What (science for) adaptation to climate change in Colombian agriculture? A commentary on “A way forward on adaptation to climate change in Colombian agriculture: perspectives towards 2050” by J. Ramirez-Villegas, M. Salazar, A. Jarvis, C. E. Navarro-Valcines.

Climate change is putting Colombian agriculture under significant stress and, if no adaptation is made, the latter will be severely impacted during the next decades. Ramirez-Villegas et al. (2012) set out a government-led, top-down, techno-scientific proposal for a way forward by which Colombian agriculture could adapt to climate change. However, this proposal largely overlooks the root causes of vulnerability of Colombian agriculture, and of smallholders in particular. I discuss some of the hidden assumptions underpinning this proposal and of the arguments employed by Ramirez-Villegas et al., based on existing literature on Colombian agriculture and the wider scientific debate on adaptation to climate change. While technical measures may play an important role in the adaptation of Colombian agriculture to climate change, I question whether the actions listed in the proposal alone and specifically for smallholders, truly represent priority issues. I suggest that by i) looking at vulnerability before adaptation, ii) contextualising climate change as one of multiple exposures, and iii) truly putting smallholders at the centre of adaptation, i.e. to learn about and with them, different and perhaps more urgent priorities for action can be identified. Ultimately, I argue that what is at stake is not only a list of adaptation measures but, more importantly, the scientific approach from which priorities for action are identified. In this respect, I propose that transformative rather than technical fix adaptation represents a better approach for Colombian agriculture and smallholders in particular, in the face of climate change.

High-latitude particle precipitation and its relationship to magnetospheric source regions

Two central issues in magnetospheric research are understanding the mapping of the low-altitude ionosphere to the distant regions of the magnetsphere, and understanding the relationship between the small-scale features detected in the various regions of the ionosphere and the global properties of the magnetosphere. The high-latitude ionosphere, through its magnetic connection to the outer magnetosphere, provides an important view of magnetospheric boundaries and the physical processes occurring there. All physical manifestations of this magnetic connectivity (waves, particle precipitation, etc.), however, have non-zero propagation times during which they are convected by the large-scale magnetospheric electric field, with phenomena undergoing different convection distances depending on their propagation times. Identification of the ionospheric signatures of magnetospheric regions and phenomena, therefore, can be difficult. Considerable progress has recently been made in identifying these convection signatures in data from low- and high-altitude satellites. This work has allowed us to learn much about issues such as: the rates of magnetic reconnection, both at the dayside magnetopause and in the magnetotail; particle transport across the open magnetopause; and particle acceleration at the magnetopause and the magnetotail current sheets.

Aspects of designing and evaluating seasonal-to-interannual Arctic sea-ice prediction systems

Using lessons from idealised predictability experiments, we discuss some issues and perspectives on the design of operational seasonal to inter-annual Arctic sea-ice prediction systems. We first review the opportunities to use a hierarchy of different types of experiment to learn about the predictability of Arctic climate. We also examine key issues for ensemble system design, such as: measuring skill, the role of ensemble size and generation of ensemble members. When assessing the potential skill of a set of prediction experiments, using more than one metric is essential as different choices can significantly alter conclusions about the presence or lack of skill. We find that increasing both the number of hindcasts and ensemble size is important for reliably assessing the correlation and expected error in forecasts. For other metrics, such as dispersion, increasing ensemble size is most important. Probabilistic measures of skill can also provide useful information about the reliability of forecasts. In addition, various methods for generating the different ensemble members are tested. The range of techniques can produce surprisingly different ensemble spread characteristics. The lessons learnt should help inform the design of future operational prediction systems.

