Future research priorities of Organic Agriculture. Policy paper of the IFOAM EU Group

This policy paper presents the main research priorities for organic farming agreed by the IFOAM EU Group. It identifies the main clusters both in a table format and with a more detailed explanation of the individual priorities. The paper was discussed at the board meeting of 13th March 2004, amended by additional input from national farmers’ associations and various research institutes from all EU members, revised with a priorisation exercise at the board meeting of 26th June in Lednice (Czech Rep) and finally was reviewed and approved at the board meeting in Bonn the 3rd September

Economic Impacts of GO TO 2040

The economy of the Chicago metropolitan region has reached a critical juncture. On the one hand, Chicagoland is currently a highly successful global region with extraordinary assets and outputs. The region successfully made the transition in the 1980s and 1990s from a primarily industrial to a knowledge and service-based economy. It has high levels of human capital, with strong concentrations in information-sector industries and knowledge-based functional clusters -- a headquarters region with thriving finance, business services, law, IT and emerging bioscience, advanced manufacturing and similar high-growth sectors. It combines multiple deep areas of specialization, providing the resilience that comes from economic diversity. It is home to the abundant quality-of-life amenities that flow from business and household prosperity.On the other hand, beneath this static portrait of our strengths lie disturbing signs of a potential loss of momentum. Trends in the last decade reveal slowing rates, compared to other regions, of growth in productivity and gross metropolitan product. Trends in innovation, new firm creation and employment are comparably lagging. The region also faces emerging challenges with respect to both spatial efficiency and governance.In this context, the Chicago Metropolitan Agency for Planning (CMAP) has just released GO TO 2040, its comprehensive, long-term plan for the Chicago metropolitan area. The plan contains recommendations aimed at shaping a wide range of regional characteristics over the next 30 years, during which time more than 2 million new residents are anticipated. Among the chief goals of GO TO 2040 are increasing the region's long-term economic prosperity, sustaining a high quality of life for the region's current and future residents and making the most effective use of public investments. To this end, the plan addresses a broad scope of interrelated issues which, in aggregate, will shape the long-term physical, economic, institutional and social character of the region.This report by RW Ventures, LLC is an independent assessment of the plan from a purely economic perspective, addressing the impacts that GO TO 2040's recommendations can be expected to have on the future of the regional economy. The assessment begins by describing how implementation of GO TO 2040's recommendations would affect the economic landscape of the region; reviews economic research and practice about the factors that influence regional economic growth; and, given both of these, articulates and illustrates the likely economic impacts that will flow from implementation of the plan. In the course of reviewing the economic implications of the plan, the assessment also provides recommendations of further steps, as the plan is implemented, for increasing its positive impact on economic growth

High-end fashion manufacturing in the UK - product, process and vision: Recommendations for a Designer and Fashion Manufacturer Alliance and a Designer Innovation and Sampling Centre

The Centre for Fashion Enterprise (CFE) was commissioned by the Department of Culture, Media and Sport (DCMS) to undertake a feasibility study to explore fully the market need for a new high-end production hub. This was in direct response to the need highlighted in the DCMS report, Creative Britain - New Talents For The New Economy, published in 2008. This study has confirmed that there is a need. However the need is for a sampling and innovation facility rather than a production hub. Designers reported a shortage of high quality sampling capacity in the UK, as well as difficulties in getting small quantities produced. Additionally, they do not know where or how to source appropriate manufacturing in the UK, Europe or globally, at the quality the market requires

Scalable and interpretable product recommendations via overlapping co-clustering

We consider the problem of generating interpretable recommendations by identifying overlapping co-clusters of clients and products, based only on positive or implicit feedback. Our approach is applicable on very large datasets because it exhibits almost linear complexity in the input examples and the number of co-clusters. We show, both on real industrial data and on publicly available datasets, that the recommendation accuracy of our algorithm is competitive to that of state-of-art matrix factorization techniques. In addition, our technique has the advantage of offering recommendations that are textually and visually interpretable. Finally, we examine how to implement our technique efficiently on Graphical Processing Units (GPUs).Comment: In IEEE International Conference on Data Engineering (ICDE) 201

On Recommendation of Learning Objects using Felder-Silverman Learning Style Model

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.The e-learning recommender system in learning institutions is increasingly becoming the preferred mode of delivery, as it enables learning anytime, anywhere. However, delivering personalised course learning objects based on learner preferences is still a challenge. Current mainstream recommendation algorithms, such as the Collaborative Filtering (CF) and Content-Based Filtering (CBF), deal with only two types of entities, namely users and items with their ratings. However, these methods do not pay attention to student preferences, such as learning styles, which are especially important for the accuracy of course learning objects prediction or recommendation. Moreover, several recommendation techniques experience cold-start and rating sparsity problems. To address the challenge of improving the quality of recommender systems, in this paper a novel recommender algorithm for machine learning is proposed, which combines students actual rating with their learning styles to recommend Top-N course learning objects (LOs). Various recommendation techniques are considered in an experimental study investigating the best technique to use in predicting student ratings for e-learning recommender systems. We use the Felder-Silverman Learning Styles Model (FSLSM) to represent both the student learning styles and the learning object profiles. The predicted rating has been compared with the actual student rating. This approach has been experimented on 80 students for an online course created in the MOODLE Learning Management System, while the evaluation of the experiments has been performed with the Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). The results of the experiment verify that the proposed approach provides a higher prediction rating and significantly increases the accuracy of the recommendation

FIRE (facilitating implementation of research evidence) : a study protocol

Research evidence underpins best practice, but is not always used in healthcare. The Promoting Action on Research Implementation in Health Services (PARIHS) framework suggests that the nature of evidence, the context in which it is used, and whether those trying to use evidence are helped (or facilitated) affect the use of evidence. Urinary incontinence has a major effect on quality of life of older people, has a high prevalence, and is a key priority within European health and social care policy. Improving continence care has the potential to improve the quality of life for older people and reduce the costs associated with providing incontinence aids

NEXT LEVEL: A COURSE RECOMMENDER SYSTEM BASED ON CAREER INTERESTS

Skills-based hiring is a talent management approach that empowers employers to align recruitment around business results, rather than around credentials and title. It starts with employers identifying the particular skills required for a role, and then screening and evaluating candidates’ competencies against those requirements. With the recent rise in employers adopting skills-based hiring practices, it has become integral for students to take courses that improve their marketability and support their long-term career success. A 2017 survey of over 32,000 students at 43 randomly selected institutions found that only 34% of students believe they will graduate with the skills and knowledge required to be successful in the job market. Furthermore, the study found that while 96% of chief academic officers believe that their institutions are very or somewhat effective at preparing students for the workforce, only 11% of business leaders strongly agree [11]. An implication of the misalignment is that college graduates lack the skills that companies need and value. Fortunately, the rise of skills-based hiring provides an opportunity for universities and students to establish and follow clearer classroom-to-career pathways. To this end, this paper presents a course recommender system that aims to improve students’ career readiness by suggesting relevant skills and courses based on their unique career interests

Opportunities for Dutch Biorefineries

Deze Roadmap Bioraffinage beschrijft een aantal mogelijke routes naar de ontwikkeling en implementatie van een bioraffinage-gerelateerde Bio-based Economy in Nederland. De Roadmap combineert korte- en middellange termijn mogelijkheden (commerciële implementatie, demonstratie plants, pilot plants en gerelateerd toegepast onderzoek) met strategisch onderzoek voor de langere termijn. Tevens zijn vier z.g. Moonshots uitgewerkt, als voorziene bioraffinagestrategieën met een grote potentie voor de Nederlandse economi