Institution
University of Western Australia
Education•Perth, Western Australia, Australia•
About: University of Western Australia is a education organization based out in Perth, Western Australia, Australia. It is known for research contribution in the topics: Population & Poison control. The organization has 29613 authors who have published 87405 publications receiving 3064466 citations. The organization is also known as: UWA & University of WA.
Papers published on a yearly basis
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TL;DR: It is suggested that “hydraulic redistribution” of water in tree roots is significant in maintaining root viability, facilitating root growth in dry soils and modifying resource availability.
Abstract: Plant roots transfer water between soil layers of different water potential thereby significantly affecting the distribution and availability of water in the soil profile We used a modification of the heat pulse method to measure sap flow in roots of Grevillea robusta and Eucalyptus camaldulensis and demonstrated a redistribution of soil water from deeper in the profile to dry surface horizons by the root system This phenomenon, termed “hydraulic lift” has been reported previously However, we also demonstrated that after the surface soils were rewetted at the break of season, water was transported by roots from the surface to deeper soil horizons – the reverse of the “hydraulic lift” behaviour described for other woody species We suggest that “hydraulic redistribution” of water in tree roots is significant in maintaining root viability, facilitating root growth in dry soils and modifying resource availability
546 citations
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TL;DR: Modelling and a sensitivity analysis of the acoustic observations from the Malaspina 2010 Circumnavigation Expedition show that the previous estimate of mesopelagic fishes biomass needs to be revised to at least one order of magnitude higher, and there is a close relationship between the open ocean fishes biomass and primary production.
Abstract: With a current estimate of ~1,000 million tons, mesopelagic fishes likely dominate the world total fishes biomass. However, recent acoustic observations show that mesopelagic fishes biomass could be significantly larger than the current estimate. Here we combine modelling and a sensitivity analysis of the acoustic observations from the Malaspina 2010 Circumnavigation Expedition to show that the previous estimate needs to be revised to at least one order of magnitude higher. We show that there is a close relationship between the open ocean fishes biomass and primary production, and that the energy transfer efficiency from phytoplankton to mesopelagic fishes in the open ocean is higher than what is typically assumed. Our results indicate that the role of mesopelagic fishes in oceanic ecosystems and global ocean biogeochemical cycles needs to be revised as they may be respiring ~10% of the primary production in deep waters. Mesopelagic fishes dominate the global fishes biomass, yet there exist major uncertainties regarding their global biomass. Irigoien et al.analyse acoustic data collected during a circumglobal cruise and show that biomass estimates should be raised by an order of magnitude.
545 citations
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TL;DR: There is an increased risk of drug-related death during the first 2 weeks after release from prison and that the risk remains elevated up to at least the fourth week, a meta-analysis confirms.
Abstract: Aims The transition from prison back into the community is particularly hazardous for drug-using offenders whose tolerance for heroin has been reduced by imprisonment. Studies have indicated an increased risk of drug-related death soon after release from prison, particularly in the first 2 weeks. For precise, up-to-date understanding of these risks, a meta-analysis was conducted on the risk of drug-related death in weeks 1 + 2 and 3 + 4 compared with later 2-week periods in the first 12 weeks after release from prison.Methods English-language studies were identified that followed up adult prisoners for mortality from time of index release for at least 12 weeks. Six studies from six prison systems met the inclusion criteria and relevant data were extracted independently. Results These studies contributed a total of 69 093 person-years and 1033 deaths in the first 12 weeks after release, of which 612 were drug-related. A three- to eightfold increased risk of drug-related death was found when comparing weeks 1 + 2 with weeks 3-12, with notable heterogeneity between countries: United Kingdom, 7.5 (95% CI: 5.7-9.9); Australia, 4.0 (95% CI: 3.4-4.8); Washing- ton State, USA, 8.4 (95% CI: 5.0-14.2) and New Mexico State, USA, 3.1 (95% CI: 1.3-7.1). Comparing weeks 3 + 4 with weeks 5-12, the pooled relative risk was: 1.7 (95% CI: 1.3-2.2). Conclusions These findings confirm that there is an increased risk of drug-related death during the first 2 weeks after release from prison and that the risk remains elevated up to at least the fourth week.
545 citations
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TL;DR: Deep convolutional neural networks are proposed to be used to learn long-term temporal information of the skeleton sequence from the frames of the generated clips, and a Multi-Task Learning Network (MTLN) is proposed to jointly process all Frames of the clips in parallel to incorporate spatial structural information for action recognition.
Abstract: This paper presents a new method for 3D action recognition with skeleton sequences (i.e., 3D trajectories of human skeleton joints). The proposed method first transforms each skeleton sequence into three clips each consisting of several frames for spatial temporal feature learning using deep neural networks. Each clip is generated from one channel of the cylindrical coordinates of the skeleton sequence. Each frame of the generated clips represents the temporal information of the entire skeleton sequence, and incorporates one particular spatial relationship between the joints. The entire clips include multiple frames with different spatial relationships, which provide useful spatial structural information of the human skeleton. We propose to use deep convolutional neural networks to learn long-term temporal information of the skeleton sequence from the frames of the generated clips, and then use a Multi-Task Learning Network (MTLN) to jointly process all frames of the generated clips in parallel to incorporate spatial structural information for action recognition. Experimental results clearly show the effectiveness of the proposed new representation and feature learning method for 3D action recognition.
544 citations
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TL;DR: Past and ongoing environmental changes ensure that many historical restoration targets will be unsustainable in the coming decades, so ecological restoration efforts should aim to conserve and restore historical ecosystems where viable, while simultaneously preparing to design or steer emerging novel ecosystems to ensure maintenance of ecological goods and services.
Abstract: Ecological history plays many roles in ecological restoration, most notably as a tool to identify and characterize appropriate targets for restoration efforts. However, ecological history also reveals deep human imprints on many ecological systems and indicates that secular climate change has kept many targets moving at centennial to millennial time scales. Past and ongoing environmental changes ensure that many historical restoration targets will be unsustainable in the coming decades. Ecological restoration efforts should aim to conserve and restore historical ecosystems where viable, while simultaneously preparing to design or steer emerging novel ecosystems to ensure maintenance of ecological goods and services.
542 citations
Authors
Showing all 29972 results
Name | H-index | Papers | Citations |
---|---|---|---|
Nicholas G. Martin | 192 | 1770 | 161952 |
Cornelia M. van Duijn | 183 | 1030 | 146009 |
Kay-Tee Khaw | 174 | 1389 | 138782 |
Steven N. Blair | 165 | 879 | 132929 |
David W. Bates | 159 | 1239 | 116698 |
Mark E. Cooper | 158 | 1463 | 124887 |
David Cameron | 154 | 1586 | 126067 |
Stephen T. Holgate | 142 | 870 | 82345 |
Jeremy K. Nicholson | 141 | 773 | 80275 |
Xin Chen | 139 | 1008 | 113088 |
Graeme J. Hankey | 137 | 844 | 143373 |
David Stuart | 136 | 1665 | 103759 |
Joachim Heinrich | 136 | 1309 | 76887 |
Carlos M. Duarte | 132 | 1173 | 86672 |
David Smith | 129 | 2184 | 100917 |