Action learning: how learning transfers from entrepreneurs to small firms

The paper presents research with small and medium enterprise (SME) owners who have participated in a leadership development programme. The primary focus of the paper is on learning transfer and factors affecting it, arguing that entrepreneurs must engage in ‘action’ in order to ‘learn’ and that under certain conditions they may transfer learning to their firm. The paper draws on data from 19 focus groups undertaken from 2010 to 2012, involving 51 participants in the LEAD Wales programme. It considers the literatures exploring learning transfer and develops a conceptual framework, outlining four areas of focus for entrepreneurial learning. Utilising thematic analysis, it describes and evaluates what (actual facts and information) and how (techniques, styles of learning) participants transfer and what actions they take to improve the business and develop their people. The paper illustrates the complex mechanisms involved in this process and concludes that action learning is a method of facilitating entrepreneurial learning which is able to help address some of the problems of engagement, relevance and value that have been highlighted previously. The paper concludes that the efficacy of an entrepreneurial learning intervention in SMEs may depend on the effectiveness of learning transfer.

An open book: what and how young children learn from picture and story books

Looking at and listening to picture and story books is a ubiquitous activity, frequently enjoyed by many young children and their parents. Well before children can read for themselves they are able to learn from books. Looking at and listening to books increases children’s general knowledge, understanding about the world and promotes language acquisition. This collection of papers demonstrates the breadth of information pre-reading children learn from books and increases our understanding of the social and cognitive mechanisms that support this learning. Our hope is that this Research Topic/eBook will be useful for researchers as well as educational practitioners and parents who are interested in optimizing children’s learning. We conceptually divide this research topic into four broad sections, which focus on the nature and attributes of picture and story books, what children learn from picture and story books, the interactions children experience during shared reading, and potential applications of research into shared reading, respectively.

Collaborative eLearning Assistant Network: caring agents are conscious agents

Would a research assistant - who can search for ideas related to those you are working on, network with others (but only share the things you have chosen to share), doesn’t need coffee and who might even, one day, appear to be conscious - help you get your work done? Would it help your students learn? There is a body of work showing that digital learning assistants can be a benefit to learners. It has been suggested that adaptive, caring, agents are more beneficial. Would a conscious agent be more caring, more adaptive, and better able to deal with changes in its learning partner’s life? Allow the system to try to dynamically model the user, so that it can make predictions about what is needed next, and how effective a particular intervention will be. Now, given that the system is essentially doing the same things as the user, why don’t we design the system so that it can try to model itself in the same way? This should mimic a primitive self-awareness. People develop their personalities, their identities, through interacting with others. It takes years for a human to develop a full sense of self. Nobody should expect a prototypical conscious computer system to be able to develop any faster than that. How can we provide a computer system with enough social contact to enable it to learn about itself and others? We can make it part of a network. Not just chatting with other computers about computer ‘stuff’, but involved in real human activity. Exposed to ‘raw meaning’ – the developing folksonomies coming out of the learning activities of humans, whether they are traditional students or lifelong learners (a term which should encompass everyone). Humans have complex psyches, comprised of multiple strands of identity which reflect as different roles in the communities of which they are part – so why not design our system the same way? With multiple internal modes of operation, each capable of being reflected onto the outside world in the form of roles – as a mentor, a research assistant, maybe even as a friend. But in order to be able to work with a human for long enough to be able to have a chance of developing the sort of rich behaviours we associate with people, the system needs to be able to function in a practical and helpful role. Unfortunately, it is unlikely to get a free ride from many people (other than its developer!) – so it needs to be able to perform a useful role, and do so securely, respecting the privacy of its partner. Can we create a system which learns to be more human whilst helping people learn?

Adaptive project planning and management based on best practices - COBRA system

Planning a project with proper considerations of all necessary factors and managing a project to ensure its successful implementation will face a lot of challenges. Initial stage in planning a project for bidding a project is costly, time consuming and usually with poor accuracy on cost and effort predictions. On the other hand, detailed information for previous projects may be buried in piles of archived documents which can be increasingly difficult to learn from the previous experiences. Project portfolio has been brought into this field aiming to improve the information sharing and management among different projects. However, the amount of information that could be shared is still limited to generic information. This paper, we report a recently developed software system COBRA to automatically generate a project plan with effort estimation of time and cost based on data collected from previous completed projects. To maximise the data sharing and management among different projects, we proposed a method of using product based planning from PRINCE2 methodology. (Automated Project Information Sharing and Management System -�COBRA) Keywords: project management, product based planning, best practice, PRINCE2

