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Transdiagnostic comparisons of intellectual abilities and work outcome in patients with mental disorders: multicentre study
- Chika Sumiyoshi, Kazutaka Ohi, Haruo Fujino, Hidenaga Yamamori, Michiko Fujimoto, Yuka Yasuda, Yota Uno, Junichi Takahashi, Kentaro Morita, Asuka Katsuki, Maeri Yamamoto, Yuko Okahisa, Ayumi Sata, Eiichi Katsumoto, Michihiko Koeda, Yoji Hirano, Masahito Nakataki, Junya Matsumoto, Kenichiro Miura, Naoki Hashimoto, Manabu Makinodan, Tsutomu Takahashi, Kiyotaka Nemoto, Toshifumi Kishimoto, Michio Suzuki, Tomiki Sumiyoshi, Ryota Hashimoto
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- Journal:
- BJPsych Open / Volume 8 / Issue 4 / July 2022
- Published online by Cambridge University Press:
- 03 June 2022, e98
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- Article
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Background
Cognitive impairment is common in people with mental disorders, leading to transdiagnostic classification based on cognitive characteristics. However, few studies have used this approach for intellectual abilities and functional outcomes.
AimsThe present study aimed to classify people with mental disorders based on intellectual abilities and functional outcomes in a data-driven manner.
MethodSeven hundred and forty-nine patients diagnosed with schizophrenia, bipolar disorder, major depression disorder or autism spectrum disorder and 1030 healthy control subjects were recruited from facilities in various regions of Japan. Two independent k-means cluster analyses were performed. First, intelligence variables (current estimated IQ, premorbid IQ, and IQ discrepancy) were included. Second, number of work hours per week was included instead of premorbid IQ.
ResultsFour clusters were identified in the two analyses. These clusters were specifically characterised in terms of IQ discrepancy in the first cluster analysis, whereas the work variable was the most salient feature in the second cluster analysis. Distributions of clinical diagnoses in the two cluster analyses showed that all diagnoses were unevenly represented across the clusters.
ConclusionsIntellectual abilities and work outcomes are effective classifiers in transdiagnostic approaches. The results of our study also suggest the importance of diagnosis-specific strategies to support functional recovery in people with mental disorders.
Chapter 18 - Urban Energy Systems
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- By Arnulf Grubler, International Institute for Applied Systems Analysis, Austria and Yale University, Xuemei Bai, Australian National University, Thomas Buettner, United Nations Department of Economic and Social Affairs, Shobhakar Dhakal, Global Carbon Project and National Institute for Environmental Studies, David J. Fisk, Imperial College London, Toshiaki Ichinose, National Institute for Environmental Studies, James E. Keirstead, Imperial College London, Gerd Sammer, University of Natural Resources and Applied Life Sciences, David Satterthwaite, International Institute for Environment and Development, Niels B. Schulz, International Institute for Applied Systems Analysis, Austria and Imperial College, Nilay Shah, Imperial College London, Julia Steinberger, The Institute of Social Ecology, Austria and University of Leeds, Helga Weisz, Potsdam Institute for Climate Impact Research, Gilbert Ahamer, University of Graz, Timothy Baynes, Commonwealth Scientific and Industrial Research Organisation, Daniel Curtis, Oxford University Centre for the Environment, Michael Doherty, Commonwealth Scientific and Industrial Research Organisation, Nick Eyre, Oxford University Centre for the Environment, Junichi Fujino, National Institute for Environmental Studies, Keisuke Hanaki, University of Tokyo, Mikiko Kainuma, National Institute for Environmental Studies, Shinji Kaneko, Hiroshima University, Manfred Lenzen, University of Sydney, Jacqui Meyers, Commonwealth Scientific and Industrial Research Organisation, Hitomi Nakanishi, University of Canberra, Victoria Novikova, Oxford University Centre for the Environment, Krishnan S. Rajan, International Institute of Information Technology, Seongwon Seo, Commonwealth Scientific and Industrial Research Organisation, Ram M. Shrestha, Asian Institute of Technology, Priyadarshi R. Shukla, Indian Institute of Management, Alice Sverdlik, International Institute for Environment and Development, Jayant Sathaye, Lawrence Berkeley National Laboratory
- Global Energy Assessment Writing Team
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- Book:
- Global Energy Assessment
- Published online:
- 05 September 2012
- Print publication:
- 27 August 2012, pp 1307-1400
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Summary
Executive Summary
More than 50% of the global population already lives in urban settlements and urban areas are projected to absorb almost all the global population growth to 2050, amounting to some additional three billion people. Over the next decades the increase in rural population in many developing countries will be overshadowed by population flows to cities. Rural populations globally are expected to peak at a level of 3.5 billion people by around 2020 and decline thereafter, albeit with heterogeneous regional trends. This adds urgency in addressing rural energy access, but our common future will be predominantly urban. Most of urban growth will continue to occur in small-to medium-sized urban centers. Growth in these smaller cities poses serious policy challenges, especially in the developing world. In small cities, data and information to guide policy are largely absent, local resources to tackle development challenges are limited, and governance and institutional capacities are weak, requiring serious efforts in capacity building, novel applications of remote sensing, information, and decision support techniques, and new institutional partnerships. While ‘megacities’ with more than 10 million inhabitants have distinctive challenges, their contribution to global urban growth will remain comparatively small.
