Building coalitions, creating change: An agenda for gender transformative research in agricultural development

The CGIAR Research Program on Aquatic Agricultural Systems (AAS) has developed its Gender Research in Development Strategy centered on a transformative approach. Translating this strategy into actual research and development practice poses a considerable challenge, as not much (documented) experience exists in the agricultural sector to draw on, and significant innovation is required. A process of transformative change requires reflecting on multiple facets and dimensions simultaneously. This working paper is a collation of think pieces, structured around broad the mes and topics, reflecting on what works (and what does not) in the application of gender transformative approaches in agriculture and other sectors, and seeking to stimulate a discussion on the way forward for CGIAR Research Programs (CRPs) and other programs to build organizational capacities and partnerships

The digital transformation of business models in the creative industries: A holistic framework and emerging trends

This paper examines how digital technologies facilitate business model innovations in the creative industries. Through a systematic literature review, a holistic business model framework is developed, which is then used to analyse the empirical evidence from the creative industries. The research found that digital technologies have facilitated pervasive changes in business models, and some significant trends have emerged. However, the reconfigured business models are often not ‘new’ in the unprecedented sense. Business model innovations are primarily reflected in using digital technologies to enable the deployment of a wider range of business models than previously available to a firm. A significant emerging trend is the increasing adoption of multiple business models as a portfolio within one firm. This is happening in firms of all sizes, when one firm uses multiple business models to servedifferent markets segments, sell different products, or engage with multi-sided markets, or to use different business models over time. The holistic business model framework is refined and extended through a recursive learning process, which can serve both as a cognitive instrument for understanding business models and a planning tool for business model innovations. The paper contributes to our understanding of the theory of business models and how digital technologies facilitate business model innovations in the creative industries. Three new themes for future research are highlighted

Strengthening Climate-Resilient Agricultural Systems in South Asia: CCAFS South Asia Regional Meeting Report

State of the art discourse on agriculture and climate change, lays emphasis on the dual role of agriculture in adapting to and mitigating climate change. Recognising the same, many countries are laying emphasis on agriculture while preparing their national adaptation plans (NAPs). In congruence with the world’s agenda to facilitate sustainable agricultural practices, while reducing poverty and hunger, CCAFS has been working for last 10 years to generate innovative solutions to promote more adaptable and resilient agriculture and food systems. South Asia regional office of Climate Change Agriculture and Food Security (CCAFS) has been: generating research based knowledge, mainstreaming climate variability and climate change issues into development strategies and institutional agendas; enhancing people's understanding of climate change issues; and facilitating informed decisions on policies and actions based on the best available information and data in India, Nepal and Bangladesh, with extended research and knowledge based services extended onto Bhutan and Sri Lanka. With the vision of drawing learnings from the work done so far to elucidate the strategy of the coming years, a regional meeting titled “Strengthening Climate-Resilient Agricultural Systems in South Asia” was organised by CCAFS- South Asia in Bali- Indonesia from 6th to 7th Oct 2019. The meeting also aspired to build as well as further strengthen already existing institutional partnership. The two-day agenda included thematic sessions on topics such as developing and evaluating alternative policy and institutional models for scaling-up climate smart food system in South Asia, big-data analytics to identify and overcome scaling limitations to climate-smart agricultural practices in South Asia, capacity building for scaling up CSA via South- South collaboration among others. The meeting culminated with an agreement on the need for revisiting CCAFS research approach to build science based evidence, to facilitate formulation of better policies and programs, for a food secure world

Participatory Modelling and Decision Support for Natural Resources Management in Climate Change Research