Song development in birds: the role of early experience and its potential effect on rehabilitation success

Environmental conditions during the early life stages of birds can have significant effects on the quality of sexual signals in adulthood, especially song, and these ultimately have consequences for breeding success and fitness. This has wide-ranging implications for the rehabilitation protocols undertaken in wildlife hospitals which aim to return captive-reared animals to their natural habitat. Here we review the current literature on bird song development and learning in order to determine the potential impact that the rearing of juvenile songbirds in captivity can have on rehabilitation success. We quantify the effects of reduced learning on song structure and relate this to the possible effects on an individual's ability to defend a territory or attract a mate. We show the importance of providing a conspecific auditory model for birds to learn from in the early stages post-fledging, either via live- or tape-tutoring and provide suggestions for tutoring regimes. We also highlight the historical focus on learning in a few model species that has left an information gap in our knowledge for most species reared at wildlife hospitals.

A Bayesian approach for dose-escalation in a phase I clinical trial incorporating pharmacodynamic endpoints

Bayesian decision procedures have already been proposed for and implemented in Phase I dose-escalation studies in healthy volunteers. The procedures have been based on pharmacokinetic responses reflecting the concentration of the drug in blood plasma and are conducted to learn about the dose-response relationship while avoiding excessive concentrations. However, in many dose-escalation studies, pharmacodynamic endpoints such as heart rate or blood pressure are observed, and it is these that should be used to control dose-escalation. These endpoints introduce additional complexity into the modeling of the problem relative to pharmacokinetic responses. Firstly, there are responses available following placebo administrations. Secondly, the pharmacodynamic responses are related directly to measurable plasma concentrations, which in turn are related to dose. Motivated by experience of data from a real study conducted in a conventional manner, this paper presents and evaluates a Bayesian procedure devised for the simultaneous monitoring of pharmacodynamic and pharmacokinetic responses. Account is also taken of the incidence of adverse events. Following logarithmic transformations, a linear model is used to relate dose to the pharmacokinetic endpoint and a quadratic model to relate the latter to the pharmacodynamic endpoint. A logistic model is used to relate the pharmacokinetic endpoint to the risk of an adverse event.

High-throughput proteomics using matrix-assisted laser desorption/ ionization mass spectrometry

It has become evident that the mystery of life will not be deciphered just by decoding its blueprint, the genetic code. In the life and biomedical sciences, research efforts are now shifting from pure gene analysis to the analysis of all biomolecules involved in the machinery of life. One area of these postgenomic research fields is proteomics. Although proteomics, which basically encompasses the analysis of proteins, is not a new concept, it is far from being a research field that can rely on routine and large-scale analyses. At the time the term proteomics was coined, a gold-rush mentality was created, promising vast and quick riches (i.e., solutions to the immensely complex questions of life and disease). Predictably, the reality has been quite different. The complexity of proteomes and the wide variations in the abundances and chemical properties of their constituents has rendered the use of systematic analytical approaches only partially successful, and biologically meaningful results have been slow to arrive. However, to learn more about how cells and, hence, life works, it is essential to understand the proteins and their complex interactions in their native environment. This is why proteomics will be an important part of the biomedical sciences for the foreseeable future. Therefore, any advances in providing the tools that make protein analysis a more routine and large-scale business, ideally using automated and rapid analytical procedures, are highly sought after. This review will provide some basics, thoughts and ideas on the exploitation of matrix-assisted laser desorption/ ionization in biological mass spectrometry - one of the most commonly used analytical tools in proteomics - for high-throughput analyses.