Energy-wise, the world is already predominantly urban. This assessment estimates that between 60–80% of final energy use globally is urban, with a central estimate of 75%. Applying national energy (or GHG inventory) reporting formats to the urban scale and to urban administrative boundaries is often referred to as a ‘production’ accounting approach and underlies the above GEA estimate.
Chapter 9 - Renewable Energy in the Context of Sustainable Development
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- By Jayant Sathaye, Oswaldo Lucon, Atiq Rahman, John Christensen, Fatima Denton, Junichi Fujino, Garvin Heath, Monirul Mirza, Hugh Rudnick, August Schlaepfer, Andrey Shmakin, Gerhard Angerer, Christian Bauer, Morgan Bazilian, Robert Brecha, Peter Burgherr, Leon Clarke, Felix Creutzig, James Edmonds, Christian Hagelüken, Gerrit Hansen, Nathan Hultman, Michael Jakob, Susanne Kadner, Manfred Lenzen, Jordan Macknick, Eric Masanet, Yu Nagai, Anne Olhoff, Karen Olsen, Michael Pahle, Ari Rabl, Richard Richels, Joyashree Roy, Tormod Schei, Christoph von Stechow, Jan Steckel, Ethan Warner, Tom Wilbanks, Yimin Zhang, Volodymyr Demkine, Ismail Elgizouli, Jeffrey Logan, Susanne Kadner
- Edited by Ottmar Edenhofer, Ramón Pichs-Madruga, Youba Sokona, Kristin Seyboth, Susanne Kadner, Timm Zwickel, Patrick Eickemeier, Gerrit Hansen, Steffen Schlömer, Christoph von Stechow, Patrick Matschoss
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- Book:
- Renewable Energy Sources and Climate Change Mitigation
- Published online:
- 05 December 2011
- Print publication:
- 21 November 2011, pp 707-790
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Summary
Executive Summary
Historically, economic development has been strongly correlated with increasing energy use and growth of greenhouse gas (GHG) emissions. Renewable energy (RE) can help decouple that correlation, contributing to sustainable development (SD). In addition, RE offers the opportunity to improve access to modern energy services for the poorest members of society, which is crucial for the achievement of any single of the eight Millennium Development Goals.
Theoretical concepts of SD can provide useful frameworks to assess the interactions between SD and RE. SD addresses concerns about relationships between human society and nature. Traditionally, SD has been framed in the three-pillar model—Economy, Ecology, and Society—allowing a schematic categorization of development goals, with the three pillars being interdependent and mutually reinforcing. Within another conceptual framework, SD can be oriented along a continuum between the two paradigms of weak sustainability and strong sustainability. The two paradigms differ in assumptions about the substitutability of natural and human-made capital. RE can contribute to the development goals of the three-pillar model and can be assessed in terms of both weak and strong SD, since RE utilization is defined as sustaining natural capital as long as its resource use does not reduce the potential for future harvest.