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This study aimed at assigning climate-relevant gaseous emissions from ruminants to animal- or feed-related origin. Three adult rumen-cannulated German Holstein steers and three forage types (corn silage (CS), alfalfa silage (AS) and grass hay (GH)) were used in a 3 × 3 Latin square design. Each period consisted of 12 days (d), during which animals received 10 kg dry matter/day of one forage as sole feed. Gaseous samples from forages and the steers´ rumen were taken and analyzed for CO2, CH4, and N2O using gas chromatography. There were large differences in the amounts of CO2 and N2O emitting from the forage types. Most N2O came from AS and only small amounts from GH and CS. Results indicate that fermented forages rich in nitrogen can release climate-relevant N2O. The highest CO2 amounts were measured in CS. Methane was not detected in any forage sample. Animals consuming CS showed slightly lower CH4 concentrations in the rumen gas sample than animals fed AS or GH. Big differences were found for ruminal N2O with the highest concentration after AS ingestion such that the N2O measured in the rumen seems to originate from the used feedstuff.

This study aimed at assigning climate-relevant gaseous emissions from ruminants to animal- or feed-related origin. Three adult rumen-cannulated German Holstein steers and three forage types (corn silage (CS), alfalfa silage (AS) and grass hay (GH)) were used in a 3 × 3 Latin square design. Each period consisted of 12 days (d), during which animals received 10 kg dry matter/day of one forage as sole feed. Gaseous samples from forages and the steers´ rumen were taken and analyzed for CO2, CH4, and N2O using gas chromatography. There were large differences in the amounts of CO2 and N2O emitting from the forage types. Most N2O came from AS and only small amounts from GH and CS. Results indicate that fermented forages rich in nitrogen can release climate-relevant N2O. The highest CO2 amounts were measured in CS. Methane was not detected in any forage sample. Animals consuming CS showed slightly lower CH4 concentrations in the rumen gas sample than animals fed AS or GH. Big differences were found for ruminal N2O with the highest concentration after AS ingestion such that the N2O measured in the rumen seems to originate from the used feedstuff.

Innovation plays a key role in meeting the challenges of the future, but despite the unprecedented investment in innovation, Portugal has seen a decline in the various indicators that assess the country’s performance. This study aims to answer questions about the state of innovation in Portugal, based on the relevant global and European innovation indicators, comparing the country’s performance with that of Ireland, Belgium, and the Czech Republic. Using secondary data collected from the reports of the last four years, explanatory research was conducted based on statistical and graphical methods in order to establish causal relationships. The areas where the main changes have taken place are presented, highlighting the aspects in which Portugal stands out for superior or poor performance, providing a benchmark for the definition of policies to foster innovation in Portugal. The results demonstrate that institutions, business sophistication, and knowledge and technology score negatively, while creativity stands out as a strength. Environmental sustainability, firms’ investment in innovation, and the impact of innovation on sales are aspects that Portugal needs to improve; human capital and the attractiveness of the R&D system deserve positive remarks. It is fundamental to understand how Portugal is preparing for the future and what the country can learn from others. This study is limited by the specific period in analysis, which could affect causal relationships, and the historical perspective could provide guidelines to the understanding of the relative position of the country. This study contributes new perspectives and knowledge about the state of innovation in Portugal, providing clues to entrepreneurs, policy makers, and the scientific community.

Innovation plays a key role in meeting the challenges of the future, but despite the unprecedented investment in innovation, Portugal has seen a decline in the various indicators that assess the country’s performance. This study aims to answer questions about the state of innovation in Portugal, based on the relevant global and European innovation indicators, comparing the country’s performance with that of Ireland, Belgium, and the Czech Republic. Using secondary data collected from the reports of the last four years, explanatory research was conducted based on statistical and graphical methods in order to establish causal relationships. The areas where the main changes have taken place are presented, highlighting the aspects in which Portugal stands out for superior or poor performance, providing a benchmark for the definition of policies to foster innovation in Portugal. The results demonstrate that institutions, business sophistication, and knowledge and technology score negatively, while creativity stands out as a strength. Environmental sustainability, firms’ investment in innovation, and the impact of innovation on sales are aspects that Portugal needs to improve; human capital and the attractiveness of the R&D system deserve positive remarks. It is fundamental to understand how Portugal is preparing for the future and what the country can learn from others. This study is limited by the specific period in analysis, which could affect causal relationships, and the historical perspective could provide guidelines to the understanding of the relative position of the country. This study contributes new perspectives and knowledge about the state of innovation in Portugal, providing clues to entrepreneurs, policy makers, and the scientific community.

Viewing a computationally-intensive problem as a self-contained challenge with its own hardware, software and scheduling strategies is an approach that should be investigated. We might suggest assigning heterogeneous hardware architectures to solve a problem, while parallel computing paradigms may play an important role in writing efficient code to solve the problem; moreover, the scheduling strategies may be examined as a possible solution. Depending on the problem complexity, finding the best possible solution using an integrated infrastructure of hardware, software and scheduling strategy can be a complex job. Developing and using ontologies and reasoning techniques play a significant role in reducing the complexity of identifying the components of such integrated infrastructures. Undertaking reasoning and inferencing regarding the domain concepts can help to find the best possible solution through a combination of hardware, software and scheduling strategies. In this paper, we present an ontology and show how we can use it to solve computationally-intensive problems from various domains. As a potential use for the idea, we present examples from the bioinformatics domain. Validation by using problems from the Elastic Optical Network domain has demonstrated the flexibility of the suggested ontology and its suitability for use with any other computationally-intensive problem domain.

Viewing a computationally-intensive problem as a self-contained challenge with its own hardware, software and scheduling strategies is an approach that should be investigated. We might suggest assigning heterogeneous hardware architectures to solve a problem, while parallel computing paradigms may play an important role in writing efficient code to solve the problem; moreover, the scheduling strategies may be examined as a possible solution. Depending on the problem complexity, finding the best possible solution using an integrated infrastructure of hardware, software and scheduling strategy can be a complex job. Developing and using ontologies and reasoning techniques play a significant role in reducing the complexity of identifying the components of such integrated infrastructures. Undertaking reasoning and inferencing regarding the domain concepts can help to find the best possible solution through a combination of hardware, software and scheduling strategies. In this paper, we present an ontology and show how we can use it to solve computationally-intensive problems from various domains. As a potential use for the idea, we present examples from the bioinformatics domain. Validation by using problems from the Elastic Optical Network domain has demonstrated the flexibility of the suggested ontology and its suitability for use with any other computationally-intensive problem domain.

The bioeconomy can support Europe’s transition to a low-carbon economy and help to meet key international, European and member state sustainability targets through the provision of bio-based products and energy derived from sustainably sourced biomass. A successful implementation of a bio-based economy in Europe will, however, require a profound transformation of our production and consumption patterns. Consumer behavior will play a major role in supporting the successful transition to a bio-based economy. This paper uses a structured quantitative survey approach to gain an understanding of consumer perspectives in relation to bio-based products. Conducted among 18–75-year-old consumers in Ireland and the Netherlands, the study indicates that consumers in both countries have a relatively positive outlook regarding bio-based products, with Irish consumers showing a slightly more positive outlook. The study finds that a larger majority of Irish consumers would prefer buying bio-based products as opposed to fossil-based products, while Irish consumers also have a slightly more positive impression than Dutch consumers that their consumer choices can be beneficial for the environment.