, although the arrangements took place in the same period of time and abovementioned context, the level of institutionalisation of shifting roles between government and residents differed among the cases. Certain pathways of evolving decision-making roles seem to be more stable than others. It is in this area that the extent of both formal and informal institutionalisation seems to play an important role.
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Circular BIOmass CAScade to 100% North Sea Region (NSR) economic activity and growth are mostly found in urban areas. Rural NSR regions experience population decline and negative economic growth. The BIOCAS project expects revitalizing and greening of rural areas go hand in hand. BIOCAS will develop rural areas of the NSR into smart specialized regions for integrated and local valorization of biomass. 13 Commercial running Bio-Cascade-Alliances (BCA’s) will be piloted, evaluated and actively shared in the involved regions. These proven concepts will accelerate adoption of high to low value bio-cascading technologies and businesses in rural regions. The project connects 18 regional initiatives around technologies, processes, businesses for the conversion of biomass streams. The initiatives collaborate in a thematic approach: Through engineering, value chain assessments, BCA’s building, partners tackle challenges that are shared by rural areas. I.e. unsustainable biomass use, a mineral surplus and soil degradation, deprivation of potentially valuable resources, and limited involvement of regional businesses and SMEs in existing bio-economy developments. The 18 partners are strongly embedded in regional settings, connected to many local partners. They will align stakeholders in BCA’s that would not have cooperated without BIOCAS interventions. Triple helix, science, business and governmental input will realize inclusive lasting bio cascade businesses, transforming costly waste to resources and viable business.Interreg IVB North Sea Region Programme: €378,520.00, fEC % 50.00%1/07/17 → 30/06/21
Human kind has a major impact on the state of life on Earth, mainly caused by habitat destruction, fragmentation and pollution related to agricultural land use and industrialization. Biodiversity is dominated by insects (~50%). Insects are vital for ecosystems through ecosystem engineering and controlling properties, such as soil formation and nutrient cycling, pollination, and in food webs as prey or controlling predator or parasite. Reducing insect diversity reduces resilience of ecosystems and increases risks of non-performance in soil fertility, pollination and pest suppression. Insects are under threat. Worldwide 41 % of insect species are in decline, 33% species threatened with extinction, and a co-occurring insect biomass loss of 2.5% per year. In Germany, insect biomass in natural areas surrounded by agriculture was reduced by 76% in 27 years. Nature inclusive agriculture and agri-environmental schemes aim to mitigate these kinds of effects. Protection measures need success indicators. Insects are excellent for biodiversity assessments, even with small landscape adaptations. Measuring insect biodiversity however is not easy. We aim to use new automated recognition techniques by machine learning with neural networks, to produce algorithms for fast and insightful insect diversity indexes. Biodiversity can be measured by indicative species (groups). We use three groups: 1) Carabid beetles (are top predators); 2) Moths (relation with host plants); 3) Flying insects (multiple functions in ecosystems, e.g. parasitism). The project wants to design user-friendly farmer/citizen science biodiversity measurements with machine learning, and use these in comparative research in 3 real life cases as proof of concept: 1) effects of agriculture on insects in hedgerows, 2) effects of different commercial crop production systems on insects, 3) effects of flower richness in crops and grassland on insects, all measured with natural reference situations