The ever greater role given to public participation by laws and regulations, in particular in the field of environmental management calls for new operational methods and tools for managers and practitioners. This paper analyses the potentials and the critical limitations of current approaches in the fields of simulation modelling (SM), public participation (PP) and decision analysis (DA), for natural resources management within the context of climate change research. The potential synergies of combining SM, PP and DA into an integrated methodological framework are identified and a methodological proposal is presented, called NetSyMoD (Network Analysis – Creative System Modelling – Decision Support), which aims at facilitating the involvement of stakeholders or experts in policy - or decision-making processes (P/DMP). A generic P/DMP is formalised in NetSyMoD as a sequence of six main phases: (i) Actors analysis; (ii) Problem analysis; (iii) Creative System Modelling; (iv) DSS design; (v) Analysis of Options; and (vi) Action taking and monitoring. Several variants of the NetSyMoD approach have been adapted to different contexts such as integrated water resources management and coastal management, and, recently it has been applied in climate change research projects. Experience has shown that NetSyMoD may be a useful framework for skilled professionals, for guiding the P/DMP, and providing practical solutions to problems encountered in the different phases of the decision/policy making process, in particular when future scenarios or projections have to be considered, such as in the case of developing and selecting adaptation policies. The various applications of NetSyMoD share the same approach for problem analysis and communication within the group of selected actors, based upon the use of creative thinking techniques, the formalisation of human-environment relationships through the DPSIR framework, and the use of multi-criteria analysis through a Decision Support System (DSS) software.Modelling, Public Participation, Natural Resource Management, Policy, Decision-Making, Governance, DSS

Developing Interventions for Scaling Up UK Upcycling

open access articleUpcycling presents one of many opportunities for reducing consumption of materials and energy. Despite recent growth evidenced by increasing numbers of practitioners and businesses based on upcycling, it remains a niche activity and requires scaling up to realise its potential benefits. This paper investigates UK household upcycling in order to develop interventions for scaling up upcycling in the UK. Mixed methods were used in four stages: (a) Interviews to gain insights into UK upcycling; (b) a survey to discover key factors influencing UK upcycling; (c) intervention development based on the synthesis of interviews and survey; and (d) use of a semi-Delphi technique to evaluate and develop initial interventions. The results showed approaches to upcycling (e.g., wood, metal and fabric as frequently used materials, online platforms as frequently used source of materials), context for upcycling (e.g., predominant use of home for upcycling), factors influencing UK upcycling with key determinants (i.e., intention, attitude and subjective norm), important demographic characteristics considering a target audience for interventions (i.e., 30+ females) and prioritised interventions for scaling up (e.g., TV and inspirational media and community workshops as short-term high priority interventions). The paper further discusses implications of the study in terms of development of theory and practice of upcycling

Quality of Life Following Massive Weight Loss and Body Contouring Surgery: an Exploratory Study.

Reconstructive surgery is a major growth intervention for body improvement, enhancing appearance and psychological well-being following massive weight loss. The psychosocial benefits include greater capacity for social networking, lower scores of body uneasiness, body image satisfaction, improved mental well-being and physical function. However little collective evidence exists regarding the impact of body contouring on patients Quality of Life (QoL) and there is a lack of systematic review and randomised controlled trials (RCTs) with a scarcity of high level evidence. The purpose of this exploratory study was to explore the QoL perceptions, experiences and outcomes of patients who have undergone body contouring following significant weight loss and to explore the relevance and potential utility of the Obesity Psychosocial State Questionnaire (OPSQ) as a valuable QoL outcomes measuring tool for use in clinical research. Data were collected in a community setting in the south of England via digitally recorded semi-structured interviews with twenty participants (18 women and 2 men), who also self-completed the Obesity Psychosocial State Questionnaire (OBSQ). Medical notes were reviewed retrospectively to gather data about body mass index (BMI), co-morbidities, eating profiles/lifestyle, uptake of bariatric surgery and type/number of body contouring procedures undergone. A thematic approach was adopted to analyse the interviews and medical record data, supported by Nvivo7 qualitative software, and a statistical approach to analyse the questionnaire data, supported by Statistical Analysis Software. The results provide unique glimpses of the body contouring interventions for empowering and facilitating a ‘transformation’, a ‘new identity’, a ‘new start’ in life, improved physical function, greater body image satisfaction, a stronger sense of well-being and an improved quality of life. A few of the participants who reported that their weight gain was powered by childhood traumas (abuse, neglect, abandonment) continued to struggle for ‘normality’, with fragile eating control and addictive traits. Eating disordered trauma survivors mentioned post traumatic flashbacks and underlying conflicts that triggered powerlessness and emotional eating. The emotional flooding with psychological and body related memories did not appear to be fully processed or released, despite counselling and binge eating programmes. The participants also confirmed the value of the OBSQ, whilst highlighting its limited set of three questions on feelings of self-efficacy towards eating habits. The study findings show that body contouring optimises quality of life with significant improvement in physical function, body image, mental health and psychosocial function. Further research is warranted to extent the scope of the findings within a sample drawn from multiple treatment centres. This would valuably: • Explore gender, ethnic and cultural variables, important to optimising quality of life. • Clarify distinguishing features between short and long-term QoL outcomes. • Lead to the development of national policy and guidelines on reconstructive ‘body contouring’ surgery following massive weight loss, in line with the call from the British Association for Plastic, Reconstructive and Aesthetic Surgeons (BAPRAS) A future multi-centre collaborative study could employ the OBSQ, supplemented by an additional tool to explore factors that influence eating habits such as the three factor eating questionnaire (such as the TFEQ-R1 21 Scale). Such research could enhance understanding of quality of life and long-term weight management