High-throughput proteomics using matrix-assisted laser desorption/ionization mass spectrometry

It has become evident that the mystery of life will not be deciphered just by decoding its blueprint, the genetic code. In the life and biomedical sciences, research efforts are now shifting from pure gene analysis to the analysis of all biomolecules involved in the machinery of life. One area of these postgenomic research fields is proteomics. Although proteomics, which basically encompasses the analysis of proteins, is not a new concept, it is far from being a research field that can rely on routine and large-scale analyses. At the time the term proteomics was coined, a gold-rush mentality was created, promising vast and quick riches (i.e., solutions to the immensely complex questions of life and disease). Predictably, the reality has been quite different. The complexity of proteomes and the wide variations in the abundances and chemical properties of their constituents has rendered the use of systematic analytical approaches only partially successful, and biologically meaningful results have been slow to arrive. However, to learn more about how cells and, hence, life works, it is essential to understand the proteins and their complex interactions in their native environment. This is why proteomics will be an important part of the biomedical sciences for the foreseeable future. Therefore, any advances in providing the tools that make protein analysis a more routine and large-scale business, ideally using automated and rapid analytical procedures, are highly sought after. This review will provide some basics, thoughts and ideas on the exploitation of matrix-assisted laser desorption/ionization in biological mass spectrometry - one of the most commonly used analytical tools in proteomics - for high-throughput analyses.

Knowledge sharing: Context, confusion and controversy

Project managers in the construction industry increasingly seek to learn from other industrial sectors. Knowledge sharing between different contexts is thus viewed as an essential source of competitive advantage. It is important therefore for project managers from all sectors to address and develop appropriate methods of knowledge sharing. However, too often it is assumed that knowledge freely exists and can be captured and shared between contexts. Such assumptions belie complexities and problems awaiting the unsuspecting knowledge-sharing protagonist. Knowledge per se is a problematic esoteric concept that does not lend itself easily to codification. Specifically tacit knowledge possessed by individuals, presents particular methodological issues for those considering harnessing its utility in return for competitive advantage. The notion that knowledge is also embedded in specific social contexts compounds this complexity. It is argued that knowledge is highly individualistic and concomitant with the various surrounding contexts within which it is shaped and enacted. Indeed, these contexts are also shaped as a consequence of knowledge adding further complexity to the problem domain. Current methods of knowledge capture, transfer and, sharing fall short of addressing these problematic issues. Research is presented that addresses these problems and proposes an alternative method of knowledge sharing. Drawing on data and observations collected from its application, the findings clearly demonstrate the crucial role of re-contextualisation, social interaction and dialectic debate in understanding knowledge sharing.

Introducing assistive technology into the homes of older people: Some lessons from the Netherlands - A case study

The authors have just completed a study of assistive technology (AT) and how it can be introduced into the existing homes of older people. As part of this empirical study some collaboration with the Netherlands took place for two reasons. First to learn about the use of assistive technology from a country where its creative use was well established and second to learn how older people influence policy. Two Dutch consultants helped the team and a short visit was paid to Eindhoven. As a result of this collaboration new ways of using AT were found and comparisons made with the policy and legislative background. In addition lessons were drawn about the involvement of older people.

Teachers as researchers and teachers as software developers: how use-case analysis helps build better educational software

A series of government initiatives has raised both the profile of ICT in the curriculum and the expectation that high quality teaching and learning resources will be accessible across electronic networks. In order for e-learning resources such as websites to have the maximum educational impact, teachers need to be involved in their design and development. Use-case analysis provides a means of defining user requirements and other constraints in such a way that software developers can produce e-learning resources which reflect teachers' professional knowledge and support their classroom practice. It has some features in common with the participatory action research used to develop other aspects of classroom practice. Two case-studies are presented: one involves the development of an on-line resource centred on transcripts of original historical documents; the other describes how 'Learning how to Learn', a major, distributed research project funded under the ESRC Teaching and Learning Research Programme is using use-case analysis to develop web resources and services.

'Word-learning wizardry' at I;6

This article explores whether infants are able to learn words as rapidly as has been reported for preschoolers. Sixty-four infants aged 1;6 were taught labels for either two moving images or two still images. Each image-label pair was presented three times, after which comprehension was assessed using an adaptation of the intermodal preferential looking paradigm. Three repetitions of each label were found to be sufficient for learning to occur, fewer than has previously been reported for infants under two years. Moreover, contrary to a previous finding, learning was equally rapid for infants who were taught labels for moving versus still images. The findings indicate that infants in the early stages of acquiring a vocabulary learn new word-referent associations with ease, and that the learning conditions that allow such learning are less restricted that was previously believed.