Introduction to TIPS: a theory for creative design

A highly intriguing problem in combining artificial intelligence and engineering design is automation of the creative and innovative phases of the design process. This paper gives a brief introduction to the theory of inventive problem solving (TIPS) selected as a theoretical basis of the authors' research efforts in this field. The research is conducted in the Stevin Project of the Knowledge-Based System Group of the University of Twente (Enschede, The Netherlands) in cooperation with the Invention Machine Laboratory (Minsk, Belarus). This collaboration aims at developing a formal basis for the creation of an automated reasoning system to support creative engineering design

Cancer Informatics for Cancer Centers (CI4CC): Building a Community Focused on Sharing Ideas and Best Practices to Improve Cancer Care and Patient Outcomes.

Cancer Informatics for Cancer Centers (CI4CC) is a grassroots, nonprofit 501c3 organization intended to provide a focused national forum for engagement of senior cancer informatics leaders, primarily aimed at academic cancer centers anywhere in the world but with a special emphasis on the 70 National Cancer Institute-funded cancer centers. Although each of the participating cancer centers is structured differently, and leaders' titles vary, we know firsthand there are similarities in both the issues we face and the solutions we achieve. As a consortium, we have initiated a dedicated listserv, an open-initiatives program, and targeted biannual face-to-face meetings. These meetings are a place to review our priorities and initiatives, providing a forum for discussion of the strategic and pragmatic issues we, as informatics leaders, individually face at our respective institutions and cancer centers. Here we provide a brief history of the CI4CC organization and meeting highlights from the latest CI4CC meeting that took place in Napa, California from October 14-16, 2019. The focus of this meeting was "intersections between informatics, data science, and population science." We conclude with a discussion on "hot topics" on the horizon for cancer informatics

Automated classification of three-dimensional reconstructions of coral reefs using convolutional neural networks

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Hopkinson, B. M., King, A. C., Owen, D. P., Johnson-Roberson, M., Long, M. H., & Bhandarkar, S. M. Automated classification of three-dimensional reconstructions of coral reefs using convolutional neural networks. PLoS One, 15(3), (2020): e0230671, doi: 10.1371/journal.pone.0230671.Coral reefs are biologically diverse and structurally complex ecosystems, which have been severally affected by human actions. Consequently, there is a need for rapid ecological assessment of coral reefs, but current approaches require time consuming manual analysis, either during a dive survey or on images collected during a survey. Reef structural complexity is essential for ecological function but is challenging to measure and often relegated to simple metrics such as rugosity. Recent advances in computer vision and machine learning offer the potential to alleviate some of these limitations. We developed an approach to automatically classify 3D reconstructions of reef sections and assessed the accuracy of this approach. 3D reconstructions of reef sections were generated using commercial Structure-from-Motion software with images extracted from video surveys. To generate a 3D classified map, locations on the 3D reconstruction were mapped back into the original images to extract multiple views of the location. Several approaches were tested to merge information from multiple views of a point into a single classification, all of which used convolutional neural networks to classify or extract features from the images, but differ in the strategy employed for merging information. Approaches to merging information entailed voting, probability averaging, and a learned neural-network layer. All approaches performed similarly achieving overall classification accuracies of ~96% and >90% accuracy on most classes. With this high classification accuracy, these approaches are suitable for many ecological applications.This study was funded by grants from the Alfred P. Sloan Foundation (BMH, BR2014-049; https://sloan.org), and the National Science Foundation (MHL, OCE-1657727; https://www.nsf.gov). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript